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The role of nurse practitioner, a subset of nurses qualified to work as primary and specialty care providers, is the fastest-growing occupation in the U.S.. By 2031, the U.S. Bureau of Labor Statistics projects a 46% growth rate in the number of nurse practitioner positions, compared with 2021. Now is clearly a great time to enter this rewarding and potentially lucrative field, and to do so, you’ll need a master’s in nursing (MSN), a degree that many universities offer online.
One of the nation’s leading online MSN programs is the University of Nevada–Las Vegas School of Nursing. In fact, it landed No. 1 in Fortune’s ranking of the best online MSN programs. The school currently offers three tracks: family nurse practitioner, psychiatric mental health nurse practitioner, and nursing education. All applicants are required to be registered nurses (RNs) with 2,000 hours of experience, and they should have a good idea of what they hope to gain from their degree. 
“For most nurses who have an RN, it’s not just about advancement,” says Deven Richardson, the outgoing enrollment coordinator at UNLV’s School of Nursing. “Some of them want to go into their own practice. Some nurse practitioners can prescribe medication. They can work in the psych field. They can do a lot of things with their degrees, but they need those advanced credentials that a program like ours grants them.”
Earning these credentials from UNLV isn’t easy. Incoming students have an average undergraduate GPA of 3.62, and the school’s overall acceptance rate is 50.3%. Fortunately, there are ways to increase your chances of landing a spot in this prestigious program.
Through our conversation with Richardson, we came up with the following guide to getting in to UNLV’s online MSN program:
If your undergraduate grades aren’t super impressive, don’t immediately throw in the towel. “What we try to do is look at the whole applicant and not just GPA,” says Richardson. “GPA isn’t always reflective of how well a student will perform in a program.”
In applying for the MSN program, you’re also applying to UNLV’s Graduate College, which considers students with GPAs of 2.75 and above. So as long as you meet that criteria, you have a chance with the School of Nursing. If your grades are on the low side, you might balance the scales with work experience. While the requirement is 2,000 hours of experience as an RN—roughly one year—some candidates come in with 20 years of hands-on nursing behind them.
Decades of experience—like a sky-high GPA—doesn’t guarantee entry. But it will give applicants a leg up. “They’ve shown they’re consistent in showing excellence in the nursing career field—they will most likely show excellence in the nursing program itself,” Richardson says. “We can at least look at them and say, ‘This person’s a very experienced nurse. We probably don’t have to worry about them too much.’” 
As part of the application, you’ll need to write a 300-word personal statement about your career goals. The key with this prompt, Richardson says, is to “come with your why.”
“Why do you want to do this?” Richardson asks. “We don’t want a 15-page dissertation on why you want to be in the master’s of nursing program. That’s not going to help anybody. Just come prepared with what you’re looking for. And because nurses are who they are, many are prepared to state in 300 words why they want to do this.”
It’s also crucial to tailor your statement to the program you’re applying to. If it’s psychiatric mental health nurse practitioner, write specifically about this field and how your UNLV degree will help you on your path.
The UNLV application asks for three letters of recommendation—a sticking point for many students. “The letters of rec usually take the longest,” Richardson says. “It’s usually a function of people not being able to find the right people to do a letter for them. And it’s also a function of people just not doing it on time.”
To avoid scrambling at the last minute, Richardson suggests reaching out to four or five potential recommenders, just in case some are slow to respond. As for what types of people you should approach, Richardson cautions against asking friends and family.
“We want professional references,” he says. “A good reference comes from a faculty member from your [bachelor’s of science in nursing] program. If you have a good relationship with a professor from university, you are OK to ask them for a letter of rec. I promise they’re fine with it. They do it all the time. I know many faculty members who have a template for it.”
And of course, it’s good to find people who can speak to your nursing abilities. Consider former bosses and people you’ve worked with at hospitals or clinics. You want them to give a “professional view” of your skills, and if they can discuss your leadership abilities, that’s even better.
“A big conversation right now is a lack of leaders in the nursing field, so they’re always looking for people willing to step up and take on more,” Richardson says. “People who can point out and say, ‘Hey, I’ve seen this person. They’re great under fire. They’re capable of doing the work that’s required from them’—that’s just a great benefit when you’re applying to any program.”
If your application makes it through the first round, you’ll take part in a video interview. You won’t actually be speaking to another person. Instead, you will give you a series of randomized questions tailored to the program you’re applying to and you’ll respond to the prompts.
“As I said, we try to look at the whole entire applicant,” Richardson says. “That’s what the interview helps with. You can’t really get a good encapsulation of a person just on some documents they submit. Having them go through the interview process gives us a more well-rounded view of our applicants.”
“Make sure you’re coming prepared for an interview,” Richardson adds. “We don’t know the questions beforehand. We won’t tell you the questions beforehand. [Applicants] need to be ready for whatever they’re coming across. They’re nurses, and they’re going to come across some unexpected things in the field.”
For a variety of complex regulatory reasons, UNLV can’t accept students from all states. For example, the family nurse practitioner and psychiatric mental health nurse practitioner tracks are unable to admit students from California.
“Certain programs need to be authorized in a certain way, and it can be cumbersome, or it can just be difficult to do so because the state doesn’t have a nursing board, as Nevada does,” Richardson says. 
It’s also worth noting that the family nurse practitioner and psychiatric mental health nurse practitioner tracks have clinical components that require students to perform hands-on nursing. UNLV will help students find clinical placements in Nevada, but things may get trickier beyond state lines. 
“We have partnerships with certain states, but it’s easier if you are within the state of Nevada,” says Richardson. “I’d always recommend students reach out and say, ‘Hey, I’m in such and such state. Is your program approved within us?’ That way, they don’t run into any issues. There’s nothing more frustrating than applying for a program and then getting told, ‘I’m sorry, we can’t accept you because you’re out of state.’ No one wants that kind of time waste.”
Richardson recommends that students not apply to UNLV until they’re totally ready. That means having all of their documents in order, but more importantly, it means being prepared to devote themselves fully to a challenging and time-consuming program.
“Come not just physically prepared, but mentally prepared,” Richardson says. “A lot of people who come to these programs have families. They have outside commitments. Consider all aspects of your life. A graduate program is a completely different sort of beast. There are a lot of things you need to consider before you commit.”
Check out all of Fortune’s rankings of degree programs, and learn more about specific career paths.

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The Ram brand and singer-songwriter, guitarist, and record producer Chris Stapleton have collaborated once again to create a one-of-a-kind Ram “Traveller” truck designed specifically by the 8-time Grammy-winning artist in collaboration with the Ram Design Studio team in Auburn Hills, Michigan.
Built on the Ram 2500, the Ram “Traveller” honors the deep-rooted collaborations between Ram and Stapleton which includes the 2016 Ram Nation concert and instrument donation for students at Stapleton’s former high school in Paintsville, Kentucky, the multi-year campaign anchored by Stapleton’s custom rendition of “I’m a Ram,” and the Country Music Hall of Fame and Museum’s current exhibit, Chris Stapleton: Since 1978, presented by Ram Trucks.
“Our relationship with Chris Stapleton is special because he is not just a partner, we consider him to be a friend. He represents our shared values of hard work, determination, and perseverance,” said Mike Koval Jr., Ram CEO. “Our journey with Chris throughout his career is something we are extremely proud of and to see this Ram Truck collaboration come to fruition is an endeavor we will cherish for a long time.”  
Working with the Ram Design Studio team, the “Traveller” features custom exterior and interior design cues that nod to the late 1970s (D-Series) and 1980s (first-gen Ram) pickups combined with the modern cues of today’s lineup.
On the exterior, styling cues stem strongly from a Stapleton favorite, the rare 1979 Dodge D-150 Palomino Edition, evoking the essence of the iconic vehicle and updated with a contemporary and modernized design. The Palomino-inspired exterior colors Linen Cream, Radar Red, Bison Brown, and Cashmere have been modernized to complement today’s finishes.
In addition, the iconic striped graphics featured on the Palomino are adapted to fit the more sculptural 2022 Ram 2500. Retro-inspired “Turbo Fin” 18-inch wheels set the aesthetic tone of the truck blending the nostalgic classic 80’s appearance and updating the style with a fully painted, deep-dished machined-faced wheel with a bright chrome center cap. Influenced by the classic Ram 1980s badge fonts, the “Traveller” badging merges the past and the present to create a distinct look. Finishing the exterior is a multi-faceted, three-dimensional Ram hood ornament added to achieve a vintage, yet modern-day appearance.
The interior of the Ram “Traveller” truck features numerous personal design details, unique colors, textures, and materials that pay homage to Stapleton’s musical career journey while representing his individual style. These details also serve a practical purpose for his everyday lifestyle.
A custom, monochromatic Bison Brown color is featured throughout the entire interior palette with a pop of color integrated into the headrests of buffalo plaid flannel material, an identical material as the jacket worn by Stapleton on the cover of his debut album, Traveller.
Walnut Burl wood appears throughout the cabin along with tailored cloth-wrapped seats, speaker grilles that draw inspiration from guitar amps, and a custom front-row bench seat. Completing the design is a customized Chris Stapleton signature inlaid into the wood of the instrument panel as another personal touch.
Aligned with the current exhibit ‘Chris Stapleton: Since 1978’ at the Country Music Hall of Fame and Museum, the Ram “Traveller” truck was revealed at the Nashville museum yesterday.
Chris Stapleton: Since 1978, presented by Ram Trucks, highlights Stapleton’s contributions to American cultural history. The exhibit runs through May 2023 and chronicles the course of Stapleton’s multi-faceted musical career, from his Kentucky roots and success as a Nashville songwriter to his rise to stardom as one of music’s most powerful and unique voices. 
This latest partnership coincides with the official release of Stapleton’s recording of “I’m a Ram” next Friday, Nov. 11th. In addition to streaming everywhere for the first time, a limited-edition 7-inch featuring the song as well as a special alternate live version of the classic Al Green tune will be available exclusively at Indie retail.
Chris Stapleton’s one-of-a-kind 2022 Ram 2500 Traveller Crew Cab 4×4 Image Gallery:
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I need my sunglasses to look at this truck. Way too much chrome. The grill is very generic and has no distinctive qualities. They found a way to ruin the good looks of the Classic body style.
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Dallas alt-pop trio, little image have released their electronic-tinged, trippy new single, “BLUE” today. The track follows their latest single and first new release of 2022, “LUNGS BURN”, further exploring their dynamic sound before the year comes to an end. Drawn from the political strife in America over the past few years, “BLUE” is a mission statement wrapped in electronic-tinged trippy pop that is entirely their own.
“What inspired ‘BLUE’ is that sometimes in our culture, things can be very, very loud and you can hear a lot of opinions,” the band says. “We love to hear all kinds of sides, but instead of screaming and yelling, we take a back seat and just listen and try to find the voice of reason. I think if a lot of people would take that approach more often, there would be a lot less chaos going on. I respect the passion and the rebellion in some aspects of things, but sometimes you have to take a step back and say, ‘Let me learn from you.’”

In 2023, the group is set to embark on a U.S. tour opening for Colony House from February through April, full dates below. Tickets are on sale now, buy HERE. The band recently blew audiences away opening for Panic! At The Disco and played a headline show at Los Angeles’ The Moroccan Lounge.
For the past eight years, little image has morphed from a group of perpetually online suburban teens who were obsessed with underground indie rock and had no idea what they wanted to be into the tight-knit outfit you see today. While many young artists had their careers derailed in 2020 due to COVID, it actually managed to save little image, which was gearing up to announce itself to the world without realizing the members needed more time for reflection.
That extra time allowed the members of little image to fully expand on the promise of their early singles “WORTH IT” and “EGO,” exploring different ways to create a pop-rock song beyond the basic guitar/bass/drums template. This new burst of creativity led to a partnership with producer Chad Copelin, whose CV includes such sonically diverse artists as Third Eye Blind, Sufjan Stevens and 5 Seconds Of Summer. Simmons credits Copelin with creating a warm, nurturing studio environment that allowed each member to explore their influences. little image are Jackson Simmons (vocals/guitar), Brandon Walters (bass/synth) and Troy Bruner (drums).
2023 TOUR DATES OPENING FOR COLONY HOUSE
2/17 – St. Louis, MO @ Del Mar Hall
2/18 – Indianapolis, IN @ Deluxe
2/19 – Louisville, KY @ Mercury Ballroom
2/21 – Charlotte, NC @ The Underground
2/23 – Orlando, FL @ House of Blues
2/24 – Birmingham, AL @ Iron City
2/25 – Atlanta, GA @ The Eastern
2/27 – Fayetteville, AR @ George’s Majestic Lounge
2/28 – Oxford, MS @ The Lyric
3/2 – Lexington, KY @ Manchester Music Hall
3/3 – Cincinnati, OH @ Bogart’s
3/4 – Cleveland, OH @ House of Blues
3/5 – Washington, DC @ 930 Club
3/7 – New York, NY @ Irving Plaza
3/8 – Boston, MA @ Paradise Rock Club
3/10 – Philadelphia, PA @ Theater of Living Arts
3/11 – Pittsburgh, PA @ Roxian Theatre
3/12 – Detroit, MI @ St Andrews Hall
3/14 – Chicago, IL @ House of Blues
3/15 – Minneapolis, MN @ Fine Line Music Cafe
3/16 – Kansas City, MO @ The Truman
3/17 – Little Rock, AR @ The Hall
3/23 – Houston, TX @ House of Blues
3/24 – Waco, TX @ Hippodrome Theatre
3/25 – Dallas, TX @ House of Blues
3/26 – Oklahoma City, OK @ The Jones Assembly
3/28 – Mesa, AZ @ The Nile
3/30 – San Diego, CA @ House of Blues
3/31 – Los Angeles, CA @ The Belasco
4/1 – San Francisco, CA @ August Music Hall
4/2 – Portland, OR @ Roseland Theater
4/4 – Seattle, WA @ Neumos
4/6 – Englewood, CO @ Gothic Theatre
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Trying to keep up with this week’s best and most exciting new music? Every Friday, we collect the best new albums available on streaming services on one page. This week, check out Rauw Alejandro’s Saturno, Wizkid’s More Love, Less Ego, Christine and the Queens’ Redcar les adorables étoiles, GloRilla’s Anyways, Life’s Great… EP, Headie One’s No Borders mixtape, and more.

Memphis rapper GloRilla caps a stellar 2022 with the release of her first official project on Yo Gotti’s CMG label. Anyways, Life’s Great‘s nine tracks include breakout hit “F.N.F. (Let’s Go)” plus recent Cardi B collaboration “Tomorrow 2.”
Stream: Spotify | Apple Music

18 months after the arrival of his celebrated sophomore LP, Vice Versa, The FADER’s fifth favorite album of 2021, Rauw Alejandro has returned with 18 new tracks. Saturno includes the previously released single “Lokera” and features from Baby Rasta, DJ Playero, Chris Palace, Arcángel, Subelo NEO, Lyanno, and Brray.
Stream: Spotify | Apple Music

Redcar les adorables étoiles (prologue) is the new album from Redcar, a.k.a. Christine and the Queens. The self-produced album was mixed by Mike Dean and features singles “Je te vois enfin”, “rien dire” and “la chanson du chevalier.” It follows two Christine and the Queens albums, Chaleur Humaine and 2018’s Chris, plus 2020 EP La vita nuova.
Stream: Spotify | Apple Music

Nigerian artist Wizkid returns with a brand new solo album. More Love, Less Ego features appearances from Ayra Starr, Don Toliver, Skillibeng, and Shenseea plus Skepta on “Wow.” Prior to the album dropping, Wizkid released “Money & Love” and “Bad To Me.” More Love, Less Ego is the follow-up to 2020’s Made In Lagos.
Stream: Spotify | Apple Music

AKAI SOLO enlists the best of New York City’s underground with his debut full-length project on billy woods’ indie imprint, Backwoodz Studioz, succeeding his August Body Feeling EP on the label. Spirit Roaming features special verses by rap duo Armand Hammer for the record’s closing track, as well as production credits from Preservation, Messiah Musik, WiFiGawd, and more, throughout the album.
Stream: Spotify | Apple Music | Bandcamp

U.K. drill MC Headie One cast his eye across Europe for his latest project, pulling in guest rappers from Italy, Sweden, Germany, France, and beyond for an album unrestricted by language or regional limitations. No Borders: European Collaboration Project follows Headie One’s 2020 debut Edna and last year’s mixtape Too Loyal For My Own Good.
Stream: Spotify | Apple Music

As a follow-up to Tony Shhnow’s widely praised Reflexions, the Atlanta rapper drops his second album of the year, Plug Motivation. Ahead of the release, the second wave plugg pioneer teased the record with two singles, “Life N Hard Times” and “Can’t Say I’m Broke.”
Stream: Spotify | Apple Music

FaltyDL is back with his first full-length since 2016’s Heaven Is For Quitters. A Nurse To My Patience is 12 tracks of subtly rendered soft rock from a veteran producer of more abstract sounds. The record features guest appearances from Julianna Barwick (twice), Mykki Blanco, Joe Goddard, and Brian DeGraw, all of whom add their personal touches to Falty’s open-book creations.
Stream: Spotify | Apple Music

Anchored by its 18-minute opening track and featuring the previously released “Dream,” Actress’ latest is an abstract-impressionist portrait of a dance floor underwater, where everything moves a bit slower and is cloaked in swirls of ambient sound.
Stream: Spotify | Apple Music

Meeting With a Judas Tree was recorded by Duval Timothy between Freetown in Sierra Leone, the village of Spoleto in Perugia in Italy, and his home studio in south London. The album marks the first release from the producer and artist since he worked with Kendrick Lamar on this year’s Mr. Morale & The Big Steppers. It features contributions from fellow musicians Yu Su, Fauzia and Lamin Fofana. The album follows Timothy’s 2020 solo album Help. Last year he released Son, a collaborative project made with Rosie Lowe.
Stream: Spotify | Apple Music

Nas and Hit-Boy reunite for the third installment of their GRAMMY-winning album series, King’s Disease III. The hip-hop legends have collaborated every year since 2020 for the programming, and even released a second album, Magic, last year. The tertiary album drops via Nas-founded Mass Appeal.
Stream: Spotify | Apple Music

SoFaygo has amassed hundreds of millions of streams in his two years of making music, thanks to hisLil Tecca-produced, Cole Bennett-directed single “Knock Knock.” Now the 21-year-old Atlanta resident releases his debut album, Pink Heartz, boasting a heavy-hitting features lineup with Lil Uzi Vert, DJ Khaled, Gunna, Don Toliver, and Ken Carson. In June of this year, SoFaygo achieved XXL Freshman status, alongside rising stars including Doechii, Saucy Santana, and BabyTron.
Stream: Spotify | Apple Music

Chicago composer and cornetist Ben Lamar Gay consistently makes some of the most interesting music on the planet. Created for EFG London Jazz Fest’s 2020 live-stream program, Certain Reveries is a long-form composition by Gay, performed in duo with percussionist Tommaso Moretti. It arrives today in tandem with Balogun, a standalone tribute to electric jazz pioneer Eddie Harris, premiering now with The FADER.
Stream: Spotify | Apple Music

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A man who stabbed a grandfather in the back and threatened to bury him alive has been jailed for life with a minimum term of 18 years.
Rolandas Karbauskas stabbed neighbour Saulius Badgziunas, 58, outside his home in Broadholme, Lincolnshire, and then dragged his body behind a garage.
Mr Badgziunas' body was found by a family friend on 14 March.
Karbauskas, 48, was found guilty of murder after a two-week trial at Lincoln Crown Court.
Passing sentence, Judge Simon Hirst said Mr Badgziunas had been looking after his two-year-old grandson on the day of the murder.
"Mr Badgziunas was plainly stabbed in the back," he said.
"For reasons which remain unknown, but may have been due to a drunken argument, you picked up a knife used to slaughter pigs."
Judge Hirst told Karbauskas he had "a degree of callousness" when he threatened the victim.
During the trial, jurors heard the Lithuanian national suffered a 20cm stab wound to the back and blunt force injuries, inflicted by his killer, who lived in a caravan at the rear of the secluded house that Mr Badgziunas shared with his daughter and two grandchildren.
The jury heard an audio recording captured by cameras installed near the property in which Karbauskas could be heard saying "bleed to death" and "I told you I would bury you alive".
Mr Badgziunas was heard to moan and say "pull it out, Ruli", a nickname used for Karbauskas.
During sentencing on Friday, Judge Hirst said there was evidence of some effort by Karbauskas to cover his tracks with nearby ground being turned over with a spade.
In a victim impact statement, Mr Badgziunas' daughter described how her world fell apart when she learned of her father's death.
Follow BBC East Yorkshire and Lincolnshire on Facebook, Twitter, and Instagram. Send your story ideas to [email protected].
Man guilty of stabbing grandfather to death
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© 2022 BBC. The BBC is not responsible for the content of external sites. Read about our approach to external linking.

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Kroc Institute for International Peace Studies
Time: Thu Nov 17, 2022, 3:30AM – 5:00PM
Location: Jenkins Nanovic Halls 1030

Join Keough School faculty and students to learn about the ongoing research of our graduate students as Master of global affairs students with a concentration in international peace studies present their capstone research projects.
Schedule of presentations
3:30 p.m.
Terrorism, violent extremism, and the role of youth in Burkina Faso: Conflict analysis and youth empowerment grant proposal
Presenter: Rayangnewende Jean Marc Tiendrebeogo
Respondent: Anna Yasevych
Moderator: Sophia Garcia

4:10 p.m.
Child migration, mobility regimes, and violence in the Global South: Understanding response-making for protecting unaccompanied children in Colombia
Presenter: Juan Mosquera Sepúlveda
Respondent: Susan Nchubiri
Moderator: Tinaishe Maramba
You are welcome to attend all or part of the presentations, either in-person or via Zoom.
Posted In: Kroc Institute Events
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Communications and Digital Media Specialist
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Events Program Manager
574-631-9370
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Copyright © 2022 University of Notre Dame
Kroc Institute for International Peace Studies 1110 Jenkins Nanovic Halls, Notre Dame, IN 46556 USA Phone (574) 631-6970 [email protected]
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When it comes to Abraham Lincoln, classical music, Andy Warhol and Truman Capote, there is always something new to learn.
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By Sebastian Modak
For many, the word “studying” conjures unpleasant memories: of impending exams, caffeine-fueled all-nighters, the frustration of just not getting it. But what if we reimagined the word in the context of the lifelong learner, not as a chore but as the channel to a joy that can be had from staying with a single subject for hours, from revisiting it again and again, even when you think there’s nothing else to learn? Treading mostly on well-trodden ground, three new audiobooks prove that no matter how much you think you know about a subject, there’s always more to study — in a way that isn’t a drag.
In the world of American history, there is perhaps no genre more written-to-oblivion than the presidential biography. So it was with some trepidation that I approached AND THERE WAS LIGHT: Abraham Lincoln and the American Struggle (Random House Audio, 17 hours, 49 minutes), by the Pulitzer Prize-winner Jon Meacham. What else is there to say, I wondered, about one of our most studied, most written about, most fiercely debated figures in our nation’s history? A lot, it turns out. In a calm, deliberate narration that matches the crispness of his prose, Meacham zeros in on Lincoln the human being. We learn of the books and pivotal experiences that shaped his moral outlook and his eventual emancipation of the country’s enslaved people. We learn of the conversations — both internal and otherwise — that were a constant backdrop to the history Lincoln was making.
As Meacham points out, many historians are concerned with whether Lincoln truly was the “Great Emancipator,” a saintly figure with a lifelong commitment to equality and liberty; or simply “a white American man engaged in the accumulation and exercise of power,” leaning on morality only when it was politically convenient. Meacham takes a measured approach, unafraid to point out the moments when Lincoln capitulated to political pressures, like when he decided “to stay on the conservative side of antislavery” in late 1861-62, as the Union faced mounting losses. But on the whole, Meacham’s meticulously researched portrait reveals a man who, while riddled with imperfections and inconsistencies, genuinely believed in the human instinct to do good. “To see him only as a political creature,” Meacham says, “is to give the means of his life priority over its ends.”
Meacham’s comprehensive history (there’s nine hours of tape before Lincoln is even elected president) will certainly equip you to hold your own next time you find yourself in conversation with a Civil War buff. But what about that friend who is always talking about his latest night out at the philharmonic? For a refreshingly quick and actually fun study guide to the intimidating world of sonatas, symphonies and Schumann, listen to DECLASSIFIED: A Low-Key Guide to the High-Strung World of Classical Music (Penguin Audio, 6 hours, 48 minutes). The writer Arianna Warsaw-Fan Rauch, who narrates the book with the easy nature of a best friend, uses her own story as a Juilliard graduate and professional violinist to bypass the gatekeepers of this wide-ranging genre.
Warsaw-Fan Rauch is no longer a touring violinist, but her journey in and out of the often cloistered world of classical music provides the narrative foundation on which she is able to break it all down. In her words: “You’ll leave these pages with enough expertise to join the ranks of those insufferable connoisseurs who’ve been scaring you away from this music for all these years — only, you won’t join their ranks, because you will know better.” By the end of the audiobook, listeners will understand why the Dorian mode of music is “the single most depressing thing mankind has ever invented,” how classical singers are similar to Australian sugar gliders (they require attention to survive), and how to decode classical pieces’ “obnoxiously complicated and sterile titles.” The audio format makes it easy to pause and listen to a piece as it is mentioned — though I wish this production had incorporated some of the music directly into the audiobook. The audiobook does come with some very handy PDFs that include listening lists, dirty letters written by Mozart, and more.
Some of the most entertaining sections of “Declassified” make you feel as if you’re a fly on the wall in conservatory auditions, cutthroat competitions and the obsessive practice routines of professional musicians. In WARHOLCAPOTE: A Nonfiction Invention (Simon & Schuster Audio, 3 hours, 22 minutes), we are flies on a very different wall. Adapted by the director Rob Roth, this play is based on 80 hours of tape recordings of conversations between Andy Warhol and Truman Capote, originally recorded in 1978. As an audiobook, “WarholCapote” is an astounding document, perhaps even more powerful — considering its source material — in our ear than on the stage. Each of these two giants of the arts has been written about extensively (in one memorable exchange, Capote raves at length about a New York Times Magazine profile of him that had just been published). But what “WarholCapote” newly reveals is a portrait of a relationship — a platonic but deeply loving one where every topic, from the purpose of art to the latest celebrity gossip, is worth parsing through. In the audiobook performance, you’ll think Stephen Spinella’s portrayal of Warhol (try counting every time he uses “God” as a drawn-out exclamation of surprise) and Dan Butler’s childlike whine as Capote are overblown — until you stop and look up a clip of what they really sounded like.
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Home – New Gear Alerts – New Audio Gear Alert: Eventide’s H90, Hitsville Reverb by UA, Warmdrive Overdrive & More
Eventide releases the H90 Harmonizer.
Eventide’s H90 builds on the iconic H9 Harmonizer with architecture from the classic H9000.
With its roots in the H9 Harmonizer multi-effects processor, the H90 offers 62 effect algorithms and hundreds of program combinations curated for a variety of instruments and genres. The compact H90 features include comprehensive I/O, flexible routing options, an intuitive UI designed for players, and a built-in tuner.
The H90’s modern ARM-based architecture, derived from the world’s most powerful effects processor, Eventide’s flagship H9000 Harmonizer, gives it the power to accommodate the ongoing creation of advanced, next-gen effects never heard before.
Click here for further information.
 
Universal Audio releases Hitsville Reverb Chambers.
Harness the timeless Motown sound with Hitsville Reverb Chambers by Universal Audio.
Hitsville studio’s attic-converted reverb chambers were essential to Motown’s iconic sound. With help from the original engineers who built them, UA captured the full character and ambience of the spaces heard on some of the greatest soul recordings ever made.
Hitsville Reverb Chambers features simple controls, allowing you to quickly dial in classic reverb sounds on vocals and instruments. And with Dynamic Room Modeling technology—the same used on UA’s Capitol Chambers and Ocean Way Studios plug‑ins—you can go deeper by repositioning the chamber mics to explore new sounds beyond the original positions.
Offered to Apollo/UAD hardware owners and UAD Spark subscribers, Hitsville Reverb Chambers is available in UAD software v10.2. Click here for further information.
 
Warm Audio debuts the Warmdrive overdrive pedal.
Warm Audio pays homage to a classic overdrive pedal with the Warmdrive.
The Warm Audio Warmdrive is a true reproduction of the most sought-after “amp-in-a-box” pedal of all time, delivering the tones of a truly unattainable overdriven amp. Both guitar heroes and modern virtuosos like SRV, Eric Clapton, Robben Ford, John Mayer, Santana, and Cory Wong are known to have used either the original amplifier or the pedal inspired by it.
With an artist roster like that, it’s no wonder that original vintage pedals are talked about amongst the most demanding and discerning chasers of tone. Staying true to the legacy, the Warmdrive delivers all the tones of the original pedal and amplifier that inspired it.
Click here for further information.
 
Novation reinvents the Circuit Rhythm with firmware 2.0.
Novation supercharges their Circuit Rhythm with the 2.0 firmware update.
With the new Beat Match feature, Circuit Rhythm owners can speed their samples up or down to get drum breaks perfectly in time with their session and make beats flow seamlessly. Fixed Length Recording lets you record samples in perfect time with their current project. A new toggle in the Sample Record View lets creators choose between a fixed length sample recording of 8, 16, 32, or 64 steps.
Beatmakers can create dynamic sonic performances and take control of grid FX parameters directly from Circuit Rhythm using editable Grid FX, so they can keep their mind on the music. They can also store patterns and muted track states to Scenes to quickly build an arrangement for their beat, without the need to have any empty patterns in a project.
Click here for further information and downloads.
 
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GHOSTLIGHT RECORDS has announced plans for a cast recording of the critically-lauded new musical Kimberly Akimbo to be released later this season. The show will officially open on Broadway on November 10th at the Booth Theatre.
A new musical with book and lyrics by Pulitzer Prize-winner David Lindsay-Abaire, music by Tony Award-winner Jeanine Tesori, based on the critically-acclaimed play of the same name by David Lindsay-Abaire, choreographed by Danny Mefford, and directed by Jessica Stone, Kimberly Akimbo had its world premiere at the Atlantic Theater Company, where it opened to rave reviews last winter. The production’s Music Director is Chris Fenwick. Kimberly Akimbo features orchestrations by John Clancy, with additional orchestrations by Macy Schmidt. The album will be produced by Jeanine Tesori, John Clancy, and David Stone with Kurt Deutsch serving as executive producer.
Watch the music video for the song “Better” – featuring Bonnie Milligan and the cast of the show below! Pre-save the album HERE.
The Broadway company of Kimberly Akimbo features the company from the Atlantic Theater world premiere production: Tony Award-winner Victoria Clark (The Light in the Piazza, Gigi) as Kimberly, Justin Cooley (who is making his Broadway debut), Tony Award nominee Steven Boyer (Hand to God, Time and the Conways), Alli Mauzey (Cry Baby, Wicked), Bonnie Milligan (Head Over Heels), Olivia Elease Hardy (Broadway debut), Fernell Hogan (The Prom, Mean Girls US Tour), Michael Iskander (Broadway debut), and Nina White (Broadway debut).
Kimberly Akimbo features scenic design by David Zinn, costume design by Sarah Laux, lighting design by Jeanette Oi-Suk Yew, sound design by Kai Harada, projection design by Lucy Mackinnon, and wig, hair, and make-up design by J. Jared Janas. The Production Stage Manager is Arabella Powell and casting is by The Telsey Office, Craig Burns, CSA.
Kim is a bright and funny Jersey teen, who happens to look like a 72-year-old lady. And yet her aging condition may be the least of her problems. Forced to maneuver family secrets, borderline personalities, and possible felony charges, Kim is determined to find happiness in a world where not even time is on her side.
has become the leading independent force in Original Broadway Cast Recordings – building a library of over 200 records over the past 22 years, featuring some of the most successful Broadway musicals and solo albums by Broadway’s brightest stars. Founded by Grammy Award winner Kurt Deutsch, Ghostlight has won Grammy Awards for The Band’s Visit, The Book of Mormon, In the Heights, and Beautiful – The Carole King Musical. Ghostlight has also released solo albums from Patti LuPone, Kelli O’Hara, Sutton Foster, Billy Porter, and more. The label continues to support the new generation of musical theater composers and has developed extensive relationships with Jason Robert Brown, Michael John LaChiusa, and David Yazbek, as well as Lin-Manuel Miranda, Pasek & Paul, Tom Kitt, Joe Iconis, and Shaina Taub. Ghostlight Records is part of the Arts Music division at Warner Music Group. GhostlightRecords.com
Review Roundup: KIMBERLY AKIMBO The Musical Opens On Broadway!
Video: On the Opening Night Red Carpet for KIMBERLY AKIMBO
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U.S. equities rallied Friday, as an earnings beat from Apple helped stocks elbow their way past a week of Wall Street misses for Big Tech.
The S&P 500 (^GSPC) gained 2.5%. The Dow Jones Industrial Average (^DJI) bounced more than 800 points, or 2.6%, to a two-month high, as it also notched a fourth-straight week of gains and its best week of the year. The tech-heavy Nasdaq Composite (^IXI) rose 2.9%. The moves came even as Treasury yields climbed back above 4%.
On the economic data front, the Federal Reserve’s preferred inflation measure showed prices are still running hot across the U.S. economy.
The core personal consumption expenditures price index (PCE) rose 0.5% in September from the prior month, the Commerce Department said Friday — a slight slowdown from August's month-over-month pace of 0.6%. The gauge showed a 5.1% increase year over year, an acceleration from the annual 4.9% seen in August. Economists surveyed by Bloomberg expected increases of 0.5%, and 5.2%, respectively.
Personal income increased 0.4% over the month and consumer spending 0.6%, compared to economist estimates of 0.4% increases for each measure.
Amazon (AMZN) shares tanked nearly 7% Friday after the e-commerce giant issued fourth-quarter sales guidance that missed Wall Street estimates and delivered disappointing Q3 results. The flub marks the second consecutive quarter that weak financials from the company have spurred double-digit percentage declines in its stock price.
But Apple (AAPL) offered a "dim light in an otherwise dark earnings season," faring better than its Big Tech peers as they grappled with macroeconomic hurdles posed by inflation, rising interest rates, and currency headwinds. The company reported record revenue but missed analyst projections in key categories such as iPhone and services. Shares rose about 8%, marking the tech giant's best day since July 2020.
Elsewhere in the technology spotlight, Elon Musk assumed ownership of Twitter (TWTR) after a dragged-out bid to purchase the social media platform was finalized late Thursday. The Tesla CEO fired top executives upon the completion of his $44 billion acquisition of the company and announced plans to reverse lifetime bans from the website.
A busy start to Friday for investors was also marked by other reports from energy conglomerates Exxon Mobil (XOM) and Chevron (CVX), which both reported earnings and revenue that topped Wall Street estimates – lifting shares of each name up by roughly 2.9% and 1.1%, respectively.
SoFi head of investment strategy Liz Young said in a note that she expects further downward revisions and other notable misses this quarter and next, which are likely to challenge the market further. Young noted, however, that on the plus side, this means that investors can tick the box on “earnings get hit.”
“As we move through that process, next up we’ll likely see the economy hit the skids in a bit more dramatic fashion than we’ve seen thus far,” Young said. “There are already several classic recession warning signs in place, and the risks that still lie ahead are bringing the likelihood of an actual recession closer into view.”
—
Alexandra Semenova is a reporter for Yahoo Finance. Follow her on Twitter @alexandraandnyc
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Two stocks that risk-averse investors should consider today are AstraZeneca (NASDAQ: AZN) and Coca-Cola (NYSE: KO). AstraZeneca is a top healthcare company with solid financials, a bright future, and a terrific dividend. Sales rose 43% year over year to $22.2 billion as AstraZeneca benefited from growth in multiple segments as well as the acquisition of rare disease company Alexion Pharmaceuticals, which it completed last year.
Shares of energy company Algonquin Power & Utilities (NYSE: AQN) fell as much as 19.5% in trading on Friday after the company reported third-quarter 2022 financial results. Adjusted net earnings fell 25% to $73.5 million, or $0.11 per share. Management said that higher interest payments and a reduction in tax subsidies were the reason for the shortfall.
There have been more than 50 changes to the Dow since 1896. Removing these three established companies could be next on the docket.
The sudden collapse of FTX, the world’s third-largest cryptocurrency exchange, underlines how important it is for any investor to learn about the risks taken when money is parked with a lightly regulated firm. Sam Bankman-Fried resigned his position as CEO and was replaced by John J. Ray III, a lawyer who has worked on the bankruptcies of Enron, Nortel Networks and many other companies. FTX, based in the Bahamas, held about $16 billion in customer assets but had lent about $10 billion of that to Alameda Research, a trading firm also run by Bankman-Fried and headquartered in Hong Kong, according to a Wall Street Journal report.
At the end of July we identified 10 stocks that insiders were piling into and shared it with our subscribers. In this article we are going to revisit our July 2022 thesis in each stock and report each stock’s performance. These stocks outperformed the market by an average of 1 percentage point since then. Here […]
These stocks have enjoyed profound growth over the last five years and are likely to continue growing indefinitely.
The consensus price target hints at a 131.8% upside potential for SoFi Technologies, Inc. (SOFI). While empirical research shows that this sought-after metric is hardly effective, an upward trend in earnings estimate revisions could mean that the stock will witness an upside in the near term.
In this article, we discussed why oil might be heading to $125 and the 10 most shorted oil stocks. If you want to skip our discussion, you can check out the 5 Most Shorted Oil Stocks. Oil prices have been volatile because there has been so much going on around the globe. These historical occurrences, such […]
Shares of connected-TV platform company Roku (NASDAQ: ROKU) jumped on Friday after an analyst put a note out for investors. As of 1 p.m. ET, Roku stock was up 9%. Dozens of analysts follow Roku stock and Jefferies analyst Andrew Uerkwitz joined them today by initiating coverage with a hold rating, according to The Fly.
Commodity stocks flew high on Friday, with some even clocking double-digit percentage gains during the day. Two C's drove Friday's rally in these stocks: China and commodity prices. China's zero-COVID policy has dealt a heavy blow to the economy and investor sentiment in recent months.
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The stock of Veru (NASDAQ: VERU) did not have a good week. As of midafternoon Friday, the share price was down by more than 35% week to date, according to data compiled by S&P Global Market Intelligence. Veru and its shareholders had high hopes for sabizabulin, an orally administered COVID treatment.
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Taylor Swift Doubles (and Triples) Down on ‘Eras’ 2023 U.S. Stadium Tour Dates: Is Your City Getting Another Show?  Billboard
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A new apartment building in Kenwood that gives residents a “curated living experience” is offering a slew of unique amenities, some of which will be available to residents by the end of November.
Aspire Kenwood, located at 4751 Aspire Blvd., is a luxury apartment building that has leased over 200 of its apartments since April. It is part of the larger Gallery at Kenwood, a $150 million project that will include a hotel, parking garage and retail upon completion.
Rent at Aspire Kenwood falls between $1,629 and $3,700 per month depending on the type of unit and term of the lease, said Lloyd Cobble, CIG Communities senior vice president of project development. Studio apartments are at the very bottom of that range.
Aspire is 82% leased and features a selection of studio, one-bedroom and two-bedroom apartments. About 30% of units were pre-leased, Cobble said.
“The rental market has been very, very strong,” Cobble told the Courier.
Aspire’s developer, CIG Communities, is heavily focusing on digital marketing to attract more tenants, Abbie Huffman, CIG Communities director of business development and brand strategy, said.
For a look inside Aspire Kenwood, flip through the photos above.
Aspire Kenwood residents are all provided with a fob that gives them access to their unit, the gym, mailroom and more. There are also Bluetooth capabilities so residents can use their phones to unlock everything.
The gym features one of Aspire’s top amenities: Peloton bikes. The exercise equipment company previously paused its sales to apartment communities, but has since revived it. Aspire is the first apartment building in Cincinnati to have Peloton bikes on site since the company’s reversal, Huffman said.
One of the benefits of having those bikes is that they serve as fitness on demand, Huffman said. While having resident events is a top priority at Aspire, she said the Peloton bikes help provide their own form of “fitness classes” – though management will probably roll fitness classes into its event offerings.
Also on its first floor, Aspire has a club room featuring a private dining room that can be reserved or used for events, a shuffleboard table and wine lockers. Aspire has hosted a few wine tasting events for its residents, Cobble said, and it eventually hopes to have a “wine club” where residents can get bottles delivered to their locker.
It all helps tie into the social offerings at Aspire, Cobble said.
On the work side, Aspire has office spaces located on floors two through five. Each space can be rented out for $400 a month, Cobble said, and they were created to use space throughout the building. Residents also will be able to take advantage of a membership-based coworking lounge equipped with its own coffee bar and beer tap once completed. CIG has a full liquor license for the property.
The newest of Aspire’s many amenities can be found on the fourth floor. The developer is finishing soundproofing on a podcast studio, adding arcade games to its golf simulator room and unveiling a new amenity to Greater Cincinnati: a Somadome room.
Somadomes are pods that take users through a self-guided meditation session, using “color light therapy” to focus and relax users. Huffman said Aspire is the first in the Greater Cincinnati area to offer a Somadome to its residents, an idea one of CIG’s regional managers had after seeing the product in a different market.
The amenity is free to use, Huffman said, and is able to be individually reserved. CIG plans to work on frosting the windows of the Somadome room in order to give users more privacy.
Residents of Aspire include anyone from young professionals to retired folks living there and seeking to take advantage of all the community has to offer. The apartments – which offer proximity to Mason, Kings Island and the highway – are seeing its studios lease the quickest. Residents all have reserved parking spaces in the roughly 801-space parking garage.
“We have a wide range of demographics and people who feel comfortable in the space,” Cobble said.
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Scientific Reports volume 12, Article number: 19157 (2022) Cite this article
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The complexity of engineering optimization problems is increasing. Classical gradient-based optimization algorithms are a mathematical means of solving complex problems whose ability to do so is limited. Metaheuristics have become more popular than exact methods for solving optimization problems because of their simplicity and the robustness of the results that they yield. Recently, population-based bio-inspired algorithms have been demonstrated to perform favorably in solving a wide range of optimization problems. The jellyfish search optimizer (JSO) is one such bio-inspired metaheuristic algorithm, which is based on the food-finding behavior of jellyfish in the ocean. According to the literature, JSO outperforms many well-known meta-heuristics in a wide range of benchmark functions and real-world applications. JSO can also be used in conjunction with other artificial intelligence-related techniques. The success of JSO in solving diverse optimization problems motivates the present comprehensive discussion of the latest findings related to JSO. This paper reviews various issues associated with JSO, such as its inspiration, variants, and applications, and will provide the latest developments and research findings concerning JSO. The systematic review contributes to the development of modified versions and the hybridization of JSO to improve upon the original JSO and present variants, and will help researchers to develop superior metaheuristic optimization algorithms with recommendations of add-on intelligent agents.
Optimization is a process that is used to find the best inputs to maximize/minimize outputs at affordable computational cost^{1, 2}. The complexity of engineering optimization problems is increasing. Classical gradient-based optimization algorithms have a limited ability to solve complex optimization problems using conventional mathematical methods^3,4,5. Obviously, some traditional methods can be used to solve optimization problems, but they may not yield optimal results. Furthermore, traditional methods cannot resolve all difficult non-linear problems in an acceptable time^{6, 7}. Metaheuristics have become more popular than exact methods for solving optimization problems because of their simplicity and the robustness of the results that they yield^8,9,10. Population-based bio-inspired algorithms have recently been demonstrated to perform well in solving a wide range of optimization problems.
Recently developed original algorithms include forensic-based investigation algorithm (FBI)⁸, the slime mould algorithm (SMA)¹¹, the group teaching optimization algorithm (GTOA)¹², dynamic group optimization (DGO)¹³, the African vultures optimization algorithm (AVOA)¹⁴, the Rao-3 algorithm¹⁵, the gorilla troops optimizer (GTO)¹⁶, smell agent optimization (SAO)¹⁷, the sparrow search algorithm (SSA)¹⁸, the artificial ecosystem optimizer (AEO)¹⁹, the starling murmuration optimizer (SMO)²⁰, the dwarf mongoose optimization algorithm (DMOA)²¹, the war strategy optimization algorithm (WSOA)²², the dynamic butterfly optimization algorithm (DBOA)²³, the artificial hummingbird optimization technique (AHOT)²⁴, and the antlion optimization algorithm (ALOA)²⁵.
Newly enhanced algorithms include the fractional-order modified Harris hawks optimizer (FMHHO)²⁶, the modified manta ray foraging optimization algorithm (MMRFOA)²⁷, an enhanced slime mould algorithm²⁸, the hybrid marine predator algorithm (HMPA)²⁹, partitioned step particle swarm optimization (PSPSO)³⁰, the improved chimp optimization algorithm (ICHOA)³¹, the high performance cuckoo search algorithm (HPCSA)³², the comprehensive learning marine predator algorithm (CLMPA)³³, the enhanced sparrow search algorithm (ESSA)³⁴, the hybrid algorithm that is known as three-learning strategy PSO (TLS-PSO)³⁵, the enhanced shuffled shepherd optimization algorithm (ESSOA)³⁶, the hybrid salp swarm algorithm with teaching-learning-based optimization (HSSATLBO)³⁷, and an enhanced hybrid of crisscross optimization and the arithmetic optimization algorithm (CSOAOA)³⁸. Both original and enhanced metaheuristic optimization algorithms are used in a wide range of fields, including engineering, business, transportation, energy, and even the social sciences.
Bio-inspired metaheuristics can be classified into four main categories based on the source of inspiration for their development; these are evolution-based, physics-based, swarm-based, and human-based. Recently, a novel swarm-based metaheuristic algorithm, called the jellyfish search optimizer (JSO)³⁹, was developed based on the food-finding behavior of jellyfish in the ocean. According to Chou and Truong³⁹, jellyfish move in the ocean in search of planktonic organisms such as fish eggs, larvae, and phytoplankton, and their movement patterns are of two major types, which are (1) following the ocean current and (2) within a jellyfish swarm. The simulation of JSO involves two phases which are diversification and intensification of the search. A time control mechanism governs the switching between these patterns of movement.
JSO can be used in conjunction with other AI-related methods, such as machine and deep learning tools, to optimize their hyper-parameters. The success of JSO in solving a wide range of optimization problems has inspired the present authors to discuss comprehensively the latest findings concerning JSO. This paper reviews various issues around JSO, including its inspiration, variants, and applications, and will provide the latest developments and research findings associated with JSO. The rest of the paper is organized as follows. “Bio-inspired jellyfish search algorithm” outlines the theoretical framework of JSO and explains its implementation in detail. “Recent improvements on and variants of JSO” presents improvements to JSO and corresponding, recently developed variants. “Applications” briefly explains novel applications of JSO in the real world and the field of artificial intelligence. “Discussion” compares performance among, and discusses potential enhancements of, JSO variants. “Conclusion and recommendations” draws conclusions and offers recommendations.
The jellyfish search optimizer (JSO) is a newly developed swarm-based optimization algorithm that was designed and proposed by Chou and Truong³⁹. The following sections discuss the inspiration by jellyfish behavior and mathematical formulations of population initialization, the movement of jellyfish in an ocean current and in a swarm, time control mechanism, and the boundary conditions. The advantages and limitations of the algorithm will also be considered.
Jellyfish live in water of various depths and temperatures around the world. They are shaped like bells; some have a diameter of less than a centimeter while others are very large^{39, 40}. They have a wide range of colors, sizes, and shapes. All of the many species exhibit particular adaptations to the oceanic environment. Their methods of feeding vary: some jellyfish use tentacles to bring food to their mouths while others use filter-feeding to eat whatever the current brings them; yet others actively hunt prey and immobilize them by stinging them with their tentacles^{39, 41}. Jellyfish use their tentacles to sting their prey, and then release a venom that paralyzes it. They do not attack creatures, but those who swim up against or touch them may be stung to death. Jellyfish are most dangerous when gathered together in a jellyfish bloom^{39, 42}.
Jellyfish have special features that enable them to control their movements. Their undersides close like an umbrella, pushing water out to propel their bodies forward. Despite this ability, they mostly drift in the water, so their motion is determined by currents and tides⁴³. Jellyfish can form a swarm, and a large mass thereof is called a jellyfish bloom^{39, 44}. In particular, jellyfish are weak swimming organisms and their orientations with respect to currents are key to the maintenance of blooms and ensuring that they do not become stranded. Numerous factors govern the formation of a swarm, including ocean currents, available nutrients, the availability of oxygen, the presence of predators, and temperature. Among these factors, ocean currents are the most important as they can collect jellyfish into a swarm^{39, 45}.
The swarming of jellyfish, their movements inside swarms and the formation of blooms as jellyfish follow ocean currents have distributed jellyfish species almost everywhere in the ocean. The quantity of food at sites that are visited by a jellyfish varies. Jellyfish thus compare the amounts of food available at various sites and identify the best of them. Accordingly, a new algorithm, called the jellyfish search optimizer (JSO)³⁹ and inspired by the search behavior and movements of jellyfish in the ocean is developed. Figure 1 shows the simulated search behavior and movement of jellyfish in ocean^{46, 47}. In the next section, the behavior and movements of jellyfish in the ocean will be mathematically modeled, and a bio-inspired optimization algorithm that is based on the mathematical model will then be presented³⁹.
Search behavior and movement of jellyfish in ocean.
The two main phases of a metaheuristic optimization algorithm are exploration and exploitation. In JSO, movement toward an ocean current is exploration, movement within a jellyfish swarm is exploitation, and a time control mechanism switches between them. Initially, the probability of exploration exceeds that of exploitation to find areas that contain promising optimal positions with respect to finding of food; over time, the probability of exploitation becomes much higher than that of exploration, and the jellyfish identify the best location inside the searched areas. Figures 2 and 3 present the flowchart and pseudocode of the single objective jellyfish search (SOJS) optimizer, respectively.
Schematic flowchart of SOJS algorithm, adapted from Ref.³⁹.
Pseudocode of JSO algorithm, adapted from Ref.³⁹.
The proposed optimization algorithm is based on three idealized rules³⁹.
Jellyfish either follow the ocean current or move inside the swarm; a time control mechanism governs the switching between these types of movement.
Jellyfish move in the ocean in search of food. They are more attracted to locations where more food is present.
The quantity of food found is determined by the location and the corresponding objective function.
The population of an artificial optimization algorithm is normally initialized at random. The disadvantages of this method are its slow convergence and its tendency to become trapped at local optima as a result of low population diversity. To improve the diversity of the initial population while maintaining simplicity, JSO uses a chaotic map³⁹ known as the logistic map⁴⁸ which provides more diverse initial populations than does random selection and it yields a lower probability of premature convergence as shown in Eq. (1)³⁹.
where, ({text{X}}_{i+1}) is the location of the ith jellyfish;({mathbf{X}}_{i}) is the logistic chaotic value of the location of the ith jellyfish; ({mathbf{X}}_{i}) is used to generate an initial population of jellyfish; ({mathbf{X}}_{o}in left(text{0,1}right)text{,}{ , {text{X}}}_{o}notin left{text{0.0,0.25,0.75,0.5,1.0}right},) and the parameter (eta) is set to 4.0^{39, 49, 50}.
An ocean current contains large quantities of nutrients, so the jellyfish are attracted to it. The direction of the ocean current ((overrightarrow{text{trend}})) is determined by averaging all of the vectors from all jellyfish in the population to the jellyfish that is currently in the best location. The ocean current can be simulated using Eq. (2) ³⁹.
where ({mathrm{X}}^{*}) is the jellyfish that is currently is in the best location in the swarm; ({varvec{upmu}}) is the mean location of all jellyfish, and (beta) > 0 is a distribution coefficient that is related to the length of the ocean current ((overrightarrow{text{trend}})). Based on the results of a sensitivity analysis in numerical experiments³⁹, (beta) =3. Thus, the new location of each jellyfish is given by Eqs. (3) and (4)³⁹.
where ({mathbf{X}}_{i}(t)) is the current location of the jellyfish and ({mathbf{X}}_{i}({text{t}}+ text{1} )) is the new location of the jellyfish.
In a swarm, jellyfish exhibit passive (type A) and active (type B) motions^{42, 51}. Initially, when a swarm has just been formed, most jellyfish exhibit type A motion. Over time, they increasingly exhibit type B motion.
Type A motion is that of jellyfish around their own locations. The corresponding updated location of each jellyfish is given by Eq. (5)³⁹.
where (mathbf{U}mathbf{b}) and (mathbf{L}mathbf{b}) are the upper bound and lower bound on the search space, respectively, and (gamma) > 0 is a motion coefficient, which is related to the length of the motion around each jellyfish’s location. The results of a sensitivity analysis in a numerical experiment³⁹ yield (gamma) = 0.1.
To simulate type B motion, a jellyfish (j) other than the one of interest is selected at random and a vector from the jellyfish of interest (i) to the selected jellyfish (j) is used to determine the direction of movement. When the quantity of food at the location of the selected jellyfish (j) exceeds that at the location of the jellyfish (i) of interest, the latter moves toward the former; it moves directly away from it if the quantity of food available to the selected jellyfish (j) is lower than that available to the jellyfish of interest (i). Consequently, each jellyfish in a swarm moves toward a better location to find food. Equations (6), (7) and (8) simulate the direction of motion and the updated location of a jellyfish³⁹, respectively. This movement is considered to be effective exploitation of the local search space.
where (f) is an objective function of location X.
The ocean current contains large amounts of nutritious food so jellyfish are attracted to it⁴³. Over time, more jellyfish gather together and a swarm is formed. When the temperature or wind changes the ocean current, the jellyfish in the swarm move toward another ocean current, and another jellyfish swarm is formed. The movements of jellyfish inside a jellyfish swarm are type A (passive motions) and type B (active motions), between which the jellyfish switch. Type A is favored in the beginning; as time goes by, type B becomes more favored³⁹.
The time control mechanism is introduced to simulate this situation. To regulate the movement of jellyfish between following the ocean current and moving inside the jellyfish swarm, the time control mechanism includes a time control function (mathrm{c}left(tright)) and a constant ({mathrm{c}}_{o}). The time control function is a random value that fluctuates from zero to unity over time. Equation (9)³⁹ provides the time control function over time; when its value exceeds ({mathrm{c}}_{o}), the jellyfish follow the ocean current. When its value is less than ({mathrm{c}}_{o}), they move inside the swarm. An exact ({mathrm{c}}_{o}) value is not known and the time control varies randomly from zero to one. Hence, ({mathrm{c}}_{o}) is set to 0.5, which is the mean of zero and one.
where (mathrm{c}left(tright)) is the time control function;({mathrm{c}}_{o}) is a constant that is set to 0.5;(t) is the time that is specified by the iteration number, and ({text{Maxiter}}) denotes the maximum number of iterations, which is an initialized parameter.
The term (left(text{1-c}left(tright)right)) is used to simulate the movement inside a swarm (type A or B)³⁹. When (randleft(text{0,1}right)) exceeds (left(text{1-c}left(tright)right)), the jellyfish exhibits type A motion. When (randleft(text{0,1}right)) is lower than (left(text{1-c}left(tright)right)), the jellyfish exhibits type B motion. Since (left(text{1-c}left(tright)right)) increases from zero to one over time, the probability that (randleft(text{0,1}right)>left(text{1-c}left(tright)right)) initially exceeds the probability that (randleft(text{0,1}right)<left(text{1-c}left(tright)right)). Therefore, type A motion is preferred to type B. As time goes by, (left(text{1-c}left(tright)right)) approaches one, and the probability that (randleft(text{0,1}right)<left(text{1-c}left(tright)right)) ultimately exceeds the probability that (randleft(text{0,1}right)>left(text{1-c}left(tright)right)). So, type B motion is favored.
Oceans are located around the world. The earth is approximately spherical, so when a jellyfish moves outside the bounded search area, it will return to the opposite bound Eq. (10) presents this re-entering process³⁹.
where,({text{X}}_{itext{,d}}) is the location of the ith jellyfish in the dth dimension;({text{X}}_{itext{,d}}^{^{prime}}) is the updated location after the boundary constraints have been applied, and ({text{U}}_{text{b,d}}) and ({text{L}}_{text{b,d}}) are the upper bound and lower bound in the dth dimension of the search space, respectively.
The jellyfish search optimizer (JSO) is one of the newest swarm intelligence algorithms; it is inspired by the behavior of jellyfish in the ocean. JSO converges more rapidly and has a stronger search ability than classic optimization methods with few algorithmic parameters. Furthermore, JSO maintains a better balance between exploration and exploitation than other algorithms. Maintaining a balance between the exploration and exploitation of a search space greatly influences the performance of an algorithm. Exploration refers to visiting entirely new regions within the search space. Exploitation refers to visiting those regions of a search space within the neighborhood of previously visited points. JSO can also be used in conjunction with other artificial intelligence (AI)-related techniques.
JSO has been shown to be efficient in solving numerous standard benchmark problems and to have both constrained and unconstrained real-world applications. However, JSO has some minor shortcomings. The algorithm may sometimes become stuck in local optima, suffer from premature convergence⁵², or take a long time to converge⁵⁵. Therefore, it has room for improvement. Necessary improvements can be made by regulating the exploration and exploitation search, preserving the diversity of its search, and accelerating convergence. The following section introduces JSO variants that have been proposed in the literature with improved optimization performance.
The literature includes variants or enhancements of JSO, hybridization, and multi‑objective versions of JSO, as shown in Fig. 4. This section will present an overview of these variants of JSO.
JSO enhancement and its variants.
Table 1 presents the enhancements of the JSO variants in recent studies with respect to population diversity, exploration, exploitation, boundary handling, and the time control mechanism. This subsection briefly describes the intelligent agents that have been proposed.
Bio-inspired optimization algorithms are sometimes enhanced to improve on one or more processes such as those associated with the algorithm parameters. Rajpurohit and Sharma⁵⁶ proposed a chaotic active swarm method (CASM) for initializing the population in JSO. They tested seven chaotic maps (logistic map, circle map, Kent map, piecewise map, sine map, sinusoidal map and tent map) and compared them on benchmark functions and classical constrained engineering design problems. These chaotic maps are implemented to modify the active swarm motion step of the original JSO algorithm. The analysis of the results suggests that the sinusoidal map outperforms all the other chaotic maps that are adopted in JSO to increase population diversity.
In the early stages of the search process, the mean of the jellyfish swarm moves toward the location of the current best jellyfish of the swarm. This situation may lead to undesirable premature convergence in the early stages of the search because the swarm probably does not comprise high-quality jellyfish. To address this issue and to improve the exploration capacity of the original JSO, a quantum-based update rule named quantum JSO (QJSO) was proposed by Kaveh et al.⁵², based on quantum theory for use in the exploration phase of the classical JSO.
The QJSO involves the quantum-based update rule, which is applied to encourage diversification in the search space. The local attractor of each jellyfish of the swarm is determined using Eq. (11)⁵²:
where ({mathbf{X}}_{itext{,d}}^{t}(t)) is the local attractor of the ith jellyfish of the swarm;({mathbf{X}}_{itext{,d}}({text{t}})) is the current location of the ith jellyfish in the swarm; ({mathbf{X}}_{mathrm{d}}^{text{best}}) is the best jellyfish identified so far, and rand1 is a random number that is uniformly distributed on (0, 1). Equation (11) indicates that ({mathbf{X}}_{itext{,d}}left({text{t}}right),) the local attractor of the ith jellyfish, lies on the line that connects ({mathbf{X}}_{itext{,d}}({text{t}})) and ({mathbf{X}}_{mathrm{d}}^{text{best}}) so that it moves following ({mathbf{X}}_{itext{,d}}({text{t}})) and ({mathbf{X}}_{mathrm{d}}^{text{best}}.)
The location of each jellyfish is updated according to Eqs. (12) and (13)⁵².
({mathbf{X}}_{itext{,d}}({text{t}}+ text{1} )) represents the new location; ({mathbf{X}}_{itext{,d}}^{t}(t)) is the current location of the ith jellyfish; rand2 and rand3 are random numbers that are uniformly distributed in (0, 1); (randi)(1, 2) generates uniformly distributed random integers in (1, 2); ({upmu}_{mathrm{d}}) is the mean location of all jellyfish of the swarm, and (beta (t)) controls the convergence of the jellyfish toward the best location that has been identified so far.
In the original JSO, distribution coefficient β was used in the global exploration phase of following the ocean current (Eq. (2)). Chou and Truong³⁹ recommended setting β = 3, which achieves very promising results. The distribution coefficient β influences the degree of diversity of the population that is used to determine a new jellyfish position. A higher β means the new position is farther from the current best position. Naturally, when the diversity of the population is small, a higher β helps to generate new positions at a greater distance from the best solution. Bujok⁵³ proposed an enhancement to this dynamic diversity control that uses a transformed adaptation of the distribution coefficient ((beta)) during the search, based on the current diversity of the jellyfish population, which is estimated using Eq. (14)⁵³:
where D represents the dimensionality of the problem; N is the population size; ({mathbf{X}}_{ij}) is the location of jellyfish (i) at dimension (j); and ({upmu}) is the mean location of all jellyfish of the swarm.
Bujok further used an eigen transformation-method to improve the diversity of population. The eigen-transformation in JSO is controlled by two parameters—the proportion of individuals that are chosen from the current population and used to calculate the covariance matrix and the pseudo-spectrum that is obtained using the eigenvector method. The former controls the proportion of the population N that is used to compute eigenvector B in Eq. (15)⁵³ .
where ({textbf{C}}) is the covariance matrix of the selected part of the population; ({varvec{B}}) is the eigenvector and ({text{D}}) is the eigenvalue. Then, the eigenvectors are employed to transform the original coordinates of the selected individual.
In each JSO generation, either the original coordinate system or the new eigen-transformed coordinate system is applied, as determined by the second control parameter, the pseudo-spectrum, using the eigenvector method. If rand < pseig, then the eigen transformation is applied to the whole generation and several subsequent steps of JSO are affected by this transformation⁵³. In the following ocean current phase (Eq. (4)), when the new position ({mathbf{X}}_{i}({text{t}}+ text{1} )) is computed, all three individual positions, ({text{X}}_{i}(t)), ({mathbf{X}}^{*}) and the average population vector, are transformed using the eigen-transformation that is given by Eq. (16)⁵³. Similarly, in the active motion phase, the eigen-transformation is applied.
After the position-updating rule is implemented, the position (({{mathbf{X}}^{^{prime}}}_{i})) is transformed from the eigen coordinate system back to the original coordinate system using Eq. (17)⁵³.
Lastly, Bujok⁵³ proposed the archiving of good old positions for use in subsequent generations to prevent getting sticking around the local optima and to improve the exploration capacity. The idea of the archive is very simple. Archive A is introduced as empty, and in every selection step, when the current and new jellyfish positions are compared, the old (current) solution is added to A if the new position is better (left(fleft({mathrm{x}}_{i+ text{1} }text{)>}f( , {text{x}}_{i}right)right)). When an archive of size N has been filled, the newly added old good solution randomly replaces one previously added. Notably, the storage of positions in A is assumed to occur in all three phases of JSO. Positions in A is used only in the following ocean current phase (Eq. (4)) to compute the average coordinates of the jellyfish population.
In the newly proposed JSO variant, the average vector is computed from the union of population N and archive A. Doing so reduces the speed of convergence (older good positions are used) but increases the probability of avoiding a local solution area, as formulated in Eq. (18)⁵³.
where ({mathbf{X}}_{i+ text{1} }) is the new position of the jellyfish; ({mathbf{X}}_{i}) is the current position of the jellyfish;({mathbf{X}}_{text{best}}) is the position of the current best jellyfish in the swarm; N is swarm size, and (beta) is the distribution coefficient ((beta) > 0, (beta) = 3).
The JSO search process is effective for exploration because the search pattern is sufficiently random for it. However, it sometimes works poorly for exploitation and so provides poor convergence. The search equation of the original JSO is based on a random selection of a solution vector from the current population that is combined randomly with the current solution vector in order to generate a new candidate solution vector. However, this search strategy is inefficient because one solution vector may contain good information on some dimensions while the other one may contain good information on other dimensions. Hence, some new JSO variants have been proposed.
Manita and Zermani⁵⁴ proposed a modified version of the jellyfish search optimizer that is known as the orthogonal learning jellyfish search optimizer (OLJSO) to solve global optimization problems. The purpose of the proposed algorithm is to increase the exploitation ability of the JSO algorithm. The original JSO can be updated as OLJSO with an orthogonal learning strategy. This strategy is based on the orthogonal learning design (OLD) concept and addresses particularly the exploitation capability. The orthogonal learning design (OLD) finds the best candidate solution by testing only a few representative combinations from the search space.
The main idea behind this method of OLD is to use the properties of the fractional experiment to determine the best sequence of levels. Based on the orthogonal design, (M + 1) offspring (solutions) are generated and these are regarded as the new search mechanism. The purpose of this procedure is to improve the exploitation capacity of the original JSO algorithm. This new strategy begins with two candidate solutions. The first one is randomly selected from the current population. The other one will be generated as given by Eq. (19)⁵⁴.
where,({mathbf{X}}_{i}) is the new location of a jellyfish; ({mathbf{X}}_{a}), ({mathbf{X}}_{b}) and ({mathbf{X}}_{c}) are randomly chosen locations that are determined by the population size (NP), (iin){1, 2,…, NP}, a, b, c (in) {1, 2,…, NP}. The experimental results reveal that the proposed algorithm strongly outperforms the original algorithm in all respects, except for execution time.
Abdel-Basset et al.⁵⁵ presented an improved version of JSO (IJSO) by integrating a novel method called the premature convergence strategy (PCS), to promote exploitation in search space and address the parameter extraction problem of photovoltaic (PV) models that are based on a single diode model (SDM) and a double diode model (DDM). This method works by preserving diversity among the members of the population while accelerating convergence toward the best solution based on two motions of the particles, which are as follows: (i) moving the current solution between two particles that are selected randomly from the population, and (ii) identifying the better of the best-so-far solution and a random solution from the population. These two motions are managed using a weight variable (a control variable) that is generated randomly in the range (0, 1). When the weight variable has a large value, the relative motion of two selected randomly particles is large, but if it is small, then the premature convergence method attends to the area between the best-so-far and the randomly selected solution.
The proposed PCS method improves the ability of the algorithm to exploit the best-so-far solution when the weight variable r is small and improves exploration around the particles to reach other regions when r is high. Mathematically, the premature convergence method is formulated as Eq. (20)⁵⁵:
where r₁, r₂, and r₃ are the indices of three solutions that are picked randomly from the population, and r is the control parameter and is a random number between (0, 1) that is used to control the motion of the current solution. If it is small, then the current solution moves to a location between the best-so-far and ({mathbf{X}}_{{r}_{3}}(t)) to accelerate convergence; if it is high, then the current solution is updated based on two randomly selected solutions from the population to improve the ability of the algorithm to reach other regions. This method is then combined with JSO to modify its performance to find better solutions in fewer iterations than the original JSO. Numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy and the rate of convergence.
Kaveh et al.⁵² proposed QJSO, to enhance the exploitation capability of the original JSO and accelerate its convergence without loss of diversity. The jellyfish exhibit passive (type A) motion around the location of the best jellyfish found so far, as follows⁵².
where ({mathbf{X}}_{i}(t)) is the current location of the jellyfish;({mathbf{X}}^{text{best}}) is the location of the best jellyfish found so far; and randi [1,2] returns a pseudorandom scalar integer in (1, 2). The term randi ([1,2]) allows exploration of the whole neighborhood of the best jellyfish found so far. Numerical results confirm that the proposed QJSO considerably outperforms the original JSO and has superior or comparable performance to those of other state-of-the-art optimization algorithms.
Following ocean currents encourages diversification in the search space (global exploration), while exploitation of the search involves passive and active motions inside jellyfish swarms. Thus, the classical JSO seems to suffer from a lack of global exploration of the search space, focusing mainly on local exploitation of the best solutions found. In the quantum jellyfish search optimizer (QJSO), proposed by Kaveh et al.⁵², a better balance between diversification and intensification of the search process is achieved using a proposed simple linear time control mechanism as follows⁵².
Such a deterministic time control mechanism results in a simple trade-off between intensification and diversification during the search.
Truong and Chou⁴⁷ proposed a fuzzy adaptive time control mechanism to improve exploration and exploitation during the movement of the jellyfish, where the ocean current rate (OCR) and the jellyfish swarm rate (JSR) are inputs and the output is bar movement bar(t). The bar(t) is used to tune the time control function c(t), according to the following equation⁴⁷.
where c(t − 1) is a time control function at time (t − 1) and c(0) = 0.5.
In the classical JSO, if a solution exceeds the boundary of the search space, then the boundary handling mechanism of Eq. (10) brings it back to the opposite bound. Such a boundary handling mechanism may cause difficulties in the convergence process. Indeed, optimal solutions often lie close to (or even on) the boundary of the search space³⁹. Thus, during the optimization process, especially in its final stages, many solutions, which are probably close to optimal, are likely to move beyond the boundaries of the search space. However, the boundary handling mechanism of Eq. (10) significantly alters the values of the design variables fall outside their corresponding bounds.
As a consequence of this boundary handling mechanism, some potentially good solutions, which fall slightly beyond the boundary of the search space, may be lost during the search process. QJSO, proposed by Kaveh et al.⁵², addresses this issue. The boundary handling mechanism of the original JSO that brings solutions back to the violated bound when they fall outside the boundary of the search space is updated using Eq. (24)⁵²:
where ({mathbf{X}}_{itext{,d}}^{^{prime}}) is the updated position of the jellyfish i with d dimensions of decision variables, and ({mathbf{U}}_{text{b, d}}) and ({mathbf{L}}_{text{b, d}}) are the upper and lower bounds, respectively.
Shaheen et al.⁵⁷ proposed the optimization of combined heat and power economic dispatch (CHPED) using a novel amalgamated heap-based and jellyfish optimizer (AHJFO). They improved the efficiency of two newly developed techniques, the heap-based optimizer (HBO) and JSO. Their proposed AHJFO incorporates an adjustment strategy function (ASF) to improve exploration in a few iterations by improving solutions that are generated using HBO. Further, as the iterations proceed, exploitation is improved by updating the solutions that are generated using JSO. The proposed AHJFO is more effective than HBO and JSO in solving the CHPED problem for medium-sized 24 unit and large 96-unit systems. Simulation results reveal the superiority of the proposed AHJFO over HBO, JSO, and other algorithms in solving CHPED problems.
Ginidi et al.⁵⁸ proposed a heap-based jellyfish search optimizer (HBJSO) to enhance the performance of two recently developed algorithms: the heap-based optimizer (HBO) and JSO. The proposed hybrid HBJSO seeks to make use of the explorative features of HBO and the exploitative features of JSO to overcome some of the issues associated with their standard forms. The proposed hybrid HBJSO, HBO, and JSO were validated and statistically compared by using them to solve a real-world optimization problem of combined heat and power economic dispatch in electrical grids. The proposed hybrid HBJSO, HBO, and JSO were applied to two medium-sized systems of 24 and 48 units, and two large systems of 84- and 96-units. The experimental results demonstrated that the proposed hybrid HBJSO outperforms the standard HBO and JSO and other reported techniques in power economic dispatch.
Rajpurohit and Sharma⁵⁹ proposed a hybrid metaheuristic (jellyfish search optimizer (JSO) and sine–cosine algorithm (SCA)) algorithm that combines the advantages of both constituents algorithms and outperforms them. They first used opposition-based learning in population initialization and then introduced a modified position update operator of the SCA into the original structure of JSO. They tested their proposed hybrid metaheuristic (JSO-SCA) on a set of benchmark functions to find the minimum weight design of a transmission tower, and it outperformed both JSO and SCA.
Utama et al.⁶⁰ proposed the hybrid-jellyfish (HJF) algorithm which combines JSO and the neighborhood exchange strategy. HJF has five major stages: (1) initializing the position of the jellyfish swarm and ocean currents; (2) updating position based on jellyfish movement; (3) applying the time control mechanism; (4) applying the rules of large rank value; and (5) improving solutions based on neighborhood exchange procedures. Their proposed algorithm was used to solve the fuel consumption capacity vehicle routing problem (FCCVRP) and numerical results indicate that it effectively reduces the total cost of fuel.
Lei et al.⁶¹ proposed an enhanced algorithm, known as the fractional-order modified strategy and Gaussian mutation mechanism jellyfish search optimizer (FOGJSO). The fractional-order modified strategy and Gaussian mutation mechanism are integrated with the original JSO to electively enhance the convergence precision tracking performance of the original JSO. The proposed algorithm outperforms various classical methods on IEEE Congress on Evolutionary Computation (CEC) 2017 and CEC 2019 test functions with respect to accuracy, stability, and convergence acceleration.
Chou and Truong⁴⁶ developed the multi-objective jellyfish search (MOJS) optimizer to solve engineering problems. MOJS integrates Lévy flight, an elite population, a fixed-size archive, a chaotic map, and the opposition-based jumping method to obtain Pareto-optimal solutions. These techniques are employed to define the motions of jellyfish in an ocean current or a swarm in multi-objective search spaces. They tested their proposed algorithm on 20 multi-objective mathematical benchmark problems and compared it with six well-known metaheuristic optimization algorithms such as MOALO (multi-objective antlion optimization), MOGWO (multi-objective grey wolf optimization), and MOPSO (multi-objective particle swarm optimization). They used MOJS to solve three constrained structural problems (25, 160, and 942-bar tower design) to minimize structural weight and maximum allowable nodal deflection. The results thus obtained indicate that the MOJS algorithm finds highly accurate approximations to Pareto-optimal fronts with a uniform distribution of solutions for the test functions. The advantages of using MOJS in solving real engineering problems and finding the best Pareto-optimal fronts are thus demonstrated.
Shaheen et al.⁶² proposed an enhanced multi-objective quasi-reflected JSO (MOQRJSO) for solving multi-dimensional optimal power flow (MDOPF) problems. They made the following two modifications to the standard JSO algorithm. (1) A cluster of a random size that represents the social community was proposed. Data are shared in the cluster and (2) quasi-opposition-based learning is incorporated into JSO to support the exploration phase. A fuzzy decision-making strategy is integrated into MOQRJSO to select the best solutions. The concept of Pareto optimality is used to extract the non-dominated solutions. The superiority of the MOQRJSO was proved by its application to an IEEE 30-bus system, an IEEE 57-bus system, the West Delta Region System of 52 buses (WDRS-52) in Egypt, and a large 118-bus system. The outcomes achieved using the proposed MOQRJSO were compared with those achieved using the conventional MOJS algorithm and other techniques in the literature. MOQRJSO yields lower fuel costs and power losses than those other techniques revealing its robustness, effectiveness, and superiority in handling MDOPF problems.
This section focuses on the use of jellyfish search optimizer (JSO) in engineering optimization, prediction and classification, and the algorithmic fine-tuning of artificial intelligence.
The jellyfish search optimizer (JSO) has been used in various engineering fields, such as power systems and energy generation, communication and networking, and civil and construction engineering as detailed below.
This section examines the uses of JSO in power systems and energy-related fields. Rai and Verma⁶³ used JSO to find the economic load dispatch of generating units, considering transmission losses. The effectiveness of the proposed method was evaluated by testing it on six systems under various loads. It was compared with the lambda-iterative and PSO algorithms to find the most efficient among them. JSO yielded the lowest fuel cost and transmission losses of the compared methods.
Tiwari et al.⁶⁴ used JSO to analyze the effect of the installation of distributed generation (DG) and a capacitor bank (CB) on a radial distribution system (RDS). They carried out a cost-based analysis that considered the major expenses that are incurred due to the installation, operation, and maintenance of DG and CB units. They tested JSO on the IEEE 33-bus RDS. The results of their simulation were compared with those of simulations of other methods in the literature. JSO outperformed these other methods in terms of both power loss minimization and profit maximization.
Farhat et al.⁶⁵ used JSO to propose a power flow model that included three types of energy sources, which were thermal power generators representing conventional energy sources, wind power generators (WPGs), and solar photovoltaic generators (SPGs). They used a modified IEEE 30-bus test system to determine its feasibility. To examine the effectiveness of the proposed power flow model, the results of its simulation were compared with the results of simulations of four other nature-inspired global optimization algorithms. The results established the effectiveness of JSO in solving the optimal power flow (OPF) problem with respect to both minimization of total generation cost and solution convergence.
Shaheen et al.⁶⁶ introduced an efficient and robust technique that used JSO for optimal Volt/VAr coordination based on a joint distribution system reconfiguration (DSR)with the integration of distributed generation units (DGs) and the operation of distribution static VAr compensators (SVCs). JSO yielded the best solution and a comparison of the proposed JSO with similar approaches demonstrated its usefulness in modern control centers.
Alam et al.⁶⁷ used JSO to track the global maximum power point (GMPP) of the solar photovoltaic (PV) module under partial shading conditions. Their results suggested that the JSO method has good tracking speed and accuracy. They also found that the JSO strategy tracks the GMPP in half of the time that is taken by the PSO algorithm under both uniform and shaded conditions.
Boutasseta et al.⁶⁸ used the JSO technique to modify the voltage of a photovoltaic array using a boost direct current to direct current (DC–DC) converter. Their experimental results revealed that JSO performs well under both normal and disturbed operating conditions.
Abdulnasser et al.⁶⁹ used JSO for the optimal sizing and placement of DGs and capacitor banks (CBs). To elucidate the efficiency of the proposed algorithm, they considered various cases; the allocation of CBs only, the allocation of DGs only, and the allocation of both CBs and DGs. The results thus obtained reveal that the JSO delivered the best results with respect to technical, economic, and emission objectives.
Ngo⁷⁰ used JSO to solve the economic dispatch problem and to reduce costs and fuel consumption in power systems. To verify the feasibility and the effectiveness of the proposed scheme, they conducted two case studies to test the optimization performance of the proposed method from multiple economic perspectives. The validation results reveal that the proposed scheme provided more speed, convergence, and robustness than the methods to which it was compared.
Nusair et al.⁷¹ used JSO and other recently developed algorithms (slime mould algorithm (SMA), artificial ecosystem-based optimization (AEO), and marine predators algorithm (MPA)) to solve both multi- and single-OPF objective problems for a power network that incorporate flexible alternating current transmission system (FACTS) and stochastic renewable energy sources. They compared these algorithms to commonly available alternatives in the literature such as PSO, moth flame optimization (MFO), and grey wolf optimization (GWO), using an IEEE 30-bus test system. Their results reveal that JSO and other recently presented algorithms (MPA, SMA, and AEO) are more effective than PSO, GWO, and MFO in solving OPF problems.
Eid⁷² used JSO to allocate distributed generators (DG) and shunt capacitor (SC) banks optimally in distribution systems. He found JSO to be practical and effective in solving such nonlinear optimization problems, yielding better results than other algorithms in the literature. Huang and Lin⁷³ used an improved jellyfish search optimizer (IJSO) to track the maximum power point (MPPT) under partial shade conditions. Their results showed that IJSO can accurately track the global maximum power point, and that it converged more quickly than an improved particle swarm optimization (IPSO) algorithm.
Shaheen et al.⁵⁷ integrated a novel amalgamated heap-based agent with jellyfish optimizer (AHJFO) to optimize combined heat and power economic dispatch (CHPED). They improved the efficiency of two newly developed techniques: the heap-based optimizer (HBO) and JSO. AHJFO incorporates an adjustment strategy function (ASF) to improve exploration in a few iterations by improving the solutions that are generated using HBO. As the iterations proceed, exploitation is improved by updating solutions that are generated using JSO. AHJFO is more effective than HBO and JSO in solving the CHPED problem for medium-sized 24-unit and large 96-unit systems. Simulation results reveal the superiority of the proposed AHJFO over HBO, JSO and other algorithms for solving the CHPED problems.
Ginidi et al.⁵⁸ proposed an innovative hybrid heap-based JSO (HBJSO) to improve upon the performance of two recently developed algorithms: the heap-based optimizer (HBO) and JSO. HBJSO uses the explorative features of HBO and the exploitative features of JSO to overcome some of the weaknesses of these algorithms in their standard forms. HBJSO, HBO, and JSO were validated and statistically compared by using them to solve a real-world optimization problem of combined heat and power (CHP) economic dispatch. HBJSO, HBO, and JSO were applied to two medium-sized 24-unit and 48-unit systems, and two large 84 unit and 96-unit systems. The experimental results demonstrate that the proposed hybrid HBJSO outperforms the standard HBO, JSO and other reported techniques when, applied to CHP economic dispatch.
Shaheen et al.⁷⁴ proposed an enhanced quasi-reflection jellyfish optimization (QRJFO) algorithm for solving the optimal power flow problem. Fuel costs, transmission losses and pollutant emissions were considered as multi-objective functions. The performance of the proposed QRJFO algorithm was evaluated on the IEEE 57-bus, the practical West Delta Region system and a large IEEE 118-bus. Simulation results demonstrate the quality of the solutions and resilience of QRJFO.
Boriratrit et al.⁷⁵ used jellyfish search extreme learning machine (JS-ELM), the Harris hawk extreme learning machine (HH-ELM), and the flower pollination extreme learning machine (FP-ELM) to increase accuracy and reduce overfitting in electric energy demand forecasting. Their results show that the JS-ELM provided a better minimum root mean square error than the state-of-the-art forecasting models.
Ali et al.⁷⁶ presented an effective optimal sizing technique for a hybrid micro-grid using JSO. Their proposed sizing approach considers uncertainty associated with hybrid renewable resources. They investigated several operating scenarios to evaluate the effectiveness of the proposed approach and compared it to various optimization techniques. Their results demonstrate the applicability of JSO to their problem of interest.
Rai and Verma⁷⁷ used JSO to solve a combined economic emission problem for an isolated micro-grid. They conducted tests on this micro-grid system, comprising traditional generators and renewable energy sources in two scenarios. They compared the results with those obtained using available algorithms to prove that the JSO algorithm was more effective than the others.
Yuan et al.⁷⁸ used the improved jellyfish search optimizer and support vector regression (IJSO-SVR) to solve the problems of grid connection and power dispatching that are caused by non stationary wind power output. IJSO exhibits good convergence ability, search stability, and optimum-seeking ability, and it is more effective than conventional methods in solving optimization problems. The IJSO-SVR model outperformed other models in the literature and presents a more economical and effective means of optimizing wind power generation to solve problems with its uncertainty and can be used in grid power generation planning and power system economic dispatch.
Chou et al.⁷⁹ used JSO and convolutional neural networks (CNNs) to evaluate the power generation capacity of plant microbial fuel cells (PMFCs) on building rooftops. Their results demonstrate the superior performance of JSO-optimized deep CNNs in learning image features and their consequent suitability for constructing models for estimating power generation by PMFCs.
This section investigates the use of JSO in the field of communication and networking. Selvakumar and Manivannan⁸⁰ used JSO to overcome the shortcomings of defragmentation in networking, and to improve the quality of network services. The proposed combination of proactive/reactive defragmentation approach and JSO (PR-DF-JSO) outperformed state-of-the-art spectrum defragmentation algorithms in terms of spectrum utilization, network efficiency, and quality of service offered based on the results of experiments and standard quality metrics. Specifically, lower spectrum fragmentation complexity, a better bandwidth fragmentation ratio, and less overall connection blocking were achieved.
Durmus et al.⁸¹ used swarm-based metaheuristic algorithms JSO, PSO, artificial bee colony (ABC), and the mayfly algorithm (MA), to determine the optimal design of linear antenna arrays. They conducted extensive experiments on the design of 10-, 16-, 24- and 32-element linear arrays and determined the amplitude and the positions of the antennas. They performed each of their experiments 30 times owing to the randomness of swarm-based optimizers, and their statistical results revealed that the novel algorithms JSO and MA outperformed the well-known PSO and ABC methods.
Aravind and Maddikunta⁸² proposed a novel optimal route selection model for use with the internet of things (IoT) in the field of healthcare that was based on an optimized adaptive neuro-fuzzy inference system (ANFIS). They selected optimal routes for medical data using a new self-adaptive jellyfish search optimizer (SA-JSO) that was an enhanced version of the original JSO algorithm³⁹. Their model outperformed others.
Structural optimization has become one of the most important and challenging branches of structural engineering, and it has consequently received considerable attention in the last few decades⁸³. Chou and Truong³⁹ developed JSO, motivated by the behavior of jellyfish in the ocean for use in civil and construction engineering. They used JSO to solve structural optimization problems, including 25, 52, and 582-bar tower designs. Their results showed that JSO not only performed best but also required the fewest evaluations of objective functions. Therefore, JSO is potentially an excellent metaheuristic algorithm for solving structural optimization problems.
Chou and Truong⁴⁶ expanded the framework of the single-objective jellyfish search (SOJS) algorithm to a multi-objective jellyfish search optimizer (MOJS) for solving engineering problems with multiple objectives. MOJS integrates Lévy flight, an elite population, a fixed-size archive, a chaotic map, and the opposition-based jumping method to obtain Pareto-optimal solutions. Three constrained structural problems (25, 160, and 942-bar tower designs) of minimizing structural weight and maximum nodal deflection have been solved using the MOJS algorithm. MOJS is an effective and efficient algorithm for solving multi-objective optimization problems in civil and construction engineering.
Kaveh et al.⁵² proposed a quantum-based JSO, named Quantum JSO (QJSO), for solving structural optimization problems. QJSO is used to solve frequency-constrained large cyclic symmetric dome optimization problems. The results thus obtained reveal that QJSO outperforms the original JSO and has superior or comparable performance to that of other state-of-the-art optimization algorithms.
Rajpurohit and Sharma⁵⁶ proposed an enhancement of JSO by the implementation of chaotic maps in population initialization. They applied their enhanced JSO to three classical constrained engineering design problems. Analysis of the results suggests that the sinusoidal map outperforms other chaotic maps in JSO and helps to find efficiently the minimum weight design of a transmission tower.
Ezzeldin et al.⁸⁴ used JSO to develop optimal strategies for the sustainable management of saltwater intrusion into coastal aquifers based on the finite element method (FEM). They tested the effectiveness of JSO by applying it to a real aquifer system in Miami Beach to maximize its total economic benefit and total pumping rate. JSO has also been used in a case study of the El-Arish Rafah aquifer, Egypt, to maximize the total pumping rate. The results in both cases were compared to relevant results in the literature, revealing that the JSO is an effective and efficient management tool.
Chou et al.⁸⁵ used JSO and convolutional neural networks (CNNs) to predict the compressive strength of ready-mixed concrete. Their analytical results reveal that computer vision-based CNNs outperform numerical data-based deep neural networks (DNNs). Thus, the bio-inspired optimization of computer vision-based convolutional neural networks has promise for predicting the compressive strength of ready-mixed concrete.
Chou et al.⁸⁶ presented jellyfish search optimizer (JSO)-XGBoost and symbiotic organisms search (SOS)-XGBoost for forecasting the nominal shear capacity of reinforced concrete walls in buildings. Their proposed methods outperform the ACI provision equation and grid search optimization (GSO)-XGBoost in the literature. Thus, they can be used to improve building safety, simplify a cumbersome shear capacity calculation process, and reduce material costs. Their systematic approach also provides a general framework for quantifying the performance of various mechanical models and empirical formulas that are used in design standards.
Truong and Chou⁴⁷ proposed a novel fuzzy adaptive jellyfish search optimizer (FAJSO) for use in the stacking system (SS) of machine learning. They integrated the JSO, the fuzzy adaptive (FA) logic controller, and stacking ensemble machine learning. Its application to construction productivity, the compressive strength of a masonry structure, the shear capacity of reinforced deep beams, the axial strength of steel tube confined concrete, and the resilient modulus of subgrade soils was investigated. Their results indicate that the FAJSO-SS outperformed other methods. Accordingly, their proposed fuzzy adaptive metaheuristic optimized stacking system is effective for providing engineering informatics in the planning and design phase.
Prediction and classification are required in a variety of areas that involve time series and cross-sectional data^{87, 88}. This section concerns articles in which JSO has been used alone or integrated with machine/deep learning algorithms for prediction and classification.
Almodfer et al.⁸⁹ employed a random vector functional link (RVFL) network that was optimized by JSO, AEO, MRFO, and SCA to predict the performance of a solar thermo-electric air-conditioning system (STEACS). Their results revealed that the RVFL-JSO outperformed the other algorithms in predicting all responses of the STEACS with a correlation coefficient of 0.948–0.999. They recommended its use for modeling STEACS systems.
Chou et al.⁹⁰ used JSO to optimize the convolutional neural network (CNN) hyper-parameters to ensure the accuracy and stability of CNN in predicting power consumption. Their analytical results provide insights into the formulation of energy policy for management units and can help power supply agencies to distribute regional power in a way that minimizes unnecessary energy loss.
Barshandeh et al.⁹¹ utilized JSO and the marine predator algorithm (MPA) to develop a learning-automata (LA)-based hybrid algorithm for benchmark function optimization and solving data clustering problem. They applied the proposed algorithm to ten datasets and compared it with competing algorithms using various metrics; the hybrid algorithm outperformed. Desuky et al.⁹² used JSO to classify imbalanced and balanced datasets. They performed experiments on 18 real imbalanced datasets, and the proposed method performed comparably with well-known and recently developed techniques.
Chou and Truong⁸⁸ tested JSO and other parameter-less algorithms (TLBO, SOS) by using them in the hyperparameters finetuning of least squares support vector regression (LSSVR) to develop a novel forecasting system. The linear time-series has been optimized using nonlinear machine learning models to identify historical patterns of regional energy consumption. Analytical results confirm that the proposed system, JSO-LSSVR, can predict multi-step-ahead energy consumption time series more accurately than can the linear model.
Chou et al.⁹³ developed a weighted-feature least squares support vector regression (WFLSSVR) model that is optimized by JSO to predict the peak friction angle (shear strength) of fiber-reinforced soil (FRS), which is a popular material for use in building geotechnical structures. Their results showed that JSO-WFLSSVR outperformed baseline, ensemble, and hybrid machine learning models, as well as empirical methods in the literature. The JSO-WFLSSVR model is also effective for selecting features and can help geotechnical engineers to estimate the shear strength of FRS.
Hoang et al.⁹⁴ implemented a support vector machine classifier that was optimized using JSO for the automatic classification of the severity of concrete spalling. It partitions input data into two classes, shallow spalling and deep spalling. Experimental results, supported by the Wilcoxon signed-rank test, reveal that the newly developed method is highly effective for classifying the severity of concrete spalling with an accuracy rate of 93.33%, an F1 score of 0.93, and an area under the receiver operating characteristic curve of 0.97.
Siddiqui et al.⁹⁵ used JSO to calculate the optimum switching angle in the modulation range to eliminate desired lower-order harmonics in a multilevel inverter (MLI) voltage control application. The total harmonic distortion (THD) values of five-, seven-, and nine-level were computed using JSO and compared with those obtained using the powerful differential evolution (DE) algorithm. The results thus obtained clearly demonstrated that the output of an MLI in JSO exhibits THD that is superior to that in the output of DE for low and medium values of the modulation index.
Çetinkaya and Duran⁹⁶ used JSO and other recently developed optimization algorithms [marine predators’ algorithm (MPA), tunicate swarm algorithm (TSA), mayfly optimization algorithm (MOA), chimp optimization algorithm (COA), slime mould optimization algorithm (SMOA), archimedes optimization algorithm (AOA), and equilibrium optimizer algorithm (EOA)] to improve the precision of the clustering-based segmentation of vessels. Simulation results of these algorithms exhibited similar convergence rates and error performances. Statistical analyses demonstrated that the stability and robustness of each metaheuristic approach sufficed to separate vessel pixels from the background pixels of a retinal image.
Wang and Gao⁹⁷ used the multi-objective jellyfish search optimizer (MOJS) to determine the weights of kernel functions. According to their experimental result concerning three American solar sites, the proposed system that integrates with MOJS provided a higher interval coverage rate and a narrower interval width than those of other systems.
Zhao⁹⁸ used single-objective JSO to classify brain function in human brain function parcellation. Experimental results show that that the new method not only has a greater searching ability than other partitioning methods, but also can obtain better spatial structures and stronger functional consistency.
Lei et al.⁶¹ proposed an enhanced algorithm, known as the fractional-order modified strategy and Gaussian mutation mechanism jellyfish search optimizer (FOGJSO), to predict rural resident income. They used FOGJSO to optimize the order of a discrete fractional time-delayed grey model for forecasting rural resident income. The results reveal that FOGJSO performed much better with respect to precision and convergence speed than did other methods.
Shubham et al.⁹⁹ used JSO for clustering between a dish type stirling solar generator, a micro hydro turbine, a diesel generator, a flywheel energy storage device, a super magnetic energy storage device and an electric vehicle in a renewable energy based microgrid to stabilize the frequency and tie line power in the system. They compared the performance of the JSO based dual stage controller with those of the black widow optimization algorithm, GA and the PSO-based controller, with respect to overshoot, undershoot, settling time and figure of demerit. JSO outperformed other optimization algorithms when used to tune dual stage (1+PI)TID controller involving a microgrid-based electric vehicle.
Hyper-parameter optimization is essential to the development of efficient models in machine learning and deep learning algorithms, as well as for quality control in industrial production^{100, 101}. JSO is an efficient and innovative algorithm that is used in hyper-parameter optimization.
Chou et al.¹⁰² used JSO to optimize the hyper-parameters of a deep learning model that is called residual network (ResNet) and is used to classify the deflection of reinforced concrete beams, based on observations made by computer vision. Their work supports an innovative method that engineers can use to measure the deflection of reinforced concrete beams. The results of their analysis revealed that the proposed ResNet model that was optimized by JSO was more accurate than conventional ResNet.
Dhevanandhini and Yamuna¹⁰³ used JSO to find the optimal coefficients of a discrete wavelet transform (DWT) to improve efficient multiple-video watermarking. They analyzed the performance of the proposed method using various metrics and compared it with the DWT-based watermarking approach, which it outperformed.
Elkabbash et al.¹⁰⁴ proposed a novel detection system that was based on optimizing the random vector functional link (RVFL) using JSO, following the dimensional reduction of Android application features. They used JSO to determine the optimal configurations of RVFL to improve classification performance. The optimized RVFL minimized the runtime of the models with the best performance metrics.
Gouda et al.¹⁰⁵ employed JSO to solve the problem of evaluating the parameters of the polymer exchange membrane fuel cells (PEMFCs) model. The maximum percentage voltage-biased error was ± 1% in all test cases, indicating that JSO can solve this problem more effectively than other algorithms.
Youssef et al.¹⁰⁶ used JSO to estimate the parameters of a single-phase power transformer from the current and voltage under any load. They consider difference between the estimated and actual values as the main objective function that must be minimized. Experimental results revealed that the parameters of the transformer equivalent circuit were accurately obtained, indicating that the algorithm can be used to estimate the parameters of a single-phase transformer.
Kızıloluk and Sert¹⁰⁷ adopted JSO to optimize the hyper-parameters of the Alex Net CNN model for feature extraction in the Faster R-CNN-JSO model for the early detection of hurricanes from satellite images. The purpose was to alert people about upcoming disasters and thus minimize casualties and material losses. Their results demonstrated that hyper-parameter optimization increased the detection performance of the proposed approach by 10% over that of Alex Net without optimized hyper-parameters. The average precision of Hurricane-faster R-CNN-JS was 97.39%, which was remarkably higher than those of other approaches.
Bisht and Sikander¹⁰⁸ used JSO to optimize the parameters of the solar photovoltaic (PV) model. They used JSO to optimize the parameters of a single-diode PV model using various performance measures, such as PV characteristics, power-voltage, and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE), and normalized mean absolute error (NMAE). Their proposed technique provided better results than other techniques, with a lower RE, RMSE, MAE, and NMAE; it also converged rapidly.
Azam et al.¹⁰⁹ utilized JSO to dampen out low-frequency oscillations (LFOs) by tuning the critical parameters of conventional lead-lag type power system stabilizers. JSO is used to tune time-domain simulations of the angular frequency, rotor angle, and control signal. They tested this method on two separate multimachine networks that were exposed to a three-phase fault, and compared it with two well-known optimization algorithms, called PSO and the backtracking search algorithm (BSA). Their results show that JSO provided better damping power system ratio than did the other algorithms. Moreover, the JSO-based approach converged in fewer iterations.
Raja and Periasamy¹¹⁰ presented the block chain and JSO-based deep generative adversarial neural network (DGANN) method for the distributed routing scheme of a wireless sensor network (WSN). They used the block chain routing protocol to detect and store packets and to transfer them from the source to the destination efficiently to improve the security and efficiency of the DGANN method. They used JSO to optimize the weight parameters of the DGANN method. The simulation results demonstrate that in the routing of a WSN, DGANN with optimized parameters outperforms others methods, such as the multidimensional scaling-map, the trust-aware routing protocol through multiple attributes, and dynamic rate-aware classified key distributional secure routing algorithms.
Usharani et al.¹¹¹ used JSO to optimize the hyperparameters of long short-term memory (LSTM) networks to enhance the error metrics of the approximate multiplier. They used their proposed pre-trained LSTM model to generate approximate design libraries for the different truncation levels as a function of area, delay, power and error metrics. Their experimental results on an 8-bit multiplier with an image processing application reveals that the proposed approximate computing multiplier achieved a superior area and power reduction with very good error rates.
Nyong-Bassey and Epemu¹¹² used JSO and PSO to identify servomechanism parameters using a two-step approach, involving a first-order transfer function and iterative minimization of a fitness score that is derived from the root mean squared error between the experimental and simulated position responses of the servomechanism of an equivalent state-space model structure. The simulated angular position step responses of the servomechanism that runs the JSO and PSO algorithms showed very closely with each other, in terms of root mean squared error. Table 2 summarizes recent advances in the application of the jellyfish search optimizer.
This section presents the findings of this study in relation to the research goals, including recent trends in the use of JSO, potential enhancements in JSO, and JSO variants, which are comparatively analyzed.
This section compares recent research works on JSO and its variants in a variety of fields. JSO is a newly developed robust algorithm that has a good population utilization rate and maintains a favorable balance between exploration and exploitation. Optimization problems vary among fields and the No Free Lunch theorem specifies that a single algorithm cannot satisfactorily solve all such problems. The literature clearly reveals that JSO is being increasingly used since its source code was recently shared in the academic community. The use of JSO for optimization has attracted substantial interest since its initial development. However, the number of relevant works on MOJS was lower than that of the single objective JSO both with respect to theoretical frameworks and applications. Figure 5 presents the number of studies related to each area in which JSO is applied, where C & N = Communication and Networking; C & CE = Civil and Construction Engineering; PS & EG = Power System and Energy Generation; P & C = Prediction and Classification; and FAI = Finetuning of Artificial Intelligence.
Number of studies related to applications of JSO.
According to Table 3, JSO and its variants are mostly applied to solve problems that are related to (1) engineering optimization (56%), including in power system and energy generation, communication and networking, and civil and construction engineering; (2) prediction and classification (21%); and (3) the finetuning of artificial intelligence (23%). Despite the favorable performance of JSO in solving many standard benchmark functions, CEC functions, and real-world constrained and unconstrained problems, the algorithm has been seldom applied to communication networks, portfolio optimization in finance, civil engineering infrastructure operations, and multiobjective optimization problems. Such applications may provide great opportunities in decision making and engineering management.
JSO has been hybridized with other recently developed algorithms, such as the proactive and reactive defragmentation algorithm (PDRFA), the heap-based optimizer (HBO) and the convolutional neural network (CNN), to improve its performance and to optimize the hyper-parameters in machine and deep learning methods. However, JSO has not yet been hybridized with other optimization algorithms such as particle swarm optimization (PSO) or the artificial bee colony (ABC) algorithm, or with traditional techniques, such as dynamic programming, or other techniques, such as adaptive reinforcement learning.
JSO has been shown to be efficient in solving numerous standard benchmark problems and real-world constrained and unconstrained applications. JSO has a good population utilization rate and maintains a favorable balance between global and local searches. However, the exploration/exploitation ability and convergence speed of the algorithm can be improved. Accordingly, researchers have developed numerous enhanced versions of JSO by upgrading its original mechanisms with artificial intelligent agents. Numerous variants or enhancements have been made by developing theoretical supplements to achieve diverse objectives.
The preceding sections of this study reported on these refinements, which have concerned the updating mechanisms in the diversity of population, the boosting agents of exploration and exploitation, improvements in the distribution coefficient for global search, the time control mechanism, and the handling of boundary conditions. The improvements include the orthogonal learning JSO (OLJSO) with an orthogonal learning strategy, the premature convergence strategy (PCS), archives of good old, solutions (positions), dynamic diversity control, and the quantum-based update rule.
This section compares jellyfish search optimizer (JSO) with the different variants and hybrids of JSO that are applied in global optimization and real-world applications. The key features of each algorithm, the problems that are solved by it and its performance are considered. Table 4 exhibits a comparative analysis of variants of JSO. The JSO variants are comparable to, or better than, the classical JSO algorithm. Notably, the standard JSO shows better performance than some hybrid optimization algorithms, such as the proactive and reactive defragmentation-JSO algorithm (PRDA-JSO) and the spectrum defragmentation algorithm (SDA).
Research on JSO was reviewed. The underlying inspiration for JSO, its population initialization and boundary conditions, mathematical formulations of ocean currents and jellyfish swarms, time control mechanism, advantages and disadvantages, variants, and applications were thoroughly discussed. Analytical findings reveal that JSO is used in various disciplines, including power systems and energy generation, communication and networking, civil and construction engineering, prediction and classification, and fine-tuning of artificial intelligence.
Experimental research has established that JSO outperforms many nature-inspired algorithms, such as PSO, DE, AEO, MRFO, SCA, WOA, TLBO, ABC, and GA, in a variety of ways³⁹. Some variants or enhancements have been made by considering the diversity of population, the updating mechanisms in exploration- or exploitation-oriented boosting, the population distribution, the time control mechanism, and the handling of boundary conditions.
Future work on JSO should consider the following: (1) Self-adaption: adaptive or self-adaptive algorithms are those that can self-tune their algorithm-specific and common control parameters. The algorithm-specific parameters in JSO include the number of iterations, population size, spatial distribution coefficients, and motion coefficients. Most relevant research has used trial-and-error experiments or sensitivity analyses to evaluate these algorithmic parameters, which are time-consuming. Accordingly, an adaptive version of JSO with the capacity to self-tune its algorithm-specific parameters is required. (2) Hybridization: in general, hybrid algorithms outperform stand-alone algorithms. Therefore, the hybridization of JSO with other conventional algorithms such as GA, PSO, ABE, DE, dynamic programming, and adaptive reinforcement learning, is a potential avenue for research. (3) Applications: JSO is currently utilized to solve a subset of complex optimization problems. More attempts to solve complicated optimization problems in the real world using JSO and its variants should be made to demonstrate the generalizability of JSO.
JSO yields competitive solutions to other complicated problems. Numerous ongoing studies have focused on minimizing the overall maintenance cost of buildings and roads, scheduling in civil and industrial engineering, and investment portfolio optimization problems in finance with limited constraints. JSO can be extended by hybridization in ways that depend on the problem to be solved. The findings in this review can therefore be used to promote future advances by considering the applications, advantages, and improvements of similar metaheuristic optimization algorithms thus developed. This work supports the theoretical framework of an enhanced version of JSO or other newly proposed optimizer that improves upon present and the original variants. It will also motivate researchers to develop novel bio-inspired metaheuristic optimization algorithms with tradeoff modifications.
The data that support this study are available from the corresponding author upon reasonable request.
Three-step in jellyfish search optimizer
Artificial bee colony
Adaptive neuro-fuzzy inference system
Artificial ecosystem optimizer
Amalgamated heap-based and jellyfish optimizer
Artificial hummingbird optimization technique
Artificial intelligence
Antlion optimization algorithm
Archimedes optimization algorithm
Adjustment strategy function
African vultures optimization algorithm
Backtracking search algorithm
Chaotic active swarm method-based jellyfish search optimizer
Capacitor bank
Chaos game optimization
Combined heat and power economic dispatch
Comprehensive learning marine predator algorithm
Convolutional neural network
Chimp optimization algorithm
Crisscross optimization and arithmetic optimization algorithm
Dynamic butterfly optimization algorithm
Direct current to direct current
Double diode model
Differential evolution
Distributed generation
Deep generative adversarial neural network
Dynamic group optimization
Dwarf mongoose optimization algorithm
Deep neural network
Distribution system reconfiguration
Discrete wavelet transform
Evolutionary local search
Equilibrium optimizer algorithm
Enhanced sparrow search algorithm
Enhanced shuffled shepherd optimization algorithm
Flexible alternating current transmission system
Fuzzy adaptive jellyfish search optimizer
Forensic-based investigation algorithm
Fuel consumption capacity vehicle routing problem
Finite element method
Fractional-order modified Harris hawk optimizer
Fractional-order and Gaussian mutation mechanism jellyfish search optimizer
Flower pollination algorithm
Flower pollination extreme learning machine
Fiber-reinforced soil
Genetic algorithm
Gradient-based optimizer
Global maximum power point
Giza pyramids construction
Grid search optimization
Gorilla troops optimizer
Group teaching optimization algorithm
Grey wolf optimizer
Heuristic-based approaches fragmentation aware
Heap-based and jellyfish search optimizer
Heap-based optimizer
Hunger games search
Harris hawk extreme learning machine
Hybrid-jellyfish
Harmonics multilevel inverter
Hybrid marine predator algorithm
High-performance cuckoo search algorithm
Hybrid salp swarm algorithm with teaching–learning-based optimization
Improved chimp optimization algorithm
Improved jellyfish search optimizer
Improved jellyfish search optimizer and support vector regression
Internet of things
Improved particle swarm optimization
Jellyfish search optimizer
Jellyfish search optimizer-XGBoost
Learning-automata
Low-frequency oscillations
Lightning search algorithm
Least squares support vector regression
Multi-dimensional optimal power flow
Moth flame optimization
Modified jellyfish search optimizer
Modified manta ray foraging optimization algorithm
Mayfly optimization algorithm
Multi-objective ant lion optimizer
Multi-objective grey wolf optimization
Multi-objective jellyfish search
Multi-objective particle swarm optimization
Multi-objective quasi-reflected jellyfish search optimizer
Marine predators algorithm
Maximum power point track
Manta ray foraging optimization
Orthogonal learning design
Orthogonal learning jellyfish search optimizer
Optimal power flow
Premature convergence strategy
Polymer exchange membrane fuel cells
Plant microbial fuel cell
Proactive and reactive defragmentation
Proactive and reactive defragmentation algorithm
Particle swarm optimization
Partitioned step particle swarm optimization
Photovoltaic
Quantum jellyfish search optimizer
Radial distribution system
Random vector functional link
Self-adaptive jellyfish search optimizer
Smell agent optimization
Shunt capacitor
Sine cosine algorithm
Spectrum defragmentation algorithm
Single diode model
Slime mould algorithm
Starling murmuration optimizer
Seagull optimization algorithm
Single objective jellyfish search
Symbiotic organisms search
Symbiotic organisms search-XGBoost
Solar photovoltaic generator
Stacking system
Sparrow search algorithm
Solar thermoelectric air-conditioning system
Static var compensator
Total harmonic distortion
Teaching-learning-based optimization
Three-learning strategy particle swarm optimization
Tabu search
Tunicate swarm algorithm
West delta region system
Weighted-feature least squares support vector regression
Wild horse optimization algorithm
Whale optimization algorithm
Wind power generator
Wireless sensor network
War strategy optimization algorithm
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The authors would like to thank the National Science and Technology Council, Taiwan, for financially supporting this research under the Grant No. 110-2221-E-011-080-MY3.
National Taiwan University of Science and Technology, Taipei, Taiwan
Jui-Sheng Chou & Asmare Molla
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DOI: https://doi.org/10.1038/s41598-022-23121-z
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In Whitefish, a new world is emerging for tabletop gamers, which for Jeff Irving means his longtime fantasy is close to becoming a reality
For nearly 30 years, the world of Vrahode has lived in the heart and mind of Jeff Irving. But for the last three years, map by map, piece by piece, card by card, and rule by rule, the fantasy world and gaming system he has created, and has long held dear, is emerging into a fully fledged tabletop adventure board game.
Over the course of his adult life, Irving has owned and operated a computer and computer game business, and he has worked extensively in the marketing industry. He’s also the founder of Weathervane Games, a gaming company whose offices consist of a desk and a table just off the kitchen of his Whitefish home, and which is sustained by a remotely connected group of contracted artists, designers and other collaborators spread out across the globe, with contributors in the United States, Europe, South America and Australia.
In explaining the world of Vrahode, as well as what sets it apart from other fantasy worlds, Irving describes it as a departure from the fantasy realms that typically draw their inspiration from medieval Europe. It’s influenced in part by premodern African civilizations and cultures and doesn’t include typical species like dwarves, elves and humans. Instead, there are races like the tree-like Toreln, mushroom-like Mynoc, centaur-like Cautuuk, and reptilian Drelrhune. There is no magic in Vrahode, but there is a similar power players can wield called ruhl.
Irving grew up in Indiana, and at a young age was introduced to the roleplaying game Dungeons and Dragons by a friend. He was skeptical at first, especially considering that the game as they played it mostly relied on pencil, paper and imagination. It was his first introduction to the world of fantasy, and it sparked a lifelong fascination with the genre.
He was already a fan of more traditional games by Milton Bradley or Monopoly creators the Parker Brothers, so the merging of his passion for fantasy and games was a natural development. In college at Ball State University he started to envision Vrahode, and then in 1990, while recovering from double pneumonia, Irving wrote what he called a sociological text for the primary races that inhabit the world of Vrahode. It came out to about 250 pages.“Is this a matrilineal descent pattern? Is it patrilineal? What are their birth rituals, what are their death rituals? Do they interact with other races? What are those interactions like? Do they barter, do they trade, what are their goods, what makes them tick? And their magic, if this race exists within the swamps, well then you would expect their magic to be kind of based around water. So it was kind of, how do you do sociology for a magical race?” Irving said, smiling just before breaking out into laughter. “It was so fun.”
 The deep dive was a way for Irving to bring in another one of his passions: anthropology. He said when he first learned about tribes in the Amazon that had never had contact with the outside world it was unlike anything he’d ever considered before, and it set off his imagination.
 Irving has written in traditional forms such as fiction and poetry, and at first thought of Vrahode as something that could be developed into a fantasy book. Eventually, though, he decided that his tendency to become intensely preoccupied with each word and detail transformed the act of writing into something he didn’t particularly enjoy, which helped send him down the path of conceptualizing Vrahode as a game. He’s brought on Virginia-based writer Shawn Dressler as the lead writer and game design consultant to help shoulder the workload for writing the game book which guides characters through Vrahode.
 An early iteration of Vrahode was contained in Irving’s description of a “war game,” which is a genre of tabletop game in which players battle each other with armies. It didn’t feel right, however, so he started developing an adventure-style version.
Life eventually got in the way of the creative process, and at one point Irving said he was struggling with depression. He left the game untouched for almost 13 years, but it never fully left him. About three years ago, he decided to recommit himself in earnest, turning his fantasy of completing the game into a reality.
According to Irving’s estimates, he’s invested tens of thousands of dollars into the game at this point.
 “I don’t care if I see anything back out of it. What I want to do is share this with people, because it’s gonna be fun. And I want to be able to sit down at a table with people and play in a world that’s been in my head since flipping 1990,” Irving said.
While Irving isn’t preoccupied with profits at this point, he’s also aware that the board game industry is expected to bring in $3.1 billion in revenue in 2022, according to the marketing website Statista.
Irving is planning for Vrahode to consist of a core game called “Vrahode—The Calteeryn Ascension,” and then three expansions. Calteeryn is a reference to a prophesied hero critical to the Vrahode storyline. A group of players will pick one member to be the Calteeryn, which comes with some added perks. The downside, as Irving explained, is that the various monsters of Vrahode tend to direct their hostility first and foremost at the Calteeryn. Vrahode is meant to have variable modes of play so that people can play in a range of settings, including by themselves or in groups of up to six people. The game will also have different modes of difficulty, and the Vrahode Game System under which the game operates will give players a chance to further create and experiment if they want to move beyond some of the established storylines in the game.
An elaborately designed map serves as the primary game board, but during various encounters and battles, players will be directed to separate game boards that enlarge the terrain to represent settings like a desert, a marsh, a tundra, a mountainside, or a dungeon. Players each have a small plastic card tray, which holds a card for the hero they select or create, as well as cards for items, abilities and other tokens to track things like “ruhl.” Dice rolls can dictate the success of some player actions in combat situations.
One aspect of the game that especially excites Irving is what he’s described as a one-of-a-kind game element dubbed the Harbinger Gaming Terrain System. That system will allow players who are exploring dungeons on one of the detailed breakout boards to create 3D spaces using a system of interlocking tiles and other pieces that can be assembled to build up the board vertically.
There’s no “dungeon master” type player who is calling the shots for the various enemies that players face. Instead, Irving has worked on developing a kind of airtight rule system that dictates how enemies behave during encounters, which will be up to players to abide by. The rule system is the most difficult part of creating a game, Irving said. The discovery of a rule that isn’t compatible with gameplay can create an effect that Irving refers to as “breaking the game,” setting off a domino effect that can throw off the game’s design and symmetry. Ensuring that the storyline, side quests, battle system, item system and other core components of the game function correctly means trying to play out as many scenarios as possible until their conclusion.
“What we’ve done on this system, as complex as it looks, is every time we’ve had a choice for realism, or simplicity, we’ve gone the simplicity way. We want it to play fast. We want it to be fun, we want it to be accessible, we want it to have a very, very small learning curve,” Irving said. “We want young kids to play it, we want families to play it. We want content creators to play within our system, not something else.”
The complete game has 1,425 cards. In addition to employing artists from countries like Italy and Brazil, some of the environmental game art comes from the work of Whitefish artist Colt Idol.  Ornate figurines representing various creatures also inhabit the game world, prototypes of which are currently 3D printed, but will eventually be manufactured through an injection-mold process.
In the coming months, Irving will be playtesting the game by himself before opening it up to external playtesting, at which point he’ll offer free food and prizes at local gaming stores in exchange for people volunteering to play the game while he takes notes on gameplay and player feedback. A game trailer is expected to come out in the summer of 2023, and then a crowdfunding effort will start next fall. The plan right now is to start manufacturing the game and its expansions in January 2024, and to get the game in players’ hands by that spring.
 “It’s plenty violent, but it also has a heart,” Irving said. “There’s a message to this game in that you have to kill things that are part of the natural world. And the heroes have to have a reckoning for that, and they do. And that’s what we wanted to do in the story is say hey, you’ve had to sacrifice a lot of wonderful things to do what you had to do to save the world, and now you have to revisit where your moral compass is. And so, we do. We give the game a heart.”
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In Whitefish, a new world is emerging for tabletop gamers, which for Jeff Irving means his longtime fantasy is close to becoming a reality
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NOTICE UNDER
FICTITIOUS NAME STATUTE
TO
WHOM IT MAY
CONCERN
Notice is hereby
given that the undersigned, pursuant to the
“Fictitious Name
Statute”, Chapter, 865.09, Florida Statutes will register with the Division of Corporations,
Department of
State, State of Florida, upon receipt of proof of the publication of this,
notice, the fictitious name to-wit:
The Joint
Chiropractic
Under which the
below named party/parties will engage in business at:
800 Formosa
Avenue
Winter Park, FL 32789
That the
party/parties
interested in
said business enterprise is/are as follows:
LG Chiro Town
Park,LLC
Dated at
Orlando, Orange County,Florida, November 2, 2022
November 11, 2022
 
NOTICE UNDER
FICTITIOUS NAME STATUTE TO
WHOM IT MAY
CONCERN
Notice is hereby
given that the undersigned, pursuant to the
“Fictitious Name
Statute”, Chapter, 865.09, Florida Statutes will register with the Division of
Corporations,
Department of
State, State of Florida, upon receipt of proof of the publication of this,
notice, the fictitious name to-wit:
The Joint
Chiropractic
Under which the
below named party/parties will engage in business at:
800 Formosa
Avenue
Winter Park, FL 32789
That the
party/parties
interested in
said business enterprise is/are as follows:
LG Chiro Willa
Springs,LLC
Dated at
Orlando, Orange County,Florida, November 2, 2022
November 11, 2022
 
GENERAL
CONTRACTOR NEEDED
Primrose Center
is seeking a General Contractor to provide Commercial renovations to a 1600sqft
wooden structure on campus. Lead-based paint found, see bid package.
Opening
Date:  November 4, 2022
Closing
Date:  November 14, 2022
Mandatory
Pre-Bid Meeting:  November 11, 2022 1:00
pm
We anticipate
this to be a 2-3 month project with a completion date no later than February
28, 2023.
To obtain a hard
copy of the Invitation for Bid (IFB) please contact Brenda Saal at:  Primrose Center, 2733 South Ferncreek Ave.,
Orlando, FL 32806 
[email protected]
November 11, 2022
 
IN THE COUNTY
COURT OF THE 7TH JUDICIAL CIRCUIT IN AND FOR VOLUSIA COUNTY, FLORIDA
CASE NO.: 2022
15872 CODL
BRIDGECREST
ACCEPTANCE CORP.,
Plaintiff,
v.
KARI LYNN DEWEY,
et al,
Defendants.
/
NOTICE OF ACTION
To the following
Defendant(s):
KARI LYNN DEWEY
(Last Known
Address: 142 Grace Street, Deland, FL 32724)
YOU ARE NOTIFIED
that an action for breach of contract and to recover personal property, the:
2015 KIA OPTIMA
WITH VIN KNAGM4A7XF5581120
has been filed
against you and you are required to serve a copy of your written defenses, if
any, to it, on Ghidotti| Berger LLP, Attorney for Plaintiff, whose address is
1031 North Miami Beach Boulevard, North Miami Beach, FL 33162 on or before
December 12, 2022, a date which is within thirty to sixty days after the first
publication of this Notice in the Orlando Business Journal and file the
original with the Clerk of this Court either before service on Plaintiff’s
attorney or immediately thereafter; otherwise a default will be entered against
you for the relief demanded in the complaint.
This notice is
provided pursuant to Administrative Order No. 2010-08.
If you are a
person with a disability who needs an accommodation in order to access court
facilities or participate in a court proceeding, you are entitled, at no cost
to you, to the provision of certain assistance. To request such an
accommodation, please contact Court Administration in advance of the date the
service is needed: Court Administration, 125 E. Orange Ave., Ste. 300, Daytona
Beach, FL 32114; (386) 257-6096. Hearing or voice impaired, please call 1 (800)
955-8770.
WITNESS my hand
and the seal of this Court this 28th day of October, 2022.
LAURA E. ROTH
As Clerk of the Court
By /s/ Jennifer
M. Hamilton
As Deputy Clerk
November 11, 2022
November 18, 2022
IN THE CIRCUIT
COURT OF THE NINTH JUDICIAL CIRCUIT, IN AND FOR ORANGE COUNTY, FLORIDA
Case No:
2022-DR-007612-O
IN THE MATTER OF
THE ADOPTION OF:
GIOVANNI XAVIER
GOBY
Adoptee.
_________/
NOTICE OF ACTION
FOR ADULT ADOPTION
TO: PATRICK
ANTOINE JACQUES CADET
7 BENNETT LANE
PALM COAST, FL 32137
YOU ARE HEREBY
NOTIFIED that a Petition for Adult Adoption has been filed in Orange County
regarding the above-named adult.  If you
wish to be notified and/or attend the final adoption hearing, please contact
the named attorney listed below or reach out to the Division 29 Judicial
Assistant, Lizandra Montero, at [email protected] or (407) 836-0477 to provide
your contact information.
BY:/s/Bethany C.
Szewczyk
BETHANY C. SZEWCZYK, ESQ.
Attorney for Petitioner
Florida Bar No. 91673
1060 Woodcock Road
Orlando, FL 32803
Phone: (321) 234.5288
Email: [email protected]
November 11, 2022
November 18, 2022
November 25, 2022
December 2, 2022
Pursuant to
Section 121.055 Florida Statues (as amended by the 1993 Florida Legislature),
the Orange County Property Appraiser Notice of Action
The Orange
County Property Appraiser provides public notice of the intent
to include the
following position in the
Florida
Retirement System’s Senior Management Service Class.
* Chief People
Officer
Additional
Information may be obtained by writing to the
Orange County
Property Appraiser
200 S. Orange
Ave., Suite 1700, Orlando, FL 32801.
November 11, 2022
November 18, 2022
IN THE CIRCUIT
COURT OF THE 5TH JUDICIAL CIRCUIT IN AND FOR LAKE COUNTY, FLORIDA
CASE NO.:
352022CA001679AXXXXX
LOANDEPOT.COM,
LLC,
Plaintiff,
v.
EDWIN J. SEDA;
ET AL,
Defendants.
/
NOTICE OF ACTION
To the following
Defendant(s):
UNKNOWN SPOUSE
OF EDWIN J. SEDA
(Last Known
Address: 302 Lily Pad Lane, Eustis, FL 32726)
YOU ARE NOTIFIED
that an action to foreclose based on boundaries established by acquiescence, on
the following described property:
THE FOLLOWING
DESCRIBED LAND, SITUATE, LYING AND BEING IN LAKE COUNTY, FLORIDA TO-WIT:
LOT 55, CRICKET
LAKE VILLAGE SECONDS ADDITION, ACCORDING TO THE MAP OR PLAT THEREOF, AS
RECORDED IN PLAT BOOK 30, PAGE 66, OF THE PUBLIC RECORDS OF LAKE COUNTY,
FLORIDA.
PROPERTY
ADDRESS: 302 LILY PAD LANE, EUSTIS, FL 32726
has been filed
against you and you are required to serve a copy of your written defenses, if
any, to it, on Ghidotti Berger LLP, Attorney for Plaintiff, whose address is
1031 North Miami Beach Boulevard, North Miami Beach, FL 33162 on or before a
date which is within thirty (30) days after the first publication of this
Notice in the Orlando Business Journal and file the original with the Clerk of
this Court either before service on Plaintiff’s attorney or immediately
thereafter; otherwise a default will be entered against you for the relief demanded
in the complaint.
This notice is
provided pursuant to Administrative Order No. 2010-08.
If you are a
person with a disability who needs any accommodation in order to participate in
a proceeding, you are entitled, at no cost to you, to the provision of certain
assistance. Please contact the ADA Coordinator at the Office of the Trial Court
Administrator, Lake County Courthouse, P.O Box 7800/550 W. Main Street,
Tavares, Florida 32778, Telephone (352) 742-4221, at least 7 days before your
scheduled court appearance, or immediately upon receiving a notification if the
time before the scheduled appearance is less than 7 days; if you are hearing or
voice impaired, call 711.
WITNESS my hand
and the seal of this Court this 26th day of October, 2022.
GARY J. COONEY
As Clerk of the Court
By /s/ D.
Latourelle
As Deputy Clerk
November 11, 2022
November 18, 2022
IN THE CIRCUIT
COURT OF THE 7TH JUDICIAL CIRCUIT IN AND FOR VOLUSIA COUNTY, FLORIDA
CASE NO.: 2022
31185 CICI
U.S. BANK TRUST
NATIONAL ASSOCIATION AS TRUSTEE OF CABANA SERIES III TRUST,
Plaintiff,
v.
MECHILLE THOMAS;
MICHAEL W. THOMAS; et al,
Defendants.
/
NOTICE OF ACTION
To the following Defendant(s):
UNKNOWN SPOUSE
OF MECHILLE THOMAS
(Last Known
Address: 6230 Cranberry Dr., Port Orange, FL 32127)
UNKNOWN SPOUSE
OF MICHAEL W. THOMAS
(Last Known
Address: 6230 Cranberry Dr., Port Orange, FL 32127)
YOU ARE NOTIFIED
that an action to foreclose based on boundaries established by acquiescence, on
the following described property:
THE FOLLOWING
DESCRIBED LAND, SITUATE, LYING AND BEING IN THE COUNTY OF VOLUSIA, FLORIDA:
LOT 16,
RIVERWOOD P.U.D., PHASE VI, ACCORDING TO THE PLAT THEREOF RECORDED IN MAP BOOK
41, PAGE 31, OF THE PUBLIC RECORDS OF VOLUSIA COUNTY, FLORIDA AND A PORTION OF
LOT 18, RIVERWOOD P.U.D. , PHASE VI, ACCORDING TO THE PLAT THEREOF RECORDED IN
MAP BOOK 44, PAGE 31 OF THE PUBLIC RECORDS OF VOLUSIA COUNTY, FLORIDA, BEING
MORE PARTICULARLY DESCRIBED AS FOLLOWS: BEGINNING AT THE SOUTHEAST CORNER OF
SAID LOT 18, RUN S87∞31`17”W, ALONG THE SOUTH LINE OF SAID LOT 18, A DISTANCE
OF 46.74 FEET TO THE NORTHWEST CORNER OF LOT 16 SAID RIVERWOOD P.U.D., PHASE
VI, THENCE N03∞51`35”W, ALONG A NORTHERLY EXTENSION OF THE WEST LINE OF SAID
LOT 16, A DISTANCE OF 46.48 FEET TO A POINT ON THE EAST LINE OF SAID LOT 18,
THENCE S58∞23`34” E, ALONG THE SAID EAST LINE, A DISTANCE OF 54.38 FEET TO THE
POINT OF BEGINNING.
PROPERTY
ADDRESS: 6230 CRANBERRY DR, PORT ORANGE, FL 32127
has been filed
against you and you are required to serve a copy of your written defenses, if
any, to it, on Ghidotti| Berger LLP, Attorney for Plaintiff, whose address is
1031 North Miami Beach Boulevard, North Miami Beach, FL 33162 on or before
December 12, 2022, a date which is within thirty (30) days after the first
publication of this Notice in the Orlando Business Journal and file the
original with the Clerk of this Court either before service on Plaintiff’s
attorney or immediately thereafter; otherwise a default will be entered against
you for the relief demanded in the complaint.
This notice is
provided pursuant to Administrative Order No. 2010-08.
If you are a
person with a disability who needs an accommodation in order to access court
facilities or participate in a court proceeding, you are entitled, at no cost
to you, to the provision of certain assistance. To request such an
accommodation, please contact Court Administration in advance of the date the
service is needed: Court Administration, 125 E. Orange Ave., Ste. 300, Daytona
Beach, FL 32114; (386) 257-6096. Hearing or voice impaired, please call 1 (800)
955-8770.
WITNESS my hand
and the seal of this Court this 26th day of October, 2022.
LAURA E. ROTH
As Clerk of the Court
By /s/ Jennifer
M. Hamilton
As Deputy Clerk
November 11, 2022
November 18, 2022
NOTICE OF
ADOPTION
PETITION TO
VACATE # 21-02-006
WHEREAS,
pursuant to procedures adopted by the Board of County Commissioners, a petition
was filed with the Board to vacate that certain portion of a 30 foot wide by
158 foot long, open and non-maintained right-of-way known as Wakulla Street,
containing approximately 4,740 square feet in Orange County, Florida (the legal
property description is on file in the office of the Comptroller Clerk of the
Board of County Commissioners).
WHEREAS, notice
of a public hearing before the Board of County Commissioners on October 25,
2022, was published in the Orlando Sentinel, a newspaper of general circulation
in Orange County, Florida, one time at least two weeks prior to the date for
the hearing; and
WHEREAS, the
Board finds that the vacating of that certain portion of a 30 foot wide by 158
foot long, open and non-maintained right-of-way known as Wakulla Street,
containing approximately 4,740 square feet will not operate to the detriment of
Orange County or the public.
THEREFORE, BE IT
RESOLVED BY THE BOARD OF COUNTY COMMISSIONERS OF ORANGE COUNTY: The county
road, right-of-way, easement, or park described above is vacated as of this
date and Orange County renounces any rights in it.
RESOLVED THIS
25TH DAY OF OCTOBER 2022.
Phil Diamond,
County Comptroller
As Clerk of the Board of County Commissioners
Orange County, Florida
November 11, 2022
 
IN THE CIRCUIT
COURT OF THE FIFTH JUDICIAL CIRCUIT IN AND FOR LAKE COUNTY, FLORIDA
CIVIL ACTION
CASE NO.: 2018-CA-002170
DIVISION:
U.S. BANK
NATIONAL ASSOCIATION,
Plaintiff,
vs.
JIMMY LAMAR
CARDWELL, et al,
Defendant(s).
____________/
NOTICE OF
RESCHEDULED SALE
NOTICE IS HEREBY
GIVEN Pursuant to an Order Rescheduling Foreclosure Sale dated October 12,
2022, and entered in Case No. 2018-CA-002170 of the Circuit Court of the Fifth
Judicial Circuit in and for Lake County, Florida in which U.S. Bank National
Association, is the Plaintiff and Jimmy Lamar Cardwell, Florida Housing Finance
Corporation, Groves at Baytree Homeowners Association, Inc., Unknown Party #1
n/k/a Alton Cardwell, Unknown Party #2 n/k/a Jimmy Cardwell, Jr., are
defendants, the Lake County Clerk of the Circuit Court will sell to the highest
and best bidder for cash in/on the first floor lobby near the information desk
in the Lake County Courthouse, 550 West Main Street, Tavares, FL  32778, Lake County, Florida at 11:00AM on the
29th day of November, 2022, the following described property as set forth in
said Final Judgment of Foreclosure:
LOT 217, GROVES
AT BAYTREE, PHASE 4, ACCORDING TO THE PLAT THEREOF, RECORDED IN PLAT BOOK 59,
PAGE(S) 80 THROUGH 83, INCLUSIVE, OF THE PUBLIC RECORDS OF LAKE COUNTY,
FLORIDA.
A/K/A 591 SIESTA
KEY AVENUE, TAVARES, FL 32778
Any person
claiming an interest in the surplus from the sale, if any, other than the
property owner as of the date of the Lis Pendens must file a claim before the
Clerk reports the surplus as unclaimed.
Dated in Lake
County, Florida this 1st day of November, 2022.
Gary J. Cooney
Clerk of the Circuit Court
Lake County, Florida
By: /s/ K.
Linares
Deputy Clerk
(CIRCUIT COURT SEAL)
Albertelli Law
Attorney for Plaintiff
P.O. Box 23028
Tampa, FL  33623
(813) 221-4743
CT – 18-025440
If you are a
person with a disability who needs any accommodation in order to participate in
this proceeding, you are entitled, at no cost to you, to the provision of
certain assistance. Please contact the ADA Coordinator at the Office of the
Trial Court Administrator, Lake County Courthouse, P.O. Box 7800/550 W. Main Street,
Tavares, Florida 32778, Telephone (352) 742-4221, at least 7 days before your
scheduled court appearance, or immediately upon receiving this notification if
the time before the scheduled appearance is less than 7 days; if you are
hearing or voice impaired, call 711 or (352) 742-3890.
November 11, 2022
November 18, 2022
 
IN THE CIRCUIT
COURT OF THE EIGHTEENTH JUDICIAL CIRCUIT IN AND FOR SEMINOLE COUNTY, FLORIDA
CIVIL ACTION
CASE NO.:
59-2022-CA-000131
DIVISION:
NATIONSTAR
MORTGAGE LLC D/B/A CHAMPION MORTGAGE COMPANY,
Plaintiff,
vs.
THE UNKNOWN
HEIRS, DEVISEES, GRANTEES, ASSIGNEES, LIENORS, CREDITORS, TRUSTEES, OR OTHER
CLAIMANTS CLAIMING BY, THROUGH, UNDER, OR AGAINST, BILLIE D. MORGAN, DECEASED,
et al,
Defendant(s).
___________/
NOTICE OF SALE
PURSUANT TO CHAPTER 45
NOTICE IS HEREBY
GIVEN Pursuant to a Final Judgment of Foreclosure dated September 27, 2022, and
entered in Case No. 59-2022-CA-000131 of the Circuit Court of the Eighteenth
Judicial Circuit in and for Seminole County, Florida in which  Nationstar Mortgage LLC d/b/a Champion
Mortgage Company, is the Plaintiff and The Unknown Heirs, Devisees, Grantees,
Assignees, Lienors, Creditors, Trustees, or other Claimants claiming by,
through, under, or against, Billie D. Morgan, deceased, United States of
America Acting through Secretary of Housing and Urban Development, Daniel
Morgan, David Michael Morgan aka Mike Morgan, Sharon Robertson aka Elaine
Morgan Robertson, Evelyn Diane Davies aka Diane Davies, are defendants, the
Seminole County Clerk of the Circuit Court will sell to the highest and best
bidder for cash  in/on online at online
at https://www.seminole.realforeclosure.com, Seminole County, Florida at
11:00AM on the November 29, 2022 the following described property as set forth
in said Final Judgment of Foreclosure:
LOT 25, BEAR
LAKE HILLS, ACCORDING TO THE PLAT THEREOF, AS RECORDED IN PLAT BOOK 13, PAGE 37
OF THE PUBLIC RECORDS OF SEMINOLE COUNTY, FLORIDA.
A/K/A 3901 ANNA
DRIVE APOPKA FL 32703
Any person
claiming an interest in the surplus from the sale, if any, other than the
property owner as of the date of the Lis Pendens must file a claim before the
Clerk reports the surplus as unclaimed.
CERTIFICATE OF
SERVICE
I HEREBY CERTIFY
that a true and correct copy of the foregoing has also been furnished to all
parties on the attached service list by mail or eService.
Dated this 3rd
day of November, 2022.
ALBERTELLI LAW
P. O. Box 23028
Tampa, FL 33623
Tel: (813) 221-4743
Fax: (813) 221-9171
eService: [email protected]
By:_/s/_Justin
Ritchie
Florida Bar #106621
Justin Ritchie, Esq.
CT – 21-007102
If you are a
person with a disability who needs any accommodation in order to participate in
this proceeding, you are entitled, at no cost to you, to the provision of
certain assistance. Please contact the ADA Coordinator, Court Administration,
301 North Park Avenue, Sanford, FL 32771, telephone number (407) 665-4227 at
least 7 days before your scheduled court appearance, or immediately upon
receiving this notification if the time before the scheduled appearance is less
than 7 days; if you are hearing impaired, call 711.
November 11, 2022
November 18, 2022
 
Notice is hereby
given that pursuant to the states self-storage facility act, Morningstar
Storage, located at 4334 Edgewater Drive, Orlando, FL 32804, 407-972-1908 will
hold an online public auction of the following stored property being sold to
satisfy a landlord’s lien at www.storageauctions.com. The sale will be final on
11-30-2022 at 9:00AM.
Dames,
Lakima  2024
Lewis,
Nikita  2212
Notice is hereby
given that pursuant to the states self-storage facility act, Morningstar
Storage, located at 2201 Golf Club Dr, DeLand, FL 32724, 386-337-4075, will
hold an online public auction of the following stored property being sold to
satisfy a landlord’s lien at www.storageauctions. com. The sale will be final
on 11-30-2022 At 9:00 a.m.
Sarondrelyn
Allen 3307
Falana Johnson
2104
Ken Short3713
Notice hereby
given that pursuant to the to the state self- storage Facility act, Morningstar
storage of Eustis , located at 19400 state Rd 44 Eustis Fl 352-388-1940 will
hold an online public auction of the following stored property being sold to
satisfy a landlord’s lien at www.storageauctions.com.The sale will be finial on
11/30/2022 at 9:00 AM.
Whitely Robert
unit 1171
Kerry Simmons
unit 1530
Notice is hereby
given that pursuant to the states self-storage act, Morningstar Storage,
located at 9700 South US Hwy 17-92, Maitland, FL 32751, (407) 986-4018, will
hold an online public auction of the following stored property being sold to
satisfy a landlord’s lien at www.storageauctions.com. The sale will be final on
11/30/2022 at 9:00 AM.
Anna Harrison,
5200
Gabriella
Morales-Otero, 2410
Notice is hereby
given that pursuant to the states self-storage facility act, Morningstar
Storage, located at 1600 Sunlife Path, Orlando, FL 32809 321-415-7939 will hold
an online public auction of the following stored property being sold to satisfy
a landlord’s lien at www.storageauctions.com. The sale will be final on
11-30-2022 at 9:00AM.
3056  Ryan Patrick Culley
3327  Angela Kay Caldwell
102728  Anas Aldamaji
A127  Wilson Valenzuela
B102  Joshua Martinez
B110. Shirley
Ann Martinez
Notice is hereby
given that pursuant to the states self-storage act, Morningstar Storage,
located at 1751 Ball Park Rd., Kissimmee, FL 34741, (407) 449-7795, will hold
an online public auction of the following stored property being sold to satisfy
a landlord’s lien at www.storageauctions.com. The sale will be final on
11/30/2022 at 9:00am.
Baez, Onix-  2208
Lugo, Alexander-
2037
Stone, Lisa-1332
Toledo Yeyez,
Rosangel- 3018
Ventura,
Michelle – 1012
November 11, 2022
November 18, 2022
 
NOTICE OF PUBLIC
SALE
To satisfy the
owner’s storage lien, PS Retail Sales, LLC will sell at public lien sale on
November 28, 2022, the personal property in the below-listed units, which may
include but are not limited to: household and personal items, office and other
equipment. The public sale of these items will begin at 09:30 AM and continue
until all units are sold. The lien sale is to be held at the online auction
website, www.storagetreasures.com, where indicated. For online lien sales, bids
will be accepted until 2 hours after the time of the sale specified.
PUBLIC STORAGE #
07029, 3150 N Hiawassee Rd, Hiawassee, FL 
32818, (407) 392-0863
Time: 09:30 AM
Sale to be held
at www.storagetreasures.com.
1602 – Britt,
Stephen; 1932 – Patterson, Cassandra; 2210 – Jackson, Malinda; 2429 – Rhynes,
Tjuana; 2520 – Cooper, Shearico; 2523 – Dugger, Antonio; 2615 – Francis,
Deahndre; 2714 – Andrea, Leanna; 2718 – Harmon, Takesha
PUBLIC STORAGE #
08326, 310 W Central Parkway, Altamonte Springs, FL  32714, (407) 487-4595
Time: 09:40 AM
Sale to be held
at www.storagetreasures.com.
0103 – Buckley,
Alicia; 0259 – Davis, Justin; 0412 – Cunningham, Tamica; 0421 – Oquendo, Nalia;
0448 – Welch, Ryan; 1026 – Hiebert, Brian; 2066 – Ricketts, Earl; 4019 –
Foster, Rebecca; 4067 – Belizaire, Tiffany; 5011 – matos, Thomas
PUBLIC STORAGE #
08705, 455 S Hunt Club Blvd, Apopka, FL 
32703, (407) 392-1542
Time: 09:50 AM
Sale to be held
at www.storagetreasures.com.
4014 – Hagen,
Dynasty; 5013 – Perdue, Shelly; 6208 – McDonald, Bobby; 6242 – Wynn, Patricia
PUBLIC STORAGE #
08732, 521 S State Road 434, Altamonte Springs, FL  32714, (407) 487-4750
Time: 10:00 AM
Sale to be held
at www.storagetreasures.com.
1021 – Harris,
Keara; 3015 – Van Middlesworth, Michele H; 5067 – Williams, Kizzie; 5103 –
Garcia, Andy; 5126 – Logue, Melanie; 5130 – Mims, Shanaya; 6075 – Torrence,
Sydney; 6131 – Diaz, Laura
PUBLIC STORAGE #
24107, 4100 John Young Parkway, Orlando, FL 
32804, (407) 930-4381
Time: 10:10 AM
Sale to be held
at www.storagetreasures.com.
B215 – Edwards,
Sheila; B224 – Groth Hair Studio Brown-Walker, Sharenee; B234 – Trevino,
Miranda; C305 – Farrel-Forstein, Randy; C315 – Koonce, Sandra; C315- Farmer,
Sandra  J; C315- Koonce, Sandra T; C315-
Farmer, Sandra; C316 – King, Alicia; C349 – Williams, Teressa; C355 – Dreamlife
Center Johnson, Stephen; D416 – Currie, Kimone; E005 – Mathis, Glenn; E076 –
Mathis, Deborah; F617 – Germain, Junior; F628 – SIMPSON, CHRISTOPHER; F629 –
Jackson, Theresa; F632 – Kirkland, Cedrea; F662 – Calixte, Bryan; G703 –
Agosto, Aliyah; G709 – Anderson, Wayne; G717 – Xavier, Michael; G732 – Nix,
Mikaela; H818 – Maurepas, Wibenson; J914 – Dreamlife Center Johnson, Steve;
J916 – Cohn, Robert; P010 – Wright, Jarick
PUBLIC STORAGE #
25780, 8255 Silver Star Rd, Orlando, FL 
32818, (321) 247-6799
Time: 10:20 AM
Sale to be held
at www.storagetreasures.com.
1012 – Hunter,
Terrance; 1103 – Hunter, Terrance; 1203 – Palin, Thomas; 1218 – Mitchell, Da
Shawn; 1302 – Lewis, Davarous; 1362 – Albury, Davardo; 1509 – Duvermont,
Gergens; 1611 – Galochkin, Nick; 1619 – Oquendo, Raynoldo; 1631 – Battle,
Corey; 2008 – Jean Julien, David; 2024 – Williams, Clarinda; 2030 – Rowell,
Alicia; 2034 – Morgan, Raymond; 2051 – Pierrissaint, Virgilet; 2173 – Anderson,
Karen; 2216 – Comacho, Maribel; 2607 – Fregis, Aubinson
PUBLIC STORAGE #
25813, 2308 N John Young Pkwy, Orlando, FL 
32804, (407) 603-0436
Time: 10:30 AM
Sale to be held
at www.storagetreasures.com.
A001 – Sanders,
Arroyo; B027A – Geraurd, Michael; B035A – bull, Wendyjo; B061 – Jones, Alice;
B074A – autman, darel; C010 – Meza, Daricus; C013 – Brewster, Shunathan; C020 –
Curry, Yara; C031 – White, Paul; C090 – 
CLJ Sales and Marketing Inc Jones, Cecil; D012 – Parker, Na’Keitha; D056
– Jackson, Wanda; D118 – Howard, Arabiaun; D124 – bingham, nick; E001 – Bryant,
Lacye; E006 – Cruz, Johnathan; E008 – Breedlove, Abinisha; E034 – Edwards,
Maya; E058 – Lespierre, Edith; F012 – Paulk, Elizabeth; F027 – Gale, Milton;
F055 – Jackson, Sandra; F092 – Williams, Theresa; F114 – Boyd, Latasha; G013 –
Allen, Camilla; G059 – Cadieux, Kesha; O016 – Young, James
PUBLIC STORAGE #
25814, 6770 Silver Star Rd, Orlando, FL 
32818, (407) 545-2394
Time: 10:40 AM
Sale to be held
at www.storagetreasures.com.
0021 – Bryant,
Valerie C; 0039 – Tanis, Tanis; 0043 – Chambers, Ragine; 0055 – Crouch, Shanta;
0075 – Crawford, Tamara; 0128 – Jones, Nykee; 0181 – Menard, Landry; 0191 –
White, Deijah; 0192 – Johnson, Shakia; 0213 – Brown, Shante; 0248 – owe,
Chauncey; 0252 – Edwards, Mae; 0259 – Longstreet, Charleen; 0265 – saintilus,
Phalonne; 0271 – Lacomb, Joanne; 0272 – Higgdon, lorenzo; 0276 – Peterson,
Stacey; 0316 – Cesar, James; 0334 – Gunter, Brandilyn; 0368 – Bernice, James;
0391 – Louis, Merline; 0392 – Carlton, Janice; 0436 – Jenkins, Ahjhane; 0451 –
Passmore, Samuel; 0462 – Bell, Jada; 0473 – Owens, Dexter; 0485 – Gaskins,
Christina; 0503 – Bell, Iesha; 0504 – Fair, Vivian; 0593 – Longstreet,
Charleen; 0595 – Dean, Keith; 0620 – allen, Chris; 0623 – Joseph, Monherlie;
0699 – Doston, Melinda; 0777 – Alvarez, Andres; 0813 – Chin, David; 0837 –
Dugger, Antonio; 0839 – Kimber, Kyle; 0875 – Singletary, Tony
PUBLIC STORAGE #
25895, 2800 W State Road 434 , Longwood, FL 
32779, (407) 392-0854
Time: 10:50 AM
Sale to be held
at www.storagetreasures.com.
0642 – veal,
Willie; 0675 – Moreau, Melissa; 0762 – Williams, Richard; 0770 – kerper,
Austin; 0823 – Barr, Teresa; 0869 – Smith, Joe; 0908 – Cherepanya, Stephen;
0944 – Piccolo, Debra
PUBLIC STORAGE #
28091, 2431 S Orange Blossom Trail, Apopka, FL 
32703, (407) 279-3958
Time: 11:00 AM
Sale to be held
at www.storagetreasures.com.
1031 – Duluc,
Katherine; 1037 – Desir, Laelda; 1142 – manning, Jay; 1164 – Calvin, Bria; 1170
– Sanchez, Daniel; 1172 – Joachin, Marc; 1284 – Ingram, Hodari; 1352 –
Robinson, Ivan; 1379 – Jackson, Kasha; B037 – Bernhagen, Marlisa; C003 –
Stuckie, Kathy; C018 – Dallas, Thomas; C033 – Delius, Jean; D090 – Kelly,
Tamicka; F012 – Miller, Ruby; F021 – James, Dwight; G002 – Tanner, Shameka
Johnson; NB05 – Heslop-Brown, Veneta; NC07 – Dutair, Claudette; P115 –
Marriott, Cana; T016- Cancel, Keila; T016- Charnonier, Abdiel; U032 – Vasquez,
Gabriel; U044 – Daniel, Bria; U046 – Huff, Brandon; V012 – Fuentes, Michael;
X009 – Meyers, Tasha
PUBLIC STORAGE #
25891, 108 W Main St, Apopka, FL  32703,
(407) 542-9698
Time: 11:10 AM
Sale to be held
at www.storagetreasures.com.
0115 – Nosil,
Hemlyne; 0516 – Carter, Shanika; 0605 – Curtis, Donna; 0623 – Cajuste,
Dominique; 1363 – Trammell, Heather; 1448 – Weir, Alicia; 1452 – Pinkerton,
Allan; 1466 – Gerena, Kiara; 1525 – Calloway, Krystal; 1742 – Lopez Elias,
Miguel; 1753 – Swift, Corderal; 1784 – roundtree, Virginia
Public sale
terms, rules, and regulations will be made available prior to the sale. All
sales are subject to cancellation. We reserve the right to refuse any bid.
Payment must be in cash or credit card-no checks. Buyers must secure the units
with their own personal locks. To claim tax-exempt status, original RESALE
certificates for each space purchased is required.  By PS Retail Sales, LLC, 701 Western Avenue,
Glendale, CA 91201. (818) 244-8080.
November 11, 2022
November 18, 2022
 
NOTICE OF PUBLIC
SALE
To satisfy the
owner’s storage lien, PS Retail Sales, LLC will sell at public lien sale on
November 28, 2022, the personal property in the below-listed units, which may
include but are not limited to: household and personal items, office and other
equipment. The public sale of these items will begin at 11:30 AM and continue
until all units are sold. The lien sale is to be held at the online auction
website, www.storagetreasures.com, where indicated. For online lien sales, bids
will be accepted until 2 hours after the time of the sale specified.
PUBLIC STORAGE #
08714, 8149 Aircenter Court, Orlando, FL 
32809, (407) 792-4965
Time: 11:30 AM
Sale to be held
at www.storagetreasures.com.
1019 – Dixson,
Barbara; 1130 – Perez, Melissa; 1143 – Lebron, Yanieliz; 1163 – mitchell,
Elizabeth; 2048 – Delgado, Alex; 2210 – Culler, Shelia Mosley; 2231 – Miranda,
Kim; 2303 – Ryan, Colin; 3055 – Ahorrios, Jeanette; 6025 – Rivera, Jafrayda;
6140 – Rosa Garcia, Pedro
PUBLIC STORAGE #
08717, 1800 Ten Point Lane, Orlando, FL 
32837, (407) 545-4431
Time: 11:40 AM
Sale to be held
at www.storagetreasures.com.
0105 – Rios,
Natalie; 0124 – Siedsma, Michael; 0235 – rondon, Nayritt; 1049 – Rios,
Cristina; 1069 – JE Grant Renovation Rivera, Emily; 2035 – Perez, Armando; 7061
– Ponte, Michelle; 7073 – Welch, Keaundra; 7090 – Siedsma, Michael; 7101 –
Bernal, Eric; 7147 – Dioulo, Franck; 7157 – Vera, Luis
PUBLIC STORAGE #
20711, 1801 W Oak Ridge Road, Orlando, FL 
32809, (407) 792-5808
Time: 11:50 AM
Sale to be held
at www.storagetreasures.com.
B046 –
Leatherwood, James; C018 – Ermer, Charles; C030 – NORTON, JOHN; C043 – Pruitt,
Termaine; C045 – Telfort, Dieula; D016 – Oritz, Nadine; E008 – Lockett,
Laquita; F005 – monteiro, victor; G019 – Hall, Joi; G020 – Green, Darius; H016
– Meza, Juan; H023 – Smith, Angelico; J010 – Cordero, Jose; J131 – Williams,
Georganne; J145 – Crespo, Kristie Laura; J156 – Velazquez, Antonio; K018 – Merkley,
David; K031 – king, Nikkia; K065 – davis, teyonda; K074 – Jones, Latasha; K092
– Wolf, Tamara
PUBLIC STORAGE #
24303, 1313 45th Street, Orlando, FL 
32839, (407) 278-8737
Time: 12:00 PM
Sale to be held
at www.storagetreasures.com.
A121 – Wilson,
Felicia; B215 – Lewis, Matthew; B224 – Slater, Joe; B228 – Morrison, Alfonso;
B230 – Price-Davis, Monica; B237 – Seymour, Glecia; B238 – phillips, Arviance;
B250 – Morris, Earnest; B292 – Mcintyre, Ebony; C328 – Ramirez, Nathalia; C338
– Jolicoeur, Shiller; C390 – Freeman, Randi; D411 – De Jesus, Ricardo; D414 –
Moore, Isaac; D417 – Drake, Roberts; D440 – Julma, Adele; D443 – Oneal,
Precious; E505 – Stanton, Joseph; E516 – almonte, daniel; E520 – Lalas, Cathy;
E541 – moonsamy, Malaysia; E549 – Mitchell, Sonia; E550 – Jackson, Regina; F600
– Johnson, Kimani; F604 – Wesley, Sonya; G714 – Louissaint, Andre; J908 –
Campbell, James; J910 – Jackson, Shequanda
PUBLIC STORAGE #
25454, 235 E Oak Ridge Road, Orlando, FL 
32809, (407) 326-9069
Time: 12:10 PM
Sale to be held at
www.storagetreasures.com.
A121 – Saddler,
Timothy; A139 – Cannaday, Kyasia; B216 – Al-Amin, Wali; B221 – Brimmer,
Shavonne; B225 – Watkins, Shante; D418 – Dangura, Ahmed; E528 – Green,
Larondale; F611 – Harrison, Rafael; G701 – Villar, Yordania; G702 – Fort,
Ritchie; G711 – Desir, Lineda; G715 – Martinez Vega, Kelvin; G734 – Davila,
gABRIEL; H810 – Brookman, Robert; I932 – Luft, Brittany; J023 – Fahlgren,
David; J024 – davis, Jeremy; K119 – Williams, Dashid; P061 – de leon, kelvin
PUBLIC STORAGE #
25782, 2783 N John Young Parkway, Kissimmee, FL 
34741, (321) 422-2079
Time: 12:20 PM
Sale to be held
at www.storagetreasures.com.
12021 – Poteet,
Robert Paul; 12042 – Clark, Amber; 12112 – White, Rachael; 12212 – Saunders,
Darryl; 206 – Culbreath, Crystal; 455 – Archibald, Briana; 471 – Berrios,
Kenny; 514 – Pennington, Jeremy; 596 – Oyola, Rotsenmary; 691 – Cabeza, Carlos;
883 – Castro Ortiz, Felix
PUBLIC STORAGE #
25806, 227 Simpson Rd, Kissimmee, FL 
34744, (407) 258-3087
Time: 12:30 PM
Sale to be held
at www.storagetreasures.com.
003 –
Rodriguez-Rodriguez, Joivan; 086 – Shivers, Darren; 246 – Osborne Santana,
Omar; 256 – Flores, Josh; 311 – Ortiz, Carmen; 320 – Kinney, Melissa; 330 –
Wynter, Nadia; 474 – Giraldo, wendy; 516 – Salcedo, Ricardo Ortiz; 535 – Landis,
Andrew J; 553 – Torres, Cindybel; 570 – Claudio, Noel; 600 – Sippio, Robert;
610 – Barger, Stephen; 623 – Clue, Les; 820 – Rodriguez, Javier; 846 – Daley,
Helekia; 877 – ruiz, christian
PUBLIC STORAGE #
25846, 1051 Buenaventura Blvd, Kissimmee, FL 
34743, (407) 258-3147
Time: 12:40 PM
Sale to be held
at www.storagetreasures.com.
01144 – Naar,
Jeannette Alexandra; 01311 – Buscampell, Jose; 02139 – Douglas, Stacy; 02142 –
Dizio, Fabrizio; 04139 – CREQUE, MARIANO; 04141 – Story, Alisha; 04525 –
Raising knowledge academy Cotto, Ariam; 05216 – Singer, Sequoyah
PUBLIC STORAGE #
25847, 951 S John Young Pkwy, Kissimmee, FL 
34741, (321) 236-6712
Time: 12:50 PM
Sale to be held
at www.storagetreasures.com.
1209 – Johnson,
Quinetta; 1215 – Morris, Ockley; 1310 – Averhart, Jasmine; 2077 – De Jesus,
Luis; 2194B – Rivera, Rayvin; 2208 – Turner, Chessirite; 2216 – Allende Rivera,
Marielys; 2323 – Lopez, Jacqueline; 2328 – Sisco, Linda
PUBLIC STORAGE #
25892, 1701 Dyer Blvd, Kissimmee, FL 
34741, (407) 392-1169
Time: 01:00 PM
Sale to be held
at www.storagetreasures.com.
0014 – Jones,
Micheal; 0041 – Ohanlon, Katrina; 0335 – Costales, Dafna; 1009 – Mega TV
Orlando Rivera, Jose; 1020 – Doyle, Troy; 2002 – Curbelo, Lizzy; 2010 – coles,
Aaliyah; 2013 – Moran Hernandez, Jonathan; 2088 – Pedraza, Pedro; 4021 –
Arroyo, Steven; 6048 – Jacobs-Wright, Timecia; 6065 – Jones, Micheal; 6073 –
Morris, Alexander; 6179 – Hill, Troy; 6207 – Concepcion, Jerany; 8051 –
Largaespada, David; 8072 – Johnson, Jamie; 8077 – Walker, Jordan
PUBLIC STORAGE #
28075, 4729 S Orange Blossom Trail, Orlando, FL 
32839, (407) 986-4867
Time: 01:10 PM
Sale to be held
at www.storagetreasures.com.
0135 – Grier,
Yevette; 0158 – Williams, Antoinette; 0231 – Grace, Crystal; 0236 – julssaint,
remy; 0320 – Harrold, Sherry; 0334 – Collier, Terrance; 0432 – Crawley,
Michelle; 0440 – Green, Jonathan; 0516 – Rivero, Yisell; 0616 – Givens,
Tawanda; 0721 – Celestine, Exanna; 0735 – Richardson, Darryl; 0809 – Simmons,
Demetris; 0811 – Silgado, Alvaro; 0812 – Egipciaco, Steve; 0822 – Jones,
Lashonda; 0908 – Smith, Jerohn; 09118 – Hernandez, James; 0924 – McCrimmon,
Jasline; 0928 – Mcneil, Aaleyah; 0933 – Cave Perez, Bryan; 0965 – Jones,
Andrea; 0969 – GUZMAN, JOSEPH; 0975 – Herberson, Paul; 0977 – smith, Katrina;
1011 – Pugh, Darius; 1059 – Barnes, Darlene; 1075 – Green, Michael; 1104 –
Hernandez Vanderpool, Juan; 1121 – Gonzalez, Evelyn; 1133 – Vargas, Estephanie;
1137 – Carter, Latasha; 1144 – Mercerlin, Daniel; 1160 – Johnson, Takelia; 1162
– Clue, Mashae; 1368 – senat, Micael; 1380 – Manzano Ramos, Jose
Public sale
terms, rules, and regulations will be made available prior to the sale. All
sales are subject to cancellation. We reserve the right to refuse any bid.
Payment must be in cash or credit card-no checks. Buyers must secure the units
with their own personal locks. To claim tax-exempt status, original RESALE
certificates for each space purchased is required.  By PS Retail Sales, LLC, 701 Western Avenue,
Glendale, CA 91201. (818) 244-8080.
November 11, 2022
November 18, 2022
 
PURSUANT TO THE
FLORIDA SELF-SERVICE STORAGE FACILITY ACT, NOTICE IS HEREBY GIVEN THAT THE
FACILITIES LISTED BELOW D/B/A SIMPLY SELF STORAGE WILL SELL AT PUBLIC AUCTION
THE PERSONAL PROPERTY IN THE BELOW-LISTED OCCUPANTS’ LEASED SPACES TO SATISFY
THE OWNER’S LIEN. THE PERSONAL PROPERTY STORED THEREIN BY THE FOLOWING
OCCUPANTS MAY INCLUDE BUT IS NOT LIMITED TO GENERAL HOUSEHOLD, OFFICE AND
PERSONAL ITEMS, FURNITURE, BOXES, CLOTHES, AND APPLIANCES. THE UNIT(S) WILL BE
SOLD AT PUBLIC AUCTION THROUGH ONLINE AUCTION SERVICES OF
WWW.STORAGETREASURES.COM WITH BIDS OPENING AT 6AM ON NOVEMBER 18, 2022 AND
CLOSING AT 1PM ON NOVEMBER 30, 2022.
SIMPLY STORAGE
SANFORD, LLC – 4051 W SR 46 SANFORD FL 32771: 1031-MICHAEL ANTHONY MERCADO,
1033-EARL GORDON SULLIVAN, 1126-DIGNA FELCIANO, 1180-TRENECE LEE,
1188-MERCEDITA SHERMAN, 2038-RITA LOUISE CRUMITY, 2084-JOY TURNER, 2124-TRAYCE
ANDERSON, 2157-KENNY SCHRAMM, 3004-JESSICA TALIAFERRO, 3016-LILIANA MARTINEZ,
3019-JAMES ROMEY HUFCOR, 3045-ANGELA PENCE , 3048-LAKEISHA COLEMAN,
3054-LATERIKA HILLERY, 3091-GOLDA MEIR HUMPHREY, 3114-TRACY BELMONT,
3127-ASHLEI KING, 4002-AUBREY HERRING, 4005-JENNIFER ALONGI HUFCOR,
4021-O’LIVIA FOSTER, 4025-ETHAN THORNOCK, 4054-BRITTANY MITZ, 316162-DANA
BERNICE JONES
SIMPLY STORAGE
ORMOND BEACH, LLC – 610 S YONGE STREET ORMOND BEACH 32174: 0334-KEVIN GARDNER,
0414-COURTNEY PRICE, 0415-ROBERT GAINES, 0423-TIFFANY SMITH, 0441-JAMES
BRADLEY, 0456-JEFFREY KNESKI, 0458-THORNTON LYON, 0468-JANESUA MADDOX,
0474-TASHONDRA TILLMON, 0475-ANGELA MAFALDO, 0479-LEA CROSBY, 0508-KATHRYN
POWEL, 0519-BERNICE FOUGERE, 0527-JOHN WESLEY IMMICH, 0535-BERNICE FOUGERE,
0562-THELMA HUTON, 0619-MARGARET QUINN RYAN, 0653-LEONIQUIA ADAMS, 0668-SOFIA
LAQUINTO, 0680-SHANNON CARIAS, 0684-VICTOR TIMPANARO, 0688-PHILLIP LOVELAND,
0698-DOREECE HINES, 0730-JEREMIAH THOMAS, 1019-DERRICK EAGAN, 1104-EMILY
ROSADO, 1108-RUSSELL OGLESBY,1142-ALLSON RAND
SSS WINTER
GARDEN, LLC – 12446 W COLONIAL DR WINTER GARDEN FL 34787: 2087- REGINALD
STANLEY; 3199- FRANCES DICKEY
SS PALM BAY
ROAD, LLC – 888 PALM BAY RD NE PALM BAY, FL 32905: 1076 – SUZETTE MERLET, 1140
– TENIKA WILLIAMS, 1144 – CLIFFORD WEEKS, 1183 – CASSIE WOODARD, 2040 – KENESHA
HARRIS, 2088- CHRISTOPHER HARPER, 3110 – DEBRA LOGUE, 5002 – SUSAN LARSON, 7001
– STEPHEN NIMBARGI, 7033 – KRISTEN CATNOTT, 7105 – CHRISTOPHER HARPER, 8079 –
JACKEEMA THOMPSON
SS COCOA, LLC –
2845 W KING ST COCOA, FL 32926: 00312 – EMILY COLEMAN, 00331 – NIKKI LALLY,
00398 – HALEN BINI, 00424 – ANTHONY WILLIAMS, 00432 – STEPHANIE SPENCER, 00435
– TINA MARIE SMITH, 00476 – CANDISE SOTO, 00491 – JOHN WALTON, 00510 – DAVID
AKINS, 00516 – ANGELA BUTLER, 00559 – STEPHEN SINCLAIR, 01345 – DAVID AKINS,
03115 – SYLVIA ANN LENT, 07240 – PHYLISIA KNOWLES, 07311 – NATIVIA KING, 13108
– DON CANHAM
SS PALM BAY, LLC
– 6350 BABCOCK ST SE PALM BAY, FL 32909: 00004-HECTOR VICENTE, 00048-CYNTHIA
LATREASE JOHNSON, 00231-ARTAVIS WILLIAMS, 00254-SAVANNAH MABERN, 00259-BOBBY
BALDWIN, 00277-JOANN LYNCH, 00295-MARTIN BERMUDEZ, 00325-SAMANTHA REYNOLDS,
00504-EVELYN BUCHANAN, 00648-ALICIA HAYES
SS ALTAMONTE
SPRINGS, LLC – 510 DOUGLAS AV ALTAMONTE SPRINGS, FL 32714: A1015-ADA MILAGROS
PAGAN, A1034-MARION MCMURRAY, B1011-SHARON GILSTRAP, B1022-WANDA AFANADOR,
C1023-SHARON GILSTRAP, C1046-GINA REED, C1128-SHAWN RODRIGUEZ,
C2026-MARY
FLEMING- C2029-MONIQUE SMITH, C2045-DARIUS TAYLOR, D1003-JOHN GARCIA,
D1011-ALBERT
NORMAN, D1043-KLACE THOMPSON, D1105-JAMES RODRIGUEZ, D2078-JAMES MCCORMICK,
D2155-HEIDI LEIGH CANTERBURY, D2161-SANDRA D. WILLIAMS, D2166-XAVIER HOQUE,
D2193-ALSONIA MCKENZIE, E1046 -LUCILLE DIXON, E1098-GENTLEFIRE FORBES,
E1145-FELICIA HENDERSON
SS NARCOOSSEE
ROAD, LLC – 7628 NARCOOSSEE ROAD ORLANDO, FL 32822: A104 – AJANE CELESTIN, A131
– JOSE NIEVES ROLDAN, B105 – JOANNE NICOLE LA COMB, B196 – JOANNE NICOLE LA
COMB, B214 – RAMON RIVERA, B221 – ALVIN LIZ, B222 – JOANNE NICOLE LA COMB, C405
– RANDALL HUNT, C416 – IAN FREITES, C544 – ERIC MAGDIEL OSTALAZA CASTILLO, C549
– THOMAS MICHAEL BOWMAN, C596 – DIOP MCKENZIE, F015 – CHRISTIAN TYLER JAMES.
SS WINDERMERE
REAMS ROAD, LLC – 13151 REAMS RD WINDERMERE, FL 34786: 1018 – DANIEL DEUTSCH,
1108 – DANIEL DEUTSCH, 1238 – DEVIN BRYANT, 1327 – MATTHEW PERRY, 2115 –
LUCINDA THOMPSON, 2302 – DILMA RAMOS, 2330 – RACHEL ELDER, 3026 – DUSTIN
FEDRICK, 3513 – JORDAN MONOSA
November 11, 2022
November 18, 2022
 
IN THE CIRCUIT
COURT FOR LAKE COUNTY, FLORIDA
PROBATE DIVISION
File No.  35-2022-CP-002049-AXXX-XX
Division
IN RE:  ESTATE OF SUZANN KAY OWENS
Deceased.
NOTICE TO
CREDITORS
The
administration of the estate of Suzann Kay Owens, deceased, whose date of death
was May 22, 2022, is pending in the Circuit Court for Lake County, Florida,
Probate Division, the address of which is 550 W. Main Street, 2nd Floor,
Tavares, Florida 32778.  The names and
addresses of the personal representative and the personal representative’s
attorney are set forth below.
All creditors of
the decedent and other persons having claims or demands against decedent’s
estate on whom a copy of this notice is required to be served must file their
claims with this court ON OR BEFORE THE LATER OF 3 MONTHS AFTER THE TIME OF THE
FIRST PUBLICATION OF THIS NOTICE OR 30 DAYS AFTER THE DATE OF SERVICE OF A COPY
OF THIS NOTICE ON THEM.
All other
creditors of the decedent and other persons having claims or demands against
decedent’s estate must file their claims with this court WITHIN 3 MONTHS AFTER
THE DATE OF THE FIRST PUBLICATION OF THIS NOTICE.
ALL CLAIMS NOT
FILED WITHIN THE TIME PERIODS SET FORTH IN FLORIDA STATUTES SECTION 733.702
WILL BE FOREVER BARRED.
NOTWITHSTANDING
THE TIME PERIODS SET FORTH ABOVE, ANY CLAIM FILED TWO (2) YEARS OR MORE AFTER
THE DECEDENT’S DATE OF DEATH IS BARRED.
The date of
first publication of this notice is November 11, 2022.
Attorney for
Personal Representative:
/s/ Brian V. Bergman
Attorney
Florida Bar Number: 0032214
MacLean and Ema, P.A.
2600 NE 14th Street Causeway
Pompano Beach, Florida 33062
Telephone: (954) 785-1900
Fax: (954) 942-1006
E-Mail: [email protected]
E-Mail: [email protected]
Personal Representative:
/s/ Jack C. Owens
7540 W.
Vermontville Highway
Vermontville, Michigan 49096
November 11, 2022
November 18, 2022
 
IN THE CIRCUIT
COURT FOR OSCEOLA COUNTY, FLORIDA
PROBATE DIVISION
File No.
2022-CP-000952
IN RE:  ESTATE OF HAROLD FAIRCHILD PYKE, JR.
Deceased.
NOTICE TO
CREDITORS
The
administration of the estate of Harold Fairchild Pyke, Jr., deceased, whose
date of death was September 10, 2022, is pending in the Circuit Court for
Osceola County, Florida, Probate Division, the address of which is 2 Courthouse
Square, Kissimmee, Florida 34741.  The
names and addresses of the personal representative and the personal
representative’s attorney are set forth below.
All creditors of
the decedent and other persons having claims or demands against decedent’s
estate on whom a copy of this notice is required to be served must file their
claims with this court ON OR BEFORE THE LATER OF 3 MONTHS AFTER THE TIME OF THE
FIRST PUBLICATION OF THIS NOTICE OR 30 DAYS AFTER THE DATE OF SERVICE OF A COPY
OF THIS NOTICE ON THEM.
All other
creditors of the decedent and other persons having claims or demands against
decedent’s estate must file their claims with this court WITHIN 3 MONTHS AFTER
THE DATE OF THE FIRST PUBLICATION OF THIS NOTICE.
ALL CLAIMS NOT
FILED WITHIN THE TIME PERIODS SET FORTH IN FLORIDA STATUTES SECTION 733.702
WILL BE FOREVER BARRED.
NOTWITHSTANDING
THE TIME PERIODS SET FORTH ABOVE, ANY CLAIM FILED TWO (2) YEARS OR MORE AFTER
THE DECEDENT’S DATE OF DEATH IS BARRED.
The date of
first publication of this notice is November 11, 2022.
Attorney for
Personal Representative:
/s/ Thomas P. Moss, Esq.
Florida Bar Number: 0157376
Sawyer & Sawyer, P.A.
8913 Conroy Windermere Rd.
Orlando, Florida 32835
Telephone: (407) 909-1900
Fax: (407) 909-1992
E-Mail: [email protected]
Secondary E-Mail: [email protected]
Personal Representative:
/s/ Harold F. Pyke III
12 Hillside Avenue
Warwick, New York 10990
November 11, 2022
November 18, 2022
 
NOTICE
PUBLIC
ANNOUNCEMENT FOR ARCHITECTURAL AND ENGINEERING SERVICES FOR ROSEMONT ELEMENTARY
SCHOOL MULTI-SYSTEM CAPITAL RENEWAL PROJECT
The School Board
of Orange County, Florida announces that Architectural and Engineering Services
are required for the project listed below.
PROJECT NAME AND
NUMBER: Rosemont ES Multi-System Capital Renewal Project, RFQ 2230PS
SERVICES TO BE
PROVIDED: Architectural and Engineering Services
PRE-SUBMITTAL
MEETING: November 16, 2022 at 10:00 a.m., via WebEx. Meeting information will
be posted on VendorLink. Attendance is not mandatory.
OCPS CONTACT:
Susan Perry, Facilities & Construction Contracting Orange County Public
Schools PROPOSALS ARE TO BE SUBMITTED: To VendorLink.
PROPOSAL DUE
DATE: December 7, 2022, 2:00 p.m.
Requirements:
Interested firms are required to comply with all requirements of the Request
for Qualification (RFQ). All solicitations for Construction Related Services
can be found at the following link
https://vendorlink.ocps.net/common/login.aspx. Furthermore, all Notices
concerning this solicitation and award shall be posted to the aforementioned
website. These Notices shall include but are not limited to shortlist meeting
dates and times, presentation meeting dates and times, intended decision, and
decision information.
Equal Employment
Opportunity: The School Board of Orange County, Florida, does not discriminate
in admission or access to, or treatment or employment in its programs and
activities, on the basis of race, color, religion, age, sex, national origin,
marital status, disability, genetic information, sexual orientation, gender
identity or expression, or any other reason prohibited by law. The following
individuals at the Ronald Blocker Educational Leadership Center, 445 West
Amelia Street, Orlando, Florida 32801, attend to compliance matters: Equal
Employment Opportunity (EEO) Officer & Title IX Coordinator: Keshara
Cowans; ADA Coordinator: Jay Cardinali; Section 504 Coordinator: Tajuana
Lee-Wenze. (407.317.3200)
November 11, 2022
November 18, 2022
November 25, 2022
 
NOTICE
PUBLIC
ANNOUNCEMENT FOR CONSTRUCTION MANAGEMENT AT RISK SERVICES FOR ROSEMONT
ELEMENTARY SCHOOL MULTI-SYSTEM CAPITAL RENEWAL PROJECT
The School Board
of Orange County, Florida announces that Construction Management at Risk
Services are required for the project listed below.
PROJECT NAME AND
NUMBER: Rosemont ES Multi-System Capital Renewal Project, RFQ 2231CM
SERVICES TO BE
PROVIDED: Construction Management at Risk Services.
PRE-SUBMITTAL
MEETING: November 16, 2022 at 10:00 a.m., via Webex. Meeting information will
be posted on VendorLink. Attendance is not mandatory.
OCPS CONTACT:
Susan Perry, Facilities & Construction Contracting Orange County Public
Schools
PROPOSALS ARE TO
BE SUBMITTED: To VendorLink.
PROPOSAL DUE
DATE: December 7, 2022, 2:00 p.m.
Requirements:
Interested firms are required to comply with all requirements of the Request
for Qualification (RFQ). All solicitations for Construction Related Services
can be found at the following link https://vendorlink.ocps.net/common/login.aspx.
Furthermore, all Notices concerning this solicitation and award shall be posted
to the aforementioned website. These Notices shall include but are not limited
to shortlist meeting dates and times, presentation meeting dates and times, intended
decision, and decision information.
Equal Employment
Opportunity: The School Board of Orange County, Florida, does not discriminate
in admission or access to, or treatment or employment in its programs and
activities, on the basis of race, color, religion, age, sex, national origin,
marital status, disability, genetic information, sexual orientation, gender
identity or expression, or any other reason prohibited by law. The following
individuals at the Ronald Blocker Educational Leadership Center, 445 West
Amelia Street, Orlando, Florida 32801, attend to compliance matters: Equal
Employment Opportunity (EEO) Officer & Title IX Coordinator: Keshara
Cowans; ADA Coordinator: Jay Cardinali; Section 504 Coordinator: Tajuana
Lee-Wenze. (407.317.3200)
November 11, 2022
November 18, 2022
November 25, 2022
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In the thriving entertainment industry of South Korea, it is rare for a relatively unknown singer to get an opportunity to record a song for a Korean drama’s original soundtrack (OST). But when it happens, K-pop composer Seo Gi-jun says, music lovers are introduced to newer voices.
From singer Punch, whose collaboration ”Stay With Me” with EXO group member Chanyeol went off the charts following the popularity of 2016 blockbuster drama ”Goblin”, to artist Gaho, who shot to fame after he sang ”Start Over” for ”Itaewon Class”, K-dramas have given new lease to the careers of many musicians.
”There are cases where an OST helped in increasing the popularity of a singer. ‘Goblin’ helped in the popularity of the song sung by Punch and Chanyeol. Also, Gaho became famous after the success of ‘Itaewon Class’,” the South Korean music composer told PTI, through an interpreter, in a group interview held at the Korea Press Center here.
It is rare that up-and-coming artists end up being part for an OST since these songs are mostly sung by leading singers, added Seo.
”K-drama OSTs help many relatively unknown singers get popularity. But, you also have to understand that it is hard for many singers who are not famous to get an opportunity to sing a song for an OST. It is very rare because these songs generally go to the singers who are already famous,” he said.
As much as an OST is a subset of a show, it is very much an independent entity and one doesn’t need to be a K-drama fan to enjoy its album.
Besides stellar performances by ensemble cast and taut storytelling, superhit K-dramas including ”Crash Landing On You”, ”Descendents of the Sun”, ”Search: WWW”, ”Hospital Playlist”, ”Something in the Rain”, and ”One Spring Night” owe their popularity to the original songs that drove the plot forward.
A hit OST has a significant impact on the popularity of a Korean drama, admitted Seo, who debuted in 2012 with Japanese singer Koda Kumi’s song ”Love Technique”.
”People usually think drama is more important and OSTs follow the popularity of drama. For me, as a composer, an OST is more important,” he added.
What songs are to Indian films, OSTs are to Korean dramas.
”Usually, Korean films don’t have OSTs. They have original sound (background score) but not songs,” said the composer, whose credits include ”Last Goodbye” sung by brother-sister duo Akum and Jung In’s ”Actually I’m” from 2015’s Korean series ”Yong-pal”.
Seo, who has participated in writing and arranging about 80 songs, said a producer doesn’t know when and where the next job might come from.
”One hard thing about being a composer is that this job doesn’t have any schedule. Usually, customers just demand songs whenever they want. Often, they ask ‘Can you make a song by next week?’ This is a normal practice in Seoul,” he said.
The hard work that goes into creating an OST is just as much as it is for a regular, flashy K-pop song. There are, however, budget constraints.
”(Production of) One song in an OST costs less than a K-pop song. Usually it is 1 million to 1.5 million won (Rs 90,000 approximately), that is if we exclude the money paid to the composer,” he added.
It is interesting how Seo, who didn’t like to study as a child, also teaches music at South Korea’s Baekseok Art University.
”(Growing up), I focused on music and I started my music studies in university and that has been my career till now,” he said.
Seo recently established a company called Gangnam Indie Records and is expanding the scope of music production here in South Korea.
Asked what could be his next future project, the musician said, ”Maybe, I’ll record another OST next week.”
(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)
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