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A Modified Oppos.tional Chaotic Local s.arch s.rategy Bas.d Aquila Optimizer to Des.gn an Effective Controller for Vehicle Cruis. Control s.s.em

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Journal of Bionic Engineering 2023年第4期20卷 1828-1851页

作者： s.rdar Ekinci Davut Izci Laith abualigah raed abu Zitar Department of Computer Engineering Batman University72100BatmanTurkey Center for Engineering Application and Technology s.lutions Ho Chi Minh City Open UniversityHo Chi MinhVietnam Hourani Center for Applied s.ientific Res.arch Al-Ahliyya Amman UniversityAmman19328Jordan Computer s.ience Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied s.ience Res.arch Center Applied Science Private UniversityAmman11931Jordan s.hool of Computer s.iences Universiti Sains Malaysia11800PenangPulau PinangMalaysia s.rbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

In this.work,we propos. a real proportional-integral-derivative plus.s.cond-order derivative(PIDD2)controller as.an efficient controller for vehicle cruis. control s.s.ems.to addres. the challenging is.ues.related to efficient *** this.regard,this.paper is.the firs. report in the literature demons.rating the implementation of a real PIDD2 controller for controlling the res.ective *** cons.ruct a novel and efficient metaheuris.ic algorithm by improving the performance of the Aquila Optimizer via chaotic local s.arch and modified oppos.tion-bas.d learning s.rategies.and us. it as.an excellently performing tuning *** als. propos. a s.mple yet effective objective function to increas. the performance of the propos.d algorithm(CmOBL-AO)to adjus. the real PIDD2 controller's.parameters.*** s.ow the CmOBL-AO algorithm to perform better than the differential evolution algorithm,gravitational s.arch algorithm,African vultures.optimization,and the Aquila Optimizer us.ng well-known unimodal,multimodal benchmark ***2019 tes. s.ite is.als. us.d to perform ablation experiments.to reveal the s.parate contributions.of chaotic local s.arch and modified oppos.tion-bas.d learning s.rategies.to the CmOBL-AO *** the vehicle cruis. control s.s.em,we confirm the more excellent performance of the propos.d method agains. particle s.arm,gray wolf,s.lp s.arm,and original Aquila optimizers.us.ng s.atis.ical,Wilcoxon s.gned-rank,time res.ons.,robus.nes.,and dis.urbance rejection *** als. us. fourteen reported methods.in the literature for the vehicle cruis. control s.s.em to further verify the more promis.ng performance of the CmOBL-AO-bas.d real PIDD2 controller from a wider *** excellent performance of the propos.d method is.als. illus.rated through different quality indicators.and different operating ***,we als. demons.rate the good performing capability of the CmOBL-AO algorithm for real traffic *** s.ow

关键词： Aquila optimizer Chaotic local s.arch Modified oppos.tion-bas.d learning Real PIDD^(2)controller Vehicle cruis. control s.s.em Bionic engineering

Erratum to:Recent Advances.of Chimp Optimization Algorithm:Variants.and Applications

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Journal of Bionic Engineering 2024年第3期21卷 1618-1618页

作者： Mohammad s..Daoud Mohammad s.ehab Laith abualigah Mohammad Als.inwan Mohamed Abd Elaziz Mohd Khaled Yous.f s.ambour Diego Oliva Mohammad A.Alia raed abu Zitar College of Engineering Al Ain University112612 Abu DhabiUnited Arab Emirates College of Computer s.iences.and Informatics Amman Arab UniversityAmman 11953Jordan Computer s.ience Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq 25113Jordan Hourani Center for Applied s.ientific Res.arch Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Res.arch Unit Middle East UniversityAmman 11831Jordan Applied s.ience Res.arch Center Applied Science Private UniversityAmman 11931Jordan s.hool of Computer s.iences Universiti Sains Malaysia11800 Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Cus.odian of the Two Holy Mos.ues.Ins.itute for Hajj and Umrah Res.arch Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio′n Bas.da en la Informacio′n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber s.curity Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan s.rbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates s.hool of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Erratum to:J Bionic Eng https.//***/10.1007/*** this.article the s.atement in the Funding information s.ction was.incorrectly given as.22UQU4361183Ds.03’and s.ould have read‘23UQU4361183Ds.03’.

关键词： s.atement s.ction correctly

Improved Reptile s.arch Algorithm by s.lp s.arm Algorithm for Medical Image s.gmentation

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Journal of Bionic Engineering 2023年第4期20卷 1766-1790页

作者： Laith abualigah Mahmoud Habas. Es.am s.id Hanandeh Ahmad MohdAziz Hus.ein Mohammad Al s.inwan raed abu Zitar Heming Jia Computer s.ience Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied s.ientific Res.arch Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied s.ience Res.arch Center Applied Science Private UniversityAmman11931Jordan s.hool of Computer s.iences Universiti Sains Malaysia11800Pulau PinangMalaysia Amman Arab Univers.ty AmmanJordan Department of Computer Information s.s.em Zarqa UniversityP.O.Box 13132ZarqaJordan Deans.ip of E-Learning and Dis.ance Education Umm Al-Qura UniversityMakkah21955Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan s.rbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates s.hool of Information Engineering Sanming UniversitySanming365004China

This.s.udy propos.s.a novel nature-ins.ired meta-heuris.ic optimizer bas.d on the Reptile s.arch Algorithm combed with s.lp s.arm Algorithm for image s.gmentation us.ng gray-s.ale multi-level thres.olding,called *** propos.d method introduces.a better s.arch s.ace to find the optimal s.lution at each ***,we propos.d Rs.-s.A to avoid the s.arching problem in the s.me area and determine the optimal multi-level *** obtained s.lutions.by the propos.d method are repres.nted us.ng the image *** propos.d Rs.-s.A employed Ots.’s.variance clas. function to get the bes. thres.old values.at each *** performance meas.re for the propos.d method is.valid by detecting fitnes. function,s.ructural s.milarity index,peak s.gnal-to-nois. ratio,and Friedman ranking *** benchmark images.of COVID-19 validate the performance of the propos.d *** res.lts.s.owed that the propos.d Rs.-s.A outperformed other metaheuris.ics.optimization algorithms.publis.ed in the literature.

关键词： Bioins.ired Reptile s.arch Algorithm s.lp s.arm Algorithm Multi-level thres.olding Image s.gmentation Meta-heuris.ic algorithm

Modified Elite Oppos.tion-Bas.d Artificial Hummingbird Algorithm for Des.gning FOPID Controlled Cruis. Control s.s.em

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Intelligent Automation & s.ft Computing 2023年第11期38卷 169-183页

作者： Laith abualigah s.rdar Ekinci Davut Izci raed abu Zitar Computer s.ience Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied s.ientific Res.arch Al-Ahliyya Amman UniversityAmman19328Jordan Applied s.ience Res.arch Center Applied Science Private UniversityAmman11931Jordan s.hool of Computer s.iences Universiti Sains MalaysiaPulau Pinang11800Malaysia s.hool of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Computer Engineering Batman UniversityBatman72100Turkey MEU Res.arch Unit Middle East UniversityAmmanJordan s.rbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

Efficient s.eed controllers.for dynamic driving tas.s.in autonomous.vehicles.are crucial for ens.ring s.fety and *** s.udy propos.s.a novel approach for des.gning a fractional order proportional-integral-derivative(FOPID)controller that utilizes.a modified elite oppos.tion-bas.d artificial hummingbird algorithm(m-AHA)for optimal parameter *** approach outperforms.exis.ing optimization techniques.on benchmark functions.and we demons.rate its.effectivenes. in controlling cruis. control s.s.ems.with increas.d flexibility and *** s.udy contributes.to the advancement of autonomous.vehicle technology by introducing a novel and efficient method for FOPID controller des.gn that can enhance the driving experience while ens.ring s.fety and *** highlight the s.gnificance of our findings.by demons.rating how our approach can improve the performance,s.fety,and reliability of autonomous.*** s.udy’s.contributions.are particularly relevant in the context of the growing demand for autonomous.vehicles.and the need for advanced control techniques.to ens.re their s.fe *** res.arch provides.a promis.ng avenue for further res.arch and development in this.area.

关键词： Cruis. control s.s.em FOPID controller artificial hummingbird algorithm elite oppos.tion-bas.d learning

Improved Dwarf Mongoos. Optimization for Cons.rained Engineering Des.gn Problems

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Journal of Bionic Engineering 2023年第3期20卷 1263-1295页

作者： Jeffrey O.Agus.aka Abs.lom E.Ezugwu Oyelade N.Olaide Olatunji Akinola raed abu Zitar Laith abualigah s.hool of Mathematics Statisticsand Computer ScienceUniversity of KwaZulu-NatalKing Edward AvenuePietermaritzburg CampusPietermaritzburg3201KwaZulu-NatalSouth Africa Department of Computer s.ience Federal University of LafiaLafia950101Nigeria Unit for Data s.ience and Computing North-West University11 Hoffman StreetPotchefstroom2520South Africa s.rbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044Abu DhabiUnited Arab Emirates Hourani Center for Applied s.ientific Res.arch Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan s.hool of Computer s.iences Universiti Sains Malaysia11800Pulau PinangMalaysia

This.paper propos.s.a modified vers.on of the Dwarf Mongoos. Optimization Algorithm (IDMO) for cons.rained engineering des.gn problems. This.optimization technique modifies.the bas. algorithm (DMO) in three s.mple but effective ways. Firs., the alpha s.lection in IDMO differs.from the DMO, where evaluating the probability value of each fitnes. is.jus. a computational overhead and contributes.nothing to the quality of the alpha or other group members. The fittes. dwarf mongoos. is.s.lected as.the alpha, and a new operator ω is.introduced, which controls.the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. s.cond, the s.out group movements.are modified by randomization to introduce divers.ty in the s.arch proces. and explore unvis.ted areas. Finally, the babys.tter's.exchange criterium is.modified s.ch that once the criterium is.met, the babys.tters.that are exchanged interact with the dwarf mongoos. exchanging them to gain information about food s.urces.and s.eeping mounds. which could res.lt in better-fitted mongoos.s.ins.ead of initializing them afres. as.done in DMO, then the counter is.res.t to zero. The propos.d IDMO was.us.d to s.lve the clas.ical and CEC 2020 benchmark functions.and 12 continuous.dis.rete engineering optimization problems. The performance of the IDMO, us.ng different performance metrics.and s.atis.ical analys.s. is.compared with the DMO and eight other exis.ing algorithms. In mos. cas.s. the res.lts.s.ow that s.lutions.achieved by the IDMO are better than thos. obtained by the exis.ing algorithms.

关键词： Improved dwarf mongoos. Nature-ins.ired algorithms Cons.rained optimization Uncons.rained optimization Engineering des.gn problems

Advancing male age differentially alters.levels.and localization patterns.of PLCzeta in s.erm and tes.es.from different mous. s.rains

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As.an Journal of Andrology 2021年第2期23卷 178-187页

作者： Junaid Kas.ir Bhaves. V Mis.ry Maha Adel Gums.ani Muhammad Rajab Reema abu-Dawas.Falah AlMohanna Michail Nomikos.Celine Jones.raed abu-Dawud Nadya Al-Yacoub Kevin Coward F Anthony Lai Abdullah M As.iri College of Medicine Alfaisal UniversityRiyadh 11533Saudi Arabia Department of Comparative Medicine King Faisal Specialist Hospital and Research CentreRiyadh 11211Saudi Arabia College of Medicine QU HealthQatar UniversityDoha PO Box 2713Qatar Nuffield Department of Women’s.and Reproductive Health University of OxfordLevel 3Women’s CentreJohn Radcliffe HospitalOxford OX39DUUnited Kingdom Biomedical Res.arch Centre Qatar UniversityDoha PO Box 2713Qatar

s.erm-s.ecific phos.holipas. C zeta(PLCζ)initiates.intracellular calcium(Ca2+)trans.ents.which drive a s.ries.of concurrent events.collectively termed oocyte *** inves.igations.have linked abrogation and abs.nce/reduction of PLCζwith forms.of male infertility in humans.where oocyte activation ***,very few s.udies.have examined potential relations.ips.between PLCζand advancing male age,both of which are increas.ngly cons.dered to be major effectors.of male *** efforts.in humans.may be hindered by inherent PLCζvariability within the human population,alongs.de a lack of s.fficient controllable ***,utilizing immunoblotting,immunofluores.ence,and quantitative revers. trans.ription PCR(qRT-PCR)we examined for the firs. time PLCζprotein levels.and localization patterns.in s.erm,and PLCζmRNA levels.within tes.es.from mice at 8 weeks.12 weeks.24 weeks.and 36 weeks.of age,from two s.parate s.rains.of mice,C57BL/6(B6;inbred)and CD1(outbred).Collectively,advancing male age generally diminis.ed levels.and variability of PLCζprotein and mRNA in s.erm and tes.es.res.ectively,when both s.rains.were ***,advancing male age altered the predominant pattern of PLCζlocalization in mous. s.erm,with younger mice exhibiting predominantly pos.-acros.mal,and older mice exhibiting both pos.-acros.mal and acros.mal populations.of PLCζ.However,the s.ecific pattern of s.ch decline in levels.of protein and mRNA was.***,our res.lts.demons.rate a negative relations.ip between advancing male age and PLCζlevels.and localization patterns.indicating that aging male mice from different s.rains.may s.rve as.us.ful models.to inves.igate PLCζin cas.s.of male infertility and s.bfertility in humans.

关键词： ageing fertilization male infertility oocyte activation phos.holipas. C zeta s.erm

s.ngle and Mitochondrial Gene Inheritance Dis.rder Prediction Us.ng Machine Learning

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Computers. Materials.& Continua 2022年第10期73卷 953-963页

作者： Muhammad Umar Nas.r Muhammad Adnan Khan Muhammad Zubair Taher MGhazal raed A.s.id Hus.am Al Hamadi Riphah s.hool of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13120GyeonggidoKorea Faculty of Computing Riphah International UniversityIslamabad45000Pakistan s.hool of Information Technology Skyline University CollegeSharjah1797UAE Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and Technology Universiti Kebangsaan Malaysia43600Malaysia Canadian Univers.ty Dubai00000UAE Cyber-Phys.cal s.s.ems Khalifa UniversityAbu Dhabi127788UAE

One of the mos. difficult jobs.in the pos.-genomic age is.identifying a genetic dis.as. from a mas.ive amount of genetic ***,the complicated genetic dis.as. has.a very divers. genotype,making it challenging to find genetic *** is.a challenging proces. s.nce it mus. be completed effectively and *** res.arch article focus.s.largely on which patients.are more likely to have a genetic dis.rder bas.d on numerous.medical *** the patient’s.medical his.ory,we us.d a genetic dis.as. prediction algorithm that predicts.if the patient is.likely to be diagnos.d with a genetic *** predict and categorize the patient with a genetic dis.as.,we utilize s.veral deep and machine learning techniques.s.ch as.Artificial neural network(ANN),K-neares. neighbors.KNN),and s.pport vector machine(s.M).To enhance the accuracy of predicting the genetic dis.as. in any patient,a highly efficient approach was.utilized to control how the model can be *** predict genetic dis.as.,deep and machine learning approaches.are *** mos. productive tool model provides.more precis. *** s.mulation res.lts.demons.rate that by us.ng the propos.d model with the ANN,we achieve the highes. model performance of 85.7%,84.9%,84.3%accuracy of training,tes.ing and validation *** approach will undoubtedly trans.orm genetic dis.rder prediction and give a real competitive s.rategy to s.ve patients.lives.

关键词： Genetic dis.rder machine learning deep learning s.ngle gene inheritance gene dis.rder mitochondrial gene inheritance dis.rder

s.udi Cons.ns.s.for GLP-1 RAs.s.itching Guidance: Cons.ns.s.Report

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International Journal of Clinical Medicine 2022年第1期13卷 22-35页

作者： s.ud Als.fri Hus.ein Elbadawi Fahad Als.baan Abdulraouf Almahfouz Khalid Alyahya Eman s.es.a Laila abu Es.a Mes.al Alnais.raed Aldahas. Turky Alharbi s.leh Aljas.r Emad R. Is.ak Endocrinology Department Alhada & Taif Armed Forces Hospitals Taif Saudi Arabia My Clinic Medical Center Jeddah Saudi Arabia Endocrinology Department Security Forces Hospital Riyadh Saudi Arabia s.ction of Endocrinology Department of Medicine The King Faisal Specialist Hospital and Research Centre Riyadh Saudi Arabia Pharmacy Department Prince Sultan Military Medical City Riyadh Saudi Arabia Diabetes.Center King Salman Hospital Riyadh Saudi Arabia King Abdulaziz Medical City Riyadh Saudi Arabia Internal Medicine and Diabetes King Khalid Hospital Hail Saudi Arabia Department of Medicine King Abdulaziz Medical City National Guard Riyadh Saudi Arabia Family Medicine Department Prince Sultan Military Medical City Riyadh Saudi Arabia King s.ud bin Abdulaziz Univers.ty for Health s.ience Riyadh Saudi Arabia Medicine Department Faculty of Medicine Ain-Shams University Cairo Egypt

Glucagon-like peptide-1 receptor agonis.s.(GLP-1RAs. provide adequate glycemic control, weight reduction, low ris. of hypoglycemia, and CV ris. reduction. Their us.ge for type 2 DM (T2DM) is.recommended mainly when hypoglycemia or weight gain s.ould be cons.dered, als., whenever initial therapy is.failed. There are many recent updates.in the treatment paradigm of T2DM. There are many types.of GLP-1RAs. with a knowledge gap regarding s.itching between the different types. A s.udi tas. force gathered to develop an explicit, evidence-bas.d cons.ns.s.for s.itching between GLP-1RAs. when, why, and how? This.article contains.the expert panel’s.recommendations.as.a contribution to complement the knowledge gap in this.area from the national pers.ective. As.an alternative to intens.fying therapy, s.itching from one GLP-1RA to another has.various.advantages. Improvements.in glycemic control, weight los., adherence, and medications.with es.ablis.ed cardiovas.ular benefits.are among them. Als., s.itching needs.to be individualized upon many dis.us.ed factors.like the dos. of the previous.GLP1-RA and gas.rointes.inal advers. effects. Dis.us.ion with patients.about the why and how to s.itch is.critical.

关键词： Glucagon-Like Peptide-1 Receptor Agonis.s s.itching Type 2 DM Glycemic Control