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A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System

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

作者： Serdar Ekinci Davut Izci Laith abualigah raed abu zitar Department of Computer Engineering Batman University72100BatmanTurkey Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi MinhVietnam Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800PenangPulau PinangMalaysia Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

In this work,we propose a real proportional-integral-derivative plus second-order derivative(PIDD2)controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient *** this regard,this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective *** construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning *** also propose a simple yet effective objective function to increase the performance of the proposed algorithm(CmOBL-AO)to adjust the real PIDD2 controller's parameters *** show the CmOBL-AO algorithm to perform better than the differential evolution algorithm,gravitational search algorithm,African vultures optimization,and the Aquila Optimizer using well-known unimodal,multimodal benchmark ***2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO *** the vehicle cruise control system,we confirm the more excellent performance of the proposed method against particle swarm,gray wolf,salp swarm,and original Aquila optimizers using statistical,Wilcoxon signed-rank,time response,robustness,and disturbance rejection *** also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider *** excellent performance of the proposed method is also illustrated through different quality indicators and different operating ***,we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic *** show

关键词： Aquila optimizer Chaotic local search Modified opposition-based learning Real PIDD^(2)controller Vehicle cruise control system Bionic engineering

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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 Sh.Daoud Mohammad Shehab Laith abualigah Mohammad Alshinwan Mohamed Abd Elaziz Mohd Khaled Yousef Shambour Diego Oliva Mohammad A.Alia raed abu zitar College of Engineering Al Ain University112612 Abu DhabiUnited Arab Emirates College of Computer Sciences and Informatics Amman Arab UniversityAmman 11953Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq 25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied Science Research Center Applied Science Private UniversityAmman 11931Jordan School of Computer Sciences Universiti Sains Malaysia11800 Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio′n Basada en la Informacio′n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber Security Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates School of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Erratum to:J Bionic Eng https://***/10.1007/*** this article the statement in the Funding information section was incorrectly given as‘22UQU4361183DSR03’and should have read‘23UQU4361183DSR03’.

关键词： statement section correctly

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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

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Intelligent Automation & Soft Computing 2023年第11期38卷 169-183页

作者： Laith abualigah Serdar Ekinci Davut Izci raed abu zitar Computer Science 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 Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Computer Engineering Batman UniversityBatman72100Turkey MEU Research Unit Middle East UniversityAmmanJordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and *** study proposes a novel approach for designing a fractional order proportional-integral-derivative(FOPID)controller that utilizes a modified elite opposition-based artificial hummingbird algorithm(m-AHA)for optimal parameter *** approach outperforms existing optimization techniques on benchmark functions,and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and *** study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and *** highlight the significance of our findings by demonstrating how our approach can improve the performance,safety,and reliability of autonomous *** study’s contributions are particularly relevant in the context of the growing demand for autonomous vehicles and the need for advanced control techniques to ensure their safe *** research provides a promising avenue for further research and development in this area.

关键词： Cruise control system FOPID controller artificial hummingbird algorithm elite opposition-based learning

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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

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

作者： Laith abualigah Mahmoud Habash Essam Said Hanandeh Ahmad MohdAziz Hussein Mohammad Al Shinwan raed abu zitar Heming Jia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia Amman Arab University AmmanJordan Department of Computer Information System Zarqa UniversityP.O.Box 13132ZarqaJordan Deanship of E-Learning and Distance Education Umm Al-Qura UniversityMakkah21955Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates School of Information Engineering Sanming UniversitySanming365004China

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding,called *** proposed method introduces a better search space to find the optimal solution at each ***,we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level *** obtained solutions by the proposed method are represented using the image *** proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each *** performance measure for the proposed method is valid by detecting fitness function,structural similarity index,peak signal-to-noise ratio,and Friedman ranking *** benchmark images of COVID-19 validate the performance of the proposed *** results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

关键词： Bioinspired Reptile Search Algorithm Salp Swarm Algorithm Multi-level thresholding Image segmentation Meta-heuristic algorithm

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Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems

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

作者： Jeffrey O.Agushaka Absalom E.Ezugwu Oyelade N.Olaide Olatunji Akinola raed abu zitar Laith abualigah School of Mathematics Statisticsand Computer ScienceUniversity of KwaZulu-NatalKing Edward AvenuePietermaritzburg CampusPietermaritzburg3201KwaZulu-NatalSouth Africa Department of Computer Science Federal University of LafiaLafia950101Nigeria Unit for Data Science and Computing North-West University11 Hoffman StreetPotchefstroom2520South Africa Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044Abu DhabiUnited Arab Emirates Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia

This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected 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. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.

关键词： Improved dwarf mongoose Nature-inspired algorithms Constrained optimization Unconstrained optimization Engineering design problems

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Recent Advances of Chimp Optimization Algorithm:Variants and Applications

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Journal of Bionic Engineering 2023年第6期20卷 2840-2862页

作者： Mohammad Sh.Daoud Mohammad Shehab Laith abualigah Mohammad Alshinwan Mohamed Abd Elaziz Mohd Khaled Yousef Shambour Diego Oliva Mohammad AAlia raed abu zitar College of Engineering Al Ain University112612Abu DhabiUnited Arab Emirates College of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Custodian of the Two Holy Mosques Institute for Haj and Umrah Research Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio'n Basada en la Informacio'n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber Security Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates School of Engineering and Technology Sunway University Malaysia27500Petaling JayaMalaysia

Chimp Optimization Algorithm(ChOA)is one of the recent metaheuristics swarm intelligence *** has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods:it has very few parameters,and no derivation information is required in the initial ***,it is simple,easy to use,flexible,scalable,and has a special capability to strike the right balance between exploration and exploitation during the search which leads to favorable ***,the ChOA has recently gained a very big research interest with tremendous audiences from several domains in a very short ***,in this review paper,several research publications using ChOA have been overviewed and ***,introductory information about ChOA is provided which illustrates the natural foundation context and its related optimization conceptual *** main operations of ChOA are procedurally discussed,and the theoretical foundation is ***,the recent versions of ChOA are discussed in detail which are categorized into modified,hybridized,and paralleled *** main applications of ChOA are also thoroughly *** applications belong to the domains of economics,image processing,engineering,neural network,power and energy,networks,*** of ChOA is also *** review paper will be helpful for the researchers and practitioners of ChOA belonging to a wide range of audiences from the domains of optimization,engineering,medical,data mining,and *** well,it is wealthy in research on health,environment,and public ***,it will aid those who are interested by providing them with potential future research.

关键词： Artificial intelligence Nature-inspired optimization algorithms Chimp optimization algorithm Optimization problems

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Recognition of Arabic Sign Language (ArSL) Using Recurrent Neural Networks

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Journal of Intelligent Learning Systems and Applications 2012年第1期4卷 41-52页

作者： Manar Maraqa Farid Al-Zboun Mufleh Dhyabat raed abu zitar College of Information Technology Ajloun National University Ajloun Jordan College of Information Technology AL Al-Bayt University Mafraq Jordan Department of Management Information Systems Al-Isra’ Private University Amman Jordan School of Engineering and Technology New York Institute of Technology Amman Jordan.

The objective of this research is to introduce the use of different types of neural networks in human hand gesture recognition for static images as well as for dynamic gestures. This work focuses on the ability of neural networks to assist in Arabic Sign Language (ArSL) hand gesture recognition. We have presented the use of feedforward neural networks and recurrent neural networks along with its different architectures;partially and fully recurrent networks. Then we have tested our proposed system;the results of the experiment have showed that the suggested system with the fully recurrent architecture has had a performance with an accuracy rate 95% for static gesture recognition.

关键词： Arabic Sign Language Feedforward Neural Networks Recurrent Neural Networks Gesture Recognition

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Advancing male age differentially alters levels and localization patterns of PLCzeta in sperm and testes from different mouse strains

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Asian Journal of Andrology 2021年第2期23卷 178-187页

作者： Junaid Kashir Bhavesh V Mistry Maha Adel Gumssani Muhammad Rajab Reema abu-Dawas Falah AlMohanna Michail Nomikos Celine Jones raed abu-Dawud Nadya Al-Yacoub Kevin Coward F Anthony Lai Abdullah M Assiri 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 Research Centre Qatar UniversityDoha PO Box 2713Qatar

Sperm-specific phospholipase C zeta(PLCζ)initiates intracellular calcium(Ca2+)transients which drive a series of concurrent events collectively termed oocyte *** investigations have linked abrogation and absence/reduction of PLCζwith forms of male infertility in humans where oocyte activation ***,very few studies have examined potential relationships between PLCζand advancing male age,both of which are increasingly considered to be major effectors of male *** efforts in humans may be hindered by inherent PLCζvariability within the human population,alongside a lack of sufficient controllable ***,utilizing immunoblotting,immunofluorescence,and quantitative reverse transcription PCR(qRT-PCR)we examined for the first time PLCζprotein levels and localization patterns in sperm,and PLCζmRNA levels within testes,from mice at 8 weeks,12 weeks,24 weeks,and 36 weeks of age,from two separate strains of mice,C57BL/6(B6;inbred)and CD1(outbred).Collectively,advancing male age generally diminished levels and variability of PLCζprotein and mRNA in sperm and testes,respectively,when both strains were ***,advancing male age altered the predominant pattern of PLCζlocalization in mouse sperm,with younger mice exhibiting predominantly post-acrosomal,and older mice exhibiting both post-acrosomal and acrosomal populations of PLCζ.However,the specific pattern of such decline in levels of protein and mRNA was ***,our results demonstrate a negative relationship between advancing male age and PLCζlevels and localization patterns,indicating that aging male mice from different strains may serve as useful models to investigate PLCζin cases of male infertility and subfertility in humans.

关键词： ageing fertilization male infertility oocyte activation phospholipase C zeta sperm

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Determination of Antibiotic Drug Cefdinir in Human Plasma Using Liquid Chromatography Tandem Mass Spectroscopy

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American Journal of Analytical Chemistry 2015年第3期6卷 239-245页

作者： Mohammad A. Al Bayyari raed S. abu Ajjour College of Science and Health Professions King Saud Bin Abdulaziz University for Health Sciences National Guard Health Affairs Jeddah KSA Bioanalytical Laboratory International Pharmaceutical Research Center Amman Jordan

The following article has been retracted due to the investigation of complaints received against it. The Editorial Board found that there are conflicts of interests between the authors and their organization. The scientific community takes a very strong view on this matter, and the American Journal of Analytical Chemistry treats all unethical behavior seriously. This paper published in Vol. 6 No. 3 239-254, 2015 has been removed from this site. Title: Determination of Antibiotic Drug Cefdinir in Human Plasma Using Liquid Chromatography Tandem Mass Spectroscopy Author: Mohammad A. Al Bayyari, raed S. abu

关键词： Cefdinir HPLC-MS/MS Plasma ESI Source Positive Ion Mode MRM Mode

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Single and Mitochondrial Gene Inheritance Disorder Prediction Using Machine Learning

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

作者： Muhammad Umar Nasir Muhammad Adnan Khan Muhammad Zubair Taher MGhazal raed A.Said Hussam Al Hamadi Riphah School 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 School of Information Technology Skyline University CollegeSharjah1797UAE Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and Technology Universiti Kebangsaan Malaysia43600Malaysia Canadian University Dubai00000UAE Cyber-Physical Systems Khalifa UniversityAbu Dhabi127788UAE

One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic ***,the complicated genetic disease has a very diverse genotype,making it challenging to find genetic *** is a challenging process since it must be completed effectively and *** research article focuses largely on which patients are more likely to have a genetic disorder based on numerous medical *** the patient’s medical history,we used a genetic disease prediction algorithm that predicts if the patient is likely to be diagnosed with a genetic *** predict and categorize the patient with a genetic disease,we utilize several deep and machine learning techniques such as Artificial neural network(ANN),K-nearest neighbors(KNN),and Support vector machine(SVM).To enhance the accuracy of predicting the genetic disease in any patient,a highly efficient approach was utilized to control how the model can be *** predict genetic disease,deep and machine learning approaches are *** most productive tool model provides more precise *** simulation results demonstrate that by using the proposed model with the ANN,we achieve the highest model performance of 85.7%,84.9%,84.3%accuracy of training,testing and validation *** approach will undoubtedly transform genetic disorder prediction and give a real competitive strategy to save patients’lives.

关键词： Genetic disorder machine learning deep learning single gene inheritance gene disorder mitochondrial gene inheritance disorder

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