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Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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Computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed A.Aziz Manar ahmed Hamza Abdelwahed Motwakel Abu Sarwar Zamani ishfaq Yaseen Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime

Locomotion of Bioinspired Underwater Snake Robots Using Metaheuristic Algorithm

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Computers, Materials & Continua 2022年第7期72卷 1293-1308页

作者： Souad Larabi-Marie-Sainte Taiseer Abdalla Elfadil Eisa Fahd N.Al-Wesabi Amani Abdulrahman Albraikan Manar ahmed Hamza Abdelwahed Motwakel ishfaq Yaseen Mesfer Al Duhayyim Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid University62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a1247Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University11564Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz University16278Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia

Snake Robots(SR)have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments,a characteristic not found in other kinds of robots(like wheeled or legged robots).Underwater Snake Robots(USR)establish a bioinspired solution in the domain of underwater *** is a key challenge to increase the motion efficiency in underwater robots,with respect to forwarding speed,by enhancing the locomotion *** the same time,energy efficiency is also considered as a crucial issue for long-term automation of the *** this aspect,the current research paper concentrates on the design of effectual Locomotion of Bioinspired Underwater Snake Robots using Metaheuristic Algorithm(LBIUSR-MA).The proposed LBIUSR-MA technique derives a bi-objective optimization problem to maximize the ForwardVelocity(FV)and minimize the Average Power Consumption(APC).LBIUSR-MA technique involves the design ofManta Ray Foraging Optimization(MRFO)technique and derives two objective functions to resolve the optimization *** addition to these,effective weighted sum technique is also used for the integration of two objective ***,the objective functions are required to be assessed for varying gait variables so as to inspect the performance of locomotion.A detailed set of simulation analyses was conducted and the experimental results demonstrate that the developed LBIUSR-MA method achieved a low Average Power Consumption(APC)value of 80.52W underδvalue of *** proposed model accomplished the minimum PAC and maximum FV of USR in an effective manner.

关键词： Bio-inspired robots underwater snake robots locomotion efficiency forwarding velocity average power consumption objective function

Optimal Deep Learning Enabled Communication System for Unmanned Aerial Vehicles

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Computer Systems Science & Engineering 2023年第4期45卷 955-969页

作者： Anwer Mustafa Hilal Jaber S.Alzahrani Dalia H.Elkamchouchi Majdy M.Eltahir ahmed S.Almasoud Abdelwahed Motwakel Abu Sarwar Zamani ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia

Recently,unmanned aerial vehicles(UAV)or drones are widely employed for several application areas such as surveillance,disaster management,*** UAVs are limited to energy,efficient coordination between them becomes essential to optimally utilize the resources and effective communication among them and base station(BS).Therefore,clustering can be employed as an effective way of accomplishing smart communication systems among multiple *** this aspect,this paper presents a group teaching optimization algorithm with deep learning enabled smart communication system(GTOADL-SCS)technique for UAV *** proposed GTOADL-SCS model encompasses a two stage process namely clustering and *** the initial stage,the GTOADL-SCS model includes a GTOA based clustering scheme to elect cluster heads(CHs)and organize ***,the GTOADL-SCS model develops a fitness function containing three input parameters as residual energy of UAVs,average neighoring distance,and UAV *** classification process,the GTOADLSCS model applies pre-trained densely connected network(DenseNet201)feature extractor with gated recurrent unit(GRU)*** ensuring the enhanced performance of the GTOADL-SCS model,a widespread simulation analysis is performed and the comparative study reported the significant outcomes over the existing approaches with maximum packet delivery ratio(PDR)of 92.60%.

关键词： Unmanned aerial vehicles energy efficiency smart communication system deep learning

Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

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Computer Systems Science & Engineering 2023年第5期45卷 1759-1773页

作者： Manar ahmed Hamza Haya Mesfer Alshahrani Sami Dhahbi Mohamed K Nour Mesfer Al Duhayyim ElSayed M.Tag El Din ishfaq Yaseen Abdelwahed Motwakel Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt

Wireless Sensor Networks(WSN)has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of *** spite of this,it is challenging to design energy-efficient *** routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of *** order to solve the restricted energy problem,it is essential to reduce the energy utilization of data,transmitted from the routing protocol and improve network *** this background,the current study proposes a novel Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-hop Routing Protocol(DEAOA-MHRP)for *** aim of the proposed DEAOA-MHRP model is select the optimal routes to reach the destination in *** accomplish this,DEAOA-MHRP model initially integrates the concepts of Different Evolution(DE)and Arithmetic Optimization Algorithms(AOA)to improve convergence rate and solution ***,the inclusion of DE in traditional AOA helps in overcoming local optima *** addition,the proposed DEAOA-MRP technique derives a fitness function comprising two input variables such as residual energy and *** order to ensure the energy efficient performance of DEAOA-MHRP model,a detailed comparative study was conducted and the results established its superior performance over recent approaches.

关键词： Wireless sensor network routing multihop communication arithmetic optimization algorithm fitness function

Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

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Computers, Materials & Continua 2022年第8期72卷 3113-3129页

作者： Murad A.A.Almekhlafi Fahd N.Al-Wesabi Majdy M.Eltahir Anwer Mustafa Hilal Amin M.El-Kustaban Abdelwahed Motwakel ishfaq Yaseen Manar ahmed Hamza Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science King Khalid UniversityMuhayelAseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayelAseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Electronic Department Faculty of EngineeringUniversity of Science and TechnologySana’aYemen

Energy is an essential element for any civilized country’s social and economic development,but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the *** Republic of Yemen has very good potential to use renewable ***,we find few studies on renewable wind energy in *** the lack of a similar analysis for the coastal city,this research newly investigates wind energy’s potential near the Almukalla area by analyzing wind ***,evaluation,model identification,determination of available energy density,computing the capacity factors for several wind turbines and calculation of wind energy were extracted at three heights of 15,30,and *** wind speeds were obtained only for the currently available data of five recent years,2005–*** study involves a preliminary assessment of Almukalla’s wind energy potential to provide a primary base and useful insights for wind engineers and *** research aims to provide useful assessment of the potential of wind energy in Almukalla for developing wind energy and an efficient wind *** Weibull distribution shows a perfect approximation for estimating the intensity of Yemen’s wind *** on both theWeibullmodel and the results of the annual wind speed data analysis for the study site in Mukalla,the capacity factor for many turbines was also calculated,and the best suitable turbine was *** to the International Wind Energy Rating criteria,Almukalla falls under Category 7,which is,rated“Superb”most of the year.

关键词： Almukalla energy potential Rayleigh distribution Weibull distribution wind power density wind speed

Optimal Quad Channel Long Short-Term Memory Based Fake News Classification on English Corpus

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Computer Systems Science & Engineering 2023年第9期46卷 3303-3319页

作者： Manar ahmed Hamza Hala J.Alshahrani Khaled Tarmissi Ayman Yafoz Amal S.Mehanna ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The term‘corpus’refers to a huge volume of structured datasets containing machine-readable *** texts are generated in a natural communicative *** explosion of social media permitted individuals to spread data with minimal examination and filters *** to this,the old problem of fake news has *** has become an important concern due to its negative impact on the *** manage the spread of fake news,automatic recognition approaches have been investigated earlier using Artificial Intelligence(AI)and Machine Learning(ML)*** perform the medicinal text classification tasks,the ML approaches were applied,and they performed quite ***,a huge effort is required from the human side to generate the labelled training *** recent progress of the Deep Learning(DL)methods seems to be a promising solution to tackle difficult types of Natural Language Processing(NLP)tasks,especially fake news *** unlock social media data,an automatic text classifier is highly helpful in the domain of *** current research article focuses on the design of the Optimal Quad ChannelHybrid Long Short-Term Memory-based Fake News Classification(QCLSTM-FNC)*** presented QCLSTM-FNC approach aims to identify and differentiate fake news from actual *** attain this,the proposed QCLSTM-FNC approach follows two methods such as the pre-processing data method and the Glovebased word embedding ***,the QCLSTM model is utilized for *** boost the classification results of the QCLSTM model,a Quasi-Oppositional Sandpiper Optimization(QOSPO)algorithm is utilized to fine-tune the *** proposed QCLSTM-FNC approach was experimentally validated against a benchmark *** QCLSTMFNC approach successfully outperformed all other existing DL models under different measures.

关键词： English corpus fake news detection social media natural language processing artificial intelligence deep learning

A high-throughput data analysis and materials discovery tool for strongly correlated materials

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npj Computational Materials 2018年第1期4卷 138-146页

作者： Hasnain hafiz Adnan Ibne Khair Hongchul Choi Abdullah Mueen Arun Bansil Stephan Eidenbenz John Wills Jian-Xin Zhu Alexander V.Balatsky Towfiq ahmed Department of Physics Northeastern UniversityBostonMA 02119USA Department of Computer Science University of New MexicoAlbuquerqueNM 87131USA Theoretical Division Los Alamos National LaboratoryLos AlamosNM 87545USA The Information Science and Technology Institute Los Alamos National LaboratoryLos AlamosNM 87545USA Nordita KTH Royal Institute of Technology and Stockholm UniversityRoslagstullsbacken 23Stockholm SE-10691Sweden Department of Physics University of ConnecticutStorrsCT 06269USA Department of Mechanical Engineering Carnegie Mellon UniversityPittsburghPA 15213USA

Modeling of f-electron systems is challenging due to the complex interplay of the effects of spin–orbit coupling,electron–electron interactions,and the hybridization of the localized f-electrons with itinerant conduction *** complexity drives not only the richness of electronic properties but also makes these materials suitable for diverse technological *** this context,we propose and implement a data-driven approach to aid the materials discovery *** deploying state-of-the-art algorithms and query tools,we train our learning models using a large,simulated dataset based on existing actinide and lanthanide *** machine-learned models so obtained can then be used to search for new classes of stable materials with desired electronic and physical *** discuss the basic structure of our f-electron database,and our approach towards cleaning and correcting the structure data *** examples of the applications of our database include successful prediction of stable superstructures of double perovskites and identification of a number of physically-relevant trends in strongly correlated features of f-electron based materials.

关键词： database desired conduction

Oxidative Stress and Dyslipidemia as Indicators of Pathogenesis of Preeclampsia in Pregnant Sudanese Women

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Journal of Biosciences and Medicines 2018年第7期6卷 48-65页

作者： hafiz ahmed Hobiel Hani Yousif Zaki Tadros Department of Biochemistry Faculty of Medicine and Health Sciences West Kordofan University Elnihoud Sudan Department of Biochemistry and Nutrition Faculty of Medicine Gezira University Medani Sudan

Background: Preeclampsia (PE) still ranks as one of obstetrics major problems and is still a serious threat, mainly in underdeveloped countries where its incidence and mortality rates are higher and is a major cause of preterm birth and intra-uterine growth restriction. Aim: To evaluate the role of oxidative stress and dyslipidemia as indicators of pathogenesis and risks of preeclampsia in pregnant Sudanese women attending Wad-Medani Obstetrics and Gynecology Teaching Hospital. Material and Method: This was a cross-sectional (case-control) study carried out in preeclamptic pregnant Sudanese women attending Wad-Medani Obstetrics and Gynecology Teaching Hospital. A total of 208 pregnant women were enrolled in the study, 111 patients and 97 women with normal pregnancy as controls;pregnant women suffering from any systemic or endocrine disorder were excluded. We compared the serum levels of total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides, nitric oxide, and total antioxidant capacity between preeclamptic and controls. Result and Conclusion: Pregnant women with increase in BMI have a higher chance of developing PE. Low level of high-density lipoprotein cholesterol and high level of low-density lipoprotein cholesterol define that dyslipidemia increases the risk of PE. Decreased levels of NO and TAC might reflect the oxidative stress and likely contribute to the pathophysiological mechanisms of PE.

关键词： Preeclampsia Oxidative Stress Total Antioxidant Capacity Nitric Oxide Dyslipidemia