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Using the Taguchi Method and Grey Relational Analysis to Optimize the Performance of a Solar Air Heater

Energy Engineering 2021年第5期118卷 1425-1438页

作者： manar b.al-hajji Nabeel Abu Shaban Shahnaz al Khalil Ayat al-Jarrah Department of Mechanical Engineering School of EngineeringThe University of JordanAmmanJordan Department of Mechanical Engineering Faculty of Engineering and Technology Al-Zaytonah University of JordanAmmanJordan Department of Mechatronics Engineering Faculty of EngineeringThe Hashemite UniversityZarqa’Jordan

Solar energy is regarded as one of the promising renewable energy sources in the *** main aim of this study is to use the Taguchi-Grey relational grade analysis to optimize the performance of two Solar Air Heaters(SAHs).A typical Grey–Taguchi method was *** Orthogonal Array,Signal-to-Noise ratio,Grey Relational Grade,and Analysis of Variance were employed to investigate the performance characteristics of *** observations were made in agreement with Jordanian climate 32°00′N latitude and 36°00′E longitude with a solar intensity of 500 W\m^(2).The operating factors selected for optimization are the tilt angle(T)with three levels(0°,22°,45°),inlet velocity(V)with two levels(1.2,1.8 m/s),and absorber plate material(M)with two levels(aluminum,wood).In this study,the Grey–Taguchi approach is validated by performing 12 individual *** results show that the process factors sequence required for a maximum SAH efficiency(SAHµ)is V>T>*** this approach,we combined the Orthogonal Array design with Grey Relational *** a result of that,the level of each operating conditions which optimizes both process responses(Temperature difference,ΔT and Solar air heater efficiency,SAHµ)can be specified with a minimum number of tests compared with classic Grey Relational *** optimal operating conditions of a SAH for multiple performance characteristics are determined as T2,M2,and V2,respectively,which are in congruence with the experimental results.

关键词： Solar air heater collector efficiency thermal efficiency grey-taguchi method robust design

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Sailfish Optimizer with Deep Transfer Learning-Enabled Arabic Handwriting Character Recognition

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Computers, Materials & Continua 2023年第3期74卷 5467-5482页

作者： Mohammed Maray badriyya b.al-onazi Jaber S.alzahrani Saeed Masoud alshahrani Najm alotaibi Sana alazwari Mahmoud Othman manar Ahmed Hamza Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Prince Saud alFaisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The recognition of the Arabic characters is a crucial task incomputer vision and Natural Language Processing fields. Some major complicationsin recognizing handwritten texts include distortion and patternvariabilities. So, the feature extraction process is a significant task in NLPmodels. If the features are automatically selected, it might result in theunavailability of adequate data for accurately forecasting the character ***, many features usually create difficulties due to high dimensionality *** this background, the current study develops a Sailfish Optimizer withDeep Transfer Learning-Enabled Arabic Handwriting Character Recognition(SFODTL-AHCR) model. The projected SFODTL-AHCR model primarilyfocuses on identifying the handwritten Arabic characters in the inputimage. The proposed SFODTL-AHCR model pre-processes the input imageby following the Histogram Equalization approach to attain this *** Inception with ResNet-v2 model examines the pre-processed image toproduce the feature vectors. The Deep Wavelet Neural Network (DWNN)model is utilized to recognize the handwritten Arabic characters. At last,the SFO algorithm is utilized for fine-tuning the parameters involved in theDWNNmodel to attain better performance. The performance of the proposedSFODTL-AHCR model was validated using a series of images. Extensivecomparative analyses were conducted. The proposed method achieved a maximum accuracy of 99.73%. The outcomes inferred the supremacy of theproposed SFODTL-AHCR model over other approaches.

关键词： Arabic language handwritten character recognition deep learning feature extraction hyperparameter tuning

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Automated Arabic Text Classification Using Hyperparameter Tuned Hybrid Deep Learning Model

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Computers, Materials & Continua 2023年第3期74卷 5447-5465页

作者： badriyya b.al-onazi Saud S.alotaib Saeed Masoud alshahrani Najm alotaibi Mrim M.alnfiai Ahmed S.Salama manar Ahmed Hamza Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Prince Saud alFaisal Institute for Diplomatic Studies Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The text classification process has been extensively investigated in various languages,especially *** classification models are vital in several Natural Language Processing(NLP)*** Arabic language has a lot of *** instance,it is the fourth mostly-used language on the internet and the sixth official language of ***,there are few studies on the text classification process in Arabic.A few text classification studies have been published earlier in the Arabic *** general,researchers face two challenges in the Arabic text classification process:low accuracy and high dimensionality of the *** this study,an Automated Arabic Text Classification using Hyperparameter Tuned Hybrid Deep Learning(AATC-HTHDL)model is *** major goal of the proposed AATC-HTHDL method is to identify different class labels for the Arabic *** first step in the proposed model is to pre-process the input data to transform it into a useful *** Term Frequency-Inverse Document Frequency(TF-IDF)model is applied to extract the feature ***,the Convolutional Neural Network with Recurrent Neural Network(CRNN)model is utilized to classify the Arabic *** the final stage,the Crow Search algorithm(CSA)is applied to fine-tune the CRNN model’s hyperparameters,showing the work’s *** proposed AATCHTHDL model was experimentally validated under different parameters and the outcomes established the supremacy of the proposed AATC-HTHDL model over other approaches.

关键词： Hybrid deep learning natural language processing arabic language text classification parameter tuning

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Computational Linguistics with Optimal Deep belief Network based Irony Detection in Social Media

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Computers, Materials & Continua 2023年第5期75卷 4137-4154页

作者： manar Ahmed Hamza Hala J.alshahrani Abdulkhaleq Q.A.Hassan Abdulbaset Gaddah Nasser allheeib Suleiman ali alsaif badriyya b.al-onazi Heba Mohsen 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 English College of Science and Arts at MahayilKing Khalid UniversityAbha62217Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Department of Computer Deanship of Preparatory Year and Supporting StudiesImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Computational linguistics refers to an interdisciplinary field associated with the computational modelling of natural language and studying appropriate computational methods for linguistic *** number of social media users has been increasing over the last few years,which have allured researchers’interest in scrutinizing the new kind of creative language utilized on the Internet to explore communication and human opinions in a *** and sarcasm detection is a complex task inNatural Language Processing(NLP).Irony detection has inferences in advertising,sentiment analysis(SA),and opinion *** the last few years,irony-aware SA has gained significant computational treatment owing to the prevalence of irony in web ***,this study develops Computational Linguistics with Optimal Deep belief Network based Irony Detection and Classification(CLODbN-IRC)model on social *** presented CLODbN-IRC model mainly focuses on the identification and classification of irony that exists in social *** attain this,the presented CLODbN-IRC model performs different stages of pre-processing and TF-IDF feature *** irony detection and classification,the DbN model is exploited in this *** last,the hyperparameters of the DbN model are optimally modified by improved artificial bee colony optimization(IAbC)*** experimental validation of the presentedCLODbN-IRCmethod can be tested by making use of benchmark *** simulation outcomes highlight the superior outcomes of the presented CLODbN-IRC model over other approaches.

关键词： Computational linguistics natural language processing deep learning irony detection social media

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Metaheuristic Resource allocation Strategy for Cluster based 6G Industrial Applications

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Computers, Materials & Continua 2022年第4期71卷 667-681页

作者： Anwer Mustafa Hilal Lamia Osman Widaa Fahd N.al-Wesabi Mohammad Medani manar Ahmed Hamza Mesfer al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The emergence of beyond 5G(b5G)and 6G networks translated personal and industrial operations highly effective,reliable,and gainful by speeding up the growth of next generation Internet of Things(IoT).Industrial equipment in 6G encompasses a huge number of wireless sensors,responsible for collecting massive quantities of *** the same time,6G network can take real-world intelligent decisions and implement automated equipment *** the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be *** has become mandatory for optimal resource allocation in 6G-enabled industrial *** this scenario,the current research paper introduces a new metaheuristic resource allocation strategy for clusterbased 6G industrial applications,named MRAS-CbIA *** technique aims at accomplishing energy efficiency and optimal resource allocation in 6G-enabled industrial *** proposed MRAS-CbIR technique involves three major ***,Weighted Clustering Technique(WCT)is employed to elect the optimal Cluster Heads(CHs)or coordinating agents with the help of three parameters namely,residual energy,distance,and node ***,Decision Tree-based Location Prediction(DTLP)mechanism is applied to determine the exact location of Management Agent(MA).Finally,Fuzzy C-means with Tunicate Swarm algorithm(FCMTSA)is used for optimal resource allocation in 6G industrial *** performance of the proposed MRAS-CbIA technique was validated and the results were examined under different *** resultant experimental values highlighted the superior performance of MRAS-CbIR technique over existing state-of-the-art methods.

关键词： 6G industrial internet of things energy efficiency resource allocation metaheuristics

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An empirical study on the complexity, security and maintainability of Ethereum-based decentralized applications (DApps)

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blockchain(Research and Applications) 2023年第2期4卷 28-40页

作者： Noama Fatima Samreen manar H.alalfi Department of Computer Science Toronto Metropolitan UniversityTorontoON M5B 2K3Canada

The Ethereum blockchain’s smart contract is a programmable transaction that performs general-purpose computations and can be executed automatically on the *** this component,blockchain technology(bT)has grown beyond the scope of cryptocurrencies and can now be applicable in various industries other than *** this paper,we investigated the current trends in Ethereum-based decentralized applications(DApps)to be able to categorize and analyze the DApps to measure the complexity of smart contracts behind them,their level of security and their correlation to the maintainability of the *** leveraged the source code analysis,security analysis,and the developmental metadata of the DApps to infer this *** on our findings,we concluded that the maintainability of Ethereum DApps is proportional to the code size,number of functions,and,most importantly,the number of outgoing invocations and statements in the smart contracts.

关键词： blockchain technology Ethereum smart contracts Code metrics Software complexity Software security Software maintainability Decentralized applications

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Hybridization of Metaheuristics based Energy Efficient Scheduling algorithm for Multi-Core Systems

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Computer Systems Science & Engineering 2023年第1期44卷 205-219页

作者： J.Jean Justus U.Sakthi K.Priyadarshini b.Thiyaneswaran Masoud alajmi Marwa Obayya manar Ahmed Hamza Department of Computer Science&Engineering St.Joseph’s College of EngineeringChennai600119India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai602105India Department of Electronics and Communication Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Electronics and Communication Engineering Sona College of TechnologySalem636005India Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The developments of multi-core systems(MCS)have considerably improved the existing technologies in thefield of computer *** MCS comprises several processors that are heterogeneous for resource capacities,working environments,topologies,and so *** existing multi-core technology unlocks additional research opportunities for energy minimization by the use of effective task *** the same time,the task scheduling process is yet to be explored in the multi-core *** paper presents a new hybrid genetic algorithm(GA)with a krill herd(KH)based energy-efficient scheduling techni-que for multi-core systems(GAKH-SMCS).The goal of the GAKH-SMCS tech-nique is to derive scheduling tasks in such a way to achieve faster completion time and minimum energy *** GAKH-SMCS model involves a multi-objectivefitness function using four parameters such as makespan,processor utilization,speedup,and energy consumption to schedule tasks *** performance of the GAKH-SMCS model has been validated against two datasets namely random dataset and benchmark *** experimental outcome ensured the effectiveness of the GAKH-SMCS model interms of makespan,pro-cessor utilization,speedup,and energy *** overall simulation results depicted that the presented GAKH-SMCS model achieves energy effi-ciency by optimal task scheduling process in MCS.

关键词： Task scheduling energy efficiency multi-core systems fitness function makespan

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Anticancer activity of Cyanothece sp. strain extracts from Egypt: First record

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Asian Pacific Journal of Tropical biomedicine 2015年第12期5卷 992-995页

作者： Nermin Adel El Semary manar Fouda Department of botany and Microbiology Faculty of Science Helwan University Department of Chemistry Faculty of Science Helwan University

Objective:To assess the anticancer activity of eight cyanobacterial hydrophilic extracts on Ehrlich ascites carcinoma cell ***:The cyanobacterial strains used in the investigation were collected from diverse habitats in *** initial cytotoxicity test of cyanobacterial hydrophilic extracts was carried out by MTT *** in vitro anticancer activity of the four most active extracts was performed on MCF-7 cells using sulforhodamine b *** and molecular techniques were used to characterise identity of the isolate from which the most potent cytotoxic extract was ***:Extracts from four cyanobacterial strains had higher cytotoxic activities scoring76.68%,77.70%,76.70%and 74.45%,respectively.A considerable anticancer effect was only detected when the concentrated extracts were *** cyanobacterial extract gave the highest anticancer activity on human breast adenocarcinoma cell line(57.6%of inhibition)as compared to *** isolate was best-matched to Cyanothece *** sequence resemblance 98%to Cyanothece *** PCC7564 and the phylogenetic analysis confirmed its close identity to the Cyanothece ***:This is the first study to report the anticancer effect of aqueous extracts derived from the unicellular Cyanothece *** Egypt and its potential as a plausible candidate for future mass biotechnological applications.

关键词： Anticancer Cell line Cyanothece Hydrophilic extrac

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Unique Solution of Integral Equations via Intuitionistic Extended Fuzzy b-Metric-Like Spaces

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 109-131页

作者： Naeem Saleem Khalil Javed Fahim Uddin Umar Ishtiaq Khalil Ahmed Thabet Abdeljawad manar A.alqudah Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Math&Stats International Islamic University IslamabadIslamabad44000Pakistan Abdus Salam School of Mathematical Sciences Government College UniversityLahore54600Pakistan Office of Research Innovation and CommercializationUniversity of Management and TechnologyLahore54770Pakistan Department of Mathematics and Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematical Sciences Faculty of SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this manuscript,our goal is to introduce the notion of intuitionistic extended fuzzy b-metric-like *** establish some fixed point theorems in this ***,we plot some graphs of an example of obtained result for better *** use the concepts of continuous triangular norms and continuous triangular conorms in an intuitionistic fuzzy metric-like *** norms are used to generalize with the probability distribution of triangle inequality in metric space *** conorms are known as dual operations of triangular *** obtained results boost the approaches of existing ones in the literature and are supported by some examples and applications.

关键词： Fixed point extended fuzzy b-metric like space intuitionistic extended fuzzy b-metric-like space integral equation

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Cat and Mouse Optimizer with Artificial Intelligence Enabled biomedical Data Classification

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Computer Systems Science & Engineering 2023年第3期44卷 2243-2257页

作者： b.Kalpana S.Dhanasekaran T.Abirami Ashit Kumar Dutta Marwa Obayya Jaber S.alzahrani manar Ahmed Hamza Department of Information Technology RMD Engineering CollegeChennai601206India Department of Information Technology Kalasalingam Academy of Research and EducationSrivilliputtur626126India Department of Information Technology Kongu Engineering CollegeErode638060India Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

biomedical data classification has become a hot research topic in recent years,thanks to the latest technological advancements made in ***-dical data is usually examined by physicians for decision making process in patient *** manual diagnosis is a tedious and time consuming task,numerous automated models,using Artificial Intelligence(AI)techniques,have been presented so *** this motivation,the current research work presents a novel biomedical Data Classification using Cat and Mouse based Optimizer with AI(bDC-CMbOAI)*** aim of the proposed bDC-CMbOAI technique is to determine the occurrence of diseases using biomedical ***,the proposed bDC-CMbOAI technique involves the design of Cat and Mouse Optimizer-based Feature Selection(CMbO-FS)technique to derive a useful subset of *** addition,Ridge Regression(RR)model is also utilized as a classifier to identify the existence of *** novelty of the current work is its designing of CMbO-FS model for data ***,CMbO-FS technique is used to get rid of unwanted features and boosts the classification *** results of the experimental analysis accomplished by bDC-CMbOAI technique on benchmark medical dataset established the supremacy of the proposed technique under different evaluation measures.

关键词： Artificial intelligence biomedical data feature selection cat and mouse optimizer ridge regression

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