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Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator

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Computers, materials & Continua 2022年第1期70卷 505-521页

作者： Summra Saleem m.Usman Ghani Khan Tanzila Saba ibrahim Abunadi Amjad Rehman Saeed Ali Bahaj Department of Computer Science UETLahorePakistan Al-Khwarizmi Institute of Computer Science UETLahorePakistan Artificial Intelligence&Data Analytics Lab CCIS Prince Sultan University Riyadh11586Saudi Arabia mIS Department College of Business Administration Prince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia

Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal *** Edge GAN,the major contribution is attribute guided vector that enables high visual quality content *** research study proposes automatic face image realism from freehand sketches based on Edge *** propose a density variant image synthesis model,allowing the input sketch to encompass face features with minute *** density level is projected into non-latent space,having a linear controlled function *** assists the user to appropriately devise the variant densities of facial sketches and image *** data set of Large Scale CelebFaces Attributes(ClebA),Labelled Faces in theWild(LFWH),Chinese University of Hong Kong(CHUK),and self-generated Asian images are used to evaluate the proposed *** solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation.

关键词： Edge generator density variant sketch generator face translation recognition residual block

Effects of constant light and dark conditions on the locomotor activity,body mass,and body temperature rhythms of Eurasian Tree Sparrows(Passer montanus)

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Avian Research 2023年第3期14卷 435-442页

作者： Lirong Zuo ibrahim mAhmad Yuanyuan Liu Limin Wang Shu Fang Dongming Li Hebei Key Laboratory of Animal Physiology Biochemistry and Molecular BiologyCollege of Life SciencesHebei Normal UniversityShijiazhuang050024Hebei ProvinceChina Hebei Collaborative Innovation Center for Eco-Environment Hebei Normal UniversityShijiazhuang050024China

Light is an essential environmental cue influencing the endogenous circadian clocks that regulate behavioral and physiological processes in *** extensive research on the circadian rhythms of avian behavior and physiology,the mechanisms by which they adapt and adjust to abnormal photoperiod conditions,such as artificial light,have yet to be fully ***,the circadian rhythms of the body mass,activity,and core and peripheral body temperatures of the Eurasian Tree Sparrow(Passer montanus,ETS)-a diurnal passerine-were examined under three different lighting conditions:constant light(LL),constant darkness(DD),and normal light-dark cycles(LD).Our results showed that the activity,body mass,core,tarsometatarsus,and eye temperatures of the ETSs varied significantly with treatment,time,and the interaction between treatment and time;however,there was no significant change in body mass in response to the interaction between time and *** LD conditions,the ETSs exhibited significant circadian rhythms in activity and core,tarsometatarsus,and eye *** LL conditions,only the core temperature exhibited significant *** DD conditions,there were no significant circadian rhythms in activity,body mass,and eye temperature;however,the core and tarsometatarsus temperatures remained *** results indicate that the core body temperature rhythm of ETS is endogenous and can be maintained under abnormal *** contrast,the activity and body surface temperature,uncoupled from the core body temperature under abnormal photoperiod conditions,strongly depend on *** results differ from those of other diurnal avian species,suggesting a unique coping mechanism of ETS in response to an abnormal photoperiod.

关键词： Eurasian Tree Sparrow Activity Body mass Body temperature Circadian rhythm

An Assessment of Authorized Car Wash Site Suitability Using a GIS-Based modeling in Khartoum City, Sudan

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Journal of Geographic Information System 2022年第2期14卷 134-152页

作者： ibrahim m. Eltom ibrahim Department of Environment and Ecology GIS and RS Applications Faculty of Geographical and Environmental Sciences University of Khartoum Khartoum Sudan

The goal of this study is to assess the ability of existing car washing stations in Khartoum City using an Arcmap suitability modeling tool. methods: In Khartoum, an increasing number of vehicle wash stations were opened every day. The main criteria are street, the slope, the hospitals, the police station, and the school, which have been used to build a model of suitability based on weight overlay in ArcGIS 10.4. The findings revealed two evaluation tendencies. One tendency involves business centers that are located on main roads but are adjacent to residential areas, while another involves business centers that have rezoned residential plots without consideration for ideal site requirements for the environment. There are locations that would be appropriate for vehicle wash centers, according to the final suitability map. On a scale of 1 to 5, less than 30% of the study area is considered suitable for a new car wash regarding class 5. On the other hand, significant areas are available for car wash development in the second value of suitability 4, but as second-ranked suitability. The assessment was accomplished by comparing the final suitability map of car washing centers to the layers which represented them.

关键词： Car Wash Centers Suitability Analysis Suitability modeling Criteria

Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

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Computers, materials & Continua 2022年第5期71卷 2599-2616页

作者： muhammad ibrahim Faisal Jamil YunJung Lee DoHyeun Kim Big Data Research Center Department of Computer Science and StatisticsJeju National UniversityKoreaJeju-si63243Korea Department of Computer Engineering(and Advanced Technology Research Institute) Jeju National UniversityJeju 63243Korea

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security *** IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,*** these applications,fitness applications have been widely considered for smart fitness *** users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness ***,scheduling such a huge number of requests for fitness exercise is a big ***,the user fitness data is critical thus securing the user fitness data from unauthorized access is also *** overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling *** proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource *** performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection *** obtained results confirm the efficiency of the proposed scheduling *** investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource *** Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches *** obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

关键词： Load balancing resource scheduling task scheduling Internet of things blockchain fitness applications

Evaluation of On-Line mPPT Algorithms for PV-Based Battery Storage Systems

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Computers, materials & Continua 2022年第11期73卷 3595-3611页

作者： Belqasem Aljafari Eydhah Almatrafi Sudhakar Babu Thanikanti Sara A.ibrahim mohamed A.Enany marwa m.Ahmed Electrical Engineering Department College of EngineeringNajran UniversityNajran11001Saudi Arabia mechanical Engineering Department College of Engineering-RabighKing Abdulaziz UniversityJeddahSaudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Desalination Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of TechnologyHyderabad500075India Electrical Power and machines Department Faculty of EngineeringZagazig UniversityZagazig44519Egypt Electrical Engineering Department Faculty of EngineeringKing Abdul-Aziz UniversityJeddah80204Saudi Arabia

This paper presents a novel Simulink models with an evaluation study of more widely used On-Line maximum Power Point tracking(mPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comparative study in terms of the dynamic response,battery state of charge(SOC),and oscillations around the maximum Power Point(mPP)of the PV-BSS to variations in climate conditions,these techniques are simulated in matlab/*** introduced methodologies are classified into two types;the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb&Observe and Incremental Conductance *** second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre-build Adaptive Neuro-Fuzzy Inference System(ANFIS)model to predict DC–DC converter optimum duty cycle to track *** evaluation study is introduced for conventional and proposed On-Line mPPT *** comparative study can be useful in specifying the appropriateness of the mPPT techniques for *** the introduced model can be used as a valued reference model for future research related to Soft Computing(SC)mPPT techniques.A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.

关键词： Photo-voltaic based battery storage systems adaptive neuro-fuzzy inference system maximum power point tracking perturb&observe technique incremental conductance technique state of charge

multi-Tier Sentiment Analysis of Social media Text Using Supervised machine Learning

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Computers, materials & Continua 2023年第3期74卷 5527-5543页

作者： Hameedur Rahman Junaid Tariq m.Ali masood Ahmad F.Subahi Osamah ibrahim Khalaf Youseef Alotaibi Department of Creative Technologies Air UniversityE-9 Islamabad44230Pakistan Department of Computer Science National University of Modern LanguagesRawalpindiPakistan Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia Al-Nahrain Nano-Renewable Energy Research Center Al-Nahrain UniversityBaghdad10072Iraq Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Sentiment Analysis(SA)is often referred to as opinion *** is defined as the extraction,identification,or characterization of the sentiment from ***,the sentiment of a textual document is classified into binary classes i.e.,positive and ***,fine-grained classification provides a better insight into the *** downside is that fine-grained classification is more challenging as compared to *** the contrary,performance deteriorates significantly in the case of multi-class *** this study,pre-processing techniques and machine learning models for the multi-class classification of sentiments were *** augment the performance,a multi-layer classification model has been *** to similitude with social media text,the movie reviews dataset has been used for the *** machine learning models namely Decision Tree,Support Vector machine,and Naive Bayes models have been implemented for the task of sentiment *** have compared the models of single-layer architecture with multi-tier *** results of multi-tier model have slight improvement over the single-layer ***,multi-tier models have better recall which allow our proposed model to learn more *** have discussed certain shortcomings of the model that will help researchers to design multi-tier models with more contextual information.

关键词： Sentiment analysis machine learning multi-class classification svm decision tree naive bayes

An Optimized Ensemble model for Prediction the Bandwidth of metamaterial Antenna

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Computers, materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed ibrahim Hattan F.Abutarboush Ali Wagdy mohamed mohamad Fouad El-Sayed m.El-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(mL)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the metamaterial *** base models are used namely:multilayer Perceptron(mLP)and Support Vector machines(SVm).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

Dipper Throated Optimization for Detecting Black-Hole Attacks inmANETs

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Computers, materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed m.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed ibrahim mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(mANET)continues to be in demand for additional debate and *** more mANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,mANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost mANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-mLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in metamaterial Antenna

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Computers, materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed m.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),multi-Layer Perceptron(mLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： metamaterial antenna dipper throated optimization feature selection parameters prediction