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Compact Bat Algorithm with Deep Learning Model for Biomedical EEG EyeState Classification

Computers, Materials & Continua 2022年第9期72卷 4589-4601页

作者： souad larabi-marie-sainte Eatedal Alabdulkreem Mohammad Alamgeer Mohamed K Nour Anwer Mustafa Hilal Mesfer Al Duhayyim Abdelwahed Motwakel Ishfaq Yaseen Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Electroencephalography(EEG)eye state classification becomes an essential tool to identify the cognitive state of *** can be used in several fields such as motor imagery recognition,drug effect detection,emotion categorization,seizure detection,*** the latest advances in deep learning(DL)models,it is possible to design an accurate and prompt EEG EyeState classification *** this view,this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification(CBADL-BEESC)*** major intention of the CBADL-BEESC technique aims to categorize the presence of EEG *** CBADL-BEESC model performs feature extraction using the ALexNet model which helps to produce useful feature *** addition,extreme learning machine autoencoder(ELM-AE)model is applied to classify the EEG signals and the parameter tuning of the ELM-AE model is performed using *** experimental result analysis of the CBADL-BEESC model is carried out on benchmark results and the comparative outcome reported the supremacy of the CBADL-BEESC model over the recent methods.

关键词： Biomedical signals EEG EyeState classification deep learning metaheuristics

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Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

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Computers, Materials & Continua 2022年第7期72卷 1951-1965页

作者： Manar Ahmed Hamza Abdelzahir Abdelmaboud souad larabi-marie-sainte Haya Mesfer Alshahrani Mesfer Al Duhayyim Hamza Awad Ibrahim Mohammed Rizwanullah Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information Systems College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityP.O.Box No.66833Rafha StreetRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia College of Computer at Al-Gunfudah Umm Al-Qura UniversityAl-Gunfudah24382Saudi Arabia

Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the ***,the quality of test cases has a considerable influence on fault revealing capability of software testing *** Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution *** ismainly intended to design a collection of test cases that can accomplish early optimization using preferred *** studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software *** this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software *** aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution *** addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO *** order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several *** experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

关键词： Software testing harris hawks optimization test case prioritization apfd execution time metaheuristics

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Malware Detection Using Decision Tree Based SVM Classifier for IoT

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Computers, Materials & Continua 2022年第7期72卷 713-726页

作者： Anwer Mustafa Hilal Siwar Ben Haj Hassine souad larabi-marie-sainte Nadhem Nemri Mohamed K.Nour Abdelwahed Motwakel Abu Sarwar Zamani Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The development in Information and Communication Technology has led to the evolution of new computing and communication *** revolution with Internet of Things(IoTs)has developed various applications in almost all domains from health care,education to entertainment with sensors and smart *** of the subsets of IoT is Internet of Medical things(IoMT)which connects medical devices,hardware and software applications through *** enables secure wireless communication over the Internet to allow efficient analysis of medical *** these smart advancements and exploitation of smart IoT devices in health care technology there increases threat and malware attacks during transmission of highly confidential medical *** work proposes a scheme by integrating machine learning approach and block chain technology to detect malware during data transmission in *** proposed Machine Learning based Block Chain Technology malware detection scheme(MLBCT-Mdetect)is implemented in three steps namely:feature extraction,Classification and *** extraction is performed by calculating the weight of each feature and reduces the features with less *** Vector Machine classifier is employed in the second step to classify the malware and benign ***,third step uses blockchain to store details of the selected features which eventually improves the detection of malware with significant improvement in speed and ***-BCT-Mdetect achieves higher accuracy with low false positive rate and higher True positive rate.

关键词： Blockchain malware detection classification feature selection internet of medical things

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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

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Optimal Bidirectional LSTM for Modulation Signal Classification in Communication Systems

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Computers, Materials & Continua 2022年第8期72卷 3055-3071页

作者： Manar Ahmed Hamza Siwar Ben Haj Hassine souad larabi-marie-sainte Mohamed K.Nour Fahd N.Al-Wesabi Abdelwahed Motwakel Anwer Mustafa Hilal Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Modulation signal classification in communication systems can be considered a pattern recognition *** works have focused on several feature extraction approaches such as fractal feature,signal constellation reconstruction,*** recent advent of deep learning(DL)models makes it possible to proficiently classify the modulation *** this view,this study designs a chaotic oppositional satin bowerbird optimization(COSBO)with bidirectional long term memory(BiLSTM)model for modulation signal classification in communication *** proposed COSBO-BiLSTM technique aims to classify the different kinds of digitally modulated *** addition,the fractal feature extraction process takes place by the use of Sevcik Fractal Dimension(SFD)***,the modulation signal classification process takes place using BiLSTM with fully convolutional network(BiLSTM-FCN).Furthermore,the optimal hyperparameter adjustment of the BiLSTM-FCN technique takes place by the use of COSBO *** order to ensure the enhanced classification performance of the COSBO-BiLSTM model,a wide range of simulations were carried *** experimental results highlighted that the COSBO-BiLSTM technique has accomplished improved performance over the existing techniques.

关键词： Complex systems communication system signal processing modulation signals classification artificial intelligence deep learning parameter tuning

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Integrated Evaluation of Soil Erosion Hazard and Risk Management in the Oued Beht Watershed Using Remote Sensing and GIS Techniques: Impacts on El Kansra Dam Siltation (Morocco)

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Journal of Geographic Information System 2014年第6期6卷 677-689页

作者： Rabii El Gaatib Abdelkader larabi Laboratory of Identification and Modelling of Natural Environment (LIMEN) Mohammadia School of Engineers (EMI) Mohammed V University Rabat Morocco

The initial state of the Oued Beht watershed (430,728 ha) is characterized by a socio-ecological vulnerability associated to the water erosion risk. Especially, the consequences are chained and the soil loss alters its hydrological behavior and its ability to protect functional and structural challenges (good land, El Kansra dam, agricultural activities). In this perspective, this study suggests a methodology, reproducible and generalizable, to assess the natural water erosion risk (R). The approach used is based on spatial processing technology of information to develop a spatial database and geographic information system (GIS) concerning biophysical and?topoclimatic parameters in the Oued Beht watershed. Thus, the risk analysis is obtained by combining thematic maps of Susceptibility (S) and potential Consequences (C). Although, the spatial analysis of maps obtained reveals the extent of susceptibility involving land degradation, with the potential risks, which generated a decrease in the storage capacity of El Kansra dam (?3.03 Mm3/year). The results show that erosion is active on more than three quarters (3/4) of the watershed, and a considerable loss of land with 8.36 Million tonnes per year. In this way, flood analysis and study of?hydrometeorological events identified the vulnerability of flood sites (hot-spot) contributing at 77%?of El Kansra siltation dam. Therefore, the consequence assessment is obtained by identifying risk elements and estimating potential damage coefficient, which represents the financial gap flow affecting the socio-economic context due to the erosion impacts.

关键词： Risk Susceptibility Vulnerability Erosion Flood Siltation Dam

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Theoretical Study on the Self, Water-assisted and Au-to-assisted Dimer Proton Transfer Reaction in the N-Hydroxy-Methylen-Formamide

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Open Journal of Physical Chemistry 2011年第2期1卷 37-44页

作者： Rezika larabi Yamina Belmiloud Meziane Brahimi Laboratoire de Physico-Chimie Théorique et de Chimie Informatique Faculté de Chimie. USTHB. BP 32 El alia 16100. Alger. Algérie

The proton transfer in the isolated, mono and dehydrated forms, isolated dimers of N-Hydroxy Methylen Formamide (NHMF) have been completely investigated in the present study using Density Functional Theory (DFT), M?ller-Plesset perturbation (MP2) and Hartree-Fock (HF) methods with the 6-31G* and 6-311G* basis sets. The barrier heights for both H2O-assisted and auto-assistance reactions are significantly lower than that of the bare tautomerization reaction from NHMF to N-Formyl Formamide (NFF), implying the importance of the superior catalytic effect of H2O in the monomer of NHMF and important role of HOCH= N-COH for the intramolecular proton transfer.

关键词： N-Hydroxy Methylen Formamide Proton Transfer HF MP2 and DFT

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Comparative Study of the DTC-IM Speed Controller Based on Artificial Intelligence

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Computer Technology and Application 2012年第5期3卷 347-352页

作者： Fethia Hamidia Abdelakader larabi Mohamed Seghir Boucherit Electrical Engineering Department Ecole National Polytechnique ENP El-harrach 16200 Algiers Algeria Electrical Engineering Department USTHB University Bab-ezzouar 16111 Algiers Algeria

Recently, artificial intelligence technique is increasingly receiving attention in solving complex and practical problem and they are widely applying in electrical machine domain. The authors consider also the direct torque control （DTC） as an alternative to conventional methods of control by pulse width modulation （PWM） and by Field oriented control （FOC）, so the application of the DTC based on artificial intelligence can show more advantages and simplified control algorithms with high performance. For this reason, the objectives of this paper can be divided into two parts, the first part is to apply neural networks and fuzzy logic techniques to the DTC control in the presence of a loop speed control comparing to the conventional regulators （as PI） to show the feasibility of these approaches, the second part is to further improve the performance of the neural network by using a neural-fuzzy regulator which combine the advantages of two techniques. Simulation results confirm the validity of the proposed techniques.

关键词： Direct torque control induction motor neural network fuzzy PI.

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Integration of Remote Sensing and GIS in Studying Land Cover Trends and Conditions in the Middle Ziz Oasis,Morocco

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International Journal of Geosciences 2013年第7期4卷 1018-1023页

作者： Ali Essahlaoui Abba Mohamed Eddahby Lhou Faouzi Mohamed larabi Abdelkader Research Group“Water Sciences and Environmental Engineering” Laboratory of Geo-Engineering and EnvironmentFaculty of SciencesMy Ismail UniversityMeknesMorocco Laboratory LIMEN“Water Resources&Information Technology” Mohammadia School of EngineersRabatMorocco Department of Geology Faculty of SciencesDhar El MahrazFezMorocco

A better understanding of the changing patterns of land use and vegetation cover is a major concern for countries whose ecosystems are under severe degradation. Indeed, the dynamics of land have direct implications on the availability of natural resources. The palm grove, of oases of Errachidia region, plays an important role in the environmental, social and economic of this region. This research was conducted in the Ziz middle, which is affected by changes in the conditions and composition of land cover change. The application of remote sensing, geographic information systems and satellite imagery analysis with multi-temporal and spatial land use provides, for territorial managers, data updated and improved and a synopsis for effective management of natural resources. This research explores the possibility of identifying, monitoring and mapping land use change and land use on the dynamics of the palm grove in the past 40 years. Satellite images used are Landsat images and multi-temporal dates (MSS (1972), TM (1987), ETM + (2001, 2006 and 2011). These images were georeferenced and radiometrically corrected. In our study, the use of vegetation indices NDVI, SAVI and MASAVI, highlight the magnitude of changes in vegetation cover between 1972 and 2011. A regressive pronounced canopy is generally recognized in the Middle Ziz. This decline is explained by the combined effect of anthropic action (urbanization) and climatic conditions.

关键词： Morocco Remote Sensing GIS Ziz Watershed Dynamic of Land Use NDVI

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Optimal Extraction of Groundwater in Gaza Coastal Aquifer

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Journal of Water Resource and Protection 2009年第4期1卷 249-259页

作者： Khalid QAHMAN Abdelkader larabi Driss OUAZAR Ahmed NAJI Alexander H.-D. CHENG 不详

Two multi-objective management models are applied on a local area selected from the regional Gaza coastal aquifer. The objectives and constraints of these management scenarios include maximizing the total volume of water pumped, minimizing the salt concentration of the pumped water, and controlling the drawdown limits. The physical model is based on the CODESA-3D density-dependent advective-dispersive solute transport model. Genetic algorithm is used as the optimization tool. The models are tested on a part of the aquifer ( ) with 9 existing pumping wells located at various depths. The results of the optimization show that the optimization/simulation approach can give better decision if there is enough information to feed to the model. It confirms that the use of the concept of safe yield alone is not enough for sustainable develop-ment of the coastal aquifer. It shows that the optimum pumping rate is in the range of 26%–34% of the total natural replenishment. The application shows that the proposed technique is a powerful tool for solving this type of management problems.

关键词： Seawater Intrusion Genetic Algorithm Pumping Optimization Density-dependent Miscible Transport

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