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Formulating layered adjustable autonomy for unmanned aerial vehicles

International Journal of Intelligent Computing and Cybernetics 2017年第4期10卷 430-450页

作者： salama a.mostafa Mohd Sharifuddin Ahmad Aida Mustapha Mazin Abed Mohammed Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaBatu PahatMalaysia College of Information Technology Universiti Tenaga NasionalKajangMalaysia Planning and Follow Up Department University of AnbarAnbarIraq

Purpose–The purpose of this paper is to propose a layered adjustable autonomy(LAA)as a dynamically adjustable autonomy model for a multi-agent *** is mainly used to efficiently manage humans’and agents’shared control of autonomous systems and maintain humans’global control over the ***/methodology/approach–The authors apply the LAA model in an agent-based autonomous unmanned aerial vehicle(UAV)*** UAV system implementation consists of two parts:software and *** software part represents the controller and the cognitive,and the hardware represents the computing machinery and the actuator of the UAV *** UAV system performs three experimental scenarios of dance,surveillance and search *** selected scenarios demonstrate different behaviors in order to create a suitable test plan and ensure significant ***–The results of the UAV system tests prove that segregating the autonomy of a system as multidimensional and adjustable layers enables humans and/or agents to perform actions at convenient autonomy ***,reducing the adjustable autonomy drawbacks of constraining the autonomy of the agents,increasing humans’workload and exposing the system to ***/value–The application of the LAA model in a UAV manifests the significance of implementing dynamic adjustable *** the autonomy within three phases of agents run cycle(taskselection,actions-selection and actions-execution)is an original idea that aims to direct agents’autonomy toward performance *** agents’abilities are well exploited when an incompetent agent switches with a more competent one.

关键词： Unmanned aerial vehicle Multi-agent system Adjustable autonomy Autonomous agent

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***:Hybrid Deep Learning for Enhancing IoT Network Intrusion Detection

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Computers, Materials & Continua 2021年第12期69卷 3945-3966页

作者： Ziadoon K.Maseer Robiah Yusof salama a.mostafa Nazrulazhar Bahaman Omar Musa Bander Ali Saleh Al-rimy Faculty of Information and Communication Technology Universiti Teknikal MalaysiaMelaka76100Malaysia Center of Intelligent and Autonomous Systems Faculty of Computer Science and Information TechnologyUniversiti Tun Hussein Onn MalaysiaJohor86400Malaysia Faculty of Business and Technology UNITAR International UniversitySelangor47301Malaysia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor81310Malaysia

With an increasing number of services connected to the internet,including cloud computing and Internet of Things(IoT)systems,the prevention of cyberattacks has become more challenging due to the high dimensionality of the network traffic data and access ***,researchers have suggested deep learning(DL)algorithms to define intrusion features through training empirical data and learning anomaly patterns of ***,due to the high dynamics and imbalanced nature of the data,the existing DL classifiers are not completely effective at distinguishing between abnormal and normal behavior line connections for modern ***,it is important to design a self-adaptive model for an intrusion detection system(IDS)to improve the detection of ***,in this paper,a novel hybrid weighted deep belief network(HW-DBN)algorithm is proposed for building an efficient and reliable IDS(***)model to detect existing and novel *** HW-DBN algorithm integrates an improved Gaussian–Bernoulli restricted Boltzmann machine(Deep GB-RBM)feature learning operator with a weighted deep neural networks(WDNN)*** CICIDS2017 dataset is selected to evaluate the *** model as it contains multiple types of attacks,complex data patterns,noise values,and imbalanced *** have compared the performance of the *** model with three recent *** results show the *** model outperforms the three other models by achieving a higher detection accuracy of 99.38%and 99.99%for web attack and bot attack scenarios,***,it can detect the occurrence of low-frequency attacks that are undetectable by other models.

关键词： Cyberattacks internet of things intrusion detection system deep learning neural network supervised and unsupervised deep learning

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A New Multi-Agent Feature Wrapper Machine Learning Approach for Heart Disease Diagnosis

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Computers, Materials & Continua 2021年第4期67卷 51-71页

作者： Mohamed Elhoseny Mazin Abed Mohammed salama a.mostafa Karrar Hameed Abdulkareem Mashael S.Maashi Begonya Garcia-Zapirain Ammar Awad Mutlag Marwah Suliman Maashi Department of Computer Science College of Computer Information TechnologyAmerican University in the Emirates503000United Arab Emirates College of Computer Science and Information Technology University of AnbarRamadi31001Iraq Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia College of Agriculture Al-Muthanna UniversitySamawah66001Iraq Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia eVIDA Lab University of DeustoBilbao48007Spain Department of Pure Science Ministry of EducationGeneral Directorate of CurriculaBaghdadIraq Department of Medical Laboratory Science Faculty of Applied Medical ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia

Heart disease(HD)is a serious widespread life-threatening *** heart of patients with HD fails to pump sufcient amounts of blood to the entire *** the occurrence of HD early and efciently may prevent the manifestation of the debilitating effects of this disease and aid in its effective *** methods for diagnosing HD are sometimes unreliable and insufcient in analyzing the related *** an alternative,noninvasive medical procedures based on machine learning(ML)methods provide reliable HD diagnosis and efcient prediction of HD ***,the existing models of automated ML-based HD diagnostic methods cannot satisfy clinical evaluation criteria because of their inability to recognize anomalies in extracted symptoms represented as classication features from patients with *** this study,we propose an automated heart disease diagnosis(AHDD)system that integrates a binary convolutional neural network(CNN)with a new multi-agent feature wrapper(MAFW)*** MAFW model consists of four software agents that operate a genetic algorithm(GA),a support vector machine(SVM),and Naïve Bayes(NB).The agents instruct the GA to perform a global search on HD features and adjust the weights of SVM and BN during initial classication.A nal tuning to CNN is then performed to ensure that the best set of features are included in HD *** CNN consists of ve layers that categorize patients as healthy or with HD according to the analysis of optimized HD *** evaluate the classication performance of the proposed AHDD system via 12 common ML techniques and conventional CNN models by using across-validation technique and by assessing six evaluation *** AHDD system achieves the highest accuracy of 90.1%,whereas the other ML and conventional CNN models attain only 72.3%–83.8%accuracy on ***,the AHDD system proposed herein has the highest capability to identify patients with *** system can be used by medical

关键词： Heart disease machine learning multi-agent feature wrapper model heart disease diagnosis HD cleveland datasets convolutional neural network

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A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

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Computers, Materials & Continua 2021年第3期66卷 3289-3310页

作者： Mazin Abed Mohammed Karrar Hameed Abdulkareem Begonya Garcia-Zapirain salama a.mostafa Mashael S.Maashi Alaa S.Al-Waisy Mohammed Ahmed Subhi Ammar Awad Mutlag Dac-Nhuong Le College of Computer Science and Information Technology University of AnbarRamadi31001Iraq College of Agriculture Al-Muthanna UniversitySamawah66001Iraq eVIDA Lab University of DeustoBilbao48007Spain Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia Faculty of Engineering and Built Environment Universiti Kebangsaan MalaysiaBangi43600Malaysia Pure Science Department Ministry of EducationGeneral Directorate of CurriculaBaghdad10Iraq Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global *** biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 *** this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 ***(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection *** on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 *** comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.

关键词： Coronavirus disease COVID-19 diagnosis machine learning convolutional neural networks resnet50 artificial neural network support vector machine X-ray images feature transfer learning

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MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb Ali Jaber Ali Mansour Christophe Osswald Nour mostafa Chamseddine Zaki Computer Science Department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

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Unwanted disorders and xenogeneic graft-versus-host disease in experimental immunodeficient mice:How to evaluate and how to report

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Animal Models and Experimental Medicine 2025年第1期8卷 20-29页

作者： Seyed mostafa Monzavi Samad Muhammadnejad Vahid Mansouri Hami Ashraf Naser Ahmadbeigi Gene Therapy Research Center Digestive Diseases Research InstituteTehran University of Medical SciencesTehranIran INSERM U981 Institut Gustave RoussyVillejuifFrance Chronic Respiratory Diseases Research Center National Research Institute of Tuberculosis and Lung Diseases(NRITLD)Shahid Beheshti University of Medical SciencesTehranIran

Human-derived tumor models are essential for preclinical development of new anti-cancer drug *** animal models bearing tumors of human origin,such as patient-derived or cell line-derived xenograft tumors,is dependent on immuno-deficient ***-bearing immunodeficient mice are susceptible to develop-ing unwanted disorders primarily irrelevant to the tumor nature;and if get involved with such disorders,reliability of the study results will be undermined,inevitably con-founding the research in ***,a rigorous health surveillance and clinical monitoring system,along with the establishment of a strictly controlled barrier facility to maintain a pathogen-free state,are *** if all pathogen control and biosafety measures are followed,there are various noninfectious disorders capable of causing tissue and multiorgan damage in immunodeficient ***,the re-searchers should be aware of sentinel signs to carefully monitor and impartially report *** review discusses clinical signs of common unwanted disorders in experi-mental immunodeficient mice,and how to examine and report them.

关键词： animal models graft-versus-host disease health surveillance preclinical drug evaluation xenograft model antitumor assays

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Optimizing Stand-Alone PV Systems:A Metaheuristic-Enhanced Fuzzy Approach for Adaptive MPPT

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China Communications 2025年第1期22卷 61-74页

作者： Tina Samavat mostafa Nazari Lin Fuhong Lei Yang Department of Computer Science and Engineering University of NevadaRenoNVUSA Faculty of Mechanical Engineering Shahrood University of TechnologyShahroodIran School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

This paper introduces a simple yet effective approach for developing fuzzy logic controllers(FLCs)to identify the maximum power point(MPP)and optimize the photovoltaic(PV)system to extract the maximum power in different environmental *** propose a robust FLC with low computational complexity by reducing the number of membership functions and *** optimize the performance of the FLC,metaheuristic algorithms are employed to determine the parameters of the *** evaluate the proposed FLC in various panel configurations under different environmental *** results indicate that the proposed FLC can easily adapt to various panel configurations and perform better than other benchmarks in terms of enhanced stability,responsiveness,and power transfer under various scenarios.

关键词： genetic algorithm imperialist competitive algorithm invasive weed algorithm maximum power point tracking

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How New Individuals Behave in a Heterogeneous Community: A Computational Approach to Norm Assimilation Using Agent-Based Systems

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Journal of Systems Science & Complexity 2020年第4期33卷 849-881页

作者： MAHMOUD Moamin AHMAD Mohd Sharifuddin mostafa salama SUBRAMAINAN Latha College of Computing and Informatics Universiti Tenaga NasionalKajangSelangorMalaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaParit RajaMalaysia

Heterogeneous community entails a number of social groups that adopt similar/different social *** such community,new individuals who join a new social group should be able to decide with which group they could assimilate based on their capabilities/values/***,they would be penalized by other members in the group for violating some norms which they cannot *** this approach,software agents would have better reasoning in simulating human *** this paper,the authors propose a norms assimilation theory,in which a new agent attempts to assimilate with a social group’s *** theory builds an approach to norm assimilation,analyzes the cases for an agent to decide to assimilate with a social group and develops a mathematical model to measure the assimilation cost and the agent’s *** approach is developed based on the agent’s internal belief about its ability and desire,and its external belief about the cost of assimilating with a number of social *** significance of this research is ***,the study paves the way to future design of intelligent systems,i.e.,software agents or robots,to closely mimic human social ***,the norm assimilation using agent-based system could be potentially utilized to simulate some social issues such as immigrants,new students,expatriate *** experiments that have been conducted demonstrate that an agent in the domain is able to calculate the assimilation cost and decide which social group to join.

关键词： Agent-based simulation heterogeneous community individuals norms norm assimilation normative systems social group

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Plenty of analytical and semi-analytical wave solutions of shallow water beneath gravity

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Journal of Ocean Engineering and Science 2022年第3期7卷 237-243页

作者： mostafa M.A.Khater SamirA.salama Department of Mathematics Faculty of ScienceJiangsu UniversityZhenjiang 212013China Department of Mathematics Obour High Institute For Engineering and TechnologyCairo 11828Egypt Division of Biochemistry Department of PharmacologyCollege of PharmacyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

This article studies novel soliton wave solutions of the nonlinear fractional ill-posed Boussinesq(NLFIPB)dynamic wave equation by applying the extended Riccati-expansion(ERE)*** Hadamard has formulated the investigated model to figure out the dynamic characterizations of waves in shallow water under *** obtained solutions are explained through some sketches in 2D and 3D and contour *** the same time,the results’accuracy is checked by comparing the obtained solutions with semianalytical solutions through the well-known Adomian decomposition(AD)*** superiority of the ERE method over the original method is *** constructed solutions are checked by submitting them back into the original model through Mathematica 12 software.

关键词： Ill-posed Boussinesq dynamical wave Analytical and semi-analytical simulations

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Semi-analytical and numerical simulations of the modified Benjamin-Bona-Mahony model

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Journal of Ocean Engineering and Science 2022年第3期7卷 264-271页

作者： mostafa M.A.Khater SamirA.salama Department of Mathematics Faculty of ScienceJiangsu UniversityZhenjiang212013China Department of Mathematics Obour High Institute For Engineering and TechnologyCairo11828Egypt Division of Biochemistry Department of PharmacologyCollege of PharmacyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

In this article,semi-analytical and numerical simulations of the well-known modified Benjamin-Bona-Mahony(mBBM)equation are *** study targets to check the accuracy of the obtained analytical solutions of the mBBM model that have been obtained in[1]through three recent analytical schemes(extended simplest equation(ESE)method,modified kudryashov(mKud)method,and SechTanh(ST)expansion method).The considered model describes the propagation of long waves in the nonlinear dispersive media in a visual *** Homotopy iteration(HI)method,exponential cubic-B-spline(ECBS)method,and trigonometric-quantic-B-spline(TQBS)method are employed to construct novel semi-analytical and accurate numerical *** obtained solutions’accuracy has been checked through some different types of two-dimensional graphs.

关键词： Modified Benjamin-Bona-Mahony equation Approximate solutions

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