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An Online fake Review Detection Approach Using famous Machine Learning Algorithms

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Computers, Materials & Continua 2024年第2期78卷 2767-2786页

作者： Asma hassan Alshehri Department of Computer Sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia

Online review platforms are becoming increasingly popular,encouraging dishonest merchants and service providers to deceive customers by creating fake reviews for their goods or *** Sybil accounts,bot farms,and real account purchases,immoral actors demonize rivals and advertise their *** academic and industry efforts have been aimed at detecting fake/fraudulent product or service evaluations for *** primary hurdle to identifying fraudulent reviews is the lack of a reliable means to distinguish fraudulent reviews from real *** paper adopts a semi-supervised machine learning method to detect fake reviews on any website,among other *** reviews are classified using a semi-supervised approach(PU-learning)since there is a shortage of labeled data,and they are ***,classification is performed using the machine learning techniques Support Vector Machine(SVM)and Nave *** performance of the suggested system has been compared with standard works,and experimental findings are assessed using several assessment metrics.

关键词： Security fake review semi-supervised learning ML algorithms review detection

The global stability and optimal control of the COVID-19 epidemic model

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International Journal of Biomathematics 2024年第1期17卷 1-28页

作者： fengsheng Chien hassan Saberi Nik Mohammad Shiraziant J.f.Gomez-Aguilar School of finance and Accounting fuzhou University of International Studies and Trade fuzhou 352020 P.R.China faculty of Business City university of Macao Macao 999078P.R.China Department of Mathematics and Statistics University of Neyshabur NeyshaburIran CONACyT-Tecnologico Nacional de Mécico/CENIDET Interior Internado Palmira S/N Col.Palmira C.P.62490CuernavacaMorelosMérico

This paper considers stability analysis of a Susceptible-Exposed-Infected-Recovered-Virus(SEIRV)model with nonlinear incidence rates and indicates the severity and weakness of control factors for disease *** Lyapunov function using Volterra-Lyapunov matrices makes it possible to study the global stability of the endemic equilibrium *** optimal control strategy is proposed to prevent the spread of coronavirus,in addition to governmental *** objective is to minimize together with the quantity of infected and exposed individuals while minimizing the total costs of treatment.A numerical study of the model is also carried out to investigate the analytical results.

关键词： Global stability SEIRV epidemic model dynamical systems Volterra-Lyapunov stability optimal control

A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in fog Computing

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Computers, Materials & Continua 2024年第9期80卷 4703-4728页

作者： Hawazen Alzahrani Tarek Sheltami Abdulaziz Barnawi Muhammad imam Ansar Yaser Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure SystemsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

The Internet of Things(IoT)links various devices to digital services and significantly improves the quality of our ***,as IoT connectivity is growing rapidly,so do the risks of network vulnerabilities and *** interesting Intrusion Detection Systems(IDSs)are presented based on machine learning(ML)techniques to overcome this *** the resource limitations of fog computing environments,a lightweight IDS is *** paper introduces a hybrid deep learning(DL)method that combines convolutional neural networks(CNN)and long short-term memory(LSTM)to build an energy-aware,anomaly-based *** test this system on a recent dataset,focusing on reducing overhead while maintaining high accuracy and a low false alarm *** compare CICIoT2023,KDD-99 and NSL-KDD datasets to evaluate the performance of the proposed IDS model based on key metrics,including latency,energy consumption,false alarm rate and detection rate *** findings show an accuracy rate over 92%and a false alarm rate below 0.38%.These results demonstrate that our system provides strong security without excessive resource *** practicality of deploying IDS with limited resources is demonstrated by the successful implementation of IDS functionality on a Raspberry Pi acting as a fog *** proposed lightweight model,with a maximum power consumption of 6.12 W,demonstrates its potential to operate effectively on energy-limited devices such as low-power fog nodes or edge *** prioritize energy efficiency whilemaintaining high accuracy,distinguishing our scheme fromexisting *** experiments demonstrate a significant reduction in false positives,ensuring accurate identification of genuine security threats while minimizing unnecessary alerts.

关键词： Intrusion detection fog computing CNN LSTM energy consumption

Machine Learning Techniques Using Deep Instinctive Encoder-Based feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad Khalid imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced Rf(ERf),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

Model Reference Adaptive Controller for Simultaneous Voltage and frequency Restoration of Autonomous AC Microgrids

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1194-1202页

作者： farahnaz Ahmadi Yazdan Batmani hassan Bevrani Department of Electrical Engineering University of KurdistanSanandajIran

In an autonomous droop-based microgrid,the sys-tem voltage and frequency(Vaf)are subject to deviations as load *** the existence of various control methods aimed at correcting system frequency deviations at the second-ary control level without any communication network,the chal-lenges associated with these methods and their abilities to simul-taneously restore microgrid Vaf have not been fully *** this paper,a multi-input multi-output(MIMO)model ref-erence adaptive controller(MRAC)is proposed to achieve Vaf restoration while accurate power sharing among distributed generators(DGs)is *** proposed MRAC,without any communication network,is designed based on two meth-ods:droop-based and inertia-based *** the microgrid,the suggested design procedure is started by defining a model reference in which the control objectives,such as the desired settling time,the maximum tolerable overshoot,and steady-state error,are ***,a feedback-feedforward con-troller is established,of which the gains are adaptively tuned by some rules derived from the Lyapunov stability *** some simulations in MATLAB/SimPowerSystem Tool-box,the proposed MRAC demonstrates satisfactory perfor-mance.

关键词： AC microgid communication-free secondary control droop-based method inertia-based method model reference adaptive controller(MRAC) simultaneous voltage and frequency restoration

Assessment of liquefaction potential based on shear wave velocity:Strain energy approach

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第9期16卷 3733-3745页

作者： Mohammad hassan Baziar Mahdi Alibolandi School of Civil Engineering Iran University of Science and TechnologyTehran16846-13114Iran

Liquefaction assessment based on strain energy is significantly superior to conventional stress-based *** main purpose of the present study is to investigate the correlation between shear wave velocity and strain energy capacity of silty *** dissipated energy until liquefaction occurs was calculated by analyzing the results of three series of comprehensive cyclic direct simple shear and triaxial tests on Ottawa f65,Nevada,and firoozkuh sands with varying silt content by weight and relative ***,the shear wave velocity of each series was obtained using bender element or resonant column ***,for the first time,a liquefaction triggering criterion,relating to effective overburden normalized liquefaction capacity energy(WL=s’c)to effective overburden stresscorrected shear wave velocity(eVs1)has been *** accuracy of the proposed criteria was evaluated using in situ *** results confirm the ability of shear wave velocity as a distinguishing parameter for separating liquefied and non-liquefied soils when it is calculated against liquefaction capacity energy(WL=s’c).However,the proposed WL=s’c-Vs1 curve,similar to previously proposed cyclic resistance ratio(CRR)-Vs1 relationships,should be used conservatively for fields vulnerable to liquefaction-induced lateral spreading.

关键词： Liquefaction Strain energy capacity Shear wave velocity Cyclic triaxial test Cyclic direct simple shear test Resonant column test Bender element test

Distributed Hybrid Model Predictive Secondary Control of DC Microgrids with Random Communication Disorders

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 925-935页

作者： Meysam Yaribeygi Zeinab Karami Qobad Shafiee hassan Bevrani the Department of Electrical Engineering K.N.Toosi University of TechnologyTehranIranand he is now with the Sportradar CompanyTrondheimNorway the Department of Engineering Cybernetics(ITK) Norwegian University of Science and Technology(NTNU)TrondheimNorway the Smart/Micro Grids Research Center Department of Electrical EngineeringUniversity of KurdistanSanandajIran

A reliable and robust communication network is essential to exchange information between distributed generators(DGs)and accurately calculate their control actions in microgrids(MGs).However,the integration of the communication network and MGs poses challenges related to the flexibility,availability,and reliability of the ***,random communication disorders such as time delays and packet loss can negatively impact the system ***,it is essential to design a suitable secondary controller(SC)with a fast dynamic response to restore voltage and appropriate powersharing,while ensuring that the effects of random communication disorders are *** this regard,an optimal distributed hybrid model predictive secondary control method is presented in this *** simulations are carried out in a mixed simulation environment based on MATLAB and OMNET++,by considering IEEE 802.11(Wi fi)using the recently developed Internet networking(INET)*** the implemented application layer,the recovery Unit is responsible for reducing the impact of random communication *** effectiveness and performance of the proposed method in comparison with a conventional model predictive control are verified by simulation results.

关键词： Microgrid model predictive control random communication disorder secondary control

An Adaptive Data-driven Method Based on fuzzy Logic for Determining Power System Voltage Status

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 707-718页

作者： Sirwan Shazdeh Hêmin Golpîra hassan Bevrani the SMGRC University of KurdistanSanandajIran Power Systems Modeling&Simulation Lab Department of Electrical EngineeringUniversity of KurdistanKurdistanSanandaj 66177-15175Iran

This paper proposes an adaptive method based on fuzzy logic that utilizes data from phasor measurement units(PMUs) to assess and classify generating-side voltage trajectories. The voltage variable and its associated derivatives are used as the input variables of a fuzzy-logic block. In addition, the voltage trajectory is compared with the pre-selected pilot-bus voltage to make a reliable decision about the voltage operational state. Different types of short-term voltage dynamics are considered in the proposed method. The fuzzy membership functions are determined using a systematic method that considers the current situation of the voltage trajectory. finally, the voltage status is categorized into four classes to determine appropriate remedial actions. The proposed method is validated on a IEEE 73-bus power system in a MATLAB environment.

关键词： fuzzy logic fault-induced delayed voltage recovery phasor measurement unit(PMU) short-term voltage stability situational awareness voltage classification

Existence and numerical approximation of a solution to frictional contact problem for electro-elastic materials

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 201-219页

作者： Othman Baiz EL-hassan Benkhira Rachid fakhar University Ibn Zohr Lab.ESERFP of OuarzazateMorocco University Moulay Ismail Faculty of SciencesLaboratory MACSESTMBP 3103Toulal-MeknesMorocco University Sultan Moulay Slimane Laboratory LS2MEPolydisciplary Faculty of Khouribga25000 KhouribgaMorocco

In this paper,a frictional contact problem between an electro-elastic body and an electrically conductive foundation is *** contact is modeled by normal compliance with finite penetration and a version of Coulomb’s law of dry friction in which the coefficient of friction depends on the *** addition,the effects of the electrical conductivity of the foundation are taken into *** model leads to a coupled system of the quasi-variational inequality of the elliptic type for the displacement and the nonlinear variational equation for the electric *** existence of a weak solution is proved by using an abstract result for elliptic variational inequalities and a fixed point ***,a finite element approximation of the problem is *** some regularity conditions,an optimal order error estimate of the approximate solution is ***,a successive iteration technique is used to solve the problem numerically and a convergence result is established.

关键词： piezoelectric material frictional contact variational Inequality fixed point process finite element method error estimation iteration method