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Internet of Things Enabled DDos Attack Detection Using Pigeon Inspired Optimization Algorithm with Deep Learning Approach

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Computers, Materials & Continua 2024年第9期80卷 4047-4064页

作者： Turki ali Alghamdi saud s.Alotaibi Department of Computer science and Artificial Intelligence College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia

Internet of Things(IoTs)provides better solutions in various fields,namely healthcare,smart transportation,home,*** Denial of service(Dos)outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT *** learning(DL)models outperform in detecting complex,non-linear relationships,allowing them to effectually severe slight deviations fromnormal IoT activities that may designate a Dos *** uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection,permitting proactive reduction events to be executed,hence securing the IoT network’s safety and ***,this study presents pigeon-inspired optimization with a DL-based attack detection and classification(PIODL-ADC)approach in an IoT *** PIODL-ADC approach implements a hyperparameter-tuned DL method for Distributed Denial-of-service(DDos)attack detection in an IoT ***,the PIODL-ADC model utilizes Z-score normalization to scale input data into a *** handling the convolutional and adaptive behaviors of IoT,the PIODL-ADCmodel employs the pigeon-inspired optimization(PIO)method for feature selection to detect the related features,considerably enhancing the recognition’s ***,the Elman Recurrent Neural Network(ERNN)model is utilized to recognize and classify DDos ***,reptile search algorithm(RsA)based hyperparameter tuning is employed to improve the precision and robustness of the ERNN method.A series of investigational validations is made to ensure the accomplishment of the PIODL-ADC *** experimental outcome exhibited that the PIODL-ADC method shows greater accomplishment when related to existing models,with a maximum accuracy of 99.81%.

关键词： Internet of things denial of service deep learning reptile search algorithm feature selection

Defining failure of endoluminal biliary drainage in the era of endoscopic ultrasound and lumen apposing metal stents

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World Journal of Gastroenterology 2024年第29期30卷 3534-3537页

作者： Faisal s ali sushovan Guha Department of Gastroenterology Hepatologyand NutritionUniversity of Texas Health Science Center at HoustonHustonTX 77054United States Department of Clinical sciences Tilman J.Fertitta Family College of MedicineUniversity of HoustonHoustonTX 77204United States

The role of endoscopy in pathologies of the bile duct and gallbladder has seen notable advancements over the past two *** advancements in stent technology,such as the development of lumen-apposing metal stents,and adoption of endoscopic ultrasound and electrosurgical principles in therapeutic endoscopy,what was once considered endoscopic failure has transformed into failure of an approach that could be salvaged by a second-or third-line endoscopic *** of these advancements in routine patient care will require formal training and multidisciplinary acceptance of established techniques and collaboration for advancement of experimental techniques to generate robust evidence that can be utilized to serve patients to the best of our ability.

关键词： Endoscopic ultrasound Guided biliary drainage Gallbladder Biliary obstruction Lumen-apposing metal stent

5G Resource Allocation Using Feature selection and Greylag Goose Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel ali Alhussan s.K.Towfek Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & sciences 2024年第8期140卷 1339-1370页

作者： ali s.Alghamdi Mohamed A.Zohdy saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and space science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer science and systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(REss).Efficient integration of stochastic REss and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of REss,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VsI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VsI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VsI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

Heat transfer analysis in particle-laden flows using the immersed boundary method

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Particuology 2024年第7期90卷 394-403页

作者： ali Abbas Zaidi Department of Mechanical Engineering University of Manitoba75A Chancellors CircleWinnipegR3T 5V6Canada

This paper investigates an efficient immersed boundary method(IBM)for multiple-core CPU machines with local grid refinement for the calculation of heat transfer between fluids and finite-sized *** fluid momentum equations are solved by using the fractional step method,while the energy equation is solved by employing the second-order Adams-Bashforth *** efficient load balancing between the CPU cores,the coupling between particles and fluid is obtained by applying the body force in the fluid equations,which depends on the solid volume fraction of particles contained in each grid cell,and then by linearly interpolating the particle temperature and velocity on the fluid grid cell(in place of the delta function commonly used in literature).several test cases from the literature are studied,and good agreement is observed between the simulation results and the ***,a scaling study on multiple core machines is performed,demonstrating the proposed IBM's capabilities for a significant reduction in processing time.

关键词： Heat transfer Immersed boundary method Particle resolved direct numerical simulations Fluid solid interactions

Bulk-boundary and RPs thermodynamics from topology perspective

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Chinese Physics C 2024年第9期48卷 244-253页

作者： Jafar sadeghi Mohammad Reza alipour saeed Noori Gashti Mohammad ali s.Afshar Department of Physics Faculty of Basic SciencesUniversity of Mazandaran P.O.Box 47416-95447BabolsarIran school of Physics Damghan UniversityP.O.Box ***DamghanIran

In this study,we investigate the bulk-boundary and restricted phase space(RPs)thermodynamics of Rissner-Nordstrom(R-N)Ads and 6-dimensional charged Gauss-Bonnet Ads black ***,we examine the topological characteristics of the considered black holes and compare them with the results of extended *** determine that the topological behavior of the bulk-boundary thermodynamics is the same as that of the extended thermodynamics,whereas the RPs thermodynamics exhibits a distinct ***,we demonstrate that within the RPs formalism,there is only one critical point with a topological charge of+1(Q_(t)=+1).Moreover,in the RPs formalism,the inclusion of higher-derivative curvature terms in the form of GaussBonnet gravity does not alter the topological classification of critical points in charged Ads black holes.

关键词： bulk-boundary restricted phase space topological charge thermodynamics

Using neural network modeling to improve the detection accuracy of land subsidence due to groundwater withdrawal

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Journal of Mountain science 2024年第7期21卷 2320-2333页

作者： ali M.RAJABI ali EDALAT Yasaman ABOLGHAsEMI Mahdi KHODAPARAsT Department of Engineering Geology University of TehranTehran ***Iran Department of Civil Engineering University of QomQom ***Iran

Despite the high efficiency of remote sensing methods for rapid and large-scale detection of subsidence phenomena,this technique has limitations such as atmospheric impact and temporal and spatial decorrelation that affect the accuracy of the *** paper proposes a method based on an artificial neural network to improve the results of monitoring land subsidence due to groundwater overexploitation by radar interferometry in the aliabad plain(Central Iran).In this regard,vertical ground deformations were monitored over 18 months using the sentinel-1A sAR *** model the land subsidence by a multilayer perceptron(MLP)artificial neural network,four parameters,including groundwater level,alluvial thickness,elastic modulus,and transmissivity have been *** model's generalizability was assessed using data derived for 144 *** to the results,the neural network estimates the land subsidence at each ground point with an accuracy of 6.8 mm.A comparison between the predicted and actual values indicated a significant *** MLP model can be used to improve the results of subsidence detection in the study area or other areas with similar characteristics.

关键词： DInsAR Land subsidence Groundwater withdrawal aliabad plain Artificial neural network

Performance of Text-Independent Automatic speaker Recognition on a Multicore system

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Tsinghua science and Technology 2024年第2期29卷 447-456页

作者： Rand Kouatly Talha ali Khan Faculty of Tech and software Engineering University of Europe for Applied SciencesPotsdam 14469Germany

This paper studies a high-speed text-independent Automatic speaker Recognition(AsR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing *** memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the AsR *** experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.

关键词： Automatic speaker Recognition(AsR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OpenMP

A Comprehensive Review on Charging Topologies and Power Electronic Converter solutions for Electric Vehicles

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Journal of Modern Power systems and Clean Energy 2024年第3期12卷 675-694页

作者： Abdelfatah ali Hossam H.H.Mousa Mostafa F.shaaban Maher A.Azzouz Ahmed s.A.Awad the Department of Electrical Engineering American University of Sharjah26666 SharjahUnited Arab Emirates the Department of Electrical Engineering South Valley University83523 QenaEgypt the Department of Electrical and Computer Engineering University of WindsorWindsorON N9B 3P4 Canada Electrical Engineering Department Qatar UniversityDoha 2713Qatar Department of Electrical and Computer Engineering Sultan Qaboos UniversityMuscat123Oman

Electric vehicles(EVs)are becoming more popular worldwide due to environmental concerns,fuel security,and price *** performance of EVs relies on the energy stored in their batteries,which can be charged using either AC(slow)or DC(fast)***,EVs can also be used as mobile power storage devices using vehicle-to-grid(V2G)*** electronic converters(PECs)have a constructive role in EV applications,both in charging EVs and in ***,this paper comprehensively investigates the state of the art of EV charging topologies and PEC solutions for EV *** examines PECs from the point of view of their classifications,configurations,control approaches,and future research prospects and their impacts on power *** can be classified into various topologies:DC-DC converters,AC-DC converters,DC-AC converters,and AC-AC *** address the limitations of traditional DC-DC converters such as switching losses,size,and high-electromagnetic interference(EMI),resonant converters and multiport converters are being used in high-voltage EV ***,power-train converters have been modified for high-efficiency and reliability in EV *** paper offers an overview of charging topologies,PECs,challenges with solutions,and future trends in the field of the EV charging station applications.

关键词： Charging station charging topology electric vehicle power electronic converter vehicle-to-grid