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RPL-Based IoT Networks under Decreased Rank Attack:Performance Analysis in Static and Mobile Environments

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Computers, Materials & Continua 2024年第1期78卷 227-247页

作者： Amal Hkiri Mouna Karmani Omar ben Bahri ahmed Mohammed Murayr Fawaz Hassan Alasmari Mohsen Machhout Physic Department Electronics and Micro-Electronics LaboratoryFaculty of Sciences of MonastirMonastir5000Tunisia Department of Science and Technology College of RanyahTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

The RPL(IPv6 Routing Protocol for Low-Power and Lossy Networks)protocol is essential for efficient communi-cation within the Internet of Things(IoT)*** its significance,RPL’s susceptibility to attacks remains a *** paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the decreased rank attack in both static andmobilenetwork *** employ the Random Direction Mobility Model(RDM)for mobile scenarios within the Cooja *** systematic evaluation focuses on critical performance metrics,including Packet Delivery Ratio(PDR),Average End to End Delay(AE2ED),throughput,Expected Transmission Count(ETX),and Average Power Consumption(APC).Our findings illuminate the disruptive impact of this attack on the routing hierarchy,resulting in decreased PDR and throughput,increased AE2ED,ETX,and *** results underscore the urgent need for robust security measures to protect RPL-based IoT ***,our study emphasizes the exacerbated impact of the attack in mobile scenarios,highlighting the evolving security requirements of IoT networks.

关键词： RPL decreased rank attacks mobility random direction model

Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors

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World Journal of Diabetes 2024年第1期15卷 53-71页

作者： Min Wang Yang Ou Xiang-Lian Yuan Xiu-Fang Zhu ben Niu Zhuang Kang Bing Zhang Anwar ahmed Guo-Qiang Xing Heng Su School of Chemical Science and Technology Yunnan UniversityKunming 650091Yunnan ProvinceChina Department of Endocrinology The First People’s Hospital of Yunnan ProvinceKunming 650032Yunnan ProvinceChina Clinical Laboratory Nanchong Central Hospital&The Second Clinical Medical College of North Sichuan Medical UniversityNanchong 637000Sichuan ProvinceChina Department of Preventive Medicine and Biostatistics Uniformed Services University of the Health SciencesBethesdaMD 20814United States The Affiliated Hospital and Second Clinical Medical College North Sichuan Medical UniversityNanchong 637000Sichuan ProvinceChina Department of Research and Development Lotus *** LLCGaithersburgMD 20878United States

BACKGROUND The lack of specific predictors for type-2 diabetes mellitus(T2DM)severely impacts early intervention/prevention *** branched-chain amino acids(BCAAs:Isoleucine,leucine,valine)and aromatic amino acids(AAAs:Tyrosine,tryptophan,phenylalanine)show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical ***,improvement is needed to support its clinical *** To evaluate the effects of body mass index(BMI)and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body *** Ninety-seven new-onset T2DM patients(<12 mo)differing in BMI[normal weight(NW),n=33,BMI=22.23±1.60;overweight,n=42,BMI=25.9±1.07;obesity(OB),n=22,BMI=31.23±2.31]from the First People’s Hospital of Yunnan Province,Kunming,China,were ***-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/*** Fasting serum AAAs,BCAAs,glutamate,and alanine were greater and high-density lipoprotein(HDL)was lower(P<0.05,each)in OB-T2DM patients than in NW-T2DM patients,especially in male OB-T2DM ***,histidine,leucine,methionine,and lysine were greater in male patients than in female ***,histidine,alanine,glutamate,lysine,valine,methionine,leucine,isoleucine,tyrosine,phenylalanine,and tryptophan were significantly correlated with abdominal adiposity,body weight and BMI,whereas isoleucine,leucine and phenylalanine were negatively correlated with *** Heterogeneously elevated amino acids,especially BCAAs/AAAs,across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM *** higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals,whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW *** potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to

关键词： Hyperaminoacidemia Branched-chain/aromatic amino acids New-onset type-2 diabetes Predictor Obesity Sex

Sports Prediction Model through Cloud Computing and Big Data Based on Artificial Intelligence Method

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Journal of Intelligent Learning Systems and Applications 2024年第2期16卷 53-79页

作者： Aws I. Abu Eid Achraf ben Miled Ahlem Fatnassi Majid A. Nawaz Ashraf F. A. Mahmoud Faroug A. Abdalla Chams Jabnoun Aida Dhibi Firas M. Allan Mohammed ahmed Elhossiny Salem Belhaj Imen ben Mohamed Faculty of Computing Studies Arab Open University Amman Jordan Computer Science Department Science College Northern Border University Arar Kingdom of Saudi Arabia Artificial Intelligence and Data Engineering Laboratory LR21ES23 Faculty of Sciences of Bizerte University of Carthage Tunis Tunisia Applied College Northern Border University Arar Kingdom of Saudi Arabia Faculty of Specific Education Mansoura University Mansoura Egypt

This article delves into the intricate relationship between big data, cloud computing, and artificial intelligence, shedding light on their fundamental attributes and interdependence. It explores the seamless amalgamation of AI methodologies within cloud computing and big data analytics, encompassing the development of a cloud computing framework built on the robust foundation of the Hadoop platform, enriched by AI learning algorithms. Additionally, it examines the creation of a predictive model empowered by tailored artificial intelligence techniques. Rigorous simulations are conducted to extract valuable insights, facilitating method evaluation and performance assessment, all within the dynamic Hadoop environment, thereby reaffirming the precision of the proposed approach. The results and analysis section reveals compelling findings derived from comprehensive simulations within the Hadoop environment. These outcomes demonstrate the efficacy of the Sport AI Model (SAIM) framework in enhancing the accuracy of sports-related outcome predictions. Through meticulous mathematical analyses and performance assessments, integrating AI with big data emerges as a powerful tool for optimizing decision-making in sports. The discussion section extends the implications of these results, highlighting the potential for SAIM to revolutionize sports forecasting, strategic planning, and performance optimization for players and coaches. The combination of big data, cloud computing, and AI offers a promising avenue for future advancements in sports analytics. This research underscores the synergy between these technologies and paves the way for innovative approaches to sports-related decision-making and performance enhancement.

关键词： Artificial Intelligence Machine Learning Spark Apache Big Data SAIM

An FPGA Design for Real-Time Image Denoising

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Computer Systems Science & Engineering 2022年第11期43卷 803-816页

作者： ahmed ben Atitallah Department of Electrical Engineering Jouf UniversitySakakaAljoufSaudi Arabia

The increasing use of images in miscellaneous applications such as medical image analysis and visual quality inspection has led to growing interest in image ***,images are often contaminated with noise which may corrupt any of the following image processing ***,noise filtering is often a necessary preprocessing step for the most image processing ***,in this paper an optimized field-programmable gate array(FPGA)design is proposed to implement the adaptive vector directional distance filter(AVDDF)in hardware/software(HW/SW)codesign context for removing noise from the images in *** that,the high-level synthesis(HLS)flow is used through the Xilinx Vivado HLS tool to reduce the design complexity of the HW *** SW part is developed based on C/C++programming language and executed on an advanced reduced instruction set computer(RISC)machines(ARM)Cortex-A53 *** communication between the SW and HW parts is achieved using the advanced extensible Interface stream(AXI-stream)interface to increase the data *** experiment results on the Xilinx ZCU102 FPGA board show an improvement in processing time of the AVDDF filter by 98%for the HW/SW implementation relative to the SW *** result is given for the same quality of image between the HW/SW and SW implementations in terms of the normalized color difference(NCD)and the peak signal to noise ratio(PSNR).

关键词： AVDDF filter image denoising HW/SW codesign high-level synthesis FPGA

Unified FPGA Design for the HEVC Dequantization and Inverse Transform Modules

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Computers, Materials & Continua 2022年第6期71卷 4319-4335页

作者： Turki M.Alanazi ahmed ben Atitallah Department of Electrical Engineering Jouf UniversitySakakaAljouf2014Saudi Arabia

As the newest standard,the High Efficiency Video Coding(HEVC)is specially designed to minimize the bitrate for video data transfer and to support High Definition(HD)and ULTRA HD video resolutions at the cost of increasing computational complexity relative to earlier standards like the ***,real-time video decoding with HEVC decoder becomes a challenging ***,the Dequantization and Inverse Transform(DE/IT)are one of the computationally intensive modules in the HEVC decoder which are used to reconstruct the residual ***,in this paper,a unified hardware architecture is proposed to implement the HEVC DE/IT module for all Transform Unit(TU)block size,including 4×4,8×8,16×16 and 32×*** architecture is designed using the High-Level Synthesis(HLS)and the Low-Level Synthesis(LLS)methods in order to compare and determine the best method to implement in real-time the DE/IT *** fact,the C/C++programming language is used to generate an optimized hardware design for DE/IT module through the Xilinx Vivado HLS *** the other hand,the LLS hardware architecture is designed by the VHSIC Hardware Description language(VHDL)and using the pipeline technique to decrease the processing *** experimental results on the Xilinx XC7Z020 FPGA show that the LLS design increases the throughput in term of frame rate by 80%relative to HLS design with a 4.4%increase in the number of Look-Up Tables(LUTs).Compared with existing related works in literature,the proposed architectures demonstrate significant advantages in hardware cost and performance improvement.

关键词： HEVC decoder dequantization IDCT/IDST LLS design HLS design FPGA

An Efficient HW/SW Design for Text Extraction from Complex Color Image

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Computers, Materials & Continua 2022年第6期71卷 5963-5977页

作者： Mohamed Amin ben Atitallah Rostom Kachouri ahmed ben Atitallah Hassene Mnif LETI(E.N.I.S.) University of SfaxSfaxTunisia Laboratory of informatics Gaspard-MongeA3SIESIEE ParisCNRSGustave Eiffel UniversityFrance National Engineering School of Gabes(ENIG) University of GabesTunisia Department of Electrical Engineering Jouf UniversitySakakaAljoufSaudi Arabia

In the context of constructing an embedded system to help visually impaired people to interpret text,in this paper,an efficient High-level synthesis(HLS)Hardware/Software(HW/SW)design for text extraction using the Gamma Correction Method(GCM)is ***,the GCM is a common method used to extract text from a complex color image and *** purpose of this work is to study the complexity of the GCM method on Xilinx ZCU102 FPGA board and to propose a HW implementation as Intellectual Property(IP)block of the critical blocks in this method using HLS flow with taking account the quality of the text *** IP is integrated and connected to the ARM Cortex-A53 as coprocessor in HW/SW codesign *** experimental results show that theHLS HW/SW implementation of the GCM method on ZCU102 FPGA board allows a reduction in processing time by about 89%compared to the SW *** result is given for the same potency and strength of SW implementation for the text extraction.

关键词： Text extraction GCM HW/SW codesign FPGA HLS flow

Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

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Computers, Materials & Continua 2022年第8期72卷 2859-2875页

作者： Areej A.Malibari Siwar ben Haj Hassine Abdelwahed Motwakel Manar ahmed Hamza Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayilAsirSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Atherosclerosis diagnosis is an inarticulate and complicated cognitive *** on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical *** the medical diagnostic outcomes need to be prompt and accurate,the recently developed artificial intelligence(AI)and deep learning(DL)models have received considerable attention among research *** study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification(MDL-BADDC)*** proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing,feature selection,classification,and parameter ***,the proposed MDL-BADDC technique designs a novel Quasi-Oppositional Barnacles Mating Optimizer(QOBMO)based feature selection ***,the deep stacked autoencoder(DSAE)based classification model is designed for the detection and classification of atherosclerosis ***,the krill herd algorithm(KHA)based parameter tuning technique is applied to properly adjust the parameter *** order to showcase the enhanced classification performance of the MDL-BADDC technique,a wide range of simulations take place on three benchmarks biomedical *** comparative result analysis reported the better performance of the MDL-BADDC technique over the compared methods.

关键词： Atherosclerosis disease biomedical data data classification machine learning disease diagnosis deep learning

Sustainable Energy Management with Traffic Prediction Strategy for Autonomous Vehicle Systems

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Computers, Materials & Continua 2022年第8期72卷 3465-3479页

作者： Manar ahmed Hamza Masoud Alajmi Jaber SAlzahrani Siwar ben Haj Hassine Abdelwahed Motwakel Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

Recent advancements of the intelligent transportation system(ITS)provide an effective way of improving the overall efficiency of the energy management strategy(EMSs)for autonomous vehicles(AVs).The use of AVs possesses many advantages such as congestion control,accident prevention,and ***,energy management and traffic flow prediction(TFP)still remains a challenging problem in *** complexity and uncertainties of driving situations adequately affect the outcome of the designed *** this view,this paper presents novel sustainable energy management with traffic flow prediction strategy(SEM-TPS)for *** SEM-TPS technique applies type II fuzzy logic system(T2FLS)energy management scheme to accomplish the desired engine torque based on distinct *** addition,the membership functions of the T2FLS scheme are chosen optimally using the barnacles mating optimizer(BMO).For accurate TFP,the bidirectional gated recurrent neural network(Bi-GRNN)model is used in AVs.A comprehensive experimental validation process is performed and the results are inspected with respect to several evaluation *** experimental outcomes highlighted the supreme performance of the SEM-TPS technique over the recent state of art approaches.

关键词： Sustainable energy transportation energy management traffic flow prediction soft computing deep learning

An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

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Computer Systems Science & Engineering 2023年第7期46卷 701-717页

作者： ahmed ben Atitallah Mohamed Amin ben Atitallah Yahia Said Mohammed Albekairi Anis Boudabous Turki MAlanazi Khaled Kaaniche Mohamed Atri Department of Electrical Engineering College of EngineeringJouf UniversitySakakaSaudi Arabia Laboratory of Informatics Gaspard-MongeA3SIESIEE ParisCNRSGustave Eiffel UniversityFrance LETI ENISUniversity of SfaxSfaxTunisia Remote Sensing Unit College of EngineeringNorthern Border UniversityArarSaudi Arabia Laboratory of Electronics and Microelectronics(LR99ES30) University of MonastirTunisia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia College of Computer Sciences King Khalid UniversityAbhaSaudi Arabia

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from *** this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into *** system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been *** this study,an acceleration of the GCM algorithm(AGCM)is *** AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original *** assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech *** text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

关键词： Text recognition system GCM AGCM OCR color images graphical interface