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Optimal Resource allocation Method for Device-to-Device Communication in 5G Networks

Computers, Materials & Continua 2022年第4期71卷 1-15页

作者： Fahd N.al-Wesabi Imran Khan Saleem Latteef Mohammed Huda Farooq Jameel mohammad alamgeer ali M.al-Sharafi Byung Seo Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Faculty of Computer and IT Sana’a UniversityYemen Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of Medical Instrumentation Techniques Engineering Electrical Engineering Technical CollegeMiddle Technical UniversityBaghdad10013Iraq Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of Computers and Information TechnologyUniversity of BishaKSA Department of Software and Communications Engineering Hongik UniversityKorea

With the rapid development of the next-generation mobile network,the number of terminal devices and applications is growing ***,how to obtain a higher data rate,wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of ***-to-Device(D2D)communication technology and other frontier communication technologies have ***-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular *** has become one of the key technologies of the fifth-generation mobile communications system(5G).D2D communication technology which is introduced into cellular networks can effectively improve spectrum utilization,enhance network coverage,reduce transmission delay and improve system throughput,but it would also bring complicated and various interferences due to reusing cellular resources at the same *** resource management is one of the most challenging and importing issues to give full play to the advantages of D2D *** resource allocation is an important factor that needs to be addressed in D2D ***,this paper proposes an optimization method based on the game-matching *** main idea is to model the optimization problem of the quality-of-experience based on user fairness and solve it through game-matching *** results show that the proposed algorithm effectively improved the resource allocation and utilization as compared with existing algorithms.

关键词： D2D communication resource allocation optimization networks

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Data Mining with Comprehensive Oppositional Based Learning for Rainfall Prediction

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Computers, Materials & Continua 2023年第2期74卷 2725-2738页

作者： mohammad alamgeer Amal al-Rasheed Ahmad alhindi Manar Ahmed Hamza Abdelwahed Motwakel Mohamed I.Eldesouki Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemMecca24382Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia

Data mining process involves a number of steps fromdata collection to visualization to identify useful data from massive data *** same time,the recent advances of machine learning(ML)and deep learning(DL)models can be utilized for effectual rainfall *** this motivation,this article develops a novel comprehensive oppositionalmoth flame optimization with deep learning for rainfall prediction(COMFO-DLRP)*** proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental ***,data pre-processing and correlation matrix(CM)based feature selection processes are carried *** addition,deep belief network(DBN)model is applied for the effective prediction of rainfall ***,COMFO algorithm was derived by integrating the concepts of comprehensive oppositional based learning(COBL)with traditional MFO ***,the COMFO algorithm is employed for the optimal hyperparameter selection of the DBN *** demonstrating the improved outcomes of the COMFO-DLRP approach,a sequence of simulations were carried out and the outcomes are assessed under distinct *** simulation outcome highlighted the enhanced outcomes of the COMFO-DLRP method on the other techniques.

关键词： Data mining rainfall prediction deep learning correlation matrix hyperparameter tuning metaheuristics

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Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

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Computers, Materials & Continua 2022年第7期72卷 109-124页

作者： Khalil Ibrahim mohammad Abuzanouneh Fahd N.al-Wesabi Amani Abdulrahman albraikan Mesfer al Duhayyim M.al-Shabi Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zamani K.Muthulakshmi Department of Information Technology College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia&Faculty of Computer and ITSana’a UniversitySana’a61101Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Management Information System College of Business and AdministrativeTaibah UniversityMedina42353Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electronics and Communication Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India

Agriculture 4.0,as the future of farming technology,comprises numerous key enabling technologies towards sustainable *** use of state-of-the-art technologies,such as the Internet of Things,transform traditional cultivation practices,like irrigation,to modern solutions of precision *** achieve effectivewater resource usage and automated irrigation in precision agriculture,recent technologies like machine learning(ML)can be *** this motivation,this paper design an IoT andML enabled smart irrigation system(IoTML-SIS)for precision *** proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for *** proposed IoTML-SIS model involves different IoT based sensors for soil moisture,humidity,temperature sensor,and ***,the sensed data are transmitted to the cloud server for processing and decision ***,artificial algae algorithm(AAA)with least squares-support vector machine(LS-SVM)model is employed for the classification process to determine the need for ***,the AAA is applied to optimally tune the parameters involved in the LS-SVM model,and thereby the classification efficiency is significantly *** performance validation of the proposed IoTML-SIS technique ensured better performance over the compared methods with the maximum accuracy of 0.975.

关键词： Automatic irrigation precision agriculture smart farming machine learning cloud computing decision making internet of things

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Robust Watermarking Scheme for NIfTI Medical Images

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Computers, Materials & Continua 2022年第5期71卷 3107-3125页

作者： Abhishek Kumar Kamred Udham Singh Visvam Devadoss Ambeth Kumar Tapan Kant Abdul Khader Jilani Saudagar Abdullah al Tameem Mohammed al Khathami Muhammad Badruddin Khan Mozaherul Hoque Abul Hasanat khalid Mahmood Malik School of Computer Science and IT JAIN(Deemed to be University)Bangalore560069India Department of Computer Science and Information Engineering National Cheng Kung UniversityTainan701Taiwan Department of Computer Science&Engineering Panimalar Engineering CollegeAnna UniversityChennai600123India Patna Women’s College Patna800001India Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Computer Science and Engineering Oakland UniversityRochester48309USA

Computed Tomography(CT)scan and Magnetic Resonance Imaging(MRI)technologies are widely used in medical *** the last few months,due to the increased use of CT scans,millions of patients have had their CT scans ***,as a result,images showing the Corona Virus for diagnostic purposes were digitally transmitted over the *** major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the *** a result,it is important to apply a robust and secure watermarking technique to these ***,watermarking schemes have been developed for various image formats,***,.bmp,***,but their impact on NIfTI(Neuroimaging Informatics Technology Initiative)images is not noteworthy.A watermarking scheme based on the Lifting Wavelet Transform(LWT)and QR factorization is presented in this *** LWT and QR are combined,the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme’s *** watermarks are added to the host image in this *** the performance of the graphics card is done by using PSNR,SSIM,Q(a formula which measures image quality),SNR,and Normalized *** watermarking scheme withstands a variety of noise attacks and conversions,including image compression and decompression.

关键词： Watermarking NIfTI LWT QR image security

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Modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

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Computers, Materials & Continua 2022年第5期71卷 3953-3968页

作者： Mesfer al Duhayyim Amani Abdulrahman albraikan Fahd N.al-Wesabi Hiba M.Burbur mohammad alamgeer Anwer Mustafa Hilal Manar Ahmed Hamza Mohammed Rizwanullah Department of Natural and Applied Sciences College of Community-AflajPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer Science College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer Science College of Science and Arts in Al-BukairiyahQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Information Systems College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Short-term traffic flow prediction (TFP) is an important area inintelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodicfeatures are susceptible to weather conditions, making TFP a challengingissue. TFP process are significantly influenced by several factors like accidentand weather. Particularly, the inclement weather conditions may have anextreme impact on travel time and traffic flow. Since most of the existing TFPtechniques do not consider the impact of weather conditions on the TF, it isneeded to develop effective TFP with the consideration of extreme weatherconditions. In this view, this paper designs an artificial intelligence based TFPwith weather conditions (AITFP-WC) for smart cities. The goal of the AITFPWC model is to enhance the performance of the TFP model with the inclusionof weather related conditions. The proposed AITFP-WC technique includesElman neural network (ENN) model to predict the flow of traffic in smartcities. Besides, tunicate swarm algorithm with feed forward neural networks(TSA-FFNN) model is employed for the weather and periodicity analysis. Atlast, a fusion of TFP and WPA processes takes place using the FFNN modelto determine the final prediction output. In order to assess the enhancedpredictive outcome of the AITFP-WC model, an extensive simulation analysisis carried out. The experimental values highlighted the enhanced performanceof the AITFP-WC technique over the recent state of art methods.

关键词： Smart cities artificial intelligence urban transportation deep learning weather condition TFP

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An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

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Computers, Materials & Continua 2022年第3期70卷 5583-5600页

作者： Anwer Mustafa Hilal Fahd N.al-Wesabi Mohammed alamgeer Manar Ahmed Hamza mohammad Mahzari Murad A.almekhlafi Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of English College of Science&HumanitiesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Faculty of Engineering Department of Electrical EngineeringCommunication EngineeringSana’a UniversityYemen

Due to the rapid increase in the exchange of text information via internet networks,the security and authenticity of digital content have become a major research *** main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital *** this paper,an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on theArabic text transmitted online via an Internet *** this purpose,the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing *** the proposed method,both embedding and extracting of the watermark are logically implemented,which causes no change in the digital *** is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital *** digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic *** extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy,robustness,and effectiveness under multiple random locations of the common tampering attacks.

关键词： Text analysis text-watermarking tampering detection text authentication

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Tailoring the optical and magnetic properties of La-BaM hexaferrites by Ni substitution

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Chinese Physics B 2022年第2期31卷 570-575页

作者： Hafiz T.ali MRamzan M Imran Arshad Nicola A.Morley M.Hassan Abbas mohammad Yusuf Atta Ur Rehman khalid Mahmood Adnan ali Nasir Amin MAjaz-un-Nabi Department of Mechanical Engineering College of EngineeringTaif UniversityTaif 21944Saudi Arabia Department of Physics Government College UniversityFaisalabadPakistan Department of Materials Science and Engineering University of SheffieldSir Robert Hadfield BuildingMapping St.SheffieldS13JDUK Department of Clinical Pharmacy College of PharmacyTaif UniversityTaif 21944Saudi Arabia

We investigate the impact of Ni insertion on the structural,optical,and magnetic properties of Ba_(0.8)La_(0.2)Fe_(12-x)Ni_(x)O_(19)hexaferrites(Ni substituted La-BaM hexaferrites).Samples were prepared using the conventional co-precipitation method and sintered at 1000℃for 4 hours to assist the crystallization *** analysis of the structure of the samples was carried out using an x-ray diffraction(XRD)*** M-type hexagonal structure of all the samples was confirmed using XRD *** lattice parameters a and c were found to be in the ranges of 5.8925±0.001 nm–5.8952±0.001 nm and 23.2123±0.001 nm–23.2219±0.001 nm,*** M-type hexagonal nature of the prepared samples was also indicated by the presence of corresponding FT-IR bands and Raman modes in the FT-IR and Raman spectra,*** results confirmed the successful synthesis of the samples according to the required stoichiometric ratio.A UV-vis spectrometer was used to record the absorption spectra of the prepared samples in the wavelength range of 200 nm–1100 *** optical energy bandgap of the samples was found to be in the range of 1.21 eV–3.39 *** M–H loops of the samples were measured at room temperature at an applied magnetic field range of 0 kOe–60 kOe.A high saturation magnetization of 99.92 emu/g was recorded in the sample with x=0 at a microwave operating frequency of 22.2 *** high value of saturation magnetization is due to the substitution of La3+ions at the spin-up(12k,2a,and 2b)*** Ni substitution is proven to be a potential candidate for the tuning of the optical and magnetic parameters of M-type ***,we suggest that the prepared samples are suitable for use in magneto-optic applications.

关键词： M-type hexaferrite nanostructured materials magnetic properties optical properties

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Adaptive task scheduling in IoT using reinforcement learning

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International Journal of Intelligent Computing and Cybernetics 2020年第3期13卷 261-282页

作者： mohammad khalid Pandit Roohie Naaz Mir mohammad Ahsan Chishti Department of Computer Science and Engineering National Institute of Technology SrinagarSrinagarIndia

Purpose-The intelligence in the Internet of Things(IoT)can be embedded by analyzing the huge volumes of data generated by it in an ultralow latency *** computational latency incurred by the cloud-only solution can be significantly brought down by the fog computing layer,which offers a computing infrastructure to minimize the latency in service delivery and *** this purpose,a task scheduling policy based on reinforcement learning(RL)is developed that can achieve the optimal resource utilization as well as minimum time to execute tasks and significantly reduce the communication costs during distributed ***/methodology/approach-To realize this,the authors proposed a two-level neural network(NN)-based task scheduling system,where the first-level NN(feed-forward neural network/convolutional neural network[FFNN/CNN])determines whether the data stream could be analyzed(executed)in the resourceconstrained environment(edge/fog)or be directly forwarded to the *** second-level NN(RL module)schedules all the tasks sent by level 1 NN to fog layer,among the available fog *** real-time task assignment policy is used to minimize the total computational latency(makespan)as well as communication ***-Experimental results indicated that the RL technique works better than the computationally infeasible greedy approach for task scheduling and the combination of RL and task clustering algorithm reduces the communication costs ***/value-The proposed algorithm fundamentally solves the problem of task scheduling in realtime fog-based IoT with best resource utilization,minimum makespan and minimum communication cost between the tasks.

关键词： Internet of things Neural networks Task scheduling

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Assessment of ecological risk for heavy metals in surface sediment of an urban river in a developing country

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International Journal of Sediment Research 2023年第6期38卷 834-846页

作者： Md Saiful Islam Md Humayun Kabir Mir mohammad ali Md Towhidul Islam Asfia Niger Md Humayun Kabir Zulhilmi Ismail Sujat Ahmed khalid A.Ibrahim Abubakr M.Idris Department of Soil Science Patuakhali Science and Technology University Department of Environmental Science and Resource Management Mawlana Bhashani Science and Technology University Department of Aquaculture Sher-e-Bangla Agricultural University Department of Soil Science Bangabandhu Sheikh Mujibur Rahman Agricultural University Centre for River and Coastal Engineering(CRCE) Universiti Teknologi Malaysia(UTM) Department of Water & Environmental Engineering Faculty of Civil EngineeringUniversiti Teknologi Malaysia(UTM) Environment Center for People & Environ(CPE) Department of Biology College of ScienceKing Khalid University Center for Environment and Tourism Studies and Research King Khalid University Department of Chemistry College of ScienceKing Khalid University Research Center for Advanced Materials Science(RCAMS) King Khalid University

The speed of increasing threats to the riverine water resources makes it more critical to protect the health of Old Brahmaputra River *** current study was done to investigate the concentrations,distributions,sources,and ecological risk of heavy metals in surface sediment from the Old Brahmaputra River,*** were collected from seven sites and analyzed with an inductively coupled plasma-mass spectrometer(ICP-MS).The results showed that mean concentrations(mg/kg) of heavy metals were in the order of nickel(Ni)(44.69)> chromium(Cr)(30.16)> lead(Pb)(19.31)>copper(Cu)(17.84)> cadmium(Cd)(3.94)> arsenic(As)(2.73).The contamination factor(CF),pollution load index(PLI),enrichment factor(EF),and geo-accumulation index(Igeo) indicated low to moderate *** unit analysis revealed that the studied metals from all stations posed low *** sediment of the study river was uncontaminated to moderately contaminated,posing a minimal ecological ***,Cr,Ni,and Pb originated from anthropogenic sources rather than geogenic sources,and caused the severity of *** this regard,pollutant-based intensive monitoring of heavy metals and holistic ecological risk assessments are required to maintain a sound and healthy aquatic environment in the river.

关键词： Heavy metals Sediment quality Ecological risk Old Brahmaputra river Source identification

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Electrical, Thermal, Photocatalytic and Antibacterial Studies of Metallic Oxide Nanocomposite Doped Polyaniline

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Journal of Materials Science & Technology 2013年第9期29卷 795-800页

作者： Saima Sultana Rafuddin mohammad Zain Khan khalid Umar M.Muneer Membrane Research Laboratory Department of Chemistry Faculty of Science Aligarh Muslim University Department of Civil Environmental and Geomatic Engineering Chadwick Building University College London Environmental Research Laboratory Department of Chemistry Faculty of Science Aligarh Muslim University

ZnO-ZrO2 nanocomposite was prepared by sol-gel method and in-situ polymerization was used to synthesize ZnO-ZrO2 nanocomposite doped polyaniline （PANI）. The materials were characterized by X-ray diffraction （XRD）, Fourier transform infrared （FTIR） spectroscopy, transmission electron microscopy （TEM）, scanning electron microscopy （SEM） and energy dispersive X-ray spectroscopy （EDX） to ensure the crystallite size, functional groups, morphology and chemical composition of the polymer nanocomposite complex. The average particle size of the ZnO-Zr02 nanoparticles was found to be 20.5 nm. Thermal gravimetric analysis （TGA） was used to study the thermal stability of the complex, shows improved thermal stability of polymer nanocomposite as compared to the pure organic polymer. The material also possesses good electrical conductivity. Additionally, the photocatalytic activity of the materials was investigated by monitoring the decolorization of Acid Blue 29 dye in a UV photocatalytic reactor and PANI-ZnO-ZrO2 was found to possess higher photocatalytic activity than pure PANI. Finally, the antibacterial activity of the materials was examined and it was observed that PANI-ZnO-ZrO2 could be used as an excellent antibacterial agent. Hence, desired properties could be integrated by mixing appropriate phases of the materials for specific applications such as heterogeneous catalyst, antibacterial agents, antibiotics delivery and high temperature conducting polymers.

关键词： Nanocomposites Polyaniline Electrical conductivity Photocatalyst Antibacterial agents

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