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CryptoNight Mining Algorithm with YAC Consensus for Social Media Marketing Using Blockchain

Computers, Materials & Continua 2022年第5期71卷 3921-3936页

作者： Anwer Mustafa Hil Fahd N.Al-Wesabi Hadeel Alsolai Ola Abdelgney Omer Ali Nadhem Nemri manar Ahmed Hamza abu Sarwar Zamani Mohammed Rizwanullah Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia&Faculty of Computer and ITSana’a UniversityYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

Social media is a platform in which user can create,share and exchange the knowledge/*** media marketing is to identify the different consumer’s demands and engages them to create marketing *** popular social media platforms are Microsoft,Snapchat,Amazon,Flipkart,Google,eBay,Instagram,Facebook,Pin interest,and *** main aim of social media marketing deals with various business partners and build good relationship with millions of customers by satisfying their *** technology is replacing old approaches in the social media marketing to new technology-based ***,this disruptive technology creates some issues like fake news,insecure,inconsistency,inaccuracy and so *** issues contribute economic instability in the society,diminishing the level of *** overcome these issues,this paper we present blockchain as disruptive technology for social media *** plays a vital role on social media marketing by providing secure to the company page in the *** properties of disruptive potential of blockchain on social media marketing is transparency,security,reliability and *** paper presents a new framework for disruptive technology in blockchain social media marketing using fusion of CryptoNight mining algorithm with YAC consensus algorithm[BCDSMM-CNYAC].This mining algorithm provides high CPU efficiency,high dimensionality of secure and detecting falsifying data attack in the social media *** the data analysis we proposed ANOVA analysis method regarding to the factors of age,time,frequency visiting times of social media *** reliability analysis of data Cronbach’s alpha tests are implemented.

关键词： Cryptonight disruptive technology smart contracts social media security YAC

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Design of Intelligent Alzheimer Disease Diagnosis Model on CIoT Environment

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Computers, Materials & Continua 2022年第6期71卷 5979-5994页

作者： Anwer Mustafa Hilal Fahd NAl-Wesabi Mohamed Tahar Ben Othman Khaled Mohamad Almustafa Nadhem Nemri Mesfer Al Duhayyim manar Ahmed Hamza abu Sarwar Zamani Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer Science College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Information Systems College of Computer and Information SystemsPrince Sultan UniversitySaudi Arabia Department of Information Systems King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Presently,cognitive Internet of Things(CIoT)with cloud computing(CC)enabled intelligent healthcare models are developed,which enables communication with intelligent devices,sensor modules,and other stakeholders in the healthcare sector to avail effective decision *** the other hand,Alzheimer disease(AD)is an advanced and degenerative illness which injures the brain cells,and its earlier detection is necessary for suitable interference by healthcare *** this aspect,this paper presents a new Oriented Features from Accelerated Segment Test(FAST)with Rotated Binary Robust Independent Elementary Features(BRIEF)Detector(ORB)with optimal artificial neural network(ORB-OANN)model for AD diagnosis and classification on the CIoT based smart healthcare *** initial pre-processing,bilateral filtering(BLF)based noise removal and region of interest(RoI)detection processes are carried *** addition,the ORBOANN model includes ORB based feature extractor and principal component analysis(PCA)based feature ***,artificial neural network(ANN)model is utilized as a classifier and the parameters of the ANN are optimally chosen by the use of salp swarm algorithm(SSA).A comprehensive experimental analysis of the ORB-OANN model is carried out on the benchmark database and the obtained results pointed out the promising outcome of the ORB-OANN technique in terms of different measures.

关键词： Cognitive internet of things machine learning parameter tuning alzheimer’s disease healthcare decision making

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Metaheuristics with Machine Learning Enabled Information Security on Cloud Environment

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Computers, Materials & Continua 2022年第10期73卷 1557-1570页

作者： Haya Mesfer Alshahrani Faisal S.Alsubaei Taiseer Abdalla Elfadil Eisa Mohamed K.Nour manar Ahmed Hamza Abdelwahed Motwakel abu Sarwar Zamani Ishfaq Yaseen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The increasing quantity of sensitive and personal data being gathered by data controllers has raised the security needs in the cloud *** computing(CC)is used for storing as well as processing ***,security becomes important as the CC handles massive quantity of outsourced,and unprotected sensitive data for public *** study introduces a novel chaotic chimp optimization with machine learning enabled information security(CCOML-IS)technique on cloud *** proposed CCOML-IS technique aims to accomplish maximum security in the CC environment by the identification of intrusions or anomalies in the *** proposed CCOML-IS technique primarily normalizes the networking data by the use of data conversion and min-max *** by,the CCOML-IS technique derives a feature selection technique using chaotic chimp optimization algorithm(CCOA).In addition,kernel ridge regression(KRR)classifier is used for the detection of security issues in the *** design of CCOA technique assists in choosing optimal features and thereby boost the classification performance.A wide set of experimentations were carried out on benchmark datasets and the results are assessed under several *** comparison study reported the enhanced outcomes of the CCOML-IS technique over the recent approaches interms of several measures.

关键词： Information security cloud computing intrusion anomalies data mining feature selection classification

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Improved Chameleon Swarm Optimization-Based Load Scheduling for IoT-Enabled Cloud Environment

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Computer Systems Science & Engineering 2023年第8期46卷 1371-1383页

作者： manar Ahmed Hamza Shaha Al-Otaibi Sami Althahabi Jaber S.Alzahrani Abdullah Mohamed Abdelwahed Motwakel abu Sarwar Zamani Mohamed I.Eldesouki Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science&Art atMahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecaa24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Internet of things(IoT)and cloud computing(CC)becomes widespread in different application domains such as business,e-commerce,healthcare,*** recent developments of IoT technology have led to an increase in large amounts of data from various *** IoT enabled cloud environment,load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource *** load scheduling problem was regarded as an optimization problem that is solved by *** this view,this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling(C3SOA-LS)technique for IoT enabled cloud *** proposed C3SOA-LS technique intends to effectually schedule the tasks and balance the load uniformly in such a way that maximum resource utilization can be ***,the presented C3SOA-LS model involves the design of circle chaotic mapping(CCM)with the traditional chameleon swarm optimization(CSO)algorithm for improving the exploration process,shows the novelty of the *** proposed C3SOA-LS model computes an objective with the minimization of energy consumption and *** experimental outcome implied that the C3SOA-LS model has showcased improved performance and uniformly balances the load over other approaches.

关键词： Cloud environment load scheduling energy consumption internet of things metaheuristics

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Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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Computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed A.Aziz manar Ahmed Hamza Abdelwahed Motwakel abu Sarwar Zamani Ishfaq Yaseen Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime

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Intelligent Deer Hunting Optimization Based Grid Scheduling Scheme

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Computers, Materials & Continua 2022年第7期72卷 181-195页

作者： Mesfer Al Duhayyim Majdy M.Eltahir Imène Issaoui Fahd N.Al-Wesabi Anwer Mustafa Hilal Fuad Ali Mohammed Al-Yarimi manar Ahmed Hamza abu Sarwar Zamani Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Natural and Applied Sciences Community CollegeQassim UniversityAl-Bukairiyah52571Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

The grid environment is a dynamic,heterogeneous,and changeable computing system that distributes various services amongst different *** attain the benefits of collaborative resource sharing in Grid computing,a novel and proficient grid resource management system(RMS)is ***,detection of an appropriate resource for the presented task is a difficult *** scientists have presented algorithms for mapping tasks to the *** of them focus on fault tolerance,user fulfillment,and load *** this motivation,this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm(DHOA),called IGSS-DHOA which schedules in such a way that the makespan gets minimized in the grid *** IGSS-DHOA technique is mainly based on the hunting nature of humans toward *** also derives an objective function with candidate solution(schedule)as input and the outcome is the makespan value denoting the quality of the candidate *** simulation results highlighted the supremacy of the IGSS-DHOA technique over the recent state of art techniques with the minimal average processing cost of 31717.9.

关键词： Grid services grid scheduling resources makespan np hard problem metaheuristics

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Parallel power system restoration planning using heuristic initialization and discrete evolutionary programming

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Journal of Modern Power Systems and Clean Energy 2017年第6期5卷 991-1003页

作者： Dian Najihah abu talib Hazlie MOKHLIS Mohamad Sofian abu TALIP Kanendra NAIDU Department of Electrical Engineering University of Malaya50603 Kuala LumpurMalaysia Electrical Technology Section University of Kuala LumpurBritish Malaysian Institute53100 GombakMalaysia

This paper proposes a sectionalizing planning for parallel power system restoration after a complete system *** restoration is conducted in order to reduce the total restoration process *** and operation knowledge of the system,operating personnel experience,and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/*** planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory *** of transmission lines that should not be restored during parallel restoration process(cut set)is determined in order to sectionalize the system into subsystems or *** island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the *** operation and constraints(black start generator availability,load-generation balance and maintaining acceptable voltage magnitude within each island)is also takeninto account in the course of this *** method is validated using the IEEE 39-bus and 118-bus *** results in terms of restoration time was compared to other methods reported in the literature.

关键词： Sectionalizing planning Parallel power system restoration Graph theory Heuristic initialization Discrete evolutionary programming(DEP)optimization method

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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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Improved Attentive Recurrent Network for Applied Linguistics-Based Offensive Speech Detection

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Computer Systems Science & Engineering 2023年第11期47卷 1691-1707页

作者： manar Ahmed Hamza Hala J.Alshahrani Khaled Tarmissi Ayman Yafoz Amira Sayed A.Aziz Mohammad Mahzari abu Sarwar Zamani Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing,language teaching,translation and speech *** ever-growing Online Social Networks(OSNs)experience a vital issue to confront,i.e.,hate *** the OSN-oriented security problems,the usage of offensive language is the most important threat that is prevalently found across the *** on the group targeted,the offensive language varies in terms of adult content,hate speech,racism,cyberbullying,abuse,trolling and *** these,hate speech is the most intimidating form of using offensive language in which the targeted groups or individuals are intimidated with the intent of creating harm,social chaos or *** Learning(ML)techniques have recently been applied to recognize hate speech-related *** current research article introduces a Grasshopper Optimization with an Attentive Recurrent Network for Offensive Speech Detection(GOARN-OSD)model for social *** GOARNOSD technique integrates the concepts of DL and metaheuristic algorithms for detecting hate *** the presented GOARN-OSD technique,the primary stage involves the data pre-processing and word embedding ***,this study utilizes the Attentive Recurrent Network(ARN)model for hate speech recognition and *** last,the Grasshopper Optimization Algorithm(GOA)is exploited as a hyperparameter optimizer to boost the performance of the hate speech recognition *** depict the promising performance of the proposed GOARN-OSD method,a widespread experimental analysis was *** comparison study outcomes demonstrate the superior performance of the proposed GOARN-OSD model over other state-of-the-art approaches.

关键词： Applied linguistics hate speech offensive language natural language processing deep learning grasshopper optimization algorithm

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Using the Taguchi Method and Grey Relational Analysis to Optimize the Performance of a Solar Air Heater

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Energy Engineering 2021年第5期118卷 1425-1438页

作者： manar B.AL-Hajji Nabeel abu Shaban Shahnaz Al Khalil Ayat Al-Jarrah Department of Mechanical Engineering School of EngineeringThe University of JordanAmmanJordan Department of Mechanical Engineering Faculty of Engineering and Technology Al-Zaytonah University of JordanAmmanJordan Department of Mechatronics Engineering Faculty of EngineeringThe Hashemite UniversityZarqa’Jordan

Solar energy is regarded as one of the promising renewable energy sources in the *** main aim of this study is to use the Taguchi-Grey relational grade analysis to optimize the performance of two Solar Air Heaters(SAHs).A typical Grey–Taguchi method was *** Orthogonal Array,Signal-to-Noise ratio,Grey Relational Grade,and Analysis of Variance were employed to investigate the performance characteristics of *** observations were made in agreement with Jordanian climate 32°00′N latitude and 36°00′E longitude with a solar intensity of 500 W\m^(2).The operating factors selected for optimization are the tilt angle(T)with three levels(0°,22°,45°),inlet velocity(V)with two levels(1.2,1.8 m/s),and absorber plate material(M)with two levels(Aluminum,wood).In this study,the Grey–Taguchi approach is validated by performing 12 individual *** results show that the process factors sequence required for a maximum SAH efficiency(SAHµ)is V>T>*** this approach,we combined the Orthogonal Array design with Grey Relational *** a result of that,the level of each operating conditions which optimizes both process responses(Temperature difference,ΔT and Solar air heater efficiency,SAHµ)can be specified with a minimum number of tests compared with classic Grey Relational *** optimal operating conditions of a SAH for multiple performance characteristics are determined as T2,M2,and V2,respectively,which are in congruence with the experimental results.

关键词： Solar air heater collector efficiency thermal efficiency grey-taguchi method robust design

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