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A Novel Technique for Early Detection of COVID-19

computers, Materials & Continua 2021年第8期68卷 2283-2298页

作者： Mohammad Yamin Adnan Ahmed Abi Sen Zenah Mahmoud AlKubaisy Rahaf Almarzouki Department of Management information systems Faculty of Economics and AdministrationKing Abdulaziz UniversityJeddah21589Saudi Arabia faculty of computer and information systems Islamic University of MadinahAl MedinaSaudi Arabia

COVID-19 is a global pandemic disease,which results from a dangerous coronavirus attack,and spreads aggressively through close contacts with infected people and *** far,there is not any prescribed line of treatment for COVID-19 *** to control the disease are very limited,partly due to the lack of knowledge about technologies which could be effectively used for early detection and control the *** detection of positive cases is critical in preventing further spread,achieving the herd immunity,and saving ***,so far we do not have effective toolkits to diagnose very early detection of the *** research findings have suggested that radiology images,such as X-rays,contain significant information to detect the presence of COVID-19 virus in early ***,to detect the presence of the disease in in very early stages from the X-ray images by the naked eye is not *** Intelligence(AI)techniques,machine learning in particular,are known to be very helpful in accurately diagnosing many diseases from radiology *** paper proposes an automatic technique to classify COVID-19 patients from their computerized tomography(CT)scan *** technique is known as Advanced Inception based Recurrent Residual Convolution Neural Network(AIRRCNN),which uses machine learning techniques for classifying *** focus on the Advanced Inception based Recurrent Residual Convolution Neural Network,because we do not find it being used in the ***,we conduct principal component analysis,which is used for dimensional *** results of our method have demonstrated an accuracy of about 99%,which is regarded to be very efficient.

关键词： COVID-19 classification feature selection dimensionality reduction chest CT deep learning deep convolutional neural network AIRRCNN

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Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

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computers, Materials & Continua 2022年第5期71卷 3019-3033页

作者： Tahir Alyas Iqra Javed Abdallah Namoun Ali Tufail Sami Alshmrany Nadia Tabassum Department of computer Science Lahore Garrison UniversityLahore54000Pakistan faculty of computer and information systems Islamic University of MadinahMadinah42351Saudi Arabia Department of computer Science Virtual University of PakistanLahore54000Pakistan

Efforts were exerted to enhance the live virtual machines(VMs)migration,including performance improvements of the live migration of services to the *** VMs empower the cloud users to store relevant data and ***,the utilization of servers has increased significantly because of the virtualization of computer systems,leading to a rise in power consumption and storage requirements by data centers,and thereby the running *** center migration technologies are used to reduce risk,minimize downtime,and streamline and accelerate the data center move ***,several parameters,such as non-network overheads and downtime adjustment,may impact the live migration time and server downtime to a large *** virtualizing the network resources,the infrastructure as a service(IaaS)can be used dynamically to allocate the bandwidth to services and monitor the network flow *** to the large amount of filthy retransmission,existing live migration systems still suffer from extensive downtime and significant performance degradation in crossdata-center *** study aims to minimize the energy consumption by restricting the VMs migration and switching off the guests depending on a threshold,thereby boosting the residual network bandwidth in the data center with a minimal breach of the service level agreement(SLA).In this research,we analyzed and evaluated the findings observed through simulating different parameters,like availability,downtime,and outage of VMs in data center *** new paradigm is composed of two forms of detection strategies in the live migration approach from the source host to the destination source machine.

关键词： Cloud computing IaaS data centre storage performance analysis live migration

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An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

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computers, Materials & Continua 2023年第1期74卷 2097-2113页

作者： Hamayun Khan Irfan Ud Din Arshad Ali Mohammad Husain Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan faculty of computer and information systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip(MPSoC)has become an integral chip design issue for multiprocessor *** performance measurement of computational systems is changing with the advancement in *** to shrinking and smaller chip size power densities onchip are increasing rapidly that increasing chip temperature in multi-core embedded *** operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor(CMOS)circuits because high on-chip temperature adversely affects the life span of the *** this paper an energy-aware dynamic power management technique based on energy aware earliest deadline first(EA-EDF)scheduling is proposed for improving the performance and reliability by reducing energy and power consumption in the system on chip(SOC).Dynamic power management(DPM)enables MPSOC to reduce power and energy consumption by adopting a suitable core configuration for task *** migration avoids peak temperature values in the multicore *** utilization factor(ui)on central processing unit(CPU)core consumes more energy and increases the temperature *** technique switches the core bymigrating such task to a core that has less temperature and is in a low power *** proposed EA-EDF scheduling technique migrates load on different cores to attain stability in temperature among multiple cores of the CPU and optimized the duration of the idle and sleep periods to enable the low-temperature *** effectiveness of the EA-EDF approach reduces the utilization and energy consumption compared to other existing methods and *** simulation results show the improvement in performance by optimizing 4.8%on u_(i) 9%,16%,23%and 25%at 520 MHz operating frequency as compared to other energy-aware techniques for MPSoCs when the least number of tasks is in running state and can

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

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Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs

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computers, Materials & Continua 2023年第1期74卷 965-981页

作者： Hamayun Khan Irfan Ud din Arshad Ali Sami Alshmrany Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan faculty of computer and information systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor *** the advancement of technology,the performance management of central processing unit(CPU)is *** densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip *** energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor(CMOS)circuits and reduces the speed by 10%–15%because excessive on-chip temperature shortens the chip’s life *** this paper,we address the scheduling&energy utilization problem by introducing and evaluating an optimal energy-aware earliest deadline first scheduling(EA-EDF)based technique formultiprocessor environments with task migration that enhances the performance and efficiency in multiprocessor systemon-chip while lowering energy and power *** selection of core andmigration of tasks prevents the system from reaching itsmaximumenergy utilization while effectively using the dynamic power management(DPM)*** in the execution of tasks the temperature and utilization factor(u_(i))on-chip increases that dissipate more *** proposed approach migrates such tasks to the core that produces less heat and consumes less power by distributing the load on other cores to lower the temperature and optimizes the duration of idle and sleep times across multiple *** performance of the EA-EDF algorithm was evaluated by an extensive set of experiments,where excellent results were reported when compared to other current techniques,the efficacy of the proposed methodology reduces the power and energy consumption by 4.3%–4.7%on a utilization of 6%,36%&46%at 520&624 MHz operating frequency when particularly in comparison to other energy-aware methods for *** are running and accurately scheduled to make an energy-efficient

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

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Reducing Dataset Specificity for Deepfakes Using Ensemble Learning

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computers, Materials & Continua 2023年第2期74卷 4261-4276页

作者： Qaiser Abbas Turki Alghamdi Yazed Alsaawy Tahir Alyas Ali Alzahrani Khawar Iqbal Malik Saira Bibi faculty of computer and information systems islamic university madinah Madinah42351Saudi Arabia Department of computer Science Lahore Garrison UniversityLahore54000Pakistan The university of Lahore Sargodha40100Pakistan university of Sargodha Department of Computer Science&ITSargodha40100Pakistan

The emergence of deep fake videos in recent years has made image falsification a real danger.A person’s face and emotions are deep-faked in a video or speech and are substituted with a different face or voice employing deep learning to analyze speech or emotional *** of how clever these videos are frequently,Manipulation is challenging to *** media are the most frequent and dangerous targets since they are weak outlets that are open to extortion or slander a *** earlier times,it was not so easy to alter the videos,which required expertise in the domain and ***,the generation of fake videos has become easier and with a high level of realism in the *** are forgeries and altered visual data that appear in still photos or video *** automatic identification systems have been developed to solve this issue,however they are constrained to certain datasets and performpoorly when applied to different *** study aims to develop an ensemble learning model utilizing a convolutional neural network(CNN)to handle deepfakes or *** employed ensemble learning,a technique combining many classifiers to achieve higher prediction performance than a single classifier,boosting themodel’s *** performance of the generated model is evaluated on Face *** work is about building a new powerful model for automatically identifying deep fake videos with the DeepFake-Detection-Challenges(DFDC)*** test our model using the DFDC,one of the most difficult datasets and get an accuracy of 96%.

关键词： Deep machine learning deep fake CNN DFDC ensemble learning

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Query Optimization Framework for Graph Database in Cloud Dew Environment

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computers, Materials & Continua 2023年第1期74卷 2317-2330页

作者： Tahir Alyas Ali Alzahrani Yazed Alsaawy Khalid Alissa Qaiser Abbas Nadia Tabassum Department of computer Science Lahore Garrison UniversityLahorePakistan faculty of computer Science and information systems islamic university madinah Madinah42351Saudi Arabia Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of computer Science Virtual University of PakistanLahorePakistan

The query optimizer uses cost-based optimization to create an execution plan with the least cost,which also consumes the least amount of *** challenge of query optimization for relational database systems is a combinatorial optimization problem,which renders exhaustive search impossible as query sizes *** in CPU performance have surpassed main memory,and disk access speeds in recent decades,allowing data compression to be used—strategies for improving database performance *** performance enhancement,compression and query optimization are the two most *** reduces the volume of data,whereas query optimization minimizes execution *** the database reduces memory requirement,data takes less time to load into memory,fewer buffer missing occur,and the size of intermediate results is more *** paper performed query optimization on the graph database in a cloud dew environment by considering,which requires less time to execute a *** factors compression and query optimization improve the performance of the *** research compares the performance of MySQL and Neo4j databases in terms of memory usage and execution time running on cloud dew servers.

关键词： Query optimization compression cloud dew decompression graph database

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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

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computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat Ullah Khalil Ullah Habib Shah Abdallah Namoun Khaliq Ur Rahman Department of computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of computer Science King Khalid UniversityAbha62529Saudi Arabia faculty of computer and information systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ

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computers, Materials & Continua 2023年第3期74卷 5641-5661页

作者： Afia Zafar Muhammad Aamir Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi faculty of computer Science and information Technology Universiti Tun Hussein Onn MalaysiaMalaysia School of Electronics Computing and MathematicsUniversity of DerbyUK Department of computer Science National University of TechnologyIslamabadPakistan Department of information Technology College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of computer Science and information systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Department of information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia Department of information systems Faculty of Computer and Information SciencesIslamic University of MadinahMadinah42351Saudi Arabia

In computer vision,convolutional neural networks have a wide range of *** representmost of today’s data,so it’s important to know how to handle these large amounts of data *** neural networks have been shown to solve image processing problems ***,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher *** technique is time consuming and requires a lot of work and domain *** a convolutional neural network architecture is a classic NP-hard optimization *** the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and *** approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random *** address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized *** study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN *** addition,different types and parameter ranges of existing genetic algorithms are *** study was conducted with various state-of-the-art methodologies and *** have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature.

关键词： Non-dominated sorted genetic algorithm convolutional neural network hyper-parameter optimization

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Hill Matrix and Radix-64 Bit Algorithm to Preserve Data Confidentiality

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computers, Materials & Continua 2023年第5期75卷 3065-3089页

作者： Ali Arshad Muhammad Nadeem Saman Riaz Syeda Wajiha Zahra Ashit Kumar Dutta Zaid Alzaid Rana Alabdan Badr Almutairi Sultan Almotairi Department of computer Science National University of TechnologyIslamabadPakistan Department of Computing Abasyn UniversityIslamabadPakistan Department of computer Science and information systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of computer Science Faculty of Computer and Information SystemsIslamic university of MadinahMedinah42351Saudi Arabia Department of information systems Faculty of Computer and Information Sciences CollegeMajmaah University11952Saudi Arabia Department of information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah 11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data,but these techniques and algorithms cannot be used to protect data from an *** cryptography is the best way to transmit data in a secure and reliable *** researchers have developed various mechanisms to transfer data securely,which can convert data from readable to unreadable,but these algorithms are not sufficient to provide complete data *** algorithm has some data security *** some effective data protection techniques are used,the attacker will not be able to decipher the encrypted data,and even if the attacker tries to tamper with the data,the attacker will not have access to the original *** this paper,various data security techniques are developed,which can be used to protect the data from attackers ***,a customized American Standard Code for information Interchange(ASCII)table is *** value of each Index is defined in a customized ASCII *** an attacker tries to decrypt the data,the attacker always tries to apply the predefined ASCII table on the Ciphertext,which in a way,can be helpful for the attacker to decrypt the *** that,a radix 64-bit encryption mechanism is used,with the help of which the number of cipher data is doubled from the original *** the number of cipher values is double the original data,the attacker tries to decrypt each *** of getting the original data,the attacker gets such data that has no relation to the original *** that,a Hill Matrix algorithm is created,with the help of which a key is generated that is used in the exact plain text for which it is created,and this Key cannot be used in any other plain *** boundaries of each Hill text work up to that *** techniques used in this paper are compared with those used in various papers and discussed that how far the current algorithm is better than all other algorit

关键词： Cryptography symmetric cipher text encryption matrix cipher encoding decoding hill matrix 64-bit encryption

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AI-Driven Learning Management systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

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computers, Materials & Continua 2024年第8期80卷 3289-3314页

作者： Sameer Qazi Muhammad Bilal Kadri Muhammad Naveed Bilal AKhawaja Sohaib Zia Khan Muhammad Mansoor Alam Mazliham Mohd Su’ud Department of computer Science Faculty of EngineeringScience and TechnologyIQRA UniversityKarachi75500Pakistan College of computer and information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia faculty of Engineering Department of Electrical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia faculty of Engineering Department of Mechanical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia faculty of Computing Riphah International UniversityIslamabad46000Pakistan faculty of Computing and Informatics(FCI)Multimedia university Cyberjaya63100Malaysia faculty of Engineering and information Technology School of Computer ScienceUniversity of Technology SydneySydneyNSW 2007Australia

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the *** foremost and most prime sector among those affected were schools,colleges,and *** education system of entire nations had shifted to online education during this *** shortcomings of Learning Management systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of *** paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user *** AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based *** layer enhancements are also required,such as AI-based online proctoring and user authentication using *** extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of *** also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

关键词： Learning management systems chatbots ChatGPT online education Internet of Things(IoT) artificial intelligence(AI) convolutional neural networks natural language processing

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