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A Game-Theoretic Approach to Safe Crowd Evacuation in Emergencies

computers, Materials & Continua 2024年第4期79卷 1631-1657页

作者： Maria Gul Imran Ali Khan Gohar Zaman Atta Rahman Jamaluddin Mir Sardar Asad Ali Biabani May IssaAldossary Mustafa Youldash Ashraf Saadeldeen Maqsood Mahmud Asiya Abdus Salam Dania Alkhulaifi Abdullah AlTurkey31Department of Computer Science COMSATS University IslamabadAbbottabad CampusAbbottabad22010Pakistan Department of Computer Science Abbottabad University of Science and TechnologyAbbottabad22010Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Science and Technology Unit Umm Al-Qura UniversityMakkah21955Saudi Arabia Deanship of Scientific Research Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyOmdurman Islamic UniversityOmdurman14415Sudan Business Analytic Program Department of Management and MarketingCollege of Business AdministrationUniversity of BahrainSakhir32038Bahrain

Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, manyresearchers proposed game theoreticmodels to avoid and remove obstacles for crowd evacuation. Game theoreticalmodels aim to study and analyze the strategic behaviors of individuals within a crowd and their interactionsduring the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. Thesemodels consider a group of individuals as homogeneous objects with the same goals, involve complex mathematicalformulation, and cannot model real-world scenarios such as panic, environmental information, crowds that movedynamically, etc. The proposed work presents a game theoretic model integrating an agent-based model to removethe obstacles from exits. The proposed model considered the parameters named: (1) obstacle size, length, andwidth, (2) removal time, (3) evacuation time, (4) crowd density, (5) obstacle identification, and (6) route *** proposed work conducts various experiments considering different conditions, such as obstacle types, obstacleremoval, and several obstacles. Evaluation results show the proposed model’s effectiveness compared with existingliterature in reducing the overall evacuation time, cell selection, and obstacle removal. The study is potentially usefulfor public safety situations such as emergency evacuations during disasters and calamities.

关键词： Safe crowd evacuation public safety emergency transition probability cooperation

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QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

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computers, Materials & Continua 2022年第1期70卷 1127-1140页

作者： Nadia Tabassum Tahir Alyas Muhammad Hamid Muhammad Saleem Saadia Malik Syeda Binish Zahra Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Statistics and Computer science University of veterinary and animal sciencesLahore54000Pakistan Department of Industrial Engineering Faculty of EngineeringRabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology-RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any *** assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation *** is the emerging environment for distributed services at various *** to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing *** of resources in the Cloud is difficult because resources provide numerous measures of quality of *** this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource *** article is focused on the cloud service’s security,cloud reliability,and could *** this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust *** findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.

关键词： Cloud computing performance quality of service machine learning neuro-fuzzy

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Self-Guided Autoencoders for Unsupervised Change Detection in Heterogeneous Remote Sensing Images

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2458-2471页

作者： Shi, Jiao Wu, Tiancheng Kai Qin, Alex Lei, Yu Jeon, Gwanggil Northwestern Polytechnical University School of Electronics and Information Xi'an710129 China Northwestern Polytechnical University in Shenzhen Research and Development Institute Shenzhen518057 China Chongqing Innovation Center of Northwestern Polytechnical University Chongqing401135 China Swinburne University of Technology Department of Computer Science and Software Engineering HawthornVIC3122 Australia Incheon National University Department of Embedded Systems Engineering Incheon22012 Korea Republic of

To address the problem of enormous differences in two heterogeneous images, the traditional unsupervised frameworks are most normally realized by converting two images into a common domain with various auxiliary strategies, such as transformation and alignment, which requires extensive calculation and has difficulty balancing the training tasks. To achieve a concise framework, this article proposes self-guided autoencoders (SGAE) for unsupervised change detection (CD) in heterogeneous remote sensing images (RSIs). Unlike traditional methods that aim to narrow the differences of heterogeneous images to highlight the changed information, SGAE forces the flow of identification in formation generated in unlabeled data through self-guided iterations. First, initial unsupervised networks output an elementary change map that will be screened to obtain reliable pseudolabels. The selected pseudolabeled samples will be used as the input of a supervised network to obtain another change map. Then, multiple change maps will be fused to refine the confidence of pseudolabels again, obtaining new fused pseudolabeled samples for the self-guided network, which will be trained with pseudolabeled samples and unlabeled samples. Finally, the above operations will be repeated to continuously optimize the net, which helps itself to extract the discriminative features for classification in self-guided iterations. Experiments compared with several algorithms on four datasets demonstrate the effectiveness and robustness of our method, which can help unsupervised models improve discriminative feature extraction and classification performance with a more flexible learning method. © 2020 IEEE.

关键词： Feature extraction

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An Efficient Steganographic Approach for Securing Text Transmission Using S-Box in Cloud 2

An Efficient Steganographic Approach for Securing Text Trans...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Ashraf, Humaira Malik, Javeria Ihsan, Uswa Al-Quayed, Fatima Humayun, Mamoona Jhanjhi, N.Z. International Islamic University Department of Computer Science and Software Engineering Islamabad Pakistan Department of Computer Science College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Department of Information Systems College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Taylor's University Malaysia Applied Science Research Center Applied Science Private University Amman11937 Jordan

ISBN: (纸本)9798350335644

In era of modern world and technology where everything is digitalized. Cloud computing emerged as one of the fastest growing parts of digital industry. With the Succor of cloud computing models, business accomplishes their objectives with least exertion when contrasted with traditional processing environment. In spite of these compensations, yet security of the information in cloud database is the significant fear in endorsement of cloud. Although several techniques have been proposed such as cryptographic and steganographic approaches, but all of these have some loopholes. Therefore, in this paper new data protection technique based on steganographic encryption is proposed which has less computational time and secure against known plain text and Man-In-Middle Attack. © 2023 IEEE.

关键词： Cryptography

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IPL Data Analysis by Web Scraping and Using PowerBI

IPL Data Analysis by Web Scraping and Using PowerBI

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Mogith P Mothiswar T B G Mohammad Abubak J. Jagannathan N. Balaganesh Software Engineering Vellore Institute of Technology Vellore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

Cricket fans throughout the world avidly follow the Indian Premier League (IPL), a competition of great fame. The IPL data is examined in this using Exploratory Data Analysis (EDA) approaches to find hidden trends, patterns, and insights. Key findings are summarized in EDA, a critical stage of data processing that is frequently complemented with visual aids. Through EDA, the goal is to investigate several factors, including team performance, player data, match results, and venue effects. Data transformation, cleaning, and visualization will all be part of producing insightful findings. Win percentages, player averages, and run distributions are examples of key performance indicators (KPIs) that will be looked at. The analysis's findings will give teams, athletes, and supporters important new information.

关键词： Visualization Technological innovation Fans Data analysis Key performance indicator Data visualization Market research Knowledge discovery Cleaning

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Building the metaverse using digital twins at all scales,states,and relations

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Virtual Reality & Intelligent Hardware 2022年第6期4卷 459-470页

作者： Zhihan LV Shuxuan XIE Yuxi LI M.Shamim HOSSAIN Abdulmotaleb El SADDIK Department of Game Design Faculty of ArtsUppsala UniversitySweden College of Computer Science and Technology Qingdao UniversityQingdaoChina Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Electrical Engineering and Computer Science(EECS) University of OttawaOttawaOntarioCanada

Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the micro-,meso-,or *** Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain ***,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social ***,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.

关键词： Digital twins Metaverse Sensor

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Arabic Sentiment Analysis of Mobile Banking Services Reviews 10

Arabic Sentiment Analysis of Mobile Banking Services Reviews

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10th International Conference on Social Networks Analysis, Management and Security, SNAMS 2023

作者： Khabour, Safaa M. Mustafa, Dheya Althebyan, Qutaibah Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Al Ain University Dept. of Cybersecurity Al Ain United Arab Emirates Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9798350318906

Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially Jordan, is seeing an increase in the usage of online banking. This propensity toward digital transition has been accelerated by the COVID-19 pandemic. Mobile banking service companies aim to effectively use customers' feedback to identify areas for improvement in customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on mobile banking reviews in Arabic, exploiting machine learning, natural language processing, and resampling methods to obtain subjective feedback, determine polarity, and identify customers' feelings in the banking domain. This work walks the reader through detailed steps of cleaning and preprocessing a manually annotated dataset of online banking reviews in Arabic, followed by features extraction and modeling, dataset splitting, and balancing training data. Finally, we examined classification algorithms including Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF). Ensemble hard and soft voting ML methods were also evaluated. We achieved a maximum accuracy of about 94% using the LR classifier and a maximum precision of 94% using the LR and hard voting methods. Our methodology will enable banks to acquire insights on how to develop their online presence and meet the demands of customers and stakeholders. © 2023 IEEE.

关键词： Sentiment analysis

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Sentiment Analysis to manage Health Crisis in Smart Cities 18

Sentiment Analysis to manage Health Crisis in Smart Cities

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18th IEEE International Conference on computer Science and information Technologies, CSIT 2023

作者： Bouhissi, Houda El Itmacene, Ouardia Oubekkou, Milissa Pavlova, Olga Hovorushchenko, Tetiana Shestakevych, Tetiana University of Bejaia LMED Laboratory Faculty of Exact Sciences Bejaia06000 Algeria University of Bejaia Faculty of Exact Sciences Bejaia06000 Algeria Khmelnytskyi National University Department of Computer Engineering & Information Systems Khmelnytskyi Ukraine Lviv Polytechnic National University Information Systems and Networks Department Lviv Ukraine

ISBN: (纸本)9798350360462

Sentiment analysis is a branch of natural language processing that analyzes textual data and provides insights into users' opinions. In the context of smart cities, sentiment analysis seeks to seamlessly integrate technological innovations into people's daily lives, fostering sustainability and enhancing overall quality of life while monitoring citizen satisfaction levels. This approach allows for more precise analysis and facilitates the implementation of strategies geared towards improving services and the general quality of life. The aim of this paper is to propose an approach for managing healthcare crises in smart cities. The proposal relies on a hybrid approach that combines LSTM for tweet classification with EHO for optimizing classification parameters. Experimental results have demonstrated the effectiveness of this proposed technique. © 2023 IEEE.

关键词： Smart city

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Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

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computer systems Science & engineering 2023年第5期45卷 1199-1210页

作者： Himanshu Sharma karthikeyan Rajagopal G.Gugapriya Rajneesh Pareek Arun Kumar HayaMesfer Alshahrani Mohamed K.Nour Hany Mahgoub Mohamed Mousa Anwer Mustafa Hilal Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia School of Electronics Engineering Vellore Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Electrical Engineering Department Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Multicarrier Waveform(MCW)has several advantages and plays a very important role in cellular *** generation(5G)MCW such as Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC)are thought to be important in 5G *** Peak to Average Power Ratio(PAPR)is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user *** paper presents a novel Divergence Selective Mapping(DSLM)and Divergence Partial Transmission Sequence(D-PTS)for 5G *** is seen that the proposed D-SLM and PTS lower PAPR with low computational *** work highlighted a combination of multi-data block partial transmit schemes along with tone *** this,an overlapping factor is used to determine the number of data blocks for every ***,considering only those data blocks that have minimum signal power,the use of DSLM and DPTS are required to eliminate the segment’s *** results reveal that the suggested hybrid technique proves to be better than the conventional PTS ***,the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing(OFDM)waveform.

关键词： 5G PAPR D-SLM D-PTS

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Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection

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computer systems Science & engineering 2023年第9期46卷 3103-3119页

作者： Khaled M.Alalayah Fatma S.Alrayes Mohamed K.Nour Khadija M.Alaidarous Ibrahim M.Alwayle Heba Mohsen Ibrahim Abdulrab Ahmed Mesfer Al Duhayyim Department of Computer Science College of Science and ArtsNajran UniversitySharurahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and *** malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,*** is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of *** prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine Learning(ML)*** study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection(LBAAA-OMLMD)approach in computer *** presented LBAAA-OMLMDmodelmainly aims to detect and classify the existence of ransomware and goodware in the *** accomplish this,the LBAAA-OMLMD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality ***,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is *** FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier *** experimental validation of the LBAAA-OMLMD model is tested using a benchmark dataset,and the outcomes are inspected in distinct *** comprehensive comparative examination demonstrated the betterment of the LBAAAOMLMD model over recent algorithms.

关键词： computer networks machine learning security malware detection feature selection ransomware

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