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Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

computers, Materials & Continua 2022年第6期71卷 6011-6037页

作者： Ahmed Saeed Alfakeeh Abdulmohsen Almalawi Fawaz Jaber Alsolami Yoosef B.Abushark Asif Irshad Khan Adel Aboud SBahaddad Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow-226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow-226028Uttar PradeshIndia

The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate *** this situation,it’s critical to design and construct software that is both secure and *** security is the most well-defined aspect of health information software systems,it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same *** this league,it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development *** research work employed the Fuzzy Analytic Network Process(Fuzzy ANP)to estimate the impact of the overall sustainable-security of health information software systems and their characteristics in order to achieve a high level of ***,the study validates the efficacy of the Fuzzy ANP procedure by testing it on five different versions of a health information software system through Fuzzy Technique for Order of Preference by Similarity to Ideal Solutions(Fuzzy TOPSIS).Despite the sensitivity of the health information software systems,this study employedmultiple versions of health information software *** compared with the existing procedures for testing the sustainable-security of health information software systems,the outcomes were conclusive and significantly more *** saving time and resources,the mechanism suggested in this research work aims to establish an outline that software practitioners can follow to enhance the sustainablesecurity of health information software systems.

关键词： Sustainable-security sustainable health information software systems analytic network process fuzzy logic

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AI-Based Vehicle Detection and Its Emission Impact on AQI 1

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19th Control Instrumentation system Conference, CISCON 2022

作者： Bhat, Suhas Sudhir Pai, M. D. Varun Holla, B. Ashutosh Pai, M. M. Manohar Department of Computer Science and Engineering Manipal Institute of Technology Manipal576104 India Department of Computer Science and Engineering Government Polytechnic Karkala Karkala574104 India Department of Information and Communication Technology Manipal Institute of Technology Manipal576104 India

ISBN: (数字)9789819995547

ISBN: (纸本)9789819995530

Vehicle traffic has a significant impact on urban quality of life. One major impact is on the air quality of the surrounding area. With increasing vehicle traffic, air quality gets drastically affected in urban cities. A dense accumulation of vehicles is commonly observed across a network of roads during peak hours, drastically affecting the air quality index of the surrounding environment. Adverse measures and prevention are required to control air quality to maintain a healthier environment. Hence, determining vehicle emission details is necessary to address the overall impact in the surrounding areas. For any organization/gated campus, it is required to minimize the air pollution caused by vehicles that regularly visit the campus. By identifying the vehicles appearing on the campus premises, their emission impact on the surrounding can be determined using the PUC certificate of the vehicle. This study performs a vehicle emission impact on a gated campus using a deep learning approach. Real-time surveillance footage is processed with a deep learning model to detect vehicle and its license plate. Furthermore, air quality sensors deployed at strategical locations provide real-time data on pollutant concentration. This combined information is further utilized by a Web application to provide statistics of AQI in real time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Air quality

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Estimating Usable-Security Through Hesitant Fuzzy Linguistic Term Sets Based Technique

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computers, Materials & Continua 2022年第3期70卷 5683-5705页

作者： Abdulaziz Attaallah Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia

The apparent contradiction between usability and security has been discussed in the literature for several *** continuous trade-off requires be acknowledging and handling whenever security solutions are ***,some progressive analysts point out that present security solutions are usually very difficult for several users,and they have expressed a willingness to simplify the security product user *** security is still mostly unexplored territory in computer *** we are all aware with security and usability on many levels,usable security has received little operational *** have recently focused primarily on usable *** consumers prefer to discard unsatisfactory solutions,attaining well-balanced degrees of both is a prerequisite for adequate *** should be examined from the viewpoint of security to be properly *** aim of this research study is to explore and discuss universally accepted and solutionindependent factors influencing the perceived usable-security of institutional *** integrated Hesitant Fuzzy Linguistic term sets based technique was chosen as the methodology,and the experts and academicians opinion were *** use of predetermined selection criteria resulted in the compilation of statistical findings and were used to determine the usable-security of five different instituational websites.

关键词： Usable security accessibility expert evaluation usability criteria fuzzy logic

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Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

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computer systems science & Engineering 2023年第10期47卷 791-807页

作者： Sundas Rukhsar Mazhar Javed Awan Usman Naseem Dilovan Asaad Zebari Mazin Abed Mohammed Marwan Ali Albahar Mohammed Thanoon Amena Mahmoud Department of Software Engineering University of Management and TechnologyLahore54770Pakistan School of Computer Science The University of SydneySydneyAustralia Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Computer Science Umm Al Qura UniversityMecca24211Saudi Arabia Computer Science Department Faculty of Computers and InformationKafrelsheikh UniversityKafrelsheikhEgypt

Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions,sentiments,and data in the modern ***,a widely used microblogging site where individuals share their thoughts in the form of tweets,has become a major source for sentiment *** recent years,there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or *** or expressions of people about a particular topic,situation,person,or product can be identified from sentences and divided into three categories:positive for good,negative for bad,and neutral for mixed or confusing *** process of analyzing changes in sentiment and the combination of these categories is known as“sentiment analysis.”In this study,sentiment analysis was performed on a dataset of 90,000 tweets using both deep learning and machine learning *** deep learning-based model long-short-term memory(LSTM)performed better than machine learning *** short-term memory achieved 87%accuracy,and the support vector machine(SVM)classifier achieved slightly worse results than LSTM at 86%.The study also tested binary classes of positive and negative,where LSTM and SVM both achieved 90%accuracy.

关键词： COVID-19 artificial intelligence machine learning deep learning sentimental analysis support vector classifier

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Judicial system in Bangladesh Using Distributed Blockchain technology 3

Judicial System in Bangladesh Using Distributed Blockchain T...

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3rd International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

作者： Rakibul Hasan, M.M. Kashem, Mohammod Abul Fatin, Md. Al-Abrar Roni, Md. Mainul Islam Bangladesh University of Professionals Department of Information and Communication Technology Dhaka Bangladesh International University of Business Agriculture and Technology Department of Computer Science and Engineering Dhaka Bangladesh Dhaka University of Engineering and Technology Department of Computer Science and Engineering Gazipur Bangladesh

ISBN: (纸本)9798350388282

The current judicial system process, which is conducted manually in Bangladesh, is characterized by a high degree of uncertainty and risk, as well as a wide range of possibilities for fraudulent documents and the preservation of the ownership details of cases. Therefore, the current system does not appear to be feasible, effective. We have created our proposed blockchain-based judicial management system with the SHA-256 data encryption technique. This system will ensure the safety of the case transactions and will be able to store, authenticate, and maintain entire pertinent information of the case document. The mentioned architecture will be able to revoke and to detect attempts to change the case by using a variety of technologies, including IPFS, Proof of Stack (PoS), and public-key cryptography. These techniques will lead to subsequent more efficient solutions than the existing systems and improve how the general public views Bangladesh's judicial system. © 2024 IEEE.

关键词： Blockchain

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Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol

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SN computer science 2024年第5期5卷 546页

作者： Khan, Surbhi Bhatia Kumar, Ankit Mashat, Arwa Pruthviraja, Dayananda Imam Rahmani, Mohammad Khalid Mathew, Jimson School of Science Engineering and Environment University of Salford Salford United Kingdom Department of Information Technology Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Rabigh 21911 Saudi Arabia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal 576104 India Department of Computer Science College of Computing and Informatics Saudi Electronic University Riyadh 11673 Saudi Arabia Department of Computer Science and Engineering Indian Institute of Technology Patna Bihar Patna India

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless sensors, and automation, facilitating the integration of various applications ranging from smart homes to wearable devices. In addition, the advent of artificial intelligence (AI) amplifies this influence by providing data-driven analytics, optimising processes, and presenting novel opportunities for growth. Nevertheless, the widespread adoption of devices within Internet of Things (IoT) networks gives rise to apprehensions regarding increased energy consumption. In order to ensure the longevity of network operations, it is imperative to employ energy-efficient protocols for sensor nodes that possess limited power resources. One example of a protocol that demonstrates this concept is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. This protocol effectively divides networks into clusters and dynamically adjusts the cluster heads to optimise the transmission of data to the base stations. Our study enhances the LEACH protocol by incorporating digital twin simulation, thereby enhancing the efficiency of IoT systems. Virtual network models and AI analytics are employed to assess energy consumption and performance. Cache nodes play a crucial role within this framework as they collect data from cluster heads in order to transmit it to the base station. By leveraging artificial intelligence (AI) and simulation techniques, we are able to improve the energy efficiency and reliability of the Internet of Things (IoT) systems. The findings indicate a significant reduction of 83% in non-functioning nodes and a notable increase of 1.66 times in energy levels of nodes compared to conventional approaches. This study highlights a potential direction for energy-efficient, AI-enhanced Internet of Things (IoT) networking through

关键词： Cluster head Clustering Data aggregation Gateway Internet of things LEACH Lifetime

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Gaps in value-driven connectivity: A case study on connectivity challenges in Northern Europe 35

Gaps in value-driven connectivity: A case study on connectiv...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Karppinen, Pasi Bandaranayake, Sameera Haukipuro, Lotta Elmistikawy, Yomn Saarnisaari, Harri University of Oulu Faculty of Information Technology and Electrical Engineering Oulu Finland University of Oulu Faculty of Science Oulu Finland Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden

ISBN: (纸本)9798350362244

Well-working Internet connectivity is a fundamental citizen right and a necessity in modern digital societies. Nevertheless, the digital divide persists and often affects rural or remote areas. To bridge the digital divide, we need to understand the specific rural use cases and challenges. This would increase understanding about problems weak Internet connectivity causes, what is required from the connectivity technology and what is needed from policymakers and regulation. The goal of this paper is to identify rural use cases and analyze consequences to future connectivity technology through a mixed-methods approach: we investigated the divide and its consequences by a questionnaire and interviews conducted in northern Europe. The study found that the main issues faced by rural internet users are related to capacity, availability, and vulnerability of internet services. These issues hinder their daily life, work activities, and expose them to system-level risks. The article discusses how these findings can inform the development of more inclusive and resilient internet connectivity solutions. © 2024 IEEE.

关键词： digital divide mobile communication rural connectivity social sustainability

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Framework for Logistics During Hajj Using Autonomous Mobile Robots 1

Framework for Logistics During Hajj Using Autonomous Mobile ...

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1st International Conference on Logistics, ICL 2024

作者： Nasti, Shoaib Mohd Chishti, Mohammad Ahsan Central University of Kashmir Department of Information Technology Ganderbal India National Institute of Technology Department of Computer Science and Engineering Srinagar India

ISBN: (纸本)9798331518844

Every year, Muslims worldwide travel to Saudi Arabia to Perform Hajj. Both government and private organizations provide various services and facilities to support these pilgrims and resolve any difficulties they may face. There is a scope for improvement in high-quality and smart logistical services for pilgrims. Smart logistic services have emerged as a practical solution to the growing complexity and volume of logistical operations. Artificial Intelligence, Internet of Things, and Robotics are all helping logistical operations to function more smoothly and efficiently. This paper briefly describes the background of the holy pilgrimage. Then, it contributes to the literature by introducing logistics services using autonomous mobile robots. Finally, the theoretical framework for the smart logistic system using an autonomous mobile robot is illustrated, which summarizes our survey on using the autonomous mobile robot for logistic services during the Hajj season. © 2024 IEEE.

关键词： Mobile robots

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A machine learning approach for accelerated design of magnesium alloys. Part A:Alloy data and property space

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Journal of Magnesium and Alloys 2023年第11期11卷 3620-3633页

作者： M.Ghorbani M.Boley P.N.H.Nakashima N.Birbilis Department of Materials Science and Engineering Monash UniversityVIC3800Australia Faculty of Information Technology Monash UniversityVIC3800Australia College of Engineering and Computer Science Australian National UniversityACT2601Australia Faculty of Engineering Science and the Built EnvironmentDeakin UniversityVIC3125Australia

Typically, magnesium alloys have been designed using a so-called hill-climbing approach, with rather incremental advances over the past century. Iterative and incremental alloy design is slow and expensive, but more importantly it does not harness all the data that exists in the field. In this work, a new approach is proposed that utilises data science and provides a detailed understanding of the data that exists in the field of Mg-alloy design to date. In this approach, first a consolidated alloy database that incorporates 916 datapoints was developed from the literature and experimental work. To analyse the characteristics of the database, alloying and thermomechanical processing effects on mechanical properties were explored via composition-process-property matrices. An unsupervised machine learning(ML) method of clustering was also implemented, using unlabelled data, with the aim of revealing potentially useful information for an alloy representation space of low dimensionality. In addition, the alloy database was correlated to thermodynamically stable secondary phases to further understand the relationships between microstructure and mechanical properties. This work not only introduces an invaluable open-source database, but it also provides, for the first-time data, insights that enable future accelerated digital Mg-alloy design.

关键词： Magnesium Alloy design Mg-alloy database Data analysis Data visualisation Unsupervised machine learning

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PointBi-FPN: An Extention to Pointpillars for LiDAR 3D Object Detection in Autonomous Vehicles Using Bi-Directional Feature Pyramid Network

PointBi-FPN: An Extention to Pointpillars for LiDAR 3D Objec...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Soumya, A. Krishna Mohan, C. Cenkeramaddi, Linga Reddy Babu, Sobhan Indian Institute of Technology Department of Computer Science and Engineering Hyderabad India University of Agder Department of Information and Communication Technology Grimstad Norway

ISBN: (纸本)9798350350821

Autonomous vehicles increasingly rely on accurate three-dimensional (3D) object detection for safe navigation. While two-dimensional (2D) methods offer computational efficiency, the shift to 3D detection enhances precision in understanding environments. Point-based and voxel-based approaches are accurate but computationally intensive for onboard deployment. Pillar-based methods like PointPillars provide efficiency but may lack detection accuracy compared to voxel-based approaches. In this paper, we focus on enhancing the performance of PointPillars, a popular pillar-based detector, using LiDAR data. The proposed approach (PointBi-FPN) employs a bi-directional feature pyramid network (Bi-FPN) as a backbone, that aggregates multiscale features in the input data, providing a holistic view of the environment, which is crucial for detecting objects of varying sizes and distances accurately. Bi-FPN improves the model's understanding of complex scenes, making it more robust to occlusions. Through extensive experimentation on the KITTI dataset, the PointBi-FPN approach demonstrates better performance across all three detection benchmarks: BEV (Bird's Eye View), 3D (Three-Dimensional), and AOS (Average Orientation Similarity). Notably, the proposed approach exhibits significant improvements, particularly in accurately detecting objects labeled as 'hard' difficulty. © 2024 IEEE.

关键词： Object detection

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