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2023 Human-Centered Cognitive systems, HCCS 2023

作者： Akhtar, Raybal Safyan, Muhammad Iqbal, Muddesar Sarwar, Sohail University of Management and Technology Department of Informatics and Systems Lahore Pakistan Government College University Lahore Department of Computer Science Lahore Pakistan Prince Sultan University Department of Communication & Network Engineering Riyadh Saudi Arabia Bahria University Islamabad Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798350359183

Online examination evaluation methods are used as an alternative to the traditional examination's way of evaluation methods. They offer a number of advantages while addressing issues associated with outdated conventional approaches. Online evaluation methods are mainly used for objective and short answers based exams but may not suitable for assessing the depth knowledge in candidates. So, candidate's descriptive examinations are conducted to assess their depth of knowledge. Descriptive evaluation methods have been put into practice for quite some time but they greatly rely on keyword-matching techniques between the questions and answers. Due to this limitation, the semantic meanings of these answers are ignored. In current research, the deficiencies in prevalent systems have been addressed by calculating the semantic and syntactic similarity between answers. Moreover, the repetitive words and similarity between counteractive answers has also been considered. We have used SQuAD1 dataset in current research. Our model has achieved a value of 0.88 in terms of accuracy for while computing similarity among listed items. © 2023 IEEE.

关键词： Semantics

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Shortest Job First with Gateway-based Resource Management Strategy for Fog Enabled Cloud Computing 4

Shortest Job First with Gateway-based Resource Management St...

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4th IEEE International Conference on Data Engineering and communication systems, ICDECS 2024

作者： Anbazhagan, K. Kumar, Rotash Thilagavathy, R. Anuradha, D. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Government Engineering College Department of Electronics and Communication Engineering Rajasthan Jhalawar India College of Engineering and Technology Srm Institute of Science and Technology Kattankulathur Department of Computing Technologies Chennai India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India

ISBN: (纸本)9798350393354

In recent years, fog computing has extended cloud services to the network edge, lowering network latency and congestion and overcoming cloud computing restrictions. Many hurdles, however, must be overcome before the benefits of the fog-IoT paradigm for low-latency applications can be completely realized. The most challenging difficulty in IoT applications is developing efficient resource management strategies that maximize throughput while minimizing delay. IoT and fog computing, rather than simply utilizing cloud computing technology, have brought intriguing new data management solutions. Fog computing makes real-time analytics applications conceivable. After combining fog computing technologies with Internet of Things (IoT) applications, the system can reply in milliseconds. Existing fog resource managers focus on a subset of fog resource management parameters such as system response time, network bandwidth, energy consumption, and latency. No Fog resource management takes multiple factors into account at the same time for decision-making, which will become increasingly crucial in intelligent homes. Gateway-based Fog Computing pioneered the introduction of the shortest job (SJFGFC) to address these difficulties. The technique is validated in an IoT-based imaginative house automation scenario before being evaluated in a small-scale bright home experiment using the iFogSim toolbox and empirical models. © 2024 IEEE.

关键词： Fog computing

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Intrusion Detection systems in Internet of Things and Mobile Ad-Hoc networks

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computer systems science & Engineering 2022年第3期40卷 1199-1215页

作者： Vasaki Ponnusamy Mamoona Humayun NZJhanjhi Aun Yichiet Maram Fahhad Almufareh Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKamparMalaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufSaudi Arabia School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia

Internet of Things(IoT)devices work mainly in wireless mediums;requiring different Intrusion Detection System(IDS)kind of solutions to leverage 802.11 header information for intrusion ***-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired *** survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods,IDS techniques,IDS placement strategies,and traffic data analysis *** paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT specific ***,the Knowledge Discovery in Databases(KDD)Cup dataset is reviewed to highlight the design challenges of wireless intrusion detection based on current data attributes and proposed several guidelines to future-proof following traffic capture methods in the wireless network(WN).The paper starts with a review of various intrusion detection techniques,data collection methods and placement *** main goal of this paper is to study the design challenges of deploying intrusion detection system in a wireless *** detection system deployment in a wireless environment is not as straightforward as in the wired network environment due to the architectural *** this paper reviews the traditional wired intrusion detection deployment methods and discusses how these techniques could be adopted into the wireless environment and also highlights the design challenges in the wireless *** main wireless environments to look into would be Wireless Sensor networks(WSN),Mobile Ad Hoc networks(MANET)and IoT as this are the future trends and a lot of attacks have been targeted into these *** it is very crucial to design an IDS specifically to target on the wireless networks.

关键词： Internet of Things MANET intrusion detection systems wireless networks

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Recent Monte Carlo-Based Simulations for Modeling Disease Spread

Recent Monte Carlo-Based Simulations for Modeling Disease Sp...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Chakroun, Mohamad Haddad, Samir Shakir, Wafaa M.R. Sayah, Jinane Kallab, Chadi Falou, Salah Universität Rostock Rostock Germany University of Balamand Koura Lebanon Al-Furat Al-Awsat Technical University Department of Computer Systems Babil Iraq University of Balamand Telecom and Networks Department Koura Lebanon Lebanese American University Jbeil Lebanon Lebanese University Department of Computer Science Tripoli Lebanon

ISBN: (纸本)9798350367560

The COVID-19 outbreak demonstrated the significance of computer models in comprehending the complex dynamics of disease transmission. Epidemiological models have played a crucial role in understanding the complexities of COVID-19, developing effective strategies for its containment, and supporting theories regarding its transmission. The SIR (Susceptible-Infectious-Recovered) paradigm classifies people into 3 separate categories: risky, infectious, and healed. Agent-Based Models (ABM) are advanced frameworks to depict actions and relation-ships of people within a community including their various de-mographics and habits. The models have been utilized to analyze the impact of COVID-19 on specific locations, healthcare systems, and the efficacy of various treatments. However, they may face difficulties in specific situations because to the need for significant computing power and information for optimization. computer models have been useful in studying disease transmission and creating effective antiviral therapies. © 2024 IEEE.

关键词： COVID-19

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Future-Proofing Mobile networks: A Digital Twin Approach to Multi-Signal Management

arXiv

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arXiv 2024年

作者： Morabito, Roberto Pandey, Bivek Daubaris, Paulius Wanigarathna, Yasith R. Tarkoma, Sasu Department of Communication Systems EURECOM France Department of Computer Science University of Helsinki Finland

Digital Twins (DTs) are set to become a key enabling technology in future wireless networks, with their use in network management increasing significantly. We developed a DT framework that leverages the heterogeneity of network access technologies as a resource for enhanced network performance and management, enabling smart data handling in the physical network. Tested in a Campus Area Network environment, our framework integrates diverse data sources to provide real-time, holistic insights into network performance and environmental sensing. We also envision that traditional analytics will evolve to rely on emerging AI models, such as Generative AI (GenAI), while leveraging current analytics capabilities. This capacity can simplify analytics processes through advanced ML models, enabling descriptive, diagnostic, predictive, and prescriptive analytics in a unified fashion. Finally, we present specific research opportunities concerning interoperability aspects and envision aligning advancements in DT technology with evolved AI integration. Copyright © 2024, The Authors. All rights reserved.

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Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors

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computers, Materials & Continua 2022年第8期72卷 2521-2543页

作者： P.Arunachalam N.Janakiraman Junaid Rashid Jungeun Kim Sovan Samanta Usman Naseem Arun Kumar Sivaraman A.Balasundaram Department of Electronics and Communication Engineering K.L.N.College of EngineeringPottapalayam630612Tamil NaduIndia Department of Computer Science and Engineering Kongju National UniversityCheonan 31080Korea Department of Mathematics Tamralipta MahavidyalayaTamluk721636West Bengal School of Computer Science University of SydneyNSW 2006Australia School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India School of Computer Science and Engineering Centre for Cyber Physical SystemsVellore Institute of TechnologyChennai600127India

In this research work,we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma(SS)is the cell structure for *** this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet ***,the structure features(SFs)such as PrincipalComponentsAnalysis(PCA),Independent ComponentsAnalysis(ICA)and Linear Discriminant Analysis(LDA)were extracted from this subband image representation with the distribution of wavelet *** SFs are used as inputs of the Support Vector Machine(SVM)***,classification of PCA+SVM,ICA+SVM,and LDA+SVM with Radial Basis Function(RBF)kernel the efficiency of the process is differentiated and compared with the best classification ***,data collected on the internet from various histopathological centres via the Internet of Things(IoT)are stored and shared on blockchain technology across a wide range of image distribution across secure data IoT *** to this,the minimum and maximum values of the kernel parameter are adjusted and updated periodically for the purpose of industrial application in device ***,these resolutions are presented with an excellent example of a technique for training and testing the cancer cell structure prognosis methods in spindle shaped cell(SSC)histopathological imaging *** performance characteristics of cross-validation are evaluated with the help of the receiver operating characteristics(ROC)curve,and significant differences in classification performance between the techniques are *** combination of LDA+SVM technique has been proven to be essential for intelligent SS cancer detection in the future,and it offers excellent classification accuracy,sensitivity,specificity.

关键词： Principal components analysis independent components analysis linear discriminant analysis support vector machine blockchain technology IoT application industry application

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Efficient Dynamic Routing in Elastic Optical networks Based on Traffic Prediction and Bandwidth Reservation 23

Efficient Dynamic Routing in Elastic Optical Networks Based ...

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23rd International Conference on Transparent Optical networks, ICTON 2023

作者： Goścień, Róza Wroclaw University of Science and Technology Faculty of Information and Communication Technologies Department of Systems and Computer Network Wyb. Wyspianskiego 27 Wroclaw50-370 Poland

ISBN: (纸本)9798350303032

In this paper, we study the problem of efficient dynamic routing in elastic optical networks. We propose a novel resource allocation strategy that benefits from the bandwidth reservation in advance based on the analysis of the traffic prediction. We also propose a mechanism for the strategy's partial implementation to provide its high flexibility and the possibility to control both the efficiency and processing time. Next, we perform numerical experiments on representative European network topology. Their aim is the selection of the strategy's beneficial configuration as well as its performance evaluation. The results prove its high efficiency - the approach reduces the bandwidth blocking probability up to 0.85%, corresponding to 16.925 Tbps of more served traffic (compared to the allocation without traffic-aware bandwidth reservation). © 2023 IEEE.

关键词： Network topology

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ST-GNN-Powered Compression for Latency Reduction in Hybrid Satellite-Terrestrial networks 8

ST-GNN-Powered Compression for Latency Reduction in Hybrid S...

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8th International Conference on Information, Control, and communication Technologies, ICCT 2024

作者： Do, Phuc Hao Due Le, Tran Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint - Petersburg State University of Telecommunications Faculty of Infocommunication Networks and Systems Saint-Petersburg Russia University of Wisconsin-Stout Department of Mathematics Statistics & Computer Science MenomonieWI United States

ISBN: (纸本)9798331517564

Hybrid Satellite-Terrestrial communication networks (HSTCNs) have emerged as a critical infrastructure for modern communication, integrating the capabilities of satellite and terrestrial networks to meet the increasing demands for connectivity and reliability. However, enhancing data transmission efficiency in such heterogeneous networks remains challenging, particularly concerning latency. This research aims to address this challenge by proposing a lossless compression method leveraging custom Spatio-Temporal Graph Neural Network (ST-GNN) architectures to reduce data transmission latency in HSTCNs. The primary objectives of this study are twofold: first, to evaluate the compression rates achieved by different ST-GNN-based network traffic compression methods, and second, to conduct a comparative analysis of data transmission latency over HSTCNs based on the compression of traffic networks. By exploiting the inherent spatio-temporal characteristics of communication data, ST- GNNs offer a promising approach to compress network traffic while minimizing latency effectively. The empirical assessment demonstrates the effectiveness of the proposed ST-GNN-based compression methods in achieving competitive compression rates compared to existing techniques. Furthermore, the comparative analysis highlights the potential of ST-GNNs in improving data transmission efficiency and reducing latency in HSTCNs. © 2024 IEEE.

关键词： Satellite communication systems

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50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-EDFA

50-km Weakly-coupled Transmission with L-band 4-LP-mode FM-E...

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2024 Asia communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical communications, IPOC 2024

作者： Huang, Shuailuo Zhu, Baolong Qiao, Gang Gao, Yuyang Zuo, Mingqing Shen, Shikui Wang, Zelin He, Yongqi Chen, Zhangyuan Li, Juhao Chen, Zhangyuan Li, Juhao China Unicom Research Institute Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Fundamental Network Technology China Mobile Research Institute Beijing China Pengcheng National Laboratory Shenzhen China

ISBN: (纸本)9798350379266

关键词： Pulse amplitude modulation

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AI-Driven Intelligent IoT systems for Real-Time Food Quality Monitoring and Analysis 2

AI-Driven Intelligent IoT Systems for Real-Time Food Quality...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Krishnan, Prabhakar Ebenezar, U. Samson Ranitha, R. Purushotham, N. Balakrishnan, T. Suresh Amrita Vishwa Vidyapeetham Center for Cyber Security Systems and Networks Amritapuri campus India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India Mohan Babu University Department of Computer Science and Engineering Mr.palliAP India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350384277

The system will monitor and analyse food quality along the supply chain in real time. The system has high performance due to the CNN algorithms. In terms of accuracy, CNN has a high performance (95.2%), precision (92.8%), recall (94.5%) and F1 score (93.6 %). These features enable the model to predict food quality under good and poor conditions, thus demonstrating its effectiveness in assessing quality. The accuracy of real-time monitoring was evaluated across the supply chain to prove system reliability. Accuracy ratings for transport, storage and processing were 96.3%, 94.7% and 92.1%. These results show the robustness of this system within dynamic supply chain environments. Further testing evaluated environmental resilience capabilities. Under normal conditions, the accuracy of this system was 95.2%, while it reduced to 92.6% and rises again up to a level of 94.3%. The adaptability of the system under harsh conditions demonstrates that it can be applied to ensure food quality in various cases. This study reveals how proposed AI-based intelligent Internet of Things system may be used for real application using an appropriate dataset selected properly. This approach can help improve the quality assurance of food in an industry that is complex by uniting advanced algorithms with real-time data monitoring. © 2024 IEEE.

关键词： Artificial Intelligence Food Quality Analysis Intelligent IoT systems Real-Time Monitoring

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