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12th International Conference on information and Education technology, ICIET 2024

作者： Shiri, Farhad Mortezapour Perumal, Thinagaran Mustapha, Norwati Mohamed, Raihani Ahmadon, Mohd Anuaruddin Bin Yamaguchi, Shingo University Putra Malaysia Faculty Of Computer Science And Information Technology Malaysia Graduate School Of Sciences And Technology For Innovation Yamaguchi University Japan

ISBN: (纸本)9798350371772

Several factors related to the physical environment, including temperature, environmental noise, CO2 levels, air pressure, humidity, and the lecturer's vocal delivery, significantly impact student satisfaction. Evaluating, quantifying, and enhancing these factors can significantly contribute to enhancing students' satisfaction with lecture quality. The objective of this study is to assess students' satisfaction regarding the quality of lectures through an analysis of data obtained from a variety of smart devices that record physical environmental parameters. In this study, the machine learning techniques employed encompass Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), K-nearest neighbors (KNN), and Stochastic Gradient Descent (SGD). Additionally, the deep learning models utilized comprise Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Bidirectional Gated Recurrent Unit (Bi-GRU), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory (Bi-LSTM). The findings of this study suggest that, on the whole, deep learning models demonstrate superior performance when it comes to classifying data about this particular problem, as compared to traditional machine learning models. Notably, the CNN model emerges as the top performer among all the models assessed, achieving an impressive accuracy rate of 74.62%. it is worth mentioning that the decision tree exhibits the highest accuracy among classical machine learning models. © 2024 IEEE.

关键词： Long short-term memory

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Enhancing Wireless Sensor Network Data Collection through Aerial Unmanned Vehicles

Enhancing Wireless Sensor Network Data Collection through Ae...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Ali Alheeti, Khattab M. Najim, Ali Hamza Satar, Nurhizam Safie Mohd Aliesawi, Salah A. Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia College of Computer and Information Technology Department of Computer Networking Systems University of Anbar Anbar Iraq Faculty of Engineering Department of Electrical and Computer Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (纸本)9798350369106

This study addresses the critical aspect of data collection within Wireless Sensor Networks (WSNs), which consist of autonomous, compact sensor devices deployed to monitor environmental conditions. These networks have limited processing capacity, storage, short-range communication capabilities, and constrained battery power. A primary challenge in WSN s revolves around data gathering, particularly when employing static sinks, leading to premature energy depletion in nodes near these sinks. Integrating mobile collectors introduces the potential for energy conservation by shortening data routes. This article introduces three distinct algorithms for optimizing data collection in WSN s. Our approach involves an in-depth analysis of diverse strategies to mitigate packet collisions and facilitate the retransmission of lost packets. Our findings underscore the considerable impact that packet collisions can exert on the overall network performance during data gathering within wireless sensor networks. Through empirical exploration and analysis, we highlight the significance of these algorithms in enhancing the efficiency, energy conservation, and reliability of data collection processes within WSNs. This research sheds light on these algorithms' vital role in addressing the pressing challenges of data gathering and network performance optimization in wireless sensor networks. © 2024 IEEE.

关键词： Aircraft accidents

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A Survey on Energy-Aware Task Scheduling Approaches for Cyber-Physical Systems using Machine Learning

A Survey on Energy-Aware Task Scheduling Approaches for Cybe...

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2023 IEEE International Conference on Computing, ICOCO 2023

作者： Shobak, Mohamad Walid Ishak, Suhaimi Abd Ahmad Kamal, Hariz Syafiq Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Malaysia

ISBN: (纸本)9798350302684

This paper presents a survey of energy-aware task scheduling in Cyber-Physical Systems (CPSs) using Machine Learning approaches. It discusses the challenges of energy-aware scheduling in CPSs, outlining the important considerations when designing scheduling algorithms. It reviews the existing literature on energy-aware CPS scheduling and provides an overview of the proposed machine learning-based approaches. Additionally, it identifies promising research directions and provides insights into the use of machine learning for energy-aware CPS scheduling. © 2023 IEEE.

关键词： Cyber Physical System

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Binary Archimedes Optimization Algorithm for Computing Dominant Metric Dimension Problem

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Intelligent Automation & Soft Computing 2023年第10期38卷 19-34页

作者： Basma Mohamed Linda Mohaisen Mohammed Amin Mathematics and Computer Science Department Faculty of ScienceMenoufia UniversityShebin Elkom32511Egypt Faculty of Computer and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia

In this paper,we consider the NP-hard problem of finding the minimum dominant resolving set of graphs.A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B.A resolving set is dominating if every vertex of G that does not belong to B is a neighbor to some vertices in *** dominant metric dimension of G is the cardinality number of the minimum dominant resolving *** dominant metric dimension is computed by a binary version of the Archimedes optimization algorithm(BAOA).The objects of BAOA are binary encoded and used to represent which one of the vertices of the graph belongs to the dominant resolving *** feasibility is enforced by repairing objects such that an additional vertex generated from vertices of G is added to B and this repairing process is iterated until B becomes the dominant resolving *** is the first attempt to determine the dominant metric dimension problem *** proposed BAOA is compared to binary whale optimization(BWOA)and binary particle optimization(BPSO)*** results confirm the superiority of the BAOA for computing the dominant metric dimension.

关键词： Dominant metric dimension archimedes optimization algorithm binary optimization alternate snake graphs

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Optimizing the Tobacco Leaf Quality Assessment System via Grey Relational and Circle Ill-Condition Index Analysis 24

Optimizing the Tobacco Leaf Quality Assessment System via Gr...

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7th International Conference on information Management and Management science, IMMS 2024

作者： Cheng, Xijie Feng, Weiqing Pang, Su Hu, Gang Cai, Shimin College of Management Science Chengdu University of Technology China Faculty of Computer Science & Information Technology Universiti Malaya Malaysia Sichuan Tobacco Company Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China China

ISBN: (纸本)9798400716997

Traditional methods for assessing tobacco leaf quality rely heavily on experience and subjective judgment, resulting in inefficiency, and a lack of accuracy and reproducibility. To address these challenges, there is an urgent need for a tobacco leaf quality assessment system capable of assessing various aspects of leaf quality in a systematic and quantitative manner. In this paper, we quantitatively analyze the tobacco leaf quality assessment system for Sichuan tobacco, specifically focusing on the Yunyan 87 variety. In further, we employ Grey Relational Analysis and Circle Ill-Condition Index Analysis for indicator selection and optimization. Through quantitative analysis, key indicators that significantly impact the assessment results and exhibit low information redundancy are retained, and weights are reallocated based on correlation analysis. The optimized system retains four core indicators: Oil Content, Delicacy, Total Nicotine, and Sugar-to-Nicotine Ratio, significantly enhancing the scientific rigor and practical utility of the assessment process. This optimized assessment tool provides a scientific basis for quality control in Sichuan tobacco production, ultimately enhancing production efficiency and product quality. © 2024 ACM.

关键词： Quality control

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An Acceptance Model of Using Mobile-Government Services(AMGS)

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computer Modeling in Engineering & sciences 2022年第5期131卷 865-880页

作者： Ahmad Althunibat Mohammad Abdallah Mohammed Amin Almaiah Nour Alabwaini Thamer Ahmad Alrawashdeh Department of Software Engineering Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmmanJordan Faculty of Computer Sciences and Information Technology King Faisal UniversityAl-AhsaSaudi Arabia

In recent years,the telecommunications sector is no longer limited to traditional communications,but has become the backbone for the use of data,content and digital applications by individuals,governments and companies to ensure the continuation of economic and social activity in light of social distancing and total closure inmost countries in the ***,electronic government(e-Government)andmobile government(m-Government)are the results of technological evolution and ***,it is important to investigate the factors that influence the intention to use m-Government services among Jordan’s *** paper proposed a new m-Government acceptance model in Jordan(AMGS);this model combines the information System(IS)Success Factor Model and Hofstede Cultural Dimensions *** study was conducted by surveying different groups of the Jordanian *** questionnaire was used to collect data from203 *** regression analysis has been conducted to analyze the *** results indicate that the significant predictors of citizen intention to use m-Government services in Jordan are information Quality,Service Quality,Uncertainty Avoidance,and Indulgence ***,the results also suggest that Power Distance is not a significant predictor of citizen intention to use m-Government services.

关键词： Acceptance test e-Government m-Government acceptance model IS success factor model Hofstede cultural dimensions theory

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Modeling and Assessment of RSSI in LoRa WAN Network Using a Neural Network Approach 21

Modeling and Assessment of RSSI in LoRa WAN Network Using a ...

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21st IEEE International Symposium on Intelligent Systems and Informatics, SISY 2023

作者： Spisic, Josip Zrnic, Matko Zagar, Drago Crgic, Kresimir Computer Science and Information Technology Department of Communications Faculty of Electrical Engineering Osijek Croatia

ISBN: (纸本)9798350343366

This study employed a l0-fold cross-validation approach to train and validate neural networks to predict the RSSI (received signal strength indicator) in LoRaWAN communication. The model's performance was accurately estimated by averaging results across multiple validation sets and training sequences, and biased outcomes were mitigated. Implementing data normalization techniques, a simple neural network architecture, regularization approaches, and iteration limits ensured robustness within the limitations of a small dataset. The assessment of three neural network models using different optimization algorithms demonstrated their potential for accurate RSSI predictions, particularly for low-power IoT devices like LoRaWAN end devices, where energy efficiency is crucial. Lightweight neural networks on such devices enable efficient data processing while conserving energy, extending their lifespan, and reducing maintenance needs. Experimentation with deeper structures and unconventional activation functions may be necessary for complex problems, further enhancing performance in specific domains like RSSI assessment for LoRaWAN end devices. © 2023 IEEE.

关键词： Iterative methods

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Quantitative skill evaluation criterion for selecting programmers in custom software development companies 28th

Quantitative skill evaluation criterion for selecting progra...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Malachowski, Bartlomiej West Pomeranian University of Technology Faculty of Computer Science and Information Technology ul. Zolnierska 49 Szczecin70-210 Poland

In custom software development companies, efficient human resource allocation is crucial, given their reliance on multi-skilled software engineers for project-based work involving complex intellectual tasks. This paper addresses the challenge of selecting appropriate candidates for project teams by proposing a multi-criteria decision-making approach that integrates both hard and soft skills. The main focus is on defining quantitative selection criterion that accurately reflects the complexity of hard skills, their interdependence, and non-linear characteristics of estimated productivity. The criterion is obtained from a hierarchical skill model represented by a directed graph and learning curve models for productivity evaluation. This quantitative criterion, which integrates the assessment of all hard skills requirements for the project, can then be supplemented with additional qualitative or quantitative criteria expressing soft skills requirements. The proposed approach is illustrated with an example of selecting candidates for a Java web service developer position in a project with strictly defined requirements. © 2024 The Authors.

关键词： computer software selection and evaluation

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

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computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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