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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： Kang, Changhoon Woo, Jongsoo Hong, James Won-Ki Department of Computer Science and Engineering POSTECH Korea Republic of Graduate School of Information Technology POSTECH Korea Republic of

ISBN: (纸本)9788995004395

Bitcoin transactions are created through the concept called Unspent Transaction Output (UTXO). Users put their own UTXOs as inputs into a transaction for Bitcoin transfer and create multiple outputs, each specifying the recipient’s wallet address and the amount to be sent. UTXO refers to an output that has not been used as an input for any transaction yet and each UTXO can only be used as an input once. However, attempting to use a UTXO more than once is called a double-spending attack. Although double-spending in Bitcoin is ultimately impossible due to the system structure, it can occur when a transaction is deemed confirmed and off-chain goods or services are provided before sufficient transaction finality is guaranteed. We consider an attempt of double-spending attack when a UTXO used as an input in a transaction for payment exists together with another transaction on the Bitcoin network that uses the same UTXO as an input. In previous research, we randomly deployed observer nodes on the Bitcoin network and proposed a method to detect double-spending attacks using transaction data in the memory pool and a graph neural network model. In this paper, we analyze the impact of adding observer nodes to the Bitcoin network on the performance of graph neural network-based Bitcoin double-spending attack detection. We conducted experiments to examine the performance differences among three strategies for adding observer nodes. However, it was difficult to compare clear differences due to the performance degradation of the model caused by the differences in graph structure between datasets. Therefore, we provide an analysis of the causes and suggestions for improvement. Copyright 2023 KICS.

关键词： Graph neural networks

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Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

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computers, Materials & Continua 2024年第8期80卷 2005-2030页

作者： Tareq Hamadneh Khalid Kaabneh Omar Alssayed Gulnara Bektemyssova Galymzhan Shaikemelev Dauren Umutkulov Zoubida Benmamoun Zeinab Monrazeri Mohammad Dehghani Department of Mathematics Al Zaytoonah University of JordanAmman11733Jordan Faculty of Information Technology Al-Ahliyya Amman UniversityAmman19328Jordan Department of Mathematics Faculty of ScienceThe Hashemite UniversityP.O.Box 330127Zarqa13133Jordan Department of Computer Engineering International Information Technology UniversityAlmaty050000Kazakhstan Faculty of Engineering Liwa CollegeAbu Dhabi41009United Arab Emirates Department of Electrical and Electronics Engineering Shiraz University of TechnologyShiraz***Iran

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and *** address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making *** this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in *** theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy *** tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) *** function served as input for the SOA ***,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and *** extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the *** study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain *** simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

关键词： Optimization supply chain management sustainable lot size optimization bio-inspired metaheuristic stork

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Agent Selection Framework for Federated Learning in Resource-Constrained Wireless Networks

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 1265-1282页

作者： Raftopoulou, Maria Da Silva, Jose Mairton B. Litjens, Remco Vincent Poor, H. Van Mieghem, Piet Uppsala University Department of Information Technology Uppsala751 05 Sweden Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands Department of Networks The Hague2595 DA Netherlands Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

Federated learning is an effective method to train a machine learning model without requiring to aggregate the potentially sensitive data of agents in a central server. However, the limited communication bandwidth, the hardware of the agents and a potential application-specific latency requirement impact how many and which agents can participate in the learning process at each communication round. In this paper, we propose a selection metric characterizing each agent's importance with respect to both the learning process and the resource efficiency of its wireless communication channel. Leveraging this importance metric, we formulate a general agent selection optimization problem, which can be adapted to different environments with latency or resource-oriented constraints. Considering an example wireless environment with latency constraints, the agent selection problem reduces to the 0/1 Knapsack problem, which we solve with a fully polynomial approximation. We then evaluate the agent selection policy in different scenarios, using extensive simulations for an example task of object classification of European traffic signs. The results indicate that agent selection policies which consider both learning and channel aspects provide benefits in terms of the attainable global model accuracy and/or the time needed to achieve a targeted accuracy level. However, in scenarios where agents have a limited number of data samples or where the latency requirement is very stringent, a pure learning-based agent selection policy is shown to be more beneficial during the early or late stages of the learning process. © 2023 CCBY.

关键词： Federated learning

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Carbon Neutrality Approaches for IoT-Enabled Applications 3

Carbon Neutrality Approaches for IoT-Enabled Applications

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3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Benedict, Shajulin Indian Institute of Information Technology Kottayam Department of Computer Science and Engineering Kerala Kottayam District686635 India

ISBN: (纸本)9781665462167

Unlike others, IoT-enabled technology has expanded its base in various sectors, including finance, healthcare, agriculture, energy, and so forth. Tens of thousands of applications and products have evolved in recent years, leading to a constant threat to global climate sustainability due to the underlying carbon emissions. Researchers have developed standalone methods/approaches that aimed to tackle carbon emission problems. However, an article that expresses a list of carbon-neutral solutions and their associated technological challenges is not available. This article explores the carbon emission problems of IoT-enabled applications;and, it categorizes the carbon neutrality methods. The exploratory analysis of different carbon-neutral approaches, presented in this article, can present novel ideas and answers to questions that hover over any carbon-conscious IoT-enabled application developers. © 2023 IEEE.

关键词： Internet of things

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Performance Enhancement of Adaptive Neural Networks Based on Learning Rate

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computers, Materials & Continua 2023年第1期74卷 2005-2019页

作者： Swaleha Zubair Anjani Kumar Singha Nitish Pathak Neelam Sharma Shabana Urooj Samia Rabeh Larguech Department of Computer Science Aligarh Muslim UniversityAligarh202002Uttar PradeshIndia Department of Information Technology Bhagwan Parshuram Institute of Technology(BPIT)GGSIPUNew Delhi110089India Department of Computer Science and Engineering Maharaja Agrasen Institute of Technology(MAIT)GGSIPUNew DelhiIndia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Deep learning is the process of determining parameters that reduce the cost function derived from the *** optimization in neural networks at the time is known as the optimal *** solve optimization,it initialize the parameters during the optimization *** should be no variation in the cost function parameters at the global *** momentum technique is a parameters optimization approach;however,it has difficulties stopping the parameter when the cost function value fulfills the global minimum(non-stop problem).Moreover,existing approaches use techniques;the learning rate is reduced during the iteration *** techniques are monotonically reducing at a steady rate over time;our goal is to make the learning rate *** present a method for determining the best parameters that adjust the learning rate in response to the cost function *** a result,after the cost function has been optimized,the process of the rate Schedule is *** approach is shown to ensure convergence to the optimal *** indicates that our strategy minimizes the cost function(or effective learning).The momentum approach is used in the proposed *** solve the Momentum approach non-stop problem,we use the cost function of the parameter in our proposed *** a result,this learning technique reduces the quantity of the parameter due to the impact of the cost function *** verify that the learning works to test the strategy,we employed proof of convergence and empirical tests using current methods and the results are obtained using Python.

关键词： Deep learning optimization convergence stochastic gradient methods

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AI-Enhanced Assistive Tools with Hand Skeleton Analysis in Online Arts Education 6

AI-Enhanced Assistive Tools with Hand Skeleton Analysis in O...

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6th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Kao, Chiao-Wen Wu, Wen-Hsuan Huang, Chi-Sheng Ming Chuan University Department of Applied Artificial Intelligence Taipei Taiwan National Taichung University of Science and Technology Department of Computer Science and Information Engineering Taichung Taiwan

ISBN: (纸本)9798350396133

The global COVID-19 pandemic has significantly impacted education worldwide, leading to a transition from traditional in-person teaching to asynchronous online learning. Thanks to the valuable contributions of numerous high-quality educational content creators, online audiovisual materials have opened up boundless opportunities for cross-border, crossdisciplinary online learning. This removes geographical and temporal barriers and broadens the spectrum of learning resources available to individuals with diverse needs. Particularly for individuals with disabilities, mobility impairments, or social anxiety, online learning offers an inclusive and accessible environment, fostering the democratization and equity of education and ensuring highquality education regardless of physical conditions or locations. However, unlike foundational subjects, the learning process for arts heavily relies on live demonstrations by teachers and imitation by students, presenting a challenge in the online learning setting especially true for beginners as learning arts often necessitates personalized guidance and real-time feedback. To address this challenge, Mediapipe technology was used to capture the hand movements of both teachers and students in this study. Aeep learning model was used to analyze the similarity of pen-holding postures between students and teachers, thereby providing real-time feedback to supplement the lack of interactivity in online drawing learning and enhance learning outcomes. The developed learning method simulates the role of teachers in traditional classrooms and widens the scope of arts education, providing AI-powered tools for those interested in cultivating aesthetics and lifelong learning opportunities. For the care of the elderly, in addition to enhancing emotional and psychological well-being through aesthetics, the method can be utilized for rehabilitation or the assessment of degenerative conditions. © 2024 IEEE.

关键词： Students

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Modified EfficientNetB3 Deep Learning Model to Classify Colour Fundus Images of Eye Diseases 5

Modified EfficientNetB3 Deep Learning Model to Classify Colo...

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5th IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2023

作者： Sharma, Riya Gangrade, Jayesh Gangrade, Shweta Mishra, Ashish Kumar, Gautam Kumar Gunjan, Vinit Manipal University Jaipur Dept of Computer Science & Engineering Jaipur India Learning Manipal University Jaipur Dept. of Artificial Intelligence & Machine Jaipur India Manipal University Jaipur Dept of Information Technology Jaipur India Jaypee Institute of Information Technology Dept of Computer Science & Engineering Noida India CMR Institute of Technology Department of Computer Science & Engineering Hyderabad India

ISBN: (纸本)9798350338287

The only way to prevent blindness from eye problems is by early detection and prompt treatment. Although colour fundus photography (CFP) is useful for fundus inspection, there is a need for computer-assisted automated diagnosis tools due to the similarities between the early symptoms of many eye disorders. The suggested approach uses cutting-edge deep learning model to categorize images into several disease categories by learning distinguishing features from the input images. The high-resolution fundus photos from individuals with diabetic retinopathy (DR), glaucoma, cataract, and healthy eyes make up most of the dataset used for this research. The experimental findings show that the suggested system achieve 97% accuracy with modified efficientNetB3 model and surpasses current approaches for categorizing eye diseases. This approach may help doctors diagnose and treat eye conditions earlier, leading to better patient outcomes. © 2023 IEEE.

关键词： Color

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Remote Heart Rate Estimation Based on ROI Extraction 16

Remote Heart Rate Estimation Based on ROI Extraction

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16th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Jian, Wei Zhang, Yuqi Hu, Ke Fudan University Center for Biomedical Engineering School of Information Science and Technology Shanghai China Fudan University School of Computer Science Shanghai China Fudan University School of Information Science and Technology Shanghai China

ISBN: (纸本)9798350330755

Remote photoplethysmography (rPPG) has acquired much attention in health monitoring and emotion detection in recent years due to its convenience by non-contact approaches. Most studies have primarily concentrated on the estimation of pulse signals methods from the region of interest (ROI). Due to the unequal distribution of rPPG signals on the facial parts, accurate extraction of the ROI is a critical process for acquiring dependable pulse signals. However, many of those methods for ROI extraction encounter challenges, such as background pixels and non-critical skin pixels existing in the ROI. This paper proposes an effective framework integrating face detection and segmentation to address the remote heart rate estimation in presence of the ROI extraction issues. The experimental results demonstrate the proposed framework can efficiently extract skin pixels carrying high-quality heart rate information. As a result, it achieves a significant improvement in the performance of heart rate estimation. © 2023 IEEE.

关键词： Face recognition

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Analyzing Sentiments of Global Workforce Towards Hybrid Work Culture in the New Normal 4th

Analyzing Sentiments of Global Workforce Towards Hybrid Wor...

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4th International Conference on Smart Systems: Innovations in Computing, SSIC 2023

作者： Vaghela, Hardika Jadeja, Mahipal K.S. School of Business Management and Information Technology Ahmedabad India Department of Computer Science and Engineering Malaviya National Institute of Technology Jaipur Jaipur India

ISBN: (纸本)9789819736898

The Covid-19 pandemic has substantially influenced human existence, impacting not just our social and economic aspects but also our professional lives. This effect is readily evident on social media platforms. Amidst the exchange of information and discussions concerning the Covid-19 pandemic, one can discern a growing wave of support for a hybrid work culture when closely examining social media activities. With this perspective in mind, we conducted an analysis of approximately 16,000 tweets to gauge public sentiment regarding the hybrid work culture. We chose Twitter as our platform for this study because it offers a wealth of data that can be effectively leveraged to gain a comprehensive insight into people’s sentiments. We have considered tweets containing the following keywords (hashtags): WFH, WorkFromHome, Remotework, and Hybridwork. By analyzing the Twitter dataset, we extract insights and ascertain the ratio of negative tweets to positive (or supportive) tweets concerning the hybrid work culture. Graphical visualizations of the polarity of the tweets support the study. We conclude that a significant percentage (around 50%) of people support hybrid work culture and show positive sentiments via tweets, whereas 30% and 20% of tweets are neutral and negative, respectively. This research aids in gaining insight into how public opinions align with the shifts in the "new normal." This study can greatly assist strategic decision-makers in planning for future organizational decisions. We combined the interpretation of the results with Wordmap (using WordCloud library of Python) in order to add more sense to the results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Tweets

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Success Factors of Enterprise Resource Planning: A State-of-the-Art Mini Review

Success Factors of Enterprise Resource Planning: A State-of-...

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2024 International Conference on Artificial Intelligence, Metaverse and Cybersecurity, ICAMAC 2024

作者： BaniMustafa, Ahmed Bulkrock, Olla Faculty of Computer Information Science Higher Colleges of Technology Abu Dhabi United Arab Emirates Software Engineering Department Princess Sumaya University for Technology Amman Jordan

ISBN: (纸本)9798350353488

Enterprise Resource Planning Systems (ERP) are vital for today’s businesses. However, the successful implementation of ERP systems faces several challenges, which can determine its success or failure. This paper provides a brief state-of-the-art review of the success factors of ERP implementation using various applications that span different contexts. The paper discusses and compares the aims defined and the techniques applied in these studies, as well as the data used and the results obtained from each of these studies. This review paper reviews published work to tackle these challenges, covering the literature published in 2020-2023. A special effort was also made to focus on high-quality papers published in top journals with high-impact factors and indexed in Scopus and Web of science. The review process is repeatable, as special keywords were used to search the literature using publishers’ databases and three specialized tools. The paper concludes by discussing the future of the successful implementation of ERP systems. The paper argues that ERP systems will continue to have a major impact on the success of today’s businesses. Therefore, they must carefully consider various factors that influence their successful implementation. © 2024 IEEE.

关键词： information use

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