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Lightweight AI and Blockchain Optimization for Enhancing Consumer Electronics Decision-Making

IEEE Transactions on Consumer Electronics 2025年

作者： Byeon, Haewon Alsaadi, Mahmood Keshta, Ismail Ahanger, Tariq Ahamed Safarova, Nodira Aldawsari, Hamad Cascone, Lucia Shabaz, Mohammad Korea University of Technology and Education Convergence Department Cheonan Korea Republic of University of Al Maarif College of Sciences Department of Computer Sciences Al Anbar31001 Iraq AlMaarefa University College of Applied Sciences Computer Science and Information Systems Department Riyadh Saudi Arabia CoBA Prince Sattam Bin Abdulaziz University Department of Management Information Systems Saudi Arabia Tashkent State University of Economics Department of Finance and Financial technologies Tashkent Uzbekistan University of Tabuk Department of Computer Science Haql University College Saudi Arabia University of Salerno Dept. of Computer Science Fisciano Italy Model Institute of Engineering and Technology J and K Jammu India

Under the "dual carbon" background, consumerelectronics consumption has become deeply ingrained in people'sminds. However, consumers often distrust the sustainabilityclaims of consumer electronics products. Artificial intelligence(AI) and blockchain technology can address this trust deficitthrough transparency and traceability mechanisms. This studyintegrates blockchain technology into traditional consumerelectronics supply chains, considering consumers' preferences andtrust in these products. An AI-based game model is proposed toanalyze the interactions among supply chain members before andafter implementing blockchain technology, under varying EdgeComputing-based power structures. This model quantitativelyevaluates emission reduction and pricing strategies, aiming tooptimize consumer surplus and total social welfare. By leveragingLightweight AI and blockchain, smart wholesale and cost-sharingcontracts are designed to establish reasonable ranges for wholesaleprices and optimal cost-sharing ratios, enhancing enterpriseoperational efficiency and achieving supply chain *** demonstrate that when consumers exhibit a strongerpreference for consumer electronics products, the adoption ofLightweight AI and blockchain delivers greater benefits across thesupply chain. Furthermore, as consumer willingness to purchasethese products increases, the advantages become morepronounced. Numerical analysis highlights that smart contractscan better coordinate the supply chain, particularly in retailer-dominated scenarios. Finally, empirical cases validate theeffectiveness of the proposed strategies and models. © 1975-2011 IEEE.

关键词： Supply chain management

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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Electronic engineering (ICEEM), International Conference on

作者： Mahmoud Elshabrawy Marwa M. Eid Abdelaziz A. Abdelhamid El-Sayed M. El-Kenawy Abdelhameed Ibrahim Dept. of Communications & Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Dep. of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Engineering and Control Systems Dept. Faculty of Engineering University Mansoura Egypt

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models.

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A Comprehensive Survey of Text Classification Techniques and Their Research Applications: Observational and Experimental Insights

arXiv

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arXiv 2024年

作者： Taha, Kamal Yoo, Paul D. Yeun, Chan Homouz, Dirar Taha, Aya Department of Computer Science Khalifa University United Arab Emirates Department of Computer Science & Information Systems University of London Birkbeck College United Kingdom Center for Cyber-Physical Systems Dept. of Electrical Engineering and Computer Science Khalifa University United Arab Emirates Department of Physics Khalifa University United Arab Emirates Brighton College Dubai United Arab Emirates

The exponential growth of textual data presents substantial challenges in management and analysis, notably due to high storage and processing costs. Text classification, a vital aspect of text mining, provides robust solutions by enabling efficient categorization and organization of text data. These techniques allow individuals, researchers, and businesses to derive meaningful patterns and insights from large volumes of text. This survey paper introduces a comprehensive taxonomy specifically designed for text classification based on research fields. The taxonomy is structured into hierarchical levels: research field-based category, research field-based sub-category, methodology-based technique, methodology sub-technique, and research field applications. We employ a dual evaluation approach: empirical and experimental. Empirically, we assess text classification techniques across four critical criteria. Experimentally, we compare and rank the methodology sub-techniques within the same methodology technique and within the same overall research field sub-category. This structured taxonomy, coupled with thorough evaluations, provides a detailed and nuanced understanding of text classification algorithms and their applications, empowering researchers to make informed decisions based on precise, field-specific insights. © 2024, CC BY-NC-SA.

关键词： Deep learning

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Investigating Online Searching Behavior Based on Google Trends in MENA Region Before and After COVID-19

Investigating Online Searching Behavior Based on Google Tren...

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Frontiers in Education (FIE) Conference

作者： Abdelkader Nasreddine Belkacem Nuraini Jamil Saed Alrabaee Dept. of Computer and Network Engineering College of IT UAE University Al Ain United Arab Emirates Dept. of Computer Science and Software Engineering College of IT UAE University Al Ain United Arab Emirates Dept. of Information Systems and Security College of IT UAE University Al Ain United Arab Emirates

The outbreak of the coronavirus disease (COVID-19) has had a profound impact on education worldwide. The rise of remote learning is one of the most significant changes in this regard, as many schools and universities were forced to close down by regional health authorities. This has also caused people to become more conservative in trade-offs between healthcare and education. Google Trends is the most common tool for analyzing online search behaviors. It is a free resource that provides information on the trends and changes in users' online interests over time based on certain terms and subjects. The online search queries on Google can be used to assess users' behaviors concerning online learning to forecast their choices regarding online education. This paper examines the frequency of users' web searches for online communication tools, courses, and learning terms. We statistically compared users in the Middle East and North Africa regions by using the volumes of searches recorded on Google Trends from January 2016 to August 2022. Moreover, we used machine learning techniques to identify differences among the keywords used. The findings statistically show that COVID-19 has led to an increase in the extent of students' attention to and interest in online learning.

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Blockchain Integration for Robust Intellectual Property Protection in New Product Development (NPD)

Blockchain Integration for Robust Intellectual Property Prot...

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Electronics and Renewable systems.(ICEARS), International Conference on

作者： P. Chinnasamy Subashini. B Nijanthan Nijanthan Madasamy Raja. G Devulapally Swetha Sreenivasulu Reddy L Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamilnadu India Department of Data Science and Business Systems School of Computing SRMIST India Computer Science and Engineering Paavai Engineering College Namakkal Tamilnadu India Information Technology Paavai Engineering College Namakkal Tamilnadu India Dept. of Computer Science and Engineering Vaagdevi Engineering College Telangana India Department of Mathematics School of Advanced Sciences Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms.

关键词： Patents Technological innovation Costs Smart contracts Intellectual property Product development Blockchains Security Protection Resilience

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Ontology-Based Method for Semantic Association Rules

Ontology-Based Method for Semantic Association Rules

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IEEE India Conference (INDICON)

作者： Abhilash C B Kavi Mahesh Dept. of Computer Science and Engineering Indian Institute of Information Technology Dharwad Dharwad India Dept. of Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Dharwad India

ISBN: (纸本)9781665452724

Finding interesting association rules is a popular and current topic in data mining. The Apriori family of algorithms is built around two rule extraction measures: support and confidence. Even though these two measures are easy to compute, they yield many rules, the majority of which are redundant and may not be of interest to the user. Also, by themselves, support and confidence do not generate strong rules. Additional measures are required to mine interesting facts from data. Ontologies have become the fundamental building blocks for structuring and formalizing data. With the semantic structuring of information, the implicit relationship between data elements makes the analyst get important facts from the data. Our study proposes a novel framework for interestingness in data by combining domain ontology with semantic interestingness measures. The ontology-based method infers rules that are semantically enriched and strong. We analyze the quality of the rule considering the factors defined by the domain experts. It is observed that our methodology generates semantically enriched rules that are more acceptable to domain experts.

关键词： COVID-19 Current measurement Semantics Knowledge based systems Influenza Ontologies Resource description framework

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Pulling Figure of Dielectric Resonator for 3D Filament Defectoscopy

Pulling Figure of Dielectric Resonator for 3D Filament Defec...

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International Scientific Symposium on Metrology and Metrology Assurance (MMA)

作者： Maryna Miroshnyk Olga Zaichenko Anatolii Miroshnyk Nataliia Hapon Yurii Pakhomov Liubov Klymenko dept. of Theoretical and Applied System Engineering V. N. Karazin Kharkiv National University Kharkov Ukraine dept. of Design and Operation of Electronic Devices Kharkiv National University of Radioelectronics Kharkiv Ukraine dept. of Design Automation Kharkiv National University of Radioelectronics) Kharkiv Ukraine dept. of Computer Science and Information Technologies O.M. Beketov National University of Urban Economy in Kharkiv Kharkiv Ukraine dept. of Specialized Computer Systems Ukrainian State University of Railway Transport Kharkiv Ukraine

ISBN: (数字)9798350352832

ISBN: (纸本)9798350352849

The research aim is to derive connection between the parameters of dielectric resonators frequency shift and the warp defect of 3D printing filament. Object of investigation are the processes of interaction of electromagnetic wave of a dielectric resonator with filament for 3D printing. The proposed model describes the connection between the frequency shift and defect warp of filament frequency pulling depending on the load.

关键词： Electromagnetic scattering Resonant frequency Estimation Metrology Three-dimensional printing Resonance Dielectrics Frequency measurement Resonators Load modeling

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Algorithmic Support for Building a Distributed IoT System in a Cloud Service

Algorithmic Support for Building a Distributed IoT System in...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Mykola Zamkovyi Svitlana Gavrylenko Kyrylo Khatsko Nataliia Khatsko dept. Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

The Internet of Things (IoT) today already connects billions of different IoT devices with the Internet. With the advent of new services and services, new challenges arise: how to make a cloud service publicly available, and reliable, how and where to store data. The article considers an example of the implementation of an IoT application with cloud components, considers the implementation of connecting IoT components to a cloud provider, and presents the IoT architecture. The focus is on the architecture and implementation of data exchange protocols, the implementation of protocols? for data collection and management of remote system components Given the large amount of data transmitted by IoT devices to the cloud, data compression and interaction with cloud services is a very relevant topic. Therefore, the article also offers recommendations for managing the traffic of IoT devices. The purpose of this article is to provide a description and algorithm for connecting IoT devices to the cloud, to bring together disparate information, and make it open and understandable to beginners and academic researchers.

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Physical and System Level Power Reduction Technique for NoC Architectures: Overview of State of the Art

Physical and System Level Power Reduction Technique for NoC ...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Djalila Belkebir Abdelhai Lati Malak Belkebir Faculty of New Information and Communication technologies Kasdi Merbah Ouargla University (UKMO) Ouargla Algeria Dept. Mathematics and Computer Science Research Laboratory on Computer Science's Complex Systems University of Oum El Bouaghi Oum El Bouaghi Algeria

Power dissipation and energy consumption are key factors for the performance improvement of modern technology systems. In recent years, several strategies have been proposed to solve the power management issues on embedded systems. In this paper, we classify the state of the art of those techniques. Classification is done based on run-time, activation, and idle state of the different components of the network on chip (NoC). We illustrate the requirement of power management based on several important parameters. A highlight is put on the drawbacks and benefits. Also, classification is done based on different NoC abstraction levels. However, by this paper, we intend to guide the researchers and application developers in getting insights about the strategies of power management techniques that will lead to the design of more efficient high performances in embedded systems.of the future.

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Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection

arXiv

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arXiv 2023年

作者： Chochlov, Muslim Ahmed, Gul Aftab Patten, James Vincent Lu, Guoxian Hou, Wei Gregg, David Buckley, Jim Dept. of Computer Science and Information Systems University of Limerick Limerick Ireland Dept. of Computer Science Trinity College Dublin Dublin Ireland WN Digital IPD and Trustworthiness Enabling Huawei Technologies Co. Ltd. Shanghai China Huawei Vulnerability Management Center Huawei Technologies Co. Ltd Guangdong Shenzhen China

Code clones can detrimentally impact software maintenance and manually detecting them in very large codebases is impractical. Additionally, automated approaches find detection of Type 3 and Type 4 (inexact) clones very challenging. While the most recent artificial deep neural networks (for example BERT-based artificial neural networks) seem to be highly effective in detecting such clones, their pairwise comparison of every code pair in the target system(s) is inefficient and scales poorly on large codebases. We therefore introduce SSCD, a BERT-based clone detection approach that targets high recall of Type 3 and Type 4 clones at scale (in line with our industrial partner’s requirements). It does so by computing a representative embedding for each code fragment and finding similar fragments using a nearest neighbour search. SSCD thus avoids the pairwise-comparison bottleneck of other Neural Network approaches while also using parallel, GPU-accelerated search to tackle scalability. This paper details the approach and an empirical assessment towards configuring and evaluating that approach in industrial setting. The configuration analysis suggests that shorter input lengths and text-only based neural network models demonstrate better efficiency in SSCD, while only slightly decreasing effectiveness. The evaluation results suggest that SSCD is more effective than state-of-the-art approaches like SAGA and SourcererCC. It is also highly efficient: in its optimal setting, SSCD effectively locates clones in the entire 320 million LOC BigCloneBench (a standard clone detection benchmark) in just under three hours. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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