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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Tsai, Shang-Te Chang, Yu-Cheng Huang, Chao-Yi Yang, Fang-Yuan Chien, Wei Wu, Zong-Rong School Art and Design Sanming University Fujian China National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan National Yunlin University of Science and Technology Department of Information Management Yunlin Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan National Yunlin University of Science and Technology Department of Technical and Vocational Program in Artificial Intelligence Yunlin Taiwan

ISBN: (纸本)9798350360721

Innovative safety in the workplace is vital as the high safety risks associated with electrical engineering construction can lead to injuries or even fatalities. Using computer vision technology, we experimented with scenarios such as 'normal operations' and 'unexpected incidents' to enhance safety measures. We integrated an Internet of Things system into the setup, enabling the system to quickly detect and alert to unexpected events in real-time, thereby improving workplace safety. © 2024 IEEE.

关键词： computer vision

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Optimizing Advanced Neural Network Architectures to Enhance the Accuracy of Extracting Online information 2

Optimizing Advanced Neural Network Architectures to Enhance ...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Mukuntharaj, C. Vijayaraj, T. Mehta, Pradnya S. Kulhar, Kuldeep Singh Agrawal, Trapty Kavitha, R. Karpagam College of Engineering Department of Electronics and Communication Engineering Coimbatore641032 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Civil Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Information Technology Karnataka Bangalore India

ISBN: (纸本)9798350308846

The extraction of records from online assets has become increasingly important for organizations to remain competitive. This requires using state-of-the-art records analytics gear, including deep getting based totally models, to better extract meaningful statistics from web resources. One of the demanding situations is to broaden extra superior neural community architectures, which can increase the records extraction accuracy. This paper explores the capacity of such architectures for enhancing the accuracy of statistics extraction from online resources. It critiques advances in deep studying fashions, encompassing CNNs, RNN and generative hostile networks. It describes how those methods may be implemented to optimize the accuracy of fact extraction from online sources. The paper additionally evaluates case studies to illustrate how these fashions can be used to beautify the accuracy of extracting online records. Sooner or later, it provides suggestions on how companies can optimize their online form extraction strategies to enhance accuracy. © 2023 IEEE.

关键词： Accuracy Enhance Evaluates Extraction Strategies

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Exploring the Behavior of Soft-Error Rate Reduction Algorithms in Digital Circuits

Exploring the Behavior of Soft-Error Rate Reduction Algorith...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Menaka, C. Saraswat, Nidhi Bhagwan, Shri Department of Computer Science and Information Technology Bangalore India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India College of Engineering Teerthanker Mahaveer University Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

Smooth mistakes in virtual circuits, which talk over with inadvertent modifications to saved bits or transmitted records because of temporary faults caused by external radiation, continue to be a trouble that ought to be tackled for the green functioning of virtual circuits. This technical abstract offers an overview of a research paper that examines the effectiveness of diverse gentle-blunders fee reduction algorithms in digital circuits. The research paper starts by introducing three techniques for mitigating tender error costs in virtual circuits: duplication, scrubbing, and blunders-correction codes. The paper then provides an evaluation of the behavior of several present smooth-mistakes charge reduction algorithms, including the Triple-creation Code, the DSP Compressor Code, the DFT feet Fault Codes, and the Alpha Detector-based Code. Through simulations and modeling, the paper evaluates the efficiency of those algorithms and compares their performances in opposition to each other and in opposition to baseline values. The paper reports that the Triple-creation Code, DSP Compressor Codes, and Alpha Detector-based total Code are able to present a powerful softerror charge reduction of up to 4 instances of the baseline values in digital circuits. There was also determined to be a sizable development in the robustness of virtual circuits when such algorithms are carried out. © 2024 IEEE.

关键词： Algorithms Circuits Compressor Functioning Scrubbing Smooth

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Effective short text classification via the fusion of hybrid features for IoT social data

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Digital Communications and Networks 2022年第6期8卷 942-954页

作者： Xiong Luo Zhijian Yu Zhigang Zhao Wenbing Zhao Jenq-Haur Wang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFoshan528399China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Department of Electrical Engineering and Computer Science Cleveland State UniversityClevelandOH44115USA Department of Computer Science and Information Engineering National Taipei University of TechnologyTaipei10608China

Nowadays short texts can be widely found in various social data in relation to the 5G-enabled Internet of Things (IoT). Short text classification is a challenging task due to its sparsity and the lack of context. Previous studies mainly tackle these problems by enhancing the semantic information or the statistical information individually. However, the improvement achieved by a single type of information is limited, while fusing various information may help to improve the classification accuracy more effectively. To fuse various information for short text classification, this article proposes a feature fusion method that integrates the statistical feature and the comprehensive semantic feature together by using the weighting mechanism and deep learning models. In the proposed method, we apply Bidirectional Encoder Representations from Transformers (BERT) to generate word vectors on the sentence level automatically, and then obtain the statistical feature, the local semantic feature and the overall semantic feature using Term Frequency-Inverse Document Frequency (TF-IDF) weighting approach, Convolutional Neural Network (CNN) and Bidirectional Gate Recurrent Unit (BiGRU). Then, the fusion feature is accordingly obtained for classification. Experiments are conducted on five popular short text classification datasets and a 5G-enabled IoT social dataset and the results show that our proposed method effectively improves the classification performance.

关键词： information fusion Short text classi fication BERT Bidirectional encoder representations fr 0om transformers Deep learning Social data

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Fuzzy Optics Enabled Antenna Model for Push-To-Talk Communication in Underwater Networks

Fuzzy Optics Enabled Antenna Model for Push-To-Talk Communic...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Pandey, Prakash Mahajan, Prerna Raizada, Aasheesh College of Engineering Teetthanker Mahaveer University Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350383348

This paper explores a unique antenna model to allow push-totalk underwater communications. This antenna version uses fuzzy logic to adaptively control the transmission and reception parameters of the antenna. The russification of the antenna parameters reduces the complexity of antenna control, permitting even low-give-up underwater gadgets to transmit and acquire alerts successfully. This version uses binary water droplet-like antenna systems, which are adaptively tuned in response to various sign energy levels. The binary antenna structure can attain enormous gains with minimal cease-consumer setup time and value. Moreover, this antenna model allows for a quick reconfiguration to suit converting water conditions and tool features, allowing the antenna to keep top-quality overall performance for underwater conversation. Our assessment of this version in actual-global situations shows that push-to-communicate communique is feasible with reasonable hyperlink reliability. © 2024 IEEE.

关键词： attaining cease-consumer communications reconfiguration underwater

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Learning-Based Collaborative Service Placement for AI-oriented Mobile Edge Computing 11

Learning-Based Collaborative Service Placement for AI-orient...

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11th International Conference on Advanced Cloud and Big Data, CBD 2023

作者： Li, Wei Li, Miao Liu, Yuezhao Liu, Jiong Cui, Lanlan Nanchang University School of Information Engineering Nanchang China National University of Defense Technology School of Information and Communication Wuhan China Xi'An University of Technology School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350345346

Next generation mobile communication technology (6G) intelligent endogenous network deeply integrates network connectivity with artificial intelligence (AI) elements. It is urgent to push AI services to the edge of the network. How to deploy computing intensive AI models in edge devices with limited resources, and consider the collaborative training and inference between edge-edge or edge-cloud is a challenge. The partition of complex edge AI models into small subtasks and the collaborative executions among the edge nodes can efficiently solve this problem. Therefore, in this paper, exploiting the dispersive resource across edge nodes and devices, we propose a collaborative service placement strategy efficiently deploying all the sub-services among edge nodes and considering the service migration due to the user's mobility. Moreover, we will explore the trade-offs between different metrics, i.e., accuracy, latency and migration cost, helping to improve the efficiency of deploying AI application at edge. To overcome the unknown system dynamics, we formulate the problem as a combinatorial contextual Multi-armed Bandit (MAB) problem. Then based on MAB theory and greedy method, we give a online learning algorithm to cope with the system dynamics. Theoretical analysis and evaluations demonstrate the proposed algorithm can effectively learn and adapt to the dynamic network environment and user demands, reduce the latency and migration cost while satisfying the minimal service requirement. © 2023 IEEE.

关键词： Computation theory

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Ownership Verification Based on Dynamic Concealment of Multiple Copyright Signatures 4th

Ownership Verification Based on Dynamic Concealment of Multi...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Bose, Saikat Arjariya, Tripti Goswami, Anirban Department of Computer Science Engineering Bhabha University Bhopal India Department of Information Technology Techno Main Salt Lake Kolkata India

ISBN: (纸本)9789819726134

This study raises a novel data security solution that focuses on dynamic authentication of e-documents transmitted in wireless domain. This is mainly achieved by concealing multiple signatures dynamically in circular orientations governed by hash operations performed on shared secret key and session random challenge. Further, with the use of particular bit sequencing patterns dynamically decided through similar hash operations and also region wise segmented casting of such signatures uplifts their security and resilience significantly. Moreover, dynamic threshold reference range based region wise variable encoding of these signatures clearly improves signature protection and recovery under various attacks. Additionally, this work also uses self-defined algebraic block transforms to embed the signature data and thereby enhancing the robustness greatly. Since receiver knows all the secret data, so by adopting exactly same hash functions and reverse mathematical operations of bit coding in proper order those casted signatures can be authenticated trustfully. Finally, exhaustive testing have fully established efficacy of this approach in contrast to the current works from various angles while it also confirms much superior authentication and confidentiality. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Authentication

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Hybrid Reptile-Snake Optimizer Based Channel Selection for Enhancing Alzheimer’s Disease Detection

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Journal of Bionic engineering 2025年第2期22卷 884-900页

作者： Digambar Puri Pramod Kachare Smith Khare Ibrahim Al-Shourbaji Abdoh Jabbari Abdalla Alameen Department of Electronics and Telecommunication Ramrao Adik Institute of TechnologyD.Y.Patil CampusNavi-MumbaiMaharashtra400706India Maersk Mc-Kinney Moller Institute Faculty of EngineeringUniversity of Southern DenmarkOdenseDenmark Department of Electrical and Electronics Engineering Jazan UniversityJazan45142Saudi Arabia Department of Computer Science University of HertfordshireHatfieldUK Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam Bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia

The global incidence of Alzheimer's Disease(AD)is on a swift *** Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using machine learning *** of AD using EEG involves multi-channel ***,the use of multiple channels may impact the classification performance due to data redundancy and *** this work,a hybrid EEG channel selection is proposed using a combination of Reptile Search Algorithm and Snake Optimizer(RSO)for AD and MCI detection based on decomposition *** Mode Decomposition(EMD),Low-Complexity Orthogonal Wavelet Filter Banks(LCOWFB),Variational Mode Decomposition,and discrete-wavelet transform decomposition techniques have been employed for subbands-based EEG *** extracted thirty-four features from each subband of EEG ***,a hybrid RSO optimizer is compared with five individual metaheuristic algorithms for effective channel *** effectiveness of this model is assessed by two publicly accessible AD EEG *** accuracy of 99.22% was achieved for binary classification from RSO with EMD using 4(out of 16)EEG ***,the RSO with LCOWFBs obtained 89.68%the average accuracy for three-class classification using 7(out of 19)*** performance reveals that RSO performs better than individual Metaheuristic algorithms with 60%fewer channels and improved accuracy of 4%than existing AD detection techniques.

关键词： Alzheimer's Disease Brain disorder Electroencephalogram Reptile Search Algorithm Snake Optimizer Optimization

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Single Person Occupancy Detection Using PIR Sensors 8th

Single Person Occupancy Detection Using PIR Sensors

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8th International Conference on Data Management, Analytics and Innovation, ICDMAI 2024

作者： Kolkar, Ranjit Geetha, V. Salvi, Sanket Department of Information Technology National Institute of Technology Karnataka Karnataka Mangalore Surthkal575025 India School of Computer Engineering and Technology MIT-WPU Maharashtra Kothrud Pune411038 India

ISBN: (纸本)9789819732418

The occupancy detection system presented in this study utilizes a combination of two PIR sensors and a micro-controller board to detect and store occupancy information in different rooms accurately. The PIR sensors detect motion within their field of view while the micro-controller processes the sensor inputs and controls the storage of occupancy data in a memory device. The circuit provides real-time occupancy status updates and allows for data retrieval for further analysis. The setup offers significant advantages such as energy efficiency, simplicity, and cost-effectiveness. The experimental results demonstrate the system's effectiveness in accurately detecting and storing occupancy information. The results show the elderly spend time in various rooms. The combined circuit has potential applications in various domains, including smart homes, energy management, and security systems, where knowledge of room occupancy patterns is crucial for optimizing resources and enhancing user experiences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Energy efficiency

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Smart Melon Farm System: Fertilizer IoT Solution

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Journal of Mobile Multimedia 2023年第5期19卷 1107-1128页

作者： Kamyod, Chayapol Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Mae Fah Luang University 57100 Thailand

Embedded systems are increasingly being employed for a wide range of applications. Small and large enterprises can benefit from sensor networks and Internet of Things technologies. Farmers, particularly the next generation of farmers, are tremendously interested in the smart farm system. This is due to Thailand's favorable geography, and young farmers are becoming more technologically literate. However, smart farm systems on the market are still too expensive and don't meet small farms' needs. Consequently, the study proposed a low-cost irrigation and fertilizer system for high-quality melon farms in Chiang Rai, Thailand. The system can properly carry out irrigation and fertilization operations on the melon farm, which require specific attention at various stages of production. As a result, the technique reduces human work while simultaneously supplying adequate water and nutrients to the entire plant. Moreover, farmers with Internet access can manually monitor or supervise the operation at any time, from any location, and on any device. The developed system may gather information from sensors and operational procedures for further analysis in order to increase output and reduce waste. The system is affordable since it was constructed primarily using open-source software and low-cost embedded components with an ergonomic architecture. The results of the comparison show that the automatic method outperforms the human approach in terms of quality and production yield. © 2023 River Publishers

关键词： fertilization IoT irrigation melon Smart farm

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