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Edge computing and Computational Task Offloading Analysis - A review study

Edge Computing and Computational Task Offloading Analysis - ...

引用

2022 international conference on Emerging Trends in electrical, control, and Telecommunication engineering, ETECTE 2022

作者： Zaidi, Tanzeel Aziz, Samia Usman, Muhammad Azam, Awais Cheema, Adeel Ashraf Ajmal, Sahar National University of Computer and Emerging Sciences Department of Computer Science Faisalabad Chiniot Pakistan

ISBN: (纸本)9781665492423

Delay constraints and energy consumption are becoming a barrier to running complex applications on mobile devices due to the rise of latency-sensitive applications. One of the fundamental technologies of Mobile Edge computing (MEC), which compensates for the limitations of mobile devices in terms of storage space, computing power, and battery efficiency, is computation offloading. The computation offloading methods in MEC networks are now the subject of extensive study for both the industry and academia, using a variety of valuable techniques and methodologies. This paper provides a detailed analysis of computing task offloading in a MEC environment. This study focuses on essential challenges related to numerous offloading goals, such as delay time, energy consumption reduction, income maximization, and system utility enhancement. © 2022 IEEE.

关键词： Computation offloading

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An FDI Resilient Dynamic Average Distributed control for DC Microgrids

An FDI Resilient Dynamic Average Distributed Control for DC ...

引用

2023 IEEE international conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Tadepalli, Phani Swecha Pullaguram, Deepak Alam, M.N. National Institute of Technology Warangal Department of Electrical Engineering Telangana 506004 India Indian Institute of Technology Department of Electrical Engineering West Bengal Kharagpur721302 India

ISBN: (纸本)9798350310573

The distributed control DC microgrids with integrated communication technologies form cyber-physical systems. Cyber-physical DC microgrids rely on peer-to-peer (P2P) communication to regulate average voltage and share proportional power. These P2P communications have greater exposure and increase the possibility of cyber intrusions. This paper aims to develop a cyber-resilient dynamic average consensus control for an autonomous DC microgrid. The proposed dynamic average resilient controller is designed to accurately track the DC microgrid network average voltage despite false data injections (FDI) attacks and also restores average voltage to nominal value while ensuring proportional current sharing. The proposed approach eliminates the need for full network connectivity and without any restrictions on the number of agents attacked. The convergence studies are carried out using input-to-state stability analysis. Further, the simulation results validate the proposed controllers efficacy against actuator and communication layer FDI attacks. © 2023 IEEE.

关键词： Cyber-attacks Cyber-Physical Systems DC Microgrids Distributed control Dynamic-average consensus Consensus False data injection Resilience

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Memristive Circuit Design of Operant Conditioning with Bridging

Memristive Circuit Design of Operant Conditioning with Bridg...

引用

2023 IEEE international conference on Memristive computing and Applications, ICMCA 2023

作者： Zhai, Yu Yue, Yi Duan, Rui Chen, Bairen Sun, Junwei Wang, Yanfeng School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China School of Information and Communication Zhengzhou Electric Power College Zhengzhou450000 China

ISBN: (纸本)9798350316230

Most of the previous operant conditioning neural network circuits only consider the basic theory and ignore the effect of additional stimuli on operant conditioning, such as bridging stimulus. In this paper, a memristor-based operant conditioning circuit with bridging is designed. The designed circuit is mainly composed of delay module, voltage control module and experience module. The various processes of operant conditioning are taken into account. The designed circuit realizes the feedback learning, experience memory, experience-based decision making and bridging functions in operant conditioning. The effect of the length of the bridging stimulus on operant conditioning is also taken into account. The study of operant conditioning with bridging can provide a reference for the study of more intelligent brain-like systems. © 2023 IEEE.

关键词： Memristors

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Quantum LSTM Model for Question Answering 8th

Quantum LSTM Model for Question Answering

引用

8th international conference on computing, control and Industrial engineering, CCIE 2024

作者： Zhao, Xingqiang Chen, Tianlong School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Department of Science and Technology Service Zhejiang Rural Commercial United Bank Co. Ltd. Hangzhou China

ISBN: (纸本)9789819769360

With the development of quantum technology, more and more quantum models have appeared. Since quantum density matrix represents all the information of the entire quantum system, novel models of meaning employing density matrices naturally model linguistic phenomena such as hyponymy and linguistic ambiguity, among others in quantum question answering tasks. Naturally, we argue that applying the quantum density matrix into classical Question Answering (QA) tasks can show more effective performance. Specifically, we (i) design a new mechanism based on Long Short-Term Memory (LSTM) to accommodate the case when the inputs are matrixes;(ii) apply the new mechanism to QA problems with Convolutional Neural Network (CNN) and gain the LSTM-based QA model with the quantum density matrix. Experiments of our new model on TREC-QA and WIKI-QA data sets show encouraging results. The application of quantum density matrix in classical question answering tasks show more effective performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Enabling IoT Continuous Connectivity in Smart Spaces 22

Enabling IoT Continuous Connectivity in Smart Spaces

引用

22nd international Symposium on Parallel and Distributed computing, ISPDC 2023

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Batalla, Jordi Mongay Dobre, Ciprian Markakis, Evangelos Mastorakis, George University of Nicosia University of Nicosia Research Foundation Departement of Computer Science Nicosia Cyprus Warsaw University of Technology Warsaw Poland University Politehnica of Bucharest National Institute for Research and Development in Informatics Automatic Control and Computers Bucharest Romania Hellenic Mediterranean University Department of Electrical and Computer Engineering Heraklion Greece Hellenic Mediterranean University Department of Management Science and Technology Agios Nikolaos Greece

ISBN: (纸本)9798350341270

Smart spaces are a rapidly emerging concept in technology. They result from the convergence of various novel technologies, such as the Internet of Things, Machine Learning and Artificial Intelligence, which allow for greater levels of automation and control within physical environments. The devices which are connected to the IoT network are equipped with sensors to acquire and exchange data. As a result, the IoT has transformed how we live, work, and play. However, the deployment in smart spaces is not always the best due to the issues arising from network node positioning. Therefore, we are investigating solutions to this problem with a novel approach which utilises Voronoi diagrams in conjunction with the algorithmic genetic technique. First, the initial positions of the IoT nodes will be determined by simulating a homogeneous Poisson point process in the smart space environment. Then, after dividing the area into the Voronoi cells, the genetic algorithm will optimise the position towards achieving full network coverage within the smart space. Experimental results prove the 100% network coverage within the specified area. © 2023 IEEE.

关键词： Genetic algorithms

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Optical and electrical Characteristics of Flexible AZO-Cu-AZO Structure Prepared Via RF Sputtering Technique

Optical and Electrical Characteristics of Flexible AZO-Cu-AZ...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： K. Kacha A. Bendjrad H. Ferhati F. Djeffal A. Benhaya Advanced Electronics Laboratory (LEA) University of Batna 2 Algeria (ISTA) University of Larbi Ben M'hidi Oum El Bouaghi Oum El Bouaghi Algeria

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

This article provides an in-depth analysis of the optical and electrical characteristics of a multilayer film consisting of AZO-Cu-AZO, which was formed using RF magnetron sputtering. The film has a thickness of 40 nm for both AZO layers and 10 nm for the middle Cu ultra-thin film. The optical characterization shows that the material has a wide range of wavelengths that it can transmit, from 442 nm to 778 nm. This range covers most of the visible and near-infrared spectrum. The material has a peak transmittance of around 70%, which suggests that it could be used as a transparent coating for optoelectronic applications. Hall effect characterization reveals a significant abundance of charge carriers of the n-type, with a concentration of 10 21 cm -3 and a good recorded electron mobility. The results indicate that the AZO-Cu-AZO layer exhibits a high level of electrical conductivity while also preserving a good optical transparency. Moreover, the economic benefits and mechanical flexibility of this structure indicate its potential use in flexible portable electronic devices and other applications. The results emphasize the significance of improving deposition methods in order to get the highest possible material performance for optoelectronic applications.

关键词： Radio frequency Performance evaluation Magnetic multilayers Optical recording Conductivity Nonhomogeneous media Optoelectronic devices Optical materials Optical films Sputtering

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Smart Interaction: Merging Augmented Reality and Internet of Things for Seamless Device control

Smart Interaction: Merging Augmented Reality and Internet of...

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2025 international conference on Intelligent computing and control Systems, ICICCS 2025

作者： Jeny, J.R.V. Sai Mahitha, B. Shashank, M. Vamsi Krishna, N. Vignan Institute of Technology and Science Department of Computer Science and Engineering(AI & ML) 508284 India

ISBN: (纸本)9798331512088

The combination of Augmented Reality (AR) and Internet of Things (IoT), often referred to as AR + IoT, offers exciting possibilities for future research and development. IoT serves as a platform for communication and remote control of connected devices, while AR provides an intuitive interface for visualizing and managing these devices through enhanced, information-rich displays. This research aims to develop an interactive and accessible home automation system that integrates IoT and AR technologies, enabling seamless remote control of electrical devices. Utilizing an ESP32/NodeMCU board interfaced with the Blynk IoT platform, the system supports device management through a mobile application and an AR interface designed in Unity. The AR interface facilitates intuitive interactions via URL-based signals, which are transmitted to the IoT hardware for execution. This dual-control mechanism enhances user flexibility and convenience, making smart home automation more accessible to users with varying technical expertise. The proposed system not only improves user interaction and control efficiency but also demonstrates the potential of AR in augmenting IoT applications, bridging the gap between physical and virtual control environments. Future enhancements could include advanced AR features, voice control, and cloud-based analytics to further optimize system performance and scalability. © 2025 IEEE.

关键词： Augmented Reality ESP32 Board Internet of Things Serial Communication Wi-Fi Connectivity

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Enhancing Dynamic Abstract Generation for Code Summarization using CODE-OAN Models and DBWTFF Frames

Enhancing Dynamic Abstract Generation for Code Summarization...

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Intelligent and Innovative Technologies in computing, electrical and Electronics (IITCEE), international conference

作者： Chandradeep Bhatt Manish Sharma Sanjay Sharma Shefali Gupta Teekam Singh Mukesh Kumar Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Computer Application Department SGRR Univeristy Dehradun India Chitkara University Institute of Engineering and Tech Chitkara University Punjab India Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Computer Science and Engineering Graphic Era Hill University Dehradun India

This research presents a robustness code abstraction generation method based on an attention mechanism. The method involves extracting high-quality code and its corresponding description language material from the programming community, specifically focusing on the text of query specifications and code responses. Redundant code and its description language material are filtered out, and the query specifications are transformed into declarative sentences for code conversion. Finally, a series model based on the attention mechanism is utilized to generate code summaries. The method effectively eliminates redundancy and noise in the code, leading to improved accuracy rates in automatic judgment, artificial evaluation, and testing. The evaluation results demonstrate superior performance compared to existing baseline methods.

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Enhancing Lightweight Face Information Detection Network with Multi-Clue Interaction and Part-Aware Supervision 25

Enhancing Lightweight Face Information Detection Network wit...

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25th international conference on Digital Image computing: Techniques and Applications, DICTA 2024

作者： Liu, Jing-Hong Chen, Yi Lee, Zer-Wei Hsu, Chih-Yuan Yen, Yu-Lun Hsiao, Pei-Yung Fu, Li-Chen National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan Automotive Research and Testing Center Taiwan National University of Kaohsiung Department of Electrical Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350379037

In recent years, technologies related to intelligent vehicles have seen rapid development, making the design of driver monitoring systems that can operate on vehicles a critical area of focus. These systems analyze drivers' facial information to assess their attention status and ability to control the vehicle. In this paper, we propose a lightweight, multitask deep learning model for detecting head pose, gaze direction, and eye state from facial images. This model is specifically designed for integration into driver monitoring systems, aiming to determine whether the driver is focused on the road. To facilitate deployment on embedded vehicle devices, our approach leverages multitask learning with carefully designed task branches to create an efficient and lightweight system. Each task is supported by dedicated branches to ensure the extraction of necessary features, with part-aware supervision enhancing the focus on relevant facial regions. Additionally, clue features encode part-specific implicit knowledge, improving task-specific feature initialization and overall model performance. We evaluate our model using the AFLW2000, BIWI, Gaze360, and CEW datasets, demonstrating that our method achieves competitive performance with reduced parameter costs. Our results show superior performance under lightweight conditions compared to existing methods, demonstrating the effectiveness of our approach in real-world applications. © 2024 IEEE.

关键词： Face recognition

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Construct a Network Security Vulnerability Knowledge Graph Based on HPO-BiLSTM-CRF 8th

Construct a Network Security Vulnerability Knowledge Graph B...

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8th international conference on computing, control and Industrial engineering, CCIE 2024

作者： Sun, Ruihan Zhuang, Yi School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9789819769360

In order to solve the problems of scattered vulnerability information and weak correlation in current vulnerability analysis technology, this paper proposes a method based on HPO-BiLSTM-CRF, which uses the unique relational data structure of the knowledge graph to provide the ability to analyze problems from a relational perspective. Method for constructing network security vulnerability knowledge graph. Based on the public vulnerability data collected from relevant databases in the field of cyberspace security, an optimized bidirectional long short-term memory network and conditional random field fusion model HPO-BiLSTM-CRF was constructed to realize knowledge extraction and store the results in the Neo4j graph database. Comparative experimental results show that the knowledge graph construction method based on HPO-BiLSTM-CRF proposed in this article has the advantages of high efficiency and high accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Knowledge graph

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