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Multi-layer network embedding on scc-based network with motif

Digital communications and Networks 2024年第3期10卷 546-556页

作者： Lu Sun Xiaona Li Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu Department of Communication Engineering Institute of Information Science TechnologyDalian Maritime UniversityDalian116026China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province DUT School of Software Technology&DUT-RU International School of Information Science and EngineeringDalian University of TechnologyDalian 116620China College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Information and Communication Engineering Hainan UniversityHaikou 570228China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China

Interconnection of all things challenges the traditional communication methods,and Semantic communication and Computing(SCC)will become new *** is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based *** previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node ***,the content of semantic information is quite *** graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of ***,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology *** Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node *** verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

关键词： Semantic communication and computing Multi-layer network Graph neural network Motif

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Flexible sensors with zero Poisson's ratio

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National Science Review 2024年第5期11卷 153-169页

作者： Xin Huang Tianzhao Bu Qingyang Zheng Shaoyu Liu Yangyang Li Han Fang Yuqi Qiu Bin Xie Zhouping Yin Hao Wu Department of Mechanical Engineering Flexible Electronics Research Center State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and Technology Department of Electronic Science and Technology School of Integrated CircuitsHuazhong University of Science and Technology

Flexible sensors have been developed for the perception of various stimuli. However, complex deformation,usually resulting from forces or strains from multi-axes, can be challenging to measure due to the lack of independent perception of multiaxial stimuli. Herein, flexible sensors based on the metamaterial membrane with zero Poisson's ratio(ZPR) are proposed to achieve independent detection of biaxial stimuli. By deliberately designing the geometric dimensions and arrangement parameters of elements, the Poisson's ratio of an elastomer membrane can be modulated from negative to positive, and the ZPR membrane can maintain a constant transverse dimension under longitudinal stimuli. Due to the accurate monitoring of grasping force by ZPR sensors that are insensitive to curvatures of contact surfaces, rigid robotic manipulators can be guided to safely grasp deformable objects. Meanwhile, the ZPR sensor can also precisely distinguish different states of manipulators. When ZPR sensors are attached to a thermal-actuation soft robot, they can accurately detect the moving distance and direction. This work presents a new strategy for independent biaxial stimuli perception through the design of mechanical metamaterials, and may inspire the future development of advanced flexible sensors for healthcare, human–machine interfaces and robotic tactile sensing.

关键词： zero Poisson's ratio metamaterials independent perception of multiaxial stimuli flexible sensor

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Anomaly Detection of MIL-STD-1553 Word Types Based on LSTM 5

Anomaly Detection of MIL-STD-1553 Word Types Based on LSTM

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Xi, Longyu Meng, Shengwei Pan, Dawei Song, Yuchen Liu, Datong Peng, Xiyuan School of Electronics and Information Engineering Harbin Institute of Technology Harbin China College of Information and Communication Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798331529192

MIL-STD-1553 is a data bus standard that is widely used in many military scenarios due to its high reliability and stability for real-time time-division multiplexing communication. The robust design of the MIL-STD-1553 helps to improve the fault tolerance of the bus system in the event of an anomaly, but detection of these anomalies is necessary to minimize their generation and ensure reliable data transmission from a testing perspective. With a variety of information transfer formats on MIL-STD-1553, it is important to find a method of anomaly detection that is accurate, efficient and universal. To address this issue, this paper proposes a method based on Long Short-Term Memory (LSTM) to predict MIL-STD-1553 word types as an indicator of anomaly detection. Firstly, this paper proposes a MIL-STD-1553 word encoding method to extract the sequential features during information transmission. Then, an LSTM-based model is used to predict the type of the next word based on the encoded sequence of known MIL-STD-1553 words. Finally, the anomalies are determined by comparing the actual word type with the predicted word type. The method was validated on datasets containing word type anomalies and datasets containing attack injections that can lead to word type anomalies. The experimental results show that the method is effective in identifying word type anomalies in MIL-STD-1553 information transfer sequences. © 2024 IEEE.

关键词： Encoding (symbols)

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Vedic Multiplier based Medical Image Encryption - A VLSI Approach 7

Vedic Multiplier based Medical Image Encryption - A VLSI App...

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7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Vinoth Raj, R. Reddy S, Meharnath Kishore, H. Karthick, V. Yazhini, K. Kamesh, M. Velammal Institute of Technology Electronics & Communication Engineering Chennai India Kongunadu College of Engineering and Technology Electronics & Communication Engineering Thottiyam India

ISBN: (纸本)9798350341485

The protection of medical image data is more crucial as telemedicine continues to advance. The use of encryption techniques can serve as an approach to safeguard sensitive information pertaining to medical images. Software-based encryption solutions exhibit reduced computational efficiency and are susceptible to security vulnerabilities. The efficacy of flexible platform-based approaches surpasses that of alternative methods. The integration of prevailing image encryption systems with typical scrambling diffusion algorithms presents a challenge due to the inherent trade-off between real-time speed and security, since the number of scrambling diffusion cycles directly impacts both aspects. The encryption method employed in this study involves the utilization of a Linear Feedback Shift Register (LFSR) as the confusion unit and a Vedic multiplier for the diffusion process. This technique demonstrates a reduction in resource utilization and power dissipation due to the utilization of hardware-friendly designs for the diffusion and confusion modules. To ensure the efficacy of the proposed medical image encryption technique, several statistical measures such as entropy, peak signal-to-noise ratio (PSNR), histograms, and correlation factors were computed from a security perspective. Furthermore, the unpredictability of the key was evaluated by the use of the NIST SP 800-22 test. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A Conformal Ingestible Ultra-Wideband Capsule Antenna for Biotelemetry communication

A Conformal Ingestible Ultra-Wideband Capsule Antenna for Bi...

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2024 International Conference on Recent Advances in Electrical, electronics, Ubiquitous communication, and Computational Intelligence, RAEEUCCI 2024

作者： Harlan, L. Susila, M. Kumar, Sachin College of Engineering and Technology SRM Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Kattankulathur603203 India Galgotias College of Engineering and Technology Department of Electronics and Communication Engineering Greater Noida201310 India

ISBN: (纸本)9798350354539

This work presents an ingestible wireless capsule endoscopy (WCE) antenna in conformal arrangements. The performance of ingestible antennas can be hindered (detuned) by several factors within the body, including the diverse electrical properties of tissues in the digestive system, the presence of electronic components within the capsule itself, variations in the thickness of the biocompatible coating, and the flexible nature of the device. The proposed meandered loop antenna enables miniaturization, low profile, cost-effectiveness, and wide bandwidth, reducing susceptibility to detuning effects in WCE. Based on simulations, the proposed antenna mounted with electronic components exhibits wide impedance bandwidths, from 0.4 -10.6 GHz, which covers the medical implants communication services (MICS) (401-406 MHz), wireless medical telemetry services (WMTS) (1.4 GHz), industrial, scientific, medical (ISM) (0.433, 0.915, and 2.45 GHz) and ultra-wideband (UWB) (3.1 -10.6 GHz) frequency bands. The proposed antenna (22.6 × 8.9 × 0.068 mm3) conformed on a compact capsule (17×7 mm2) has a gain of -37.0, - 35.3, - 29.1, - 32.3, and - 26.2 for 0.413, 0.433, 0.915, 1.4, and 2.45 GHz (central frequencies) respectively. In addition, the antenna is validated for robustness using different homogeneous phantoms (colon, muscle, small intestine, and stomach), and performance metrics such as far-field and SAR have been evaluated for central frequencies considering muscle phantom. © 2024 IEEE.

关键词： Cost effectiveness

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A Metaheuristic Approach Based Adaptive Filter Design for EEG Noise Mitigation Application 3

A Metaheuristic Approach Based Adaptive Filter Design for EE...

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3rd International Conference on Power, Control and Computing Technologies, ICPC2T 2024

作者： Yadav, Shubbam Saha, Suman Kumar Kar, Rajib National Institute of Technology Department of Electronics and Communication Engineering Raipur Raipur India National Institute of Technology Department of Electronics and Communication Engineering Durgapur Durgapur India

ISBN: (纸本)9798350349207

Electroencephalography stands as a well-established clinical procedure, pivotal in diagnosing a myriad of brain disorders. However, electroencephalogram (EEG) waveforms are susceptible to an array of noise sources, which significantly complicate EEG data analysis. In this study, the authors have employed adaptive filtering in conjunction with metaheuristic algorithms to mitigate noise in EEG signals. Specifically, we have utilized the Harmony Search (HS), Gravitational Search Algorithm (GSA), and Preacher's Optimization Algorithm (POA) to address artifacts within epileptic EEG signals. We have quantified various fidelity parameters, including Mean Squared Error (MSE), Maximum Error (ME), and the output Signal-to-Noise Ratio (SNR{o}). Notably, our proposed adaptive filter based on POA has demonstrated superior performance when compared to previously documented filtering techniques. In summary, our proposed approach exhibits enhanced accuracy and is deemed more suitable for EEG filtering when contrasted with existing methods. © 2024 IEEE.

关键词： Adaptive filters

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IoT Based Animal Detection and Alert System for Farm Fields

IoT Based Animal Detection and Alert System for Farm Fields

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2024 International Conference on communication, Computing and Internet of Things, IC3IoT 2024

作者： Manikandan, T. Kumaresan, S. Joshua Muruganandham, A. Nandalal, V. Babuji, R. Rajalakshmi Engineering College Department Of Electronics And Communication Engineering Chennai India Saveetha Institute Of Medical And Technical Sciences Saveetha School Of Engineering Department Of Ece Chennai India Rajarajeswari College Of Engineering Vtu Department Of Electronics And Communication Engineering Bangaluru India Sri Krishna College Of Engineering And Technology Department Of Electronics And Communication Engineering Coimbatore India R.M.K Engineering College Department Of Electronics And Communication Engineering Chennai India

ISBN: (纸本)9798350352689

The main objective of this work is to alert the farmer when an animal enters into their farm field and prevent the animal entering into the form field. The animals suddenly entering to the field is the major issue that farm owners frequently deal with. The traditional farming techniques need to be replaced with smart farming methods in order to prevent the entry of animals. The proposed sytem uses the sensors, arduino and Internet of Things (IoT). This developed system also enables the farm owner to get the Short Message Service (SMS) through Global System for Mobile (GSM). In addition, it provides the access to the farm owner to control the entry of the animal to farm field automatically or manually from the home. As the developed system transmits the real time pictures of the animal to the farm owner through telegram bot, he/she will be well prepared to protect the animals. Further, the developed system makes use of speaker to play the same detected animal sound as a way to repel the animal. It also produces the fog and lights to prevent the immediate entry of animals. Thus, this work facilitates the smart way to control the wild animals entering to the farmland. © 2024 IEEE.

关键词： Animals

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An Optimized Field Programmable Gate Array Based Noise Reduction Techniques for Fetal Electrocardiogram Signal Processing 2

An Optimized Field Programmable Gate Array Based Noise Reduc...

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2nd IEEE International Conference on Integrated Intelligence and communication Systems, ICIICS 2024

作者： Aadhavan, K. Balasubramanian, M. Sowmya, S. Jose, Deepa Kagoo, Lysander B. Al-Zaidi, Rabab Department of Electronics and Communication Engineering Meenakshi Sundararajan Engineering College Chennai India Department of Electronics and Communication Engineering KCG College of Technology Chennai India School of Science Engineering and Environment University of Salford Salford Manchester United Kingdom

ISBN: (纸本)9798331504960

Analyzing fetal electrocardiogram (FECG) signals is essential for identifying fetal cardiac disorders early on, although noise interference is still a problem. Conventional signal processing techniques can produce conflicting findings. With an emphasis on three important noise reduction methods the Kalman Filter, Discrete wavelet transform, and Finite impulse response this study evaluates the performance of the PYNQZ2 and NEXYS A7 Field Programmable Gate Array (FPGA) boards in real-time FECG signal monitoring. With a mean squared error of 0.58% and a signal-to-noise ratio of 31.1 dB, the Kalman Filter fared better than the other filters, especially when it came to lowering dynamic noise in real-time applications. Furthermore, the PYNQ Z2 was outperformed by the NEXYS A7 board at processing FECG signals efficiently. effectively. By providing insights into the best noise reduction strategies and improving the accuracy of FECG monitoring in biomedical applications, this comparative analysis advances FPGA-based signal processing systems. © 2024 IEEE.

关键词： Mean square error

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Optimization Of Neural Network Architectures for Real-Time Object Detection in Autonomous Vehicles Using Variational Mimetic Operator Networks 2

Optimization Of Neural Network Architectures for Real-Time O...

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Kodeeswari, K. Loganathan, P. Narmatha, P. Mutha, Rakhi Jayasudha, F.V. Savitha, V. Kongu Engineering College Department of Electronics and Communication Engineering Erode India Department of Electronics and Communication Engineering Namakkal India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bangalore India Amity University Department of Information Technology Rajasthan Jaipur India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Chennai119 India Erode Sengunthar Engineering College Department of Electronics and Communication Engineering Erode638 05 India

ISBN: (纸本)9798331534950

The Research focus lies in the optimization of neural network structures specifically for real-time object recognition applications in autonomous vehicles, which is accomplished through the use of Vibrational Mimetic Operator Networks (VMON) as the technology baseline. By combining variation principles with mimetic approaches, VMON achieves improved generalization and computational efficiency in the solution process. Due to tight latency requirements in autonomous vehicle applications, conventional neural architectures frequently find it challenging to strike a balance between speed and detection performance. To this end, harness dynamically adaptable layers and parameter pruning within framework, enabling efficient inference without sacrificing accuracy. Intersperse the architecture with both localized and global feedback mechanisms that dynamically renormalize weights in real time, minimizing response lag of system even more. Large-scale experiments show that VMON beats baseline detectors, such as YOLO and Faster R-CNN on latency, with up to 35% reduction in processing time in average autonomous navigation scenarios. Taken together, results highlight the ability of VMON to set new benchmarks in efficiency for object detection and pave the way for safer and more reliable autonomous vehicle systems. This will be followed by research on the scalability of this methodology to various vehicular platforms and conditions of real-world traffic. © 2024 IEEE.

关键词： Image segmentation

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Performance Enhancement of MIMO-OFDM System with Perfect Channel Estimation Using Delayed Feedback 1

Performance Enhancement of MIMO-OFDM System with Perfect Cha...

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1st International Conference on Advances in Computer Science, Electrical, electronics, and communication Technologies, CE2CT 2025

作者： Suban, A. Jagaprathaban, J. Nithin Narayanan, S. Thanaseelan, A. UG-Final year in Electronics and Communication Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518578

Using multiple broadcast and capturing antennas to create MIMO channels can enhance capacity by a factor equal to the smaller of the number of broadcasting or capturing elements. To reduce inter-symbol interference and increase system capacity, Subcarrier-Based Transmission Technique (OFDM) is employed in MIMO channels (MIMO-OFDM) to enable efficient wideband transmission in this study. Two separate space-time codes are used by the MIMO-OFDM system for two sets of two broadcasting antennas. Pre-whitening and Closest-point interpretation based on Iterative interference suppression are used at the receiver to decode the separate space-time codes. The primary goal of this work is to estimate the ideal channel utilising delayed feedback, in which the transmitter and receiver estimate the feedback. Guard bits are used here for the OFDM signals. We discovered that LS is a perfect channel by examining the estimators' results in MATLAB. Thus, the optimal method for channel estimation is delayed feedback. Additionally, the experimental results guarantee improved performance when a MIMO-OFDM system employs Delayed Feedback and Channel Estimation. © 2025 IEEE.

关键词： Space time codes

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