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Cybersecurity 2024年第2期7卷 13-27页

作者： B S Sharmila Rohini Nagapadma Depatment of Electronics and communication engineering The National Institute of EngineeringMysoreKarnataka 570008India

In recent years,many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify *** deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge *** study proposes quantized autoencoder(QAE)model for intrusion detection systems to detect *** is an optimization model derived from autoencoders that incorporate pruning,clustering,and integer quantization *** autoencoder uint8(QAE-u8)and quantized autoencoder float16(QAE-f16)are two variants of QAE built to deploy computationally expensive Al models into Edge ***,we have generated a Real-Time Internet of Things 2022 dataset for normal and attack *** autoencoder model operates on normal traffic during the training *** same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error(RE)of the anomaly will be high,which helps to identify the ***,we study the performance of the autoencoders,QAE-u8,and QAE-f16 using accuracy,precision,recall,and F1 score through an extensive experimental *** showed that QAE-u8 outperforms all other models with a reduction of 70.01%in average memory utilization,92.23%in memory size compression,and 27.94%in peak CPU ***,the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.

关键词： IoT constrained system

A Generalized Array Factor for Time-Modulated Hexagonal Based Antenna Array Geometry With Novel Trapezoidal Switching

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1967-1972页

作者： Gopi Ram Department of Electronics and communication engineering National Institute of TechnologyWarangal 506004India

The concept of the time-modulated array has been emerging as an alternative to the complex phase shifters,which lowers the cost of the array feeding network due to the utilization of radio frequency(RF)*** various forms of hexagonal antenna array geometries can be used for applications like surveillance tracking in phased array radar and wireless communication *** work proposes the generalized array factor(AF)for the hexagonal antenna array geometry based on time *** time modulation in generalized hexagonal geometry can maintain the fixed static amplitude excitation,giving more flexibility over ***,a novel trapezoidal switching function is also proposed and applied to the generalized array factor to enable future researchers to use this array factor in the field of advancement to observe how switching schemes like trapezoidal and rectangular affect the array pattern's side lobe level(SLL).The generalized equation can be utilized for the analysis and synthesis of radiation characteristics of the time-modulated hexagonal array(TMHA),time-modulated concentric hexagonal array(TMCHA),time-modulated hexagonal cylindrical array(TMHCA),and time-modulated hexagonal concentric cylindrical array(TMHCCA).The numerical result illustrates the generation of AF of time-modulated hexagonal structures and also shows that the trapezoidal switching sequence outperforms the rectangular switch using the cat swarm optimization(CSO)approach.

关键词： Hexagonal array geometry radiation pattern time-modulation trapezoidal pulse

Joint Rain Streaks & Haze Removal Network for Object Detection

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Computers, Materials & Continua 2024年第6期79卷 4683-4702页

作者： Ragini Thatikonda Prakash Kodali Ramalingaswamy Cheruku Eswaramoorthy K.V Department of Electronics and communication engineering National Institute of TechnologyWarangal506004India Department of Computer Science and engineering National Institute of TechnologyWarangal506004India Department of Electronics and communication engineering Indian Institute of Information TechnologyDesign and ManufacturingKurnool518008India

In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.

关键词： Image deraining Selective Dense Residual Module(SDRM) Selective Kernel Fusion Module(SKFM) Selective KernelDense Residual M-Shaped Network(SKDRMNet)

Graph Signal Reconstruction from Low-Resolution Multi-Bit Observations

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Chinese Journal of Electronics 2024年第1期33卷 153-160页

作者： Zhaoting LIU Chen YU Yafeng WANG Shuchen LIU School of communication engineering Hangzhou Dianzi University

Low hardware cost and power consumption in information transmission, processing and storage is an urgent demand for many big data problems, in which the high-dimensional data often be modelled as graph *** paper considers the problem of recovering a smooth graph signal by using its low-resolution multi-bit quantized observations. The underlying problem is formulated as a regularized maximum-likelihood optimization and is solved via an expectation maximization scheme. With this scheme, the multi-bit graph signal recovery(MB-GSR) is efficiently implemented by using the quantized observations collected from random subsets of graph nodes. The simulation results show that increasing the sampling resolution to 2 or 3 bits per sample leads to a considerable performance improvement, while the energy consumption and implementation costs remain much lower compared to the implementation of high resolution sampling.

关键词： Quantization (signal) Costs Power demand Simulation Energy resolution Signal sampling Signal reconstruction

Secure resource allocation against colluding eavesdropping in a user-centric cell-free massive multiple-input multiple-output system

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Frontiers of Information Technology & Electronic engineering 2024年第4期25卷 500-512页

作者： Na LI Yuanyuan GAO Kui XU Xiaochen XIA Huazhi HU Yang LI Yueyue ZHANG College of communication engineering Army Engineering University of PLANanjing 210007China

We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive *** address the problem of limited pilot resources,a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel *** at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers,based on the local partial zero-forcing precoding scheme,a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral *** results show that the proposed scheme can effectively reduce channel estimation error and improve system security.

关键词： Cell-free Colluding eavesdropping Limited pilot resources Access point selection Security rate

Intelligent secure near-field communication

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Science China(Information Sciences) 2024年第9期67卷 340-341页

作者： Nan ZHANG Jifa ZHANG Chengwen XING Na DENG Nan ZHAO School of Information and communication engineering Dalian University of Technology School of Information and Electronics Beijing Institute of Technology

The research and development efforts for the sixth generation(6G) wireless communication are underway to fulfill the growing demands for wireless communications. 6G is expected to become the key enabler for diverse new applications and services [1]. To achieve the excellent performance, 6G will implement extremely large-scale antenna arrays(ELAAs), terahertz [2], and new types of antennas with metamaterials, leading to a paradigm shift for the electromagnetic characteristics.

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LiDAR-based estimation of bounding box coordinates using Gaussian process regression and particle swarm optimization

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Biomimetic Intelligence & Robotics 2024年第1期4卷 24-35页

作者： Vinodha K. E.S.Gopi Tushar Agnibhoj Department of Electronics and communication engineering National Institute of Technology TiruchirappalliTamil Nadu620015India

Camera-based object tracking systems in a given closed environment lack privacy and *** this study,light detection and ranging(LiDAR)was applied to track objects similar to the camera tracking in a closed environment,guaranteeing privacy and *** primary objective was to demonstrate the efficacy of the proposed technique through carefully designed experiments conducted using two *** Scenario I,the study illustrates the capability of the proposed technique to detect the locations of multiple objects positioned on a flat surface,achieved by analyzing LiDAR data collected from several locations within the closed *** II demonstrates the effectiveness of the proposed technique in detecting multiple objects using LiDAR data obtained from a single,fixed ***-time experiments are conducted with human subjects navigating predefined *** individuals move within an environment,while LiDAR,fixed at the center,dynamically tracks and identifies their locations at multiple *** demonstrate that a single,strategically positioned LiDAR can adeptly detect objects in motion around ***,this study provides a comparison of various regression techniques for predicting bounding box *** process regression(GPR),combined with particle swarm optimization(PSO)for prediction,achieves the lowest prediction mean square error of all the regression techniques examined at *** tuning of GPR using PSO significantly minimizes the regression *** of the experiment pave the way for its extension to various real-time applications such as crowd management in malls,surveillance systems,and various Internet of Things scenarios.

关键词： LiDAR Data acquisition Bounding box Gaussian process regression Particle swarm optimization(PSO)

Blockchain-Based Certificateless Cross-Domain Authentication Scheme in the Industrial Internet of Things

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Computers, Materials and Continua 2024年第3期80卷 3835-3854页

作者： Li Z. Liu X. Zhang N. Wei Z. Department of Electronic and communication engineering Beijing Electronic Science and Technology Institute Beijing 100070 China

The Industrial Internet of Things (IIoT) consists of massive devices in different management domains, and the lack of trust among cross-domain entities leads to risks of data security and privacy leakage during information exchange. To address the above challenges, a viable solution that combines Certificateless Public Key Cryptography (CL-PKC) with blockchain technology can be utilized. However, as many existing schemes rely on a single Key Generation Center (KGC), they are prone to problems such as single points of failure and high computational overhead. In this case, this paper proposes a novel blockchain-based certificateless cross-domain authentication scheme, that integrates the threshold secret sharing mechanism without a trusted center, meanwhile, adopts blockchain technology to enable cross-domain entities to authenticate with each other and to negotiate session keys securely. This scheme also supports the dynamic joining and removing of multiple KGCs, ensuring secure and efficient cross-domain authentication and key negotiation. Comparative analysis with other protocols demonstrates that the proposed cross-domain authentication protocol can achieve high security with relatively low computational overhead. Moreover, this paper evaluates the scheme based on Hyperledger Fabric blockchain environment and simulates the performance of the certificateless scheme under different threshold parameters, and the simulation results show that the scheme has high performance. Copyright © 2024 The Authors. Published by Tech Science Press.

关键词： blockchain certificateless cross-domain authentication IIoT

Image Fusion Based on Bioinspired Rattlesnake Visual Mechanism Under Lighting Environments of Day and Night Two Levels

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Journal of Bionic engineering 2024年第3期21卷 1496-1510页

作者： Yong Wang Hongmin Zou College of communication engineering Jilin UniversityChangchun130012China

This study,grounded in Waxman fusion method,introduces an algorithm for the fusion of visible and infrared images,tailored to a two-level lighting environment,inspired by the mathematical model of the visual receptive field of rattlesnakes and the two-mode cells'*** research presented here is segmented into three *** the first segment,we design a preprocessing module to judge the ambient light intensity and divide the lighting environment into two levels:day and *** second segment proposes two distinct network structures designed specifically for these daytime and nighttime *** the daytime images,where visible light information is predominant,we feed the ON-VIS signal and the IR-enhanced visual signal into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel,***,for nighttime images where infrared information takes precedence,the ON-IR signal and the Visual-enhanced IR signal are separately input into the central excitation and surrounding suppression regions of the ON-center receptive field in the B *** outcome is a pseudo-color fused *** third segment employs five different no-reference image quality assessment methods to evaluate the quality of thirteen sets of pseudo-color images produced by fusing infrared and visible *** images are then compared with those obtained by six other methods cited in the relevant *** empirical results indicate that this study's outcomes surpass the comparative results in terms of average gradient and spatial *** one or two sets of fused images underperformed in terms of standard deviation and entropy when compared to the control *** sets of fused images did not perform as well as the comparison in the QAB/F *** conclusion,the fused images generated through the proposed method show superior performance in terms of scene detail,visual perception,and image sharpness

关键词： Rattlesnake Visible image Infrared image Daylight Bionic

Improve Chinese Aspect Sentiment Quadruplet Prediction via Instruction Learning Based on Large Generate Models

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Computers, Materials & Continua 2024年第3期78卷 3391-3412页

作者： Zhaoliang Wu Yuewei Wu Xiaoli Feng Jiajun Zou Fulian Yin College of Information and communication engineering Communication University of ChinaBeijing100024China The State Key Laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China Department of Electronic engineering Tsinghua UniversityBeijing100084China

Aspect-Based Sentiment Analysis(ABSA)is a fundamental area of research in Natural Language Processing(NLP).Within ABSA,Aspect Sentiment Quad Prediction(ASQP)aims to accurately identify sentiment quadruplets in target sentences,including aspect terms,aspect categories,corresponding opinion terms,and sentiment ***,most existing research has focused on English ***,while ASQP has seen significant progress in English,the Chinese ASQP task has remained relatively *** inspiration from methods applied to English ASQP,we propose Chinese generation templates and employ prompt-based instruction learning to enhance the model’s understanding of the task,ultimately improving ASQP performance in the Chinese ***,under the same pre-training model configuration,our approach achieved a 5.79%improvement in the F1 score compared to the previously leading ***,when utilizing a larger model with reduced training parameters,the F1 score demonstrated an 8.14%***,we suggest a novel evaluation metric based on the characteristics of generative models,better-reflecting model *** results validate the effectiveness of our approach.

关键词： ABSA ASQP LLMs sentiment analysis Chinese comments