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5th IEEE International Conference on Recent Trends in computer Science and Technology, ICRTCST 2024

作者： Vivek, N. Suriya, A. Kamala, V. Chinnasamy, N.V. Akshya, J. Sundarrajan, M. Choudhry, Mani Deepak SRM Institute of Science and Technology Department of Computational Intelligence Chennai India KGiSL Institute of Technology Department of Computer Science and Engineering Coimbatore India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India SRM Institute of Science and Technology Department of Networking and Communications Chennai India KGiSL Institute of Technology Department of Information Technology Coimbatore India

ISBN: (纸本)9798350351378

Autonomous robotic cars' rapid, accurate, and efficient product handling and navigation are changing warehouse inventory management. These 24/7 smart vehicles save labor costs, human error, and operational inefficiencies. Time-consuming and incorrect manual scanning and recording is used for inventory management. Traditional autonomous car Q-learning algorithms may suffer in dynamic inventory circumstances and lack the complexity needed for real-time decision-making. Our research creates novel algorithms for autonomous robotic cars. The Deep Q-Network (DQN) we utilize for navigation adapts better to changing circumstances than ordinary Q-learning. YOLO object detection replaces slower QR code recognition for inventory monitoring. We use Decision Trees to find QR code data insights for decision-making. Our research results are promising. A greater cumulative reward curve over 100 simulated episodes gives DQN a 40% learning efficiency advantage over Q-learning. With 95% accuracy, YOLO outperformed Haar Cascade classifiers in QR code detection by 40% speed and 15% accuracy. Decision Trees identified QR code data 5.9% better than Rule-Based Systems, indicating inventory dependability. Autonomous robots can simplify inventory management in warehouses. Algorithmic technology allows these ambulances to drive intelligently, detect warehouse things faster and more accurately, and make decisions based on complicated data. These advanced artificial intelligence algorithms may make robotic systems more responsive and customized, changing inventory management subfields. These algorithms must be updated so autonomous cars can drive to meet logistical needs. © 2024 IEEE.

关键词： Object detection

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Prioritizing Vulnerability Assessment Items Using LLM Based on IoT Device Documentations

Prioritizing Vulnerability Assessment Items Using LLM Based ...

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International Conference on Internet of Things: Systems, Management and Security

作者： Yuka Ikegami Ryotaro Negishi Kento Hasegawa Seira Hidano Kazuhide Fukushima Kazuo Hashimoto Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University KDDI Research Inc

ISBN: (数字)9798350366501

ISBN: (纸本)9798350366518

With the rapid increase in demand for IoT devices, malicious attacks targeting vulnerabilities in IoT devices have been frequent in recent years. It is highly expected that the vulnerabilities can be removed from them through vulnerability assessment. However, the wide variety of IoT devices is not standardized, and it is difficult to set up vulnerability assessment items mechanically for those IoT devices, which causes a major obstacle to automate the vulnerability assessment for IoT devices. In this paper, we propose a method to prioritize vulnerability assessment items for every IoT device by effectively utilizing a large language model (LLM). The proposed method generates the answers that take into account the specifications of individual IoT devices using LLM by introducing Retrieval Augmented Generation (RAG), and determines how much suitable each vulnerability assessment item is for every IoT device by calculating the suitability using semantic entropy. Performing security tests based on the suitability must improve time efficiency while maintaining the coverage of the tests. Through the evaluation experiments, we obtained a suitability of vulnerability assessment items for the two types of IoT devices, which indicates 0.8 or higher in both the devices in terms of area under the curve (AUC).

关键词： Performance evaluation Large language models Semantics Manuals Documentation Entropy Internet of Things Security Testing

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Double RIS-Assisted MIMO Systems Over Spatially Correlated Rician Fading Channels and Finite Scatterers

Double RIS-Assisted MIMO Systems Over Spatially Correlated R...

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作者： An Le, Ha Van Chien, Trinh Nguyen, Van Duc Choi, Wan Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul08826 Korea Republic of Hanoi100000 Viet Nam Hanoi100000 Viet Nam

This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with finite scatterers, spatial correlation, and the existence of a double-scattering link between the transceiver. First, the statistical information is driven in closed form for the aggregated channels, unveiling various influences of the system and environment on the average channel power gains. Next, we study two active and passive beamforming designs corresponding to two objectives. The first problem maximizes channel capacity by jointly optimizing the active precoding and combining matrices at the transceivers and passive beamforming at the double RISs subject to the transmitting power constraint. In order to tackle the inherently non-convex issue, we propose an efficient alternating optimization algorithm (AO) based on the alternating direction method of multipliers (ADMM). The second problem enhances communication reliability by jointly training the encoder and decoder at the transceivers and the phase shifters at the RISs. Each neural network representing a system entity in an end-to-end learning framework is proposed to minimize the symbol error rate of the detected symbols by controlling the transceiver and the RISs' phase shifts. Numerical results verify our analysis and demonstrate the superior improvements of phase shift designs to boost system performance. © 1972-2012 IEEE.

关键词： Fading channels

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An Efficient Breast Cancer Detection Framework for Medical Diagnosis Applications

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computers, Materials & Continua 2022年第1期70卷 1315-1334页

作者： Naglaa F.Soliman Naglaa S.Ali Mahmoud I.Aly Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt International Academy for Engineering and Media Science October CityEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Breast cancer is themost common type of cancer,and it is the reason for cancer death toll in women in recent *** diagnosis is essential to handle breast cancer patients for treatment at the right *** with mammography is the preferred examination for breast cancer,as it is available worldwide and ***-Aided Detection(CAD)systems are used to analyze medical images to detect breast cancer,*** death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after *** of mammogram images has four main steps:pre-processing,segmentation of the region of interest,feature extraction and classification of the images into normal or abnormal *** paper presents an efficient framework for processing of mammogram images and introduces an algorithm for segmentation of the images to detect *** pre-processing step of mammogram images includes removal of digitization noise using a 2D median filter,removal of artifacts using morphological operations,and contrast enhancement using a fuzzy enhancement *** proposed fuzzy image enhancement technique is analyzed and compared with conventional techniques based on an Enhancement Measure(EME)and local contrast *** comparison shows an outstanding performance of the proposed technique from the visual and numerical *** segmentation process is performed using Otsu’smultiple thresholding *** method segments the image regions into five classes with variable intensities using four *** effectiveness is measured based on visual quality of the segmentation output,as it gives details about the image and positions of *** performance of the proposed framework is measured using Dice coefficient,Hausdorff,and Peak Signal-to-Noise Ratio(PSNR)*** segmented tumor region with the proposed segmentation method is 81%of the ground truth region provided by an ***,the proposed framew

关键词： Breast cancer mammogram images CAD contrast enhancement fuzzy logic segmentation

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Progressive Motion Boosting for Video Frame Interpolation

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IEEE Transactions on Multimedia 2023年 25卷 8076-8090页

作者： Xiao, Jing Xu, Kangmin Hu, Mengshun Liao, Liang Wang, Zheng Lin, Chia-Wen Wang, Mi Satoh, Shin'Ichi The School of Computer Science Wuhan University Wuhan430072 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430072 China The Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo101-8430 Japan

Video frame interpolation has made great progress in estimating advanced optical flow and synthesizing in-between frames sequentially. However, frame interpolation involving various resolutions and motions remains challenging due to limited or fixed pre-trained networks. Inspired by the success of the coarse-to-fine scheme for video frame interpolation, i.e., gradually interpolating frames of different resolutions, we propose a progressive boosting network (ProBoost-Net) based on a multi-scale framework to achieve flexible recurrent scales and then gradually optimize optical flow estimation and frame interpolation. Specifically, we designed a dense motion boosting (DMB) module to transfer features close to real motion to the decoded features from the later scales, which provides complementary information to refine the motion further. Furthermore, to ensure the accuracy of the estimated motion features at each scale, we propose a motion adaptive fusion (MAF) module that adaptively deals with motions with different receptive fields according to the motion conditions. Thanks to the framework’s flexible recurrent scales, we can customize the number of scales and make trade-offs between computation and quality depending on the application scenario. Extensive experiments with various datasets demonstrated the superiority of our proposed method over state-of-the-art approaches in various scenarios. © 2023 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Motion estimation

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Securing NOMA by an Active RIS: Joint Reflection and Jamming Design

Securing NOMA by an Active RIS: Joint Reflection and Jamming...

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2023 IEEE/CIC International Conference on communications in China, ICCC 2023

作者： Ji, Mengyi Chen, Jian Lv, Lu Ye, Yinghui Luo, Hao Ding, Zhiguo Xidian University School of Telecommunications Engineering China Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Khalifa University Department of Electrical Engineering and Computer Science United Arab Emirates

ISBN: (纸本)9798350345384

This paper proposes a new active reconfigurable intelligent surface (A-RIS) assisted joint reflection and jamming (JRJ) scheme to enhance the physical layer security of non-orthogonal multiple access, provide higher degrees of freedom, and overcome the effect of double fading. Specifically, the elements on the A-RIS are exploited for simultaneous signal reflection and jamming generation. The transmit beamforming, amplification factor, working mode, and phase shift of each A-RIS element are jointly optimized to maximize the system sum rate by considering imperfect channel state information of an eavesdropper. A penalty based alternating optimization algorithm is then devised to solve the above resource allocation problem. Numerical results are provided to demonstrate the security advantage of the proposed JRJ scheme over the existing baselines. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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Differential coding scheme based FSO channel for optical coherent DP-16 QAM transceiver systems

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Journal of Optical communications 2024年第2期45卷 331-345页

作者： Urooj, Shabana Alwadai, Norah Muhammad Sorathiya, Vishal Lavadiya, Sunil Parmar, Juveriya Patel, Shobhit K. Abd El-Aziz, Ismail A. Rashed, Ahmed Nabih Zaki Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf 32951 Egypt Department of Electrical Engineering College of Engineering Princess Nourah bint Abdulrahman University Riyadh84428 Saudi Arabia Department of Physics College of Sciences Princess Nourah bint Abdulrahman University Riyadh84428 Saudi Arabia Department of Information and Communication Technology Marwadi University Rajkot India Department of Physics Marwadi University Rajkot360003 India Department of Electronics and Communication Engineering Marwadi University Rajkot360003 India Department of Computer Engineering Marwadi University Rajkot360003 India Benha Faculty of Engineering Benha University Benha Egypt

This article has indicated optical coherent differential polarization (DP) 16 quadrature amplitude modulation (QAM) transceiver systems with free-space optical (FSO) channel in the presence of differential coding scheme. The optical coherent DP 16-QAM receiver executes the reverse process conversion of the optical signal into an electrical one that is detected to the users. The proposed optical coherent DP-16 QAM transceiver systems based FSO channel model with differential coding has been presented and compared with the previous model. However, the simulation results have confidence realization about the superiority of the proposed simulation model. Hence the proposed optical coherent DP-16 QAM transceiver systems simulation model with differential coding is verified and validated the enhancement performance based on simulation performance parameters. © 2024 Walter de Gruyter GmbH. All rights reserved.

关键词： Quadrature amplitude modulation

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Secure mmWave-NOMA Multi-BS Vehicular communications Using Cooperative Jamming

Secure mmWave-NOMA Multi-BS Vehicular Communications Using C...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Yan, Yiting Ju, Ying Hu, Jiawei Liu, Lei Pei, Qingqi Yau, Kok-Lim Alvin Wu, Celimuge Zhang, Ning Xidian University School of Telecommunications Engineering Xi'an710071 China Universiti Tunku Abdul Rahman School of Internet Engineering and Computer Science Selangor 43200 Malaysia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan University of Windsor Department of Electrical and Computer Engineering WindsorN9B-3P4 Canada

ISBN: (纸本)9798350351255

The fronthaul network architecture is the key to dealing with the massive traffic effectively and providing high-quality service, and the multiple base stations (BSs) deployed by it face the gigantic data transmission, which has given the demand for high-capacity communication and information security in the vehicular network. In this paper, we combine the millimeter wave (mmWave) communication and non-orthogonal multiple access (NOMA) technologies to escalate the communication capacity of multiple vehicle users (VUs), and propose a blockage-based cooperative jamming strategy to solve potential security risks in the vehicular network. In particular, with the help of jam-mers selected by this strategy, transmission security is enhanced simultaneously without escalating the instability of connections caused by the time-varying nature of vehicular networks under the NOMA transmission mechanism when the base station (BS) does not fully understand the channel state information (CSI) of VUs. Then we comprehensively analyze the specific distribution of roadways and the distance distribution of VUs under the NOMA strategy, and derive the performance metrics of the network based on the stochastic geometry method. Numerical results show that the proposed cooperative jamming scheme can effectively improve the secrecy performance of the vehicular network. © 2024 IEEE.

关键词： Jamming

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Scale-Based Slicer Placement in Elastic Optical Networks

Scale-Based Slicer Placement in Elastic Optical Networks

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2023 Opto-Electronics and communications Conference, OECC 2023

作者： Kitsuwan, Nattapong Pavarangkoon, Praphan The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan King Mongkut's Institute of Technology Ladkrabang School of Information Technology Bangkok Thailand

ISBN: (纸本)9781665462136

This paper proposes a scale-based slicer placement scheme to reduce bandwidth blocking rate (BBR) in elastic optical networks (EONs). In EONs, a slicing-stitching technology is adopted to overcome a spectrum slot allocation rule that the spectrum slots of the same request must be consecutive on the same link. This technology is done by slicers to split a spectrum band into multiple sub-spectrum components. In EONs with limited slicers, determining equally the number of slicers on every node may not result in a low BBR since the traffic volume on each node is not the same. We investigate and determine the number of slicers needed for each node as a scale-based policy. The simulation results show that our scheme achieves a BBR reduction of 91%, compared to the conventional scheme. © 2023 IEEE.

关键词： Fiber optic networks

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Chaotic Sparrow Search Algorithm with Deep Learning for Anomaly Detection in Internet of Things

Chaotic Sparrow Search Algorithm with Deep Learning for Anom...

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2023 International Conference on Integrated Intelligence and Communication Systems, ICIICS 2023

作者： Mohammed, Ibraheem Hatem Kumar, Bura Vijay Babu, Bukya Mohan Goud, Bollipelly PruthviRaj Al-Attabi, Kassem Al Rafidain University College Department of Computer Communications Engineering Bagdad Iraq SR University School of Computer Science and Artificial Intelligence Warangal India Hyderabad India Anurag University Hyderabad India The Islamic University Najaf Iraq

ISBN: (纸本)9798350315455

Anomaly Detection (AD) systems play a crucial role in identifying potential cyber-attacks or data breaches by recognizing patterns of irregular data within the Internet of Things (IoT). Standard Machine Learning (ML) techniques often prove inefficient in the face of unpredictable network behaviors and diverse anomalous methods. Deep Learning (DL) has appeared as an efficient as well as robust approach for AD, capable of classifying abnormal behaviors or patterns in data. A Chaotic Sparrow Search Algorithm with DL utilizing Recurrent Neural Network (RNN-CSSA) is proposed for AD in IoT aided sustainable smart cities. A primary objective of RNN-CSSA technique is to accurately detect anomalies in IoT aided smart cities. To achieve this, the RNN-CSSA system employs Binary Pigeon optimization Algorithm (BPEO) for effective feature selection. Additionally, CSSA technique utilizes the RNN approach for classifying anomalies. The evaluations results of the RNN-CSSA algorithm utilized the benchmark databases such as UCI-SECOM and UNSW NB-15. The results exhibit an effectiveness of proposed RNN-CSSA methodology, achieving accuracies of 99.54% and 99.55% in UNSW NB-15 and UCISECOM, when compared with existing models. © 2023 IEEE.

关键词： Anomaly Detection Binary Pigeon optimization Algorithm Chaotic Sparrow Search Algorithm Deep learning Internet of Things

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