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Developing Sustainable Solutions Using Technological Approaches for Disaster Management and Energy Access in Mountainous Ranges: A Case Study of Sera Village, India 4

Developing Sustainable Solutions Using Technological Approac...

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4th International Conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Kumar, Y. Jagadish Surya Vamsi, D. Nishaanth, K.N. Mouria, Naren Raghul, K.R. Sampath Kumar, S. Cornet, Souresh Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering India Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Computer Engineering India Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Communication Engineering India Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering India Amrita Vishwa Vidyapeetham Amritapuri Amrita School for Sustainable Futures India

ISBN: (纸本)9798350343670

This research looks at two essential aspects of sustainable development in India's mountainous regions: energy access and vulnerability to natural disasters such as landslides. The research is based on an inductive in-depth evaluation of Sera village in Uttarakhand using Participatory Rural Appraisal (PRA) tools and Human-Centered Design (HCD) techniques. This approach enables a thorough understanding of these regions' complex challenges in order to provide relevant technological alternatives to meet the identified challenges. An integrated solution for landslide prediction powered by a hydropower system is presented, incorporating image processing and deep learning. This research provides useful insights for future work to address the issues inhabitants face of mountainous settings, ultimately supporting sustainable development in rural areas. © 2024 IEEE.

关键词： Deep learning Image Processing Landslides Live-in-Labs® Participatory Rural Appraisal Rural Electrification

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Secure Student Record Management using Visual Cryptography in Educational Systems 9

Secure Student Record Management using Visual Cryptography i...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Chinnasamy, P. Deepalakshmi, P. Kiranchandu, E. Gireesh, C. Kiran, G. Priya, D. Divya School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Virudhunagar India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350377972

Cloud computing is vital for data transmission and storage in the digital era, highlighting the urgent requirement for strong data security measures. Conventional encryption techniques such as RSA, while dependable, have considerable computational burden and energy requirements owing to their extensive key sizes. This study examines the efficacy of Elliptic Curve Cryptography (ECC) as a superior solution for data security in cloud environments. The suggested method utilizes ECC's reduced key sizes to attain improved computational efficiency and energy saving, all while upholding rigorous encryption standards. A comparison research indicates that ECC surpasses RSA in performance and resource efficiency, rendering it especially appropriate for extensive cloud systems handling significant amounts of sensitive information. This research examines the implementation of the Advanced Encryption Standard (AES) algorithm in Cipher Block Chaining (CBC) mode for image encryption. The AES-CBC technique efficiently safeguards images by transforming them into encrypted formats, so obstructing illegal access. Comparative assessments using alternative encryption methods highlight AES's enhanced security and computational efficacy. Collectively, these findings underscore the capability of ECC and AES to overcome the shortcomings of conventional encryption, providing secure and resource-efficient solutions for contemporary cloud computing issues. © 2024 IEEE.

关键词： Cloud security

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Robust Device-Free Mmwave Sensing with Specular Reflection Interference Mitigation

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IEEE Transactions on Mobile computing 2025年第7期24卷 5749-5764页

作者： Liu, Yulin Wang, Jie Gao, Qinghua Pan, Miao Fang, Yuguang Dalian Maritime University School of Information Science and Technology Dalian116026 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

Device-Free mmWave Sensing (DFWS) could sense target state by analyzing how target activities influence the surrounding mmWave signals. It has emerged as a promising sensing technology. However, when employing DFWS indoors, specular reflection interference arises due to the specular reflectors. This interference often induces ghost targets, impacting the accurate estimation of the number and position of targets, resulting in degradation in sensing performance. To tackle this issue, we delve into the generation mechanism of specular reflection interference and analyze its multi-domain characteristics. Through exploration, we discern its temporal sparsity, spatial symmetry or collinearity, and frequency correlation characteristics, and propose four metrics to measure them, accordingly. Specifically, we propose a temporal characteristic quantitative evaluation metric based on identity matching, spatial symmetry and collinearity quantitative evaluation metrics based on geometric analysis, and a frequency correlation quantitative evaluation metric based on Doppler velocity correction, respectively. Based on these metrics, we design a novel Specular Reflection Interference Mitigation (SRIM) method and develop a robust SRIM-DFWS prototype system based on a 60 GHz mmWave radar to validate our proposed method. Experimental results demonstrate that our proposed method could achieve accurate and effective mitigation of specular reflection interference in device-free target tracking. © 2002-2012 IEEE.

关键词： Radar interference

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Ensemble-Based Reliability Enhancement for Edge-Deployed CNNs in Few-Shot Scenarios

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 1062-1075页

作者： Gao, Zhen Liu, Shuang Zhao, Junbo Wang, Xiaofei Wang, Yu Han, Zhu Tianjin University School of Electrical and Information Engineering Tianjin300072 China Tsinghua University School of Electronic Engineering Beijing100084 China Tianjin University College of Intelligence and Computing Tianjin300072 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States

Convolutional Neural Networks (CNNs) have been applied in wide areas of computer vision, and edge intelligence is expected to provide instant AI service with the support of broadband mobile networks. However, the deployment of CNNs on network edge faces severe challenges. First, edge or embedded devices are usually not reliable, and hardware failures can corrupt the CNN system, which is unacceptable for critical applications, such as autonomous driving and object detection on space platforms. Second, edge or embedded devices are usually resource-limited, and therefore traditional redundancy-based protection methods are not applicable due to huge overhead. Although network pruning is effective to reduce the complexity of CNNs, we cannot have sufficient data for performance recovery in many scenarios due to privacy and security concerns. To enhance the reliability of CNNs on resource-limited devices with the few-shot constraint, we propose to construct an ensemble system with weak base CNNs pruned from the original strong CNN. To improve the ensemble performance with diverse base CNNs, we first propose a novel filter importance evaluation method by combining the amplitude and gradient information of the filter. Since the gradient part is related to the input data, different subsets of data are used for layer sensitivity analysis for different base CNNs, so that the different pruning configurations can be obtained for each base CNN. On this basis, a modified ReLU function is proposed to determine the final pruning rate of each layer in each base CNN. Extensive experiments prove that the proposed solution can effectively improve the reliability of CNNs with much less resource requirement for each edge server. © 2023 CCBY.

关键词： Reliability

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Twitching Control for Pneumatic Artificial Muscle Actuators

Twitching Control for Pneumatic Artificial Muscle Actuators

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Bogdan, Piotr A. Smith, Oliver Klein, Frederico B. Gianni, Mario University of Plymouth School of Engineering Computing and Mathematics Faculty of Science and Engineering United Kingdom University of Liverpool School of Electrical Engineering Electronics and Computer Science United Kingdom

ISBN: (纸本)9798350325706

In this work we present the design and development of a twitching control system for pneumatic artificial muscle (PAM) actuators. In this system, a shape memory alloy (SMA) poppet valve is used to control the flow of air pressurizing the inner bladder of a McKibben-based PAM. The valve is driven by pulse width modulation with changing frequency, allowing the PAM to resemble the mammalian muscles twitching. An adjustable passive exhaust orifice is used in place of an exhaust air valve to release the air pressure from the bladder mimicking natural muscle relaxation behaviour. Experiments under isometric and isotonic contractions show that the proposed control system reduces hysteresis of about 72% compared to continuous activation against 15% loss in contraction force with respect to conventional exhaust air valves. © 2023 IEEE.

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An Imperceptible Adversarial Attack Against 3D Object Detectors in Autonomous Driving

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IEEE Internet of Things Journal 2025年第12期12卷 21404-21414页

作者： Wang, Yizhou Wu, Libing Jin, Jiong Wang, Enshu Zhang, Zhuangzhuang Zhao, Yu Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Swinburne University of Technology School of Engineering MelbourneVIC3122 Australia Wuhan University School of Cyber Science and Engineering Wuhan430072 China City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

As LiDAR-based 3D object detection gains attention, existing research on point cloud adversarial attacks has exposed vulnerabilities in 3D neural network models, which can further impact the reliability of perception systems in autonomous driving. However, current adversarial attacks primarily focus on the point cloud classification tasks, while detection tasks are more challenging to attack because they involve the localization of multiple targets and the sparse distribution of objects. Existing methods often implement attacks by adding global perturbations to the point clouds, which results in poor attack performance and lack of imperceptibility. In this paper, we investigate the robustness of 3D object detectors against adversarial examples. We propose a novel imperceptible attack method to generate 3D adversarial point clouds. First, we introduce the saliency map for the point clouds, assigning the unique value to each point to measure its importance to the model's discrimination results. These salient points are then aggregated and adaptively matched to different attack areas corresponding to different targets. Next, we design an optimization-based attack algorithm to generate adversarial point clouds, which are supervised by a dual-loss function consisting of the detection loss to ensure attack effectiveness and the distance loss to limit gap with the original point cloud. Finally, we conducted experiments on two real-world datasets, the KITTI and Waymo Open datasets, to evaluate the proposed attack method. Extensive experiments demonstrate that our attack method achieves average attack success rates of 83.07% and 77.11% on two datasets against seven 3D object detectors with minimal perturbations. Additionally, the generated adversarial point clouds exhibit strong transferability across multiple mainstream detectors. © 2025 IEEE.

关键词： Object detection

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Weakly-Supervised Learning for Aspect-Based Sentiment Analysis of Urdu Tweets 8

Weakly-Supervised Learning for Aspect-Based Sentiment Analys...

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8th Student Research Workshop, RANLPStud 2023

作者： Zoya Department of Computing School of Electrical Engineering & Computer Science National University of Sciences & Technology IslamabadH-12 Pakistan

Aspect-based sentiment analysis (ABSA) is vital for text comprehension which benefits applications across various domains. This field involves the two main sub-tasks including aspect extraction and sentiment classification. Existing methods to tackle this problem normally address only one sub-task or utilize topic models that may result in overlapping concepts. Moreover, such algorithms often rely on extensive labeled data and external language resources, making their application costly and time-consuming in new domains and especially for resource-poor languages like Urdu. The lack of aspect mining studies in Urdu literature further exacerbates the inapplicability of existing methods for Urdu language. The primary challenge lies in the preprocessing of data to ensure its suitability for language comprehension by the model, as well as the availability of appropriate pre-trained models, domain embeddings, and tools. This paper implements an ABSA model Huang et al. (2020) for unlabeled Urdu tweets with minimal user guidance, utilizing a small set of seed words for each aspect and sentiment class. The model first learns sentiment and aspect joint topic embeddings in the word embedding space with regularization to encourage topic distinctiveness. Afterwards, it employs deep neural models for pre-training with embedding-based predictions and self-training on unlabeled data. Furthermore, we optimize the model for improved performance by substituting the CNN with the BiLSTM classifier for sentence-level sentiment and aspect classification. Our optimized model achieves significant improvements over baselines in aspect and sentiment classification for Urdu tweets with accuracy of 64.8% and 72.8% respectively, demonstrating its effectiveness in generating joint topics and addressing existing limitations in Urdu ABSA. © 2023 Incoma Ltd. All rights reserved.

关键词： Sentiment analysis

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Fixed-time-synchronized control: a system-dimension-categorized approach

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science China(Information sciences) 2023年第7期66卷 177-194页

作者： Wanyue JIANG Shuzhi Sam GE Dongyu LI Institute for Future & Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Department of Electrical and Computer Engineering National University of Singapore School of Cyber Science and Technology Beihang University Shanghai Institute of Satellite Engineering

This study addresses the fixed-time-synchronized control problem of perturbed multi-input multioutput(MIMO) systems. In the task of fixed-time-synchronized control, different dimensions of the output signal in MIMO systems are required to reach the desired value simultaneously within a fixed time *** MIMO system is categorized into two cases: the input-dimension-dominant and the state-dimensiondominant cases. The classification is defined according to the dimension of system signals and, more importantly, the capability of converging at the same time. For each kind of MIMO system, sufficient Lyapunov conditions for fixed-time-synchronized convergence are explored, and the corresponding robust sliding mode controllers are designed. Moreover, perturbations are compensated using the super-twisting technique. The brake control of the vertical takeoff and landing aircraft is considered to verify the proposed method for the input-dimension-dominant case, which shows the essential advantages of decreasing the energy consumption and the output trajectory length. Furthermore, comparative numerical simulations are performed to show the semi-time-synchronized property for the state-dimension-dominant case.

关键词： fixed-time-synchronized convergence sliding mode control perturbed MIMO systems

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Securing MIMO Wiretap Channel With Learning-Based Friendly Jamming Under Imperfect CSI

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IEEE Internet of Things Journal 2025年第11期12卷 16009-16022页

作者： Minh Tuan, Bui Nguyen, Diep N. Linh Trung, Nguyen Nguyen, Van-Dinh Van Huynh, Nguyen Thai Hoang, Dinh Krunz, Marwan Dutkiewicz, Eryk University of Technology Sydney School of Electrical and Data Engineering SydneyNSW2007 Australia University of Engineering and Technology Vietnam National University Faculty of Electronics and Telecommunications Hanoi100000 Viet Nam College of Engineering and Computer Science VinUniversity Hanoi100000 Viet Nam University of Liverpool Department of Electrical Engineering and Electronics LiverpoolL69 3GJ United Kingdom The University of Arizona Department of Electrical and Computer Engineering TucsonAZ85721 United States

Wireless communications are particularly vulnerable to eavesdropping attacks due to their broadcast nature. To effectively deal with eavesdroppers, existing security techniques usually require accurate channel state information (CSI), e.g., for friendly jamming (FJ), and/or additional computing resources at transceivers, e.g., cryptography-based solutions, which unfortunately may not be feasible in practice. This challenge is even more acute in low-end IoT devices. We thus introduce a novel deep learning-based FJ framework that can effectively defeat eavesdropping attacks with imperfect CSI and even without CSI of legitimate channels. In particular, we first develop an autoencoder-based communication architecture with FJ, namely, AEFJ, to jointly maximize the secrecy rate and minimize the block error rate (BLER) at the receiver without requiring perfect CSI of the legitimate channels. In addition, to deal with the case without CSI, we leverage the mutual information neural estimation (MINE) concept and design a MINE-based FJ scheme that can achieve comparable security performance to the conventional FJ methods that require perfect CSI. Extensive simulations in a multiple-input-multiple-output (MIMO) system demonstrate that our proposed solution can effectively deal with eavesdropping attacks in various settings. Moreover, the proposed framework can seamlessly integrate MIMO security and detection tasks into a unified end-to-end learning process. This integrated approach can significantly maximize the throughput and minimize the BLER, offering a good solution for enhancing communication security in wireless communication systems. © 2014 IEEE.

关键词： Jamming

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Active pixel image sensor array for dual vision using large-area bilayer WS_(2)

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InfoMat 2024年第4期6卷 68-82页

作者： Arindam Bala Mayuri Sritharan Na Liu Muhammad Naqi Anamika Sen Gyuchull Han Hyun Yeol Rho Youngki Yoon Sunkook Kim School of Advanced Materials Science and Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Waterloo Institute for Nanotechnology(WIN) University of WaterlooWaterlooOntarioCanada Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioCanada

Transition metal dichalcogenides(TMDs)are a promising candidate for developing advanced sensors,particularly for day and night vision systems in vehicles,drones,and security *** traditional systems rely on separate sensors for different lighting conditions,TMDs can absorb light across a broad-spectrum *** this study,a dual vision active pixel image sensor array based on bilayer WS2 phototransistors was *** bilayer WS2 film was synthesized using a combined process of radio-frequency sputtering and chemical vapor *** WS2-based thin-film transistors(TFTs)exhibit high average mobility,excellent Ion/Ioff,and uniform electrical *** optoelectronic properties of the TFTs array exhibited consistent behavior and can detect visible to near-infrared light with the highest responsivity of 1821 A W1(at a wavelength of 405 nm)owing to the photogating ***,red,green,blue,and near-infrared image sensing capabilities of active pixel image sensor array utilizing light stencil projection were *** proposed image sensor array utilizing WS2 phototransistors has the potential to revolutionize the field of vision sensing,which could lead to a range of new opportunities in various applications,including night vision,pedestrian detection,various surveillance,and security systems.

关键词： dual vision image sensors infrared wavelength detection phototransistors thin-film transistor arrays transition metal dichalcogenides

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