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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Fabiani, Linda Schlecht, Sebastian J. Elvander, Filip Aalto University Dept. of Information and Communications Engineering Finland Friedrich-Alexander-Universität Erlangen-Nürnberg Dept. of Electrical and Computer Engineering Germany

ISBN: (纸本)9798350354058

In audio signal processing, having an effective metric for comparing audio data is essential to ensure an accurate understanding of sound properties and attributes. In this work, we formulate two novel approaches for measuring the similarity between audio signals in the time-frequency domain, taking advantage of principles from classical optimal transport problems and sliced Wasserstein distances. Using optimal transport to construct the metric allows for a more robust signal content comparison, considering not only the signals' individual elements but also the global distribution in the signal space. Additionally, the sliced Wasserstein methods expand the use of the distances to high dimensional problems. By integrating both time and frequency aspects into our metrics, we aim for a more comprehensive comparison that can better handle various types of signal distortions. Results show promising behavior in accurately measuring distances for increasing signal differences and avoiding the presence of local minima in the loss curves. © 2024 IEEE.

关键词： Audio signal processing

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Online Transit Entanglement Routing in Quantum Networks: Architecture Design and Optimization

Online Transit Entanglement Routing in Quantum Networks: Arc...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ho, Wan-Ting Fang, Shing-Yan Hsieh, Wei-Chia Cheni, Li-Feng Kuo, Jian-Jhih Tsai, Ming-Jer National Tsing Hua University Dept. of Computer Science Hsinchu Taiwan National Chung Cheng University Dept. of Computer Science and Information Engineering Chiayi Taiwan

ISBN: (纸本)9798350351255

Quantum networks (QNs) gradually gain significant attention due to their higher security compared with classical networks. Conventional approaches in QN routing often aggregate multiple requests into a batch before determining their routing paths. However, this approach may overlook the limited lifetime of qubits, resulting in critical decoherence. In this paper, we present a new online entanglement routing architecture with an online optimization problem and propose a novel [1, O(log |V|)]-competitive algorithm supporting online requests with admission control, aiming to maximize the number of admitted requests. Finally, extensive simulation results show that our algorithm can outperform the existing approaches by up to 98%. © 2024 IEEE.

关键词： Quantum entanglement

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Recognition of Wh-Question Sign Gestures in Video Streams using an Attention Driven C3D-BiLSTM Network 2

Recognition of Wh-Question Sign Gestures in Video Streams us...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Dey, Arnab Biswas, Samit Le, Dac-Nhuong Dept. of Computer Science and Technology Indian Institute of Engineering Science and Technology Howrah Shibpur711103 India Faculty of Information Technology Haiphong University Haiphong180000 Viet Nam

Human sign language is a visual and gestural means of communication used by people with hearing impairments to interact with others. It has the potential to enable interaction between individuals who struggle with verbal communication and those who lack the essential proficiency to comprehend sign language. Wh-questions constitute a substantial portion of daily sign language interactions. Automatic recognition of Wh-question words in sign language, encompassing interrogative words, has received limited attention in gesture recognition. In this context, a novel dataset named the American Question Sign Video dataset (AQSVd) has been introduced as a significant contribution. Recognizing Wh-question signs in video streams empowers individuals to effectively convey messages through hand movements and gestures, fostering inclusivity and accessibility in communication for deaf and hearing-impaired individuals. The paper proposes a Deep Convolutional-3D BiLSTM Multi-head Attention network for recognizing American Wh-Question word sign gestures in video streams. Incorporating Multi-head attention in the proposed model enhances its ability to capture intricate spatial and temporal features, essential for accurate gesture recognition. The proposed model is thoroughly evaluated across a range of datasets, such as INCLUDE50, WLASL-100, and our AQSVd dataset, achieving remarkable results. Specifically, our model demonstrated an outstanding 98.91% validation accuracy on the AQSVd dataset. The C3D-BiLSTM MHAttention model outperforms other state-of-the-art models, demonstrating its superiority in sign language recognition tasks. The proposed dataset and C3D-BiLSTM Multi-head Attention model contribute significantly to this field, offering potential benefits in education, human-robot interaction, and overall communication for the hearing-impaired community. © 2024 Elsevier B.V.. All rights reserved.

关键词： Gesture recognition

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Prediction of Cyclone with Metrological Factors using Gradient Boosting Algorithm 4

Prediction of Cyclone with Metrological Factors using Gradie...

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4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Durai Arumugam, S.S.L. Praveenkumar, R. Shreya, P. Selvakumar, J. Easwari Engineering College Dept. of Information Technology Chennai India Easwari Engineering College Dept. of Electronics and Communication Engineering Chennai India Sri Ramakrishna Engineering College Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350300093

Innovations in computer vision and satellite imaging technologies have made fully automatic weather forecasting a reality. The cyclone prediction system is developed with the goal of reducing both natural disasters and human casualties. Machine Learning object recognition system is created to pinpoint the cyclone, which contains more information about the storm's activity. This is crucial work because it pinpoints the exact spot where the cyclone's formation. The accuracy of cyclone forecasts from many machine learning and deep learning models is 86%-95% or higher, while the accuracy of cyclone eye detection is 87% or higher from the same models. The impressive findings show that the experiment can surpass both established methods and previous attempts. © 2023 IEEE.

关键词： Weather forecasting

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On the Role of ANN on the Estimation of Payload Inertia in Parallel Kinematic Machine 3

On the Role of ANN on the Estimation of Payload Inertia in P...

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3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Fuentes, José Alfonso Farías Giuletti, Nicola Carnevale, Marco Giberti, Hermes Università di Pavia Dept. Electrical Computer and Biomedical Engineering Pavia Italy Università di Pavia Dept. Industrial and Information Engineering Pavia Italy

ISBN: (纸本)9798350378009

In the robotic field, accurately estimating the inertial parameters of a robot payload is essential for improving path-following precision in model-based robot control. Nowadays, there are two main approaches to address this problem. One approach involves using direct measurement of the interaction between the robot End-Effector and the payload in terms of motions and exchanged forces-torques. The other approach involves a standard dynamic robot identification problem, considering the payload as an extension of the last robot link. Several of these techniques have been tested and consolidated for serial robots. However, results obtained for the estimation using Parallel Kinematic Machines have been less accurate than those using serial robots, especially when no direct measurement is considered, due to the complexity of their kinematic chain and the greater impact of uncertainties in their geometrical and dynamic parameters. The purpose of this work is to evaluate the performance of an approach for estimating the inertial properties of the payload using a trained data-driven model, namely an Artificial Neural Network (ANN). This model takes as input the same information available to the machine when direct measurements are made (i.e., positions and forces exchanged between the End-Effector and the payload) and returns as output the inertia tensor and center of mass of the payload. The developed method is validated and compared with standard model-based approaches (e.g., Least Square Method based on the Newton-Euler equations). This work is the first step towards developing a novel approach for estimating the inertial properties of the robot payload using data-driven models with the inputs of the indirect method (i.e., actuator's motion and torque), in order to use as few sensors as possible. © 2024 IEEE.

关键词： Euler equations

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Enhancing Power Grid Resilience: Advanced Strategies for Detecting and Analyzing Faults in Three-Phase Transmission Lines

Enhancing Power Grid Resilience: Advanced Strategies for Det...

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2024 IEEE International Conference on information technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Ahmed, Khandakar Rabbi Shayer, Khandokar Shadman Shuvo, Jahidul Islam Haque, F.M. Mahmudul Salam, Towfika Miraz, Shafiun Noman, Abdullah Al Sobuj, Md. Shohanur Islam Arafat, Md. Yaqub Rial, Md Istiak Hasan Miyan Research Institute International University of Business Agriculture and Technology Uttara Model Town Dhaka Bangladesh Dept. of Mechatronics Engineering Kazla Rajshahi6204 Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Jahangirnagar University Dept. of Institute of Information Technology Saver Dhaka1342 Bangladesh Hajee Mohammad Danesh Science and Technology University Dept. of Electrical and Electronic Engineering Dhaka Bangladesh International University of Business Agriculture and Technology Dept. of Mechanical Engineering Dhaka Bangladesh Dept. of Computer Science and Engineering Andhra Pradesh Kakinada533291 India

ISBN: (纸本)9798350382693

Power system fault analysis is a process that establishes the bus voltages and line currents when various fault types occur. Three-phase balanced faults and unbalanced faults are two categories of power system faults. Single line-to-ground, line-to-line, and double line-to-ground faults are three different types of unbalanced faults that can occur on transmission lines for power systems. Fault analysis is used to choose and set the proper protective devices and switchgear. Determining the bus voltages and line currents is critical while investigating power system issues. Numerous mathematical calculation techniques are shown in the process, which is challenging to do by hand. The calculation can be performed quickly on a computer using a Simulink created using MATLAB. However, an error occurs when inverting an extensive bus system's Y-bus to Z-bus in the conventional short circuit study;this paper offers a solution that is solved using 'MATLAB SIMULINK' to reduce error. © 2024 IEEE.

关键词： Power system analysis

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Securing of Cloud Storage Data Using Hybrid AES-ECC Cryptographic Approach

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Journal of Mobile Multimedia 2023年第2期19卷 363-388页

作者： Kumar, Sunil Kumar, Dilip Dept. of Computer Science and Engineering National Institute of Technology Jamshedpur India

Internet has revolutionized the world in a way no one could have ever imagined. It paved the way for various different technologies, that have transformed the world exceptionally. Internet enabled cloud technology which provides cost-effective, scalable, on-demand computing resources with little to no downtime. Cloud storage allows its users to store and access private data from anywhere in the world without needing any high-end computing system. Cloud storage isn’t always secure, but that doesn’t imply it isn’t. The security of a data depends on the security policies followed by the provider along with the security of the communication channel via which the data is being sent. Encryption is used to obfuscate the data so that it can only be viewed when correct credentials, known as encryption keys, are provided. Following study proposes an encryption technique using ECC (Elliptic Curve Cryptography) along with AES (Advance Encryption Standard) to provide data confidentiality in an efficient way for securing data on cloud and hence, protect the personal information of user from any adversary. This new method is more effective, and the results are superior as a consequence. © 2022 River Publishers.

关键词： AES asymmetric encryption authentication blowfish cloud storage security ECC Symmetric encryption

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Human Activity Recognition using ShuffleNetV2 Model

Human Activity Recognition using ShuffleNetV2 Model

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Shanufa Nazrin, P.S. Benifa, J.V. Bibal Anu, K.P. Vijayakumar, Aiswarya Dept. of Computer Science Kerala Thrissur India Indian Institute of Information Technology Dept.of Computer Science and Engineering Kerala kottayam India

ISBN: (纸本)9798350394580

HAR is specified as the crucial task within the field of computer vision and artificial intelligence. Main aim of HAR is to observing and labelling different human activity images of distinct data sources by machines such as computer. HAR has applications in various fields. CNN model is an appropriate model for HAR task, due to their ability to automaticaly acquire relevant spatial features, capture hierarchical representations, and handle input of various sizes and types. So it is utilized for developing HAR model. This model can detect objects and also can classify images. The model contains wide ranging catogories. ShuffleNetV2 is a particular architecture within it, mainly for efficient and lightweight deep learning task. This paper develops an intelligent HAR using ShuffleNetV2 model which acquired an accuracy about 69.52 percentage. © 2023 IEEE.

关键词： HAR Human activity ShuffleNetV2

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A Survey on Blockchain-Based Certificate Authentication System: From Traditional to Digital 4

A Survey on Blockchain-Based Certificate Authentication Syst...

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4th International Conference on Ubiquitous Computing and Intelligent information Systems, ICUIS 2024

作者： Saraswathi, R Vijaya Vasavi Swathi, Meda Venkata Punwatkar, Sakshi Manoj Konduru, Shreya Sami, Mohammed Abdul Vnr Vignana Jyothi Institute of Engineering and Technology Dept. Of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331529635

This research study pertains to the essential problems of certificate authentication within academic organizations. It concentrates on the major issues of forgery and inefficiencies as well as administrative bottlenecks that arise in conventional systems. The usual ways, which are based on one authority organization, are likely to be compromised, move slowly on verification, and have increased overhead costs. Blockchain technology is a distributed way of doing things without a middleman, and thus it is able to improve security, transparency, and the immutability of educational records. The article identifies the shortcomings of the present blockchain-based implementations with the focus on scalability, interoperability with legacy infrastructure, and high transaction costs. In the paper, an experiment on Ethereum-based smart contracts as well as the Secure Hash Algorithm (SHA-256) and InterPlanetary File System (IPFS) technologies shows the potential of these technologies to a certificate validation system by providing cryptographic integrity and, therefore, data storage that cannot be altered. The proposed work introduces a decentralized architecture that uses smart contracts for certificate issuing and verification to some extent. By integrating cryptographic hashing mechanisms, the system provides real-time, verifiable, and immutable credential records, addressing both fraud prevention and operational inefficiencies. © 2024 IEEE.

关键词： Ethereum

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Real-time Human Movement Recognition and Interaction in Virtual Fitness using Image Recognition and Motion Analysis 12

Real-time Human Movement Recognition and Interaction in Virt...

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12th International Conference on Awareness Science and technology, iCAST 2023

作者： Yeh, ChunHsiu Shen, Wei-Cheng Ma, Chi-Wei Yeh, Qiu-Tong Kuo, Chung-Wei Chen, Jong-Shin Dept. of Information Engineering Computer Science Feng Chia University Taichung Taiwan CollegeofComputerScience Jimei University Xiamen China Dept. of Information Communication Engineering ChaoYang University of Technology Taichung Taiwan

ISBN: (纸本)9798350324693

This research focuses on the application of image recognition, motion detection, and artificial intelligence techniques to achieve real-time identification and analysis of human movements in a dynamic manner. The primary goal is to establish a seamless association between captured human movements and corresponding actions performed by virtual avatars. The implementation involves the utilization of image processing methodologies from python's OpenCV and pygame libraries. MediaPipe technology is employed to capture users' images and facilitate accurate detection of specific movement patterns. By calculating the angles between users' limbs and torso, the correctness of certain movements can be assessed. The research is practically developed and applied to a simulated fitness system, where an interactive exercise game platform is devised. The system is characterized by its engaging user interface, enhancing the ease and enjoyment of fitness activities. The seamless integration of interactive virtual avatars and real users within physical activities serves to stimulate greater participation, particularly among the elderly. The amalgamation of image recognition and motion detection technologies presents opportunities for combining fitness and entertainment in diverse life scenarios, offering an enhanced experience of physical exercise and enjoyment. © 2023 IEEE.

关键词： Image recognition

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