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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Kanade, Aditya Sharma, Mansi Muniyandi, Manivannan Indian Institute of Technology Madras Department of Electrical Engineering India Amrita Vishwa Vidyapeetham Amrita School of Computing Coimbatore Department of Computer Science and Engineering India Indian Institute of Technology Madras Department of Applied Mechanics India

ISBN: (纸本)9781728163277

Physical rehabilitation programs frequently begin with a brief stay in the hospital and continue with home-based rehabilitation. Lack of feedback on exercise correctness is a significant issue in home-based rehabilitation. Deep learning-based movement quality assessment (MQA) can assist with home-based rehabilitation by providing the necessary quantitative feedback. However, systems developed for home-based settings must be fast and offer interpretability of the generated assessment. In this paper, we explore an attention-guided transformer-based architecture for MQA. A comparative analysis against the current state-of-the-art methods is undertaken to establish the validity of the proposed model. Further, we show that the proposed model offers significant performance improvement in training and inference time, which is pivotal for any real-time system. Finally, we show that analysis of the attention maps of the proposed model can give critical insights into the decision-making process of the deep-learning model, thus improving the overall interpretability of predicted assessment scores. © 2023 IEEE.

关键词： attention mechanism deep learning Movement Quality Assessment performance score generation transformer

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Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

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Computers, Materials & Continua 2024年第6期79卷 3585-3629页

作者： Imtiaz Ahmad Tariq Hussain Babar Shah Altaf Hussain Iqtidar Ali Farman Ali Institute of Computer Sciences and Information Technology The University of AgriculturePeshawarPakistan School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina College of Technological Innovation Zayed UniversityDubaiUnited Arab Emirates School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063South Korea

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and *** of them is a sensor network with embedded sensors working as the primary nodes,termed Wireless Sensor Networks(WSNs),in which numerous sensors are connected to at least one Base Station(BS).These sensors gather information from the environment and transmit it to a BS or gathering *** have several challenges,including throughput,energy usage,and network lifetime *** strategies have been applied to get over these *** may,therefore,be thought of as the best way to solve such ***,it is crucial to analyze effective Cluster Head(CH)selection to maximize efficiency throughput,extend the network lifetime,and minimize energy *** paper proposed an Accelerated Particle Swarm Optimization(APSO)algorithm based on the Low Energy Adaptive Clustering Hierarchy(LEACH),Neighboring Based Energy Efficient Routing(NBEER),Cooperative Energy Efficient Routing(CEER),and Cooperative Relay Neighboring Based Energy Efficient Routing(CR-NBEER)*** the help of APSO in the implementation of the WSN,the main methodology of this article has taken *** simulation findings in this study demonstrated that the suggested approach uses less energy,with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH,1.003 to 0.0521 for 10 CH,and 0.1734 to 0.0911 for 15 *** sending packets ratio was also raised for all three CH selection scenarios,increasing from 659 to *** number of dead nodes likewise dropped for the given combination,falling between 71 and *** network lifetime was deemed to have risen based on the results found.A hybrid with a few valuable parameters can further improve the suggested APSO-based *** to underwater,WSN can make use of the proposed *** overall results have been evaluated and

关键词： Wireless sensor network cluster head selection low energy adaptive clustering hierarchy accelerated particle swarm optimization

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A Survey of Fault Tolerance in Cloud computing

A Survey of Fault Tolerance in Cloud Computing

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2024 International Symposium of Systems, Advanced Technologies and Knowledge, ISSATK 2024

作者： Elhajjej, Om Kolthoum Alyaoui, Nouha Dardouri, Samia Chabir, Karim Tunisia Higher Institute of Applied Sciences and Technology Computer Science and Telecommunications Department Zarroug Gafsa Tunisia Shaqra University College of Computing and Information Technology Department of Computer Science Saudi Arabia University of Carthage InnoV'COM Laboratory-Sup'Com Tunisia

ISBN: (纸本)9798331540173

This paper is designed to provide a comprehensive overview of the latest developments in fault tolerance methods for cloud computing. Maintaining high availability and reliability of cloud environments requires fault tolerance. This paper explores fault tolerance in the context of cloud computing and discusses recent challenges and innovations in the field. Moreover, it examines the ongoing research efforts to improve fault-tolerance architectures. At the end of the paper, the paper presents system-level metrics that are relevant to fault tolerance. © 2024 IEEE.

关键词： Cloud computing architecture

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Explicating the Exact γCD Value for the Tensor Product of Graphs 9th

Explicating the Exact γCD Value for the Tensor Product of G...

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9th International Conference on Discrete Mathematics and Mathematical Modeling in Digital Era, ICDMMMDE 2023

作者： Praveenkumar, L. Mahadevan, G. Sivagnanam, C. Tyagi, Sanjay K. Department of Mathematics The Gandhigram Rural Institute – Deemed to be University Tamilnadu Gandhigram India Mathematics and Computing Skills Unit University of Technology and Applied Sciences – Sur Sur Oman Department of General Studies Higher College of Technology Fujairah4114 United Arab Emirates

ISBN: (纸本)9789819726394

Let γCD(H) denote the corona domination number (CD-number) of the graph H. The idea of CD-number was first coined by G. Mahadevan et al. in 2021. The CD-number of a graph is the minimum cardinality of a dominating set S with the condition that every vertex in the graph induced by S is either a pendent vertex or support vertices. In this paper, we carry over the study of CD-number to identify the exact value of γCD(Pr⊗Ps), γCD(Cr⊗Cs), γCD(Prc⊗Ps), etc. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Corona domination number Domination number Pendant vertex Support vertex Tensor product

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Social mining for sustainable cities: thematic study of gender-based violence coverage in news articles and domestic violence in relation to COVID-19

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Journal of Ambient Intelligence and Humanized computing 2023年第11期14卷 14631-14642页

作者： Manzoor, Muhammad Asad Hassan, Saeed-Ul Muazzam, Amina Tuarob, Suppawong Nawaz, Raheel Department of Computer Science Information Technology University 346-B Ferozepur Road Lahore Pakistan Department of Computing and Mathematics Manchester Metropolitan University Manchester United Kingdom Department of Applied Psychology Lahore College for Women University Lahore54000 Pakistan Faculty of Information and Communication Technology Mahidol University Salaya Thailand Department of Operations Technology Events and Hospitality Management Manchester Metropolitan University Manchester United Kingdom

We argue that social computing and its diverse applications can contribute to the attainment of sustainable development goals (SDGs)—specifically to the SDGs concerning gender equality and empowerment of all women and girls, and to make cities and human settlements inclusive. To achieve the above goals for the sustainable growth of societies, it is crucial to study gender-based violence (GBV) in a smart city context, which is a common component of violence across socio-economic groups globally. This paper analyzes the nature of news articles reported in English newspapers of Pakistan, India, and the UK—accumulating 12,693 gender-based violence-related news articles. For the qualitative textual analysis, we employ Latent Dirichlet allocation for topic modeling and propose a Doc2Vec based word-embeddings model to classify gender-based violence-related content, called GBV2Vec. Further, by leveraging GBV2Vec, we also build an online tool that analyzes the sensitivity of Gender-based violence-related content from the textual data. We run a case study on GBV concerning COVID-19 by feeding the data collected through Google News API. Finally, we show different news reporting trends and the nature of the gender-based violence committed during the testing times of COVID-19. The approach and the toolkit that this paper proposes will be of great value to decision-makers and human rights activists, given the prompt and coordinated performance against gender-based violence in smart city context—and can contribute to the achievement of SDGs for sustainable growth of human societies. © 2022, Crown.

关键词： COVID-19

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Efficient Vehicle Detection and Classification using YOLO v8 for Real-Time Applications

Efficient Vehicle Detection and Classification using YOLO v8...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Ravichandran, M. Laxmikant, Kumar Muthu, Annamalai Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India University of Technology & Applied Science Department of Electrical and Electronics Engineering Nizwa Oman

ISBN: (纸本)9798350308167

In the realm of real-time applications such as autonomous driving and surveillance, efficient vehicle detection stands as a paramount concern. The revolutionary You Only Look Once (YOLO) framework, renowned for its rapid object recognition, has reshaped this landscape. This study delves into the fusion of real-time vehicle detection and YOLO v8, optimizing its architecture for swift and precise identification. Empirical validation underscores the model's prowess, achieving a remarkable accuracy of 97.9% on mAP50 and 91.3% on mAP50-95. This achievement not only attests to the model's accuracy but also reaffirms its real-time processing capabilities. The implications resonate across transportation safety and urban planning, promising transformative potential. This research underscores the power of YOLO v8 in intelligent object detection, poised to reshape and enhance various domains. © 2023 IEEE.

关键词： mAP50 mAP50-95 Object Detection Vehicle Detection YOLO Framework

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Designing a hybrid neural network framework for real-time anomaly detection in cybersecurity applications

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International Journal of Information technology (Singapore) 2025年 1-7页

作者： Jain, Aaditya Ead, Waleed M. Alshahrani, Mohammed Altamimi, Jawaher Suliman Aklan, Fawaz Rihan, Shaza Dawood College of Computing Sciences and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India Faculty of Computing and Information Al-Baha University Al-Baha Saudi Arabia Faculty of Computers and Artificial Intelligence Beni-Suef University Beni-Suef Egypt Computers Department Applied College Najran University Najran Saudi Arabia Applied College Najran University Najran Saudi Arabia Department of Computer Science Faculty of Applied Science Taiz University Taiz P.O. Box 6803 Taiz Yemen

As cybersecurity is becoming a prominent domain, it is an imperative to provide real-time anomaly detection for early threat detection and to keep networks safe. In this paper, an optimized hybrid neural network-framework is proposed to detect anomalies at several attack vectors with high efficacy. The framework comprises convolutional neural network equipped with long-short term memory (CNN-LSTM) for temporal and spatial representation of data. As the system accommodates new data and keeps on learning, it adjusts itself becoming a significant mean in counteracting against emerging threats with less latency in detection. In order to verify the efficiency and robustness of the proposed framework, a series of real-time simulation is designed using key performance metrics such as detection rate, false alarm rate and processing time. The results show higher improvement in accuracy and speed of anomaly detection, which makes the framework a useful instrument to reinforce cybersecurity defense during real-time scenarios. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2025.

关键词： Anomaly detection Convolutional neural network (CNN) Cybersecurity Hybrid approach Long-short term memory (LSTM)

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Multi-Keyword Graded Exploration in Encrypted Cloud Data for Industries Based on Rc4+ and Forest 1

Multi-Keyword Graded Exploration in Encrypted Cloud Data for...

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1st IEEE International Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Balamurugan, P. Suresh Thangakrishnan, M. Arulkumaran, G. Jayagopalan, Santhosh School of Computing Dept. of Networking and Communications SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Einstein College of Engineering CSE India School of Computing and Information Technology REVA University Bengaluru India British Applied College Department of Computing Umm Al Quwain United Arab Emirates

ISBN: (纸本)9798350345957

The vast amounts of storage space offered by the cloud encourage businesses to store their most sensitive files and data on remote servers accessible over the internet. When comparing a local server and personal computer to a cloud environment, it's clear that many more tasks can be accomplished with the former. Cost, speed, global scalability, productivity, and performance are just a few of the six reasons why cloud services have gained popularity among businesses and consumers alike in recent years. This paper presents the River cypher RC4+ (RCPF) scheme for fast, efficient, and secure multi-keyword search indexing in an encrypted cloud environment. In order to encrypt and decrypt data, the RC4+ algorithm uses a final symmetric secret key that is created by a pseudorandom byte generator. In order to generate an index list for each file in a shorter amount of time, a minimal spanning tree is formed. After that, the encrypted index list is searched by the cloud server, and relevant files are ranked according to the search query. The user's decryption of the encrypted data using the symmetric key behaves as a whole. © 2023 IEEE.

关键词： Cryptography

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INVARIANCE ANALYSIS, SYMMETRY REDUCTION AND CONSERVATION LAWS FOR A BIOLOGICAL POPULATION MODEL IN POROUS MEDIA

arXiv

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arXiv 2024年

作者： Joshi, Urvashi Sharma, Aniruddha Kumar Arora, Rajan Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee India

This research paper talks about using complex mathematical tools to study and figure out the behavior of biological populations in porous media. Porous media offer a unique environment where various factors, including fluid flow and nutrient diffusion, significantly influence population dynamics. The theory of Lie symmetries is used to find inherent symmetries in the governing equation of the population model, helping to find conservation laws and invariant solutions. The derivation and analysis of the optimal system provide insights into the most influential parameters affecting population growth and distribution. Furthermore, the study explores the construction of invariant solutions, which aid in characterizing long-term population behavior. The article concludes with the non-linear self-adjointness property and conservation laws for the model. Copyright © 2024, The Authors. All rights reserved.

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On the System Performance of Mobile Edge computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 668-685页

作者： Van-Truong Truong Van Nhan Vo Dac-Binh Ha Chakchai So-In the Faculty of Electrical-Electronic Engineering Duy Tan University the Institute of Research and Development Duy Tan University the Faculty of Information Technology Duy Tan University IEEE the Applied Network Technology(ANT)Laboratory Department of Computer ScienceCollege of ComputingKhon Kaen University

In this paper,we study the system performance of mobile edge computing(MEC)wireless sensor networks(WSNs)using a multiantenna access point(AP)and two sensor clusters based on uplink nonorthogonal multiple access(NOMA).Due to limited computation and energy resources,the cluster heads(CHs)offload their tasks to a multiantenna AP over Nakagami-m *** proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining(SC)or maximal ratio combining(MRC)and each cluster selects a CH to participate in the communication process by employing the sensor node(SN)*** derive the closed-form exact expressions of the successful computation probability(SCP)to evaluate the system performance with the latency and energy consumption constraints of the considered *** results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas,number of SNs in each cluster,task length,working frequency,offloading ratio,and transmit power ***,to determine the optimal resource parameters,i.e.,the offloading ratio,power allocation of the two CHs,and MEC AP resources,we proposed two algorithms to achieve the best system *** approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar *** use Monte Carlo simulations to confirm the validity of our analysis.

关键词： Mobile edge computing(MEC) Nakagami-m fading offloading selection combining(SC)/maximal ratio combining(MRC) successful computation probability(SCP) uplink nonortho-gonal multiple access(NOMA) wireless sensor networks(WSNs)

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