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2023 International Conference on Recent Advances in science and engineering Technology, ICRASET 2023

作者： Kumar, E. S. R. Ravi Babu Chandolu, Suresh Kumar, K. Parish Venkata Rao, Muvva Venkateswara Muralidhar, V. Nagarjuna, Kaja Vellela, Sai Srinivas V. R. Siddhartha Engineering College Dept. of Mathematics Vijayawada India Dhanekula Institute of Engineering and Technology Dept. of Cse Vijayawada India V. R. Siddhartha Engineering College Dept. of Computer Applications Vijayawada India Nri Institute of Technology Dept. of Cse Vijayawada India VVIT-Nambur Dept. of Csm Guntur India Stanley College of Engineering & Technology for Women Dept. of Information Technology Hyderabad India Chalapathi Institute of Technology Dept. of CSE-Data Science Guntur India

ISBN: (纸本)9798350306927

Because of their ability to be deployed in open environments with a high degree of flexibility and mobility, Unmanned Aerial Vehicles (UAVs) have garnered a considerable amount of attention in both military and civilian applications with the goals of enabling ubiquitous connectivity and fostering dynamic communications. The challenge is caused by aspects other than mobile ad hoc networks (MANET), specifically aerial mobility in three-dimensional space and frequently shifting topology. One and the same node in the UAV network is responsible for all three functions. The communication path is typically made up of multiple hops, and the routing decision has a substantial impact on how well the network performs. When choosing the most effective routing system, performance analysis should receive a significant amount of attention and effort. As a result of this impetus. The COAER-UAVC approach that has been given creates efficient communication pathways between the UAVs. To a large extent, it is predicated on the behaviors of Coot in their natural environments, such as fighting and hunting iguanas and evading predators. In addition, the COAER-UAVC technique that has been provided places an emphasis on the development of fitness functions with the goal of minimizing both energy consumption and communication delay. In order to show the optimum performance of the COAER-UAVC system, a diverse collection of simulations have to be carried out. The results of the experiments demonstrated that using the COAER-UAVC strategy resulted in significantly enhanced performance in comparison to using other methods. © 2023 IEEE.

关键词： Routing protocols

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EMGTTL: Transformers-Based Transfer Learning for Classification of ADL using Raw Surface EMG Signals

arXiv

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arXiv 2024年

作者： Kareemulla, Ashraf Ali Sanodiya, Rakesh Kumar Turlapaty, Anish Chand Naidu, Surya Dept. of Computer Science and Engineering Indian Institute of Information Technology Sri City India Dept. of Electronics and Communication Engineering Indian Institute of Information Technology Sri City India

Surface Electromyography (sEMG) is widely studied for its applications in rehabilitation, prosthetics, robotic arm control, and human-machine interaction. However, classifying Activities of Daily Living (ADL) using sEMG signals often requires extensive feature extraction, which can be time-consuming and energy-intensive. The objective of this study is stated as follows. Given sEMG datasets, such as electromyography analysis of human activity databases (DB1 and DB4), with multi-channel signals corresponding to ADL, is it possible to determine the ADL categories without explicit feature extraction from sEMG signals. Further is it possible to learn across the datasets to improve the classification performances. A classification framework, named EMGTTL, is developed that uses transformers for classification of ADL and the performance is enhanced by cross-data transfer learning. The methodology is implemented on EMAHA-DB1 and EMAHA-DB4. Experiments have shown that the transformer architecture achieved 64.47% accuracy for DB1 and 68.82% for DB4. Further, using transfer learning, the accuracy improved to 66.75% for DB1 (pre-trained on DB4) and 71.04% for DB4 (pre-trained on DB1). © 2024, CC BY.

关键词： Adversarial machine learning

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Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals

Relating Muscle Activity and Mouse Sensitivity in FPS Game P...

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International Conference on Biomedical engineering (IBIOMED)

作者： Vaibhav Prajapati Anish C. Turlapaty Himangshu Sarma Mrinmoy Ghorai Dept. of Electronics and Communication Engineering Indian Institute of Information Technology Sri City India Dept. of Computer Science and Engineering Indian Institute of Information Technology Sri City India

ISBN: (数字)9798350389265

ISBN: (纸本)9798350389272

In the domain of first-person shooter (FPS) gaming, mouse sensitivity is crucial for performance. This paper presents an analysis showing the correlation between specific muscle activity and mouse movement. We analyzed mouse movements from twelve subjects with varying sensitivity levels. A new dataset electromyography analysis of human activity database 8 (EMAHA-DB8), is introduced which involved four mouse designs and two game modes: Medium (normal movement) and Hard (aggressive movement). Sensitivity settings were standardized using effective dots per inch (eDPI), calculated as Mouse DPI multiplied by in-game sensitivity. Hand muscle activity was measured using five Noraxon Ultium wireless surface electromyography (sEMG) sensors with Ag/AgCl electrodes. Various regression models, including Random Forest, Support Vector Regressor, K-Nearest Neighbors Regressor, MLP Regressor, and Gradient Boost Regressor, were used to predict eDPI from muscle movement patterns. Sequential feature selection identified the top ten features, highlighting the most significant muscles for predicting sensitivity. The results demonstrate that the Extensor Carpi Radialis (ECR) is the most active muscle, followed by the Extensor Digitorum (ED), while playing the chosen FPS game. These findings give insights for ergonomic and personalized equipment design to enhance gaming experience and performance.

关键词： Sensitivity Biological system modeling Games Muscles Predictive models Nearest neighbor methods Electromyography Data models Vectors Random forests

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ElHa Net: A Pattern Recognition Neural Network

ElHa Net: A Pattern Recognition Neural Network

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Elsadig Ahmed Mohamed Babiker Hanan Hassan Ali Adlan Dept. of Computer Science College of Computer Engineering and Science Prince Sattam Bin Abdulaziz University Kharj KSA Dept. of Computer Science Faculty of Mathematical Sciences Uof K Dept. of Computer Science College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh KSA

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

Neural Networks are the state-of-the-art models that derive intelligent systems. Generalization of the neural network model is a judge of how well an architecture mimic human intelligence. Self-extraction neural networks become the dominant neural networks, especially in autonomous systems such as intelligent robotics, autonomous vehicles, ⃛ etc. This paper presents a neural network based on distance measure, ElHaNet Neural Network. ElHaNet network is a self-extraction neural network and is capable of pattern recognition. ElHaNet architecture composed of an extraction phase and a classification phase. Neurons in the extraction network capture patterns in the presented input. The classification network performs on the input patterns to be classified according to the problem in hand. The developed architecture is bench marked against well-known architectures for hand written digit recognition. The performance of the network is found to compete favorably with state-of-the-art models in the literature.

关键词： Hands Human intelligence Neurons Pattern recognition Biological neural networks Robots Autonomous vehicles

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A Novel Cloud-Based Framework for Leaf Disease Detection and Classification: Enhancing Plant Health Using Android Applications 3

A Novel Cloud-Based Framework for Leaf Disease Detection and...

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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Kiran, Ajmeera Namdev, Arpit Chandan, Radha Raman Waghmare, Pravin B. Dhabliya, Dharmesh Gupta, Ankur Mlr Institute of Technology Dept. of Cse Hyderabad Telangana Dundigal India University Institute of Technology Rgpv Dept. of It MP Bhopal India School of Management Sciences Dept. of Computer Science UP Varanasi India Acharya Shrimannarayan Polytechnic Msbte Dept. of Civil Engineering Mumbai India Vishwakarma Institute of Information Technology Dept. of It Maharashtra Pune India Vaish College of Engineering Dept. of Cse Haryana Rohtak India

ISBN: (纸本)9798350330724

The difficult challenge of identifying the leaf disease in agriculture is employed to stop the dangerous epidemic. The majority of plant diseases are brought on by fungus, bacteria, and viruses, with the fungi often attached to the plant's reproductive organs. As a result, bacteria have simpler life cycles and are more dangerous than fungi. Similar to bacteria, viruses are microscopic particles that contain genetic information and protein but no additional protein. Therefore, it is crucial to spot illness in plant leaves. Therefore, the goal of this research is to identify leaf disease in a cloudy environment. The use of smartphones for many applications has increased recently. A brand-new operating system called Android is freely accessible in the Android Market. Thus, this study uses an Android application to develop a cloud-based illness categorization system. © 2023 IEEE.

关键词： Agriculture

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Reducing Client-Side Cost in Secure Inner Product Evaluations

Reducing Client-Side Cost in Secure Inner Product Evaluation...

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International Conference on information Networking

作者： Changhee Hahn Dongyoung Koo Junbeom Hur dept. Electrical and Information Engineering Seoul National University of Science and Technology South Korea dept. Convergence Security Hansung University South Korea dept. Computer Science and Engineering Korea University South Korea

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

In the era of ubiquitous data collection and analysis, preserving privacy while utilizing data, such as inner product evaluations, poses a significant challenge. One such method is inner product functional encryption (IPFE), which enables the computation of inner products on encrypted vectors without exposing the vectors themselves. However, the computational intensity of IPFE decryption poses challenges, particularly for resource-limited client devices and high-dimensional vectors. To facilitate partial decryption, prior IPFE schemes require the client to derive a partial decryption key from an assigned secret key, incurring computation costs linear to the vector dimension. In this paper, we provide a framework for the challenges of IPFE, enabling efficient decryption outsourcing, maintaining data privacy, and facilitating key generation outsourcing in IPFE schemes. In the proposed framework, outsourced decryption using a partial decryption key generates a masked plaintext that only the client can unmask. Furthermore, the process of deriving the partial decryption key can be fully outsourced, thereby ensuring that the client’s computational burden remains constant.

关键词： Data privacy Costs Data collection Vectors Outsourcing Encryption Computational efficiency

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Implementation of an AI-based Competitive Cheerleading Coaching Assistant System

Implementation of an AI-based Competitive Cheerleading Coach...

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2023 IET International Conference on engineering Technologies and Applications, ICETA 2023

作者： Yang, Chun-Hung Tu, Jiun-Yu Wu, Dong-Shing Zhuang, Ya-Ting Tsai, Pei-Ying Hsu, Chen-Kai Dept. of Electronic Engineering Southern Taiwan University of Science and Technology No.1 Nantai St. Yungkang Dist. Tainan City710301 Taiwan Dept. of Computer Science and Information Engineering Southern Taiwan University of Science and Technology No.1 Nantai St. Yungkang Dist. Tainan City710301 Taiwan

ISBN: (纸本)9781839539848

Competitive cheerleading is a highly complex and intense sport characterized by intricate motions. The complexity and high intensity of the sport often lead to various sports injuries. Therefore, the role of coaches is crucial in the training process of competitive cheerleading. However, due to the insufficient number of coaches, there are inevitably challenges in providing individual attention to all team members during training. To alleviate the workload of coaches and enhance the effectiveness of self-directed training for team members, this study has developed a cheerleading coach assistant system with artificial intelligence technology. This system demonstrates high judgment accuracy and significantly improves the standardization of basic motions for competitive cheerleaders, reducing the possibility of sports injuries. © The Institution of engineering & Technology 2023.

关键词： Sports

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Smart Sensor Technologies and Its Location-Aware Applications

Smart Sensor Technologies and Its Location-Aware Application...

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2023 IET International Conference on engineering Technologies and Applications, ICETA 2023

作者： Wu, Dong-Shing Tu, Jiun-Yu Yang, Chun-Hung Dept. of Computer Science and Information Engineering Southern Taiwan University of Science and Technology No.1 Nantai St. Yungkang Dist. Tainan City710301 Taiwan Dept. of Electronic Engineering Southern Taiwan University of Science and Technology No.1 Nantai St. Yungkang Dist. Tainan City710301 Taiwan

ISBN: (纸本)9781839539848

Owing to the popularity and miniaturization for the embedded systems, many types of sensors are integrated with the embedded systems as the smart sensors by the electronic manufacturers, and thus the uses can apply the estimation capabilities of smart sensors to perform real-time signal processing, judgment, and control function. This paper introduces a unidirectional localization technology with low-complexity computing in smart sensor nodes. The proposed technology formulates the estimated location of a target as an optimization problem based on the real-time signal estimation, and the problem can be solved in the centralized or decentralized way. The computer simulation results illustrate that in a static localization scenario, the suggested location-aware application exhibits superior estimation accuracy compared to the conventional approach. © The Institution of engineering & Technology 2023.

关键词： Smart sensors

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Edge Node Load Balancing Using Game Theoretic Approaches 5

Edge Node Load Balancing Using Game Theoretic Approaches

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5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Haldar, Rajdeep Rooj, Saptadip Sharma, Neeraj Das, Ritambhar Mandal, Arnab Bandyopadhyay, Anjan Dept. of Information Technology Bhubaneswar India Lovely Professional University School of Computer Science and Engineering Jalandhar India School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798331522100

This paper explores the application of game theoretic approaches to load balancing across edge nodes within distributed computing systems. Focusing on a non-cooperative game model, we aim to enhance system efficiency by strategically optimizing resource allocation and load distribution among autonomous edge nodes. Initial simulations demonstrate that our approach not only addresses the inherent complexities of edge environments but also outperforms traditional load balancing mechanisms in terms of both operational efficiency and system responsiveness. © 2025 IEEE.

关键词： Edge computing

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Near-Optimal UAV Deployment for Delay-Bounded Data Collection in IoT Networks

Near-Optimal UAV Deployment for Delay-Bounded Data Collectio...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Shu-Wei Chang Jian-Jhih Kuo Mong-Jen Kao Bo-Zhong Chen Qian-Jing Wang Dept. of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

The rapid growth of Internet of Things (IoT) applications has spurred the need for efficient data collection mechanisms. Traditional approaches relying on fixed infrastructure have limitations in coverage, scalability, and deployment costs. Unmanned Aerial Vehicles (UAVs) have emerged as a promising alternative due to their mobility and flexibility. In this paper, we aim to minimize the number of UAVs deployed to collect data in IoT networks while considering a delay budget for energy limitation and data freshness. To this end, we propose a novel 3-approximation dynamic-programming-based algorithm called GPUDA to address the challenges of efficient data collection from IoT devices via UAVs for real-world scenarios where the number of UAVs owned by an individual or organization is unlikely to be excessive, improving the best-known approximation ratio of 4. GPUDA is a geometric partition-based method that incorporates data rounding techniques. The experimental results demonstrate that the proposed algorithm requires 35.01% to 58.55% fewer deployed UAVs than the existing algorithms on average.

关键词： Simulation Scalability Heuristic algorithms Switched mode power supplies Organizations Data collection Autonomous aerial vehicles

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