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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Harinandan, R. Mahesh Kumar, N. Pratyush Vamshi, Puram Padma, Chennagiri Rajarao Krishnappa, Krutthika Hirebasur Raghunandan, Jahnavi Rohini Sagar College of Engineering Department of Electronics and Communication Engineering Dayananda Bengaluru560078 India Dayananda Sagar College of Engineering Department of Medical Electronics Engineering Bengaluru560078 India Southern University and A and M College Computer Science Department Baton RougeLA70807 United States

ISBN: (纸本)9798350367461

Anterior Cruciate Ligament (ACL) injuries are common in sports and can have long-term effects on the injured party. They frequently require intensive rehabilitation. The creation, assessment, and proof of concept of an electronic monitoring tool designed to identify and stop ACL injuries are presented in this work. In later stages, we use machine learning algorithms to analyse biomechanical data in real-time, giving users immediate feedback on movement patterns such as slowing down walking pace or prohibiting the user from moving at a certain angle to avoid any sort of injury risk factors. The device makes use of wearable sensors, such as an MPU6050 (accelerometer/gyroscope) sensor and an Electromyography (EMG) sensor. Through a series of laboratory tests and field trials, the effectiveness and usability of the device were assessed, demonstrating its potential to improve athlete performance, prevent injuries, and enhance rehabilitation outcomes. According to the findings, there is hope for reducing the risk of ACL injuries and improving sports training regimens with the use of an electronic monitoring device. © 2024 IEEE.

关键词： Electromyography

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Intelligent Multi-tariff Payment Collection System for Inter-Municipal Buses in the department of Atlántico – Colombia 14th

Intelligent Multi-tariff Payment Collection System for Inter...

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14th International Conference on Intelligent Human computer Interaction, IHCI 2022

作者： Ariza-Colpas, Paola-Patricia Hernandez-Sánchez, Guillermo Serrano-Torné, Guillermo Piñeres-Melo, Marlon Alberto Butt-Aziz, Shariq Morales-Ortega, Roberto-Cesar Department of Computer Science and Electronics Universidad de la Costa CUC Barranquilla080002 Colombia Extreme Technologies Barranquilla080002 Colombia Department of Systems Engineering Universidad del Norte Barranquilla081001 Colombia Department of Computer Science and IT University of Lahore Lahore44000 Pakistan

ISBN: (纸本)9783031271984

In the department of Atlántico-Colombia, inter-municipal transport companies operate that mobilize 325,000 people daily. The nature of inter-municipal transport makes it very difficult for companies and vehicle owners to have real control of the income of each bus because, unlike urban transport, the value of the ticket depends on the place of getting on and off each bus. One of the main motivations of this research is to help solve the problems associated with the management of drivers who usually hire assistants who manually and visually control each passenger’s entry and exit points and, according to this criterion, calculate the amount to be paid. Charge individually. Since there is no certainty of the actual monetary income from the buses, companies and owners charge drivers a fixed daily value (fee). The objective of the platform described in this article is to manage the analysis of economic resources generated in public transport activity. This form of work affects the formality of the transport sector and generates a loss of competitiveness in the department Atlántico – Colombia. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Buses

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Soft,full Wheatstone bridge 3D pressure sensors for cardiovascular monitoring

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npj Flexible Electronics 2024年第1期8卷 910-917页

作者： Yoonseok Park Haiwen Luan Kyeongha Kwon Ted S.Chung Seyong Oh Jae-Young Yoo Gooyoon Chung Junha Kim Suhyeon Kim Sung Soo Kwak Junhwan Choi Hoang-Phuong Phan Seonggwang Yoo Hyoyoung Jeong Jaeho Shin Sang Min Won Hong-Joon Yoon Yei Hwan Jung John A.Rogers Department of Advanced Materials Engineering for Information and Electronics Integrated Education Institute for Frontier Science&Technology(BK21 Four)Kyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea Department of Mechanical and Aerospace Engineering University of California San DiegoLa JollaCA 92093USA School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Department of Mechanical Engineering Columbia UniversityNew YorkNYUSA Division of Electrical Engineering Hanyang University ERICAAnsan 15588Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Biomedical Research Division Korea Institute of Science and TechnologySeoul 02792Republic of Korea Department of Chemical Engineering Dankook UniversityYonginGyeonggi-do 16890Republic of Korea School of Mechanical and Manufacturing Engineering Tyree Institute of Health EngineeringUniversity of New South WalesSydneyNSW 2052Australia Querrey Simpson Institute for Bioelectronics Northwestern University EvanstonEvanstonIL 60208USA Department of Electrical and Computer Engineering University of California DavisDavisCA 95616USA Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-do 16419Republic of Korea Department of Electronic Engineering Gachon UniversitySeongnamsiGyeonggi-do 13120Republic of Korea Department of Electronic Engineering Hanyang UniversitySeoulRepublic of Korea Department of Materials Science and Engineering Biomedical EngineeringNeurological SurgeryChemistryMechanical EngineeringElectrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical SchoolCenter for Bio-Integrated ElectronicsNorthwestern University EvanstonEvanstonIL 60208USA

Variations in parameters associated with the ambient environment can introduce noise in soft,body-worn *** example,many piezoresistive pressure sensors exhibit a high degree of sensitivity to fluctuations in temperature,thereby requiring active compensation *** research presented here addresses this challenge with a multilayered 3D microsystem design that integrates four piezoresistive sensors in a full-Wheatstone bridge *** optimized layout of the sensors relative to the neutral mechanical plane leads to both an insensitivity to temperature and an increased sensitivity to pressure,relative to previously reported devices that rely on similar operating *** this 3D pressure sensor into a soft,flexible electronics platform yields a system capable of real-time,wireless measurements from the surface of the *** above the radial and carotid arteries yields high-quality waveforms associated with pulsatile blood flow,with quantitative correlations to blood *** results establish the materials and engineering aspects of a technology with broad potential in remote health monitoring.

关键词： Wheat bridge thereby

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TemporalSwin-FPN Net: A Novel Pipeline for Metadata-Driven Sequence Classification in Camera Trap Imagery

TemporalSwin-FPN Net: A Novel Pipeline for Metadata-Driven S...

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Sameeruddin Muhammad Wei Xiang Scott Mann Kang Han Supriya Nair Department of Computer Science & IT La Trobe University Melbourne Australia OutofBox Solutions Tech Pty Ltd Melbourne Australia

ISBN: (数字)9798350379037

ISBN: (纸本)9798350379044

In wildlife conservation, camera traps generate a significant volume of data that requires extensive manual analysis to extract insights, particularly for species identification. Existing tools and methods for analysing camera trap data typically classify images individually, while the devices are configured to capture multiple pictures in burst mode, often accompanied by metadata. In this paper, we introduce a novel metadata-driven pipeline based on the enhanced Swin Transformer architecture, named TemporalSwin-FPN Net, which utilises metadata to improve classification through a sequential analysis pipeline. This approach shifts the focus from analysing individual snapshots to sequences of images, thereby enriching the architecture with more comprehensive data for species classification. TemporalSwin-FPN Net has achieved a remarkable accuracy of 99.7% on the Australian camera trap dataset, and consistently outperformed the baseline models with 94.89% and 93.32% on the Snapshot Safari dataset for Camdeboo and Mountain Zebra projects, surpassing them by 9.62% and 8.54%. Moreover, integrating the TemporalSwin-FPN Net into our proposed pipeline has significantly reduced the end-to-end processing time for a test dataset of 12,922 images, from 10 minutes 54 seconds to just 6 minutes 41 seconds, thereby substantially enhancing data processing efficiency.

关键词： Sequential analysis Accuracy Pipelines Wildlife Metadata Cameras Transformers Stakeholders Reliability Monitoring

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Characterization of Vertical Wind Speed Profiles Based on Ward's Agglomerative Clustering Algorithm

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1437-1449页

作者： M.C.Bueso A.Molina-García A.P.Ramallo-González A.Fernández-Guillamón Department of Applied Mathematics and Statistics Universidad Politécnica de Cartagena30202 CartagenaSpain Department of Automatics Electrical Engineering and Electronic TechnologyUniversidad Politécnica de Cartagena30202 CartagenaSpain Department of Information and Communications Engineering Computer Science FacultyUniversity of Murcia30100 MurciaSpain Universidad de Castilla La-Mancha Campus Universitario02071 AlbaceteSpain

Wind turbine blades have been constantly increasing since wind energy becomes a popular renewable energy source to generate electricity. Therefore, the wind sector requires a more efficient and representative characterization of vertical wind speed profiles to assess the potential for a wind power plant site. This paper proposes an alternative characterization of vertical wind speed profiles based on Ward's agglomerative clustering algorithm, including both wind speed module and direction data. This approach gives a more accurate incoming wind speed variation around the rotor swept area, and subsequently, provides a more realistic and complete wind speed vector characterization for vertical profiles. Real wind database collected for 2018 in the Forschungsplattformen in Nordund Ostsee(FINO) research platform is used to assess the methodology. A preliminary pre-processing stage is proposed to select the appropriated number of heights and remove missing or incomplete data. Finally, two locations and four heights are selected, and 561588 wind data are characterized. Results and discussion are also included in this paper. The methodology can be applied to other wind database and locations to characterize vertical wind speed profiles and identify the most likely wind data vector patterns.

关键词： Clustering algorithm wind speed data management power generation

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A New Index based on Power Splitting Indices for Predicting Proper Time of Controlled Islanding

A New Index based on Power Splitting Indices for Predicting ...

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2023 IEEE Texas Power and Energy Conference, TPEC 2023

作者： Davarikia, Hamzeh Znidi, Faycal Barati, Masoud Rathore, Heena McNeese State University Department of Electrical Engineering Lake CharlesLA United States Texas A&M Uuniversity Department of Electrical Engineering TexarkanaTX United States University of Pittsburgh Department of Electrical & Computer Engineering PittsburghPA United States Texas State University Department of Computer Science San MarcosTX United States

ISBN: (纸本)9781665490719

In the event of large disturbances, the practice of controlled islanding is used as a last resort to prevent cascading outages. The application of the strategy at the right time is crucial to maintaining system security. A controlled islanding strategy may be deployed efficiently at the right time by predicting the time of uncontrolled system splitting. The purpose of this study is to predict the appropriate islanding time to prevent catastrophic blackout and uncontrolled islanding based on existing relationships between coherent generator groups. A new instability index is derived from the proximity of inter-area oscillations to power splitting indices. Power splitting indices are derived using synchronization coefficients, which recognize the conditions in the system that warrant controlled islanding. The critical values of indices are calculated in offline mode using simulation data from IEEE 39-Buses, and their online performance is evaluated following a controlled islanding strategy. Through the introduction of these indices, system degradation can be effectively evaluated, and blackouts can be predicted early and prevented by controlled islanding at the right time. © 2023 IEEE.

关键词： Forecasting

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Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicular Edge Computing 24th

Blockchain-Empowered Resource Allocation and Data Security ...

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24th International Conference on Web Information Systems engineering, WISE 2023

作者： Wang, Maojie Han, Shaodong Chen, Guihong Yin, Jiao Cao, Jinli School of Cyber Security Guangdong Polytechnic Normal University Guangzhou510635 China Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia

ISBN: (纸本)9789819972531

Vehicular networking technology is advancing rapidly, and one promising area of research is blockchain-based vehicular edge computing to enhance resource allocation and data security. This paper aims to optimize resource allocation and data security in vehicular edge computing by leveraging blockchain technology, thereby improving the overall system efficiency and reliability. By integrating the computational, storage, and communication capabilities of vehicles with blockchain, efficient utilization of edge computing and fair resource allocation are achieved. Additionally, data encryption techniques are introduced to ensure data security and privacy protection. Experimental results demonstrate that the system can automatically identify and allocate the most suitable edge computing nodes, thereby enhancing the responsiveness and quality of computational tasks. The blockchain-based vehicular edge offloading system not only optimizes the performance of vehicular networking systems and enhances user experience but also strengthens data security and privacy protection, providing a novel solution for the development of the vehicular networking industry. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Detecting Parkinson's Disease with Prediction: A Novel SVM Approach 1

Detecting Parkinson's Disease with Prediction: A Novel SVM A...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Krishnappa, Krutthika Hirebasur Shashidhar, R. Shashank, M.P. Roopa, M. Southern University and A&m College Department of Computer Science Baton RougeLA United States Jss Science and Technology University Department of Electronics and Communication Engineering Mysuru India Dayananada Sagar College of Engineering Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350316469

In recent years, the prevalence of neurological diseases has been on the rise due to an increasing population and aging. Conditions like Parkinson's disease, stroke, cerebral palsy, and others often lead to dysarthria among patients. Detecting and treating Parkinson's disease promptly is crucial as it can pose challenges to managing the disease's progression and have adverse effects on a patient's mental and physical well-being when symptoms worsen. Previous research has been predominantly using the concept of machine learning for Parkinson's exposure. This study introduces a novel integrated Support Vector Machine archetypal for detecting the disease by gathering data, organizing it followed by training and testing, finally assessing its performance thereby decreasing the causalities. The experimental findings indicate the use of SVM model proposed in the research achieves an accurateness rate of 87 percentages and f1-score of 0.87%. © 2023 IEEE.

关键词： deep learning machine learning Parkinson infection SVM

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Evolutional Codes: Novel Efficient Graph Data Representation for Mobile Edge Computing

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IEEE Transactions on Network science and engineering 2024年第1期11卷 1387-1397页

作者： Sun, Elaine Y.-N. Wu, Hsiao-Chun Huang, Scott C.-H. Kuan, Yen-Cheng Yung, Chi National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Chungli32003 Taiwan International College of Semiconductor Technology Hsinchu30010 Taiwan

To transmit big graph data emerging from prevalent social networks and biological networks over mobile devices has become challenging nowadays. Since graphs are usually represented by the associated adjacency matrices or graph data structures, dynamic node (vertex) re-ordering to reflect the nodes' real relations (for example, spatial or structural relations) is desirable in practice but impossible for these two existing graph-representation methods. lately, we proposed a novel evolutional coding technique, which can restructure graph data dynamically, flexibly, and efficiently for transmission among mobile devices. Memory efficiency, in terms of number of memory storage units, is a crucial performance measure for mobile edge computing. To select the optimal graph-representation strategy for arbitrary graph data, we define a new graph-taxonomy metric dependent on the edge density (edges per node) in this work. According to our newly defined graph-taxonomy metric, one can choose the optimal graph-representation solution among the three aforementioned methods in terms of required memory-storage space for any application. Pertinent theorems and proofs for the underlying comparative studies on graph representation are presented in this article. © 2013 IEEE.

关键词： Digital storage

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Scalable Video Streaming Solutions Using Federated Learning

Scalable Video Streaming Solutions Using Federated Learning

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International Conference on Smart Communications and Networking (SmartNets)

作者： Mahmoud Darwich Kasem Khalil Magdy Bayoumi Department of Mathematics and Computer Science University of Mount Union Alliance OH Department of Electrical and Computer Engineering University of Mississippi University MS Department of Electrical and Computer Engineering University of Louisiana at Lafayette LA

ISBN: (数字)9798350385328

ISBN: (纸本)9798350385335

The proliferation of video streaming services demands scalable solutions that can adapt to diverse user requirements and network conditions while maintaining privacy and efficiency. This research explores the application of Federated Learning (FL) as a paradigm to address these challenges. We propose a novel FL-based framework for scalable video streaming, focusing on optimizing streaming quality and bandwidth utilization across heterogeneous devices and networks. Our framework leverages decentralized data processing and model training across multiple nodes, reducing the need for centralized data collection and thereby enhancing privacy. We introduce an adaptive algorithm within the FL framework that dynamically adjusts streaming parameters based on user context, network conditions, and device capabilities. This approach ensures optimal video quality and efficient bandwidth usage without compromising user privacy. To validate the efficacy of our proposed solution, we conducted extensive experiments using a simulated environment that mimics real-world streaming scenarios with varying network conditions and device types. The results demonstrate a significant improvement in streaming efficiency and quality. Specifically, our FL-based framework achieved a 25% reduction in bandwidth usage compared to traditional streaming methods, while maintaining or enhancing video quality. Additionally, the user experience, measured through Quality of Experience (QoE) metrics, showed an average improvement of 18%, indicating not only a more efficient but also a more satisfactory streaming experience for users.

关键词： Measurement Privacy Federated learning Bit rate Bandwidth Streaming media User experience

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