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检索条件"任意字段=11th International Conference on Embedded and Real-Time Computing Systems and Applications"

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time-Domain Heart Sound Classification Using Neural Audio Codecs

Time-Domain Heart Sound Classification Using Neural Audio Co...

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international conference of Advanced Informatics: Concept, theory and Application (ICAICTA)

作者： Ansh Mishra Jia Qi Yip Eng Siong Chng Department of Physics IIT Delhi New Delhi India Interdisciplinary Graduate Programme Nanyang Technological University (NTU) Singapore School of Computer Science and Engineering Nanyang Technological University (NTU) Singapore

ISBN: (数字)9798331520311

ISBN: (纸本)9798331520328

Heart auscultation remains a valuable approach for early detection of valvular heart disease, but its efficacy depends on physician skill. the rise of telehealth services necessitates consideration of heart sound transmission and classification through compressed formats. While neural audio codecs offer impressive compression rates, they may introduce distortions that could impact classification accuracy. We propose a novel approach to perform heart sound classification directly on the continuous representations of the codec, rather than on reconstructed audio. Our method demonstrates good performance on the heart sound classification task while leveraging the encoder of the audio codec, potentially improving robustness and efficiency in telehealth applications. Using the Descript Audio Codec encoder combined with a modified M5 convolutional neural network, our approach achieves a Classification Error Rate of 0.78 on the Yaseen Dataset, outperforming models trained on transmitted audio and comparing favorably with state-of-the-art methods. this performance, coupled with the method's inherent robustness to transmission artifacts, highlights its potential for improving remote cardiac diagnostics in telehealth settings.

关键词： Heart Codecs Error analysis Telemedicine Computational modeling Medical services Robustness real-time systems time-domain analysis Informatics

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11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

引用

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 international conference on Artificial Intelligence applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

the proceedings contain 35 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical Image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling Algorithms for Decision Making;employing Natural Language Processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep Learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic Images;An Intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An Automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI Images;the Use of Robotics in Critical Use Cases: the 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards realizing 5G Implementation;experimentation Scenarios for Machine Learning-Based Resource Management;efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise Distributed Generation Monitoring and real-time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep Learning Based Facial Expressions An

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Open-Ended Coaxial Probe Based Chloride Concentration Prediction in Water Using Machine Learning Algorithms

Open-Ended Coaxial Probe Based Chloride Concentration Predic...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Hanima Kannan C H Veena Venugopal Deepa Gupta Parul Mathur Dhanesh G Kurup Priyanka Mathur Department of Electronics and Communication Engineering RF and Wireless Systems Laboratory Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Physical Science Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India School of Engineering and Applied Science Benette University Greater Noida UP India

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Monitoring chloride levels in water is essential for environmental health, industrial processes, and safe drinking water, as both high and low concentrations can cause harm for living being. this paper presents a novel approach to detecting chloride concentrations using Open-Ended Coaxial Probe (OECP) sensing combined with machine learning algorithms. OECP sensing offers real-time, non-destructive, and precise monitoring, enabling early detection of contaminants. Scattering parameter ( $S$ 11) data across a broad frequency range was collected with varying chloride concentrations in controlled laboratory experiments. thirteen machine learning algorithms were trained to predict chloride concentrations, with different datasets for training and testing to ensure robustness. Among these, CatBoost demonstrated the best performance. After fine tuning and cross-validation, the CatBoost model achieved a test Mean Square Error (MSE) of 0.00627 and Coefficient of Determination (R2) of 0.9936, showcasing its accuracy for applications in water monitoring, corrosion prevention, and safeguarding public health.

关键词： Machine learning algorithms Water quality Predictive models real-time systems Sensors Scattering parameters Probes Public healthcare Tuning Testing

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Flexibility Trading from P2P Networks to Improve the Grid Frequency Response in the Presence of RTEM and MARL-Based AGC systems 11

Flexibility Trading from P2P Networks to Improve the Grid Fr...

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11th IEEE international conference on Power Electronics, Drives and Energy systems, PEDES 2024

作者： Debbarma, Liza Debbarma, Sanjoy Singh, Piyush Pratap National Institute of Technology Department of Electrical Engineering Meghalaya Shillong India

With the gradual shift from conventional units to renewable energy sources (RES), the modern grid is facing diminished frequency regulation (FR) capabilities, making traditional control methods less effective. In response, this paper proposes an advanced multi-agent reinforcement learning (MARL) control strategy for FR in a RES-dominated power system. the system includes a residential microgrid with diverse distributed energy resources engaged in peer-to-peer (P2P) energy trading at the distribution level, while automatic generation control (AGC) and a dynamic real-time energy market (RTEM) coordinate at the transmission level to balance load and generation. the RTEM dispatches energy every five minutes to support the FR process, complementing AGC operations. Following disturbances, the microgrid utilizes demand-side flexibility alongside AGC and RTEM operations to quickly restore system frequency to its steady state. MARL, implemented using the Deep Deterministic Policy Gradient algorithm, is applied to both AGC and microgrid systems. Here, P2P trading is facilitated through a consumer-prosumer contract participation matrix. the results show that flexibility from P2P networks, in conjunction with AGC and RTEM systems, significantly improves grid frequency response. © 2024 IEEE.

关键词： Reinforcement learning

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Stability theory with real Life applications

Stability Theory with Real Life Applications

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international conference on System Modeling & Advancement in Research Trends (SMART)

作者： Rashi Arya Gopal Kumar Gupta Abhinav Saxena Vipin Kumar Department of Mathematics Faculty of Engineering Teerthanker Mahaveer University Moradabad

ISBN: (纸本)9781665487351

Stability theory is widely developed for actual systems. Mathematicians and engineers generally utilize its solutions to practical issues in Electrical Engineering, Electronics, and Mechanical Engineering. this paper aims to present some further practical applications of stability theory. First, we discussed the SEIR model used in this research to show how the disease-free equilibrium was asymptotically stable. the coexistence of the three species are then depicted by three-component model which is asymptotically stable around the positive interior biological equilibrium with two hazardous zooplankton and phytoplankton. In addition to these, it is investigated whether a class of non-linear time-varying control systems has exponential stability, as well as the stability of a logistic model of an isolated population.

关键词： Asymptotic stability Biological system modeling Sociology Control systems Stability analysis Mathematical models Control theory

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Securing UAV Delivery systems with Blockchain and Large Language Models: An Innovative Logistics Solution

Securing UAV Delivery Systems with Blockchain and Large Lang...

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Machine Intelligence theory and applications (MiTA), international conference on

作者： Chengzu Dong Naeem Syed Frank Jiang Rose Elphick-Darling Shiping Chen Jun Zhang Meiqu Lu Xiao Liu School of Information Technology Faculty of Sci Eng & Built Env Deakin University Geelong Australia Centre for Regional and Rural Futures Faculty of Sci Eng & Built Env Deakin University Geelong Australia Data61 CSIRO Sydney Australia Hanyang University ERICA Zhejiang Normal University Melbourne Victoria University Melbourne Australia School of Artificial Intelligence Guangxi Minzu University Nanning China

ISBN: (数字)9798350385670

ISBN: (纸本)9798350385687

In the evolving landscape of logistics and supply chain management, Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution to enhance delivery efficiency and reach. However, the integration of UAVs into mainstream logistics faces significant challenges, including security, data integrity, and scalable customer interaction. this study proposes an innovative framework that leverages blockchain technology and large language models to address these challenges, offering a secure, transparent, and intelligent UAV delivery system. By integrating blockchain, we ensure the immutability and transparency of delivery transactions, enhancing trust in UAV-operated logistics. Concurrently, the employment of large language models facilitates intelligent route optimization, dynamic task allocation, and real-time customer service through natural language processing capabilities. We present a comprehensive analysis of the proposed system’s architecture, security features, and operational efficiency through simulated delivery scenarios. Our findings indicate a notable improvement in delivery times, reduced operational costs, and enhanced customer satisfaction. this research not only contributes to the theoretical understanding of blockchain and AI applications in logistics but also provides a practical roadmap for implementing secure and efficient UAV delivery systems in the future.

关键词： Supply chain management Large language models Scalability Autonomous aerial vehicles Chatbots Blockchains Security Resource management Vehicle dynamics Logistics

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Advanced IoT Security Solutions with Deep Learning and Big Data Analytics

Advanced IoT Security Solutions with Deep Learning and Big D...

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IEEE UP Section conference on Electrical Computer and Electronics (UPCON)

作者： Ankur Gupta Dinesh Chandra Misra Department of CSE Dr. K.N. Modi University Newai Rajasthan India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

the exponential growth of IoT has enabled the deployment of smart systems and applications across several industries, enabling hitherto impossible degrees of connectivity and innovation. However, due to the limited processing capabilities and very high data quantities produced by IoT devices, security has emerged as a major concern with their extensive adoption. Here, we take a close look at the ways in which big data analytics and deep learning (DL) could strengthen IoT security. there is an emphasis on the pros and cons of currently used techniques as well as fresh findings in the field. Although deep learning models have made great strides in detecting suspicious activity and intricate attack patterns in IoT networks, big data analytics allows us to analyze the massive amounts generated by these devices in real-time. IoT security, the inner workings of big data-driven security systems, and the potential uses of deep learning techniques like CNNs, RNNs, and LSTM are all explored in this research. IoT system security might be enhanced by combining deep learning with big data analytics. Data availability, confidentiality, and integrity may be safeguarded in heavily networked situations in this way. Traditional research based on deep learning has supposedly produced results with an accuracy rate of more than $\mathbf{9 0 \%}$ . the research here compares and contrasts testing and training durations and simulates the quality of both sets of assessments.

关键词： Deep learning Training Adaptation models Accuracy Big Data real-time systems Internet of things Security Long short term memory Testing

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Development of Safety Monitoring and Alert System for 2 Wheelers

Development of Safety Monitoring and Alert System for 2 Whee...

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international conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Gurinder Bawa Zamen Latef Naser Hayder Sharif Laith H. A. Fezaa Jasgurpreet Singh Chohan Ruby Pant Stellantis Auburn Hills MI USA National University of Science and Technology Dhi Qar Iraq Medical technical college Al-Farahidi University Iraq Department of Optical Techniques Al-Zahrawi University College Karbala Iraq University Center for Research and Development Chandigarh University Mohali Punjab India Department of Mechanical Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun India

ISBN: (数字)9798350350357

ISBN: (纸本)9798350350364

the growing interest in the Internet of things (IoT) has made innovative approaches to safety monitoring and real-time data collection possible. Using real-time location, speed, and pulse rate data, this study presents an Internet of things (IoT)-based safety monitoring and alert system for 2-wheelers that aims to improve bikers' safety. Utilizing a GPS module, a pulse sensor, and a speed sensor, the device makes use of an ESP8266 microprocessor. the position, speed, and health parameters of a cyclist are to be tracked and sent in real-time to a smartphone application. A designated contact can receive instant alerts from the system in the case of an accident when it detects abrupt movements. this studyprovides a thorough description of the system's architecture, hardware, and software implementation in this document. the method illustrates connecting the ESP8266 to the mobile application, integrating sensors, gathering data, and developing algorithms for accident detection. Experimental results show that the system can precisely track a cyclist's whereabouts, keep an eye on their health indicators, and recognize accident situations. this study observed that the Internet of things (IoT)-based safety monitoring and alert system for 2-wheelers has a lot of potential to improve riders' security and safety while also offering useful information to athletes and health-conscious people. the system provides chances for extra study and advancement in the field of Internet of things applications for wellbeing and personal safety.

关键词： Tracking Software algorithms real-time systems Software Safety Internet of things Security

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Modeling Datasets in Distributed Monitoring systems

Modeling Datasets in Distributed Monitoring Systems

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IEEE international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and applications

作者： Yana A. Bekeneva Saint Petersburg Electrotechnical University “LETI” St. Petersburg Russian Federation

ISBN: (纸本)9781665426060

Automated detection of abnormal events in processes in real time is an urgent and important task. To identify various kinds of anomalies, various Data Mining methods are often used. Often, to obtain high accuracy of the analysis, preliminary training is required using a large amount of data and representative samples. However, it is not always possible to obtain a representative sample of various kinds of anomalies from real sources. this paper proposes an approach to modeling datasets generated by distributed heterogeneous monitoring systems.

关键词： Training conferences Data acquisition Distributed databases Training data Data models real-time systems

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Adaptive Admission Control Policy in Distributed real time Database System

Adaptive Admission Control Policy in Distributed Real Time D...

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international conference on System Modeling & Advancement in Research Trends (SMART)

作者： Nupa Ram Chauhan Rakesh Kumar Dwivedi Computer Science & Engineering CCSIT TMU Moradabad India Computer Science & Engineering Faculty of Engineering TMU Moradabad India

ISBN: (纸本)9781665487351

Today's real time computers activities and applications required data services in the distributed platform where real time applications have been needed for databases, in which data and operations have special characteristics in terms of time constraints. It stores large amount of data with time-sensitive manner and process it within fix given time frame. the requirement for real time computers activities and its applications are increasing in distributed real time database system (DRTDBS) including advanced traffic control, global environment control, nationwide power grid control etc. the transaction work load in DRTDBS has not balanced and the transaction processing patterns have time varying and distorted. Due to the unbalanced computation workload on DRTDBS and unpredictable communication delay can lead to miss the large number of transaction deadline. Hence, an adaptive admission control architecture and protocol have required for DRTDBS. the Adaptive admission Control Policy has fulfil to accessing and maintaining real time computers activities and application of data for satisfy timing constraints of transaction supported applications. this paper presents an adaptive admission control architecture and an efficient set of protocol. the local controller controls the local transaction request and global load balancer works global transaction request on distributed environment. the functionality of Adaptive Admission Control Policy have increased the performance because minimizing the miss ratio and increasing throughput. the experiment results show that an adaptive admission control policy effectively balances the workload in distributed real time database system under tight transaction workload as compared to existing protocols.

关键词： Computers Wide area networks Protocols Adaptive systems Admission control Distributed databases Process control

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