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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

共 6276 条记录，以下是151-160 订阅

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Aqua Watch: A Nitrate sensor with Color Intelligence 6

Aqua Watch: A Nitrate Sensor with Color Intelligence

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6th ieee international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Maity, Souraja Maji, Soumadeep Bagchi, Surajit Heritage Institute of Technology Applied Electronics and Instrumentation Engg. Kolkata India Heritage Institute of Technology Electronics and Communication Engg. Kolkata India

ISBN: (纸本)9798350306613

Monitoring nitrate levels in water bodies is crucial, as excessive nitrate concentrations can cause eutrophication and potentially harmful impacts on human. this paper presents the realization process of a nitrate sensor with color intelligence to detect the nitrate-concentration dependent shift in intensities of yellow color when aqueous nitrate reacts chemically with acidic brucine sulphate solution. An UV-VIS spectrophotometer was used to calibrate the sensor. A machine learning mathematical was developed. A few of the performance indices such as accuracy (± 98.78 %), sensitivity (2.5 mV /ppm), stability and ease of use were investigated. the operating range of the sensor was 1-100 ppm (extendable range) with Least Detection Limit (LDL) as 1 ppm. the output from the sensor is fed to the ESP 8266, which has built-in Wi-Fi connectivity and embedded TCP/IP networking software, to process the machine learning mathematical model and communicate the data to the internet for in situ and remote measurements and future uses. © 2024 ieee.

关键词： aqueous environmental monitoring nitrate sensor performance index water quality

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2024 6th international conference on System Reliability and Safety Engineering, SRSE 2024

2024 6th International Conference on System Reliability and ...

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6th international conference on System Reliability and Safety Engineering, SRSE 2024

ISBN: (纸本)9798350356083

the proceedings contain 80 papers. the topics discussed include: a review of research on the security of train control networks;optimal replacement policy for wireless sensor networks considering loss;a study on reliability algorithm for complex electronic systems with periodic maintenance;research on risk assessment method for aircraft braking system based on improved FMEA;evaluating the A3RSRP handover to determine optimal performance in HetNet using stochastic petri net;preliminary research on human error analysis and accident risk assessment of operators with dynamic human-machine interaction simulation of advanced control room in nuclear power plants;intelligent fault diagnosis of rolling bearing based on incremental learning;and a remaining useful life prediction method for hydrogen fuel cell based on a multi-phase wiener process-based degradation model.

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Stable Soft sensor Modeling for Industrial systems 7

Stable Soft Sensor Modeling for Industrial Systems

引用

ieee 7th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Cao, Liang Cao, Yankai Gopaluni, R. Bhushan Univ British Columbia Chem & Biol Engn Vancouver BC V6T 1Z3 Canada

ISBN: (纸本)9798350363029;9798350363012

Learning trustworthy models is essential for machine learning tasks, as many researchers have revealed the vulnerability of machine learning models, especially when the fundamental independent and identically distributed (IID) assumption is not satisfied. Building a trustworthy model is promising when training on big representative data but fails to work with limited data. In this paper, we focus on solving small sample problems and unstable prediction problems in machine learning. First, to deal with small sample problems, we propose using a uniform manifold approximation and projection (UMAP) algorithm to generate high-quality virtual samples. then, with the generated big data and original small data, we use the stable learning method to achieve stable predictions. In addition to a detailed description of the UMAP algorithm and the stable learning algorithm, we also discuss the corresponding theoretical explanations and implementation details. Finally, several comparison studies are implemented on the Tennessee Eastman benchmark process to validate the effectiveness of the proposed method.

关键词： trustworthy model small sample UMAP stable learning soft sensor

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Spectral Clustering Based Resource Allocation Strategy for distributed Large-scale Network Emulation 25

Spectral Clustering Based Resource Allocation Strategy for D...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Jiyan Gu, Rentao Bai, Lin Sch. of Information and Communication Engineering Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Beijing China School of Economics and Management Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350330014

Nowadays, networks are increasingly reliant on software frameworks and virtualization. To obtain relevant pre-dictions of the behavior of their protocols, network emulation tools play a crucial role. However, as networks grow in size and complexity, the emulation task demands more physical resources such as CPU and memory. Consequently, a single physical machine is no longer sufficient to handle large-scale network emulation. Instead, distributed network emulation tools must be employed for resource-intensive network emulation tasks. In resource-intensive distributed network emulation, the physical resource allocation is NP-hard to perform appropriately. In this paper, we propose SCBG (spectral clustering based greedy node placement algorithm) as a means to enhance the bandwidth utilization between physical nodes in distributed emulation. SCBG aims to address the communication bottleneck in distributed network simulation, surpassing the algorithm proposed by Distrinet, while also improving the algorithm's execution speed. Additionally, SCBG incorporates optimization for time dilation when physical bandwidth resources are severely insufficient. this optimization leads to a reduction in the additional time required for network simulation after applying time dilation. Experimental results demonstrate that SCBG surpasses the algorithm in Distrinet across a diverse range of intricate large-scale networks. © 2023 ieee.

关键词： Optimization

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2024 6th international conference on Energy, Power and Grid, ICEPG 2024

2024 6th International Conference on Energy, Power and Grid,...

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6th international conference on Energy, Power and Grid, ICEPG 2024

ISBN: (纸本)9798350377798

the proceedings contain 358 papers. the topics discussed include: high gain dc-dc converter based on quasi-Z-Source;short-term smart grid load forecasting based on CNN-BiLSTM with attention mechanism;research on maximum power point tracking control method for ship photovoltaic system;effect of AC voltage frequency on partial discharge characteristics of GIS;distributed rapid fault self-healing scheme for active distribution networks;load optimization control method for multiple open rack vaporizers in liquefied natural gas station;analysis of transient stability in wind power grid integration systems;and random forest based heating power prediction for single crystal furnace.

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SELF-CARE: Selective Fusion with Context-Aware Low-Power Edge computing for Stress Detection 18

SELF-CARE: Selective Fusion with Context-Aware Low-Power Edg...

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18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Rashid, Nafiul Mortlock, Trier Al Faruque, Mohammad Abdullah Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA USA

ISBN: (纸本)9781665495127

Detecting human stress levels and emotional states with physiological body-worn sensors is a complex task, but one with many health-related benefits. Robustness to sensor measurement noise and energy efficiency of low-power devices remain key challenges in stress detection. We propose SELFCARE, a fully wrist-based method for stress detection that employs context-aware selective sensor fusion that dynamically adapts based on data from the sensors. Our method uses motion to determine the context of the system and learns to adjust the fused sensors accordingly, improving performance while maintaining energy efficiency. SELF-CARE obtains state-of-theart performance across the publicly available WESAD dataset, achieving 86.34% and 94.12% accuracy for the 3-class and 2-class classification problems, respectively. Evaluation on real hardware shows that our approach achieves up to 2.2x (3-class) and 2.7x (2-class) energy efficiency compared to traditional sensor fusion.

关键词： Stress detection edge computing energy efficiency sensor fusion

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Implementation of Power Electronics Devices Control systems Based on a Real-Time Operating System 6

Implementation of Power Electronics Devices Control Systems ...

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6th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2024

作者： Rozhkov, Alexander N. Mostovoi, Dmitry V. Rashitov, Pavel A. Badalyan, Artush V. Zhuravlev, Ivan I. Krasnoperov, Roman N. National Research University 'MPEI' Power Electronic Department Moscow Russia

ISBN: (纸本)9798350382891

the article describes the capabilities of a real-time operating system (RTOS) from the point of view of its application in solving problems of controlling power electronics devices. Using the example of implemented power electronics devices, most of which have been put into pilot operation, the capabilities and advantages of the proposed approach to implementing converter control systems are shown. It has been demonstrated that with the help of real-time operating system it is possible to implement not only centralized control systems, but also distributed ones that exchange information between devices and modules using the required protocol and data format. How a RTOS can be applied to control systems of power electronics devices, which require fast and accurate responses to input and output data changes described. How to use a RTOS to implement common control tasks such as switching, modulation, protection, and synchronization explained. the results presented in the article can be used in the design of control systems for power electronics devices and other electrical energy converters. © 2024 ieee.

关键词： distributed parameter control systems

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distributed resource low-delay interaction method for low-voltage substation based on communication quality-aware reinforcement learning 6

Distributed resource low-delay interaction method for low-vo...

引用

6th international conference on Energy, Power and Grid, ICEPG 2024

作者： Shi, Zhan Guangdong Power Grid Co. Ltd Power Dispatching and Control Center Guangdong China

ISBN: (纸本)9798350377798

In the distribution substation, edge computing can optimize the allocation and utilization of overall distributed resources, which is essential for ensuring efficient energy utilization and stable operation of the power grid. However, because of electromagnetic interference during data transmission at the device, the traditional upper confidence bound (UCB) algorithm neglects the impact of communication quality when estimating confidence bounds, leading to a deviation in the value estimation of actions and an increase in data processing delay. To tackle this issue, a distributed resource low-delay optimization algorithm for substations based on communication quality-aware UCB is proposed. Firstly, we propose the low-delay interaction architecture for low-voltage substations with communication quality-aware distributed resources. Moreover, by optimizing the data migration strategy, the problem of minimizing edge-edge collaborative data processing delay is formulated. To address this issue, we convert it into a multi-armed bandit (MAB) problem and solve it by using the proposed algorithm. this algorithm incorporates communication quality weight into the calculation formula for edge server preference value, enabling real-time awareness of migration channel quality during the data migration process and improving the efficiency of distributed resource interaction in the distribution substation. Finally, the proposed algorithm's effectiveness is confirmed through simulation. © 2024 ieee.

关键词： Reinforcement learning

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Proceedings of the 2024 6th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2024

Proceedings of the 2024 6th International Youth Conference o...

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6th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2024

ISBN: (纸本)9798350382891

the proceedings contain 289 papers. the topics discussed include: evaluation of cognitive computing and algorithms in engineering;a study on the application of using hypernetwork and low rank adaptation for text-to-image generation based on diffusion models;radar based lateral clearance decreasing warning system;improving production management and control with intelligent chatbot services;interrogation of SAW-resonator-based vibration sensor by low cost SDR;development of a beam steering system for a phased antenna array with variable duration of control pulses;algorithms for optimizing the values of parametric series of machine tools;metagraph storage implementation using relational database based on mutability/temporality approach;and quadrupole microwave diagnostics of azimuthally asymmetric plasma formations.

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Communication Analysis for Multidimensional Parallel Training of Large-scale DNN Models 25

Communication Analysis for Multidimensional Parallel Trainin...

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作者： Lai, Zhiquan Hao, Yanqi Li, Shengwei Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China

ISBN: (纸本)9798350330014

Multidimensional parallel training has been widely applied to train large-scale deep learning models like GPT-3. the efficiency of parameter communication among training devices/processes is often the performance bottleneck of large model training. Analysis of parameter communication mode and traffic has important reference significance for the research of interconnection network design and computing task scheduling to improve the training performance. In this paper, we analyze the parametric communication modes in typical 3D parallel training (data parallelism, pipeline parallelism, and tensor parallelism), and model the traffic in different communication modes. Finally, taking GPT-3 as an example, we present the communication in its 3D parallel training. © 2023 ieee.

关键词： Deep neural networks

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