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

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Machine Learning for Job-flow Online Scheduling and Resources Allocation in distributed computing 6

Machine Learning for Job-flow Online Scheduling and Resource...

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6th international conference on Information Technologies in Engineering Education, Inforino 2022

作者： Toporkov, Victor Yemelyanov, Dmitry Bulkhak, Artem National Research University MPEI Moscow Russia

ISBN: (纸本)9781665405775

In this work we study a promising approach for efficient online scheduling of job-flows in high performance and distributed parallel computing. the majority of job-flow optimization approaches, including backfilling and microscheduling, require apriori knowledge of a full job queue to make the optimization decisions. In a more general scenario when user jobs are submitted individually, the resources selection and allocation should be performed immediately in the online mode. In this work we consider a neural network prototype model trained to perform online optimization decisions based on a known optimal solution. For this purpose, we designed MLAK algorithm which implements 0-1 knapsack problem based on the apriori unknown utility function. In a dedicated simulation experiments with different utility functions MLAK provides resources selection efficiency comparable to a classical greedy algorithm. the interdisciplinary nature of the considered problem and its solution (including elements from the areas of optimization, scheduling algorithms, machine learning and simulation) makes it a good study example in technical disciplines. © 2022 ieee.

关键词： Greedy algorithms Scheduling algorithms Computational modeling Scalability Prototypes Machine learning Parallel processing

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Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge 8

Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation...

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8th ieee international conference on Smart computing (SMARTCOMP)

作者： Hasan, Zahid Dey, Emon Ramamurthy, Sreenivasan Ramasamy Roy, Nirmalya Misra, Archan Univ Maryland Baltimore Cty Dept Informat Syst Ctr Real Time Distributed Sensing & Auton CARDS Mobile Pervas & Sensor Comp Lab Baltimore MD 21228 USA Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore

ISBN: (纸本)9781665481526

In this demo paper, we design and prototype RhythmEdge [1], a low-cost, deep-learning-based contact-less system for regular HR monitoring applications. RhythmEdge benefits over existing approaches by facilitating contact-less nature, real-time/offline operation, inexpensive and available sensing components, and computing devices. Our RhythmEdge system is portable and easily deployable for reliable HR estimation in moderately controlled indoor or outdoor environments. RhythmEdge measures HR via detecting changes in blood volume from facial videos (Remote Photoplethysmography;rPPG) and provides instant assessment using off-the-shelf commercially available resource-constrained edge platforms and video cameras. We demonstrate the scalability, flexibility, and compatibility of the RhythmEdge by deploying it on three resource-constrained platforms of differing architectures (NVIDIA Jetson Nano, Google Coral Development Board, Raspberry Pi) and three heterogeneous cameras of differing sensitivity, resolution, properties (web camera, action camera, and DSLR). RhythmEdge further stores longitudinal cardiovascular information and provides instant notification to the users. We thoroughly test the prototype stability, latency, and feasibility for three edge computing platforms by profiling their runtime, memory, and power usage.

关键词： Heart rate Volume measurement Prototypes Estimation Cameras Ubiquitous computing Real-time systems

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LeakG3PD: A Python Generator and Simulated Water Distribution System Dataset 25th

LeakG3PD: A Python Generator and Simulated Water Distributio...

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25th international conference on Intelligent Data Engineering and Automated Learning

作者： Figueiredo, Matheus Pilotto Oliveira, Lizandro de Souza Lucca, Giancarlo Yamin, Adenauer Correa dos Santos, Wesley Huckembeck Lopes, Tiago da Rosa Univ Catolica Pelotas Pelotas RS Brazil Parallel & Distributed Proc Res Grp G3PD Pelotas RS Brazil Univ Fed Pelotas Pelotas RS Brazil Autonomous Sanitat Serv Pelotas Pelotas RS Brazil

ISBN: (纸本)9783031777370;9783031777387

the United Nations' (UN) 2030 Agenda for Sustainable Development 6th goal is of special interest here: "Ensure availability and sustainable management of water and sanitation for all". To manage consumption water, it's surely fundamental to be able to measure, diagnose and control the whole path from it's origin in natural reservoirs till the end customers, requiring a net of sensors along the Water Distribution System (WDS). Such a network of sensors, will generate data over time constituting a dataset on which computer intelligence algorithms can work to detect abnormal behaviour, especially leakages. Unfortunately in Brazil the initiatives in monitoring WDS through sensors are very incipient. Since we don't have a real dataset with sensor information over time yet, in this work we aim to provide a solution to this part of the problem through simulation. In 2018, LeakDB [1] was presented as a "benchmark dataset for leakage diagnosis in water distribution systems", in fact a very important and interesting work. However it has some drawbacks, especially inconsistent data, which prevents its use as a solid basis. In this paper we improve LeakDB implementing LeakG3PD, opening the path to analyze the viability of different solutions in water management, with special focus on leakages.

关键词： Water distribution systems (WDS) Simulated Dataset Leakage Detection and Isolation Algorithms (LDIA) LeakDB LeakG3PD

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Secure Wireless sensor Network Design Using a New Method of High-Speed Lightweight Encryption 6

Secure Wireless Sensor Network Design Using a New Method of ...

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6th international conference on computing, Communication, Control and Automation, ICCUBEA 2022

作者： Kori, Prachi Cecil, Kanchan Jabalpur Engineering College Department of Electronics and Telecommunication M.P Jabalpur India

ISBN: (纸本)9781665484510

Data streaming over a wireless network such as Wireless sensor Networks, where wireless terminals (like PDAs, mobile phones, palmtops) access in data conferencing system, new challenges will be brought about. goal for this paper is to propose a high-speed lightweight encryption (HSLE) for low computational capability controller of WSN, HSLE scheme which reduces latency overhead by modifying existing approaches in order to encrypting data using a probabilistic encryption of data blocks. Proposed work is also useful when we communicate our confidential data on WSN or IoT it should be secure, we just have to save an encrypted data on cloud servers. proposed work is a new key-based algorithm and uses HSLE encryption instead for high end AES. Proposed methods cause significant speed enhancement for data encryption with similar security, in addition, it is best suited in order to communication between hand-held devices such as mobile phones, palmtops etc. algorithm may be used between sites where processing capacity and battery power are limited and efficient encryption is main necessity. this work is implemented on MATLAB and a wireless sensor network of maximum 100 nodes developed for testing the proposed network node encryption system, the time delay observed for the communication in 100 nodes WSN is less in compare with the other available works. © 2022 ieee.

关键词： Cryptography

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Power Generation Control Optimizing Framework of distributed Power System with Renewables 6

Power Generation Control Optimizing Framework of Distributed...

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ieee 6th international conference on Condition Assessment Techniques in Electrical systems (ieee CATCON)

作者： Bhowmik, Mrinmay Mishra, Joynath Mohan, Harshit Mahapatra, Sadhan Univ Petr & Energy Studies SoE Elect & Elect Engn Dehra Dun Uttarakhand India Indian Inst Technol Kharagpur Kharagpur W Bengal India Indian Inst Technol Dept Min Engn Kharagpur W Bengal India Tezpur Univ Cent Univ Dept Energy Technol Tezpur Assam India

ISBN: (纸本)9781665473804

Multi-area power integration and its distribution is an essential direction of power grid control. Consequently, investigation of multi-area power grid system (MAPS) is very crucial for improving the power quality. Crucial issues of MAPS include the operating system frequency and automatic voltage regulation (AVR). the controlling of these parameters sustain the steady output voltage at the specific required level. this paper represent the optimization of an automatic generation control plan(AGC) for multi-area power systems with a Proportional Integrator Differentiator(PID) controller. In this study, a control line tracking system has been brought up for interconnected three areas - solar thermal (STPP) and two thermal power systems (conventional mean coal, petroleum) by using generation rate constraints (GRC) & Artificial Neural Network (ANN).the simulation results clear that an ANN-based PID controller enhances the dynamic performance of the interconnected system and reduces the overshoots concerning the change in operating frequency in each area.

关键词： Multi-Area Power grid System MAPS Automatic Generation Control AGC Solar thermal Power Plant STTP Generation Rate Constrains GRC Artificial Neural Network ANN

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ReFrAEN: a Reconfigurable Vibration Analysis Framework for Constrained sensor Nodes 17

ReFrAEN: a Reconfigurable Vibration Analysis Framework for C...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： thangarajan, Ashok Samraj Yang, Fan Joosen, Wouter Michiels, Sam Hughes, Danny Katholieke Univ Leuven Imec DistriNet Leuven Belgium

ISBN: (纸本)9781665439299

Vibration monitoring uses data gathered from accelerometers to study kinetic phenomena in applications such as: structural health monitoring and predictive maintenance. the Internet of things (IoT) has the potential to greatly expand the range and scope of vibration monitoring applications by delivering long-life wireless sensors that can be cost-effectively embedded in hard to reach places such as;within machines, infrastructure or the built environment. However, achieving this vision is difficult due to the stringent resource constraints of contemporary IoT devices and networks. this has led the research community to develop a creative range of application-specific near-sensor processing firmware. However, systematic support for generic vibration monitoring on resource-poor IoT networks remains an open problem. We tackle this challenge by introducing ReFrAEN, a software framework that efficiently enables a wide range of vibration monitoring applications on IoT networks. ReFrAEN achieves this through a deeply configurable combination of compression techniques and data processing algorithms. these features allow end-users to effectively trade-off between resource consumption and data resolution in order to meet battery life constraints while preserving sufficient data quality to support the target application. Our evaluation shows that ReFrAEN is capable of identifying bearing faults, while dramatically improving battery lifetime and reducing latency in comparison to prior approaches.

关键词： IoT Near sensor Processing Vibration Monitoring

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Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In distributed Smart systems 17

Synthetic Traffic Signs Dataset for Traffic Sign Detection &...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Siniosoglou, Ilias Sarigiannidis, Panagiotis Spyridis, Yannis Khadka, Anish Efstathopoulos, Georgios Lagkas, thomas Univ Western Macedonia Dept Elect & Comp Engn Kozani Greece 0 Infin Ltd London England Int Hellen Univ Dept Comp Sci Kavala Campus Kavala Greece

ISBN: (纸本)9781665439299

Traffic sign recognition (TSR) is a key aspect involved in the development of robust automated transportation systems. It inherently involves the task of traffic sign detection (TSD), which can be challenging due to traffic signs often being subject to deterioration or occlusion, caused by various environmental factors, or through actions of vandalism. Even though, notable advancements have been achieved in the areas of TSR and TSD, few studies have provided robust algorithms, able to be generalized in real-world applications. this mostly stems from the lack of an extensive traffic sign dataset, standardized for benchmarking purposes. In light of the aforementioned, this paper presents a novel traffic sign dataset, which consists of the Carla Traffic Sign Detection (CTSD), and the Carla Traffic Sign Recognition Dataset (CATERED), targeting the detection and recognition processes respectively. Using the proposed dataset for training and evaluation, a deep Auto-Encoder algorithm is presented, demonstrating high accuracy in detecting and recognizing the distorted traffic signs. Finally, the system is further extended to a federated learning environment, exemplifying its applicability in modern decentralized and interconnected architectures.

关键词： Traffic Sign Recognition Traffic Sign Detection Autoencoder Federated Learning Image synthesis Image classification Anomaly Detection

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2022 6th international conference on Robotics and Automation Sciences, ICRAS 2022

2022 6th International Conference on Robotics and Automation...

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6th international conference on Robotics and Automation Sciences, ICRAS 2022

ISBN: (纸本)9781665467841

the proceedings contain 52 papers. the topics discussed include: a teleoperation method based on posture shared control strategy;distributed robust h-infinity control based on load frequency control of interconnected energy under bounded disturbances;non-constant distance control for vehicle platoon system;semi-active suspension damping control based on single acceleration sensor;event-triggered adaptive dynamic programming of load frequency control;phase-based dynamic movement primitives for powered knee-ankle prosthesis control;research on influencing factors of plant target precision spray;a three dimensional guidance and control method for suicide UAV and the flight test verification;and data-free knowledge distillation for privacy-preserving efficient UAV networks.

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Overview of Task Offloading of Wireless sensor Network in Edge computing Environment

Overview of Task Offloading of Wireless Sensor Network in Ed...

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ieee international conference on Electronic Information and Communication Technology (ICEICT)

作者： XiQiang Hou YiFan Hu Fuqiang Wang School of information and control engineering Qingdao University of Technology Qingdao China Shandong Computer Science Center and Shandong Provincial Key Laboratory of Computer Networks Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Computer Science Center and Shandong Provincial Key Laboratory of Computer Networks Qilu University of Technology (Shandong Academy of Sciences) China

this review article introduces the concepts, server architecture and application scenarios of Mobile Edge computing (MEC) and Wireless sensor Network (WSN). By differentiating between rechargeable and non-rechargeable systems, it presents the research status of task offloading in WSN in an edge computing environment. Various strategies are analyzed and compared in terms of their characteristics and application domains. the existing methods can reduce offloading latency and energy consumption, but still face some issues. Based on this, the research hotspots of edge computing task offloading for WSN are summarized, and its research and development trends are pointed out.

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Toward Unattended 24/7 Monitoring and Localization of Leaks of Electrical Insulating Gases and their Decomposition Products 59

Toward Unattended 24/7 Monitoring and Localization of Leaks ...

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59th international Universities Power Engineering conference, UPEC 2024

作者： Potyrailo, Radislav A. Shan, Shiyao Cheng, Baokai Arevalos, Edward Younsi, Karim Ndiaye, Ibrahima Cao, Yang Ge Vernova Advanced Research NiskayunaNY United States Ge Aerospace Research NiskayunaNY United States University of Connecticut StorrsCT United States

ISBN: (纸本)9798350379730

An electrical power grid consists of diverse types of gas-insulated equipment (GIE) that experiences different environmental stress depending on geographical locations and climate conditions. Over the operational lifetime, gradual aging of GIE can lead to partial discharges, decomposition of electrical insulating gas media, and gas leaks. Prognostics and elimination of leaks of electrical insulating gas media is an important unmet need in making the grid safer. Here, we demonstrate an approach for unattended monitoring and localization of leaks of electrical insulating gases and their decomposition products from GIE assets using spatially distributed sensor node systems. these sensors are based on multivariable design principles and utilize a multiband dielectric excitation scheme. In initial laboratory tests, the Limits of Detection (LODs) at part-per-billion levels of gas concentrations were achieved in detection of model decomposition products of g3. Further, different leak volatiles were differentiated indoors and outdoors under dynamic test conditions. Localization of leaks of different volatiles was also achieved on a model outdoor industrial asset. the detector sensitivity and low noise levels allowed detection of model leaks as far as 52 meters in indoor settings and 43 meters outdoors under ambient wind conditions. We are working toward field validation of developed sensor systems to deliver reliable alarms 1 - 6 months earlier than conventional alarms, thus providing solutions for more cost-effective monitoring and management of GIE assets of utilities. © 2024 ieee.

关键词： sensor nodes

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