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检索条件"任意字段=5th IEEE International Conference on Distributed Computing in Sensor Systems"

共 5705 条记录，以下是521-530 订阅

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HVAC scheduling for demand response in a distributed CCHP system considering latent load 5

HVAC scheduling for demand response in a distributed CCHP sy...

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5th ieee international Electrical and Energy conference, CIEEC 2022

作者： Lin, Junguang Zhou, Yamin Zhao, Shenyi Wu, Fan Qin, Ganghua Yu, Zitao Zheng, Menglian Zhejiang Energy R&d Institute Co. Ltd Hangzhou China Institute of Thermal Science and Power Systems College of Energy Engineering Hangzhou China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

distributed combined cooling, heating, and power (CCHP) systems are expected to be widely adopted in the building sector in the near term owing to the superiors of the combined CCHP systems over the conventional systems with respect to the energy and exergy efficiencies. Recognizing that the rapid revolution in the Internet of things and optimization methods enables active interaction between suppliers and consumers, demand response has gained increasing attentions, particularly in the building sector and multi-energy systems. Recognizing that few of previous study considered latent cooling power which was found to account for a significant portion of the total energy consumption of the cooling devices, the present study aims to provide a scheduling framework for a distributed CCHP system considering the latent cooling power under a time-of-use tariff. the simulation results for an industry park in China show that the proposed demand response strategy that takes into account the latent load effectively yields a declination in the daily operation cost of the CCHP system by up to 6.3%. © 2022 ieee.

关键词： Scheduling

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Impact of 3D Printed Infill Patterns on Flexible Non-Invasive Serum Glucose sensor 5

Impact of 3D Printed Infill Patterns on Flexible Non-Invasiv...

引用

5th ieee international conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Persad, Jeevan Mahadeo, Megan Rocke, Sean The University of the West Indies Department of Electrical and Computer Engineering St. Augustine Trinidad and Tobago

ISBN: (纸本)9781665457330

Noninvasive monitoring methods can potentially improve the quality of patient care for noncommunicable diseases such as diabetes and chronic kidney disease. However, many communities most affected by noncommunicable diseases are low- and middle-income. 3D printed electronics can potentially offer a simple and low-cost solution for the manufacture of noninvasive measurement sensors. In this work the impact of the infill patterns of a 3D printing manufacturing method for a flexible double u-slot patch antenna is investigated. A rigid version of the patch using a traditional glass-epoxy circuit board has been previously considered for noninvasive measurement. this work considers a flexible 3D printed substrate for the patch. the patch performance is examined using the measured S11 reflection coefficient for each antenna. the measured data suggests that the changes in the infill patterns result in a shift and variation in the number of resonant frequencies and the magnitude of the response. © 2023 ieee.

关键词： Glucose sensors

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RIFFLE: A distributed Network Operating System with Re-configurability for Multiple Domains 21

RIFFLE: A Distributed Network Operating System with Re-confi...

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21st ieee international conference on Ubiquitous computing and Communications / 5th ieee international conference on Data Science and Computational Intelligence / 21st ieee international conference on Computer and Information Technology

作者： Zhou, Boyang Wu, Chunming Chen, Shuangxi Li, Zhen Fan, Hong Intelligent Networks Inst Zhejiang Lab Hangzhou 311100 Peoples R China UCAS Hangzhou Inst Adv Study Sch Intelligent Sci & Technol Hangzhou 310024 Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou 311127 Peoples R China Jiaxing Key Lab Ind Internet Jiaxing 314036 Peoples R China Res Ctr Intelligent Technol Standardizat Zhejiang Lab Hangzhou 311100 Peoples R China Shanghai Univ Elect Power Dept Elect Engn Shanghai 200090 Peoples R China

ISBN: (纸本)9781665477260

the distributed network control in software-defined networking is greatly challenged by the design demands of evolving a running distributed control plane (DCP), and by the complexity of handling the control state dynamics. In this paper, we propose RIFFLE to address the problem using a distributed network operating system approach. RIFFLE enables the evolvability of control states of DCP deployed on a global scale. RIFFLE handles spatial and temporal dynamics that occur when updating and migrating the distributed control states, which overcomes the critical barrier to the evolvability. It fills the gap by enabling temporal reconfigurability in DCP. Moreover, RIFFLE reduces the complexities of building and maintaining network control services in DCP by enabling componentization and abstracting the underlying network dynamics. We evaluated the prototype RIFFLE through experiments running in PlanetLab. the results show that the prototype scales well for 135 nodes. We also validate that RIFFLE ensures the continuity and low content request delay for the supported the information-centric network supported during cache update periods owing to the enabled evolvability.

关键词： Software-Defined Networking Network Architecture distributed Control Plane

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Fault Diagnosis Research of distributed Photovoltaic System Based on Support Vector Machine

Fault Diagnosis Research of Distributed Photovoltaic System ...

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Consumer Electronics and Computer Engineering (ICCECE), 2021 ieee international conference on

作者： Xinran Wang Di Bai Shenyang Institute of Engineering Shenyang China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

In order to improve the precision and efficiency of fault diagnosis of distributed photovoltaic (PV) systems, an efficient fault diagnosis model is constructed by combining the classification ability of support vector machine and the advantages of distributed computing. the analysis results show that the model has a classification accuracy of 97.6%, a recall of 96.5% and an F1 value of 96.8% on the experimental dataset, which can adapt to a variety of operating states and fault scenarios, and maintains a high diagnostic performance under the condition of multiple fault superposition, with a classification accuracy of 91.8%-94.2%, demonstrating a strong applicability and robustness, and providing a reliable technological support for the intelligent operation and maintenance of PV systems. It shows strong applicability and robustness, and provides reliable technical support for intelligent operation and maintenance of PV systems.

关键词： Fault diagnosis Support vector machines Photovoltaic systems Industries Adaptation models Accuracy Computational modeling Robustness Maintenance distributed computing

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Accelerating 6TiSCH Network Formation 17

Accelerating 6TiSCH Network Formation

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

作者： Tanaka, Yasuyuki Minet, Pascale Watteyne, thomas Teraoka, Fumio Toshiba Co Ltd Corp R&D Ctr Kawasaki Kanagawa Japan INRIA EVA Team Paris France Keio Univ Fac Sci & Technol Yokohama Kanagawa Japan

ISBN: (纸本)9781665439299

Wireless sensor networking is a key enabler of Industrial IoT. IETF (Internet Engineering Task Force) has standardized a protocol suite called 6TiSCH (IPv6 over the TSCH mode of ieee802.15.4e). 6TiSCH builds an IPv6 multi-hop wireless network with the ieee802.15.4 radio, which achieves low energy consumption and high reliability. Although network formation time is one of key performance indicators of wireless sensor networks, it has not been studied well with 6TiSCH standard protocols such as MSF (6TiSCH Minimal Scheduling Function) and CoJP (Constrained Join Protocol). In this paper, we propose a scheduling function called SF-Fastboot which shortens network formation time of 6TiSCH. We evaluate SF-Fastboot by simulation comparing with MSF, the state-of-the-art scheduling function. the simulation shows SF-Fastboot reduces network formation time by 41 % - 80 %.

关键词： 6TiSCH TSCH ieee802.15.4 Network formation Scheduling Lifetime

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WiDeo: One Shot Domain Adaptation for Cross-Environment WiFi-Based Activity Classification through RF-Visual Joint Embedding 17

WiDeo: One Shot Domain Adaptation for Cross-Environment WiFi...

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

作者： Islam, Md Tamzeed Nirjon, Shahriar Univ N Carolina Dept Comp Sci Chapel Hill NC 27515 USA

ISBN: (纸本)9781665439299

the effect of environmental change in WiFi signal is a major obstacle for generalized WiFi-based activity recognition. In this paper, we propose a novel method for adapting a WiFi-based activity classifier, that is trained on a large-scale dataset for an environment, to a new environment with only one labeled sample per activity. To this end, we propose a novel representation extraction algorithm using the supervision of visual data during the training phase. Our proposed feature extraction explicitly learns the corresponding relation between WiFi signal and movement of human body parts. For environment adaptation, we propose a framework that relies on only one labeled sample per activity class in comparison with current state-of-the-art solutions which are not suitable for few-shot adaptation. We collect data from four volunteers from five different environments and show that our proposed solution is able to achieve 28% higher accuracy than state-of-the-art solutions for environmental adaptation.

关键词： Training Visualization Adaptation models Correlation distributed databases Activity recognition Feature extraction

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Scalable Channels Allocation in Smart Environments Considering Cross-Interference 17

Scalable Channels Allocation in Smart Environments Consideri...

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

作者： Rocha, Alexandre Mosca, Eduardo E. da Silva, Gabriel G. Gomes, Rafael L. State Univ Ceara UECE Fortaleza Ceara Brazil

ISBN: (纸本)9781665439299

Recently, the Internet of things (IoT) arose as paradigm to evolve the daily tasks and to deploy new intelligent services in the environments, turning them into Smart Environments (SEs). A SE is composed of heterogeneous wireless devices, where part of them are mobile. these heterogeneous devices suffer a problem of cross-interference, since most of them use the 2.4 GHz Industrial, Scientific and Medical bands ISM for communication. the cross-interference problem affects directly the Quality of Service (QoS), mainly the low transmission power devices that provide the basis of the services running on the top of the network. Within this context, this paper presents the Scalable Cross-Interference Mitigation (SCIM), an algorithm to mitigate the cross-interference problem in smart environments. the SCIM algorithm considers the mobility of the devices and their communication capacity to perform a scalable wireless channels assignment. the results, from the experiments performed, suggest that the SCIM algorithm minimizes the total interference of the SE, while increases the packet delivery, when compared to existing approaches.

关键词： Performance evaluation Wireless communication Wireless sensor networks Interference Quality of service Channel allocation Turning

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Developing Verified Multidomain Connectivity using distributed Blockchain for Mobile Edge of the Network in 5g and Even Beyond

Developing Verified Multidomain Connectivity using Distribut...

引用

2023 international conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Kundra, Danish Chitkara University Chitkara University Institute of Engineering and Technology Punjab India

ISBN: (纸本)9798350322309

MECs enable the connectivity of mobile networks components with Web accessibility in 5G and later by reducing the workload on the core processor units (CPU) just at information centers base. the protection of individual data in a heterogeneous technology model for multi-server interaction is essential considering the ever-growing demand of applications. Most contemporary methods don't focus on the privacy of customers or products;rather, they focus on the anonymous of topologies. In this research, different MEC platforms are designed using blockchain, and adaptable method is used as either a transportation & a topologies privacy-preserving router. Typically, routed agreement is achieved by participation methods that keep topological confidentiality secret. Blockchain technology is used to create multiplexed commitment & confidence connection as well as cooperative flow monitoring through membership. through the membership services & agreement method, blockchain is used to establish multiplexed loyalty & trusted connection and collaboration flow validation. Experimenting to determine the viability and effectiveness of our idea. the statistics show that the suggested strategy can significantly increase the legitimacy & effectiveness of MEC cooperation. © 2023 ieee.

关键词： Mobile edge computing

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Effective Severity Assessment of Parkinson's Disease using Wearable sensors in Free-living IoT Environment 29

Effective Severity Assessment of Parkinson's Disease using W...

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29th ieee international conference on Parallel and distributed systems, ICPADS 2023

作者： Li, Ziheng Zhao, Yuting Qi, Jun Wang, Xulong Yang, Yun Yang, Po National Pilot School of Software Yunnan University Kunming China Xi'an JiaoTong-Liverpool University Department of Computing Suzhou China University of Sheffield Department of Computer Science Sheffield United Kingdom

ISBN: (纸本)9798350330717

Internet of things (IoT) Wearable technology plays a crucial role in assisting the diagnosis of Parkinson's disease (PD), and an efficient model for auxiliary diagnosis of the severity of PD can help reduce the workload for doctors. However, due to the influence of data collection environments and annotators, noisy label data is inevitable, which may have a negative impact on modeling the severity of PD. To address the above challenges, on the one hand, we collected a large number of activity signal data of Parkinson's patients in free-living environments, and on the other hand, we proposed an efficient PD stage assessment framework, which includes a noisy label processing method to alleviate the noisy label negative impact. Specifically, we collected signal data from 15 healthy controls and 68 PD patients through 12 activities, and then we proposed a framework for noisy label detection and correction. the experimental results on real PD data sets demonstrated that the proposed framework achieve 75.9% accuracy in PD stage assessment and significantly improve the classification performance of different types of basic classifiers, which is better than other noisy label detection algorithms and other PD stage assessment frameworks. Overall, in this work, we focus on modeling PD severity in free-living environments using a single wearable sensor and reducing the negative impact of noisy label data to better help PD patients manage the disease. © 2023 ieee.

关键词： Noisy Label detection Parkinson's disease Disease stage diagnosis model Wearable sensor

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An End-to-End Motion Planner Using sensor Fusion for Autonomous Driving 5

An End-to-End Motion Planner Using Sensor Fusion for Autonom...

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5th international conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： thu, Nguyen thi Hoai Han, Dong Seog Kyungpook Natl Univ Grad Sch Sch Elect & Elect Engn Daegu South Korea Kyungpook Natl Univ Sch Elect Engn Daegu South Korea

ISBN: (纸本)9781665456456

Autonomous driving vehicles and advanced driver-assistance systems are gaining tremendous attention with the hope of providing a new transportation mode that is more convenient and ensures road safety. Different types of sensors are deployed together with the aid of deep learning (DL) techniques to help the vehicle perceive the surrounding environment and navigate toward the destination. In this paper, we implemented a deep learning-based motion planner using sensor fusion from LiDAR point clouds and camera RGB images to predict future waypoints. the model is trained in an end-to-end manner in which input are the multimodal sensor data, and output is the predicted future waypoints. A transformer module with a self-attention mechanism is used to integrate the representation of the two sensor modalities. During training, auxiliary tasks including depth estimation and bird-eye-view semantic segmentation are carried out to provide an intermediate representation of the perception process as well as to enhance the performance of the motion planning task. Experimental results obtained from different model configurations on the Longest6 benchmark have shown that our proposed model achieves competitive performance compared to baselines.

关键词： Autonomous vehicles Motion planning sensor fusion End-to-end deep learning

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