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共 5105 条记录，以下是61-70 订阅

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Vehicle-Mounted Millimeter-Wave Radar Vital Signs Detection and Early Warning Control System

Vehicle-Mounted Millimeter-Wave Radar Vital Signs Detection ...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Wenshan Li Hunan Institute of Traffic Engineering Hengyang Hunan China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Traditional methods of monitoring vital signs in vehicles often fall short when it comes to response time, especially in fast-moving situations. To tackle this, our paper introduces a groundbreaking solution: leveraging millimeter-wave radar technology to monitor vital signs in real time within the vehicle, providing timely alerts when necessary. This approach not only enhances the accuracy of readings but also ensures a swift response that is crucial during vehicle operation. By tapping into the unique abilities of millimeter-wave radar to detect subtle human signs, we propose a novel method that processes radar signals to monitor vital signs like heart rate and respiratory rate. This technique is highly effective in meeting the stringent demands of real-time accuracy and speed, especially while driving. Our system includes three main components: radar sensors, a signal processing unit, and an early-warning control module, working together seamlessly to ensure optimal monitoring. The radar sensor continuously transmits and receives millimeter-wave signals, allowing it to track vital signs without interruption. A specially designed feature extraction algorithm filters out noise and extracts critical information, including heart and respiratory rates. Then, advanced algorithms analyze this data in real time, spotting any abnormalities and triggering alerts through the control module. What sets this system apart is its rigorous testing under various vehicle speeds and environmental conditions, confirming its stability, reliability, and fast response times. In real-world applications, the system responds to a high heart rate in 3.7 to 4.0 seconds and to a rapid breathing rate in 4.1 to 4.3 seconds. This millimeter-wave radar-based system offers a fresh approach to vehicle safety, combining practicality with promising future potential.

关键词： Heart rate Accuracy Signal processing algorithms Millimeter wave radar Real-time systems Stability analysis sensor systems sensors Time factors Monitoring

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IoT-Integrated Convolutional Neural Network for Accurate Vehicle Acoustic Signal Analysis

IoT-Integrated Convolutional Neural Network for Accurate Veh...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： P. Sasikala K Subha Sharmini Venkatesan Sorakka Ponnappan K. R. Kavitha K. Gunasekaran C. Srinivasan Department of Mathematics Vinayaka Mission's Kirupananda Variyar Engineering College Vinayaka Mission's Research Foundation (Deemed to be University) Salem India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Mechanical Engineering Sathyabama Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Sona College of Technology Salem India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

This paper examines the use of IoT-integrated Convolutional Neural Networks (CNNs) for precise analysis of vehicle audio signals. The context highlights the growing intricacy of vehicle systems and the need for advanced monitoring methods. Acoustic signals generated by different vehicle components may provide significant insights about vehicle health; nevertheless, traditional analysis techniques are often ineffective. The Internet of Things (IoT) technology allows real-time data collection from sensors installed on vehicles, which is then analyzed using CNNs to identify certain patterns and abnormalities in auditory signals. The approaches used include using IoT sensors to record various vehicle noises and utilizing CNNs for feature extraction and classification, providing great defect detection precision. The results indicate the system's capacity to detect engine faults, braking deficiencies, and other mechanical concerns early, enabling quick treatments. It presents a novel methodology for vehicle monitoring, enhancing predictive maintenance, safety, and performance, with prospects for future developments in autonomous diagnostics. The proposed system improved vehicle acoustic signal processing using IoT and CNN models, achieving high accuracy of 99% in anomaly detection, preventive maintenance, and real-time traffic monitoring.

关键词： Training Accuracy Noise Real-time systems Acoustics sensor systems sensors Convolutional neural networks Internet of Things Intelligent sensors

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Predictive Maintenance for IoT-Enabled Wireless Devices Using AdaBoost with Synthetic Minority Oversampling Technique

Predictive Maintenance for IoT-Enabled Wireless Devices Usin...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Montater MuhsnHasan Meghana A Panjagari Kavitha T. Aditya Sai Srinivas P. K. Chidambaram Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Al Diwaniyah Iraq Department of Electrical and Electronics Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Electronics and Communication Engineering CVR College of Engineering Hyderabad India Department of Artificial Intelligence and Machine Learning Jayaprakash Narayan College of Engineering Mahbubnagar India Department of Mechanical Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Nowadays, the rapid growth of predictive maintenance methods has become crucial for Internet of Things (IoT) enabled wireless devices. The existing Random Forest (RF) utilized to predict device failures although, the complexity of IoT device data led to scalability issues. Hence, this research proposes an Adaptive Boosting with Synthetic Minority Oversampling Technique (AdaBoost-SMOTE) for predicting device failures. The proposed AdaBoost-SMOTE overcome the scalability issues by handling imbalanced data and reducing dimensionality for accurate prediction. Initially, the input data is collected from IoT-enabled sensors and preprocessed with z-score normalization to scale the features. Then, Permutation Importance (PI) is employed to select the optimal features by ranking the feature score based on its importance. After that, SMOTE is used to handle the imbalance data and then, AdaBoost is employed to predict the machine failures by assigning the higher weights to misclassified samples in an iterative manner. Finally, hyperparameter tuning is done by using Grid Search Cross-Validation (GSCV) to optimize the parameters by selecting best CV score as a best set of hyperparameters. From the results, the proposed AdaBoost-SMOTE achieved best results in terms of accuracy (97%), precision (95%), recall (93%), and F1-score (94%) when compared to existing AdaBoost.

关键词： Wireless communication Wireless sensor networks Accuracy Scalability Data preprocessing Boosting Internet of Things Integrated circuit modeling Tuning Predictive maintenance

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An Optimization of Security and Trust Management in distributed systems

An Optimization of Security and Trust Management in Distribu...

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3rd ieee international Advance computing conference (IACC)

作者： Ahmed, Alsharif Mohamed Y. Qian, Depei Beihang Univ BUAA Sch Comp Sci & Engn Beijing Peoples R China

ISBN: (纸本)9781467345286

with the development of cloud computing, the security and trust management in distributed systems is changeable. This paper proposes an architecture and solution of security and trust management for distributed systems which use cloud computing. Since the solution requires future technologies, an optimization to the security and trust management, including multi-paths transmission, virtual personal networks and encryption, is proposed. This optimization will enhance the security and trust in distributed systems.

关键词： optimization Security amd trust management Distrubuted systems multi-path transmission

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Using Virtual Events for Edge-based Data Stream Reduction in distributed Publish/Subscribe systems 3

Using Virtual Events for Edge-based Data Stream Reduction in...

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3rd ieee international conference on Fog and Edge computing (ICFEC)

作者： Zehnder, Philipp Wiener, Patrick Riemer, Dominik FZI Res Ctr Informat Technol Karlsruhe Germany

ISBN: (纸本)9781728123653

distributed publish/subscribe systems are an enabling technology for Industrial Internet of Things applications. While the number of sensors increases, network bandwidth becomes a bottleneck. Existing solutions typically aim to reduce network load either by pre-processing events directly on the edge or by aggregating events into larger batches. However, these approaches are rather static and do not adequately account for the application requirements of subscribers or the actual values of sensor measurements. This paper introduces methods for publish/subscribe systems to dynamically adapt payloads of events at runtime based on i) different data reduction and transformation strategies, ii) a wrapper solution around existing message brokers and iii) a semantics-based event schema registry. Consumers are able to subscribe to various quality levels and receive virtual events, that are reconstructed directly at the subscriber based on knowledge from the semantic model and dynamic decision rules. Our evaluation shows that the concept of virtual events can reduce the network load between publishers, the message broker and subscribers compared to multiple investigated compression techniques.

关键词： Publish/Subscribe systems Edge Processing Semantic Web

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A Study of distributed MOEA/D Based on Spark Framework 19

A Study of Distributed MOEA/D Based on Spark Framework

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19th ieee international conference on High Performance computing and Communications (HPCC) / 15th ieee international conference on Smart City (SmartCity) / 3rd ieee international conference on Data Science and systems (DSS)

作者： Zhang, Defu Ma, Yingdong Chen, Jinxiu Xiamen Univ Dept Comp Sci Xiamen Peoples R China

ISBN: (纸本)9781538625880

We carry out a careful study of Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and propose some implementation schemas in the Spark Framework. Focusing on the setting of weight vectors, we propose two partitioning schemas, which define the distribution mode for the algorithm. The first partitioning schema is to define a partition by a group of weight vectors that are close to each other. The other schema is to distribute close weights to different partitions. Experiments in distributed framework indicate that, for most benchmarks, the schemas in distributed framework can obtain better results and better performance in expansibility.

关键词： multi-objective optimization decomposition distributed computation evolutionary algorithm

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Management of distributed Electrical Storage in Wide Area Communication systems 19

Management of Distributed Electrical Storage in Wide Area Co...

引用

作者： Feihn, Heinz Ulrich Boehmer Hinkle, Mark A. Kenyon, Richard Wallace Mickelson, Alan Univ Colorado 1111 Engn Dr Boulder CO 80309 USA

ISBN: (纸本)9781538625880

Centralized electrical storage system management in islanded micro-grids is treated both theoretically and experimentally. An overview of the types of distributed islands in Wi-Fi Long Distance networks is the starting point, followed by examples of WiLDNets and associated reliability problems. Presentation of an archetypical tree structure communication system serves to introduce a centralized management system that may be used to improve reliability of multi-community private networks. An existing Wi-Fi long distance testbed with distributed storage serves as an islanded micro-grid for experimental study. Centralized management algorithms are tested. The results are generalized to the case of large meshed communication system.

关键词： computers sensors monitoring modeling

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A distributed system for answering range queries on sensor network data

A distributed system for answering range queries on sensor n...

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3rd ieee international conference on Pervasive computing and Communications

作者： Cuzzocrea, A Furfaro, F Greco, S Masciari, E Mazzeo, GM Saccà, D Univ Calabria DEIS I-87030 Commenda Di Rende Italy

ISBN: (纸本)0769523005

A distributed system for approximate query answering on sensor network data is proposed, where a suitable compression technique is exploited to represent data and support query answering. Each node of the system stores either detailed or summarized sensor readings. Query answers are computed by identifying the set of nodes that contain (either compressed or not) data involved in the query, and eventually partitioning the query in a set of sub-queries to be evaluated at different nodes. Queries are partitioned according to a cost model aiming at making the evaluation efficient and guaranteeing the desired degree of accuracy of query answers.

关键词： distributed computer systems

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Autonomous Resource Management and Control Algorithms for distributed Wireless sensor Networks

Autonomous Resource Management and Control Algorithms for Di...

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3rd ieee/ACS international conference on Computer systems and Applications (AICCSA-05)

作者： Talukder, Ashit Bhatt, Rajan Chandramouli, L. Ali, Syed Muhammad Pidva, Rishi Monacos, S. Univ So Calif CHLA Jet Prop Lab NASA Los Angeles CA 90089 USA

ISBN: (纸本)9780780387355

We discuss a novel framework for integrated sensing and resource management in a distributed intelligent sensor network with sensor nodes whose useful active lifetime is significantly shorter than the required lifetime of the sensor system. Past sensor network research has focused on security and communication, but largely ignored the overall dynamic resource management issue of such distributed systems. Our contribution is in integrated control optimization and resource management algorithms to ensure proper functioning of distributed sensors in extremely limited bandwidth, power, and storage. In this paper, we present a novel genetic algorithm for real-time system control and resource management that handles multiple conflicting objectives and constraints in the distributed system. Our framework is suitable for dynamic environments where the desired system performance and resource usage changes dynamically while being constrained by limited amount of resources.

关键词： Evolutionary algorithm control distributed sensing machine learning sensor networks pattern recognition resource management mathematical optimization wireless communication

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DCEIL: distributed Community Detection with the CEIL Score 19

DCEIL: Distributed Community Detection with the CEIL Score

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作者： Jain, Akash Nasre, Rupesh Ravindran, Balaraman IIT Madras Dept Comp Sci & Engn Robert Bosch Ctr Data Sci & AI Madras Tamil Nadu India

ISBN: (纸本)9781538625880

Community detection in complex networks has a wide range of applications such as detection of cyber-communities in social networks, recommendations based on the interest group, and estimating hidden features in a social network. In distributed frameworks, the primary focus has been scalability. However, the accuracy of the algorithm's output is also critical. We propose the first distributed community detection algorithm based on the state-of-the-art CEIL scoring function. Our algorithm, named DCEIL, is fast, scalable and maintains the quality of communities. DCEIL outperforms the existing state-of-theart distributed Louvain algorithm by 180% on an average in Normalized Mutual Information (NMI) Index and 6.61% on an average in Jaccard Index metrics. DCEIL completes execution for 1 billion edges within 112 minutes and outperforms state-of-the-art distributed Louvain algorithm by 4.3x. DCEIL critically exploits three novel heuristics which address the existing issues with distributed community detection algorithms that have the hierarchical structure of CEIL or Louvain methods. Further, our proposed heuristics are generic as well as efficient, and we illustrate their efficacy by enhancing the accuracy of distributed Louvain algorithm by 22.91% on an average in Jaccard Index, and the average execution time by 1.68 x over popular datasets.

关键词： Image edge detection Measurement Detection algorithms Indexes Clustering algorithms Data models Mutual information

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