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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710867

The proceedings contain 93 papers. The special focus in this conference is on Autonomous Unmanned systems. The topics include: Multi-UAV Collaborative Search Strategy Based on Improved Genetic Algorithm;Joint Beamforming and Power Allocation in a MIMO Radar Network with Per-antenna Power Control;intelligent Trajectory Planning Algorithm for Unmanned Aerial Vehicles Based on Track Deception Against Radar Networks;Maneuvering Multi-target Tracking Based on DLSTM and Dynamic Association Gate;A DNN-Based GLMB Algorithm for Multi-sensor Multi-target Tracking with Dense Group Clutter;efficient Multiple Extended Target Tracking Based on Minimum Spanning Tree;improved Adaptive Sliding Mode Cooperative Guidance Law with Multi-constraints;a Cooperative Guidance Law with Multi-constraints for Intercepting Maneuvering Target;alleviating Local Optima and Enhancing Path Planning: A Deep Reinforcement Learning Approach for Autonomous Exploration;Research on Target Tracking Algorithm Between UAVs in Unknown Environment;a Maneuver Detection-Range Parameterized Cubature Kalman Filter for Bearings-Only Maneuvering Target Tracking;improvement of Ensemble Kalman Filter for Hypersonic Target Tracking;anti-bias Target Association Method Based on Laplacian Spectrum and Kuhn-Munkres Algorithm;Fully Automated UAV Cluster Pollution Source Detection Algorithm;Status and Application of Artificial Intelligence-Based Cooperative Positioning and Navigation Technology for UAV Clusters;a Fusion Method with Information Gains for distributed Multi-sensor Network;space Targets Tracking Algorithm Based on Improved State Equation with Universal Variable Updating;Multi-UAV Target Localization Based on 3D Object Detection and Visual Fusion;Real-World Experiments on Acoustic Detection of Small UAVs;relative Localization of Vehicle-to-Drone Coordination Based on Lidar;P-LVIO: A Plane-Based Lidar Visual Inertial Odometry in Urban Environments;a New Threat Assessment Method for Airborne Targets Based on Dynami

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710942

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indexPDT: A High Scalable distributed Classification Approach with Novel Cache Structure for Geo-location 25

indexPDT: A High Scalable Distributed Classification Approac...

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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： Sun, Zhijie Li, Jing Xie, Jun Zheng, Binfan Zeng, Li Zhao, Rongqian Huawei Technologies Co. Ltd. Shenzhen China

ISBN: (纸本)9798350330014

Geo-location, also known as measurement report (MR) location, is a technique to determine the geographic location of user equipment (UE) and the behaviour attribute of telephone traffic based on wireless signals measured by the mobile communication network. The geographic location information can help to support network performance monitoring and evaluation. Considering accuracy and cost, we mainly adopt a hybrid location scheme combined with feature matching location and Weighted Centroid Correction Location (WCCL). As for feature matching location, over 20 billion samples gathered from tens of thousands of cells daily updated. Due to the vast data scale, feature analysis encounters a severe performance bottleneck. To address this problem, we design the indexed parallel decision tree (indexPDT) operator and integrate it into WindTensor, a self-innovated distributed machine learning (ML) engine. indexPDT is a classifier unit of the random forest (RF) algorithm with a novel cache structure. It performs structured cache processing on the dataset's meta-information, which can accompany the splitting of nodes. The cache structure can be quickly converted into statistical information to help find the optimal splitting point, effectively reducing memory usage and improving performance. Under the public datasets testing on 5 nodes, the mean speedup ratios are 86x and 3x compared with SparkML and XGBoost, respectively. In the Geo-location scenario, for a single cell, the speedup ratios are 82x and 4x compared with SparkML and XG Boost, respectively. © 2023 ieee.

关键词： Location

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710829

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A Study on Load Balancing for Large-scale distributed computing Based on Improved Deep Learning 3

A Study on Load Balancing for Large-scale Distributed Comput...

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3rd international conference on Intelligent Design, ICID 2022

作者： Leng, Di Qiu, Ziliang Chen, Xi Ren, Binhua Huang, Xiang Shenzhen Power Supply Bureau Co. Ltd Guangdong Shenzhen China Co. Ltd Guangdong Shenzhen China CSG Digital Power Grid Research Institute Co. Ltd Guangdong Guangzhou China

ISBN: (数字)9781665476775

ISBN: (纸本)9781665476775

Some large-scale distributed computing load balancing methods suffer from excessive service violation rate. A large-scale distributed computing load balancing method based on improved deep learning is designed to improve the above problem. It takes the approach of offloading some of the downstream computing tasks, identifies large-scale distributed computing flow architectures, introduces the concept of linear functions, constructs a server energy consumption model, records the timestamps of state changes separately in sequential order, and designs load balancing methods based on improved deep learning. Experimental results: The mean service violation rates of the large-scale distributed computing load balancing method in the paper, and the other two large-scale distributed computing load balancing methods are: 16.016%, 19.487% and 18.688% respectively, indicating that the performance of the designed large-scale distributed computing load balancing method, after incorporating the improved deep learning algorithm, is more perfect. © 2022 ieee.

关键词： Energy utilization

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710980

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AI Powered COVID-19 Detection System using Non -Contact Sensing Technology and Deep Learning Techniques 18

AI Powered COVID-19 Detection System using Non -Contact Sens...

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

作者： Kogilavani, S., V Sathishkumar, V. E. Subramanian, Malliga Kongu Engn Coll Dept Comp Sci & Engn Erode Tamil Nadu India Hanyang Univ Dept Ind Engn 222 Wangsimini Ro Seoul 04763 South Korea

ISBN: (纸本)9781665495127

The SARS-CoV-2 virus causes coronary artery disease (COVID-19). The majority of persons who are infected with the virus will have mild to severe respiratory illness and recover without the need for therapy. Some, on the other hand, will become critically unwell and require medical assistance. People over the age of 65, as well as those with underlying medical diseases such as cardiovascular disease, diabetes, chronic respiratory disease, or cancer, are at a higher risk of developing serious illness. Being thoroughly informed on the disease and how it spreads is the best strategy to avoid and slow down transmission. Stay at least 1 metre apart from other people to avoid infection. In this research work, we focus on how non-contact sensing technology and deep learning technique are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. The proposed system captures images from the patient using non -contact sensing technologies and feeds the data into deep learning convolutional neural network architectures such as VGG16, VGG19, ResNet101, NASNet, DenseNet121, MobileNet, Xception, EfficientNet, and InceptionV3. In comparison to other architectures, the VGG16 architecture delivers superior accuracy.

关键词： Non-Contact sensor Deep Learning COVID-19 Health Care Respiratory System VGG16

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A Scalable and distributed Hierarchical Architecture for Network Monitoring-on-Demand 3

A Scalable and Distributed Hierarchical Architecture for Net...

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3rd international conference on 6G Networking, 6GNet 2024

作者： Madhukumar, Hari Bower, Thomas A. Vasilakos, Xenofon Ullauri, Juan Parra Lema, Maria Simeonidou, Dimitra University of Bristol Smart Internet Lab Bristol United Kingdom Weaver Labs Bristol United Kingdom

ISBN: (纸本)9798350378597

Efficient resource orchestration within cloud-native and future 6G infrastructures is a major challenge and essential for maintaining seamless service delivery. We present a novel monitoring approach as part of the REASON 6G architecture that is designed to leverage microservices and cloud-native technologies, which extend beyond traditional technological or administrative domain boundaries, incorporating the edge domain within ubiquitous networks. The core of this approach is the development of Monitoring Applications (mApps) and the Matching Service. The former are microservices tracking/gathering data metrics from a data source such as the edge system, while the latter is a request-matching messaging system built on the WireMQ messaging library, with its appropriately designed well-defined Northbound (NB) and Southbound (SB) APIs facilitating secure, scalable data distribution across cloud-native environments. This microservice-based approach enhances flexibility, scalability, and maintainability in monitoring systems, making it particularly suitable for complex environments like 5G and future 6G networks. Moreover, it allows cross-domain extendability and interoperability through its hierarchical design. Our presented WireMQ-based prototype supports authentication and authorization, ensuring controlled and secure access to data. It also offers features like historical data storage, data watchers and triggers, and topic abstraction for data protection. In this work, we demonstrate its capabilities in a decentralised and distributed network. © 2024 ieee.

关键词： 5G mobile communication systems

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Implementation of the Tapered Fiber sensor, for Measuring Failures Induced by Vibration in Rotary Electric Motors Using the ANSYS Simulator 3

Implementation of the Tapered Fiber Sensor, for Measuring Fa...

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Nandankar, Praful V. Balaji, M. Hemachandu, P. Cheerla, Sreevardhan Pradhan, Manoj Kumar Dabral, Amar Prakash Government College of Engineering Chandrapur Gondwana University Department of Electrical Engineering Maharashtra Gadchiroli442605 India V R Siddhartha Engineering College Department of Mechanical Engineering Andhra Pradesh Vijayawada520007 India Sasi Institute of Technology and Engineering Department of Electrical and Electronics Engineering Andhra Pradesh Tadepalligudem534101 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communications Engineering Andhra Pradesh Vaddeswaram522302 India Srinix College of Engineering Department of Electrical Engineering Odisha Balasore756003 India Graphic Era Deemed to Be University Department of Hospitality Management Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350322842

In this work, a sensor based on Narrowed Optical Fibers (NOF) or Taper, as it is also known, is developed, which allows the measurement of vibrations in electric motors using the cantilever or cantilever bar mechanical model. The objective of this study is to characterize the tapered fiber sensor, based on the vibration measurement range, to accurately measure vibration-induced faults in rotary electric motors. For this, a theoretical study of the mechanical system used is carried out, and then the behavior of the structure is modeled using the ANSYS simulator to determine the frequency values that can be measured with the sensor. Then a practical assembly of the measurement system is developed where a LASER at 1310 nm, an InGasAs 675RE Rifocs photodetector, an ISOTRON model 256-100 commercial accelerometer is used as a light source, for the characterization in frequencies and obtaining the frequency nature of the model. Finally, the system is coupled to electric motors to which vibration faults are introduced that are detected by the developed system. © 2023 ieee.

关键词： Nanocantilevers

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710904

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