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Quantifying Robotic Swarm Coverage 15th

Quantifying Robotic Swarm Coverage

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15th international conference on informatics in control, automation and robotics (ICINCO)

作者： Anderson, Brendon G. Loeser, Eva Gee, Marissa Ren, Fei Biswas, Swagata Turanova, Olga Haberland, Matt Bertozzi, Andrea L. Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA Univ Calif San Diego Dept Math San Diego CA 92093 USA Cornell Univ Ctr Appl Math Ithaca NY 14853 USA Univ Calif Berkeley Ind Engn & Operat Res Berkeley CA 94720 USA Univ Edinburgh Sch Math Edinburgh EH9 3FD Midlothian Scotland Inst Adv Study Sch Math Princeton NJ 08540 USA Cal Poly BioResource & Agr Engn San Luis Obispo CA 93407 USA Univ Calif Los Angeles Dept Math Los Angeles CA 90095 USA

ISBN: (纸本)9783030319939;9783030319922

In the field of swarm robotics, the design and implementation of spatial density control laws has received much attention, with less emphasis being placed on performance evaluation. This work fills that gap by introducing an error metric that provides a quantitative measure of coverage for use with any control scheme. The proposed error metric is continuously sensitive to changes in the swarm distribution, unlike commonly used discretization methods. We analyze the theoretical and computational properties of the error metric and propose two benchmarks to which error metric values can be compared. The first uses the realizable extrema of the error metric to compute the relative error of an observed swarm distribution. We also show that the error metric extrema can be used to help choose the swarm size and effective radius of each robot required to achieve a desired level of coverage. The second bench-mark compares the observed distribution of error metric values to the probability density function of the error metric when robot positions are randomly sampled from the target distribution. We demonstrate the utility of this benchmark in assessing the performance of stochastic control algorithms. We prove that the error metric obeys a central limit theorem, develop a streamlined method for performing computations, and place the standard statistical tests used here on a firm theoretical footing. We provide rigorous theoretical development, computational methodologies, numerical examples, and MATLAB code for both benchmarks.

关键词： Swarm robotics Multi-agent systems Coverage optimization Central limit theorem

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3rd international conference on Smart Computing and informatics, SCI 2018

3rd International Conference on Smart Computing and Informat...

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3rd international conference on Smart Computing and informatics, SCI 2018

ISBN: (纸本)9789811392818

The proceedings contain 75 papers. The special focus in this conference is on Smart Computing and informatics. The topics include: An Empirical Analysis on FDI and ICT in India;Infiltration Loss Affects Toward Groundwater Fluctuation Through CANFIS in Arid Watershed: A Case Study;Skull Stripping of Brain MRI Using Mathematical Morphology;Rainfall Forecasting Through ANN and SVM in Bolangir Watershed, India;skin Melanoma Assessment with Machine-Learning Approach—A Study;a Survey on Techniques for Prediction of Asthma;A Study on Mining of Tumor Pixel Group in Flair Modality Brain MRI;prediction of Flood Using Adaptive Neuro-Fuzzy Inference Systems: A Case Study;an Analysis of Total Risk Management in Performances of Public Sector Banks in India;genetic Algorithm-Based Motif Search Problem: A Review;continuous Wavelets for Pre-processing and Analysis of Cough Signals;the Subset-Sum Problem as an Optimization Problem;predicting a Model for the Financial Risk Tolerance of Retail Investors of Durgapur City on Their Demographic Factors Using Multiple Discriminant Analysis;image Encryption Using Modified Elliptic Curve Cryptography and Hill Cipher;a Review on Advanced Techniques on Plant Pest Detection and Classification;a Comparison of Prediction Capabilities of Bayesian Regularization and Levenberg–Marquardt Training Algorithms for Cryptocurrencies;integration and Rule-Based Pre-processing of Scientific Publication Records from Multiple Data Sources;security Architecture for IoT-Based Home automation;Investigation of the Effects of Critical Success Factors on Enterprise Resource Planning (ERP) Systems Implementation in the United Arab Emirates;a Voice-Based Information Extraction System;driver Drowsiness Detection Using Viola Jones Algorithm;intelligent Auto Visual Tracking;preface.

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Machine Learning Detects Anomalies in OPS-SAT Telemetry 23rd

Machine Learning Detects Anomalies in OPS-SAT Telemetry

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23rd international conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Kotowski, Krzysztof Andrzejewski, Jacek Musial, Alicja Evans, David Zelenevskiy, Vladimir Bammens, Sam Laurinovics, Rodrigo Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland European Space Agency/ESOC Robert-Bosch-Str. 5 Darmstadt64293 Germany Telespazio Germany GmbH Europaplatz 5 Darmstadt64293 Germany IrbGS ltd "Viraki" Ance Parish IrbeneLV-3601 Latvia

ISBN: (纸本)9783031359941

Detecting anomalies in satellite telemetry data is pivotal in ensuring its safe operations. Although there exist various data-driven techniques for the task of determining abnormal parts of the signal, they are virtually never validated over real telemetries. Analyzing such data is challenging due to its intrinsic characteristics, as telemetry may be noisy and affected by incorrect acquisition, resulting in missing parts of the signal. In this paper, we tackle this issue and propose a machine learning approach for detecting anomalies in single-channel satellite telemetry. To validate its capabilities in a practical scenario, we build a dataset capturing the nominal and anomalous telemetry data captured on board OPS-SAT—a nanosatellite launched and operated by the European Space Agency. Our extensive experimental study showed that the proposed algorithm offers high-quality anomaly detection in real-life satellite telemetry, reaching 98.4% accuracy over the unseen test set. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Energy-Based Functional Modelling for control Architecture Design: An Application to Energy Management for a Hybrid Electric Vehicle 14th

Energy-Based Functional Modelling for Control Architecture D...

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14th international conference on informatics in control, automation and robotics (ICINCO)

作者： Mokukcu, Mert Fiani, Philippe Chavanne, Sylvain Taleb, Lahsen Ait Vlad, Cristina Godoy, Emmanuel Sherpa Engn R&D Dept F-92250 La Garenne Colombes France Univ Paris Saclay Univ Paris Sud Cent Supelec CNRSL2SUMR 8506 3 Rue Joliot Curie F-91192 Gif Sur Yvette France

ISBN: (纸本)9783030112929;9783030112912

The increasing complexity of energy systems leads to a growing interest in energy management that is actively studied using modelling methods and simulation tools capable to represent the re system's behavior. In this study, a functional energetic modelling method is proposed to design the control architecture for the management of the energy flow. This method relies on local control loops, a decision manager (DM) and basic equations. When the functional level of abstraction is used to model a complex system, the evaluation of the model accuracy (from an energetic point of view) and the validation of energy management strategies are simplified by fast simulations due to low model complexity. Even if the functional model allows a first-stage validation of the energy allocation within the system, the energy management strategies have to be tested using a more precise model, which is the multi-physical model of the system. The multi-physical modelling level has its own local controllers and global resource manager (GRM) to handle the energy allocation between the different components. The second-stage in the validation is completed by adapting the functional model in order to obtain the high-level controller (i.e. the GRM) for the multi-physical level. The development of the control architecture of the multi-physical model based on the functional model requires two steps: (i) adjusting the functional elements' parameters and (ii) proposing a method to interconnect the models at both levels of representation (functional and multi-physical levels). The modelling and the parametrization of the functional elements are demonstrated on a hybrid electric vehicle (HEV). The GRM design is detailed and the simulation results of the HEV system at multi-physical level are illustrated to validate the system architecture, the component sizing and the energy management strategy. The fuel consumption is evaluated in comparison to the HEV's design specifications.

关键词： control design Energy management Complex systems Modelling Integrated design Systems modelling Interconnected systems System-level design System verification Automotive engineering System architecture

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Smart Monitoring and Disease Detection for Robotic Harvesting of Tomatoes

Smart Monitoring and Disease Detection for Robotic Harvestin...

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Advancements in Computing (ICAC), 2019 international conference on

作者： Imesh Pasindu Sumeera Viraj Ravindu Dilshan Akshith Kalhara Oshada Senaweera Rajitha de Silva Chandimal Jayawardena Sri Lanka Institute of Information Technology Malabe Sri Lanka Lincoln Agri-Robotics Centre Lincoln Institute for Agri-Food Technology University of Lincoln UK Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9781665408639

Tomato is a one of the most popular produced and extensively consumed vegetables in the world. Typical agricultural systems make extensive use of human labor which is more costly and less effective. This research explores the minimization of human labor through automation. The diseases infected by tomato plants are hard to detect. Identifying these diseases in advance would save the cultivation of the disease from spreading, thereby saving the crop. It is also a difficult task to recognize the ripe harvest and experienced labor is required. The efficiency of the harvesting method will be increased by automating the identification process of ripened fruits. Manually picking tomatoes can cause some harm to the fruits during plucking due to inconsistencies in human labor. Such damage will be reduced through a better implemented robotic scheme. This paper presents the development of autonomous system for tomato harvesting and disease detection.

关键词： Costs Navigation Robot kinematics Image processing Production Manipulators Agriculture

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

8th EAI International Conference on Advancement of Science a...

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

ISBN: (纸本)9783030806170

The proceedings contain 74 papers. The special focus in this conference is on Advancement of Science and Technology. The topics include: Earliest-Arrival Route: A Global Optimized Communication for Networked control Systems;Impulsive Noise Mitigation Using Hybrid Nonlinear Preprocessor and Turbo Code in OFDM-PLC System;comparative Analysis of Kalman Filtering and Machine Learning Based Cardiovascular Signal Processing Algorithms;modeling and Analysis of Three-Phase Inverter for Induction Motor Drive for Three-Wheel Electric Vehicle Application;performance Analysis of Multicarrier Modulation Techniques for Next Generation Networks;synchronous Generator Excitation Loss Detection Based on Reactive Power Flow Limit;estimation of Synchrophasor Parameters in the Presence of 3rd & 5th Harmonics and White Gaussian Noise;Performance Analysis of Vertical Sectorization in Sub-6-GHz Frequency Bands for 4G Mobile Network Under Realistic Deployment Scenario;power Loss Reduction and Voltage Profile Improvement of Radial Distribution System Through Simultaneous Network Reconfiguration and Distributed Generation Integration;A Comprehensive Review and Evaluation of Classical MPPT Techniques for a Photovoltaic System;antiviral Activity of Aloe pirottae A. Berger Root Extracts Against Influenza A and B Viruses, Picornaviruses and Dengue Virus: An Endemic Plant Species of Ethiopia;dynamic Performance Evaluation of Type-3 Compensator for Switch-Mode Dc-Dc Converter;inset-Feed Rectangular Microstrip Patch Antenna Array Performance Enhancement for 5G Mobile Applications;blockchain Based Green Coffee Supply Chain Management to Improve Traceability and Transparency (Case Study on Sidama Coffee);wireless Local Area Network Intrusion Detection System Using Deep Belief Networks;Direct Adaptive Fuzzy PI Strategy for a Smooth MPPT of Variable Speed Wind Turbines.

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

8th EAI International Conference on Advancement of Science a...

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

ISBN: (纸本)9783030806200

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Spatial-temporal characteristics and influencing factors of NO2and SO2in the Beijing-Tianjin-Hebei region based on satellite remote sensing 3

Spatial-temporal characteristics and influencing factors of ...

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3rd international conference on Environmental Prevention and Pollution control Technologies, EPPCT 2021

作者： Zhai, Haoran Yao, Jiaqi Qi, Jianwei Wang, Guanghui Zhang, Tao Land Satellite Remote Sensing Application Center Ministry of Natural Resources of P. R. China Beijing100048 China College of Resource Environment and Tourism Capital Normal University Beijing100048 China School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou221116 China

Air is an indispensable natural resource for all human activities. As an essential trace gas in the atmosphere, high NO2 and SO2 will affect the natural environment and human health. Based on the Ozone Monitoring Instrument's data, the temporal and spatial distribution of NO2 and SO2 concentrations in the Beijing-Tianjin-Hebei region from 2005 to 2017 was analyzed. Results showed that, on the annual scale, the concentration increased at first and then decreased. On the monthly scale, both of the two had regular fluctuations with annual cycles. The spatial distribution of pollutants was high in the southeast and low in the northwest. By analyzing the influencing factors of pollutants, it was found that environmental conditions are more the periodic fluctuations and spatial distribution differences of image density, and policy-oriented conditions are the main reason for the concentration trend decline in the later period. © Published under licence by IOP Publishing Ltd.

关键词： Spatial distribution

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Immune Optimization Algorithm for Traveling Salesman Problem Based on Clustering Analysis and Self-Circulation 21

Immune Optimization Algorithm for Traveling Salesman Problem...

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Proceedings of the 3rd international conference on Advanced Information Science and System

作者： Yunqiang Gao Yan Shen Zhe Yang Dapeng Chen Mingxin Yuan School of Mechanical Engineering Jiangsu University of Science and Technology China School of Mechanical and Power Engineering Jiangsu University of Science and Technology China Department of Robotics Jiangsu Institute of automation China

ISBN: (纸本)9781450385862

In order to improve the population diversity during immune optimization of high-dimensional TSP problem, avoid falling into local optimal solutions, and then improve the algorithm's global optimization capability and optimization efficiency, Immune Optimization Algorithm for TSP Based on Cluster Analysis and Self-Circulation, (IOATCS) is proposed. Inspired by cluster analysis, TSP population data is classified and evolved according to the relevance of the problem to improve the efficiency of population optimization; a self-circulation strategy is designed to obtain new offspring through the self-circulation and crossover of the parent body, and then inherit the gene fragments of excellent individuals to the offspring, which improves the global search ability of the algorithm. The test results of six groups of high-dimensional TSP problems show that compared with the basic genetic algorithm, immune genetic algorithm and ant colony algorithm, the planning performance of the algorithm in this paper is the best, and the average relative error and relative error standard deviation of the algorithm are reduced by 10.21% and 4.54% respectively, and the average convergence algebra and convergence algebra standard deviation are reduced by 31.2% and 38.7% respectively, which verifies the strong optimization ability, high optimization efficiency and good stability of the proposed algorithm.

关键词： self-circulation immune evolution high-dimensional TSP cluster analysis adaptability

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Private Cloud in 6G Networks: A Study from the Total Cost of Ownership Perspective 3rd

Private Cloud in 6G Networks: A Study from the Total Cost of...

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3rd EAI international conference on 6G for Future Wireless Networks, 6GN 2020

作者： Chi, Yuanfang Dai, Wei Fan, Yuan Ruan, Jun Hwang, Kai Cai, Wei Alibaba Group Beijing China The Chinese University of Hong Kong Shenzhen Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (纸本)9783030639402

Security and privacy concerns are increasingly important when massive data processing and transferring becomes a reality in the era of the Sixth Generation (6G) Networks. Under this circumstance, it becomes a trend that the enterprises tend to host their data and services on private clouds dedicated to their own use, rather than the public cloud services. However, in contrary to the well-investigated total cost of ownership (TCO) for public clouds, the analytic research on the cost of purchase and operation for private clouds is still a blank. In this work, we first review the state-of-the-art TCO literature to summarize the models, tools, and cost optimization techniques for public clouds. Based on our survey, we envision the TCO modeling and optimization for private clouds by comparing the differences of features between public and private clouds. © 2020, ICST Institute for Computer Sciences, Social informatics and Telecommunications Engineering.

关键词： Queueing networks

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