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A study for Motion-Planning Method Resident-tracking Robot based on Reinforcement Learning 30

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A study for Motion-Planning Method Resident-tracking Robot b...

30th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2019

作者： Sugimoto, Masashi Yoshioka, Takashi Ishii, Kohei Nonaka, Shogo Deguchi, Mikio Tsuzuki, Shinji Hiran, Masatsugu Electrical and Electronic Engineering Course Ehime University Division of Electrical and Electronic Engineering and Computer Science 3 Bunkyo-cho Matsuyama City Ehime Pref.790-8577 Japan National Institute of Technology Kagawa College Department of Electrical and Computer Engineering 355 Chokushi-cho Takamatsu City Kagawa Pref.761-8058 Japan National Institute of Technology Kagawa College. Department of Electro-Mechanical Systems Engineering 355 Chokushi-cho Takamatsu City Kagawa Pref.761-8058 Japan National Institute of Technology Tsuyama College Department of Integrated Science and Technology 624-1 Numa Tsuyama City Okayama Pref.790-8577 Japan National Institute of Technology Niihama College Department of Electronics and Control Engineering 7-1 Yakumo-cho Niihama City Ehime Pref.790-8580 Japan National Institute of Technology Niihama College Department of Electrical Engineering and Information Science 7-1 Yakumo-cho Niihama City Ehime Pref.792-8580 Japan

ISBN: (纸本)9781728126746

Among the advanced countries, especially in Japan, we are facing on the decreasing birthrate and aging population ahead of the world. In recent, population of single-living elder, and elderly people have been taking care by same-aged person, have been actualized. Unfortunately, the population of caregivers is decreasing according to year. In this situation, the Elderly Person Watching System has been focused on. Especially, robotics, Internet of Things, and Artificial Intelligence technology have been having high affinity with this system. In this study, firstly, the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. The whole tasks are working based on Reinforcement Learning. Thus, the behavior algorithm of the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. From the verification experiment, the simulation results showed the proposed method has been acquired actions to switch the desired task. © 2019 IEEE.

关键词： Reinforcement learning

Uplink-downlink duality between multiple-access and broadcast channels with compressing relays

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arXiv 2020年

作者： Liu, Liang Liu, Ya-Feng Patil, Pratik Yu, Wei the Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong the State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Edward S. Rogers Sr. Department of Electrical and Computer Engineering the University of Toronto the Department of Statistics and Data Science and the Machine Learning Department Carnegie Mellon University PittsburghPA15213 United States The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 10 King’s College Road TorontoONM5S3G4 Canada

—Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers;the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear programming

Condition Monitoring of a Campus Microgrid Elements using Smart Sensors

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Procedia computer Science 2019年 163卷 109-116页

作者： Kaisar R. Khan Muhammad Shoaib Siddiqui Yazed Al Saawy Nurul Islam Atiqur Rahman Department of Electrical Engineering and Computer Science McNeese State University Lake Charles Louisiana 70609 USA Faculty of Computer & Information Systems Islamic University of Madinah Madinah 42351 KSA British Columbia Institute of Technology Canada

A Microgrid (MG) is an independent grid with both load and its own generation that has the option to be connected to the grid or can be islanded. Intelligent monitoring and control of MG make it as a building block for smart grid technology. With automation and distributed control, load and generation management can be done remotely. We are currently running a campus MG with high efficiency combined heat and power (CHP) generation and renewable energy sources. The space heating is achieved by the recaptured unused heat from CHP generators. The rotatory loads connected to the MG is monitored by the smart wireless enabled sensors that can be accessed by using the internet. A distributed control system (DCS) from our industry partner ABB Inc. (800- XA system) is providing remote control and protection of MGs critical components using multiple industry standard communication protocol (Modbus, Profibus etc.). The study shows that the controlling of water flow to the CHP generator by using remote automation technology provide higher thermal recovery for space heating. Also the smart monitoring and distributed control provide energy savings and warning for preventive maintenance

关键词： Microgrid internet of thing building energy management condition monitoring

Signal Estimation and System Identification With Nonlinear Dynamic Sensors

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Signal Estimation and System Identification With Nonlinear D...

Control Technology and Applications (CCTA),

作者： Julian Berberich Mario Sznaier Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Department of Electrical and Computer Engineering Northeastern University Boston MA USA

We consider the problem of estimating the output of an unknown discrete-time linear time-invariant system and identifying a model of the system, where only measurements via a nonlinear dynamic sensor with known dynamics are available. The main result of this paper is a rank-constrained semidefinite program, which provides an equivalent characterization of this identification and estimation problem. This extends existing results from Wiener system identification to the more general case that the nonlinear block exhibits dynamic behavior, which is a commonly found scenario in practical applications. Notably, the result can be applied in the presence of nonlinear sensors with general non-invertible system dynamics. Two examples are used to illustrate the applicability of our approach.

关键词： Linear systems Nonlinear dynamical systems Sensor systems Estimation Transfer functions Noise measurement

Metrics Reloaded: Recommendations for image analysis validation

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arXiv 2022年

作者： Maier-Hein, Lena Reinke, Annika Godau, Patrick Tizabi, Minu D. Buettner, Florian Christodoulou, Evangelia Glocker, Ben Isensee, Fabian Kleesiek, Jens Kozubek, Michal Reyes, Mauricio Riegler, Michael A. Wiesenfarth, Manuel Emre Kavur, A. Sudre, Carole H. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Rädsch, Tim Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Jorge Cardoso, M. Cheplygina, Veronika Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian Ginneken, Bram Van Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kofler, Florian Kopp-Schneider, Annette Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rajpoot, Nasir Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Smeden, Maarten Van Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben Van Varoquaux, Gaël Jäger, Paul F. Heidelberg Division of Intelligent Medical Systems and HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt-Marburg Germany Heidelberg Goethe University Frankfurt Germany Department of Medicine Goethe University Frankfurt Germany Department of Informatics Frankfurt Cancer Insititute Germany Department of Computing Imperial College London London United Kingdom Heidelberg Division of Medical Image Computing and HI Applied Computer Vision Lab Germany Institute for AI in Medicine University Medicine Essen Essen Germany Centre for Biomedical Image Analysis Faculty of Informatics Masaryk University Brno Czech Republic ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Bern Switzerland Simula Metropolitan Center for Digital Engineering Oslo Norway UiT The Arctic University of Norway Romsø Norway Heidelberg Division of Biostatistics Germany Heidelberg Division of Intelligent Medical Systems Division of Medical Image Computing HI Applied Computer Vision Lab Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Heidelberg Division of Medical Image Computing Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. It was developed by a large international consortium in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint – a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. © 2022, CC BY.

关键词： Semantic Segmentation

Time Series Forecasting of New Cases and New Deaths Rate for COVID-19 using Deep Learning Methods

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arXiv 2021年

作者： Ayoobi, Nooshin Sharifrazi, Danial Alizadehsani, Roohallah Shoeibi, Afshin Gorriz, Juan M. Moosaei, Hossein Khosravi, Abbas Nahavandi, Saeid Chofreh, Abdoulmohammad Gholamzadeh Goni, Feybi Ariani Klemeš, Jiří Jaromír Mosavi, Amir Department of Mathematics Savitribai Phule Pune University Pune411007 India Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Department of Signal Theory Networking and Communications Universidad de Granada Spain Department of Mathematics Faculty of Science University of Bojnord Iran Sustainable Process Integration Laboratory - SPIL NETME Centre Faculty of Mechanical Engineering Brno University of Technology - VUT Brno Technická 2896/2 Brno616 69 Czech Republic Department of Management Faculty of Business and Management Brno University of Technology VUT Brno Kolejní 2906/4 Brno612 00 Czech Republic Faculty of Civil Engineering Technische Universität Dresden Dresden01069 Germany John von Neumann Faculty of Informatics Obuda University Budapest1034 Hungary School of Economics and Business Norwegian University of Life Sciences 1430 Norway

The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs to many countries. Predicting the number of new cases and deaths during this period can be a useful step in predicting the costs and facilities required in the future. The purpose of this study is to predict new cases and deaths rate one, three and seven-day ahead during the next 100 days. The motivation for predicting every n days (instead of just every day) is the investigation of the possibility of computational cost reduction and still achieving reasonable performance. Such a scenario may be encountered real-time forecasting of time series. Six different deep learning methods are examined on the data adopted from the WHO website. Three methods are LSTM, Convolutional LSTM, and GRU. The bidirectional extension is then considered for each method to forecast the rate of new cases and new deaths in Australia and Iran countries. This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series. To the best of our knowledge, this is the first time that Bi-GRU and Bi-Conv-LSTM models are used for prediction on COVID-19 new cases and new deaths time series. The evaluation of the methods is presented in the form of graphs and Friedman statistical test. The results show that the bidirectional models have lower errors than other models. Several error evaluation metrics are presented to compare all models, and finally, the superiority of bidirectional methods is determined. This research could be useful for organizations working against COVID-19 and determining their long-term plans. Copyright © 2021, The Authors. All rights reserved.

关键词： Coronavirus

Exact Recovery of Extended Targets Using Multistatic Interferometric Measurements via Generalized Wirtinger Flow

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arXiv 2019年

作者： Son, Il-Young Yonel, Bariscan Yazici, Birsen Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute 110 8th Street TroyNY12180 United States

In this paper, we present a novel approach that can exactly recover extended targets in wave-based multistatic interferometric imaging, based on Generalized Wirtinger Flow (GWF) theory [1]. Interferometric imaging is a generalization of phase retrieval, which arises from cross-correlation of measurements from pairs of receivers in multistatic configuration. Unlike standard Wirtinger Flow, GWF theory guarantees exact recovery for arbitrary lifted forward models that satisfy the restricted isometry property over rank-1, positive semi-definite (PSD) matrices with a sufficiently small restricted isometry constant (RIC). To this end, we design a deterministic, lifted forward model for interferometric multistatic radar satisfying the exact recovery conditions of the GWF theory. Our results quantify a lower limit on the pixel spacing and the minimal sample complexity for exact multistatic radar imaging via GWF. We provide a numerical study of our RIC and pixel spacing bounds, which shows that GWF can achieve exact recovery with super-resolution. While our primary interest lies in radar imaging, our method is also applicable to other multistatic wave-based imaging problems such as those arising in acoustics and geophysics. Copyright © 2019, The Authors. All rights reserved.

关键词： Pixels

Nonlinear compact localized modes in flux-dressed octagonal-diamond photonic lattice

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arXiv 2021年

作者： Stojanović, M.G. Gündoğdu, S. Leykam, D. Angelakis, D.G. Krasić, M. Stojanović Stepić, M. Maluckov, Aleksandra COHERENCE Vinča Institute of Nuclear Sciences University of Belgrade National Institute of the Republic of Serbia P.O.B. 522 Belgrade11001 Serbia Center for Theoretical Physics of Complex Systems Institute for Basic Science Daejeon34126 Korea Republic of Department of Physics Humboldt-Universität zu Berlin Newtonstrasse 15 Berlin12489 Germany Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore117543 Singapore School of Electrical and Computer Engineering Technical University of Crete Chania73100 Greece Faculty of Technology University of Niš Leskovac16000 Serbia

Tuning the values of artificial flux in the two-dimensional octagonal-diamond lattice drives topological phase transitions, including between singular and non-singular flatbands. We study the dynamical properties of nonlinear compact localized modes that can be continued from linear flatband modes. We show how the stability of the compact localized modes can be tuned by the nonlinearity strength or the applied artificial flux. Our model can be realized using ring resonator lattices or nonlinear waveguide arrays. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical lattices

An Online Approach to Physical Watermark Design

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arXiv 2019年

作者： Liu, Hanxiao Mo, Yilin Yan, Jiaqi Xie, Lihua Johansson, Karl H. School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation and BNRist Tsinghua University China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper considers the problem of designing physical watermark signals in order to optimally detect possible replay attack in a linear time-invariant system, under the assumption that the system parameters are unknown and need to be identified online. We first provide a replay attack model, where an adversary replays the previous sensor data in order to fool the system. A physical watermarking scheme, which leverages a random control input as a watermark to detect the replay attack, is then introduced. The optimal watermark signal design problem is cast as an optimization problem, which aims to achieve the optimal trade-off between control performance and intrusion detection. An online watermarking design and system identification algorithm is provided to deal with systems with unknown parameters. We prove that the proposed algorithm converges to the optimal one and characterize the almost sure convergence rate. A numerical example and an industrial process example are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Intrusion detection