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Dynamic Resilient Network Games with Applications to Multi-Agent Consensus

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arXiv 2020年

作者： Nugraha, Yurid Cetinkaya, Ahmet Hayakawa, Tomohisa Ishii, Hideaki Zhu, Quanyan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama226-8502 Japan Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

A cyber security problem in a networked system formulated as a resilient graph problem based on a game-theoretic approach is considered. The connectivity of the underlying graph of the network system is reduced by an attacker who removes some of the edges whereas the defender attempts to recover them. Both players are subject to energy constraints so that their actions are restricted and cannot be performed continuously. For this two-stage game, which is played repeatedly over time, we characterize the optimal strategies for the attacker and the defender in terms of edge connectivity and the number of connected components of the graph. The resilient graph game is then applied to a multi-agent consensus problem. We study how the attacks and the recovery on the edges affect the consensus process. Finally, we also provide numerical simulation to illustrate the results. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

Towards advanced interfaces for citizen curation

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Towards advanced interfaces for citizen curation

2020 AVI2CH Workshop on Advanced Visual Interfaces and Interactions in Cultural Heritage, AVI2CH 2020

作者： Bruni, Luis Emilio Diaz, Lily Gangemi, Aldo Daga, Enrico Kuflik, Tsvi Mulholland, Paul Pescarin, Sofia Damiano, Rossana Lieto, Antonio Peroni, Silivio Wecker, Alan Department of Architecture Design and Media Technology Alborg University Denmark Department of Media Media lab Aalto University Aalto Finland DHARC - Department of Classical Philology and Italian Studies University of Bologna ISTC-CNR Rome Italy Knowledge Media Institute Open University Milton Keynes United Kingdom Information Systems University of Haifa Haifa Israel CNR ISPC Rome Italy Computer Science and CIRMA University of Turin Turin Italy DHARC - Department of Classical Philology and Italian Studies University of Bologna Rome Italy

The SPICE project builds on the growing trend for museums, rather than providing an authoritative view, to present multiple voices related to their collection and exhibitions. In SPICE, an approach we term citizen curation is proposed as a way of supporting visitors to share their own interpretations of museum objects and reflect on the variety of interpretations contributed by others. In order to capture a wide range of voices, interfaces will be designed specifically to engage minority groups that tend to be under-represented in cultural activities. To achieve this goal, the interface will need to be intuitive, aesthetic and accessible for different audiences. The paper presents the challenges we face and initial proposals for engaging visitors in citizen curation. © Copyright 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Museums

Generation expansion planning in the presence of wind power plants using a genetic algorithm model

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arXiv 2020年

作者： Sahragard, Ali Falaghi, Hamid Farhadi, Mahdi Mosavi, Amir Estebsari, Abouzar Khorasan Regional Electricity Company Birjand Iran Department of Electric and Computer Engineering University of Birjand Iran Department of Computer and Industries Birjand University of Technology Birjand Iran Department of Informatics J. Selye University Komarno94501 Slovakia School of the Built Environment and Architecture London South Bank University London United Kingdom

One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on Genetic Algorithm (GA) for GEP in the presence of wind power plants. Since it is desired to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow obtaining the maximum reasonable amount of wind penetration in the network. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be *** Codes 68T01 Copyright © 2020, The Authors. All rights reserved.

关键词： Electric power generation

NeuroPod: a real-time neuromorphic spiking CPG applied to robotics

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arXiv 2019年

作者： Gutierrez-Galan, Daniel Dominguez-Morales, Juan P. Perez-Peña, Fernando Linares-Barranco, Alejandro Robotics and Computer Technology Lab Universidad de Sevilla Spain Department of Computer Architecture and Technology Universidad de Cádiz Spain

Initially, robots were developed with the aim of making our life easier, carrying out repetitive or dangerous tasks for humans. Although they were able to perform these tasks, the latest generation of robots are being designed to take a step further, by performing more complex tasks that have been carried out by smart animals or humans up to date. To this end, inspiration needs to be taken from biological examples. For instance, insects are able to optimally solve complex environment navigation problems, and many researchers have started to mimic how these insects behave. Recent interest in neuromorphic engineering has motivated us to present a real-time, neuromorphic, spike-based Central Pattern Generator of application in neurorobotics, using an arthropod-like robot. A Spiking Neural Network was designed and implemented on SpiNNaker. The network models a complex, online-change capable Central Pattern Generator which generates three gaits for a hexapod robot locomotion. Reconfigurable hardware was used to manage both the motors of the robot and the real-time communication interface with the Spiking Neural Networks. Real-time measurements confirm the simulation results, and locomotion tests show that NeuroPod can perform the gaits without any balance loss or added delay. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

Adaptive Window Size Based Deep Neural Network for Driving Maneuver Prediction

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Adaptive Window Size Based Deep Neural Network for Driving M...

Chinese Control and Decision Conference, CCDC

作者： Jun Gao Honghui Zhu Yi Lu Murphey School of Electromechanical and Architecture Engineering Jianghan University Wuhan China School of Logistics Engineering Wuhan University of Technology Wuhan China Department of Electrical and Computer Engineering University of Michigan-Dearborn Dearborn Michigan USA

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Driving maneuver prediction is one of the most challenging tasks in Advanced Driver Assistance System (ADAS), it can provide an early notification for ADAS to predict dangerous circumstances and take appropriate actions. However, it is difficult to well modeling the driving maneuver process due to the complexity and uncertainty of traffic status. To address this issue, we propose a novel model, denoted as DMPM, which uses deep learning method for Driving Maneuver Prediction (DMP) from multi-modal data, i.e. front view videos and vehicle signals. Firstly, with Adaptive Window Size Selector (AWSS), DMPM is able to dynamically identify the optimal sliding window size for the input data. Secondly, the Global Context Video Network (GCV Network) is proposed combing with Root-ResNet+Weighted Channel Dropout (WCD) architecture to extract the features from multi-modal data efficiently. Specially, including the Global Context (GC) block, GCV Network has an ability of modeling long-range dependency. Finally, a Long Short-Term Memory (LSTM) network that captures temporal dependencies is leveraged for driving maneuver prediction. The experimental results show that the DMPM is capable of learning the latent features of driving maneuver and achieving significantly better performance than other popular models on a real-world driving data set.

关键词： Microsoft Windows Videos Vehicles computer architecture Adaptive systems Feature extraction Computational efficiency

Features of the cadmium chalcogenide substrates with surface nanostructure

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Materials Today: Proceedings 2021年 35卷 626-629页

作者： Tetiana Mazur Mykhailo Slyotov Myroslav Mazur Volodymyr Prokopiv Oksana Kinzerska Oleksii Slyotov Department of Solid State Physics and Chemistry/Faculty of Physics and Technology Vasyl Stefanyk Precarpathian National University 57 Shevchenko Str. Ivano-Frankivsk 76019 Ukraine Department of General and Applied Physics/Institute of Architecture Construction and Power Engineering Ivano-Frankisvsk National Technical University of Oil and Gas 15 Karpatska Str. Ivano-Frankivsk 76019 Ukraine Department of Optics/Physical Technical and Computer Science Institute Publishing and Printing Yuriy Fedkovych Chernivtsi National University 2 Kotsubinsky Str. 58012 Chernivtsi Ukraine Department of Physics of Semiconductors and Nanostructures/Physical Technical and Computer Science Institute Yuriy Fedkovych Chernivtsi National University 2 Kotsubinsky Str. 58012 Chernivtsi Ukraine

The effect of single crystalline CdTe, CdSe, CdS substrates normalizing annealing on their optical properties was investigated, and the surface nanostructure formation was determined by the study of optical transmission spectra, photoluminescence and atomic force microscopy (AFM) topograms. Possibility obtaining of intense luminescence in the border region, formed by interband recombination and transitions due to size quantization of the charge carrier energy, is determined.

关键词： Cadmium chalcogenides Normalizing annealing Optical transmission Photoluminescence Size quantization of energy

Transforming disaster risk reduction with AI and big data: Legal and interdisciplinary perspectives

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arXiv 2024年

作者： Chun, Kwok P. Octavianti, Thanti Dogulu, Nilay Tyralis, Hristos Papacharalampous, Georgia Rowberry, Ryan Fan, Pingyu Everard, Mark Francesch-Huidobro, Maria Migliari, Wellington Hannah, David M. Marshall, John Travis Calasanz, Rafael Tolosana Staddon, Chad Ansharyani, Ida Dieppois, Bastien Lewis, Todd R. Ponce, Juli Ibrean, Silvia Ferreira, Tiago Miguel Peliño-Golle, Chinkie Mu, Ye Delgado, Manuel Espinoza, Elizabeth Silvestre Keulertz, Martin Gopinath, Deepak Li, Cheng School of Architecture and Environment University of the West of England United Kingdom World Meteorological Organization Genève Switzerland Construction Agency Hellenic Air Force Mesogion Avenue 227-231 Cholargos15561 Greece Department of Topography School of Rural Surveying and Geoinformatics Engineering National Technical University of Athens Greece Georgia State University College of Law AtlantaGA United States Department of Geography Hong Kong Baptist University Hong Kong Department of Geography The University of Hong Kong Hong Kong Law School University of Barcelona Catalonia Spain School of Geography Earth & Environmental Sciences University of Birmingham United Kingdom Georgia State University College of Law United States Department of Computer Science and Systems Engineering Universidad de Zaragoza Spain Department of Agriculture Universitas Samawa Indonesia Coventry University Coventry United Kingdom University of the West of England United Kingdom UN Volunteer United Nations Volunteers Hermann-Ehlers-Strasse 10 Bonn Germany College of Arts Technology and Environment School of Engineering University of the West of England United Kingdom EcoWaste Coalition Philippines Philippines Department of Geography University of California Santa Barbara United States University of the West of England Faculty of Business and Law United Kingdom Inclima Department of Ecology Yangzhou University China

Managing complex disaster risks requires interdisciplinary efforts. Breaking down silos between law, social sciences, and natural sciences is critical for all processes of disaster risk reduction. This enables adaptive systems for the rapid evolution of AI technology, which has significantly impacted the intersection of law and natural environments. Exploring how AI influences legal frameworks and environmental management, while also examining how legal and environmental considerations can confine AI within the socioeconomic domain, is essential. From a co-production review perspective, drawing on insights from lawyers, social scientists, and environmental scientists, principles for responsible data mining are proposed based on safety, transparency, fairness, accountability, and contestability. This discussion offers a blueprint for interdisciplinary collaboration to create adaptive law systems based on AI integration of knowledge from environmental and social sciences. Discrepancies in the use of language between environmental scientists and decision-makers in terms of usefulness and accuracy hamper how AI can be used based on the principles of legal considerations for a safe, trustworthy, and contestable disaster management framework. When social networks are useful for mitigating disaster risks based on AI, the legal implications related to privacy and liability of the outcomes of disaster management must be considered. Fair and accountable principles emphasise environmental considerations and foster socioeconomic discussions related to public engagement. AI also has an important role to play in education, bringing together the next generations of law, social sciences, and natural sciences to work on interdisciplinary solutions in harmony. Although emerging AI approaches can be powerful tools for disaster management, they must be implemented with ethical considerations and safeguards to address concerns about bias, transparency, and privacy. The responsible execu

关键词： Decision making

Big mobility data reveals hyperlocal air pollution exposure disparities in the Bronx, New York

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Nature Cities

Nature Cities 2024年第8期1卷 512-521页

作者： Iacopo Testi An Wang Sanjana Paul Simone Mora Fábio Duarte Paolo Santi Carlo Ratti Erica Walker Marguerite Nyhan Senseable City Lab Department of Urban Studies and Planning Massachusetts Institute of Technology Cambridge MA USA Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong SAR China Department of Computer Science Norwegian University of Science and Technology Trondheim Norway Istituto di Informatica e Telematica Consiglio Nazionale delle Ricerche Pisa Italy ABC Department Politecnico di Milano Milan Italy School of Public Health Brown University Providence RI USA School of Engineering and Architecture University College Cork Cork Ireland

Air pollution disproportionately affects socially disadvantaged populations. Our study bridges the existing gap in quantifying mobility-based exposure and its associated disparity issues. We combined the granular mobility of over 500,000 unique anonymized users daily and hyperlocal air pollution data in 100 × 100-m grid cells to quantify disparities in particulate matter exposure in a racially diverse and dense urban area of New York City. Our approach advances the study of exposure and its disparity from individualized exposure tracking to a population-representative scale. We observed apparently different spatial patterns between personal exposure and exposure disparities, noting that people from Hispanic-majority and low-income neighborhoods were those most severely and disproportionately exposed to fine particulate matter (PM2.5) pollution. We reveal that race and ethnicity are much stronger indicators of exposure disparity than income. Our study further demonstrates that within-group variation contributes a major portion to exposure disparities, suggesting more granular mitigation plans are needed to target high-exposure individuals from socially disadvantaged groups in addition to generic air quality improvement.

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Rockburst prediction using artificial intelligence techniques:A review

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岩石力学通报（英文）

岩石力学通报（英文） 2024年第3期3卷 1-13页

作者： Yu Zhang Kongyi Fang Manchao He Dongqiao Liu Junchao Wang Zhengjia Guo School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China Thomas Lord Department of Computer Science University of Southern CaliforniaLos Angeles90007CAUSA

Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation *** disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict *** rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a *** the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst *** previous research,several scholars have attempted to summarize the application of AI techniques in rockburst ***,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive *** on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI ***,pertinent definitions of rockburst and its associated hazards are ***,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each ***,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.

关键词： Rockburst Rockburst prediction Artificial intelligence techniques