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9th International Conference on Data science, Technology and Applications, DATA 2020

作者： Abghari, Shahrooz Boeva, Veselka Brage, Jens Grahn, Håkan Department of Computer Science Blekinge Institute of Technology Karlskrona Sweden NODA Intelligent Systems AB Karlshamn Sweden

ISBN: (纸本)9789897584404

In this study, we propose a multi-view clustering approach for mining and analysing multi-view network datasets. The proposed approach is applied and evaluated on a real-world scenario for monitoring and analysing district heating (DH) network conditions and identifying substations with sub-optimal behaviour. Initially, geographical locations of the substations are used to build an approximate graph representation of the DH network. Two different analyses can further be applied in this context: step-wise and parallel-wise multi-view clustering. The step-wise analysis is meant to sequentially consider and analyse substations with respect to a few different views. At each step, a new clustering solution is built on top of the one generated by the previously considered view, which organizes the substations in a hierarchical structure that can be used for multi-view comparisons. The parallel-wise analysis on the other hand, provides the opportunity to analyse substations with regards to two different views in parallel. Such analysis is aimed to represent and identify the relationships between substations by organizing them in a bipartite graph and analysing the substations distribution with respect to each view. The proposed data analysis and visualization approach arms domain experts with means for analysing DH network performance. In addition, it will facilitate the identification of substations with deviating operational behaviour based on comparative analysis with their closely located neighbours. Copyright © 2020 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： District heating

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Vision-based Human Fall Detection systems using Deep Learning: A Review

arXiv

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arXiv 2022年

作者： Alam, Ekram Sufian, Abu Dutta, Paramartha Leo, Marco Department of Computer Science Gour Mahavidyalaya West Bengal India Department of Computer Science University of Gour Banga India Department of Computer and System Sciences Visva-Bharati University India National Research Council of Italy Institute of Applied Sciences and Intelligent Systems Lecce73100 Italy

Human fall is one of the very critical health issues, especially for elders and disabled people living alone. The number of elder populations is increasing steadily worldwide. Therefore, human fall detection is becoming an effective technique for assistive living for those people. For assistive living, deep learning and computer vision have been used largely. In this review article, we discuss deep learning (DL)-based state-of-the-arts non-intrusive (vision-based) fall detection techniques. We also present a survey on fall detection benchmark datasets. For a clear understanding, we briefly discuss different metrics which are used to evaluate the performance of the fall detection systems. This article also gives a future direction on vision-based human fall detection techniques. © 2022, CC BY.

关键词： Fall detection

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A Sociable Robotic Platform to Make Career Advices for Undergraduates 22nd

A Sociable Robotic Platform to Make Career Advices for Under...

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22nd International Conference on Human computer Interaction,HCII 2020

作者： Mithsara, W. K. Malithi Manawadu, Udaka A. De Silva, P. Ravindra S. Robotics and Intelligent Systems Laboratory Department of Computer Science University of Sri Jayewardenepura Nugegoda Sri Lanka Robot Engineering Laboratory Graduate School of Computer Science and Engineering University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9783030601164

Most of the undergraduates couldn’t figure out a proper direction for their future careers since advising depends on the person and students show aversion in revealing their information to other humans. This research focused on creating a social robotic platform to interact with undergraduates in the field of computer science to realize possible career paths, as recent researches show social companion robots tend to form a stronger bond, which helps the addressee to share their information easily. The robot was created as a tabletop robot employing minimalistic design with a friendly view attached with speech synthesis for communicating purposes. Data was collected from 202 persons, who followed a degree in computer science. Data contains their experience, qualifications, and skills. Thereafter an artificial neural network was created using supervised learning to predict the career path with 95% performance accuracy. The experiment was performed by engaging 15 students from the final year who are a doing degree in computer science and they were asked to provide feedback on the interactions with the robot. The gathered responses highlighted robot animacy, interaction, technology and usefulness. Therefore, from the results it can be concluded that a majority of the students accepted the robot, interacted without hesitation and had friendly conversations with the robot where they valued the generated output from the robot. © 2020, Springer Nature Switzerland AG.

关键词： Neural networks

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Ergodic Rate Analysis of RIS-Assisted BAC-NOMA systems Under Nakagami-m Fading

Ergodic Rate Analysis of RIS-Assisted BAC-NOMA Systems Under...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Sarah Basharat Syed Ali Hassan Haejoon Jung Kapal Dev Aamir Mahmood Mikael Gidlund School of Electrical Engineering and Computer Science (SEECS) National University of Sciences & Technology (NUST) Islamabad Pakistan Department of Electronic Engineering Kyung Hee University Yongin South Korea Department of Institute of Intelligent Systems University of Johannesburg South Africa Department of Computer and Electrical Engineering Mid Sweden University Sundsvall Sweden

In this paper, we investigate the reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access-based backscatter communication (BAC-NOMA) system under Nakagami-m fading channels and element-splitting protocol. To evaluate the system performance, we first approximate the composite channel gain, i.e., the product of the forward and backscatter channel gains, as a Gamma random variable via the central limit theorem (CLT) and method of moments (MoM). Then, by leveraging the obtained results, we derive the closed-form expressions for the ergodic rates of the strong and weak backscatter nodes (BNs). To provide further insights, we conduct the asymptotic analysis in the high signal-to-noise ratio (SNR) regime. Our numerical results show an excellent correlation with the simulation results, validating our analysis, and demonstrate that the desired system performance can be achieved by adjusting the power reflection and element-splitting coefficients. Moreover, the results reveal the significant performance gain of the RIS-assisted BAC-NOMA system over the conventional BAC-NOMA system.

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User distributions in shard-based blockchain network: queueing modeling, game analysis, and protocol design 21

User distributions in shard-based blockchain network: queuei...

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22nd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2021

作者： Chen, Canhui Ma, Qian Chen, Xu Huang, Jianwei School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen China Pazhou Lab Guangzhou China School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Chinese University of Hong Kong Shenzhen Hong Kong

ISBN: (纸本)9781450385589

Sharding is one of the most promising and practical methods to achieve horizontal scalability of blockchain networks. However, the increasing number of cross-shard transactions in blockchain sharding protocols may degrade the system throughput. In this paper, we investigate how to distribute users properly in the shard-based blockchains to boost the system transaction performance. We first build an open Jackson queueing network model to capture users' transaction dynamics on shards. Then we cast users' interactions as a shard-based blockchain game, wherein each user aims to minimize its transaction confirmation time and transaction fee. We investigate the equilibrium of the game, and design a polynomial-time algorithm to find efficient equilibria with good system performance. We further design a novel sharding protocol with dynamic user distribution for the permissionless blockchain, and the protocol can maintain good performance in long-term dynamic environment. Extensive numerical results using realistic blockchain transaction data demonstrate that the proposed algorithm and the designed protocol can achieve superior performance for shard-based blockchains. © 2021 ACM.

关键词： Game theory

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A Generic Load Flow Solution for Droop-Controlled AC Microgrids Considering Electric Vehicle Loads 11

A Generic Load Flow Solution for Droop-Controlled AC Microgr...

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11th IEEE International Conference on Power Electronics, Drives and Energy systems, PEDES 2024

作者： Meena, Ghanshyam Mathur, Akhilesh Singh, V.P. Murari, Krishna Kamalasadan, Sukumar Malaviya National Institute of Technology Department of Electrical Engineering Rajasthan Jaipur302017 India The University of Toledo Electrical Engineering and Computer Science Department ToledoOH43606 United States University of North Carolina at Charlotte Power Energy and Intelligent Systems Laboratory Epic Department of Electrical Engineering CharlotteNC28223 United States

Microgrids (MGs) have become more unpredictable due to integration of renewable generation sources. Several methods are used to solve load flow problems in MGs. Load flow analysis is a complex problem for islanded MGs due to the absence of slack bus and dependency of active power generation of droop-controlled DGs on frequency. In this paper, a Modified Newton Raphson (MNR) approach is used to perform load flow analysis of isolated MGs considering various types of electric vehicle (EV) loads. The presented method has been validated on 6-bus and 38-bus test systems of the islanded microgrid to give an accurate and simple approach for computing the load flow solutions. © 2024 IEEE.

关键词： Islanding

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MUCOR: A Multiparty Conversation Based Robotic Interface to Evaluate Job Applicants 22nd

MUCOR: A Multiparty Conversation Based Robotic Interface to ...

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22nd International Conference on Human computer Interaction,HCII 2020

作者： Senaratna, H.A.S.D. Manawadu, Udaka A. Hansika, W.K.N. Samarasinghe, S.W.A.M.D. De Silva, P. Ravindra S. Robotics and Intelligent Systems Laboratory Department of Computer Science University of Sri Jayewardenepura Nugegoda Sri Lanka Robot Engineering Laboratory Graduate School of Computer Science and Engineering University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9783030601164

"MUCOR" is a robotic interface made up of three small-sized, table-top robots that go through Linkedin profiles of job applicants and discuss the applicants’ information. Robots categorize applicants into ordered levels based on their competencies mentioned. Robots built following minimalist design concepts consist of a cylindrical head and a body that occupy less space. A score is calculated for each candidate and categorized into levels by a model built including Agglomerative Clustering and Gaussian Mixture Model. The model itself identifies the number of levels into which the applicants can be categorized, through the iterations. MUCOR is built for job recruiters who spend more time to find background information about applicants prior to an interview. Conversation among robots and the user creates a Passive Social Interface in which the user does not involve in the conversation, but gain knowledge by listening. The recruiter only has to input the LinkedIn IDs into a mobile application and listen to the conversation among robots. MUCOR was experimented with professional recruiters and their feedback highlighted that the synchronization of speech with the robot’s body movements has a fair impact on the user experience about the robot behavior. © 2020, Springer Nature Switzerland AG.

关键词： Human robot interaction

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SmartCHANGE: AI-based long-term health risk evaluation for driving behaviour change strategies in children and youth 3

SmartCHANGE: AI-based long-term health risk evaluation for d...

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3rd International Conference on Applied Mathematics and computer science, ICAMCS 2023

作者： Rescic, Nina Alberts, Janna Altenburg, Teatske M. Chinapaw, Mai J. M. De Nigro, Antonio Fenoglio, Dario Gjoreski, Martin Gradisek, Anton Jurak, Gregor Kiourtis, Athanasios Kyriazis, Dimosthenis Langheinrich, Marc Mancuso, Elena Mavrogiorgou, Argyro Pechenizkiy, Mykola Pratola, Roberto Ribeiro, Jose Soric, Maroje Taj, Fawad Tammelin, Tuija H. Vastenburg, Martijn Vilanova, Anna Vrijkotte, Tanja G. M. Lustrek, Mitja Jožef Stefan Institute Department of Intelligent Systems Ljubljana Slovenia ConnectedCare Research & Development Nijmegen Netherlands Vrije Universiteit Amsterdam Amsterdam Public Health Research Institute Department of Public and Occupational Health Amsterdam Umc Amsterdam Netherlands Informatica S.p.A. Engineering Ingegneria Rome Italy Università della Svizzera Italiana Faculty of Informatics Lugano Switzerland University of Ljubljana Faculty of Sports Ljubljana Slovenia University of Piraeus Department of Digital Systems Piraeus Greece Eindhoven University of Technology Department of Mathematics and Computer Science Eindhoven Netherlands University of Porto Faculty of Sport Porto Portugal Jamk University of Applied Sciences Likes School of Health and Social Studies Jyväskylä Finland

ISBN: (纸本)9798350324266

The SmartCHANGE project, a Horizon-Europe Research & Innovation project that has been ongoing since May 2023 and is scheduled to conclude in April 2027, aims to develop AI-driven decision-support tools to identify and reduce the long-term risk of non-communicable chronic diseases (NCDs) in children and youth. NCDs have become a significant public health burden in developed countries, with common risk factors including obesity, low physical fitness, and unhealthy lifestyle habits. Childhood and adolescence are critical periods for establishing healthy habits, and early intervention can prevent or delay the onset of NCDs later in life. However, current tools for identifying high-risk individuals mainly focus on adults, leading to missed opportunities for early detection. The SmartCHANGE project aims to address this gap by creating trustworthy AI tools that accurately assess risk factors in children and youth and promote optimised strategies for risk reduction. The paper outlines the plan for the project from the project's proposed methodologies, including dataset utilisation, data cleaning, risk prediction models (basic and complex), and the implementation of federated learning. Additionally, it discusses user experience aspects such as participatory design, suggested applications, and the evaluation of project outcomes. © 2023 IEEE.

关键词： Health risks

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Deep Learning of First-Order Nonlinear Hyperbolic Conservation Law Solvers

SSRN

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SSRN 2023年

作者： Morand, Victor Müller, Nils Weightman, Ryan Keimer, Alexander Piccoli, Benedetto Bayen, Alexandre M. Ecole Polytechnique Palaiseau France Department of Electrical Engineering and Computer Science University of California BerkeleyCA United States Max Planck Institute for Software Systems Saarland Informatics Campus Germany Max Planck Institute for Intelligent Systems Germany Department of Mathematics Rutgers University NJ United States Department of Mathematics FAU Erlangen-Nürnberg Germany

In this contribution, we study the numerical approximation of scalar conservation laws by computational optimization of the numerical flux function in a first-order finite volume method. The cell-averaging inherent to finite volume schemes presents a challenge in the design of such numerical flux functions toward achieving high solution accuracy. Dense neural networks, as well as (piecewise) polynomials, serve as function classes for the numerical flux. Using a parametrization of such a function class, we optimize the numerical flux with respect to its solution accuracy on a set of Riemann problems for which we have closed-form solutions. By design, our resulting first-order finite volume schemes are *** show empirically that the proposed schemes can achieve higher accuracy than the Godunov and EnquistOsher method on a wide range of *** proposed method can be applied to the inverse problem, i.e., the data-driven synthesis of macroscopic physical laws for real-world flux phenomena. © 2023, The Authors. All rights reserved.

关键词： Finite volume method

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Riemannian Online Optimistic Algorithms with Dynamic Regret

引用

IEEE Transactions on Automatic Control 2025年

作者： Wang, Xi Yuan, Deming Hong, Yiguang Hu, Zihao Wang, Lei Shi, Guodong University of New South Wales School of Electrical Engineering & Telecommunications SydneyNSW2052 Australia Nanjing University of Science and Technology School of Automation Nanjing210094 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Hong Kong University of Science and Technology Department of Mathematics Hong Kong Zhejiang University College of Control Science and Engineering Zhejiang 310058 China The University of Sydney Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering NSW2006 Australia

In this paper, we consider Riemannian online convex optimization with dynamic regret, which involves minimizing the cumulative loss difference between a learner's decisions and a sequence of adaptive decisions across dynamic environments over time on Riemannian manifolds. First, we propose Riemannian Online Optimistic Gradient Descent (R-OOGD), which extends the classical optimistic algorithms to Riemannian manifolds, requiring one gradient inquiry per round. We then propose Riemannian Adaptive Online Optimistic Gradient Descent (R-AOOGD) by incorporating the meta-expert framework into R-OOGD. We analyze the dynamic regret of R-OOGD and R-AOOGD in terms of the regularity of the sequence of cost functions and comparators. The dynamic regret bound matches the results in Euclidean space and with a scale adjustment of O(1+κ D2/√1-KD2) related to the sectional curvature lower bound κ, sectional curvature upper bound and feasible set diameter. Finally, we provide numerical experiments to illustrate the performance of the proposed algorithms. © 1963-2012 IEEE.

关键词： Optimization algorithms

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