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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： N.A. Likhachov A.V. Likhachov Department of structural mechanics Novosibirsk State University of Architecture and Civil Engineering NSUACE (Sibstrin) Novosibirsk Russia Research group of computer science and applied mathematics Institute of Automation and Electrometry IAE SB RAS Novosibirsk Russia

The problem of automatic analysis of X-ray images of large reinforced concrete structures is considered. The aim is to improve the accuracy of the evaluation of the shape and size of projections of internal cracks in the armature. The analysis is based on the classification of image elements by brightness threshold. In this case, it is complicated by the fact that the image has low contrast. To increase it, it is proposed to use an entropy filter whose window size is consistent with the noise level in the image. The study, including a computational experiment, confirmed the effectiveness of the proposed method.

关键词： Brightness Entropy Filtering Detectors Industrial engineering Microsoft Windows Concrete

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Comprehensive review of optimization strategies for phase change materials: Techniques, applications, and challenges in thermal storage systems

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International Communications in Heat and Mass Transfer 2025年 166卷

作者： Izadi, Mohsen Pop, Ioan Shehzad, Sabir Ali Alqurashi, Faris Mohamed, Mohamed H. Hajjar, Ahmad Mahariq, Ibrahim Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Engineering & Technology Duy Tan University Da Nang Viet Nam Mechanical Engineering Department Faculty of Engineering Lorestan University Khorramabad Iran Department of Applied Mathematics Babes-Bolyai University Cluj-Napoca Romania Department of Mathematics COMSATS University Islamabad Sahiwal57000 Pakistan Department of Mechanical Engineering College of Engineering University of Bisha P.O. Box 551 Bisha61922 Saudi Arabia Mechanical Engineering Dept. College of Engineering and Architecture Umm Al-Qura University P.O. 5555 Makkah Saudi Arabia Center for Environmental Intelligence and College of Engineering and Computer Science VinUniversity Hanoi Viet Nam College of Engineering and Architecture Gulf University for Science and Technology Mishref India Najjad Zeenni Faculty of Engineering Al Quds University Jerusalem Korea Republic of University College Korea University Seoul02481 Taiwan Department of Medical Research China Medical University Hospital China Medical University Taichung Jordan Applied Science Research Center Applied Science Private University Amman Jordan

Phase Change Materials (PCMs) are widely recognized for their potential in thermal energy storage systems due to their high latent heat capacity. However, their practical application is significantly hindered by low thermal conductivity, which limits the charging and discharging rates of energy. This review provides a comprehensive and critical synthesis of recent passive techniques developed to enhance the thermal performance of PCMs. These include finned structures, porous media, nanoparticle dispersion, geometrical modifications, and multi-PCM strategies. Quantitative comparisons show that the use of fins can reduce melting time by up to 65 %, while metallic porous matrices can improve thermal conductivity by over 500 %. Incorporation of nanoparticles has demonstrated up to 25 % enhancement in heat transfer rates, albeit with increased viscosity. Geometrical innovations and multi-PCM layering have enabled tailored thermal responses across temperature ranges, suitable for applications such as solar thermal systems and building-integrated energy storage. Furthermore, this review identifies trade-offs associated with each method, including design complexity, cost, and material compatibility, and presents a comparative performance table to guide selection based on system requirements. Hybrid enhancement strategies, such as nanoparticle-doped PCMs embedded in metal foams, are also proposed as a promising direction for future research. The review concludes with specific, forward-looking insights, highlighting opportunities for PCM-based solutions in solar desalination, cold-chain transport, and passive building cooling under real-world constraints. © 2025 Elsevier Ltd

关键词： Metal foams

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QM-FOrMS: A portable and cost-effective upper extremity rehabilitation system

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Smart Health 2019年 14卷

作者： Lin, Feng Ajay, Jerry Langan, Jeanne Cavuoto, Lora Nwogu, Ifeoma Subryan, Heamchand Xu, Wenyao ICSR College of Computer Science and Technology Zhejiang University United States Department of Computer Science and Engineering University at Buffalo (SUNY) United States Department of Rehabilitation Science University at Buffalo (SUNY) United States Department of Industrial and Systems Engineering University at Buffalo (SUNY) United States Buffalo School of Architecture and Planning University at Buffalo (SUNY) United States Department of Computer Science Rochester Institute of Technology United States

Long-term rehabilitation opportunities are critical for millions of individuals with chronic upper limb motor deficits striving to improve their motor performance. While formal rehabilitation is well organized in the acute stages of stroke, there is minimal professional support of rehabilitation across the lifespan. In this paper, we introduce an upper extremity rehabilitation system, the Quality of Movement Feedback-Oriented Measurement System (QM-FOrMS), by integrating cost-effective portable sensors and clinically verified motion quality analysis towards individuals with upper limb motor deficits. Specifically, QM-FOrMS is comprised of an eTextile pressure sensitive mat, named Smart Mat, a sensory can, named Smart Can, and a mobile device. A personalizable and adaptive upper limb rehabilitation program is developed, including both unilateral and bilateral functional activities which can be selected from a list or custom designed to further tailor the program to the individual. © 2019 Elsevier Inc.

关键词： Customized exercise programs Quality of movement Stroke rehabilitation Upper extremity rehabilitation

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Efficient reward-based structural plasticity on a SpiNNaker 2 prototype

arXiv

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arXiv 2019年

作者： Yan, Yexin Kappel, David Neumärker, Felix Partzsch, Johannes Vogginger, Bernhard Höppner, Sebastian Furber, Steve Maass, Wolfgang Legenstein, Robert Mayr, Christian Technische Universität Dresden Chair of Highly Parallel VLSI Systems and Neuromorphic Circuits Dresden Germany Technische Universität Graz Institute for Theoretical Computer Science Graz Austria University of Manchester School of Computer Science Manchester United Kingdom Bernstein Center for Computational Neuroscience III Physikalisches Institut-Biophysik Georg-August Universität Göttingen Germany

Advances in neuroscience uncover the mechanisms employed by the brain to efficiently solve complex learning tasks with very limited resources. However, the efficiency is often lost when one tries to port these findings to a silicon substrate, since brain-inspired algorithms often make extensive use of complex functions such as random number generators, that are expensive to compute on standard general purpose hardware. The prototype chip of the 2nd generation SpiNNaker system is designed to overcome this problem. Low-power ARM processors equipped with a random number generator and an exponential function accelerator enable the efficient execution of brain-inspired algorithms. We implement the recently introduced reward-based synaptic sampling model that employs structural plasticity to learn a function or task. The numerical simulation of the model requires to update the synapse variables in each time step including an explorative random term. To the best of our knowledge, this is the most complex synapse model implemented so far on the SpiNNaker system. By making efficient use of the hardware accelerators and numerical optimizations the computation time of one plasticity update is reduced by a factor of 2. This, combined with fitting the model into to the local SRAM, leads to 62% energy reduction compared to the case without accelerators and the use of external DRAM. The model implementation is integrated into the SpiNNaker software framework allowing for scalability onto larger systems. The hardware-software system presented in this work paves the way for power-efficient mobile and biomedical applications with biologically plausible brain-inspired algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Random number generation

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HPC AI500: A Benchmark Suite for HPC AI Systems 1st

HPC AI500: A Benchmark Suite for HPC AI Systems

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Jiang, Zihan Gao, Wanling Wang, Lei Xiong, Xingwang Zhang, Yuchen Wen, Xu Luo, Chunjie Ye, Hainan Lu, Xiaoyi Zhang, Yunquan Feng, Shengzhong Li, Kenli Xu, Weijia Zhan, Jianfeng State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Dover DE United States Beijing Academy of Frontier Sciences and Technology Beijing China State University of New York Buffalo United States Department of Computer Science and Engineering The Ohio State University Columbus United States National Supercomputing Center in Shenzhen Shenzhen China National Supercomputing Center in Changsha Changsha China National Supercomputing Center in Jinan Jinan China Texas Advanced Computing Center The Texas University at Austin Austin United States

ISBN: (纸本)9783030328122

In recent years, with the trend of applying deep learning (DL) in high performance scientific computing, the unique characteristics of emerging DL workloads in HPC raise great challenges in designing, implementing HPC AI systems. The community needs a new yard stick for evaluating the future HPC systems. In this paper, we propose HPC AI500—a benchmark suite for evaluating HPC systems that running scientific DL workloads. Covering the most representative scientific fields, each workload from HPC AI500 is based on real-world scientific DL applications. Currently, we choose 14 scientific DL benchmarks from perspectives of application scenarios, data sets, and software stack. We propose a set of metrics for comprehensively evaluating the HPC AI systems, considering both accuracy, performance as well as power and cost. We provide a scalable reference implementation of HPC AI500. The specification and source code are publicly available from http://***/HPCAI500/***. Meanwhile, the AI benchmark suites for datacenter, IoT, Edge are also released on the BenchCouncil web site. © 2019, Springer Nature Switzerland AG.

关键词： Benchmarking

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Identification of Delay Thresholds Representing the Perceived Quality of Enterprise Applications

Identification of Delay Thresholds Representing the Perceive...

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International Workshop on Quality of Multimedia Experience, QoMEx

作者： Kathrin Borchert Stanislav Lange Thomas Zinner Matthias Hirth Chair of Communication Networks Am Hubland Institute of Computer Science Würzburg Germany

Modern enterprise applications are often designed as distributed architectures, e.g., thin client computing and thus degradations in network related Quality of Service (QoS) parameters may also negatively impact the user-perceived Quality of Experience (QoE) of the application. In this work, we create a model to predict the perceived application quality based on measurements of objective technical parameters. For this, we gathered a data set in a cooperating enterprise over a timespan of nearly three months. As the obtained data set is subject to bias that originates from seasonal effects as well as a limited and predefined set of technical parameters, we further evaluate how to identify segments of the data that lead to misclassification. Last, we quantify the trade-off between the gain in the QoE prediction accuracy and the amount of filtered data.

关键词： Quality of experience Monitoring Tools Quality of service Delays Companies

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Phonon fluctuation diagnostics: Origin of charge order in AV3Sb5 kagome metals

arXiv

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arXiv 2025年

作者： Enzner, Stefan Berges, Jan Schobert, Arne Oh, Dongjin Kang, Mingu Comin, Riccardo Thomale, Ronny Wehling, Tim Sante, Domenico Di Sangiovanni, Giorgio Institut für Theoretische Physik und Astrophysik and Würzburg-Dresden Cluster of Excellence ct.qmat Universität Würzburg Würzburg97074 Germany U Bremen Excellence Chair Bremen Center for Computational Materials Science MAPEX Center for Materials and Processes University of Bremen Bremen28359 Germany Institut für Theoretische Physik Universität Bremen Bremen28359 Germany I. Institute of Theoretical Physics University of Hamburg Hamburg22607 Germany Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering University of California at San Diego La Jolla CA92037 United States The Hamburg Centre for Ultrafast Imaging Hamburg22761 Germany Department of Physics and Astronomy University of Bologna Bologna40127 Italy

The microsopic origin of the charge-density wave (CDW) in AV3Sb5 (A = K, Rb, Cs) kagome metals remains a longstanding question, often revolving around electron-phonon coupling and purely electronic mechanisms involving Van Hove scenarios, nesting, and sublattice interference. To reveal the processes driving the CDW transition, we combine ab-initio calculations analysis of the phonon self-energy and angle-resolved photoemission spectroscopy (ARPES). Our momentum-resolved study, supported by ARPES data, reveals that lattice instabilities in the V-135 family of kagome metals appear to also be driven by electronic states far from high-symmetry points, where these states exhibit the strongest coupling with the phonon modes responsible for the CDW distortion. Footing on an interpretation scheme based on phonon fluctuation diagnostics, our work challenges and revises theories that so far have exclusively attributed CDW formation to nesting effects close to the Fermi level. © 2025, CC BY.

关键词： Photoelectron spectroscopy

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Information Freshness-Aware Task Offloading in Air-Ground Integrated Edge Computing Systems

arXiv

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arXiv 2020年

作者： Chen, Xianfu Wu, Celimuge Chen, Tao Liu, Zhi Zhang, Honggang Bennis, Mehdi Liu, Hang Ji, Yusheng VTT Technical Research Centre of Finland Finland Graduate School of Informatics and Engineering University of Electro-Communications Tokyo Japan Department of Mathematical and Systems Engineering Shizuoka University Japan Zhejiang University Hangzhou China Centre for Wireless Communications University of Oulu Finland Department of Electrical Engineering and Computer Science Catholic University of America United States Information Systems Architecture Research Division National Institute of Informatics Tokyo Japan

This paper studies the problem of information freshness-aware task offloading in an air-ground integrated multi-access edge computing system, which is deployed by an infrastructure provider (InP). A third-party real-time application service provider provides computing services to the subscribed mobile users (MUs) with the limited communication and computation resources from the InP based on a long-term business agreement. Due to the dynamic characteristics, the interactions among the MUs are modelled by a non-cooperative stochastic game, in which the control policies are coupled and each MU aims to selfishly maximize its own expected long-term payoff. To address the Nash equilibrium solutions, we propose that each MU behaves in accordance with the local system states and conjectures, based on which the stochastic game is transformed into a single-agent Markov decision process. Moreover, we derive a novel online deep reinforcement learning (RL) scheme that adopts two separate double deep Q-networks for each MU to approximate the Q-factor and the post-decision Q-factor. Using the proposed deep RL scheme, each MU in the system is able to make decisions without a priori statistical knowledge of dynamics. Numerical experiments examine the potentials of the proposed scheme in balancing the age of information and the energy consumption. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Eager to Learn vs. Quick to Complain? How a socially adaptive robot architecture performs with different robot personalities

Eager to Learn vs. Quick to Complain? How a socially adaptiv...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ana Tanevska Francesco Rea Giulio Sandini Lola Cañamero Alessandra Sciutti Department of Robotics Brain and Cognitive Science Italian Institute of Technology (IIT) Genova Italy Embodied Emotion Cognition and (Inter-)Action (EECAiA) Lab School of Computer Science University of Hertfordshire Hatfield United Kingdom Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology (IIT) Genova Italy

A social robot that is aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. We are interested in exploring how would an adaptive architecture function and personalize to different users when given different initial values of its variables, i.e. when implementing the same adaptive framework with different robot personalities. Would an architecture that learns very quickly outperform a slower but steadier learning profile? To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and test different robot profiles.

关键词： Robots computer architecture Face Testing Skin Torso Visualization

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Automatic Generation of Neural Network Topology to Forecast the International Integration Processes

Automatic Generation of Neural Network Topology to Forecast ...

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International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： L. Bilgaeva E. Sadykova V. Filippov The Chair “Computer Science Systems” East Siberia State University of Technology and Management ESSUTM Ulan-Ude Russia The Laboratory “Nature management issues” Baikal Institute of Nature Management SB RAS BINM SB RAS Ulan-Ude Russia

The article is devoted to the automatic generation of neural network topology based on genetic algorithm to solve the problem of forecasting indicators of international integration processes. The paper proposes and implements a modification of the classic algorithm NEAT, consisting in the automatic selection of activation functions, which allowed to expand the set of possible solutions. The proposed method of predicting targets using the window method based on pre-predicted factor variables. This approach significantly increases the accuracy of forecasting.

关键词： Training Network topology Encoding Topology Biological neural networks Neurons Genetic algorithms

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