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arXiv 2025年

作者： Kabir, Muhammad Ashad Roy, Nidita Hossain, Md. Ekramul Featherston, Jill Ahmed, Sayed School of Computing Mathematics and Engineering Charles Sturt University BathurstNSW2795 Australia Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Complex Systems Research Group Faculty of Engineering The University of Sydney DarlingtonNSW2008 Australia School of Medicine Cardiff University Cardiff WalesCF14 4YS United Kingdom Foot Balance Technology Pty Ltd WestmeadNSW2145 Australia Offloading Clinic High-Risk Foot Services Nepean Hospital KingswoodNSW2750 Australia Charles Sturt University Panorama Ave BathurstNSW2795 Australia

Chronic wounds represent a major global health challenge, imposing substantial economic and social burdens worldwide. Traditional methods of visually inspecting and identifying wound tissue are often time-intensive, costly, inaccurate, imprecise, and inconsistent, with a high degree of variability between clinicians. Deep learning (DL) techniques have emerged as promising solutions for medical wound tissue segmentation. However, a notable limitation in this field is the lack of publicly available labelled datasets and a standardised performance evaluation of state-of-the-art DL models on such datasets. This study addresses this gap by comprehensively evaluating various DL models for wound tissue segmentation using a novel dataset. We have curated a dataset comprising 147 wound images exhibiting six tissue types: slough, granulation, maceration, necrosis, bone, and tendon. The dataset was meticulously labelled for semantic segmentation employing supervised machine learning techniques. Three distinct labelling formats were developed – full image, patch, and superpixel. Our investigation encompassed a wide array of DL segmentation and classification methodologies, ranging from conventional approaches like UNet, to generative adversarial networks such as cGAN, and modified techniques like FPN+VGG16. Also, we explored DL-based classification methods (e.g., ResNet50) and machine learning-based classification leveraging DL features (e.g., AlexNet+RF). In total, 82 wound tissue segmentation models were derived across the three labelling formats. Our analysis yielded several notable findings, including identifying optimal DL models for each labelling format based on weighted average Dice or F1 scores. Notably, FPN+VGG16 emerged as the top-performing DL model for wound tissue segmentation, achieving a dice score of 82.25%. This study provides a valuable benchmark for evaluating wound image segmentation and classification models, offering insights to inform future research and

关键词： Semantic Segmentation

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Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

arXiv

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： Robotics

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Heuristic Search for Nonlinear Substitutions for Cryptographic Applications

Lecture Notes on Data Engineering and Communications Technol...

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Lecture Notes on Data engineering and Communications Technologies 2023年 180卷 288-298页

作者： Kuznetsov, Oleksandr Frontoni, Emanuele Kandiy, Sergey Smirnov, Oleksii Ulianovska, Yuliia Kobylianska, Olena Department of Political Sciences Communication and International Relations University of Macerata Via Crescimbeni 30/32 Macerata62100 Italy Department of Information and Communication Systems Security Faculty of Comupter Science V. N. Karazin Kharkiv National University 4 Svobody Sq Kharkiv61022 Ukraine Department of Information Engineering Marche Polytechnic University Via Brecce Bianche 12 Ancona60131 Italy Cybersecurity & Software Academic Department Central Ukrainian National Technical University 8 University Avenue Kropyvnytskyi25006 Ukraine Department of Computer Science and Software Engineering University of Customs and Finance Vernadskogo Street 2/4 Dnipro49000 Ukraine

Heuristic algorithms are used to solve complex computational problems quickly in various computer applications. Such algorithms use heuristic functions that rank the search alternatives instead of a full enumeration of possible variants. The algorithm selects, at each iteration, an alternative with the best value for the heuristics. In this paper, we investigate the complex computational problem of finding highly nonlinear substitutions (S-boxes) in the space of 8-bit permutations. The generation of S-boxes is an important field of research, since nonlinear substitutions are widely used in various cryptographic applications. For instance, S-boxes in symmetric ciphers are responsible for cryptographic strength to linear, differential, algebraic, and other types of cryptanalysis. We propose new heuristics in the form of a cost function, calculated with the Walsh-Hadamard transform. We use the Hill Climbing Algorithm to find highly nonlinear substitutions. Our experiments demonstrate that the new heuristics give good results – it takes about 80,000 iterations of the algorithm to generate 8-bit S-boxes with a nonlinearity of 104. For the optimized parameters, the number of iterations of the algorithm is comparable to the best known results, which confirms the significance and value of the research. © The Author(s).

关键词： Cost functions

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A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power systems

arXiv

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arXiv 2022年

作者： Hallaji, Ehsan Razavi-Far, Roozbeh Wang, Meng Saif, Mehrdad Fardanesh, Bruce The Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada The Faculty of Computer Science University of New Brunswick FrederictonNBE3B 5A3 Canada The Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States The Department of Research and Technology Development New York Power Authority White PlainsNY10601 United States

This paper presents a novel data-driven framework to aid in system state estimation when the power system is under unobservable false data injection attacks. The proposed framework dynamically detects and classifies false data injection attacks. Then, it retrieves the control signal using the acquired information. This process is accomplished in three main modules, with novel designs, for detection, classification, and control signal retrieval. The detection module monitors historical changes in phasor measurements and captures any deviation pattern caused by an attack on a complex plane. This approach can help to reveal characteristics of the attacks including the direction, magnitude, and ratio of the injected false data. Using this information, the signal retrieval module can easily recover the original control signal and remove the injected false data. Further information regarding the attack type can be obtained through the classifier module. The proposed ensemble learner is compatible with harsh learning conditions including the lack of labeled data, concept drift, concept evolution, recurring classes, and independence from external updates. The proposed novel classifier can dynamically learn from data and classify attacks under all these harsh learning conditions. The introduced framework is evaluated w.r.t. real-world data captured from the Central New York Power System. The obtained results indicate the efficacy and stability of the proposed framework. © 2022, CC BY.

关键词： Cyber Physical System

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Phase transitions of heliconical smectic-C and heliconical nematic phases in banana-shaped liquid crystals

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Physical Review E 2020年第5期101卷 050701(R)-050701(R)页

作者： Akihiko Matsuyama Department of Physics and Information Technology Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka Fukuoka 820-8502 Japan

A mean-field theory is introduced to describe heliconical nematic (NTB), heliconical smectic-C (SmCTB), and biaxial heliconical smectic-C (SmCTB,b) phases with mirror symmetry breaking. We extend our previous theories of the NTB phase to the heliconical smectic-C phases, by taking into account one-dimensional spatial ordering of smectic layers. The calculated phase diagrams on the temperature–alkyl chain length plane show a rich variety of phase transitions: first- and second-order NTB−SmCTB transitions, etc., including tricritical, tetracritical, and multicritical points. Our theory is qualitatively consistent with an experimental phase diagram.

关键词： Liquid crystal phase transitions Biaxial liquid crystals Liquid crystals Smectic liquid crystals

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Introduction of the Study Results of the Moon Electrical Power systems 22

Introduction of the Study Results of the Moon Electrical Pow...

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22nd IAA Symposium on Building Blocks for Future Space Exploration and Development at the 75th International Astronautical Congress, IAC 2024

作者： Oka, Noriaki Yamauchi, Kenji Ijichi, Koichi Yanagawa, Hiroki Kashimura, Osamu Uchida, Atsushi Tanaka, Koji Mitani, Tomohiko Honjo, Kazuhiko Ishikawa, Ryo Ishimura, Kosei Fujino, Yoshiyuki Fujita, Kazuhisa Itoh, Kenji Kawakami, Yoshihiro Ishikawa, Yoji Yamaguchi, Hiroshi Ogawa, Akihiko Japan Space Systems 3-5-8 Shibakoen Minato-ku Tokyo105-0011 Japan Emerging Technologies and Security Division Mitsubishi Research Institute Inc. 10-3 Nagatacho 2-chome Chiyoda-ku Tokyo100-8141 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo-ku Kanagawa Sagamihara252-5210 Japan Kyoto University Gokasho Kyoto Uji611-0011 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Dept. of Modern Mechanical Engineering School of Creative Science and Engineering Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo169-8555 Japan Faculty of Science and Engineering Toyo University 2100 Kujirai Saitama-ken Kawagoe350-8585 Japan 1955-1 Kurematsu-cho chuo-ku Shizuoka Hamamatsu431-1202 Japan Department of Electrical and Electronic Engineering College of Engineering Kanazawa Institute of Technology 7-1 Ohgigaoka Ishikawa Nonoichi921-8501 Japan Obayashi Future Lab. Technology Division Obayashi Corporation 2-15-2 Konan Minato-ku Tokyo108-8502 Japan 492 Minosho-machi Nara-ken YamatoKoriyama639-1186 Japan Electronics Technologies Office Technologies Development Department IHI Aerospace Co. Ltd. 900 Fujiki Gunma-ken Tomioka-shi370-2398 Japan

ISBN: (纸本)9798331312251

Since the year of 2021, Ministry of Economy, Trade and Industry (METI) started work on the energy issues on the Moon including the feasibility study of the electrical power system with Mitsubishi Research Institute, Japan Space systems, Institute of Space and Astronautical science of Japan Aerospace Exploration Agency (JAXA), the universities and the industries. The architecture of the Moon electrical power infrastructure is found to be more like those of the power infrastructure of the earth than current satellite power system, and consisted of the power generation, power distribution grid and the power storage, and supplying electrical power to the consumer. The differences are that the environment of the Moon such as the vacuum and temperature condition, the influence of the regolith, etc. should have to be considered, and also the transportation cost of the construction is the key factor for the necessary technology to be selected. Of course, the technologies already established by the International Space Station (ISS) should be applied where necessary such as in the human habitable area. And more feature of the Moon is that the power generation on the Moon orbit and be sent to the surface or the inside the Permanent Shadow Region (PSR) other than on the surface of the Moon. The main consumer of the power system until the year 2050th is the water extraction and then the electrolysis of the water for, such as, the propellant for the transportation means and the electricity for the human habitant. The results of the system feasibility study of the Moon power architecture and also the electric power system team activities including the discussion with the hydrogen production team are going to be introduced. Copyright © 2024 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Space power generation

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Machine learning for modelling unstructured grid data in computational physics: a review

arXiv

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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

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Proof of Space Transactions: A Novel Blockchain Protocol for Secure Authentication of Satellite Transactions

Research Square

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Research Square 2021年

作者： Torky, Mohamed Goda, Essam Hassanein, Aboul Ella Snasel, Vaclav Gaber, Tarek Higher Institute of Computer Science and Information Systems Culture & Science City Computer Science 6 October City 12573 Egypt Computer Science Cairo12611 Egypt Faculty of Computer and Artificial Intelligence Cairo University Information Technology Cairo12631 Egypt VSB-Technical University of Ostrava Czech Republic School of Science Engineering and Environment University of Salford ManchesterM5 4WT United Kingdom Faculty of Computers and Informatics Suez Canal University Ismailia41522 Egypt Egypt

Blockchain technology can play a vital role in the space industry and satellite communication. This disruptive technology can build decentralized and secure protocols for processing and manipulating space transactions in the form of space digital tokens (SDTs). Tokenizing space transactions in the form of SDTs will enable various blockchain-based applications in the space industry. Moreover, blockchain protocols based on smart contracts can be utilized to authenticate many space transactions and P2P communications in a transparent, verifiable, and secure manner. This paper proposes a new blockchain-based solution for managing and securing satellite transactions using a novel concept called SDT. SDT is then used to develop a new blockchain protocol called proof of space transactions (PoST), which is then used in proposing a new blockchain-based protocol for authenticating satellite transactions. The proposed PoST protocol is implemented and simulated using the Ethereum blockchain. Five metrics are used to evaluate the protocol’s performance: Ethereum GAZ, read latency, transaction latency, read throughput, and transaction throughput. The performance evaluation results proved the efficiency and reliability of PoST in managing and securing satellite transactions. © 2021, CC BY.

关键词： Blockchain

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Distributed optimal load frequency control with stochastic wind power generation

arXiv

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arXiv 2021年

作者： Silani, Amirreza Cucuzzella, Michele Scherpen, Jacquelien M.A. Yazdanpanah, Mohammad Javad Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

Motivated by the inadequacy of conventional control methods for power networks with a large share of renewable generation, in this paper we study the (stochastic) passivity property of wind turbines based on the Doubly Fed Induction Generator (DFIG). Differently from the majority of the results in the literature, where renewable generation is ignored or assumed to be constant, we model wind power generation as a stochastic process, where wind speed is described by a class of stochastic differential equations. Then, we design a distributed control scheme that achieves load frequency control and economic dispatch, ensuring the stochastic stability of the controlled network. © 2021, CC BY.

关键词： Stochastic systems

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Adaptive control for flow and volume regulation in multi-producer district heating systems

arXiv

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arXiv 2021年

作者： Martinez, Juan Eduardo Machado Cucuzzella, Michele Pronk, Nina Scherpen, Jacquelien M.A. The Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands The Department of Electrical Computer and Biomedical Engineering University of Pavia via Ferrata 5 Pavia27100 Italy

Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored-decentralized-adaptive control scheme addressing this problem whilst offering closed-loop stability guarantees. We focus on a system configuration comprising multiple heat producers, consumers and storage tanks exchanging energy through a common distribution network, which are features of modern and prospective district heating installations. The proposed controller is based on passivity, backstepping and (indirect) adaptive control theory. Copyright © 2021, The Authors. All rights reserved.

关键词： District heating

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