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arXiv 2025年

作者： Biazetto, Paulo H.F. de Andrade, Gustavo A. Oliveira, Tiago Roux Krstic, Miroslav Post-graduate Program in Automation and Systems Engineering Federal University of Santa Catarina Florianópolis88040-370 Brazil Department of Automation and Systems Engineering Federal University of Santa Catarina Florianópolis88040-370 Brazil Department of Electronics and Telecommunication Engineering State University of Rio de Janeiro Rio de Janeiro20550-900 Brazil Department of Mechanical and Aerospace Engineering University of California San DiegoCA92093-0411 United States

This paper presents the design and analysis of an extremum seeking (ES) controller for scalar static maps in the context of infinite-dimensional dynamics governed by the 1D Euler-Bernoulli (EB) beam Partial Differential Equation (PDE). The beam is actuated at one end (using position and moment actuators). The map’s input is the displacement at the beam’s uncontrolled end, which is subject to a sliding boundary condition. Notably, ES for this class of PDEs remains unexplored in the existing literature. To compensate for PDE actuation dynamics, we employ a boundary control law via a backstepping transformation and averaging-based estimates for the gradient and Hessian of the static map to be optimized. This compensation controller leverages a Schrödinger equation representation of the EB beam and adapts existing backstepping designs to stabilize the beam. Using the semigroup and averaging theory in infinite dimensions, we prove local exponential convergence to a small neighborhood of the unknown optimal point. Finally, simulations illustrate the effectiveness of the design in optimizing the unknown static map. Copyright © 2025, The Authors. All rights reserved.

关键词： Schrodinger equation

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Single Inductor Dual Buck Inverter Classical and Predictive Linear Voltage Controller Comparison

Single Inductor Dual Buck Inverter Classical and Predictive ...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Luis David Patarroyo-Gutierrez Nelson Nayoshi Nakamoto Yamaguti Oscar Mauricio Hernández-Gómez Daniel Abreu Macedo Da Silva School of electronic Engineering Universidad Pedagógica y Tecnológica de Colombia Tunja-Boyacá Colombia Dep. of Automation and Systems Federal University of Santa Catarina Florianopolis SC Brazil Electrical Engineering Graduate Program Federal University of Pará Belem Brazil

This article presents the mathematical model of a 2 KW DBI (Dual Buck Inverter) converter that can be used in renewable energy applications. The inverter operating modes are described with the equations that model their behavior with the activation signals of the MOSFETs. The switching model is built. Simulation results are presented by applying linear control through a PI controller and GPC (Generalized Predictive Controller) hybridized in PID structure; simulation results are recorded in PSIM© verifying the control response due to changes in the load and the input DC voltage level.

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Gait proficiency index in children aged 3.5 to 9.5 years old

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Research on Biomedical engineering 2021年第2期37卷 429-437页

作者： das Neves, Ana Maria Bender Seidenfuss de Souza, Leandro Daniel Aires, Andréia Gomes Souza, Thalita Borges Giacomazzi, Leandro Peserico Dachi, Édison Pereira Baptista, Rafael Reimann School of Technology Graduate Program in Electrical Engineering PUCRS Porto Alegre Brazil School of Health and Life Sciences Undergraduate Program in Physical Education PUCRS Porto Alegre Brazil School of Technology Undergraduate Program in Electrical Engineering PUCRS Porto Alegre Brazil School of Technology Associate Degree Program in Industrial Automation and Embedded Systems SENAI Porto Alegre Brazil School of Technology and School of Health and Life Sciences Pontifical Catholic University of Rio Grande do Sul Av. Ipiranga 6681 Partenon Porto Alegre90619-900 Brazil

Introduction: The purpose of this study is to present a novel approach for gait assessment called gait proficiency index (GPI) using only ground reaction forces (GRF)-derived parameters. Material and methods: Barefoot gait from 51 healthy children was evaluated with the GPI in this study. The participants walked at their self-selected speed along a 6-m walkway with 8 force platforms placed in pairs. The force-time analysis resulted in a dynamic symmetry assessment (DSA) that is the result of vertical GRF component distribution for all gait cycles both the left and right foot. DSA and impulse calculation from GRF led to the calculation of the GPI, which is the relationship between the impulse of load response and mid-stance and impulse of terminal stance and pre-swing of both right and left feet multiplied by the DSA index. The children were divided into three groups with 17 participants each and classified according to age (mean age ± standard deviation): G1 (4.39 ± 0.511), G2 (6.33 ± 0.639), G3 (8.49 ± 0.636). Results: The results show that as children mature, the GPI seems to increase from G1 to G2 and decreases from G2 to G3 and that both the standard deviations and coefficient of variation decrease with the increase of age. Conclusions: This can be an indicative that the index can assess improvements in gait quality through age. However, there was no statistical significance between the groups in this variable. Also, the correlation between either DSA and age or GPI and age found is weak to make other conclusions but that the study of adults should be included to either validate or refute the use of GPI. © 2021, Sociedade Brasileira de Engenharia Biomedica.

关键词： Biophysics

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Towards Real-Time Machining Tool Failure Forecast Approach for Smart Manufacturing systems

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IFAC-PapersOnLine 2022年第2期55卷 548-553页

作者： Nicolas Nebelung Mario D.S. de Oliveira Santos Sofia T. Helena Athon F.C.S. de Moura Leite Matheus B. Canciglieri Anderson L. Szejka Control and Automation Engineering Department Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil Junior Scientific Initiation Program at the Nossa Senhora de Medianeira School and Pontifical Catholic University of Paraná Curitiba – Paraná Brazil Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil

Industry 4.0 is characterized by a dynamic market that constantly looking for new methods to optimize and integrate manufacturing processes. In this context, Artificial Intelligence has gained prominence in problem-solving, such as failure prediction and decision making, thus improving product quality, and consequently bringing competitiveness to the company. Aiming to contribute to this scenario, this research develops a data treatment system that, from an intelligent tool and an interoperable ontological model, automates the prediction and detection of failures in machining machines lines. The system was developed for the prediction of faults in machining lines includes an artificial intelligence formed from prediction algorithms and inferences, it is possible to guarantee the correct treatment and communication of data at different stages of the process. For the experimental research, was used data collected from a machining line of a public dataset. The information is collected and classified by Artificial Intelligence that supports a decision system. The prediction of tool wear would enable the system to infer the type of problem that is causing this wear, a possible root cause, and the needed maintenance based on the ontological inference tool. By this classification of data, it is possible to achieve, through inferences, a reduction in the decision scope, bringing the possible problems caused by the incoming value. The semantic interoperability ensures correct data exchange and processing, which generates a more assertive view of production failures. The system may help companies to increase their productive process by helping them identify future failures in production if applied in a real scenario.

关键词： Industry 4.0 Smart System Artificial Intelligence Machine Learning Ontology Machine Failure Forecast

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Formability of Third Generation Advanced High Strength Steel: Experimental and Theoretical Approach

SSRN

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SSRN 2024年

作者： Butuc, Marilena C. Vincze, Gabriela Santos, Rafael Pereira, António Santos, Abel D. Amaral, Rui L. Barlat, Frederic Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Portugal LASI - Intelligent Systems Associate Laboratory Guimarães Portugal Graduate Program in Metallurgical Engineering Universidade Federal Fluminense Rio de Janeiro Volta Redonda Brazil Faculty of Engineering University of Porto R. Dr. Roberto Frias s/n Porto4200-465 Portugal INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering Portugal Graduate Institute of Ferrous Technology Pohang University of Science and Technology Korea Republic of

The aim of this paper is to evaluate, predict and analyze the plastic properties and formability of third-generation advanced high-strength steel (3genAHSS), with a specific focus on USS CR980XG3™️ AHSS as the reference material. Forming limit diagrams were determined, utilizing a range of experimental methods, including Nakajima tests, Erichsen tests, uniaxial tensile tests, and the Bulge test. A pivotal aspect is the application of an advanced sheet metal forming limit model based on Marciniak-Kuczynski analysis to simulate localized necking onset. Various constitutive equations, such as von Mises, Hill 48, and Yld2000-2d yield conditions, were used in simulation, alongside strain hardening laws like Swift and Voce. Comparative analyses were conducted to assess the accuracy of different models in predicting forming limits, with a particular emphasis on the influence of strain rate sensitivity. The study underscores the significant impact of the experimental method on forming limit values, highlighting that Yld2000-2d and the Swift hardening law with strain rate sensitivity provide optimal reproducibility of experimental data. Furthermore, the research emphasizes the necessity of considering strain rate sensitivity for accurate numerical simulations, stressing the effectiveness of the Marciniak-Kuczynski model when combined with proper constitutive equations in predicting forming limits for USS CR980XG3™️ AHSS. © 2024, The Authors. All rights reserved.

关键词： Strain hardening

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An ultra thin,bright,and sensitive interactive tactile display based on organic mechanoluminescence for dual-mode handwriting identification

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InfoMat 2024年第6期6卷 76-87页

作者： Tingting Hou Wenlang Li Haoyu Wang Yuantian Zheng Chaojie Chen Haoran Zhang Kai Chen Huilin Xie Xin Li Shaoshuai He Siwei Zhang Dengfeng Peng Cheng Yang Jacky W.Y.Lam Ben Zhong Tang Yunlong Zi Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kongthe People's Republic of China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong Kongthe People's Republic of China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenthe People's Republic of China Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)Guangzhouthe People's Republic of China The Hong Kong University of Science and Technology Interdisciplinary Program Office Hong Kong SARthe People's Republic of China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenthe People's Republic of China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenthe People's Republic of China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhenthe People's Republic of China Guangzhou HKUST Fok Ying Tung Research Institute Guangzhouthe People's Republic of China

Visible light-based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users ***,many inorganic mechanoluminescent(ML)materials-based interactive media,typically ZnS-loaded phosphors(ZLPs),have been successfully ***,organic ML materials-based solutions were rarely exploited despite their huge merits of strong structural modification,abundant luminescence property,low cost,easy preparation,and so ***,we propose a novel interactive tactile display(ITD)based on organic ML materials(Cz-A6-dye)and triboelectric nanogenerator,with ultra-brightness(130%enhancement)and ultra-low threshold pressure(57%reduction)as compared to *** proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously,without extra power ***,the relationship between the luminous performance of organic ML materials and mechanical force is quantified,benefiting from the uniform ML layer *** by convolutional neural networks,the high-accuracy recognition(97.1%)for handwriting and identity of users is realized at the same ***,the ITD has great potential for intelligent wearable electronics and classified military applications.

关键词： interactive media organic mechanoluminescence triboelectric nanogenerators

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Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach

Vision-based Semantic Communications for Metaverse Services:...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Guangyuan Liu Hongyang Du Dusit Niyato Jiawen Kang Zehui Xiong Boon Hee Soong Energy Research Institute@NTU Interdisciplinary Graduate Program School of Computer Science and Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Electronic Engineering Nanyang Technological University Singapore

The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect users' behaviour. Achieving real-time synchronization between the virtual bilocation and the user is complex, placing high demands on the Metaverse Service Provider (MSP)'s rendering resource allocation scheme. To tackle this issue, we propose a semantic communication framework that leverages contest theory to model the interactions between users and MSPs and determine optimal resource allocation for each user. To reduce the consumption of network resources in wireless transmission, we use the semantic communication technique to reduce the amount of data to be transmitted. Under our simulation settings, the encoded semantic data only contains 51 bytes of skeleton coordinates instead of the image size of 8.243 megabytes. Moreover, we implement Deep Q-Network to optimize reward settings for maximum performance and efficient resource allocation. With the optimal reward setting, users are incentivized to select their respective suitable uploading frequency, reducing down-sampling loss due to rendering resource constraints by 66.076% compared with the traditional average distribution method. The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

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Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

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arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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Real engineering Problems in an Undergraduate Course: The learning methodologies and assessment tools

Real Engineering Problems in an Undergraduate Course: The le...

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World engineering Education Forum - Global engineering Deans Council (WEEF-GEDC)

作者： Ricardo A. Diogo André L.A.C. Venâncio Maria Angela M. Roveredo Santos Eduardo F.R. Loures Neri dos Santos Knowledge Engineering&Management Graduate Program Federal University of Santa Catarina Florianopolis Brazil Industrial&Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Control and Automation Engineering/Mechatronics Engineering Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781665424899

This paper presents the context of the Ubiquitous Computing course carried out in an Industrial engineering undergraduate program throughout 2020 and the first semester of 2021. This course took advantage of the Institutional Modernization program led by the Control and automation engineering Undergraduate program, which consists in the modernization of undergraduate engineering programs at the Pontifical Catholic University of Paraná. The course aimed to help develop competencies, i.e., a set of knowledge, skills, and attributes aligned with Student Outcomes suggested by ABET. Also, the course proposal brought the productive sector very close to the academic environment, proposing real engineering problems as challenges. However, what are the methods and assessment tools for practical learning in a course with modern elements? This paper proposed the flipped learning and the Challenge-Based Learning Framework with the support of the CDIO Framework as learning methodologies to answer such question. Additionally, quizzes, tests, presentations, rubrics, and peer evaluation were applied as assessment tools to measure the student's progress. Finally, students were listened to about their perceptions during the course. The results suggested that the learning methodologies and assessment tools are suitable for the course context, although some improvements are expected for the following course offers. Moreover, students approved the initiative to bring in real challenges proposed by companies, the mentoring hours, and the feedback about the projects.

关键词： automation Companies Industrial engineering Ubiquitous computing Proposals Mentoring engineering education

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Semantic Communications for Artificial Intelligence Generated Content (AIGC) Toward Effective Content Creation

arXiv

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arXiv 2023年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada

Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed. Particularly, a content generation level is introduced on top of the semantic level that provides a clear outline of how AIGC and SemCom interact with each other to produce meaningful and effective content. Moreover, a novel framework that employs AIGC technology is proposed as an encoder and decoder for semantic information, considering the joint optimization of semantic extraction and evaluation metrics tailored to AIGC services. The framework can adapt to different types of content generated, the required quality and the semantic information utilized. By employing a Deep Q Network (DQN), a case study is presented that provides useful insights into the feasibility of the optimization problem and its convergence characteristics. © 2023, CC BY.

关键词： Wireless networks

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