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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Ambrogio, Giuseppina Borgia, Carmine Bortolini, Marco Catapano, Gerardo Conforti, Domenico De Napoli, Luigi Gagliardi, Francesco Galizia, Francesco Gabriele Guido, Rosita Longo, Francesco Mirabelli, Federica Mirabelli, Giovanni Mundo, Domenico Regattieri, Alberto Saffioti, Maria Rosaria Scordamaglia, Gabriele Solina, Vittorio Umbrello, Domenico Veltri, Pierpaolo University of Calabria Department of Mechanical Engineering Energy Engineering and Management Engineering Italy University of Bologna Department of Industrial Engineering Italy University of Calabria Department of Computer Engineering Modeling Electronics and Systems Engineering Italy

Industry 5.0 emphasizes human-centric approaches in technological advancement, particularly crucial in healthcare applications such as prosthetics development. While individual technologies like additive manufacturing, machine learning, digital twins, and tissue engineering have shown promise in prosthetics innovation, their integration remains a significant challenge. This paper presents a novel multidisciplinary framework developed through the National Centre for High-Performance Computing (CN-HPC) project, which addresses the gap between individual technological capabilities and their coordinated application in personalized prosthetics development. The framework, implemented through collaboration between six research groups from two universities, employs the House of Quality methodology to align technological integration with patient needs. Our approach encompasses a comprehensive seven-step process, from initial patient requirements definition through virtual modeling, production process optimization, virtual sensing, machine learning enhancement, digital twin simulation, to advanced tissue engineering. A data model facilitates seamless information exchange between different technological domains and research groups. This research contributes to the field by providing a scalable, human-centered framework for technology integration in medical device development, potentially extending beyond prosthetics to other healthcare applications. The proposed framework represents a significant step toward realizing the full potential of Industry 5.0 in healthcare manufacturing through the systematic integration of advanced technologies for delivering personalized prosthetic solutions. © 2024 The Authors. Published by Elsevier B.V.

关键词： Tissue engineering

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research on the simulation and optimization of enterprise information factory graphics based on computer 3D technology 3

Research on the simulation and optimization of enterprise in...

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3rd international conference on computers, Information Processing and advanced education, CIPAE 2022

作者： Yang, Xia Chengdu Polytechnic Sichuan Chengdu China

ISBN: (纸本)9781665468121

The rapid development of computer technology has led more and more enterprises to enter the era of information-based production management. Virtual reality technology and digital factory, as an important part of enterprise information construction, have been accepted by more and more enterprises, and have played an important economic benefit in it. In this paper, based on virtual reality technology, three modules of layout simulation, process planning and logistics simulation of the digital factory are analyzed, and simulation models are constructed, and optimization schemes are proposed. Through experimental simulation, the utilization rate of each equipment and the quantity of finished products in the production plant were compared and analyzed. The simulation results show that the optimized scheme improves the actual production capacity and productivity of the workshop and saves the cost of investment, thus proving the effectiveness of the optimized scheme. © 2022 IEEE.

关键词： Virtual reality

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Implementing a Wide Frequency Range Tightly Coupled Wireless Charging System Using Hybrid Topology 4

Implementing a Wide Frequency Range Tightly Coupled Wireless...

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4th international conference on computers, Information Processing and advanced education, CIPAE 2023

作者： Wu, Xiaorui Liang, Jiatian Xiao, Jing Gong, Wenlan Mo, Yuhong Wu, Ning Electric Power Research Institute of Guangxi Power Grid Co. Ltd Southern Power Grid Corporation Wireless Power Transmission Joint Laboratory Nanning China Chongqing University College of Automation Chongqing China

ISBN: (纸本)9798350342710

In response to the issue of coupling coefficient and frequency variation leading to system output power fluctuations in wireless power transmission systems, this paper proposes a tightly coupled wireless charging system with a wide frequency range based on hybrid topology. Firstly, output characteristics of SS and LCC-LCC topology circuits are analyzed in this paper, then a hybrid topology structure with a DDQ coil structure is proposed. Secondary, a parameter optimization method is proposed to optimize the parameters of the compensation network. Finally, build the system circuit in MATLAB simulation software to verify the feasibility of theoretical analysis. The simulation results show that when the system frequency changes between 78kHz and 96kHz, the output power of the system remains approximately 11kW, and when the coupling coefficient changes, the output power of the system can also maintain stationarity. © 2023 IEEE.

关键词： MATLAB

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DPA-2:a large atomic model as a multitask learner

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npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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Data Generation for Photovoltaic Systems: Enhancing Accuracy with the Huld Model

Data Generation for Photovoltaic Systems: Enhancing Accuracy...

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2024 IEEE international conference on Big Data, BigData 2024

作者： Ardebili, Ali Aghazadeh Livera, Andreas Georghiou, George E. Longo, Antonella Ficarella, Antonio HSPI Dept. of Research and Development Rome Italy University of Salento CRISR Dept. of Engineering for Innovation Lecce Italy University of Cyprus PV Technology Laboratory FOSS Research Centre for Sustainable Energy Dept. of Electrical and Computer Engineering Nicosia1678 Cyprus

ISBN: (纸本)9798350362480

Gaps in current numerical models highlight challenges in accurately simulating photovoltaic (PV) systems, particularly their sensitivity to weather forecast outputs and the impact of environmental factors such as wind speed and humidity. These factors introduce discrepancies between simulated and real-life PV system performance. This study investigates the potential of open-source PV physical models, leveraging pvlib-python, to address these challenges. The research focuses on enhancing the accuracy of these models to generate synthetic data that closely replicate real-world conditions. Using the single diode equation implemented in pvlib-python, DC power production data from a real-life PV module is simulated, with initial discrepancies identified and mitigated through the integration of Huld model. This integration aims to improve the accuracy of synthetic data, thereby bridging the gap between simulated and actual performance metrics. The efficacy of the enhanced predictive models is evaluated using historical field measurements from a PV system testbed, demonstrating advancements in simulating PV system behaviors with enhanced accuracy and reliability. The results unveil a significant enhancement in synthetic data generation using PVLib and Huld model. © 2024 IEEE.

关键词： Accuracy Enhancement Digital Twin Energy simulation Huld Model Performance modeling Photovoltaic Systems Pvlib Python Renewable Energy Synthetic Data Generation

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Evaluation of Large Language Model Generated Dialogues for an AI Based VR Nurse Training Simulator 16th

Evaluation of Large Language Model Generated Dialogues for a...

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16th international conference on Virtual, Augmented and Mixed Reality (VAMR)

作者： Kapadia, Nimit Gokhale, Shreekant Nepomuceno, Anthony Cheng, Wanning Bothwell, Samantha Mathews, Maureen Shallat, John S. Schultz, Celeste Gupta, Avinash Univ Illinois Champaign IL 61820 USA Carle Fdn Hosp Urbana IL 61801 USA OSF HealthCare Peoria IL 61603 USA Univ Illinois Chicago IL 60607 USA

ISBN: (纸本)9783031610400;9783031610417

This paper explores the efficacy of Large Language Models (LLMs) in generating dialogues for patient avatars in Virtual Reality (VR) nurse training simulators. With the integration of technology in healthcare education evolving rapidly, the potential of NLP to enhance nurse training through realistic patient interactions presents a significant opportunity. Our study introduces a novel LLM-based dialogue generation system, leveraging models such as ChatGPT, GoogleBard, and ClaudeAI. We detail the development of our script generation system, which was a collaborative endeavor involving nurses, technical artists, and developers. The system, tested on the Meta Quest 2 VR headset, integrates complex dialogues created through a synthesis of clinical expertise and advanced NLP, aimed at simulating real-world nursing scenarios. Through a comprehensive evaluation involving lexical and semantic similarity tests compared to clinical expert-generated scripts, we assess the potential of LLMs as suitable alternatives for script generation. The findings aim to contribute to the development of a more interactive and effective VR nurse training simulator, enhancing communication skills among nursing students for improved patient care outcomes. This research underscores the importance of advanced NLP applications in healthcare education, offering insights into the practicality and limitations of employing LLMs in clinical training environments.

关键词： Large Language Models Nurse Training simulation Natural Language Processing Healthcare education Patient Avatars Dialogue Generation ChatGPT Bard ClaudeAI Virtual Reality Extended Reality

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Model Based Design of the Hydraulic Actuator

Model Based Design of the Hydraulic Actuator

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international Scientific-Technical conference on Hydraulic and Pneumatic Drives and Controls, NSHP 2023

作者： Noskievič, Petr Milata, Jan Faculty of Mechanical Engineering VŠB-Technical University of Ostrava 17. Listopadu 2172/15 Ostrava–Poruba Czech Republic Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava 17. Listopadu 2172/15 Ostrava–Poruba Czech Republic

ISBN: (纸本)9783031430015

The paper is focused on the Model Based Design of the closed loop control of the linear hydraulic drive. Model-Based-Design is progressive methodology for design of control systems, embedded control systems and for testing of the implemented software. The hydraulic servo drives represent very important parts of the modern machines. The demands on their accuracy and dynamics require the use of the modern controller design approaches based on the computer simulation and comprehensive tools of their implementation. The novel created MATLAB-application named Hydraulic System Control–Model Based Design is introduced. The application concentrates the knowledge of the possible solutions of the closed loop control systems suitable for hydraulic drives and supports the use and tuning of the controllers different structures. The parameterization of the drive can be done using the known data from the data sheets of the servo valve and cylinder or can be based on the experimentally obtained characteristics which can be evaluated using the identification methods. The application is a user-friendly environment and creates also comfortable access to the MATLAB-toolboxes and their use. It simplifies the process of the controller design based on the implemented non-linear, linear respectively linearized mathematical models of the hydraulic drive, because the tools for the linearization of the non-linear model are available. The parameters of the controller can be verified by the simulation of the linear or non-linear model. The created MATLAB-application represents the Model-in-the-Loop (MIL) simulation of the control of the hydraulic drive and supports very important part of the development cycle called V-Model. Practical use of the application is demonstrated on the design of the closed loop position control of the hydraulic drive installed on the test rig. The simulated and measured data are presented as well as the results of the Hardware-in-the-Loop simulation of the control of

关键词： MATLAB

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Hybrid CNN-SVM Classifier for Emotion Recognition Using Brain Waves 4

Hybrid CNN-SVM Classifier for Emotion Recognition Using Brai...

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4th international conference on Embedded and Distributed Systems, EDiS 2024

作者： Yassine, Ferdi Ahmed Abdelkader, Ghazli Tahri Mohammed University Department of Mathematics and Computer Sciences Bechar Algeria

ISBN: (纸本)9798331519872

The field of information fusion and deep learning (DL) has advanced significantly in recent years, enabling computers and other devices to perceive, recognize, and evaluate emotions. In addition to distinct physiological rhythms and alterations in behavior, mental health, and physical attributes, emotions constitute a mental state. The first three techniques might not be effective because people occasionally accidentally or purposely hide their true feelings. We call this social masking phenomena. By using physiological clues, emotion detection could become more objective and reliable. Important features of emotional states can be inferred from electroencephalography (EEG) signals since they react to changes in emotional states faster and more sensitively than peripheral neurophysiological signals. Automatic electroencephalography (EEG) emotion identification is one challenging component of human-computer interaction (HCI). Inspired by the powerful feature learning capabilities of recently emerging deep learning algorithms, several advanced deep learning models have been used more often to obtain high-level feature representations for EEG emotion recognition. In order to classify EEG emotions more quickly and accurately, this research introduces a hybrid model based on convolutional neural networks (CNN) and support vector machines (SVM). Experimental results show that the suggested strategy outperforms previous approaches in modeling training with a smaller loss value and more generalization. The categorization accuracy as a whole was 98.361%. This percentage is higher when compared to other learning strategies. Furthermore, compared to other models, the proposed model takes less time and much less complex. © 2024 IEEE.

关键词： Electroencephalography

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modeling of Information System for Blended education Quality Assurance and Socio-Economic Impact 16

Modeling of Information System for Blended Education Quality...

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16th IEEE international conference on advanced Trends in Radioelectronics, Telecommunications and computer Engineering, TCSET 2022

作者： Volk, Iurii Artyukhov, Artem Lyeonov, Serhiy Sumy State University Faculty of Electronics and Information Technologies Department of Applied Mathematics and Complex Systems Modeling Sumy Ukraine Institute for Business Economics and Management Department of Marketing Sumy State University Sumy Ukraine Sumy State University Economic Cybernetics Department Economics and Management Sumy Ukraine

ISBN: (纸本)9781665468619

Current paper is devoted to modeling of information-analytical system for blended education quality assurance considering the socio-economic impact of this kind of educational services. Based on bibliometrical analysis, we outlined the necessity to consider the formats of quality assurance, its criteria, organization and management of blended learning with socio-economical problems as a joint system. Proposed system contains conceptual components and interfaces describing the interactions within developed quality assurance algorithm. Each component and interface are backed up by information services and socio-economic indicators for assessing system viability. We introduced the sequence for multi-level quality assurance procedures for the blended learning environment. We demonstrated that blended education quality assurance procedure requires effective instruments such as technology and experience transfer, gamification, research-based learning, etc. We proposed to use immersive learning techniques as an instrument to increase education quality and strengthen the bonds between main stakeholders. © 2022 IEEE.

关键词： Quality assurance

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Bandwidth Utilization Analysis for TVET education on Metro-E Campus Network 4

Bandwidth Utilization Analysis for TVET Education on Metro-E...

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4th international conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2024

作者： Abdullah, Nor Paezah Kassim, Murizah Deni, Sayang Mohd School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Selangor Malaysia Pulau Pinang Nibong Tebal Malaysia Universiti Teknologi MARA Selangor Shah Alam Malaysia College of Computing Informatics and Media Studies Universiti Teknologi MARA Selangor Shah Alam Malaysia

ISBN: (纸本)9798350391183

This paper presents a bandwidth utilization analysis and internet application usage for Technical and Vocational education and Training (TVET) education on the Metro-E campus network. Despite upgrading high-speed Internet from 50Mbps to 150Mbps, the campus is still experiencing internet link congestion, affecting the Quality of Services (QoS). Campus QoS was analyzed, and data was collected over three months on a campus Metro-E network at the primary Internet gateway. The results show the bandwidth consumption for the Integrated Performance modeling Environment (IPME). Inbound network capacity usage peaks at 100% and then drops to 30% of available capacity, demonstrating that the network experiences both high and low demand times. However, Unifi broadband shows that inbound data usage ranges from 72% to 100%. The high demand for inbound Unifi traffic could suggest a critical service or a strong reliance on Unifi for inbound communication. PERDA-TECH students use most of the total 22014300.81MB of inbound data from online applications. They use these internet apps for E-learning and online simulation, YouTube, TikTok, and Facebook for multimedia and creative learning, and FTP applications for transferring files across websites or enhancing information. This research is significant in deploying QoS bandwidth management, policing, and shaping future QoS for TVET education on the Metro-E campus network. © 2024 IEEE.

关键词： Quality of service

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