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15th Biomedical engineering International Conference, BMEiCON 2023

作者： Pidech, Jutamas Neubert, Manida Swangnetr Chuchuen, Oranat Khon Kaen University Faculty of Engineering Biomedical Engineering Program Khon Kaen Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Human-Robot Collaboration and Systems Integration Research Unit Bangkok Thailand Khon Kaen University Faculty of Engineering Department of Chemical Engineering Khon Khon Kaen Thailand

ISBN: (纸本)9798350345247

Current work environments have undergone a noticeable shift towards higher cognitive demands and increased involvement in multitask performance. It has therefore become crucial to investigate the levels of mental workload experienced by operators. Simulated cognitive multitasking, with varying workload intensity, duration and work order, was tested in 18 volunteers to determine its impact on task performance, perceived workload, galvanic skin response;GSR, and cortisol levels in sweat and saliva. The results showed that as workload intensity increased, there was a concurrent increase in perceived workload and a significant negative impact on task performance. As time progressed, there was a notable increase in performance. Differences in GSR can be observed based on time on task and order of stressor levels delivered to the participants. Preliminary results of cortisol levels in sweat and saliva showed distinct trends in relation to workload intensity. © 2023 IEEE.

关键词： Multitasking

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Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第1期2卷 40-51页

作者： Ferrando, Robert Pagnier, Laurent Mieth, Robert Liang, Zhirui Dvorkin, Yury Bienstock, Daniel Chertkov, Michael University of Arizona Program in Applied Mathematics and Department of Mathematics TucsonAZ85721 United States Department of Industrial and Systems Engineering at Rutgers University PiscatawayNJ08854 United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218-2625 United States Elec. and Comp. Eng. and Ralph o'Connor Sustainable Energy Institute Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218-2625 United States Columbia University IEOR New YorkNY10027 United States

This article addresses the challenge of efficiently recovering exact solutions to the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically, PIMA-AS-OPF employs the active set learning technique and expands its capabilities to account for curtailment in load or renewable power generation, which is a common challenge in real-world power systems. The core of PIMA-AS-OPF is a fully-connected neural network that takes the net load and the system topology as input. The outputs of this neural network include active constraints such as saturated generators and transmission lines, as well as non-zero load shedding and wind curtailments. These outputs allow for reducing the original market-clearing optimization to a system of linear equations, which can be solved efficiently and yield both the dispatch decisions and the locational marginal prices (LMPs). The dispatch decisions and LMPs are then tested for their feasibility with respect to the requirements for efficient market-clearing results. The accuracy and scalability of the proposed method is tested on a realistic 1814-bus NYISO system with current and future renewable energy penetration levels. © 2023 IEEE.

关键词： Costs

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Adaptive Droop Controlled-VSCs in MVDC Distribution systems with ESS Engagement 6

Adaptive Droop Controlled-VSCs in MVDC Distribution Systems ...

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6th International Future Energy Electronics Conference, IFEEC 2023

作者： Sun, Pingyang Pinthurat, Watcharakorn Li, Gen Khalid, Muhammad Town, Graham Konstantinou, Georgios Unsw School of Electrical Engineering and Telecommunications Sydney Australia Rajamangala University of Technology Tawan-ok Department of Electrical Engineering Chanthaburi Thailand Dtu Department of Engineering Technology and Didactics Electric Energy Denmark Kfupm Electrical Engineering Department Saudi Arabia Kfupm Interdisciplinary Research Center for Renewable Energy and Power Systems Saudi Arabia School of Engineering Macquarie University Australia

ISBN: (纸本)9798350339888

A novel adaptive droop control (ADC) is proposed in this paper for voltage source converter (VSC)-based medium-voltage direct current (MVDC) distribution systems. The proposed ADC can achieve MVDC bus voltage management and power sharing between VSCs with overloading operation consideration, solving the issue that all VSCs on the rectifier/inverter side reach their power limits concurrently after a large system disturbance. It is accomplished by factoring in the real-time power/voltage values at VSC stations and a newly introduced extended power component. This component is contingent on the actual operational state of the energy storage systems (ESSs) in MVDC systems and inversely correlated with the power delivered/absorbed by the ESSs. The effectiveness of proposed ADC is confirmed through an MVDC distribution system model built in RTDS real-time digital simulators. © 2023 IEEE.

关键词： Energy storage

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Effect of Overload and Underload on Subsequent Deformation Behavior during Cyclic Deformation

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Zairyo/Journal of the Society of Materials Science, Japan 2022年第2期71卷 159-166页

作者： Kondou, Ryouji Yama, Katsunari Energy and Environmental Program School of Engineering Faculty of Engineering University of the Ryukyus Nishihara-cho Nakagami-gun Okinawa903-0213 Japan Department of Mechanical Systems Engineering Graduate School of Engineering and Science University of the Ryukyus Nishihara-cho Nakagami-gun Okinawa903-0213 Japan

A multi-scale analysis of elasto-plastic deformation and dislocation movement and accumulation of tricrystalline models during cyclic deformation was performed. The accumulation of dislocations in geometrically necessary dislocations (GNDs) and statistically stored dislocations (SSDs) was investigated in detail. Experimental observations have shown that fatigue life and fatigue crack propagation are also deteriorated when the material is subjected to overload or underload. However, in the microscopic and mesoscopic regions, where the effects of the crack tip shape change are not related to the size of the crack tip, a different phenomenon is essentially occurring. In this paper, the effects of overload and underload are investigated using a simple model without a crack. From the analysis results, it was found that the dislocation structure generated in the material subjected to overload or underload affects the subsequent deformation behavior. However, even though the absolute values are the same, the effects of overloading and underloading on the subsequent deformation are different, and underloading increases the non-uniformity of the subsequent deformation, which is on the dangerous side, while overloading decreases with increasing the number of repetitions. ©2022 The Society of Materials Science, Japan

关键词： Crack tips

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3D Geometric Shape Assembly via Efficient Point Cloud Matching 41

3D Geometric Shape Assembly via Efficient Point Cloud Matchi...

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41st International Conference on Machine Learning, ICML 2024

作者： Lee, Nahyuk Min, Juhong Lee, Junha Kim, Seungwook Lee, Kanghee Park, Jaesik Cho, Minsu Department of Computer Science and Engineering POSTECH Pohang Korea Republic of Graduate School of Artificial Intelligence POSTECH Pohang Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local correspondences between point clouds of part shapes in both coarse- and fine-levels. To this end, we introduce Proxy Match Transform (PMT), an approximate high-order feature transform layer that enables reliable matching between mating surfaces of parts while incurring low costs in memory and compute. Building upon PMT, we introduce a new framework, dubbed Proxy Match TransformeR (PMTR), for the geometric assembly task. We evaluate the proposed PMTR on the large-scale 3D geometric shape assembly benchmark dataset of Breaking Bad and demonstrate its superior performance and efficiency compared to state-of-the-art methods. Project page: https://***/pmtr. Copyright 2024 by the author(s)

关键词： 3D modeling

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Deep Semantic and Attentive Network for Unsupervised Video Summarization

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ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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Enhancing Safety Measures in a Steel Manufacturing Facility;Factory X Case Study

Enhancing Safety Measures in a Steel Manufacturing Facility;...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ali, Mariam Kassem, Sally S. Elatriby, Sherif A. Nile University Industrial Engineering Program Smart Engineering Systems Research Center Giza12613 Egypt Cairo Univesityt Faculty of Computers and Artificial Intelligence Operations Research and Decision Support Department Giza12613 Egypt University Helwan Faculty of Engineering Helwan Cairo11792 Egypt

ISBN: (纸本)9798350369106

Productivity and safety of the workers have been issues in most manufacturing facilities in Egypt and all over the world, as the main aim of any manufacturing facility is to increase profit and limit costs as much as possible. Through analysis and simulation, this paper aims to create a safe workplace for the worker;risk assessment and Failure Mode and Effect Analysis (FMEA) and the basics of the international standards ISO 31000 and ISO 45001 have been conducted to evaluate different hazards and potential risks. Moreover, lean tools such as 6S and Visual Management are proposed solutions to enhance workplace safety and decrease the possibility or severity of potential risks. Therefore, a new workplace design, an example of a high-level hazard in industry in Egypt's local market, has been established for the steel manufacturing facility under consideration using Sketch Up. The results of the proposed solutions, such as new frameworks, worker safety training, equipment replacements, and applying lean tools, have shown a practically acceptable percentage of safety improvements and a decreasing risk priority number (RPN). The percentage decrease for (RPN) ranges between 31.43% to 90.47% for different potential risks. © 2024 IEEE.

关键词： Agile manufacturing systems

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Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 295-312页

作者： Sarah P.Madruga Augusto H.B.M.Tavares Saulo O.D.Luiz Tiago P.do Nascimento Antonio Marcus N.Lima Graduate Program of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil Department of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil IEEE Department of Computer Systems Universidade Federal da ParaibaJoao Pessoa-PBBrazil

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural ***,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations *** network training is performed offline,which requires low computational *** target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation *** a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small *** compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the *** was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve *** allocation error was also determined in both ***,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

关键词： Aerodynamics effects control allocation minidrone multi-rotor UAV neural networks

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SF(DA)2: SOURCE-FREE DOMAIN ADAPTATION THROUGH THE LENS OF DATA AUGMENTATION 12

SF(DA)2: SOURCE-FREE DOMAIN ADAPTATION THROUGH THE LENS OF D...

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12th International Conference on Learning Representations, ICLR 2024

作者： Hwang, Uiwon Lee, Jonghyun Shin, Juhyeon Yoon, Sungroh Division of Digital Healthcare Yonsei University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

In the face of the deep learning model's vulnerability to domain shift, source-free domain adaptation (SFDA) methods have been proposed to adapt models to new, unseen target domains without requiring access to source domain data. Although the potential benefits of applying data augmentation to SFDA are attractive, several challenges arise such as the dependence on prior knowledge of class-preserving transformations and the increase in memory and computational requirements. In this paper, we propose Source-free Domain Adaptation Through the Lens of Data Augmentation (SF(DA)2), a novel approach that leverages the benefits of data augmentation without suffering from these challenges. We construct an augmentation graph in the feature space of the pretrained model using the neighbor relationships between target features and propose spectral neighborhood clustering to identify partitions in the prediction space. Furthermore, we propose implicit feature augmentation and feature disentanglement as regularization loss functions that effectively utilize class semantic information within the feature space. These regularizers simulate the inclusion of an unlimited number of augmented target features into the augmentation graph while minimizing computational and memory demands. Our method shows superior adaptation performance in SFDA scenarios, including 2D image and 3D point cloud datasets and a highly imbalanced dataset. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Deep learning

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Successful Digital Transformations Demand Process and Measurable Functions

Successful Digital Transformations Demand Process and Measur...

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2022 Portland International Conference on Management of engineering and Technology, PICMET 2022

作者： Pacyna, Elizabeth M. Langford, Gary O. Portland State University Systems Engineering Program Etm Department PortlandOR United States

ISBN: (数字)9781890843410

ISBN: (纸本)9781890843410

A common notion underscoring popular beliefs of organizational growth in the digital future involves transforming processes to sustain or improve operations. Although a plethora of measures and metrics abound, digital transformation must begin with a strict ontological separation into those that are counted and those that are measurable/measured. The results of organizational processes can be counted. Thus, the aim is to characterize processes as distinct from functions, where the difference provides a basis for evaluating an organization's existing and proposed processes through countable items;and developing functional performances with measurable impacts, consequences, and costs. The result is an understanding of the measured value and worth of the transformations. By applying an ontological framework, we find that measurement theory captures the losses often missed or misinterpreted when planning and executing digital transformation. Significantly, these losses also hinder work and mask the true nature of the impacts of transformation. We posit the reported 'failures' of digital transformation may implicate procedural counting and presumed measurements - both of which violate measurement theory. © 2022 PICMET.

关键词： Ontology

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