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IISE Annual Conference and Expo 2023

作者： Rabbi, Md Fazle Emon, Solayman Hossain Nishat, Ehtesham Mahmud Tseng, Tzu-Liang Bill Ferdoushi, Atira Huang, Chun-Che Rahman, Md Fashiar Department of Industrial Manufacturing and Systems Engineering The University of Texas El PasoTX79968 United States Data Science Program The University of Texas at El Paso El PasoTX79968 United States Khulna9203 Bangladesh University of Rajshahi Rajshahi6205 Bangladesh National Chi Nan University Puli Taiwan

ISBN: (纸本)9781713877851

Wind turbines are subjected to continuous rotational stresses and unusual external forces such as storms, lightning, strikes by flying objects, etc., which may cause defects in turbine blades. Hence, it requires a periodical inspection to ensure proper functionality and avoid catastrophic failure. The task of inspection is challenging due to the remote location and inconvenient reachability by human inspection. Researchers used images with cropped defects from the wind turbine in the literature. They neglected possible background biases, which may hinder real-time and autonomous defect detection using aerial vehicles such as drones or others. To overcome such challenges, in this paper, we experiment with defect detection accuracy by having the defects with the background using a two-step deep-learning methodology. In the first step, we develop virtual models of wind turbines to synthesize the near-reality images for four types of common defects - cracks, leading edge erosion, bending, and light striking damage. The Unity® perception package is used to generate wind turbine blade defects images with variations in background, randomness, camera angle, and light effects. In the second step, a customized U-Net architecture is trained to classify and segment the defect in turbine blades. The outcomes of U-Net architecture have been thoroughly tested and compared with 5-fold validation datasets. The proposed methodology provides reasonable defect detection accuracy, making it suitable for autonomous and remote inspection through aerial vehicles. © IISE and Expo *** rights reserved.

关键词： Turbomachine blades

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Photovoltaic Microinverter with Hybrid Energy Storage System (HESS) and Virtual Impedance Control for Injection into a Microgrid

Photovoltaic Microinverter with Hybrid Energy Storage System...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Patricio Gaisse Javier Muñoz Marco Rivera Carlos Restrepo Galina Mirzaeva Engineering Systems Doctoral Program Faculty of Engineering University of Talca Curicó Chile Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó Chile Doctorate in Engineering Systems Faculty of Engineering Universidad de Talca Curicó Chile School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW Australia

In this work, a photovoltaic (PV) microinverter is developed, which includes an hybrid energy storage system based on a battery and an ultracapacitor that are connected in parallel to the dc-link through two buck-boost bidirectional converters. The PV panel is connected in parallel to dc-link through an unidirectional boost converter. For the dc-ac stage, a two-stage Flyback / H-bridge inverter will be considered, which will be used to inject the available power into a microgrid. The study proposes the necessary control strategies to manage the power flow according to generation and injection conditions, where a virtual impedance loop is incorporated in the control of the energy storage elements. The presented results confirm the suitability of the proposed strategy.

关键词： Photovoltaic systems Microgrids Hybrid power systems Batteries Circuit stability Topology Impedance

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A Planning Model for Distributed Resources and Hydrogen System Considering Network's Enhancement

A Planning Model for Distributed Resources and Hydrogen Syst...

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IEEE International Energy Conference and Exhibition (EnergyCon)

作者： Adnan S. Al-Bukhaytan Muhammad Asif Electrical Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Architectural Engineering and Construction Management King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

This research develops a comprehensive planning model that integrates various distributed energy resources (DERs) to supply the load in a distribution network (DN) at optimal minimum costs. The DERs include renewable energy resources (RESs) such as photovoltaic systems (PV) and wind turbines (WT), thermal generators (TG), and battery energy storage systems (BESS). Moreover, hydrogen systems comprising components such as electrolyzers (ED), fuel cells (FC), and hydrogen storage (HS) are considered. Additionally, the DN is assumed to be grid-connected, allowing the distribution system operator (DSO) to buy the required electrical energy from the grid at hourly market prices. Moreover, the DN enhancement is also considered an option for the DSO. The main objective is to develop an optimization model that determines the optimal sizing and location of the DERs along with the selected lines to be upgraded, aiming to meet the load at the optimal minimum cost while maintaining DN constraints. The proposed model has been tested on a modified IEEE-38 bus radial DN. Various case studies and sensitivity analyses were implemented to evaluate the effectiveness of the proposed model.

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Data-Driven Intelligent Prediction Model for Gearbox Temperature in Wind Turbines

Data-Driven Intelligent Prediction Model for Gearbox Tempera...

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International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Abdulbasit Hassan Md Shafiullah Asif Islam Muhammad Majid Gulzar Waleed M. Hamanah Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Centre for Sustainable Energy Systems KFUPM Dhahran Saudi Arabia Electrical Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Applied Research Centre for Metrology Standards & Testing KFUPM Dhahran Saudi Arabia

ISBN: (数字)9798350378078

ISBN: (纸本)9798350378085

Wind power has become increasingly popular due to the demand for sustainable energy sources. A fundamental problem these renewable sources face is the energy cost, thus challenging their efficient operation and maintenance (O&M). Predictive maintenance (PM) has been developed to be an economical solution for the active overcoming of problems, such as wind turbine (WT) gearbox bearing failures that seriously affect the performance and stability of renewable energy systems (RES). This study develops a predictive model of gearbox-bearing temperature using advanced machine learning algorithms such as multiple linear regression (MLR), Extreme Gradient boosting (XGBoost), and Random forest (RF) from the WT supervisory control and data acquisition (SCADA) system. The RF model performed better than the MLR and XGBoost model, with an R-squared value of 0.9840, and the Root mean square error (RMSE) and the Mean absolute percentage error (MAPE) were discovered to be 0.7352 and 0.88%, respectively.

关键词： Radio frequency Temperature measurement Renewable energy sources Machine learning algorithms SCADA systems Predictive models Wind power generation Wind turbines Wind forecasting Predictive maintenance

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UAV-Based Optimization for Fruit Counting in Greenhouses

UAV-Based Optimization for Fruit Counting in Greenhouses

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： João Vítor R. Vasconcelos Thayron M. Hudson André G. dos Santos Martin Saska Alexandre S. Brandão Department of Electrical Engineering Núcleo de Especialização em Robótica Graduate Program on Computer Science Federal Univer-sity of Vicosa Vicosa MG Brazil Graduate Program on Computer Science Federal University of Vicosa Vicosa MG Brazil Department of Cybernetics Multi-robot Systems Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a solution for counting fruit in agricultural greenhouses using Unmanned Aerial Vehicles (UAV s). Initially, a heuristic based on Simulated Annealing was used to optimize the UAV's trajectory, ensuring efficient coverage of the beds. Next, digital image processing (DIP) techniques were implemented to count the fruit, including depth segmentation, application of bounding boxes, color filtering, and element counting. The DIP accuracy was evaluated in multiple scenarios and the results indicate high reliability in fruit counting, with the potential to optimize agricultural operations and provide valuable information to producers. Possible future improvements could include further refinements in image processing to increase the accuracy of counting other fruits. Ultimately, this work contributes to the advancement of automation in agriculture by offering a viable and efficient solution for counting fruit in greenhouses using UAV s.

关键词： Image segmentation Accuracy Image color analysis Greenhouses Simulated annealing Autonomous aerial vehicles Trajectory

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Superpixel Tokenization for Vision Transformers: Preserving Semantic Integrity in Visual Tokens

arXiv

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arXiv 2024年

作者： Lew, Jaihyun Jang, Soohyuk Lee, Jaehoon Yoo, Seungryong Kim, Eunji Lee, Saehyung Mok, Jisoo Kim, Siwon Yoon, Sungroh Interdisciplinary Program in AI Seoul National University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Amazon United States AIIS ASRI INMC ISRC Seoul National University Korea Republic of

Transformers, a groundbreaking architecture proposed for natural language processing (NLP), have also achieved remarkable success in computer vision. A cornerstone of their success lies in the attention mechanism, which models relationships among tokens. While the tokenization process in NLP inherently ensures that each token maintains semantic integrity without containing multiple meanings, the grid-based tokenization of Vision Transformer (ViT) relies on uniformly partitioned square image patches, which may result in an arbitrary mixing of visual concepts within a token. In this work, we propose a novel tokenization pipeline that replaces the grid-based tokenization with superpixels, encouraging each token to capture a distinct visual concept. Unlike square image patches, superpixels are formed in varying shapes, sizes, and locations, making direct substitution challenging. To address this, our pipeline first generates pixel-level embeddings and efficiently aggregates them within superpixel clusters, producing superpixel tokens that seamlessly replace patch tokens in ViT. Extensive experiments demonstrate that our approach enhances the performance of ViT on various downstream tasks and introduces intriguing properties such as adaptive inference and semantic integrity in tokens. © 2024, CC BY.

关键词： Semantics

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Recent Advancements in Nanophotonics for Optofluidics

arXiv

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arXiv 2024年

作者： Yang, Sen Hong, Chuchuan Zhu, Guodong Anyika, Theodore Hong, Ikjun Ndukaife, Justus C. Institute of Physics Chinese Academy of Sciences Beijing National Laboratory for Condensed Matter Physics Beijing100190 China Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37240 United States

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently, driven by the concerted efforts of researchers across various scientific disciplines, notably for its successful applications in biomedical science. In this review, we explore a range of optofluidic architectures developed over the past decade, with a primary focus on mechanisms for precise control of micro and nanoscale biological objects and their applications in sensing. Regarding nanoparticle manipulation, we delve into mechanisms based on optical nanotweezers using nanolocalized light fields and light-based hybrid effects with dramatically improved performance and capabilities. In the context of sensing, we emphasize those works that used optofluidics to aggregate molecules or particles to promote sensing and detection. Additionally, we highlight emerging research directions, encompassing both fundamental principles and practical applications in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Flow of fluids

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The Multiple Determinants of Infection Prevention and Control Practices in Nursing Homes: A Scoping Review

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Journal of the American Medical Directors Association 2025年第6期26卷 105593页

作者： Fujimoto, Kanako Utsumi, Momoe Swa, Toshiyuki Furuya, Aoi Ikuji, Ayumi Nakanishi, Ayami Harada, Nahoko of Interdisciplinary Science and Engineering in Health Systems Okayama University Okayama Okayama Japan of Health and Nursing Sciences Kyoto Prefectural University of Medicine Kyoto Kyoto Japan Division of Health Sciences of Medicine The University of Osaka Osaka Suita Japan Department of Nursing Ikeda Municipal Hospital Osaka Ikeda Japan Department of Nursing University Hospital Kyoto Prefectural University of Medicine Kyoto Kyoto Japan Faculty of Interdisciplinary Science and Engineering in Health Systems Okayama University Okayama Okayama Japan

Objectives: To map the barriers and facilitators influencing infection prevention and control (IPC) practices in nursing homes (NHs) from a behavior change perspective and to identify research gaps. Design: Scoping review using the Joanna Briggs Institute methodology. Setting and Participants: NHs for older adults and health care workers in NHs. Methods: We conducted database searches in March 2022 and updated them in November 2024, including additional sources from citation tracking and reference list checks. We analyzed barriers and facilitators using the Theoretical Domains Framework (TDF) and the Capability, Opportunity, and Motivation–Behavior (COM-B) model. Results: Of 1591 identified records, 54 reports published between 2003 and 2024 met our inclusion criteria. The analysis identified 101 determinants (25 in Capability, 46 in Opportunity, and 30 in Motivation within the COM-B model) categorized into 36 categories and 16 themes as barriers and facilitators. The most frequently mentioned barriers were related to the “Environmental context and resources” domain of the TDF. Relatively few reports addressed the determinants of the TDF domain classified within the Motivation area of the COM-B model. Although many facilitators were identified in this area, including beliefs, intentions, and goals, they were coded based on limited descriptions. Conclusions and Implications: This review provides a detailed mapping of the barriers and facilitators to IPC in NHs based on existing literature. It demonstrates the complexity of sustaining IPC practices, influenced by multiple determinants. Although Motivation may impact IPC adherence, its determinants remain insufficiently studied, indicating a research gap. Further research is needed to explore these determinants and understand how Motivation interacts with other factors in IPC implementation. © 2025 The Author(s)

关键词： behavior change health care workers Infection prevention and control long-term care facilities nursing homes older adults

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Photoresponse of Thermally Evaporated Copper Oxide-Based Solar Cells

Photoresponse of Thermally Evaporated Copper Oxide-Based Sol...

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Solar Conference (MENA-SC), Middle East and North Africa

作者： Abdul Hai Alami Mohamad Ayoub Adnan Alashkar Shamma Alasad Ayman Mdallal Siren Khuri Haya Aljaghoub Sustainable and Renewable Energy Engineering Department Sustainable Energy & Power Systems Research Centre University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Mechancial Engineering Department American University of Sharjah Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre University of Sharjah Sharjah United Arab Emirates Industrial Engineering and Engineering Management Department University of Sharjah Sharjah United Arab Emirates

This study reports on the fabrication and characterization of a copper oxide (CuO)-based photoactive cell. Copper was thermally evaporated onto two substrates and post-treated using chemical and thermal treatments to obtain different semiconducting types of CuO. Absorption measurements were conducted to obtain the bandgaps of CuO, which were found to be 1.51 eV and 1.21 eV, for the chemically and thermally treated CuO, respectively. Finally, a chronoamperometry test was conducted to confirm the photoresponse of the cell, which showed a doubling of output current values under light conditions compared to dark conditions.

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Federated Multilinear Principal Component Analysis with Applications in Prognostics

arXiv

引用

arXiv 2023年

作者： Zhou, Chengyu Su, Yuqi Xia, Tangbin Fang, Xiaolei Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University United States Operations Research Program North Carolina State University United States Department of Industrial Engineering Shanghai Jiao Tong University China

Multilinear Principal Component Analysis (MPCA) is a widely utilized method for the dimension reduction of tensor data. However, the integration of MPCA into federated learning remains unexplored in existing research. To tackle this gap, this article proposes a Federated Multilinear Principal Component Analysis (FMPCA) method, which enables multiple users to collaboratively reduce the dimension of their tensor data while keeping each user's data local and confidential. The proposed FMPCA method is guaranteed to have the same performance as traditional MPCA. An application of the proposed FMPCA in industrial prognostics is also demonstrated. Simulated data and a real-world data set are used to validate the performance of the proposed method. © 2023, CC BY.

关键词： Principal component analysis

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