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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Shota Omi Yasuaki Nakayama Naoki Kawamoto Sustainability Laboratory European R&D Centre Hitachi Europe Ltd London UK Environmental Systems Research Department Reseasrch & Development Group Hitachi Ltd Hitachi Japan

Implementation of inverter-based resources (IBrs) accompanied with phasing out of unabated thermal power plants for decarbonisation brings stability challenges to future power grids. For ensuring the stable operation of IBrs, short-circuit level is a key criterion. Short-circuit level can be improved by installing synchronous condensers, which provide short-circuit current, reactive power, and inertia to the power system. The installation place of synchronous condensers affects the improvement of short circuit level and voltage profile of the power grid. However, the optimal placement problem of synchronous condensers becomes a Mixed-Integer Nonlinear Programming problem, which is too complex to be solved directly, due to the nonlinearity of the short circuit level and reactive power flow. To solve this complex problem, we applied Benders decomposition with a linearisation of the short circuit constraint. Preliminary evaluation with WSCC 9-bus and IEEE 118-bus standard system models on single period ensures that the proposed approach can provide a solution for improving short circuit level and reducing total expenditure.

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Evolution of Metallic Connection Technologies of Busbar in Silicon Solar Cells: Brief review 15

Evolution of Metallic Connection Technologies of Busbar in S...

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15th IEEE International Conference on Industry Applications, INdUSCON 2023

作者： Silveira, A.M.C. Neves, M.r.M. Garcia, r. Alvarez, H. Villalva, M.G. Marques, F.C. Kretly, L.C. School of Electrical and Computer Engineering Communications Department - DECOM Campinas Brazil School of Electrical and Computer Engineering Dept. of Systems and Energy - DSE Campinas Brazil Institute of Physics Gleb Wataghin Dept. of Applied Physics - DFA Campinas Brazil Build Your Dreams Company - BYD Dept. Research and Development - R&D Campinas Brazil

ISBN: (纸本)9798350314182

This work consists of presenting a brief review of the evolution of metallic connection technologies in busbars applied to the front and rear of solar cells, thus demonstrating their fundamentals, materials and essential manufacturing processes that impact on improving the energy efficiency of solar modules. In this brief review, one can follow the technical limitations that led to the evolution of metallic connection technologies in busbars over time and their impacts on the photovoltaic market. Contributing to a broad understanding of the resistive components of solar cells that consists of the series resistance parameter. © 2023 IEEE.

关键词： Busbarless Effective Shadow ribbon Busbar Serie resistance Solar cell TLM Wire Busbar

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Virtual Metrology using Transfer Learning with domain Knowledge

Virtual Metrology using Transfer Learning with Domain Knowle...

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Joint e-Manufacturing and design Collaboration Symposium (eMdC) & International Symposium on Semiconductor Manufacturing (ISSM)

作者： Masaaki Takada Kazuya Kikuchi Xueting Wang Takumi Ito Gen Li Itakura Akihiro Yasuhisa Oomuro System AI Lab. Advanced Intelligent Systems Corporate R&D Center Toshiba Corporation Kawasaki-shi Japan Advanced Semiconductor Device Development Center Toshiba Electronic Devices & Storage Corporation Ishikawa Japan

ISBN: (数字)9798331510589

ISBN: (纸本)9798331510596

Virtual Metrology (VM) is essential in semiconductor manufacturing for predicting wafer properties using sensor data. However, building accurate VM is challenging due to issues like high dimensionality and nonstationarity. Traditional methods such as Lasso perform feature selection and parameter estimation simultaneously; however they may conflict with domain knowledge. We introduce Weighted Transfer Lasso, a novel method that incorporates domain knowledge into the regression model. Experiments using reactive ion etching data demonstrate improved accuracy and consistency compared to traditional methods, highlighting its potential for reliable VM updates.

关键词： Semiconductor device modeling Accuracy Parameter estimation Transfer learning Semiconductor device manufacture Metrology Ions Feature extraction Production facilities reliability

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Classification of ISAr Images Generated from Model-based Approaches Using deep Learning 39

Classification of ISAR Images Generated from Model-based App...

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39th International Conference on Information Networking, ICOIN 2025

作者： Park, Soyoon Cho, Seonmin Lee, Seongwook Jeong, Taewon Choi, Youngjae Lee, Seungeui Bae, Youngseok Chung-Ang University School of Electrical and Electronics Engineering College of ICT Engineering Seoul Korea Republic of Institute of Radio Frequency Engineering and Electronics Karlsruhe Institute of Technology Karlsruhe Germany Advanced R&D Center Hanwha Systems Gyeonggi-do Korea Republic of Emerging Science and Technology Directorate Agency for Defense Development Daejeon Korea Republic of

ISBN: (纸本)9798331506940

The classification of small, low-observable airborne targets, such as drones and birds, poses significant challenges due to their low detection rates. Conventional vision sensorbased approaches often suffer from reduced performance in low-visibility environments or adverse weather conditions. Additionally, the integration of infrared sensors alongside camera sensors increases hardware complexity and cost, rendering such solutions inefficient. To address these limitations, we propose a method that leverages deep learning and inverse synthetic aperture radar (ISAr) imaging for accurate target classification, using only radar sensors. Our proposed deep learning-based ISAr image classifier comprises two key components: simulated ISAr image generation and deep learning-based classification. We construct simulated ISAr datasets using point scatter (PS) modeling for quadcopter drones, hexacopter drones, and aircraft, and three-dimension (3d) mesh modeling for birds, unmanned aerial vehicles, and quadcopter drones. The two datasets based on PS and 3d mesh modeling are used to train a proposed deep learning classifier. The proposed classifier can achieve a classification accuracy of 98% on the PS-based dataset and 9 6% on the 3d mesh-based dataset, where scattering was calculated using the physical optics method. © 2025 IEEE.

关键词： Inverse synthetic aperture radar

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Quick update of Virtual Metrology using Weighted Transfer Lasso

Quick update of Virtual Metrology using Weighted Transfer La...

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Joint e-Manufacturing and design Collaboration Symposium (eMdC) & International Symposium on Semiconductor Manufacturing (ISSM)

作者： Kazuya Kikuchi Masaaki Takada Wang Xueting Takumi Ito Yasuhisa Oomuro Gen Li Advanced Semiconductor Device Development Center Toshiba Electronic Devices & Storage Corporation Nomi Japan System AI Lab. Advanced Intelligent Systems Corporate R&D Center Toshiba Corporation Kawasaki-Shi Japan

ISBN: (数字)9798331510589

ISBN: (纸本)9798331510596

This paper reports on a new update method for Virtual Metrology (VM). VM is a widely used technique in equipment quality control (QC) of semiconductor manufacturing. When using VMs in a semiconductor factory, VM models must be updated. The traditional approach is to collect a large amount of data over a long period to update the VM. We aim to update VM quickly, achieving high accuracy in a short period. To achieve this aim, we developed a new method called "Weighted Transfer Lasso". In this paper, we report that it achieves high accuracy with quick update VM using Weighted Transfer Lasso. Weighted Transfer Lasso showed a higher correlation coefficient and reasonable variable selection. Therefore, when we launch the new 300mm equipment, we can achieve quick update of VM using Weighted Transfer Lasso.

关键词： Correlation coefficient Semiconductor device modeling Knowledge engineering Accuracy Input variables Quality control Semiconductor device manufacture Metrology Production facilities

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Exploring deep Learning Methods for Computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(dL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of dL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of dL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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research on HrI Evaluation System and diver Safety Equipment

Research on HRI Evaluation System and Diver Safety Equipment

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Lee, Ye Jun Kim, Min-Gyu Shin, Myung-Jun Park, Tae Sung Kim, Jinhyung Kim, Sunghun Lee, Kichoon Lee, Jihun Min, Jeongtack Research Center Pohang Korea Republic of Pusan National University Hospital Pusan National University School of Medicine Department of Rehabilitation Medicine Busan Korea Republic of Institute of Technology Pusan National University Hospital Department of Convergence Medical Busan Korea Republic of Technical Research Center RNWare Co. Ltd Daegu Korea Republic of Gleam-Systems System Development Division Daejeon Korea Republic of Gleam-Systems Modeling and Simulation Division Daejeon Korea Republic of Marine Leisure Equipment R&d Center Pohang Korea Republic of

ISBN: (纸本)9798331540081

Scuba diving is a common aquatic leisure sport that many individuals enjoy in the sea. With the increasing number of people participating, there is a corresponding rise in related incidents and accidents. Typically, such events are caused by inadequate user proficiency with equipment, sudden onset of physical symptoms, failure to respond to external obstacles, and equipment malfunctions. As interest in scuba diving grows, the development of diver safety equipment that enhances convenience and usability through the interaction between divers and equipment is crucial, not only to assist underwater activities but also to preemptively prevent accidents. This paper explores the analysis of divers' physiological conditions and diver equipment evaluation criteria. Building upon this, it proposes a HrI(Human-robot Interaction) evaluation system to facilitate the research and development of safety equipment for secure scuba diving operations. © 2024 IEEE.

关键词： Human robot interaction

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PCd Milling Cutter remaining Useful Life Prediction for Titanium and Aluminum Mirror Milling by Using S2S-LSTM deep Learning Technology

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Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao 2021年第5期42卷 461-470页

作者： Chen, Shang-Liang Lee, Kuei-Ming Huang, Yen-Hsiang Lu, Yu-Ting Lin, Yu-Fu Huang, Ho-Chuan Institute of Manufacturing Information and Systems National Cheng Kung University Tainan70101 Taiwan Micro Mechanical Manufacturing R&D Department Metal Industries Research & Development Centre Kaohsiung811 Taiwan Department of Intelligent Commerce National Kaohsiung University of Applied Sciences Kaohsiung824 Taiwan

Both the titanium alloy and aluminum alloy cutting by using Polycrystalline diamond (PCd) milling cutter for obtaining mirror milling surface results are important processing technologies in the industry. To improve the production efficiency or enhance the cutting performance of this cutting technology, the remaining Useful Life (rUL) prediction of PCd milling cutter becomes one of the major issues nowadays. The Sequence to Sequence Long Short-term Memory (S2S-LSTM) is used in this research as the prediction model to carry out PCd milling cutter's rUL prediction, and two times of PCd milling cutting experiments for titanium and aluminum alloy are designed and carried out. In the experiments, the data of the vibration signal, sound signal, and the surface roughnesses of the workpieces are measured and used as the datasets. The prediction model yielded F1-scores of 98.1% and 95.8% by using the validation datasets of the two experiments. The proposed model is also compared with other AI (Artificial Intelligent) models, such as rNN (recurrent Neural Network), GrU (Gated recurrent Unit), and LSTM under the same batch size, epoch, learning rate, and other hyper-parameters. © 2021, Chinese Mechanical Engineering Society. All right reserved.

关键词： Mirrors

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Identification of cell type-specific cell-penetrating peptides through in vivo phage display leveraged by next generation sequencing

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Biomedicine and Pharmacotherapy 2025年 182卷 117740-117740页

作者： Kohl, Franziska Laufkötter, Oliver Firth, Mike Krimpenfort, Luc Mangla, Priyanka Ansarizadeh, Mohammadhassan Geylan, Gökçe Eklund, Lauri de Maria, Leonardo Jakobsson, Lars Wiseman, John Centre for Genomics Research Discovery Sciences BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden Department of Medical Biochemistry and Biophysics Karolinska Institutet Stockholm Sweden Department of Life Science Informatics B-IT Rheinische Friedrich-Wilhelms-Universität Bonn Germany Data Sciences and Quantitative Biology Discovery Sciences BioPharmaceuticals R&D AstraZeneca Cambridge United Kingdom Oligonucleotides and Targeted Delivery Discovery Sciences BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden Oulu Center for Cell-Matrix Research University of Oulu Oulu Finland Faculty of Biochemistry and Molecular Medicine University of Oulu Oulu Finland Biocenter Oulu University of Oulu Oulu Finland Molecular AI Discovery Sciences BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden Division of Systems and Synthetic Biology Department of Life Sciences Chalmers University of Technology Gothenburg Sweden Research and Early Development Respiratory & Immunology BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden

Vascular anomalies (VA) refer to abnormal blood or lymphatic vessel architecture, most often as a result of dysregulated growth. Venous malformations (VM), a subgroup of VAs, are triggered by activating mutations in the Angiopoietin/TIE2-PI3K/AKT/mTOr signaling pathway with TIE2 L914F (gene name TEK) being one of the most frequent mutations in patients with VMs. Although systemic targeting of the overactivated pathway is possible, it would be a therapeutic advantage to restrict treatment to only the affected lesions. To identify peptides with potential selective binding to TIE2 L914F lesions we applied in vivo phage display to TIE2 L914F-overexpressing endothelial cells (ECs) in a subcutaneous matrigel xenograft mouse model of VMs. By panning for lesion-targeting phages in combination with subcellular fractionation, a screen for cell-penetrating candidate phages was established. Employing Next Generation Sequencing (NGS) and a refined bioinformatic analysis we were able to identify many novel cell-penetrating peptides (CPPs). To pinpoint the most selective and viable CCP candidates a hierarchical clustering algorithm was utilized. This method aggregated CPPs with highly similar sequences into a small number of clusters from which consensus sequences could be derived. Selected candidate CPPs exhibited uptake in TIE2 L914F-expressing human umbilical vein endothelial cells (HUVEC) in culture and were able to deliver sirNA into these cells. In conclusion, our NGS bioinformatic-supported approach led to the identification of novel and selective CPPs capable of transporting a sirNA cargo into targeted cells. © 2024

关键词： Bioinformatic analysis Cell-penetrating peptides In vivo phage display Next generation sequencing Vascular anomalies

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High-voltage converter with 2 kV SiC MOSFETs for electric fast charging stations

High-voltage converter with 2 kV SiC MOSFETs for electric fa...

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European Conference on Power Electronics and Applications

作者： david derix Christian Blaum Wolfram Kruschel daniel Heer Andreas Hensel Jonas Pfeiffer Ainhoa Puyadena Mier Juan Mena Carrillo Jürgen Thoma Christoph drexler Michael Schmidhuber Peter Friedrichs Power Electronics and Grid Integration Fraunhofer Institute for Solar Energy Systems Freiburg Germany Advance R&D SUMIDA Components & Modules GmbH Germany Power Module Development Infineon Technologies AG Warstein Germany Technical Marketing Infineon Technologies AG Warstein Germany Business Excellence Infineon Technologies AG Munich Germany Technology Development Infineon Technologies AG Erlangen Germany

ISBN: (数字)9798350364446

ISBN: (纸本)9798350364453

In this project, the power electronic system technology for future high-performance charging systems along highways or large inner-city electric charging stations with several MVA system sizes with reduced material demand is presented. The concept is based on a dC bus with 1.5 kV and corresponding high efficient power electronics to connect the vehicles to the dC grid. This approach leads to a cost-efficient system. Key components are an electrically isolated dC converter based on 2 kV SiC power modules and an inductive transformer with switching frequencies up to 50 kHz and an output power of 175 kW.

关键词： road transportation MOSFET Silicon carbide Switching frequency Europe Multichip modules High-voltage techniques Transformers Power electronics Power generation

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