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IEEE Petroleum and Chemical Industry Conference - Brasil (PCIC Brasil)

作者： Joseph K. Banda Lucas S. Araujo Danilo I. Brandao Fernando P. Marafão Elisabetta Tedeschi Department of Electric Power Engineering Norwegian University of Science and Technology (NTNU) Trondheim Norway Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais (UFMG) Belo Horizonte Brazil Department of Control and Automation Engineering Universidade Estadual Paulista (Unesp) Sorocaba Brazil Department of Industrial Engineering University of Trento Trento Italy

ISBN: (数字)9798350368154

ISBN: (纸本)9798350368161

The electrification of offshore oil and gas platforms (OOGPs), using offshore wind turbines, is now a reality, aimed at minimizing carbon emissions. In this scenario, the utilization of battery energy storage systems (BESS) improves both efficiency and power quality. As this integration comes with a high CAPEX, industries demand exploring BESS for multiple ancillary services on OOGPs. Thus, this paper proposes an alternative approach to energizing a power transformer (PT) using the BESS power conversion system (PCS) on the platform, aiming to minimize inrush currents. This avoids the necessity for additional bulky devices, converters, or dc voltage sources specifically designated for this purpose. The strategy consists of manipulating residual core flux using BESS PCS followed by a controlled switching, which reduces inrush currents during PT energization. The results show effective reduction of the inrush current from 2.31 pu to 0.16 pu for the presented case study.

关键词： Offshore installations Battery energy storage system Oils Voltage Switches Oil insulation Transformer cores

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Implementation of a Current Linear Regulator Based on a GaN HEMT for Laser Diode Manipulations

Implementation of a Current Linear Regulator Based on a GaN ...

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International Conference on Power Electronics (ICPE)

作者： Kai-Jun Pai Chang-Hua Lin Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taiwan R.O.C.

In this study, a gallium nitride (GaN) high electron mobility transistor (HEMT) combined with the operational amplifier was applied to develop a two-level linear regulator (TLLR). Using the TLLR, the operating current of the laser diode can be formed in the constant-current or pulse-width modulation mode to emit the continuous-wave or short-pulsed laser, respectively. When the operating current of the laser diode was operated at the high-frequency PWM, the parasitic elements on the GaN HEMT, laser diodes, print-circuit board (PCB), and power wires influence the rising-edge slope of the laser operating current. In accordance with the physical packages of the GaN HEMT and laser diode, their equivalent circuit model parameters were provided in this study; therefore, the TLLR simulation circuit with its parasitic element was established. The simulation and experiment waveforms can be obtained to confirm the developed TLLR.

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Parallel Approximations for High-Dimensional Multivariate Normal Probability Computation in Confidence Region Detection Applications

Parallel Approximations for High-Dimensional Multivariate No...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Xiran Zhang Sameh Abdulah Jian Cao Hatem Ltaief Ying Sun Marc G. Genton David E. Keyes Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Statistics Program King Abdullah University of Science and Technology Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Mathematics The University of Houston Houston Texas USA

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

Addressing the statistical challenge of computing the multivariate normal (MVN) probability in high dimensions holds significant potential for enhancing various applications. For example, the critical task of detecting confidence regions where a process probability surpasses a specific threshold is essential in diverse applications, such as pinpointing tumor locations in magnetic resonance imaging (MRI) scan images, determining hydraulic parameters in groundwater flow issues, and forecasting regional wind power to optimize wind turbine placement, among numerous others. One common way to compute high-dimensional MVN probabilities is the Separation-of-Variables (SOV) algorithm. This algorithm is known for its high computational complexity of O(n 3 ) and space complexity of O(n 2 ), mainly due to a Cholesky factorization operation for an n×n covariance matrix, where n represents the dimensionality of the MVN problem. This work proposes a high-performance computing framework that allows scaling the SOV algorithm and, subsequently, the confidence region detection algorithm. The framework leverages parallel linear algebra algorithms with a task-based programming model to achieve performance scalability in computing process probabilities, especially on large-scale systems. In addition, we enhance our implementation by incorporating Tile Low-Rank (TLR) approximation techniques to reduce algorithmic complexity without compromising the necessary accuracy. To evaluate the performance and accuracy of our framework, we conduct assessments using simulated data and a wind speed dataset. Our proposed implementation effectively handles high-dimensional multivariate normal (MVN) probability computations on shared and distributed-memory systems using finite precision arithmetics and TLR approximation computation. Performance results show a significant speedup of up to 20X in solving the MVN problem using TLR approximation compared to the reference dense solution without sacrificin

关键词： Accuracy Tensors Wind speed Magnetic resonance imaging Linear algebra Wind power generation Approximation algorithms

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IoT and Peer-to-peer Signal Notification Methods Reduce the Time Needed to Detect Wildfire Heat Points

IoT and Peer-to-peer Signal Notification Methods Reduce the ...

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International Conference on Green technology and Sustainable Development (GTSD)

作者： Nattawat Panlawan Teerasak Somsak Jutturit Thongpron Worrajak Muangjai Montri Ngaodet Visut Assanavijit Phiched Thanin Suriyon Sungkham Kosol Oranpiroj Noppom Patcharaprakiti Peeraya Somsak Kan Nakaiam Faculty of Engineering RMUTL Program in Electrical Engineering Chiang Mai Thailand College of Integrated Science and Technology RMUTL Chiang Mai Thailand Research and Development Institute RMUTL Chiang Mai Thailand Faculty of Business Administration and Liberal Arts RMUTL Chiang Mai Thailand

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

The issue of dust and smoke resulting from forest fires in northern Thailand. This is caused by people burning the forest to get forest products. Individuals can start forest fires by intentionally burning the forest to extract forest resources. Deforestation negatively affects the well-being of vulnerable patients and has repercussions on public health. The decrease in tourist numbers impacts the economy. Individuals setting fire to the forest to gather forest resources impact government and public sector connections. The education sector has implemented many strategies to educate and mitigate forest fires. There is a fire suppression system. Remove garbage, leaves, and branches that are flammable. However, forest fires remain a concern. Collaboration among three entities in the community can aid in preventing unauthorized forest fires through communal procedures. From multiple ministries, the local organization department, and the central government Collaborating to safeguard Forest fire suppression and afforestation This study is a component of the forest fire surveillance division. If the forest fire's location is not clearly indicated, participating in combined operations will lead to issues because of the overlap in operational responsibilities. Previously, thermal imaging satellites were utilized for coordinate determination. If the satellite completes two orbits each day and identifies a hot location, it initiates a forest fire. Firefighters cannot reach the area to put out forest fires; thus, they need to enter from a nearby, accessible location. Joining the forest fire prevention volunteer organization is challenging and will require approximately 24 to 25 hours. This study aims to conserve energy by utilizing an loT system that transmits peer-to-peer signals. Individuals are prepared to dismantle this system. The villagers can develop it themselves due to its modest cost of $10. During a forest fire (temperature exceeding 50 degrees Celsius), specific ope

关键词： Meters Heating systems Temperature distribution Wildfires Satellites Government Forestry

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technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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A Framework for Selecting and Implementing Ground Mobile Inspection Robots in Industrial Applications

A Framework for Selecting and Implementing Ground Mobile Ins...

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IEEE Latin American Robotics Symposium, LARS

作者： Filipe Silveira Reynaldo Mateus Gago Ralf Luis De Moura Gustavo Medeiros Freitas Industrial Technology Architecture Vale S.A Coronel Fabriciano MG Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Industrial Technology Architecture Vale S.A Vitória ES Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

The utilization of ground mobile inspection robots in industrial applications has gained significant traction due to their ability to enhance safety, efficiency, and data accuracy in hazardous environments. This paper introduces a framework designed to assist in selecting and implementing these robots in industrial setting, addressing the critical need for choosing the most suitable for specific inspection tasks. The framework categorizes critical capabilities into several key domains including navigation, inspection, integration, constructive characteristics and support. Then, this paper evaluates nine robots based on those domains, revealing significant variances in their capabilities, and establishes a workflow for selecting the most suitable robots to address the specific needs of different inspection tasks. This paper concludes that the adoption of this framework and workflow may guide industries in making informed decisions about integrating inspection robots, thereby improving operational safety, reducing risks, and enhancing inspection efficiency.

关键词： Industries Systematics Accuracy Service robots Navigation Focusing Inspection programming Safety

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Grafted AlGaAs/GeSn Optical Pumping Laser Operating up to 130 K

arXiv

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arXiv 2024年

作者： Zhou, Jie Vincent, Daniel Acharya, Sudip Ojo, Solomon Abrand, Alireza Liu, Yang Gong, Jiarui Liu, Dong Haessly, Samuel Shen, Jianping Xu, Shining Li, Yiran Lu, Yi Stanchu, Hryhorii Mawst, Luke Claflin, Bruce Mohseni, Parsian K. Ma, Zhenqiang Yu, Shui-Qing Department of Electrical and Computer Engineering University of Wisconsin - Madison Madison53706 United States Department of Electrical Engineering University of Arkansas FayettevilleAR72701 United States Microelectronics-Photonics Program University of Arkansas FayettevilleAR72701 United States Department of Electrical and Microelectronic Engineering Rochester Institute of Technology RochesterNY14623 United States Air Force Research Laboratory Wright-Patterson AFB OH45433 United States

Group IV GeSn double-heterostructure (DHS) lasers offer unique advantages of a direct bandgap and CMOS compatibility. However, further improvements in laser performance have been bottlenecked by limited junction properties of GeSn through conventional epitaxy and wafer bonding. This work leverages semiconductor grafting to synthesize and characterize optically pumped ridge edge-emitting lasers (EELs) with an AlGaAs nanomembrane (NM) transfer-printed onto an epitaxially grown GeSn substrate, interfaced by an ultrathin Al2O3 layer. The grafted AlGaAs/GeSn DHS lasers show a lasing threshold of 11.06 mW at 77 K and a maximum lasing temperature of 130 K. These results highlight the potential of the grafting technique for enhancing charge carrier and optical field confinements, paving the way for room-temperature electrically injected GeSn lasers. Copyright © 2024, The Authors. All rights reserved.

关键词： Wafer bonding

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A peristaltic soft, wearable robot for compression and massage therapy

arXiv

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arXiv 2022年

作者： Zhu, Mengjia Ferstera, Adrian Dinulescu, Stejara Kastor, Nikolas Linnander, Max Hawkes, Elliot W. Visell, Yon Media Arts and Technology Program Department of Electrical and Computer Engineering Department of Mechanical Engineering California NanoSystems Institute University of California Santa Barbara United States Mechanical Engineering Program Department of Mechanical Engineering ETH Zurich Switzerland

Soft robotics is attractive for wearable applications that require conformal interactions with the human body. Soft wearable robotic garments hold promise for supplying dynamic compression or massage therapies, such as are applied for disorders affecting lymphatic and blood circulation. In this paper, we present a wearable robot capable of supplying dynamic compression and massage therapy via peristaltic motion of finger-sized soft, fluidic actuators. We show that this peristaltic wearable robot can supply dynamic compression pressures exceeding 22 kPa at frequencies of 14 Hz or more, meeting requirements for compression and massage therapy. A large variety of software-programmable compression wave patterns can be generated by varying frequency, amplitude, phase delay, and duration parameters. We first demonstrate the utility of this peristaltic wearable robot for compression therapy, showing fluid transport in a laboratory model of the upper limb. We theoretically and empirically identify driving regimes that optimize fluid transport. We second demonstrate the utility of this garment for dynamic massage therapy. These findings show the potential of such a wearable robot for the treatment of several health disorders associated with lymphatic and blood circulation, such as lymphedema and blood clots. © 2022, CC BY.

关键词： Blood

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The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

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2022 IEEE Creative Communication and Innovative technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of Computer Science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

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Development of Color Detection Based on Camera Infrared Filter with Python Image Processing

Development of Color Detection Based on Camera Infrared Filt...

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Student Conference on Research and Development (SCOReD)

作者： Joshu Leonardy Nawal Zuhdaniel Aflah Mohd Rashidi Bin Salim Mohd Haniff Bin Ibrahim Hadi Bin Manap Wildan Panji Tresna Faculty of Electrical Engineering Universiti Teknologi Malaysia JohorBahru Malaysia Military Physics Study Program The Republic of Indonesia Defense University Bogor Indonesia Faculty of Electrical & Electronic Engineering Technology University Malaysia Pahang Al Sultan Abdullah Pekan Malaysia Research Center for Photonics National Research and Inovation Agency Indonesia South Tangerang Indonesia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

This research explores the use of a modified infrared (IR) camera equipped with a high-pass filter to distinguish between natural objects (vegetation) and artificial objects (synthetic military uniforms) in an environment where vegetation makes objects difficult to detect. In military operations, especially guerrilla warfare in tropical forests, detecting enemies camouflaged in vegetation makes it difficult to distinguish targeted objects. Visible light cameras usually struggle to distinguish between synthetic and natural colors. This methodology involves the use of Python programming and various libraries, such as Computer Vision (CV), to process images captured by modified cameras. A graphical user interface (GUI) was developed to analyze color values, focusing on the red, green, and blue spectra. The results show that the modified IR camera can more effectively separate synthetic and natural object color peaks compared to a standard visible light camera, offering potential applications in military reconnaissance and sniper operations. This research demonstrates how image processing can improve object detection in complex environments.

关键词： Image color analysis Vegetation mapping Object detection Reconnaissance programming Cameras Standards Research and development Graphical user interfaces Python

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