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arXiv 2019年

作者： Cheng, Zilong Ma, Jun Li, Xiaocong Tomizuka, Masayoshi Lee, Tong Heng The Integrative Sciences and Engineering Programme NUS Graduate School National University of Singapore 119077 Singapore Guangzhou China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States The Department of Mechanical Engineering University of California BerkeleyCA94720 United States

For linear time-invariant (LTI) systems, the design of an optimal controller is a commonly encountered problem in many applications. Among all the optimization approaches available, the linear quadratic regulator (LQR) methodology certainly garners much attention and interest. As is well-known, standard numerical tools in linear algebra are readily available to determine the optimal static LQR feedback gain matrix when all the system state variables are measurable. However, in various certain scenarios where some of the system state variables are not measurable, and consequent prescribed structural constraints on the controller structure arise, the optimization problem can become intractable due to the non-convexity characteristics that can then be present. In such cases, some first-order methods have been proposed to cater to these problems, but all of these methods, if at all successful, are limited to linear convergence. To speed up the convergence, a second-order approach in the matrix space is essential, with appropriate methodology to solve the linear equality constrained static output feedback (SOF) problem with a suitably defined linear quadratic cost function. Thus in this work, an efficient method is proposed in the matrix space to calculate the Hessian matrix by solving several Lyapunov equations. Then a new optimization technique is applied to deal with the indefiniteness of the Hessian matrix. Subsequently, through Newton's method with linear equality constraints, a second-order optimization algorithm is developed to effectively solve the constrained SOF LQR problem. Finally, two numerical examples are described which demonstrate the applicability and effectiveness of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Constrained optimization

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Hybrid Global Flexible Power Point Tracking Algorithm for Photovoltaic Systems

Hybrid Global Flexible Power Point Tracking Algorithm for Ph...

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European Conference on Power Electronics and Applications

作者： Anusha Kumaresan Hossein Dehghani Tafti Glen G. Farivar Josep Pou Kai Strunz Dusit Niyato Energy Research Institute at NTU Interdisciplinary Graduate Programme Nanyang Technological University Singapore Engineering Institute of Technology (EIT) Australia Department of Electrical and Electronic Engineering The University of Melbourne Victoria Australia School of Electrical and Electronic Engineering Nanyang Technological University Singapore Chair for Sustainable Electric Networks and Sources of Energy Technische Universität Berlin Germany School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350364446

ISBN: (纸本)9798350364453

Frequency support in grid-connected photovoltaic (PV) systems is achieved by employing flexible power point tracking (FPPT) algorithms. Subsequently, according to the grid frequency requirements, the PV power is curtailed to a power reference, unlike the traditional method of operating the PV at the maximum power point. In practical cases, the PV arrays are prone to partial shading, and hence, there is a requirement to formulate the FPPT algorithms that operates effectively during such cases. Moreover, fast transient response is a necessity, which implies that the algorithms proposed in this paper is desirable. This paper proposes a hybrid global FPPT (GFPPT) algorithm based on secant and Newton’s method, to shift the PV operating point to the required power reference. The Newton’s method offers quadratic convergence rate and the secant method guarantees convergence. Hence, a hybrid algorithm consisting of these two methods will provide both fast and guaranteed convergence. Validation through simulation is presented in this paper and the proposed method is compared with the recently presented perturb and observe (P&O) GFPPT algorithm in the literature.

关键词： Photovoltaic systems Transient response Europe Voltage Hybrid power systems Convergence

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Coastalwql for Stitching, Pre-Processing and Visualization of Push Broom Hyperspectral Imagery for Uav-Based Coastal Water Quality Monitoring

SSRN

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SSRN 2023年

作者： Pak, Hui Ying Kieu, Hieu Trung Law, Adrian Wing-Keung Lin, Weisi Khoo, Eugene Environmental Process Modelling Centre Nanyang Environment and Water Research Institute Nanyang Technological University 1 CleanTech Loop 637141 Singapore Interdisciplinary Graduate Programme Graduate College Nanyang Technological University 61 Nanyang Drive 637335 Singapore School of Civil and Environmental Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Engineering and Project Management Division Maritime and Port Authority of Singapore Singapore119963 Singapore

In recent years, Unmanned-Aerial Vehicles (UAVs) and hyperspectral sensors are emerging as popular alternatives for monitoring water quality on-demand. However, image stitching for largely featureless scenes such as open seas has shown to be challenging, and few studies have delved into this domain for push broom hyperspectral images. This study introduces CoastalWQL, with a proposed workflow that entails a GPS-based image stitching method with time delay correction, on top of essential pre-processing procedures to improve the quality of the image mosaic such as sun glint correction and object classification using either an XGBoost and U-net model. CoastalWQL also provides the flexibility for users to specify a trained Deep Neural Network (DNN) or XGBoost model to produce a prediction map for water quality monitoring applications, and a visualization platform to efficiently generate production-ready maps. The results of CoastalWQL have been validated with field surveys at the coastal region of Singapore. © 2023, The Authors. All rights reserved.

关键词： Remote sensing

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Learning stochastic majority votes by minimizing a PAC-bayes generalization bound 21

Learning stochastic majority votes by minimizing a PAC-bayes...

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Proceedings of the 35th International Conference on Neural Information Processing Systems

作者： Valentina Zantedeschi Paul Viallard Emilie Morvant Rémi Emonet Amaury Habrard Pascal Germain Benjamin Guedj Inria Lille - Nord Europe research centre France and The Inria London Programme France and UK and University College London Department of Computer Science Centre for Artificial Intelligence UK Univ Lyon UJM-Saint-Etienne CNRS Institut d Optique Graduate School Laboratoire Hubert Curien UMR 5516 Saint-Etienne France Département d'informatique et de génie logiciel Université Laval Québec Canada

ISBN: (纸本)9781713845393

We investigate a stochastic counterpart of majority votes over finite ensembles of classifiers, and study its generalization properties. While our approach holds for arbitrary distributions, we instantiate it with Dirichlet distributions: this allows for a closed-form and differentiable expression for the expected risk, which then turns the generalization bound into a tractable training objective. The resulting stochastic majority vote learning algorithm achieves state-of-the-art accuracy and benefits from (non-vacuous) tight generalization bounds, in a series of numerical experiments when compared to competing algorithms which also minimize PAC-Bayes objectives – both with uninformed (data-independent) and informed (data-dependent) priors.

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Candidate eclipsing binary systems with a δ Scuti star in Northern TESS field

arXiv

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arXiv 2022年

作者： Aliçavuş, Filiz Kahraman Gümüs, D. Kırmızıtas, Ö. Ekinci, Ö. Çavuş, S. Kaya, Y.T. Aliçavuş, F. Çanakkale Onsekiz Mart University Faculty of Sciences and Arts Physics Department Çanakkale17100 Turkey Çanakkale Onsekiz Mart University Astrophysics Research Center Ulup0131nar ̆ Observatory ÇanakkaleTR-17100 Turkey Istanbul University Institute of Graduate Studies in Science Programme of Astronomy and Space Sciences Beyazıt Istanbul34116 Turkey Çanakkale Onsekiz Mart University School of Graduate Studies Department of Physics ÇanakkaleTR-17100 Turkey Çanakkale Onsekiz Mart University School of Graduate Studies Department of Space Sciences and Technologies ÇanakkaleTR-17100 Turkey Çanakkale Onsekiz Mart University Faculty of Engineering Computer Engineering ÇanakkaleTR-17100 Turkey

Existence of pulsating stars in eclipsing binaries have been known for decades. These types of objects are extremely valuable systems for astronomical studies as they exhibit both eclipsing and pulsation variations. The eclipsing binaries are the only way to directly measure the mass and radius of stars with a good accuracy (≤ 1%), while the pulsations are a unique way to probe the stellar interior via oscillation frequencies. There are different types of pulsating stars existing in eclipsing binaries. One of them is the δ Scuti variables. Currently, the known number of δ Scuti stars in eclipsing binaries is around 90 according to the latest catalog of these variables. An increasing number of these kinds of variables is important to understand the stellar structure, evolution and the effect of binarity on the pulsations. Therefore, in this study, we focus on discovering new eclipsing binaries with δ Scuti component(s). We searched for the northern TESS field with a visual inspection by following some criteria such as light curve shape, the existence of pulsation like variations in the out-of-eclipse light curve and the Teff values of the targets. As a result of these criteria, we determined some targets. The TESS light curves of the selected targets first were removed from the binarity and frequency analysis was performed on the residuals. The luminosity, absolute and bolometric magnitudes of the targets were calculated as well. To find how much of these parameters represent the primary binary component (more luminous) we also computed the flux density ratio of the systems by utilizing the area of the eclipses. In addition, the positions of the systems in the H-R diagram was examined considering the flux density ratios. As a consequence of the investigation, we defined 38 candidates δ Scuti and also one Maia variable in eclipsing binary systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Stars

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Learning stochastic majority votes by minimizing a PAC-bayes generalization bound

arXiv

引用

arXiv 2021年

作者： Zantedeschi, Valentina Viallard, Paul Morvant, Emilie Emonet, Rémi Habrard, Amaury Germain, Pascal Guedj, Benjamin Inria Lille - Nord Europe research centre France The Inria London Programme France University College London Department of Computer Science Centre for Artificial Intelligence United Kingdom Univ Lyon UJM-Saint-Etienne CNRS Institut d Optique Graduate School Laboratoire Hubert Curien UMR 5516 Saint-EtienneF-42023 France Département d’informatique et de génie logiciel Université Laval Québec Canada

关键词： Stochastic systems

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Decomposing 3D Neuroimaging into 2+1D Processing for Schizophrenia Recognition

arXiv

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arXiv 2022年

作者： Hu, Mengjiao Jiang, Xudong Sim, Kang Zhou, Juan Helen Guan, Cuntai Interdisciplinary Graduate Programme NTU Institute for Health Technologies Nanyang Technological University Singapore Center for Sleep and Cognition Department of Medicine Yong Loo Lin School of Medicine National University of Singapore Singapore School of Electrical & Electronic Engineering Nanyang Technological University Singapore Singapore Singapore Translational Magnetic Resonance Research Yong Loo Lin School of Medicine National University of Singapore Singapore School of Computer Science and Engineering School of Electrical and Electronic Engineering Nanyang Technological University Singapore

Deep learning has been successfully applied to recognizing both natural images and medical images. However, there remains a gap in recognizing 3D neuroimaging data, especially for psychiatric diseases such as schizophrenia and depression that have no visible alteration in specific slices. In this study, we propose to process the 3D data by a 2+1D framework so that we can exploit the powerful deep 2D Convolutional Neural Network (CNN) networks pre-trained on the huge ImageNet dataset for 3D neuroimaging recognition. Specifically, 3D volumes of Magnetic Resonance Imaging (MRI) metrics (grey matter, white matter, and cerebrospinal fluid) are decomposed to 2D slices according to neighboring voxel positions and inputted to 2D CNN models pre-trained on the ImageNet to extract feature maps from three views (axial, coronal, and sagittal). Global pooling is applied to remove redundant information as the activation patterns are sparsely distributed over feature maps. Channel-wise and slice-wise convolutions are proposed to aggregate the contextual information in the third view dimension unprocessed by the 2D CNN model. Multi-metric and multi-view information are fused for final prediction. Our approach outperforms handcrafted feature-based machine learning, deep feature approach with a support vector machine (SVM) classifier and 3D CNN models trained from scratch with better cross-validation results on publicly available Northwestern University Schizophrenia Dataset and the results are replicated on another independent dataset. Copyright © 2022, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Spider Plot Model for Analysis of Individual Appraisal Performance Towards Career Planning in Organizations

引用

Journal of Physics: Conference Series 2019年第1期1179卷

作者： Muhamad Djufri Abdul Malek Bin A Tambi Mustafa Mamat Sukono Budiono Ismanto Hadi Akademi Keuangan dan Bisnis Indonesia Internasional (AKBII) Bandung Indonesia Faculty of Economics and Management Science Universiti Sultan Zainal Abidin Malaysia Master Programme in Management Post Graduate Programme Universitas Narotama Surabaya Indonesia Faculty of Informatice and Computer Science Universiti Sultan Zainal Abidin Malaysia Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Malaysia

Career planning at the organizational level must be translated into career planning at the individual employee level. Performance appraisal can be used more broadly so that it can be the main tool for companies in employee career planning. The purpose of this study is to measure how much influence the Performance Evaluation of Career Planning from employees who have occupied managerial levels goes to the next career level. In this paper, analysis of individual employee performance is carried out using the Spider Plot model. The results of analyzing individual performance from managers in different units can explain quickly and easily the appearance of the Spider Plot diagram. So, it is expected that individual career planning can be easily mapped through performance appraisal so that it can be used in career planning.

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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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Generalized penalty for circular coordinate representation

arXiv

引用

arXiv 2020年

作者： Luo, Hengrui Patania, Alice Kim, Jisu Vejdemo-Johansson, Mikael Lawrence Berkeley National Laboratory 1 Cyclotron Rd BerkeleyCA94720 United States Department of Statistics College of Arts and Sciences Ohio State University 1958 Neil Ave ColumbusOH43210 United States Indiana University 1001 IN-45/46 E SR Bypass BloomingtonIN47408 United States DataShape Team Inria Saclay France LMO Université Paris-Saclay Bâtiment 307 Faculté des Sciences d'Orsay Université Paris-Saclay rue Michel Magat Orsay Île-De-France 91400 France Department of Mathematics CUNY College of Staten Island Computer Science Programme CUNY Graduate Center 2800 Victory Boulevard 1S-215 Staten IslandNY10314 United States

MSC Codes 55N31, 62R40, 68T09Topological Data Analysis (TDA) provides novel approaches that allow us to analyze the geometrical shapes and topological structures of a dataset. As one important application, TDA can be used for data visualization and dimension reduction. We follow the framework of circular coordinate representation, which allows us to perform dimension reduction and visualization for high-dimensional datasets on a torus using persistent cohomology. In this paper, we propose a method to adapt the circular coordinate framework to take into account the roughness of circular coordinates in change-point and high-dimensional applications. To do that, we use a generalized penalty function instead of an L2 penalty in the traditional circular coordinate algorithm. We provide simulation experiments and real data analyses to support our claim that circular coordinates with generalized penalty will detect the change in high-dimensional datasets under different sampling schemes while preserving the topological structures. Copyright © 2020, The Authors. All rights reserved.

关键词： Clustering algorithms

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