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6. GMM-Workshops Mikro-Nano-Integration - 6th GMM Workshop on Micro-Nano-Integration

作者： Klauser, W. Bartenwerfer, M. Elfert, P. Krauskopf, E. Fatikow, S. Division Microrobotics and Control Engineering Department of Computing Science University of Oldenburg OldenburgD-26129 Germany

ISBN: (纸本)9783800742783

This work combines the Electron Beam induced Deposition technique with a purposeful scanning pattern generation for the scanning electron microscope by means of a self-developed scan generator. This allows for deposition of nanogranular metal structures with specific geometries, which can be used as strain sensors on the nano- and microscale. Furthermore, the deposition process is combined with a vision-based automation sequence using a self-developed software framework for drift compensation. © 2016 VDE VERLAG GMBH ∙ Berlin ∙ Offenbach

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Modeling and compensating thermal drift in time divergent AFM measurements 6

Modeling and compensating thermal drift in time divergent AF...

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6. GMM-Workshops Mikro-Nano-Integration - 6th GMM Workshop on Micro-Nano-Integration

作者： Krauskopf, J.E. Bartenwerfer, M. Fatikow, S. Division Microrobotics and Control Engineering Department of Computing Science University of Oldenburg OldenburgD-26129 Germany

ISBN: (纸本)9783800742783

Thermal drift is a problem in imaging with atomic force microscopes. In this work we present an extension of the well known gradient-based methods for optical flow calculation, developed by Horn & Schunk as well as Lucas & Kanade. We also analyse different trajectories and evaluate their suitability for use with the aforementioned methods. As part of this theoretical work, we are able to show that the methods by Horn & Schunk and Lucas & Kanade are extendable to the thermal drift problem. Furthermore, we compare different standard trajectories with a self-developed evaluation system and propose a favourable trajectory for drift estimation and compensation. © 2016 VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Trajectories

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An auto-tuning controller for networked control systems 15

An auto-tuning controller for networked control systems

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15th International Conference on Electronics, Information, and Communications, ICEIC 2016

作者： Thuy, Pham Xuan Hiep, Nguyen Tran Automatic Control and Computing Engineering Department Le Quy Don Technical University Hanoi Viet Nam

ISBN: (纸本)9781467380164

In this paper, we introduce a proportional-integral-derivative (PID) auto-tuning controller by using relay feedback and online gain updating method for networked control systems (NCSs). The proposed controller takes both advantages of relay feedback, which provides the initial knowledge of the control system, and updating method, that adapts to the changing input and load disturbance. In order to validate the effectiveness of our design, the proposed controller is evaluated experimentally with cFP 2220 platform from National Instruments, and with LabVIEW programming software. The results show that our design obtains superior tracking performance. © 2016 IEEE.

关键词： controllers

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Exploring the scalability of multiple signatures in iris recognition using GA on the acceptance frontier search

Exploring the scalability of multiple signatures in iris rec...

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Congress on Evolutionary Computation

作者： Fernando Bernardo Gladston Moreira Eduardo Luz Paulo H. C. Oliveira Álvaro Gaurda Automation and Control Engineering Department Universidade Federal de Ouro Preto Ouro Preto MG Brazil Computing Department Universidade Federal de Ouro Preto Ouro Preto MG Brazil

ISBN: (纸本)9781509046027

For decades iris recognition has been widely studied by the scientific community due to its almost unique and stable patterns. Iris recognition biometric systems apply mathematical pattern-recognition techniques to an iris' image of an individual's eye to extract its feature vector. Comparing the dissimilarities from two feature vectors with an acceptance threshold, the system decides if the two vectors are from the same individual's eye. If applied in a well-controlled environment, iris recognition can achieve outstanding accuracies, however, to accomplish that in non-controlled environments is still a challenge researchers are constantly trying to compensate open issues in this context. In order to better explore the patterns found in the iris, researchers have recently begun using a classification approach using multiple signatures, hoping to improve the algorithm robustness. This work aims to explore the effectiveness and scalability of using multiple signatures with a 2-D Gabor filter in a biometric verification system through iris recognition. This is done using two independent Genetic Algorithms to search for the best parameters to the feature extraction technique and on the acceptance frontier search. The method was evaluated by analyzing the behavior of the Half Total Error Rate (HTER) when the number of partitions varies. The experiments showed that the best result was found with 12 partitions on the iris, reaching 0.21% of HTER.

关键词： Iris recognition Feature extraction Genetic algorithms Image segmentation Databases Iris Robustness

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Multitarget tracking with the von mises-fisher filter and probabilistic data association

Multitarget tracking with the von mises-fisher filter and pr...

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作者： Markovíc, Ivan Bukal, Mario Cesíc, Josiṕ Petrovíc, Ivan Department of Computer and Control Engineering University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Department of Applied Mathematics University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

Directional data emerge in many scientific disciplines due to the nature of the observed phenomena or the working principles of a sensor. The problem of tracking with direction-only sensors is challenging since the motion of the target typically resides either in 3D or 2D Euclidean space, while the corresponding measurements reside either on the unit sphere or the unit circle, respectively. Furthermore, in multitarget tracking there is the need to deal with the problem of pairing sensors measurements with targets in the presence of clutter (the data association problem). In this paper we propose to approach multitarget tracking in clutter with directiononly data by setting it on the unit hypersphere, thus tracking the objects with a Bayesian estimator based on the von Mises-Fisher distribution and probabilistic data association. To achieve this goal we derive the probabilistic data association (PDA) filter and the joint probabilistic data association (JPDA) filter for the Bayesian von Mises-Fisher estimation on the unit hypersphere. The final PDA and JPDA filter equations are derived with respect to the Kullback-Leibler divergence by preserving the first moment of the hyperspherical distribution. Although the fundamental equations are given for the hyperspherical case, we focus on the filters on the unit 1-sphere (circle in 2) and the unit 2-sphere (surface of the unit ball in 3). The proposed approach is validated through synthetic data experiments on 100 Monte Carlo runs simulating multitarget tracking with noisy directional measurements and clutter. © 2016 JAIF.

关键词： Clutter (information theory)

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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Fault diagnosis for multi-energy flows of energy internet: Framework and prospects

Fault diagnosis for multi-energy flows of energy internet: F...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Tao Wang, Jun Fan, Zhennan Wei, Xiaoguang Zang, Tianlei Pérez-Jiménez, Mario J. Huang, Tao School of Electrical Engineering and Electronic Information Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies and Equipment Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China State Key Laboratory of Security Control and Simulation of Power Systems and Large Scale Generation Department of Electrical Engineering Tsinghua University Beijing China Research Groupon Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla Spain Department of Energy Politecnico di Torino Torino Italy

ISBN: (纸本)9781538614273

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. © 2017 IEEE.

关键词： Failure analysis

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Automatic microtubule tracking in fluorescence images of cells doped with increasing concentrations of taxol and nocodazole

arXiv

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arXiv 2018年

作者： Varrecchia, Marilena Levine, Joshua Olmo, Gabriella Grangetto, Marco Gai, Marta Di Cunto, Ferdinando Dept. of Control and Computing Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino Italy Computer Science Dept. Corso Svizzera 185 Torino Italy Department of Molecular Biotechnology and Health Sciences University of Torino Via Nizza 52 Torino Italy Neuroscience Institute Cavalieri Ottolenghi University of Torino c.o. Azienda Ospedaliero-Universitaria San Luigi Gonzaga Regione Gonzole 10 Orbassano Italy

In this paper we explore detection and tracking of astral microtubules, a sub-population of microtubules which only exists during and immediately before mitosis and aids in the spindle orientation by connecting it to the cell cortex. Its analysis can be useful to determine the presence of certain diseases, such as brain pathologies and cancer. The proposed algorithm focuses on overcoming the problems regarding fluorescence microscopy images and microtubule behaviour by using various image processing techniques and is then compared with three existing algorithms, tested on consistent sets of images. Copyright © 2018, The Authors. All rights reserved.

关键词： Fluorescence microscopy

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Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program

arXiv

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arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

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Device-independent verification of Einstein-Podolsky-Rosen steering

arXiv

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arXiv 2019年

作者： Zhao, Yuan-Yuan Zhang, Chao Cheng, Shuming Li, Xinhui Guo, Yu Liu, Bi-Heng Ku, Huan-Yu Chen, Shin-Liang Wen, Qiaoyan Huang, Yun-Feng Xiang, Guo-Yong Li, Chuan-Feng Guo, Guang-Can College of the Science China University of Petroleum Qingdao266580 China National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructure Nanjing University Nanjing210093 China Peng Cheng Laboratory Shenzhen518055 China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei230026 China Department of Control Science and Engineering Tongji University Shanghai201804 China Institute for Advanced Study Tongji University Shanghai200092 China Institute for Quantum Computing Baidu Research Beijing100193 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China National Laboratory of Solid State Microstructures School of Physics Nanjing University Nanjing210093 China Faculty of Physics University of Vienna Boltzmanngasse 5 Vienna1090 Austria Austrian Academy of Sciences Boltzmanngasse 3 Vienna1090 Austria Department of Physics National Chung Hsing University Taichung40227 Taiwan

Entanglement lies at the heart of quantum mechanics, and has been identified an essential resource for diverse applications in quantum information. If entanglement could be verified without any trust in the devices of observers, i.e., in a device-independent (DI) way, then the high security can be guaranteed for various quantum information processing tasks. In this work, we propose and experimentally demonstrate a DI protocol to certify the presence of entanglement based on Einstein-Podolsky-Rosen (EPR) steering. We first establish the DI verification framework by taking the advantages of measurement-device-independent technique and self-testing, which is able to verify all bipartite EPR-steerable states. In the scenario of three-measurement settings for per party, the protocol is robust in tolerance of inefficient measurements and imperfect self-testing. Moreover, a four-photon experiment is implemented for verification beyond Bell nonlocal states. Our work presents the new insight into quantum physics and paves the way for realistic implementations of secure quantum information processing tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum optics

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