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467 results on '"Toyota Technological Institute"'

1. Charge Generation in a Dye-Sensitized Solid-State Cell under Different Modes of Illumination

Author: Sirimanne, P.M., Shirata, T., Soga, T., and Jimbo, T.
Published: 2002
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2. Compartmentalizing the cuprate strange metal

Author: Berben, M., Ayres, J., Duffy, C., Hinlopen, R. D. H., Hsu, Y. -T., Leroux, M., Gilmutdinov, I., Massoudzadegan, M., Vignolles, D., Huang, Y., Kondo, T., Takeuchi, T., Cooper, J. R., Friedemann, S., Carrington, A., Proust, C., Hussey, N. E., High Field Magnet Laboratory (HFML-EMFL), Radboud University [Nijmegen], H. H. Wills Physics Laboratory [Bristol], University of Bristol [Bristol], Laboratoire national des champs magnétiques intenses - Toulouse (LNCMI-T), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Van der Waals-Zeeman Institute, University of Amsterdam [Amsterdam] (UvA), Institute for Solid State Physics [Tokyo] (ISSP), The University of Tokyo (UTokyo), Toyota Technological Institute, Toyota Technological Institute - Nagoya, Cavendish Laboratory, and University of Cambridge [UK] (CAM)
Subjects: [PHYS.COND.CM-S]Physics [physics]/Condensed Matter [cond-mat]/Superconductivity [cond-mat.supr-con], Superconductivity (cond-mat.supr-con), Condensed Matter - Strongly Correlated Electrons, Strongly Correlated Electrons (cond-mat.str-el), Condensed Matter::Superconductivity, Condensed Matter - Superconductivity, FOS: Physical sciences, [PHYS.COND.CM-SCE]Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]
Abstract: 28 pages including supplementary; It has long been recognized that the key to unlocking the mystery of cuprate high-Tc superconductivity lies in understanding the anomalous normal state from which pairs form and condense. While many of its defining properties have been identified, they are often considered either at a singular doping level or as an isolated phenomenon as a function of doping. As a result, their relation to each other and to the pseudogap (PG), strange metal (SM) and non-superconducting (non-SC) regimes that define the cuprate phase diagram has yet to be elucidated. Here, we report a high-field in-plane MR study on several cuprate families spanning all 3 regimes that reveal a complex yet nonetheless systematic evolution of the form of the MR, with each regime possessing its own distinct scaling behavior. In the PG regime, the MR exhibits pure H/T^2 scaling at low fields and H-linearity at the highest field strengths. While the H-linearity persists inside the SM regime, the scaling changes abruptly to H/T. The size of the H-linear slope, meanwhile, is found to be correlated with both the T-linear resistivity coefficient and Tc, strengthening the characterization of the SM regime as a quantum critical phase. We interpret the omnipresence of H-linear MR across both regimes as a signature of highly anisotropic, possibly discontinuous features on the Fermi surface. Finally, within the non-SC, Fermi-liquid regime, we observe a recovery of conventional Kohler scaling. This comprehensive study establishes the distinct nature of the magnetotransport within each regime and identifies power-law scaling of the normal state MR as a defining feature of SC hole-doped cuprates. The incompatibility of such power-law scaling with any known variant of Boltzmann transport theory motivates the quest for an altogether new theoretical framework, one in which the MR is entirely decoupled from elastic impurity scattering.
Published: 2022

3. Stochastic Bandits with Vector Losses: Minimizing $\ell^\infty$-Norm of Relative Losses

Author: Shang, Xuedong, Shao, Han, Qian, Jian, Scool (Scool), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Sequential Learning (SEQUEL), Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), and Massachusetts Institute of Technology (MIT)
Subjects: FOS: Computer and information sciences, Computer Science - Machine Learning, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Statistics - Machine Learning, Machine Learning (stat.ML), Machine Learning (cs.LG)
Abstract: Multi-armed bandits are widely applied in scenarios like recommender systems, for which the goal is to maximize the click rate. However, more factors should be considered, e.g., user stickiness, user growth rate, user experience assessment, etc. In this paper, we model this situation as a problem of $K$-armed bandit with multiple losses. We define relative loss vector of an arm where the $i$-th entry compares the arm and the optimal arm with respect to the $i$-th loss. We study two goals: (a) finding the arm with the minimum $\ell^\infty$-norm of relative losses with a given confidence level (which refers to fixed-confidence best-arm identification); (b) minimizing the $\ell^\infty$-norm of cumulative relative losses (which refers to regret minimization). For goal (a), we derive a problem-dependent sample complexity lower bound and discuss how to achieve matching algorithms. For goal (b), we provide a regret lower bound of $\Omega(T^{2/3})$ and provide a matching algorithm., Comment: 14 pages
Published: 2020
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4. Structure Adaptive Algorithms for Stochastic Bandits

Author: Degenne, Rémy, Shao, Han, Koolen, Wouter M., Statistical Machine Learning and Parsimony (SIERRA), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Centrum voor Wiskunde en Informatica (CWI), Centrum Wiskunde & Informatica (CWI)-Netherlands Organisation for Scientific Research, This work was funded in part by the French government under management of Agence Nationale de la Recherche as part of the 'Investissements d’avenir' program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute). H. Shao is supported in part by the National Science Foundation under grant CCF-181501., and ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019)
Subjects: Computer Science::Machine Learning, FOS: Computer and information sciences, Computer Science - Machine Learning, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, Machine Learning (stat.ML), Machine Learning (cs.LG)
Abstract: We study reward maximisation in a wide class of structured stochastic multi-armed bandit problems, where the mean rewards of arms satisfy some given structural constraints, e.g. linear, unimodal, sparse, etc. Our aim is to develop methods that are flexible (in that they easily adapt to different structures), powerful (in that they perform well empirically and/or provably match instance-dependent lower bounds) and efficient in that the per-round computational burden is small. We develop asymptotically optimal algorithms from instance-dependent lower-bounds using iterative saddle-point solvers. Our approach generalises recent iterative methods for pure exploration to reward maximisation, where a major challenge arises from the estimation of the sub-optimality gaps and their reciprocals. Still we manage to achieve all the above desiderata. Notably, our technique avoids the computational cost of the full-blown saddle point oracle employed by previous work, while at the same time enabling finite-time regret bounds. Our experiments reveal that our method successfully leverages the structural assumptions, while its regret is at worst comparable to that of vanilla UCB., Comment: 10+18 pages. To be published in the proceedings of ICML 2020
Published: 2020
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5. Prediction of homo- and hetero-protein complexes by protein docking and template-based modeling: a CASP-CAPRI experiment

Author: Eichiro Ichiishi, Dmitri Beglov, Bernard Maigret, Gyu Rie Lee, Artem B. Mamonov, Shoshana J. Wodak, Jonathan C. Fuller, Dima Kozakov, Jong Young Joung, Petr Popov, Xiaofeng Yu, Keehyoung Joo, João P. G. L. M. Rodrigues, Anna Vangone, Koen M. Visscher, Xiaoqin Zou, Paul A. Bates, Andriy Kryshtafovych, Shourya S. Roy Burman, Daisuke Kihara, Romina Oliva, Efrat Ben-Zeev, Jeffrey J. Gray, Yang Shen, Li C. Xue, Sameer Velankar, Emilie Neveu, Shruthi Viswanath, Dina Schneidman-Duhovny, Juan Esquivel-Rodríguez, Mieczyslaw Torchala, Amit Roy, Alexandre M. J. J. Bonvin, David R. Hall, Tanggis Bohnuud, Xusi Han, David W. Ritchie, Ron Elber, Daisuke Kuroda, Zhiwei Ma, Joan Segura, Carlos A. Del Carpio, Nicholas A. Marze, Jong Yun Kim, Andrej Sali, Petras J. Kundrotas, Ezgi Karaca, Neil J. Bruce, Chaok Seok, Panagiotis L. Kastritis, Shen You Huang, Ilya A. Vakser, Lim Heo, Sanbo Qin, Raphael A. G. Chaleil, Adrien S. J. Melquiond, Miguel Romero-Durana, Anisah W. Ghoorah, Surendra S. Negi, Andrey Tovchigrechko, Françoise Ochsenbein, Narcis Fernandez-Fuentes, Liming Qiu, Miriam Eisenstein, Mehdi Nellen, Marie-Dominique Devignes, Lenna X. Peterson, Jinchao Yu, Minkyung Baek, Brian G. Pierce, Hasup Lee, Toshiyuki Oda, Rebecca C. Wade, Raphael Guerois, Juan Fernández-Recio, Iain H. Moal, Edrisse Chermak, Sergei Grudinin, Sangwoo Park, Ivan Anishchenko, Chengfei Yan, Thom Vreven, Kentaro Tomii, Bing Xia, Hyung Rae Kim, Chiara Pallara, Jooyoung Lee, Kazunori D. Yamada, Xianjin Xu, Kenichiro Imai, Zhiping Weng, Luigi Cavallo, Tyler M. Borrman, Jianlin Cheng, Marc F. Lensink, Huan-Xiang Zhou, Jilong Li, Gydo C. P. van Zundert, Brian Jiménez-García, Tsukasa Nakamura, Scott E. Mottarella, Sandor Vajda, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] ( IRI ), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), European Molecular Biology Laboratory, European Bioinformatics Institute, Genome Center [UC Davis], University of California at Davis, Research Support Computing [Columbia], University of Missouri-Columbia, Bioinformatics Consortium and Department of Computer Science [Columbia], Department of Bioengineering and Therapeutic Sciences, University of California [San Francisco] ( UCSF ), Department of Pharmaceutical Chemistry, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, University of California [San Francisco] ( UCSF ) -California Institute for Quantitative Biosciences, GN7 of the National Institute for Bioinformatics (INB) and Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Institute of Biological, Environmental and Rural Sciences ( IBERS ), Institute for Computational Engineering and Sciences [Austin] ( ICES ), University of Texas at Austin [Austin], Department of Computer Science, Department of Chemistry, Algorithms for Modeling and Simulation of Nanosystems ( NANO-D ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Laboratoire Jean Kuntzmann ( LJK ), Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Institut National Polytechnique de Grenoble ( INPG ), Moscow Institute of Physics and Technology [Moscow] ( MIPT ), Seoul National University [Seoul], Florida State University [Tallahassee] ( FSU ), Computational Algorithms for Protein Structures and Interactions ( CAPSID ), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Department of Complex Systems, Artificial Intelligence & Robotics ( LORIA - AIS ), Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), University of Mauritius, Biomolecular Modelling Laboratory, The Francis Crick Institute, Lincoln's Inn Fields Laboratory, G-INCPM, Weizmann Institute of Science, Chemical Research Support [Rehovot], Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch ( UTMB ), Program in Bioinformatics and Integrative Biology [Worcester], University of Massachusetts Medical School [Worcester] ( UMASS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Sud - Paris 11 ( UP11 ), Bijvoet Center for Biomolecular Research [Utrecht], Utrecht University [Utrecht], Dalton Cardiovascular Research Center [Columbia], Department of Computer Science [Columbia], Informatics Intitute, Department of Biochemistry, University of Missouri, UNIVERSITY OF MISSOURI, Toyota Technological Institute at Chicago [Chicago] ( TTIC ), Department of Biological Sciences, Purdue University, Purdue University [West Lafayette], Department of Computer Science [Purdue], Bioinformatics and Computational Biosciences Branch, Rocky Mountain Laboratories, Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies, Center for Molecular Biology ( ZMBH ), Universität Heidelberg [Heidelberg], Interdisciplinary Center for Scientiﬁc Computing ( IWR ), Department of Molecular Biosciences [Lawrence], University of Kansas [Lawrence] ( KU ), Computational Biology Research Center ( CBRC ), National Institute of Advanced Industrial Science and Technology ( AIST ), Graduate School of Frontier Sciences, The University of Tokyo, Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion ( BSC - CNS ), Center for In-Silico Protein Science, Korea Institute for Advanced Study ( KIAS ), Center for Advanced Computation, Department of Biomedical Engineering [Boston], Boston University [Boston] ( BU ), Institute of Biological Diversity, International Pacific Institute of Indiana, Drosophila Genetic Resource Center, Kyoto Institute of Technology, International University of Health and Welfare Hospital ( IUHW Hospital ), International University of Health and Welfare Hospital, Department of Chemical and Biomolecular Engineering [Baltimore], Johns Hopkins University ( JHU ), Program in Molecular Biophysics [Baltimore], King Abdullah University of Science and Technology ( KAUST ), University of Naples, J Craig Venter Institute, Structural Biology Research Center, VIB, 1050 Brussels, Belgium, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] (IRI), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), University of Missouri [Columbia] (Mizzou), University of Missouri System, University of California [San Francisco] (UC San Francisco), Centro Nacional de Biotecnología [Madrid] (CNB-CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Institute of Biological, Environmental and Rural Sciences (IBERS), Institute for Computational Engineering and Sciences [Austin] (ICES), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Moscow Institute of Physics and Technology [Moscow] (MIPT), Seoul National University [Seoul] (SNU), Florida State University [Tallahassee] (FSU), Computational Algorithms for Protein Structures and Interactions (CAPSID), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Biomolecular Modelling Laboratory [London], The Francis Crick Institute [London], Weizmann Institute of Science [Rehovot, Israël], The University of Texas Medical Branch (UTMB), University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS)-University of Massachusetts System (UMASS), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Assemblage moléculaire et intégrité du génome (AMIG), Département Biochimie, Biophysique et Biologie Structurale (B3S), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of Missouri System-University of Missouri System, Toyota Technological Institute at Chicago [Chicago] (TTIC), Department of Biological Sciences [Lafayette IN], Heidelberg Institute for Theoretical Studies (HITS ), Center for Molecular Biology (ZMBH), Universität Heidelberg [Heidelberg] = Heidelberg University, Interdisciplinary Center for Scientiﬁc Computing (IWR), University of Kansas [Lawrence] (KU), Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), The University of Tokyo (UTokyo), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Korea Institute for Advanced Study (KIAS), Boston University [Boston] (BU), International University of Health and Welfare Hospital (IUHW Hospital), Johns Hopkins University (JHU), King Abdullah University of Science and Technology (KAUST), University of Naples Federico II = Università degli studi di Napoli Federico II, J. Craig Venter Institute, VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Droit et Santé-Université de Lille, Sciences et Technologies, University of California-University of California, University of California [San Francisco] (UCSF), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), University of Naples Federico II, Barcelona Supercomputing Center, NMR Spectroscopy, and Sub NMR Spectroscopy
Subjects: 0301 basic medicine, Protein Conformation, alpha-Helical, Protein Folding, Computer science, International Cooperation, Amino Acid Motifs, Oligomer state, Homoprotein, DATA-BANK, computer.software_genre, Molecular Docking Simulation, Biochemistry, CAPRI Round 30, DESIGN, Structural Biology, ALIGN, Blind prediction, AFFINITY, Protein interaction, Enginyeria biomèdica [Àrees temàtiques de la UPC], ZDOCK, Oligomer State, computer.file_format, Articles, Protein structure prediction, Proteïnes--Investigació, 3. Good health, WEB SERVER, CASP, Thermodynamics, Data mining, CAPRI, Protein docking, Molecular Biology, Algorithms, INTERFACES, Protein Binding, [ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation, Bioinformatics, STRUCTURAL BIOLOGY, Computational biology, Molecular Dynamics Simulation, Article, 03 medical and health sciences, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Heteroprotein, Humans, Protein binding, Macromolecular docking, Protein Interaction Domains and Motifs, Homology modeling, ALGORITHM, Protein-protein docking, Internet, Binding Sites, Models, Statistical, 030102 biochemistry & molecular biology, Bacteria, Sequence Homology, Amino Acid, Computational Biology, Proteins, Protein Data Bank, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Protein Structure, Tertiary, 030104 developmental biology, Structural biology, Docking (molecular), Protein structure, Protein Conformation, beta-Strand, Protein Multimerization, oligomer state, blind prediction, protein interaction, protein docking, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Software
Abstract: We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”
Published: 2016

6. Deep filter banks for texture recognition, description, and segmentation

Author: Iasonas Kokkinos, Subhransu Maji, Mircea Cimpoi, Andrea Vedaldi, Department of Engineering Science, University of Oxford [Oxford], Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Oxford, Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris
Subjects: FOS: Computer and information sciences, Filter banks, Computer science, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Context (language use), 02 engineering and technology, Convolutional neural network, Texture (geology), Article, Image texture, Artificial Intelligence, Texture filtering, 0202 electrical engineering, electronic engineering, information engineering, Segmentation, Computer vision, ComputingMilieux_MISCELLANEOUS, business.industry, Deep learning, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Pattern recognition, Texture and material recognition, Visual attributes, Pattern recognition (psychology), Convolutional neural networks, Datasets and benchmarks, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, Fisher vectors, business, Software
Abstract: Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture representations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another., 29 pages; 13 figures; 8 tables
Published: 2016

7. Modeling local and global deformations in Deep Learning: Epitomic convolution, Multiple Instance Learning, and sliding window detection

Author: Pierre-André Savalle, George Papandreou, Iasonas Kokkinos, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris
Subjects: Contextual image classification, Computer science, business.industry, Deep learning, Detector, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Pattern recognition, 02 engineering and technology, Pascal (programming language), Convolutional neural network, Object detection, Sliding window protocol, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, computer, ComputingMilieux_MISCELLANEOUS, computer.programming_language
Abstract: Deep Convolutional Neural Networks (DCNNs) achieve invariance to domain transformations (deformations) by using multiple ‘max-pooling’ (MP) layers. In this work we show that alternative methods of modeling deformations can improve the accuracy and efficiency of DCNNs. First, we introduce epitomic convolution as an alternative to the common convolution-MP cascade of DCNNs, that comes with the same computational cost but favorable learning properties. Second, we introduce a Multiple Instance Learning algorithm to accommodate global translation and scaling in image classification, yielding an efficient algorithm that trains and tests a DCNN in a consistent manner. Third we develop a DCNN sliding window detector that explicitly, but efficiently, searches over the object's position, scale, and aspect ratio. We provide competitive image classification and localization results on the ImageNet dataset and object detection results on Pascal VOC2007.
Published: 2015

8. Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection

Author: Papandreou, George, Kokkinos, Iasonas, Savalle, Pierre-André, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec, Toyota Technological Institute at Chicago, Ecole Centrale Paris, Inria Saclay Ile de France, Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris
Subjects: [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Abstract: Deep Convolutional Neural Networks (DCNNs) commonly use generic 'max-pooling' (MP) layers to extract deformation-invariant features, but we argue in favor of a more refined treatment. First, we introduce epitomic con-volution as a building block alternative to the common convolution-MP cascade of DCNNs; while having identical complexity to MP, Epitomic Convolution allows for pa-rameter sharing across different filters, resulting in faster convergence and better generalization. Second, we introduce a Multiple Instance Learning approach to explicitly accommodate global translation and scaling when training a DCNN exclusively with class labels. For this we rely on a 'patchwork' data structure that efficiently lays out all image scales and positions as candidates to a DCNN. Factoring global and local deformations allows a DCNN to 'focus its resources' on the treatment of non-rigid defor-mations and yields a substantial classification accuracy improvement. Third, further pursuing this idea, we develop an efficient DCNN sliding window object detector that employs explicit search over position, scale, and aspect ratio. We provide competitive image classification and localization results on the ImageNet dataset and object detection results on the Pascal VOC 2007 benchmark.
Published: 2014

9. Deformable Part Models with CNN Features

Author: Savalle, Pierre-André, Tsogkas, Stavros, Papandreou, George, Kokkinos, Iasonas, Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris, Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Ecole Centrale Paris-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Subjects: [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Abstract: International audience; In this work we report on progress in integrating deep convo-lutional features with Deformable Part Models (DPMs). We substitute the Histogram-of-Gradient features of DPMs with Convolutional Neural Network (CNN) features, obtained from the top-most, fifth, convolutional layer of Krizhevsky's network [8]. We demonstrate that we thereby obtain a substantial boost in performance (+14.5 mAP) when compared to the baseline HOG-based models. This only partially bridges the gap between DPMs and the currently top-performing R-CNN method of [4], suggesting that more radical changes to DPMs may be needed.
Published: 2014

10. Understanding Objects in Detail with Fine-grained Attributes

Author: Ross Girshick, Juho Kannala, Siddharth Mahendran, Naomi Saphra, Andrea Vedaldi, Esa Rahtu, Stavros Tsogkas, Subhransu Maji, Iasonas Kokkinos, David J. Weiss, Ben Taskar, Karen Simonyan, Matthew B. Blaschko, Sammy Mohamed, Department of Engineering Science, University of Oxford [Oxford], Center for Imaging Science (CIS), Johns Hopkins University (JHU), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Department of Computer Science, University of Chicago, University of Chicago, Center for Machine Vision Research (CMV), University of Oulu, Machine Vision Group (MVG), Google Inc., Department of Computer Science & Engineering (CSE), University of Washington [Seattle], Stony Brook University [SUNY] (SBU), State University of New York (SUNY), University of Oxford, Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris
Subjects: Relation (database), business.industry, Computer science, Cognitive neuroscience of visual object recognition, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Cascade algorithm, Object (computer science), Crowdsourcing, Machine learning, computer.software_genre, Object detection, Object-class detection, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Artificial intelligence, Data mining, business, computer
Abstract: International audience; We study the problem of understanding objects in detail, intended as recognizing a wide array of fine-grained object attributes. To this end, we introduce a dataset of 7,413 airplanes annotated in detail with parts and their attributes, leveraging images donated by airplane spotters and crowd-sourcing both the design and collection of the detailed annotations. We provide a number of insights that should help researchers interested in designing fine-grained datasets for other basic level categories. We show that the collected data can be used to study the relation between part detection and attribute prediction by diagnosing the performance of classifiers that pool information from different parts of an object. We note that the prediction of certain attributes can benefit substantially from accurate part detection. We also show that, differently from previous results in object detection, employing a large number of part templates can improve detection accuracy at the expenses of detection speed. We finally propose a coarse-to-fine approach to speed up detection through a hierarchical cascade algorithm.
Published: 2014

11. Describing Textures in the Wild

Author: Subhransu Maji, Andrea Vedaldi, Iasonas Kokkinos, Mircea Cimpoi, Sammy Mohamed, Department of Engineering Science, University of Oxford [Oxford], Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Stony Brook University [SUNY] (SBU), State University of New York (SUNY), University of Oxford, Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris
Subjects: FOS: Computer and information sciences, Basis (linear algebra), Computer science, business.industry, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Cognitive neuroscience of visual object recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, Convolutional neural network, Texture (geology), Visualization, Image texture, Dimension (vector space), Artificial intelligence, business, Representation (mathematics), ComputingMethodologies_COMPUTERGRAPHICS
Abstract: Patterns and textures are defining characteristics of many natural objects: a shirt can be striped, the wings of a butterfly can be veined, and the skin of an animal can be scaly. Aiming at supporting this analytical dimension in image understanding, we address the challenging problem of describing textures with semantic attributes. We identify a rich vocabulary of forty-seven texture terms and use them to describe a large dataset of patterns collected in the wild.The resulting Describable Textures Dataset (DTD) is the basis to seek for the best texture representation for recognizing describable texture attributes in images. We port from object recognition to texture recognition the Improved Fisher Vector (IFV) and show that, surprisingly, it outperforms specialized texture descriptors not only on our problem, but also in established material recognition datasets. We also show that the describable attributes are excellent texture descriptors, transferring between datasets and tasks; in particular, combined with IFV, they significantly outperform the state-of-the-art by more than 8 percent on both FMD and KTHTIPS-2b benchmarks. We also demonstrate that they produce intuitive descriptions of materials and Internet images., Comment: 13 pages; 12 figures Fixed misplaced affiliation
Published: 2014

12. Fine-Grained Visual Classification of Aircraft

Author: Maji, Subhransu, Rahtu, Esa, Kannala, Juho, Blaschko, Matthew, Vedaldi, Andrea, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Machine Vision Group (MVG), University of Oulu, Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec, Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris, Department of Engineering Science, University of Oxford, Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and University of Oxford [Oxford]
Subjects: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Abstract: This paper introduces FGVC-Aircraft, a new dataset containing 10,000 images of aircraft spanning 100 aircraft models, organised in a three-level hierarchy. At the finer level, differences between models are often subtle but always visually measurable, making visual recognition challenging but possible. A benchmark is obtained by defining corresponding classification tasks and evaluation protocols, and baseline results are presented. The construction of this dataset was made possible by the work of aircraft enthusiasts, a strategy that can extend to the study of number of other object classes. Compared to the domains usually considered in fine-grained visual classification (FGVC), for example animals, aircraft are rigid and hence less deformable. They, however, present other interesting modes of variation, including purpose, size, designation, structure, historical style, and branding.
Published: 2013

13. Mid-infrared supercontinuum generation in suspended-core chalcogenide and tellurite optical fibers

Author: Weiqing Gao, Grégory Gadret, Jean-Charles Jules, I. Savelli, Christophe Finot, T. Kohoutek, Frédéric Désévédavy, J. Fatome, O. Mouawad, Hiroyasu Kawashima, Frédéric Smektala, Takenobu Suzuki, Yasutake Ohishi, Pierre-Yves Bony, Bertrand Kibler, Laboratoire Interdisciplinaire Carnot de Bourgogne ( LICB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), SLCO, Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Toyota Technological Institute, Toyota Technological Institute - Nagoya, Laboratoire Interdisciplinaire Carnot de Bourgogne (LICB), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), and Finot, Christophe
Subjects: [PHYS.PHYS.PHYS-OPTICS] Physics [physics]/Physics [physics]/Optics [physics.optics], Optical fiber, Materials science, Kerr effect, Chalcogenide, 02 engineering and technology, 01 natural sciences, law.invention, 010309 optics, Optical pumping, chemistry.chemical_compound, Zero-dispersion wavelength, Optics, law, 0103 physical sciences, ComputingMilieux_MISCELLANEOUS, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics], [ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics], business.industry, 021001 nanoscience & nanotechnology, Supercontinuum, Wavelength, chemistry, Optical parametric oscillator, 0210 nano-technology, business
Abstract: Summary form only given. The generation of optical supercontinua in the mid-infrared region and especially their expansion beyond the intrinsic limit dictated by fused silica is currently a subject of high interest. Tellurite and chalcogenide glasses have serious advantages because of their wide transmittance window which can reach more than 10 μm while the Kerr nonlinearity can be 500 times stronger than fused silica. These different features make them serious candidates for broad mid-infrared supercontinuum generation. For example, supercontinuum as broad as 4000-nm bandwidth has been generated in a sub-cm long Tellurite microstructured fiber by Domachuk et al. in ref. [1] by means of a femtosecond regime pumping. In this work, two kinds of soft-glasses, Tellurite and As2S3 chalcogenide suspended-core fibers with nearly 3-μm core diameter have been designed and pumped in their anomalous dispersion regime by means of an optical parametric oscillator delivering 200-fs pulses between 1700 and 2500 nm [2]. Figure 1a shows the resulting supercontinua obtained at the output of a 40-cm long sample of our tellurite fiber characterized by a 3.4-μm triangular core size. The nonlinear coefficient was evaluated to γ = 175 W-1.km-1, linear losses to 1.5 dB/m at 1550 nm and the zero dispersion wavelength (ZDW) was measured near 1660 nm. The pump wavelength was fixed to 1745 nm and resulting spectra have been recorded as a function of injected power. The broadest 112-mW supercontinuum is characterized by a 2000-nm bandwidth, corresponding to almost 2 octaves and is remarkably flat (a 1900-nm span contained in a -20 dB range). Figure 1b presents the corresponding numerical simulations, which reproduce quite well the dynamics highlighted during our experiments [2]. Figure 2a illustrates the experimental results obtained from a 45-mm long sample of our 3.2-μm suspended-core chalcogenide fiber. The nonlinear Kerr coefficient was estimated to U = 1175 W-1.km-1, linear losses to 1 dB/m at pump wavelength and a ZDW close to 2330 nm. Figure 2a shows the resulting spectrum for a pump wavelength of 2300 nm and an injected power of 70 mW. The supercontinuum extends from 1200 nm to 3200 nm in the -20 dB range. Note however that large residual OH absorption bands are clearly visible around 2.9 μm and beyond 3.2 μm and thus limiting supercontinuum expansion. Taking into account these extra losses, the corresponding numerical simulations illustrated in Fig. 2b are in good agreement with our experimental recordings.
Published: 2013

14. Which Factors Contributes to Resolving Coreference Chains with Bayesian Networks?

Author: Weissenbacher, Davy, Sasaki, Yutaka, Multimedia content-based indexing (TEXMEX), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), COIN, CoIN Laboratory [Nagoya] (COIN), Toyota Technological Institute - Japan-Toyota Technological Institute - Japan, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique
Subjects: [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, Coreference Resolution, Anaphoricity Resolution, Clinical Informatics, Bayesian Networks
Abstract: International audience; This paper describes coreference chain resolution with Bayesian Networks. Several factors in the resolution of coreference chains may greatly affect the final performance. If the choice of machine learning algorithm and the features the learner relies on are largely addressed by the community, others factors implicated in the resolution, such as noisy features, anaphoricity resolution or the search windows, have been less studied, and their importance remains unclear. In this article, we describe a mention-pair resolver using Bayesian Networks, targeting coreference resolution in discharge summaries. We present a study of the contributions of comprehensive factors involved in the resolution using the 2011 i2b2/VA challenge data set. The results of our study indicate that, besides the use of noisy features for the resolution, anaphoricity resolution has the biggest effect on the coreference chain resolution performance.
Published: 2013

15. Superconducting and mechanical properties of impregnated REBCO pancake coils under large hoop stress

Author: Satoshi Hanai, Xavier Chaud, Y. Miyoshi, K. Watanabe, Takumi Suzuki, T. Suwa, T. Saito, Hisaki Sakamoto, Hidetoshi Oguro, Masanori Daibo, F. Debray, Satoshi Awaji, I. Inoue, Gen Nishijima, Pascal Tixador, K. Marukawa, The University of Tokyo, Laboratory of Stem Cell Therapy Center for Experimental Medicine, The University of Tokyo-Institute of Medical Sciences, Central Research Laboratory (CRL), Hitachi Ltd, Laboratoire national des champs magnétiques intenses - Grenoble (LNCMI-G), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Génie Electrique de Grenoble (G2ELab), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS), Central Research Laboratory ( CRL ), Chimie Structurale des Macromolécules ( CSM ), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire national des champs magnétiques intenses - Grenoble ( LNCMI ), Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Génie Electrique de Grenoble ( G2ELab ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut polytechnique de Grenoble - Grenoble Institute of Technology ( Grenoble INP ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ), Tohoku University [Sendai], Toyota Technological Institute, Toyota Technological Institute - Nagoya, National Institute for Materials Science (NIMS), Fujikura Co., Ltd., Nagoya University, Centre National de la Recherche Scientifique (CNRS), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Magnétisme et Supraconductivité (MagSup), Institut Néel (NEEL), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)
Subjects: 010302 applied physics, [PHYS]Physics [physics], Materials science, Deformation (mechanics), [SPI.NRJ]Engineering Sciences [physics]/Electric power, Superconducting magnet, Epoxy, Condensed Matter Physics, 01 natural sciences, Electronic, Optical and Magnetic Materials, Magnetic field, Stress (mechanics), Nuclear magnetic resonance, [ SPI.NRJ ] Engineering Sciences [physics]/Electric power, Electromagnetic coil, visual_art, 0103 physical sciences, visual_art.visual_art_medium, Cylinder stress, Electrical and Electronic Engineering, Composite material, 010306 general physics, Electrical conductor, ComputingMilieux_MISCELLANEOUS
Abstract: International audience; We performed hoop stress tests of REBCO multilayer pancake coils impregnated by epoxy resin. The mechanical deformation and electric field-current properties were measured under the large hoop stress. The maximum hoop stress of about 530 MPa per Hastelloy substrate, calculated from the BJR relation, was applied in the background magnetic field of 8 T. Because the hoop stress level is much smaller than the mechanical tolerance of the GdBCO tape, the coil performance was limited by the angular dependence of critical current in this test. Furthermore, the hoop stress test under the large electromagnetic stresses was also carried out for the other (Y, Gd)BCO coil. The (Y, Gd)BCO epoxy impregnated coil was operated without any degradation even in the huge hoop stress over 1300 MPa. The mechanical deformation of the coil is analysed on the basis of the measured strains. We confirmed the large strain about 0.3%-0.5% because of the hoop stress over 1300 MPa at I op = 460 A and B = 13.5 T but no degradation of the coils. However, it is suggested that the coil deformation is very complicated under the large electromagnetic stress.
Published: 2013

16. Towards a detailed understanding of objects and scenes in natural images

Author: Blaschko, Matthew, Girshick, Ross, Kannala, Juho, Kokkinos, Iasonas, Mahendran, Siddarth, Maji, Subhransu, Mohamed, Sammy, Rahtu, Esa, Saphra, Naomi, Simonyan, Karen, Taskar, Ben, Vedaldi, Andrea, Weiss, David, Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris, Department of Computer Science, University of Chicago, University of Chicago, Machine Vision Group (MVG), University of Oulu, Center for Imaging Science (CIS), Johns Hopkins University (JHU), Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Stony Brook University [SUNY] (SBU), State University of New York (SUNY), Carnegie Mellon University [Pittsburgh] (CMU), Department of Engineering Science, University of Oxford, Department of Computer Science & Engineering (CSE), University of Washington [Seattle], Department of Computer and Information Science [Pennsylvania] (CIS), University of Pennsylvania, Ecole Centrale Paris-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Oxford [Oxford], and University of Pennsylvania [Philadelphia]
Published: 2012

17. Sparse Prediction with the $k$-Support Norm

Author: Argyriou, Andreas, Foygel, Rina, Srebro, Nathan, Centre de vision numérique (CVN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec, Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris, Department of Statistics [Stanford], Stanford University, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Ecole Centrale Paris-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Subjects: FOS: Computer and information sciences, Statistics::Machine Learning, Computer Science - Learning, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Machine Learning (stat.ML), Machine Learning (cs.LG)
Abstract: We derive a novel norm that corresponds to the tightest convex relaxation of sparsity combined with an $\ell_2$ penalty. We show that this new {\em $k$-support norm} provides a tighter relaxation than the elastic net and is thus a good replacement for the Lasso or the elastic net in sparse prediction problems. Through the study of the $k$-support norm, we also bound the looseness of the elastic net, thus shedding new light on it and providing justification for its use.
Published: 2012

18. Half-life measurements of stored fully ionized and hydrogen-like 122I ions

Author: Zygmunt Patyk, Yu. A. Litvinov, Paul Kienle, C. Brandau, D. Shubina, Regina Reuschl, R. Knöbel, M. Mazzocco, Takayuki Yamaguchi, C. Kozhuharov, C. Scheidenberger, D. Boutin, U. Spillmann, I. Hachiuma, F. Bosch, H.G. Essel, Helmut Weick, M. Winkler, K. Namihira, T. Faestermann, M. Steck, Nicolas Winckler, G. Münzenberg, Takuji Izumikawa, Takashi Ohtsubo, Hans Geissel, M. S. Sanjari, Martino Trassinelli, L. Batist, F. Nolden, C. Dimopoulou, D. R. Atanasov, Bao-Hua Sun, S. Hess, Th. Stöhlker, Danyal Winters, Ruishi Mao, Sergey Litvinov, I. I. Tupitsyn, Toshio Suzuki, Renate Märtin, D. L. Balabanski, J. Kurcewicz, N. Kuzminchuk, Helmholtz zentrum für Schwerionenforschung GmbH (GSI), Institut des Nanosciences de Paris (INSP), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), BMBF [CHN 11/012], Japanese Ministry of Education, Science and Culture [A19204023], Bulgarian National Science Fund [DID-02/16], DFG Excellence Cluster Universe of the Technische Universitat Munchen, Helmholtz International Centre for FAIR, Alliance Program of the Helmholtz Association [HA216/EMMI], CAS [2009J2-23], International Max Planck Research School for Precision Tests of Fundamental Symmetries at MPIK, NECT, NSFC [11105010], Narodowe Centrum Nauki (Poland) [2011/01/B/ST2/05131], Département Recherches Subatomiques (DRS-IPHC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), Technische Universität München [München] (TUM), Stefan Meyer Institut für subatomare Physik (SMI), Toyota Technological Institute, Toyota Technological Institute - Nagoya, Advanced Materials Institute and Department of Chemistry, and Fukuoka University
Subjects: Physics, Nuclear and High Energy Physics, Energetic neutral atom, [PHYS.PHYS.PHYS-ATOM-PH]Physics [physics]/Physics [physics]/Atomic Physics [physics.atom-ph], 010308 nuclear & particles physics, Electron capture, Hadron, 01 natural sciences, 7. Clean energy, Ion, Total angular momentum quantum number, Ionization, 0103 physical sciences, Exponential decay, Atomic physics, [PHYS.COND]Physics [physics]/Condensed Matter [cond-mat], 010306 general physics, ComputingMilieux_MISCELLANEOUS, Lepton
Abstract: International audience; The half-lives of fully ionized and hydrogen-like (H-like) I-122 ions have been measured in a heavy-ion storage ring. The beta(+)-decay constants for both charge states and the electron capture (EC) decay constant of H-like ions have been determined. The EC-decay constant in H-like I-122 ions lambda(H-like)(EC) = 7.35(33) . 10(-4) s(-1) is, within the uncertainty, the same as the one in neutral atoms. This result is in agreement with the estimates of recent theoretical considerations on the EC-decay of few-electron ions that explicitly take into account the conservation of the total angular momentum of the nucleus plus lepton(s) system and its projections. No firm confirmation could be concluded from our results on the predicted effect that allowed Gamow-Teller transitions become forbidden if the initial and final total angular momenta are not equal.
Published: 2012

19. Mid-infrared 2000-nm bandwidth supercontinuum generation in suspended-core microstructured Sulfide and Tellurite optical fibers

Author: O. Mouawad, Yasutake Ohishi, Grégory Gadret, Julien Fatome, Frédéric Smektala, Takenobu Suzuki, Jean-Charles Jules, Frédéric Désévédavy, I. Savelli, Tomas Kohoutek, Weiqing Gao, Bertrand Kibler, Pierre-Yves Bony, Hiroyasu Kawashima, Laboratoire Interdisciplinaire Carnot de Bourgogne ( LICB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), SLCO, Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Toyota Technological Institute, Toyota Technological Institute - Nagoya, Laboratoire Interdisciplinaire Carnot de Bourgogne (LICB), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), and Fatome, Julien
Subjects: Materials science, Optical fiber, Light, Chalcogenide, PUMP, MU-M, FABRICATION, Physics::Optics, 02 engineering and technology, Sulfides, PHOTONIC CRYSTAL FIBERS, 01 natural sciences, NM, law.invention, 010309 optics, chemistry.chemical_compound, Optics, DISPERSION, law, 0103 physical sciences, Optical Fibers, business.industry, Lasers, OH, AS2S3 GLASS, Equipment Design, 021001 nanoscience & nanotechnology, Laser, Atomic and Molecular Physics, and Optics, Supercontinuum, CONTINUUM GENERATION, CHALCOGENIDE, chemistry, Nonlinear Dynamics, Femtosecond, Optical parametric oscillator, Sapphire, Tellurium, 0210 nano-technology, business, Photonic-crystal fiber
Abstract: International audience; In this work, we report the experimental observation of supercontinua generation in two kinds of suspended-core microstructured soft-glass optical fibers. Low loss, highly nonlinear, tellurite and As2S3 chalcogenide fibers have been fabricated and pumped close to their zero-dispersion wavelength in the femtosecond regime by means of an optical parametric oscillator pumped by a Ti:Sapphire laser. When coupled into the fibers, the femtosecond pulses result in 2000-nm bandwidth supercontinua reaching the Mid-Infrared region and extending from 750 nm to 2.8 mu m in tellurite fibers and 1 mu m to 3.2 mu m in chalcogenide fibers, respectively.
Published: 2012

20. Comment on 'Reactive force fields for surface chemical reactions: A case study with hydrogen dissociation on Pd surfaces' [J. Chem. Phys. 132, 014704 (2010)]

Author: W. Dong, Xiangjian Shen, Xiaohong Yan, Yang Xiao, Ningbo University of Technology (NBUT), Zhejiang University, Laboratoire de Chimie - UMR5182 (LC), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut de Chimie du CNRS (INC), Institut fuer Festkoerperforschung Juelich, Forschungszentrum Juelich, Toyota Technological Institute, Toyota Technological Institute - Nagoya, École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Hydrogen, Chemistry, General Physics and Astronomy, Thermodynamics, Second moment of area, chemistry.chemical_element, 02 engineering and technology, 021001 nanoscience & nanotechnology, 01 natural sciences, Adsorption desorption kinetics, Dissociative adsorption, Bond order, Dissociation (chemistry), [CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry, Formalism (philosophy of mathematics), 0103 physical sciences, Physical chemistry, Surface chemical, Physical and Theoretical Chemistry, 010306 general physics, 0210 nano-technology, ComputingMilieux_MISCELLANEOUS
Abstract: In a recent paper [Y. Xiao, W. Dong, and H. F. Busnengo, J. Chem. Phys. 132, 014704 (2010)], two of us (Y.X. and W.D.) and H. F. Busnengo reported the parameterization of some reactive force fields (RFF) for describing the dissociative adsorption of H2 on Pd surfaces. They obtained a sufficiently accurate RFF by using the reactive bond order (REBO) formalism of Brenner and showed that the simpler RFF based on the second moment approximation (SMA) failed in giving reliable results. It was concluded that the failure is due to the oversimplified expressions of RFF based on SMA and hence the lack of necessary flexibility. The results of our more recent investigation show that this conclusion needs to be corrected. A more suitable choice of the parameterization conditions allows, in fact, for obtaining a reliable RFF from SMA also.
Published: 2011

21. Recent developments in chalcogenide PCF

Author: Smektala, Frédéric, El Amraoui, Mohammed, Fatome, Julien, Kibler, Bertrand, Jules, Jean-Charles, Gadret, Grégory, Désévédavy, Frédéric, Renversez, Gilles, Troles, Johann, Brillant, Laurent, Duhant, M., Canat, Guillaume, Ohishi, Y., Laboratoire Interdisciplinaire Carnot de Bourgogne (LICB), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), SLCO, Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences Chimiques de Rennes (ISCR), Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Plate-Forme d'Etudes et de Recherche sur les Fibres Optiques Spéciales (PERFOS), association PERFOS, ONERA - The French Aerospace Lab [Palaiseau], ONERA-Université Paris Saclay (COmUE), ONERA - The French Aerospace Lab [Châtillon], Toyota Technological Institute, Toyota Technological Institute - Nagoya, Laboratoire Interdisciplinaire Carnot de Bourgogne ( LICB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Institut des Sciences Chimiques de Rennes ( ISCR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Ecole Nationale Supérieure de Chimie de Rennes-Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), Plate-Forme d'Etudes et de Recherche sur les Fibres Optiques Spéciales ( PERFOS ), ONERA - The French Aerospace Lab ( Palaiseau ), ONERA, ONERA - The French Aerospace Lab ( Chatillon ), Smektala, Frédéric, Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [PHYS.PHYS.PHYS-OPTICS] Physics [physics]/Physics [physics]/Optics [physics.optics], [CHIM.MATE] Chemical Sciences/Material chemistry, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics], [ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics], [ CHIM.MATE ] Chemical Sciences/Material chemistry, [CHIM.MATE]Chemical Sciences/Material chemistry, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2011

22. Visible Light Generation and its Influence on Supercontinuum in Chalcogenide As2S3 Microstructured Optical Fiber

Author: Yasutake Ohishi, Frédéric Désévédavy, Meisong Liao, Xin Yan, Takenobu Suzuki, Grégory Gadret, Mohammed El-Amraoui, Weiqing Gao, Chihiro Kito, Frédéric Smektala, Tomas Kohoutek, Jean-Charles Jules, Toyota Technological Institute, Toyota Technological Institute - Nagoya, Laboratoire Interdisciplinaire Carnot de Bourgogne ( LICB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Interdisciplinaire Carnot de Bourgogne (LICB), and Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)
Subjects: All-silica fiber, Optical fiber, Materials science, General Physics and Astronomy, Polarization-maintaining optical fiber, 02 engineering and technology, 01 natural sciences, Graded-index fiber, law.invention, 010309 optics, Optics, law, 0103 physical sciences, Plastic optical fiber, ComputingMilieux_MISCELLANEOUS, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics], [ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics], business.industry, Plastic-clad silica fiber, General Engineering, [CHIM.MATE]Chemical Sciences/Material chemistry, Microstructured optical fiber, 021001 nanoscience & nanotechnology, [ PHYS.PHYS.PHYS-CHEM-PH ] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph], [ CHIM.MATE ] Chemical Sciences/Material chemistry, Optoelectronics, [PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph], 0210 nano-technology, business, Photonic-crystal fiber
Abstract: We demonstrate visible light generation in chalcogenide As2S3 microstructured optical fiber. The generated visible light causes irreversible damage to the fiber core because of the high absorption coefficient of chalcogenide glasses in the visible band. The SCs (supercontinua) are measured in both untapered and tapered As2S3 fibers, no wider SC is obtained in the tapered one. The SC growth is prevented by the visible light generation since the damage to the fiber core decreases the fiber transmission substantially. This effect can be avoided by designing the fiber to enable the pump source to work in single-mode operation.
Published: 2011

23. Demonstration of Experimental Infrared Spectral Broadening in Chalcogenide As2S3 Suspended Core Microstructured Optical Fibers

Author: Smektala, Frédéric, El Amraoui, Mohammed, Jules, Jean-Charles, Gadret, Grégory, Fatome, Julien, Kibler, Bertrand, Desevedavy, Frédéric, Qin, G., Suzuki, T., Ohishi, Y., Polacchini, Cesar, Skripatchev, Igor, Messadeq, Younes, Renversez, Gilles, Szpulak, M., Laboratoire Interdisciplinaire Carnot de Bourgogne ( LICB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), SLCO, Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Toyota Technological Institute, Toyota Technological Institute - Nagoya, Institute of Physics, Laboratoire Interdisciplinaire Carnot de Bourgogne (LICB), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), and Smektala, Frédéric
Subjects: [PHYS.PHYS.PHYS-OPTICS] Physics [physics]/Physics [physics]/Optics [physics.optics], [CHIM.MATE] Chemical Sciences/Material chemistry, [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics], [ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics], [ CHIM.MATE ] Chemical Sciences/Material chemistry, [CHIM.MATE]Chemical Sciences/Material chemistry, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2010

24. Topological Inference via Meshing

Author: Hudson, Benoît, Miller, Gary, Oudot, Steve, Sheehy, Donald, Toyota Technological Institute, Toyota Technological Institute at Chicago [Chicago] (TTIC), Computer Science Department - Carnegie Mellon University, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Geometric computing (GEOMETRICA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria), and INRIA
Subjects: offsets, ACM: F.: Theory of Computation/F.2: ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY/F.2.2: Nonnumerical Algorithms and Problems/F.2.2.1: Computations on discrete structures, Topological persistence, Delaunay triangulation, sparse Voronoi refinement, ACM: F.: Theory of Computation/F.2: ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY/F.2.2: Nonnumerical Algorithms and Problems/F.2.2.2: Geometrical problems and computations, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.5: Computational Geometry and Object Modeling/I.3.5.3: Geometric algorithms, languages, and systems
Abstract: We apply ideas from mesh generation to improve the time and space complexities of computing the full persistent homological information associated with a point cloud $P$ in Euclidean space $\R^d$. Classical approaches rely on the \v Cech, Rips, $\alpha$-complex, or witness complex filtrations of $P$, whose complexities scale up very badly with $d$. For instance, the $\alpha$-complex filtration incurs the $n^{\Omega(d)}$ size of the Delaunay triangulation, where $n$ is the size of $P$. The common alternative is to truncate the filtrations when the sizes of the complexes become prohibitive, possibly before discovering the most relevant topological features. In this paper we propose a new collection of filtrations, based on the Delaunay triangulation of a carefully-chosen superset of $P$, whose sizes are reduced to $2^{O(d^2)}n$. A nice property of these filtrations is to be interleaved multiplicatively with the family of offsets of $P$, so that the persistence diagram of $P$ can be approximated in $2^{O(d^2)}n^3$ time in theory, with a near-linear observed running time in practice (ignoring the constant factors depending exponentially on $d$). Thus, our approach remains tractable in medium dimensions, say 4 to 10.
Published: 2009

25. Enhancement of 800 nm upconversion emission in a thulium doped tellurite microstructured fiber pumped by a 1560 nm femtosecond fiber laser

Author: Ohishi, Yasutake [Research Center for Advanced Photon Technology, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468–8511 (Japan)]
Published: 2016
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26. Mass transport via in-plane nanopores in graphene oxide membranes

Author: Tobias Foller, Lukas Madauß, Dali Ji, Xiaojun Ren, K. Kanishka H. De Silva, Tiziana Musso, Masamichi Yoshimura, Henning Lebius, Abdenacer Benyagoub, Priyank V. Kumar, Marika Schleberger, Rakesh Joshi, University of New South Wales [Sydney] (UNSW), Fachbereich Physik [Duisburg], Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Toyota Technological Institute - Nagoya, Matériaux, Défauts et IRradiations (MADIR), Centre de recherche sur les Ions, les MAtériaux et la Photonique (CIMAP - UMR 6252), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Matériaux Avancés (IRMA), Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), and European Project: 824096,RADIATE
Subjects: Condensed Matter - Materials Science, Mechanical Engineering, [PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, General Materials Science, Bioengineering, General Chemistry, Physics - Applied Physics, Applied Physics (physics.app-ph), Physik (inkl. Astronomie), Condensed Matter Physics
Abstract: Angstrom-confined solvents in 2D laminates can travel through interlayer spacings, through gaps between adjacent sheets, and via in-plane pores. Among these, experimental access to investigate the mass transport through in-plane pores is lacking. Our experiments allow an understanding of this mass transport via the controlled variation of oxygen functionalities, size and density of in-plane pores in graphene oxide membranes. Contrary to expectations, our transport experiments show that higher in-plane pore densities may not necessarily lead to higher water permeability. We observed that membranes with a high in-plane pore density but a low amount of oxygen functionalities exhibit a complete blockage of water. However, when water- ethanol mixtures with a weaker hydrogen network are used, these membranes show an enhanced permeation. Our combined experimental and computational results suggest that the transport mechanism is governed by the attraction of the solvents toward the pores with functional groups and hindered by the strong hydrogen network of water formed under angstrom confinement.
Published: 2022
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27. One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits

Author: Gaillard, Pierre, Saha, Aadirupa, Dan, Soham, Apprentissage de modèles à partir de données massives (Thoth), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Toyota Technological Institute at Chicago [Chicago] (TTIC), Indiana University of Pennsylvania, Pennsylvania State System of Higher Education (PASSHE), IBM Watson Health, Ruiz, Francisco and Dy, Jennifer and van de Meent, and Jan-Willem
Subjects: FOS: Computer and information sciences, Computer Science - Machine Learning, [INFO]Computer Science [cs], Machine Learning (cs.LG)
Abstract: International audience; We address the problem of `Internal Regret' in Sleeping Bandits in the fully adversarial setup, as well as draw connections between different existing notions of sleeping regrets in the multiarmed bandits (MAB) literature and consequently analyze the implications: Our first contribution is to propose the new notion of Internal Regret for sleeping MAB. We then proposed an algorithm that yields sublinear regret in that measure, even for a completely adversarial sequence of losses and availabilities. We further show that a low sleeping internal regret always implies a low external regret, and as well as a low policy regret for iid sequence of losses. The main contribution of this work precisely lies in unifying different notions of existing regret in sleeping bandits and understand the implication of one to another. Finally, we also extend our results to the setting of Dueling Bandits (DB)--a preference feedback variant of MAB, and proposed a reduction to MAB idea to design a low regret algorithm for sleeping dueling bandits with stochastic preferences and adversarial availabilities. The efficacy of our algorithms is justified through empirical evaluations.
Published: 2022
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28. Annealing effects on recombinative activity of nickel at direct silicon bonded interface

Author: Yamaguchi, Masafumi [Toyota Technological Institute, 2-12-1 Hisakata, Tempaku-ku, Nagoya, 468-8511 (Japan)]
Published: 2015
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29. Femtosecond upconverted photocurrent spectroscopy of InAs quantum nanostructures

Author: Kamiya, Itaru [Toyota Technological Institute, Nagoya, Aichi 468-8511 (Japan)]
Published: 2015
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30. Fabrication of DNA/Hydroxyapatite nanocomposites by simulated body fluid for gene delivery

Author: Okamoto, Masami [Advanced Polymeric Nanostructured Materials Engineering, Graduate School of Engineering, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2015
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31. High efficiency of the spin-orbit torques induced domain wall motion in asymmetric interfacial multilayered Tb/Co wires

Author: Awano, Hiroyuki [Toyota Technological Institute, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2015
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32. Growth orientation dependence of Si doping in GaAsN

Author: Yamaguchi, Masafumi [Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya, 468-8511 (Japan)]
Published: 2015
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33. Hole traps associated with high-concentration residual carriers in p-type GaAsN grown by chemical beam epitaxy

Author: Yamaguchi, Masafumi [Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2015
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34. Si etching with reactive neutral beams of very low energy

Author: Hara, Tamio [Toyota Technological Institute, 2-12-1 Hisakata, Tenpaku-ku, Nagoya 468-8511 (Japan)]
Published: 2014
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35. Multiple soliton self-frequency shift cancellations in a temporally tailored photonic crystal fiber

Author: Ohishi, Yasutake [Research Center for Advanced Photon Technology, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2014
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36. Modeling SARS‐CoV‐2 proteins in the CASP‐commons experiment

Author: Kryshtafovych, Andriy, Moult, John, Billings, Wendy, Della Corte, Dennis, Fidelis, Krzysztof, Kwon, Sohee, Olechnovič, Kliment, Seok, Chaok, Venclovas, Česlovas, Won, Jonghun, Adhikari, Badri, Adiyaman, Recep, Aguirre-Plans, Joaquim, Anishchenko, Ivan, Baek, Minkyung, Baker, David, Baldassarre, Frederico, Barger, Jacob, Bhattacharya, Sutanu, Bhattacharya, Debswapna, Bitton, Mor, Cao, Renzhi, Cheng, Jianlin, Christoffer, Charles, Czaplewski, Cezary, Elofsson, Arne, Faraggi, Eshel, Feig, Michael, Fernandez-Fuentes, Narcis, Grishin, Nick, Grudinin, Sergei, Guo, Zhiye, Hanazono, Yuya, Hassabis, Demis, Hedelius, Bryce, Heo, Lim, Hiranuma, Naozumi, Hunt, Cassandra, Igashov, Ilia, Ishida, Takashi, Jernigan, Robert, Jones, David, Jumper, John, Kadukova, Maria, Kandathil, Shaun, Keasar, Chen, Kihara, Daisuke, Kinch, Lisa, Kiyota, Yasuomi, Kloczkowski, Andrzje, Kohli, Pushmeet, Kogut, Mateusz, Laine, Elodie, Lilley, Cade, Liu, Jian, Liwo, Adam, Lubecka, Emilia, Mondal, Arup, Morris, Connor, Mcguffin, Liam, Molina, Alexis, Nakamura, Tsukasa, Oliva, Baldo, Perez, Alberto, Pozzati, Gabriele, Sarkar, Daipayan, Sato, Rin, Schwede, Torsten, Shrestha, Bikash, Sidi, Tomer, Studer, Gabriel, Shuvo, Md Hossain, Takeda-Shitaka, Mayuko, Takei, Yuma, Terashi, Genki, Tomii, Kentaro, Tsuchiya, Yuko, Tunyasuvunakool, Kathryn, Waliner, Björn, Wu, Tianqi, Xu, Jinbo, Yamamori, Yu, Zhang, Chengxin, Zhang, Yang, Zheng, Wei, University of California [Davis] (UC Davis), University of California (UC), Institute for Bioscience and Biotechnology Research [Rockville, MD, États-Unis] (IBBR), University of Maryland [College Park], University of Maryland System-University of Maryland System, Brigham Young University (BYU), Seoul National University [Seoul] (SNU), Vilnius University [Vilnius], University of Missouri [St. Louis], University of Missouri System, University of Reading (UOR), Universitat Pompeu Fabra [Barcelona] (UPF), Biorobotics Lab (University of Washington), University of Washington [Seattle], Royal Institute of Technology [Stockholm] (KTH ), Auburn University (AU), Ben-Gurion University of the Negev (BGU), Pacific Lutheran University [Tacoma] (PLU), University of Missouri [Columbia] (Mizzou), Purdue University [West Lafayette], University of Gdańsk (UG), Stockholm University, Indiana University - Purdue University Indianapolis (IUPUI), Indiana University System, Michigan State University [East Lansing], Michigan State University System, Aberystwyth University, University of Texas Southwestern Medical Center [Dallas], Données, Apprentissage et Optimisation (DAO), Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), National Institutes for Quantum and Radiological Science and Technology (QST), DeepMind [London], DeepMind Technologies, Moscow Institute of Physics and Technology [Moscow] (MIPT), Tokyo Institute of Technology [Tokyo] (TITECH), Iowa State University (ISU), University College of London [London] (UCL), Kitasato University, Ohio State University [Columbus] (OSU), Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology (LCQB), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Florida [Gainesville] (UF), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Tohoku University [Sendai], University of Basel (Unibas), National Institute of Advanced Industrial Science and Technology (AIST), Linköping University (LIU), Toyota Technological Institute at Chicago [Chicago] (TTIC), University of Michigan [Ann Arbor], University of Michigan System, University of California, University of Maryland [Baltimore], Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), and Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: Models, Molecular, 2019-20 coronavirus outbreak, Research groups, Protein Conformation, Computer science, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Model accuracy, Genome, Viral, computer.software_genre, Biochemistry, SARS‐CoV‐2, Viroporin Proteins, Domain (software engineering), Viral Proteins, 03 medical and health sciences, Protein Domains, Structural Biology, EMA, Humans, CASP, Molecular Biology, Research Articles, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, COVID, 0303 health sciences, SARS-CoV-2, 030302 biochemistry & molecular biology, COVID-19, Protein structure prediction, Model quality, Critical assessment, Data mining, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Research Article
Abstract: International audience; Critical Assessment of Structure Prediction (CASP) is an organization aimed at advancing the state of the art in computing protein structure from sequence. In the spring of 2020, CASP launched a community project to compute the structures of the most structurally challenging proteins coded for in the SARS-CoV-2 genome. Forty-seven research groups submitted over 3000 three-dimensional models and 700 sets of accuracy estimates on 10 proteins. The resulting models were released to the public. CASP community members also worked together to provide estimates of local and global accuracy and identify structure-based domain boundaries for some proteins. Subsequently, two of these structures (ORF3a and ORF8) have been solved experimentally, allowing assessment of both model quality and the accuracy estimates. Models from the AlphaFold2 group were found to have good agreement with the experimental structures, with main chain GDT_TS accuracy scores ranging from 63 (a correct topology) to 87 (competitive with experiment).
Published: 2021

37. Self-Q-switching behavior of erbium-doped tellurite microstructured fiber lasers

Author: Ohishi, Yasutake [Research Center for Advanced Photon Technology, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2014
Full Text: View/download PDF

38. Triangular-barrier quantum rod photodiodes: Their fabrication and detector characteristics

Author: Sakaki, H. [Toyota Technological Institute, 2-12-1 Hisakata, Tempaku-ku, Nagoya 468-0034 (Japan)]
Published: 2014
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39. Supercontinuum generation and lasing in thulium doped tellurite microstructured fibers

Author: Ohishi, Yasutake [Research Center for Advanced Photon Technology, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2014
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40. Nanocrystalline-Si-dot multi-layers fabrication by chemical vapor deposition with H-plasma surface treatment and evaluation of structure and quantum confinement effects

Author: Ohshita, Yoshio [Toyota Technological Institute, Nagoya 468-8511 (Japan)]
Published: 2014
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41. Analysis of defects in GaAsN grown by chemical beam epitaxy on high index GaAs substrates

Author: Yamaguchi, Masafumi [Toyota Technological Institute, Nagoya (Japan)]
Published: 2013
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42. III-V-N materials for super high-efficiency multijunction solar cells

Author: Ohshita, Yoshio [Toyota Technological Institute, Nagoya 468-8511 (Japan)]
Published: 2012
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43. Hydrogen released from bulk ZnO single crystals investigated by time-of-flight electron-stimulated desorption

Author: Ueda, Kazuyuki [Nano High-Tech Research Center, Graduate School of Engineering, Toyota Technological Institute, Nagoya 468-8511 (Japan)]
Published: 2010
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44. Correlation between near infrared emission and bismuth radical species of Bi{sub 2}O{sub 3}-containing aluminoborate glass

Author: Ohishi, Yasutake [Department of Future-Oriented Basic Science and Materials, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2009
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45. Pinning down the strong wilber 1 bound for binary search trees

Author: Chalermsook, Parinya, Chuzhoy, Julia, Saranurak, Thatchaphol, Byrka, Jaroslaw, Meka, Raghu, Professorship Chalermsook Parinya, Toyota Technological Institute at Chicago, Department of Computer Science, Aalto-yliopisto, and Aalto University
Subjects: FOS: Computer and information sciences, Wilber bounds, Dynamic optimality, Computer Science - Data Structures and Algorithms, Binary search trees, Data Structures and Algorithms (cs.DS), Theory of computation → Data structures design and analysis
Abstract: openaire: EC/H2020/759557/EU//ALGOCom The dynamic optimality conjecture, postulating the existence of an O(1)-competitive online algorithm for binary search trees (BSTs), is among the most fundamental open problems in dynamic data structures. Despite extensive work and some notable progress, including, for example, the Tango Trees (Demaine et al., FOCS 2004), that give the best currently known O(log log n)-competitive algorithm, the conjecture remains widely open. One of the main hurdles towards settling the conjecture is that we currently do not have approximation algorithms achieving better than an O(log log n)-approximation, even in the offline setting. All known non-trivial algorithms for BST's so far rely on comparing the algorithm's cost with the so-called Wilber's first bound (WB-1). Therefore, establishing the worst-case relationship between this bound and the optimal solution cost appears crucial for further progress, and it is an interesting open question in its own right. Our contribution is two-fold. First, we show that the gap between the WB-1 bound and the optimal solution value can be as large as Ω(log log n/log log log n); in fact, we show that the gap holds even for several stronger variants of the bound. Second, we provide a simple algorithm, that, given an integer D > 0, obtains an O(D)-approximation in time exp ( O (n1/2Ω(D) log n )). In particular, this yields a constant-factor approximation algorithm with sub-exponential running time. Moreover, we obtain a simpler and cleaner efficient O(log log n)-approximation algorithm that can be used in an online setting. Finally, we suggest a new bound, that we call the Guillotine Bound, that is stronger than WB-1, while maintaining its algorithm-friendly nature, that we hope will lead to better algorithms. All our results use the geometric interpretation of the problem, leading to cleaner and simpler analysis.
Published: 2020

46. Advanced bismuth-doped lead-germanate glass for broadband optical gain devices

Author: Ohishi, Y [Toyota Technological Institute, 2-12, Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2008
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47. Effect of crystalline orientation on parallel and perpendicular exchange biases in FePt/FeMn multilayers

Author: Suzuki, Takao [Information Storage Materials Laboratory, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2008
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48. Structural and magneto-optical properties of FeRh thin films

Author: Suzuki, Takao [Information Storage Materials Laboratory, Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2008
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49. Simulink Model for PWM-Supplied Laminated Magnetic Cores Including Hysteresis, Eddy-Current and Excess Losses

Author: Wilmar Martinez, Paavo Rasilo, Alex Ruderman, Keisuke Fujisaki, Jorma Kyyrä, Tampere University, Electrical Energy Engineering, Martinez, Wilmar/0000-0002-3050-1944, Rasilo, Paavo/0000-0002-0721-5800, Kyyra, Jorma/0000-0002-8178-0613, Department of Electrical Engineering and Automation, KU Leuven, Toyota Technological Institute, Nazarbayev University, Aalto-yliopisto, and Aalto University
Subjects: Materials science, Numerical models, inductors, Lamination, 02 engineering and technology, Index Terms-Eddy currents, Inductor, law.invention, Magnetic cores, Mathematical model, law, Frequency measurement, 0202 electrical engineering, electronic engineering, information engineering, Eddy current, Electrical and Electronic Engineering, inverters, ta113, ta213, Eddy currents, pulse width modulation, 213 Electronic, automation and communications engineering, electronics, 020208 electrical & electronic engineering, Mechanics, Magnetic hysteresis, Lamination (geology), Hysteresis, hysteresis, Integrated circuit modeling, Inverter, Skin effect, pulsewidth modulation, Pulse-width modulation
Abstract: The simulation models are available at https://github.com/prasilo/simulink-pwm-inductor/tree/v1.0 A new implementation of an iron-loss model for laminated magnetic cores in the MATLAB/Simulink environment is proposed in this paper. The model is based on numerically solving a one-dimensional diffusion problem for the eddy currents in the core lamination and applying an accurate hysteresis model as the constitutive law. An excess loss model is also considered. The model is identified merely based on the catalog data provided by the core material manufacturer. The implementation is validated with analytical and finite-element models and experimentally in the case of a toroidal inductor supplied from a GaN FET full-bridge inverter with 5-500 kHz switching frequencies and a deadtime of 300 ns. Despite the simple identification, a good correspondence is observed between the simulated and measured iron losses, the average difference being 3.3% over the wide switching frequency range. It is shown that accounting for the skin effect in the laminations is significant, in order to correctly model the iron losses at different switching frequencies. Some differences between the measured and simulated results at high switching frequencies are also discussed. The model is concluded to be applicable for designing and analyzing laminated magnetic cores in combination with power-electronics circuits. The Simulink models are openly available.
Published: 2018

50. A Germanium Back Contact Type Thermophotovoltaic Cell

Author: Yamaguchi, Masafumi [Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya 468-8511 (Japan)]
Published: 2007
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