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arXiv 2017年

作者： Gieseke, Fabian Bloemen, Steven van den Bogaard, Cas Heskes, Tom Kindler, Jonas Scalzo, Richard A. Ribeiro, Valério A.R.M. van Roestel, Jan Groot, Paul J. Yuan, Fang Möller, Anais Tucker, Brad E. Institute for Computing and Information Sciences Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands Department of Computer Science University of Copenhagen Sigurdsgade 41 Copenhagen2200 Denmark Department of Astrophysics IMAPP Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands NOVA Optical InfraRed Instrumentation Group Oude Hoogeveensedijk 4 PD Dwingeloo7991 Netherlands Institute of Cognitive Science University of Osnabrück Wachsbleiche 27 Osnabrück49090 Germany Research School of Astronomy and Astrophysics Australian National University CanberraACT2611 Australia Australia Centre for Translational Data Science University of Sydney DarlingtonNSW2008 Australia CIDMA Departamento de Física Universidade de Aveiro Campus de Santiago Aveiro3810-193 Portugal Instituto de Telecomunicações Campus de Santiago Aveiro3810-193 Portugal Department of Physics and Astronomy Botswana International University of Science and Technology Private Bay 16 Palapye Botswana

Current synoptic sky surveys monitor large areas of the sky to find variable and transient astronomical sources. As the number of detections per night at a single telescope easily exceeds several thousand, current detection pipelines make intensive use of machine learning algorithms to classify the detected objects and to filter out the most interesting candidates. A number of upcoming surveys will produce up to three orders of magnitude more data, which renders high-precision classification systems essential to reduce the manual and, hence, expensive vetting by human experts. We present an approach based on convolutional neural networks to discriminate between true astrophysical sources and artefacts in reference-subtracted optical images. We show that relatively simple networks are already competitive with state-of-the-art systems and that their quality can further be improved via slightly deeper networks and additional preprocessing steps – eventually yielding models outperforming state-of-the-art systems. In particular, our best model correctly classifies about 97.3% of all "real"and 99.7% of all"bogus"instances on a test set containing 1,942"bogus"and 227 "real" instances in total. Furthermore, the networks considered in this work can also successfully classify these objects at hand without relying on difference images, which might pave the way for future detection pipelines not containing image subtraction steps at all. Copyright © 2017, The Authors. All rights reserved.

关键词： Surveys

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Undoped Layered Perovskite Oxynitride Li2LaTa2O6N for Photocatalytic CO2Reduction with Visible Light

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Angewandte Chemie 2018年第27期130卷

作者： Takayoshi Oshima Tom Ichibha Ken Sinkou Qin Kanemichi Muraoka Junie Jhon M. Vequizo Keisuke Hibino Ryo Kuriki Shunsuke Yamashita Kenta Hongo Tomoki Uchiyama Kotaro Fujii Daling Lu Ryo Maezono Akira Yamakata Hideki Kato Koji Kimoto Masatomo Yashima Yoshiharu Uchimoto Masato Kakihana Osamu Ishitani Hiroshi Kageyama Kazuhiko Maeda Department of Chemistry School of Science Tokyo Institute of Technology 2-12-1-NE-2 Ookayama Meguro-ku Tokyo 152-8550 Japan Japan Society for the Promotion of Science Kojimachi Business Center Building 5-3-1 Kojimachi Chiyoda-ku Tokyo 102-0083 Japan School of Information Science JAIST Asahidai 1-1 Nomi Ishikawa 923-1292 Japan Graduate School of Engineering Toyota Technological Institute 2-12-1 Hisakata Tempaku Nagoya 468-8511 Japan Research Center for Advanced Measurement and Characterization National Institute for Materials Science 1-1 Namiki Tsukuba Ibaraki 305-0044 Japan Research Center for Advanced Computing Infrastructure JAIST Asahidai 1-1 Nomi Ishikawa 923-1292 Japan Center for Materials Research by Information Integration Research and Services Division of Materials Data and Integrated System National Institute for Materials Science Tsukuba 305-0047 Japan PRESTO (Japan) Science and Technology Agency 4-1-8 Honcho Kawaguchi-shi Saitama 322-0012 Japan Computational Engineering Applications Unit RIKEN 2-1 Hirosawa Wako Saitama 351-0198 Japan Graduate school of Human and Environmental Studies Kyoto University Yoshida-nihonmatsu-cho Sakyo-ku Kyoto 606-8501 Japan Suzukakedai Materials Analysis Division Technical Department Tokyo Institute of Technology 4259 Nagatsuta-cho Midori-ku Yokohama 226-8503 Japan Institute of Multidisciplinary Research for Advanced Materials Tohoku University 2-1-1 Katahira Aoba-ku Sendai 980-8577 Japan Graduate School of Engineering Kyoto University Nishikyo-ku Kyoto 615-8510 Japan

Oxynitrides are promising visible‐light‐responsive photocatalysts, but their structures are almost confined with three‐dimensional (3D) structures such as perovskites. A phase‐pure Li 2 LaTa 2 O 6 N with a layered perovskite structure was successfully prepared by thermal ammonolysis of a lithium‐rich oxide precursor. Li 2 LaTa 2 O 6 N exhibited high crystallinity and visible‐light absorption up to 500 nm. As opposed to well‐known 3D oxynitride perovskites, Li 2 LaTa 2 O 6 N supported by a binuclear Ru II complex was capable of stably and selectively converting CO 2 into formate under visible light ( λ >400 nm). Transient absorption spectroscopy indicated that, as compared to 3D oxynitrides, Li 2 LaTa 2 O 6 N possesses a lower density of mid‐gap states that work as recombination centers of photogenerated electron/hole pairs, but a higher density of reactive electrons, which is responsible for the higher photocatalytic performance of this layered oxynitride.

关键词： CO2-Reduktion Oxynitride Perowskite Photokatalyse Sichtbares Licht

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Simulate Human Saccadic Scan-Paths in Target Searching

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International Journal of Intelligence science 2016年第1期6卷 1-9页

作者： Lijuan Duan Jun Miao David M. W. Powers Jili Gu Laiyun Qing Beijing Key Laboratory of Trusted Computing Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data College of Computer Science and Technology Beijing University of Technology Beijing China National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing Technology CAS Beijing China School of Computer Science Engineering & Maths Flinders University of South Australia Adelaide South Australia Beijing Samsung Telecom R&D Center Beijing China University of Chinese Academy of Sciences Beijing China

Human saccade is a dynamic process of information pursuit. There are many methods using either global context or local context cues to model human saccadic scan-paths. In contrast to them, this paper introduces a model for gaze movement control using both global and local cues. To test the performance of this model, an experiment is done to collect human eye movement data by using an SMI iVIEW X Hi-Speed eye tracker with a sampling rate of 1250 Hz. The experiment used a two-by-four mixed design with the location of the targets and the four initial positions. We compare the saccadic scan-paths generated by the proposed model against human eye movement data on a face benchmark dataset. Experimental results demonstrate that the simulated scan-paths by the proposed model are similar to human saccades in term of the fixation order, Hausdorff distance, and prediction accuracy for both static fixation locations and dynamic scan-paths.

关键词： Saccadic Scan-Paths Eye Movement Fixation Locations Dynamic Scan-Paths

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PennyLane: Automatic differentiation of hybrid quantum-classical computations

arXiv

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arXiv 2018年

作者： Bergholm, Ville Izaac, Josh Schuld, Maria Gogolin, Christian Ahmed, Shahnawaz Ajith, Vishnu Alam, M. Sohaib Alonso-Linaje, Guillermo AkashNarayanan, B. Asadi, Ali Arrazola, Juan Miguel Azad, Utkarsh Banning, Sam Blank, Carsten Bromley, Thomas R. Cordier, Benjamin A. Ceroni, Jack Delgado, Alain Matteo, Olivia Di Dusko, Amintor Garg, Tanya Guala, Diego Hayes, Anthony Hill, Ryan Ijaz, Aroosa Isacsson, Theodor Ittah, David Jahangiri, Soran Jain, Prateek Jiang, Edward Khandelwal, Ankit Kottmann, Korbinian Lang, Robert A. Lee, Christina Loke, Thomas Lowe, Angus McKiernan, Keri Meyer, Johannes Jakob Montañez-Barrera, J.A. Moyard, Romain Niu, Zeyue O’Riordan, Lee James Oud, Steven Panigrahi, Ashish Park, Chae-Yeun Polatajko, Daniel Quesada, Nicolás Roberts, Chase Sá, Nahum Schoch, Isidor Shi, Borun Shu, Shuli Sim, Sukin Singh, Arshpreet Strandberg, Ingrid Soni, Jay Száva, Antal Thabet, Slimane Vargas-Hernández, Rodrigo A. Vincent, Trevor Vitucci, Nicola Weber, Maurice Wierichs, David Wiersema, Roeland Willmann, Moritz Wong, Vincent Zhang, Shaoming Killoran, Nathan Xanadu 777 Bay Street Toronto Canada Wallenberg Centre for Quantum Technology Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg412 96 Sweden Indian Institute of Information Technology Kottayam India NASA Ames Research Center Moffett FieldCA94035 United States Mountain ViewCA94043 United States data cybernetics Martin-Kolmsperger-Str 26 Landsberg86899 Germany Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University PortlandOR97202 United States Dept. of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Physics Indian Institute of Technology Roorkee Uttarakhand Roorkee India qBraid 5235 South Harper Court ChicagoIL60615 United States Factal Analytics Level 2 Chimes Building Plot 61 Sector - 44 Haryana Gurgaon122003 India Centre for High Energy Physics Indian Institute of Science Karnataka Bengaluru560012 India ICFO - Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Av. Carl Friedrich Gauss 3 Castelldefels Barcelona08860 Spain Chemical Physics Theory Group Department of Chemistry University of Toronto Canada DUG Technology 76 Kings Park Rd West PerthWA6005 Australia Rigetti Computing 2919 Seventh Street BerkeleyCA94710 United States Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute for Advanced Simulation Jülich Supercomputing Centre Forschungszentrum Jülich Jülich52425 Germany University of Amsterdam Netherlands School of Physical Sciences National Institute of Science Education and Research HBNI Odisha Jatni752 050 India Cervest United Kingdom Centro Brasileiro de Pesquisas Físicas Rua Dr. Xavier Sigaud 150 Rio de Janeiro22290-180 Brazil Zurich8092 Switzerland Neo4j UK Ltd United Kingdom Zapata Computing Inc. United States ITC Infotech Bangalore India Department of Microtechnology and Nanoscienc

PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices, supporting both qubit and continuous-variable paradigms. PennyLane’s core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation. PennyLane thus extends the automatic differentiation algorithms common in optimization and machine learning to include quantum and hybrid computations. A plugin system makes the framework compatible with any gate-based quantum simulator or hardware. We provide plugins for hardware providers including the Xanadu Cloud, Amazon Braket, and IBM Quantum, allowing PennyLane optimizations to be run on publicly accessible quantum devices. On the classical front, PennyLane interfaces with accelerated machine learning libraries such as TensorFlow, PyTorch, JAX, and Autograd. PennyLane can be used for the optimization of variational quantum eigensolvers, quantum approximate optimization, quantum machine learning models, and many other applications. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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Multivariate Spearman's p for Aggregating Ranks Using Copulas

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Journal of Machine Learning Research 2016年 17卷 1-30页

作者： Bedo, Justin Ong, Cheng Soon Walter and Eliza Hall Institute 1G Royal Parade ParkvilleVIC3052 Australia Department of Computing and Information Systems University of Melbourne VIC3010 Australia Data61 CSIRO 7 London Circuit CanberraACT2601 Australia Research School of Computer Science Australian National University Department of Electrical and Electronic Engineering VIC3010 Australia

We study the problem of rank aggregation: given a set of ranked lists, we want to form a consensus ranking. Furthermore, we consider the case of extreme lists: i.e., only the rank of the best or worst elements are known. We impute missing ranks and generalise Spearman's to extreme ranks. Our main contribution is the derivation of a non-parametric estimator for rank aggregation based on multivariate extensions of Spearman's p, which measures correlation between a set of ranked lists. Multivariate Spearman's p is defined using copulas, and we show that the geometric mean of normalised ranks maximises multivariate correlation. Motivated by this, we propose a weighted geometric mean approach for learning to rank which has a closed form least squares solution. When only the best (top-k) or worst (bottom-k) elements of a ranked list are known, we impute the missing ranks by the average value, allowing us to apply Spearman's κ. We discuss an optimistic and pessimistic imputation of missing values, which respectively maximise and minimise correlation, and show its effect on aggregating university rankings. Finally, we demonstrate good performance on the rank aggregation benchmarks MQ2007 and MQ2008. © 2016 Justin Bed}o and Cheng Soon Ong.

关键词： Benchmarking

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Guest Editorial Measuring and Troubleshooting the Internet: Algorithms, Tools and Applications

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IEEE Journal on Selected Areas in Communications 2016年第6期34卷 1805-1806页

作者： Maurizio Dusi Alessandro Finamore Kimberly Claffy Nevil Brownlee Darryl Veitch Copan Diagnostics Inc. Murrieta CA USA Telefonica Research Distrito Telefonica Madrid Spain Center for Applied Internet Data Analysis San Diego Supercomputer Center La Jolla CA USA Department of Computer Science The University of Auckland Auckland New Zealand School of Computing and Communications Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia

The ubiquity of Internet access and the wide variety of Internet-enabled devices and applications have made the Internet a principal pillar of the information Society. Decentralized and diverse, the Internet is resilient and universal. However, its distributed nature leads to operational brittleness and difficulty in identifying and tracking the root causes of performance and availability issues.

关键词： Special issues and sections Internet Algorithm design and analysis Performance analysis Quality of service

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Energy Efficient Path Planning Techniques for UAV-based Systems with Space Discretization

Energy Efficient Path Planning Techniques for UAV-based Syst...

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IEEE Wireless Communications and Networking Conference

作者： Shaimaa Ahmed Amr Mohamed Khaled Harras Mohamed Kholief Saleh Mesbah Electrical and Computer Engineering Department Qatar University School of Computer Science Carnegie Mellon University College of Computing and Information Technology AAST Remote Sensing and Spatial Studies Unit College of Engineering and Technology AAST

ISBN: (纸本)9781467398152

Unmanned Aerial Vehicles are miniature air-crafts that have proliferated in many military and civil applications. Their affordability allows for tasks to be held with not just one but a fleet of UAVs. One of the problems that arise with the use of multi-UAVs is the multi-UAV path planning and assignment problem. We propose three algorithms that aim at assigning energy efficient trajectories for a fleet of UAVs. Our optimal path planning solution (OPP) is formulated using a Mixed Integer Linear Programming model (MILP). We also propose two other heuristic solutions that are greedy in nature;namely, Greedy Least Cost (GLC) and First Detect First Reserve (FDFR). To aid with collision avoidance, we adopt the concept of space discretization, and present a more realistic view of the space a UAV occupies. The comparative study of our proposed solutions reveals insightful trade-offs between energy consumption and complexity.

关键词： Unmanned Aerial Vehicle greedy method vehicle Path planning Energy efficiency Collision avoidance Discretization drone honey bees Mixed integer linear programming Fleet Religious Missions energy consumption

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Hierarchical ID-Based Searchable Encryption with Constant Size Ciphertext in Cloud

Hierarchical ID-Based Searchable Encryption with Constant Si...

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IEEE International Conference on Smart City

作者： Xiaofen Wang Xiaosong Zhang Yi Mu School of Computer Science and Engineering Big Data Research Center University of Electronic Science and Technology of China School of Computing and Information Technology University of Wollongong

ISBN: (纸本)9781509018949

In a hierarchical system, a set of users with ranked rights are organized in a tree-architecture, and the user with higher grade can search and access data of users with lower grade in its branch. Nowadays hierarchical systems are constructed by utilizing the cloud to improve their performance due to the cloud server's powerful computation and storage capabilities. However, the untrusted cloud server may give rise to the risk of private information exposure. To enable ranked and controllable data search in cloud without revealing users' privacy in a hierarchical system is a challenging open problem. In this paper, we formally define the hierarchical searchable encryption, where the user in the hierarchical system can search the data of its descendants. A basic hierarchical ID-based searchable encryption (HIBSE) scheme with constant size ciphertext and probe (i.e. trapdoor) is proposed, which satisfies IND-sID-CKA security. An extended secure channel free HIBSE scheme is also given, where the user can search the data of all his descendants at one time, and it achieves IND-sID-OKGA. The performance evaluation demonstrates that the extended scheme greatly reduces the computation cost when the user searches the data of all his descendants in the branch. Therefore, the extended scheme is efficient and practical in various applications.

关键词： Hierarchical System Cloud computing Searchable Encryption Privacy-Preserving

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