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arXiv 2020年

作者： Sánchez-Sáez, Paula Reyes, I. Valenzuela, C. Förster, F. Eyheramendy, S. Elorrieta, F. Bauer, F.E. Cabrera-Vives, G. Estévez, P.A. Catelan, M. Pignata, G. Huijse, P. de Cicco, D. Arévalo, P. Carrasco-Davis, R. Abril, J. Kurtev, R. Borissova, J. Arredondo, J. Castillo-Navarrete, E. Rodriguez, D. Ruz-Mieres, D. Moya, A. Sabatini-Gacitúa, L. Sepúlveda-Cobo, C. Camacho-Iñiguez, E. Nuncio Monseñor Sótero Sanz 100 Providencia Santiago Chile Instituto de Astrofísica Facultad de Física Pontificia Universidad Católica de Chile Casilla 306 Santiago 22 Chile Faculty of Engineering and Sciences Universidad Adolfo Ibañez Diagonal Las Torres 2700 Peñalolén Santiago Chile Center for Mathematical Modeling Universidad de Chile Beauchef 851 North building 7th floor Santiago8320000 Chile Department of Electrical Engineering Universidad de Chile Av. Tupper 2007 Santiago8320000 Chile Data Observatory Diagonal Las Torres 2640 Peñalolén Santiago Chile Departmento de Matemáticas Facultad de Ciencia Universidad de Santiago de Chile Estación Central Av. Libertador Bernardo O'Higgins 3663 Santiago Chile Departamento de Astronomía Universidad de Chile Casilla 36D Santiago Chile Centro de Astroingeniería Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Space Science Institute 4750 Walnut Street Suite 205 BoulderCO80301 United States Department of Computer Science University of Concepcón Edmundo Larenas 219 Concepción Chile Departamento de Ciencias Fisícas Universidad Andres Bello Avda. Republica 252 Santiago Chile Informatics Institute Universidad Austral de Chile General Lagos 2086 Valdivia Chile Instituto de Física y Astronomía Facultad de Ciencias Universidad de Valparaíso Gran Bretana No. 1111 Playa Ancha Valparaíso Chile Alonso de Córdova 3107 Vitacura Santiago Chile - Unidad Asociada al CSIC Plaza San Juan 1 TeruelE-44001 Spain

We present the first version of the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses variability features computed from the ZTF alert stream, and colors obtained from AllWISE and ZTF photometry. We apply a Balanced Random Forest algorithm with a two-level scheme, where the top level classifies each source as periodic, stochastic, or transient, and the bottom level further resolves each of these hierarchical classes, amongst 15 total classes. This classifier corresponds to the first attempt to classify multiple classes of stochastic variables (including core- and host-dominated active galactic nuclei, blazars, young stellar objects, and cataclysmic variables) in addition to different classes of periodic and transient sources, using real data. We created a labeled set using various public catalogs (such as the Catalina Surveys and Gaia DR2 variable stars catalogs, and the Million Quasars catalog), and we classify all objects with ≥ 6 g-band or ≥ 6 r-band detections in ZTF (868,371 sources as of 2020/06/09), providing updated classifications for sources with new alerts every day. For the top level we obtain macro-averaged precision and recall scores of 0.96 and 0.99, respectively, and for the bottom level we obtain macro-averaged precision and recall scores of 0.57 and 0.76, respectively. Updated classifications from the light curve classifier can be found at the ALeRCE Explorer website. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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Distance range queries in spatialhadoop 21

Distance range queries in spatialhadoop

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21st Jornadas de Ingenieria del Software y Bases de Datos, JISBD 2016 - 21st Conference on Software engineering and Databases, JISBD 2016

作者： García-García, Francisco Corral, Antonio Iribarne, Luis Vassilakopoulos, Michael Dept. of Informatics University of Almeria Almeria Spain Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece

Efficient processing of Distance Range Queries (DRQs) is of great importance in spatial databases due to the wide area of applications. This type of spatial query is characterized by a distance range over one or two datasets. The most representative and known DRQs are the Ε Distance Range Query (ΕDRQ) and the Ε Distance Range Join Query (ΕDRJQ). Given the increasing volume of spatial data, it is difficult to perform a DRQ on a centralized machine efficiently. Moreover, the ΕDRJQ is an expensive spatial operation, since it can be considered a combination of the ΕDR and the spatial join queries. For this reason, this paper addresses the problem of computing DRQs on big spatial datasets in SpatialHadoop, an extension of Hadoop that supports spatial operations efficiently, and proposes new algorithms in SpatialHadoop to perform efficient parallel DRQs on large-scale spatial datasets. We have evaluated the performance of the proposed algorithms in several situations with big synthetic and real-world datasets. The experiments have demonstrated the efficiency and scalability of our proposal. © 2016 Sistedes. All rights reserved.

关键词： MapReduce

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Enhancing virtual reality systems with smart wearable devices 17

Enhancing virtual reality systems with smart wearable device...

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17th IEEE International Conference on Mobile Data Management, IEEE MDM 2016

作者： Alshaal, Salah Eddin Michael, Stylianos Pamporis, Andreas Herodotou, Herodotos Samaras, George Andreou, Panayiotis Department of Computing University of Central Lancashire Cyprus/InSPIRE Center Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Cyprus

ISBN: (纸本)9781509008834

The proliferation of wearable and smartphone devices with embedded sensors has enabled researchers and engineers to study and understand user behavior at an extremely high fidelity, particularly for use in industries such as entertainment, health, and retail. However, identified user patterns are yet to be integrated into modern systems with immersive capabilities, such as VR systems, which still remain constrained by limited application interaction models exposed to developers. In this paper, we present Smart VR, a platform that allows developers to seamlessly incorporate user behavior into VR apps. We present the high-level architecture of Smart VR, and show how it facilitates communication, data acquisition, and context recognition between smart wearable devices and mediator systems (e.g., smartphones, tablets, PCs). We demonstrate Smart VR in the context of a VR app for retail stores to show how it can be used to substitute the requirement of cumbersome input devices (e.g., mouse, keyboard) with more natural means of user-app interaction (e.g., user gestures such as swiping and tapping) to improve user experience. © 2016 IEEE.

关键词： Smartphones

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Scheduling independent tasks on heterogeneous computing systems by optimizing various objectives 11

Scheduling independent tasks on heterogeneous computing syst...

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11th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2016

作者： Gogos, Christos Valouxis, Christos Alefragis, Panayiotis Xanthopoulos, Iordanis Housos, Efthymios Technological Educational Institute of Epirus Department of Computer and Informatics Engineering Laboratory of Knowledge and Intelligent Computing Arta Greece Ministry of Education Achaia Branch Office Patras Greece Technological Educational Institute of Western Greece Department of Computer and Informatics Engineering Patras Greece University of Patras Department of Electrical and Computer Engineering Patras Greece

ISBN: (纸本)9780992998417

Scheduling tasks on a set of heterogeneous machines is a problem with both theoretical and practical interest. In this paper, the problem of scheduling independent tasks while trying to optimize four different objectives is studied. These objectives are makespan, flowtime, resource utilization and matching proximity. Four mathematical models are presented that optimize each individual objective. Then, certain objectives are combined forming a weighted sum single objective in order to reach good compromise solutions. A number of experiments were undertaken that demonstrated the applicability of using a mathematical integer programming solver in solving several instances of the problem. An interesting result is that when makespan is the single objective, as a side-effect, high resource utilization is obtained also. © PATAT *** rights reserved.

关键词： Integer programming

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Prediction and understanding of soft proton contamination in XMM-Newton: A machine learning approach

arXiv

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arXiv 2020年

作者： Kronberg, Elena A. Gastaldello, Fabio Haaland, Stein Smirnov, Artem Berrendorf, Max Ghizzardi, Simona Kuntz, K.D. Sivadas, Nithin Allen, Robert C. Tiengo, Andrea Ilie, Raluca Huang, Yu Kistler, Lynn University of Munich Theresienstr. 41 Munich80333 Germany Milano via A. Corti 12 MilanoI-20133 Italy Birkeland Centre for Space Science University of Bergen Allégaten 55 Bergen5007 Norway Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen Germany German Research Centre for Geosciences Albert-Einstein-Strae 42-46 Potsdam14473 Germany Geophysical Center of the Russian Academy of Sciences Molodezhnaya St. 3 Moscow119296 Russia Institute of Informatics University of Munich Oettingenstrae 67 Munich80538 Germany Henry A. Rowland Department of Physics & Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States Department of Electrical and Computer Engineering Boston University 8 Saint Mary’s Street BostonMA02134 United States Johns Hopkins University Applied Physics Lab 11100 Johns Hopkins Rd LaurelMD20723 United States Scuola Universitaria Superiore IUSS Pavia piazza della Vittoria 15 PaviaI-27100 Italy INFN Sezione di Pavia via A. Bassi 6 PaviaI-27100 Italy University of Illinois at Urbana-Champaign ECEB 306 N. Wright Street 5054 UrbanaIL61801 United States Space Science Center University of New Hampshire Morse Hall Rm 408 DurhamNH03824 United States

One of the major and unfortunately unforeseen sources of background for the current generation of X-ray telescopes are few tens to hundreds of keV (soft) protons concentrated by the mirrors. One such telescope is the European Space Agency’s (ESA) X-ray Multi-Mirror Mission (XMM-Newton). Its observing time lost due to background contamination is about 40%. This loss of observing time affects all the major broad science goals of this observatory, ranging from cosmology to astrophysics of neutron stars and black holes. The soft proton background could dramatically impact future large X-ray missions such as the ESA planned Athena missiona). Physical processes that trigger this background are still poorly understood. We use a Machine Learning (ML) approach to delineate related important parameters and to develop a model to predict the background contamination using 12 years of XMM observations. As predictors we use the location of satellite, solar and geomagnetic activity parameters. We revealed that the contamination is most strongly related to the distance in southern direction, Z, (XMM observations were in the southern hemisphere), the solar wind radial velocity and the location on the magnetospheric magnetic field lines. We derived simple empirical models for the first two individual predictors and an ML model which utilizes an ensemble of the predictors (Extra Trees Regressor) and gives better performance. Based on our analysis, future missions should minimize observations during times associated with high solar wind speed and avoid closed magnetic field lines, especially at the dusk flank region in the southern hemisphere. Copyright © 2020, The Authors. All rights reserved.

关键词： Gamma rays

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Overview of energy storage technologies and a short-term storage application for wind turbines 26

Overview of energy storage technologies and a short-term sto...

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26th Annual International Ocean and Polar engineering Conference, ISOPE 2016

作者： Argyrou, Maria C. Christodoulides, Paul Marouchos, Christos C. Kalogirou, Soteris A. Florides, Georgios A. Lazari, Lazaros Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Faculty of Engineering and Technology Cyprus University of Technology Limassol Cyprus Department of Mechanical Engineering and Materials Science and Engineering Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781880653883

The spreading of renewables has become stronger due to the increased air pollution. On the other hand, the penetration of renewable energy technologies causes major problems to the stability of the grid. Along with the fluctuations of the renewable energy technologies production, storage is important for power and voltage smoothing. Thus, storage technologies have gained an increased attention considering the distributed generation. This paper presents an up to date comprehensive overview of energy storage technologies. It incorporates characteristics and functionalities of each storage technology, as well as their advantages and drawbacks compared with other storage technologies. A demonstration of a short-term energy storage application in a gridconnected small wind turbine is given. The circuit is operated at the maximum power point (MPP), succeeding its connection and synchronization with the low-voltage grid. It also utilizes the energy generated by the wind turbine when a fault appears for a short period of time, through the supercapacitor. © Copyright 2016 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Supercapacitor

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Ocean surface current prediction based on HF radar observations using trajectory-oriented association rule mining

Ocean surface current prediction based on HF radar observati...

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IEEE International Conference on Big Data

作者： Kulsawasd Jitkajornwanich Peerapon Vateekul Upa Gupta Teeranai Kormongkolkul Arnon Jirakittayakorn Siam Lawawirojwong Siwapon Srisonphan Dept. of Computer Science King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Dept. of Computer Engineering Chulalongkorn University Bangkok Thailand Chulalongkorn University Big Data Analytics & IoT Center (CUBIC) Dept. of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand GISTDA Academy Geo-Informatics & Space Technology Development Agency (PO) Bangkok Thailand Dept. of Electrical Engineering Kasetsart University Bangkok Thailand

HF (high frequency) coastal radar system is used to capture the surface current behavior - in terms of velocity and direction - in the ocean near the coast. 18 HF coastal radar stations were implemented along the Gulf of Thailand in order to monitor for disasters (e.g., Tsunami) as well as relevant risks. The HF systems are also to serve other life-critical applications, such as water quality control and monitoring, chemical spill backtracking, and marine navigation. However, not all the applications can benefit from this near-real-time HF data; some applications in different domains require forecast values. The examples include search-and-rescue system and hazardous materials spill trajectory prediction. Therefore, in this paper, we propose a predictive model for future current data based on historical HF coastal radar data sets, utilizing association rule mining combined with an object dispersion concept. So, the full potential of HF radar systems can be exploited. The spatial and temporal dimensions are taken into account when designing our predictive system, which consists of two phases: ocean surface current track formulation and spatio-temporal association rule mining. The experiments are performed on a two-year HF radar dataset (2014-2015) using Google Cloud Platform. The resulting forecast current values: velocity and direction are then compared with testing datasets (using 10-fold cross validation) of the actual recorded values and evaluated based on percentage accuracy and RMSE, respectively.

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A preliminary design of an intelligent system for the optimal utilization of renewable energy sources in buildings 26

A preliminary design of an intelligent system for the optima...

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26th Annual International Ocean and Polar engineering Conference, ISOPE 2016

作者： Georgiou, Giorgos S. Christodoulides, Paul Kalogirou, Soteris A. Florides, Georgios A. Lazari, Lazaros Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Faculty of Engineering and Technology Cyprus University of Technology Limassol Cyprus Department of Mechanical Engineering and Materials Science and Engineering Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781880653883

Renewable energy is important nowadays, not only as an environmental scientific issue, but as an obligation with regard to the European regulations. As a result, scientific interest has increased towards the improvement of the different renewable energy technologies and their optimum utilization in different applications. Initially the paper reviews previous studies regarding the optimum utilization and control of the renewable energy generation installed in buildings and in general in building energy management. The final section of the paper is a novel application related to the studies reviewed;however, this application uses a new and simple way to minimize the energy consumption levels through linear programming optimization. © Copyright 2016 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Energy utilization

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A network approach to quantifying radiotherapy effect on cancer: radiosensitive gene group centrality

arXiv

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arXiv 2018年

作者： Yao, Yu-Xiang Bing, Zhi-Tong Huang, Liang Huang, Zi-Gang Lai, Ying-Cheng School of Physical Science and Technology Lanzhou University Lanzhou730000 China Evidence Based Medicine Center School of Basic Medical Science of Lanzhou University Lanzhou730000 China Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province Lanzhou730000 China Department of Computational Physics Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China Key Laboratory of Biomedical Information Engineering of Ministry of Education National Engineering Research Center of Health Care and Medical Devices Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs Institute of Health and Rehabilitation Science School of Life Science and Technology Xi’an Jiaotong University Xi’an710049 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Radiotherapy plays a vital role in cancer treatment, for which accurate prognosis is important for guiding sequential treatment and improving the curative effect for patients. An issue of great significance in radiotherapy is to assess tumor radiosensitivity for devising the optimal treatment strategy. Previous studies focused on gene expression in cells closely associated with radiosensitivity, but factors such as the response of a cancer patient to irradiation and the patient survival time are largely ignored. For clinical cancer treatment, a specific pre-treatment indicator taking into account cancer cell type and patient radiosensitivity is of great value but it has been missing. Here, we propose an effective indicator for radiosensitivity: radiosensitive gene group centrality (RSGGC), which characterizes the importance of the group of genes that are radiosensitive in the whole gene correlation network. We demonstrate, using both clinical patient data and experimental cancer cell lines, which RSGGC can provide a quantitative estimate of the effect of radiotherapy, with factors such as the patient survival time and the survived fraction of cancer cell lines under radiotherapy fully taken into account. Our main finding is that, for patients with a higher RSGGC score before radiotherapy, cancer treatment tends tobe more effective. The RSGGC can have significant applications in clinical prognosis, serving as a key measure to classifying radiosensitive and radioresistant patients. Copyright © 2018, The Authors. All rights reserved.

关键词： Radiotherapy

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