96 research outputs found

    Design Space Exploration and Resource Management of Multi/Many-Core Systems

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    The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

    Remote Sensing in Mangroves

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    The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the worl

    DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search

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    Kernel Density Estimation (KDE) is a nonparametric method for estimating the shape of a density function, given a set of samples from the distribution. Recently, locality-sensitive hashing, originally proposed as a tool for nearest neighbor search, has been shown to enable fast KDE data structures. However, these approaches do not take advantage of the many other advances that have been made in algorithms for nearest neighbor algorithms. We present an algorithm called Density Estimation from Approximate Nearest Neighbors (DEANN) where we apply Approximate Nearest Neighbor (ANN) algorithms as a black box subroutine to compute an unbiased KDE. The idea is to find points that have a large contribution to the KDE using ANN, compute their contribution exactly, and approximate the remainder with Random Sampling (RS). We present a theoretical argument that supports the idea that an ANN subroutine can speed up the evaluation. Furthermore, we provide a C++ implementation with a Python interface that can make use of an arbitrary ANN implementation as a subroutine for KDE evaluation. We show empirically that our implementation outperforms state of the art implementations in all high dimensional datasets we considered, and matches the performance of RS in cases where the ANN yield no gains in performance.Comment: 24 pages, 1 figure. Submitted for revie

    Book of short Abstracts of the 11th International Symposium on Digital Earth

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    The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

    China’s Foreign Investment Legal Regime:Progress and Limitations

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    筑波大学計算科学研究センター 平成30年度 年次報告書

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    まえがき ...... 21 センター組織と構成員 ...... 42 平成30 年度の活動状況 ...... 83 各研究部門の報告 ...... 15I. 素粒子物理研究部門 ...... 15II. 宇宙物理研究部門 ....... 40III. 原子核物理研究部門 ...... 65IV. 量子物性研究部門 ...... 83V. 生命科学研究部門 ...... 110 V-1. 生命機能情報分野 ...... 110 V-2. 分子進化分野 ...... 125VI. 地球環境研究部門 ...... 140VII. 高性能計算システム研究部門 ...... 155VIII. 計算情報学研究部門 ...... 207 VIII-1. データ基盤分野 ...... 207 VIII-2. 計算メディア分野 ...... 22

    Power System Simulation, Control and Optimization

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    This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence

    Performance evaluation of the WRF model under different physical schemes for air quality purposes in Buenos Aires, Argentina

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    Este trabajo presenta la evaluación de desempeño del Modelo para la Predicción e Investigación del Clima (WRF, por su sigla en inglés) para estimar la velocidad y dirección del viento, temperatura del aire y fracción de vapor de agua en superficie, considerando 22 configuraciones en alta resolución espacial (1 km) durante una semana de invierno y una de primavera, con el fin de determinar los esquemas que presentan mejor desempeño en el Área Metropolitana de Buenos Aires, Argentina, para ser utilizados en estudios de calidad del aire. Los resultados muestran que el uso de un esquema urbano afecta mayormente a la velocidad del viento y a la temperatura. El esquema urbano con una capa (UCM) acoplado con el esquema de capa límite (PBL) Boulac presenta el mejor desempeño para velocidad del viento. La dirección del viento y la fracción de vapor de agua son más sensibles al esquema de suelo, dando mejores resultados con el esquema de superficie Noah-Mp. Los errores tanto de dirección como de velocidad del viento son mayores cuando esta última toma valores pequeños. Al remover los valores de velocidad del viento menores a 2.6 m s–1 para la semana de invierno y 3.1 m s–1 para la de primavera, los errores cuadráticos de la dirección del viento decaen entre 50 y 72% de su valor original, dependiendo de la configuración y la semana. En general, en las condiciones estudiadas, las configuraciones que incluyen Noah-Mp o la combinación de Boulac con el esquema urbano simple son más adecuadas para utilizarse en estudios de calidad del aire, ya que reproducen de forma aceptable la temperatura y la fracción de vapor de agua con errores menores al 10% y Correlaciones mayores a 0.7, y poseen el mejor desempeño para dirección y velocidad del viento, respectivamente.This work presents the performance evaluation of the Weather Research and Forecasting (WRF) model to estimate surface wind speed and direction, air temperature, and water vapor mixing ratio considering 22 configurations at high spatial resolution (1 km) during one week in winter and one week in spring, in order to determine the best-performing schemes for air quality purposes in the Metropolitan Area of Buenos Aires, Argentina. Results show that the use of urban schemes mostly affects wind speed and temperature. The single-layer urban canopy model (UCM) coupled with the Boulac planetary boundary layer (PBL) scheme exhibits the best results for wind speed. Wind direction and water vapor mixing ratio are more sensitive to the land surface model scheme, with results slightly improving with the Noah-MP land surface model. Wind speed and direction errors are larger when the former is lower. When removing from the analysis wind speed values below 2.6 ms-1 for the winter week and 3.1 ms-1 for the spring week, the root mean square errors for wind direction decreased between 50 and 72% of the original value, depending on the configuration and week. Overall, under the studied conditions, configurations including Noah-Mp land surface model or the combination of a simple UCM with BouLac PBL are suitable for air quality applications, as they reproduce both temperature and water vapor mixing ratio relatively well, with errors below 10% and Correlation values above 0.7, and are the best performing configurations for wind direction and speed, respectively.Fil: Luque, Solange Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-argentino Sobre Estudios del Clima y Sus Impactos.; ArgentinaFil: Fita Borrell, Lluís. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-argentino Sobre Estudios del Clima y Sus Impactos.; ArgentinaFil: Pineda Rojas, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-argentino Sobre Estudios del Clima y Sus Impactos.; Argentin

    Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

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    The implementation of artificial intelligence (AI), together with robotics, sensors, sensor networks, Internet of Things (IoT), and machine/deep learning modeling, has reached the forefront of research activities, moving towards the goal of increasing the efficiency in a multitude of applications and purposes related to environmental sciences. The development and deployment of AI tools requires specific considerations, approaches, and methodologies for their effective and accurate applications. This Special Issue focused on the applications of AI to environmental systems related to hazard assessment in urban, agriculture, and forestry areas

    Land Use Change from Non-urban to Urban Areas

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    This reprint is related to land-use change and non-urban and urban relationships at all spatiotemporal scales and also focuses on land-use planning and regulatory strategies for a sustainable future. Spatiotemporal dynamics, socioeconomic implication, water supply problems and deforestation land degradation (e.g., increase of imperviousness surfaces) produced by urban expansion and their resource requirements are of particular interest. The Guest Editors expect that this reprint will contribute to sustainable development in non-urban and urban areas
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