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Institution

Waseda University

EducationTokyo, Japan
About: Waseda University is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Large Hadron Collider & Catalysis. The organization has 24220 authors who have published 46859 publications receiving 837855 citations. The organization is also known as: Waseda daigaku & Sōdai.


Papers
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Journal ArticleDOI
Georges Aad, T. Abajyan1, Brad Abbott2, J. Abdallah3  +2863 moreInstitutions (179)
TL;DR: In this article, the authors measured the jet energy resolution using data recorded with the ATLAS detector in proton-proton collisions at root s = 7 TeV, which corresponds to an integrated luminosity of 35 pb(-1).
Abstract: The measurement of the jet energy resolution is presented using data recorded with the ATLAS detector in proton-proton collisions at root s = 7 TeV. The sample corresponds to an integrated luminosity of 35 pb(-1). Jets are reconstructed from energy deposits measured by the calorimeters and calibrated using different jet calibration schemes. The jet energy resolution is measured with two different in situ methods which are found to be in agreement within uncertainties. The total uncertainties on these measurements range from 20 % to 10 % for jets within vertical bar y vertical bar < 2.8 and with transverse momenta increasing from 30 GeV to 500 GeV. Overall, the Monte Carlo simulation of the jet energy resolution agrees with the data within 10 %.

212 citations

Journal ArticleDOI
TL;DR: In this paper, the selective reduction of NO by CH 4 on zeolite catalysts has been investigated and it was found that Ga-ZSM-5 and In-ZMM-5 were highly active and selective for NO reduction by CH4.

212 citations

Journal ArticleDOI
TL;DR: A modular system for the real-time analysis of body movement and gesture, with a particular focus on the understanding of affect and expressive content in gesture, is developed.
Abstract: The goal of the EyesWeb project is to develop a modular system for the real-time analysis of body movement and gesture. Such information can be used to control and generate sound, music, and visual media, and to control actuators (e.g., robots). Another goal of the project is to explore and develop models of interaction by extending music language toward gesture and visual languages, with a particular focus on the understanding of affect and expressive content in gesture. For example, we attempt to distinguish the expressive content from two instances of the same movement

212 citations

Journal ArticleDOI
TL;DR: An image-based percolation model is proposed that extracts a continuous texture by referring to the connectivity of brightness and the shape of the percolated region, depending on the length criterion of the scalable local image processing techniques.
Abstract: In this paper, we introduce a novel image-based approach to detect cracks in concrete surfaces. Crack detection is important for the inspection, diagnosis, and maintenance of concrete structures. However, conventional image-based approaches cannot achieve precise detection since the image of the concrete surface contains various types of noise due to different causes such as concrete blebs, stain, insufficient contrast, and shading. In order to detect the cracks with high fidelity, we assume that they are composed of thin interconnected textures and propose an image-based percolation model that extracts a continuous texture by referring to the connectivity of brightness and the shape of the percolated region, depending on the length criterion of the scalable local image processing techniques. Additionally, noise reduction based on the percolation model is proposed. We evaluated the validity of the proposed technique by using precision recall and receiver operating characteristic (ROC) analysis by means of some experiments with actual concrete surface images. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

211 citations

Journal ArticleDOI
A. A. Abdo1, A. A. Abdo2, Markus Ackermann3, Marco Ajello3  +209 moreInstitutions (36)
TL;DR: In this paper, the gamma-ray luminosities of FRI radio galaxies are significantly smaller than those of BL Lac objects detected by the LAT, whereas the FRII sources are quite similar to those of FSRQs, which could reflect different beaming factors for the gamma radiation emission.
Abstract: Analysis is presented on 15 months of data taken with the Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope for 11 non-blazar AGNs, including 7 FRI radio galaxies and 4 FRII radio sources consisting of 2 FRII radio galaxies and 2 steep spectrum radio quasars. The broad line FRI radio galaxy 3C 120 is reported here as a gamma-ray source for the first time. The analysis is based on directional associations of LAT sources with radio sources in the 3CR, 3CRR and MS4 (collectively referred to as 3C-MS) catalogs. Seven of the eleven LAT sources associated with 3C-MS radio sources have spectral indices larger than 2.3 and, except for the FRI radio galaxy NGC 1275 that shows possible spectral curvature, are well described by a power law. No evidence for time variability is found for any sources other than NGC 1275. The gamma-ray luminosities of FRI radio galaxies are significantly smaller than those of BL Lac objects detected by the LAT, whereas the gamma-ray luminosities of FRII sources are quite similar to those of FSRQs, which could reflect different beaming factors for the gamma-ray emission. A core dominance study of the 3CRR sample indicate that sources closer to the jet axis are preferentially detected with the Fermi-LAT, insofar as the gamma-ray--detected misaligned AGNs have larger core dominance at a given average radio flux. The results are discussed in view of the AGN unification scenario.

210 citations


Authors

Showing all 24378 results

NameH-indexPapersCitations
Yusuke Nakamura1792076160313
Yoshio Bando147123480883
Charles Maguire142119795026
Kazunori Kataoka13890870412
Senta Greene134134690697
Intae Yu134137289870
Kohei Yorita131138991177
Wei Xie128128177097
Susumu Kitagawa12580969594
Leon O. Chua12282471612
Jun Kataoka12160354274
S. Youssef12068365110
Katsuhiko Mikoshiba12086662394
Yusuke Yamauchi117100051685
Teruo Okano11747647081
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202380
2022237
20212,347
20202,467
20192,367
20182,289