1,819 research outputs found

    Summary of the Sussex-Huawei Locomotion-Transportation Recognition Challenge

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    In this paper we summarize the contributions of participants to the Sussex-Huawei Transportation-Locomotion (SHL) Recognition Challenge organized at the HASCA Workshop of UbiComp 2018. The SHL challenge is a machine learning and data science competition, which aims to recognize eight transportation activities (Still, Walk, Run, Bike, Bus, Car, Train, Subway) from the inertial and pressure sensor data of a smartphone. We introduce the dataset used in the challenge and the protocol for the competition. We present a meta-analysis of the contributions from 19 submissions, their approaches, the software tools used, computational cost and the achieved results. Overall, two entries achieved F1 scores above 90%, eight with F1 scores between 80% and 90%, and nine between 50% and 80%

    Optical Spectropolarimetry of SN 2002ap: High Velocity Asymmetric Explosion

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    We present spectropolarimetry of the Type Ic supernova SN 2002ap and give a preliminary analysis: the data were taken at two epochs, close to and one month later than the visual maximum (2002 February 8). In addition we present June 9 spectropolarimetry without analysis. The data show the development of linear polarization. Distinct polarization profiles were seen only in the O I \lambda 7773 multiplet/Ca II IR triplet absorption trough at maximum light and in the Ca II IR triplet absorption trough a month later, with the latter showing a peak polarization as high as ~2 %. The intrinsic polarization shows three clear position angles: 80 degs for the February continuum, 120 degs for the February line feature, and 150 degs for the March data. We conclude that there are multiple asymmetric components in the ejecta. We suggest that the supernova has a bulk asymmetry with an axial ratio projected on the sky that is different from 1 by of order 10 %. Furthermore, we suggest very speculatively that a high velocity ejecta component moving faster than ~0.115c (e.g., a jet) contributes to polarization in the February epoch.Comment: 7 pages, 3 figures, accepted for publication in the Astrophysical Journal (Letters

    Summary of the Sussex-Huawei Locomotion-Transportation Recognition Challenge 2019

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    In this paper we summarize the contributions of participants to the third Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCAWorkshop of UbiComp/ISWC 2020. The goal of this machine learning/data science challenge is to recognize eight locomotion and transportation activities (Still, Walk, Run, Bike, Bus, Car, Train, Subway) from the inertial sensor data of a smartphone in a user-independent manner with an unknown target phone position. The training data of a “train” user is available from smartphones placed at four body positions (Hand, Torso, Bag and Hips). The testing data originates from “test” users with a smartphone placed at one, but unknown, body position. We introduce the dataset used in the challenge and the protocol of the competition. We present a meta-analysis of the contributions from 15 submissions, their approaches, the software tools used, computational cost and the achieved results. Overall, one submission achieved F1 scores above 80%, three with F1 scores between 70% and 80%, seven between 50% and 70%, and four below 50%, with a latency of maximum of 5 seconds

    MITSuME--Multicolor Imaging Telescopes for Survey and Monstrous Explosions

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    Development of MITSuME is reported. Two 50-cm optical telescopes have been built at Akeno in Yamanashi prefecture and at Okayama Astrophysical Observatory (OAO) in Okayama prefecture. Three CCD cameras for simultaneous g'RcIc photometry are to be mounted on each focal plane, covering a wide FOV of about 30" x 30". The limiting magnitude at V is fainter than 18. In addition to these two optical telescopes, a 91-cm IR telescope with a 1 deg x 1 deg field of view is being built at OAO, which performs photometry in YJHK bands. These robotic telescopes can start the observation of counterparts of a GRB within a minute from an alert. We aim to obtain photometric redshifts exceeding 10 with these telescopes. The performance and the current construction status of the telescopes are presented.Comment: 4 pages, 3 figures, 4th Workshop on Gamma-Ray Burst in the Afterglow Era, Roma, October 18-22, 200

    Summary of the Sussex-Huawei locomotion-transportation recognition challenge 2020

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    In this paper we summarize the contributions of participants to the third Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCAWorkshop of UbiComp/ISWC 2020. The goal of this machine learning/data science challenge is to recognize eight locomotion and transportation activities (Still, Walk, Run, Bike, Bus, Car, Train, Subway) from the inertial sensor data of a smartphone in a user-independent manner with an unknown target phone position. The training data of a “train” user is available from smartphones placed at four body positions (Hand, Torso, Bag and Hips). The testing data originates from “test” users with a smartphone placed at one, but unknown, body position. We introduce the dataset used in the challenge and the protocol of the competition. We present a meta-analysis of the contributions from 15 submissions, their approaches, the software tools used, computational cost and the achieved results. Overall, one submission achieved F1 scores above 80%, three with F1 scores between 70% and 80%, seven between 50% and 70%, and four below 50%, with a latency of maximum of 5 seconds
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