26 research outputs found

    Field measurements of absolute gravity in East Antarctica

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    This paper reports the results of field-based absolute gravity measurements aimed at detecting gravity change and crustal displacement caused by glacial isostatic adjustment. The project was initiated within the framework of the 53rd Japanese Antarctic Research Expedition (JARE53). Absolute gravity measurements, together with GPS measurements, were planned at several outcrops along the Prince Olav Coast and Sôya Coast of East Antarctica, including at Syowa Station. Since the icebreaker Shirase (AGB 5003) was unable to moor alongside Syowa Station, operations were somewhat restricted during JARE53. However, despite this setback, we were able to complete measurements at two sites: Syowa Station and Langhovde. The absolute gravity value at the Syowa Station IAGBN (A) site, observed using an FG-5 absolute gravimeter (serial number 210; FG-5 #210), was 982 524 322.7±0.1 μGal, and the gravity change rate at the beginning of 2012 was –0.26 μGal∙a-1. An absolute gravity value of 982 535 584.2±0.7 μGal was obtained using a portable A-10 absolute gravimeter (serial number 017; A-10 #017) at the newly located site AGS01 in Langhovde

    Measurement of the bbb\overline{b} dijet cross section in pp collisions at s=7\sqrt{s} = 7 TeV with the ATLAS detector

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    Search for single production of vector-like quarks decaying into Wb in pp collisions at s=8\sqrt{s} = 8 TeV with the ATLAS detector

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    Measurement of the charge asymmetry in top-quark pair production in the lepton-plus-jets final state in pp collision data at s=8TeV\sqrt{s}=8\,\mathrm TeV{} with the ATLAS detector

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    Search for dark matter in association with a Higgs boson decaying to bb-quarks in pppp collisions at s=13\sqrt s=13 TeV with the ATLAS detector

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    Charged-particle distributions at low transverse momentum in s=13\sqrt{s} = 13 TeV pppp interactions measured with the ATLAS detector at the LHC

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    ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

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    Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants

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    Abstract. We proposed a method of using machine learning with various features for the recognition of Japanese notational variants. We increased 0.06 at the F-measure by specic features using existing dictionaries and character pairs useful for recognizing notational vari-ants and obtained 0.91 at the F-measure for the recognition of notational variants. By using the method, we could extract 160 thousand word pairs with a precision rate of 0.9. We also constructed a method using patterns in addition to machine learning and observed that we could extract 4.2 million notational variant pairs with a precision rate of 0.78. We conrmed that our method was much better than an existing method through experiments
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