Waseda University

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

Measurement of neutral mesons in p+p collisions at √s=200GeV and scaling properties of hadron production

Abstract: The PHENIX experiment at the Relativistic Heavy Ion Collider has measured the invariant differential cross section for production of K-S(0), omega, eta', and phi mesons in p + p collisions at root s 200 GeV. Measurements of omega and phi production in different decay channels give consistent results. New results for the omega are in agreement with previously published data and extend the measured p(T) coverage. The spectral shapes of all hadron transverse momentum distributions measured by PHENIX are well described by a Tsallis distribution functional form with only two parameters, n and T, determining the high-p(T) and characterizing the low-p(T) regions of the spectra, respectively. The values of these parameters are very similar for all analyzed meson spectra, but with a lower parameter T extracted for protons. The integrated invariant cross sections calculated from the fitted distributions are found to be consistent with existing measurements and with statistical model predictions.

Recent advances in enantioselective [2 + 2 + 2] cycloaddition

Abstract: Enantioselective cycloaddition using chiral transition metal catalysts is an atom-economical and efficient synthetic tool for the construction of chiral carbo- and heterocyclic skeletons. This short account discloses our recent results of inter- and intramolecular enantioselective [2 + 2 + 2] cycloadditions of alkyne and/or alkene moiety(ies). Chiral iridium complexes catalyzed the alkyne trimerization for the generation of axial chirality(ies), and chiral rhodium ones catalyzed alkyne-alkyne-alkene cyclization for the generation of a quaternary carbon including spirocyclic system.

Multiscale space---time fluid---structure interaction techniques

Abstract: We present the multiscale space---time techniques we have developed for fluid---structure interaction (FSI) computations. Some of these techniques are multiscale in the way the time integration is performed (i.e. temporally multiscale), some are multiscale in the way the spatial discretization is done (i.e. spatially multiscale), and some are in the context of the sequentially-coupled FSI (SCFSI) techniques developed by the Team for Advanced Flow Simulation and Modeling $${({\rm T} \bigstar {\rm AFSM})}$$ . In the multiscale SCFSI technique, the FSI computational effort is reduced at the stage we do not need it and the accuracy of the fluid mechanics (or structural mechanics) computation is increased at the stage we need accurate, detailed flow (or structure) computation. As ways of increasing the computational accuracy when or where needed, and beyond just increasing the mesh refinement or decreasing the time-step size, we propose switching to more accurate versions of the Deforming-Spatial-Domain/Stabilized Space---Time (DSD/SST) formulation, using more polynomial power for the basis functions of the spatial discretization or time integration, and using an advanced turbulence model. Specifically, for more polynomial power in time integration, we propose to use NURBS, and as an advanced turbulence model to be used with the DSD/SST formulation, we introduce a space---time version of the residual-based variational multiscale method. We present a number of test computations showing the performance of the multiscale space---time techniques we are proposing. We also present a stability and accuracy analysis for the higher-accuracy versions of the DSD/SST formulation.

OTA: Optimal Transport Assignment for Object Detection

Abstract: Recent advances in label assignment in object detection mainly seek to independently define positive/negative training samples for each ground-truth (gt) object. In this paper, we innovatively revisit the label assignment from a global perspective and propose to formulate the assigning procedure as an Optimal Transport (OT) problem – a well-studied topic in Optimization Theory. Concretely, we define the unit transportation cost between each demander (anchor) and supplier (gt) pair as the weighted summation of their classification and regression losses. After formulation, finding the best assignment solution is converted to solve the optimal transport plan at minimal transportation costs, which can be solved via Sinkhorn-Knopp Iteration. On COCO, a single FCOS-ResNet-50 detector equipped with Optimal Transport Assignment (OTA) can reach 40.7% mAP under 1× scheduler, outperforming all other existing assigning methods. Extensive experiments conducted on COCO and CrowdHuman further validate the effectiveness of our proposed OTA, especially its superiority in crowd scenarios. The code is available at https://github.com/Megvii-BaseDetection/OTA.

Autonomous Mobile Robot Navigation Using Passive RFID in Indoor Environment

Abstract: This paper proposes an efficient method for localization and pose estimation for mobile robot navigation using passive radio-frequency identification (RFID). We assume that the robot is able to identify IC tags and measure the robot's pose based on the relation between the previous and current location according to the IC tags. However, there arises the problem of uncertainty of location due to the nature of the antenna and IC tags. In other words, an error is always present which is relative to the sensing area of the antenna. Many researches have used external sensors in order to reduce the location errors, with few researches presented involving purely RFID driven systems. Our proposed algorithm that uses only passive RFID is able to estimate the robot's location and orientation more precisely by using trigonometric functions and the IC tags' Cartesian coordinates in a regular gridlike pattern. The experimental results show that the proposed method effectively estimates both the location and the pose of a mobile robot during navigation.