Tokyo Institute of Technology

About: Tokyo Institute of Technology is a education organization based out in Tokyo, Tôkyô, Japan. It is known for research contribution in the topics: Thin film & Catalysis. The organization has 46775 authors who have published 101656 publications receiving 2357893 citations. The organization is also known as: Tokyo Tech & Tokodai.

Control and Analysis of the Modular Multilevel Cascade Converter Based on Double-Star Chopper-Cells (MMCC-DSCC)

Abstract: This paper presents the modular multilevel cascade converter based on double-star chopper-cells, which is intended for grid connection to medium-voltage power systems without using line-frequency transformers. The converter is characterized by a modular arm structure consisting of cascade connection of multiple bidirectional pulsewidth modulation chopper-cells with floating dc capacitors. This arm structure requires voltage-balancing control of all the dc capacitors. However, the voltage control combining an averaging control with an individual-balancing control imposes certain limitations on operating conditions. This paper proposes an arm-balancing control to achieve voltage balancing under all the operating conditions. The validity of the arm-balancing control as well as the theory developed in this paper is confirmed by computer simulation and experiment.

Single-Image Noise Level Estimation for Blind Denoising

Abstract: Noise level is an important parameter to many image processing applications. For example, the performance of an image denoising algorithm can be much degraded due to the poor noise level estimation. Most existing denoising algorithms simply assume the noise level is known that largely prevents them from practical use. Moreover, even with the given true noise level, these denoising algorithms still cannot achieve the best performance, especially for scenes with rich texture. In this paper, we propose a patch-based noise level estimation algorithm and suggest that the noise level parameter should be tuned according to the scene complexity. Our approach includes the process of selecting low-rank patches without high frequency components from a single noisy image. The selection is based on the gradients of the patches and their statistics. Then, the noise level is estimated from the selected patches using principal component analysis. Because the true noise level does not always provide the best performance for nonblind denoising algorithms, we further tune the noise level parameter for nonblind denoising. Experiments demonstrate that both the accuracy and stability are superior to the state of the art noise level estimation algorithm for various scenes and noise levels.

Experimentally determined postspinel transformation boundary in Mg2SiO4 using MgO as an internal pressure standard and its geophysical implications

Abstract: [1] We have determined the postspinel transformation boundary in Mg2SiO4 by combining quench technique with in situ pressure measurements, using multiple internal pressure standards including Au, MgO, and Pt. The experimentally determined boundary is in general agreement with previous in situ measurements in which the Au scale of Anderson et al. [1989] was used to calculate pressure: Using this pressure scale, it occurs at significantly lower pressures compared to that corresponding to the 660-km seismic discontinuity. In this study, we also report new experimental data on the transformation boundary determined using MgO as an internal standard. The results show that the transition boundary is located at pressures close to the 660-km discontinuity using the MgO pressure scale of Speziale et al. [2001] and can be represented by a linear equation, P(GPa) = 25.12 − 0.0013T(°C). The Clapeyron slope for the postspinel transition boundary is precisely determined and is significantly less negative than previous estimates. Our results, based on the MgO pressure scale, support the conventional hypothesis that the postspinel transformation is responsible for the observed 660-km seismic discontinuity.

ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis

Abstract: Publicly available database of co-expressed gene sets would be a valuable tool for a wide variety of experimental designs, including targeting of genes for functional identification or for regulatory investigation. Here, we report the construction of an Arabidopsis thaliana trans-factor and cis-element prediction database (ATTED-II) that provides co-regulated gene relationships based on co-expressed genes deduced from microarray data and the predicted cis elements. ATTED-II (http://www.atted.bio.titech.ac.jp) includes the following features: (i) lists and networks of co-expressed genes calculated from 58 publicly available experimental series, which are composed of 1388 GeneChip data in A.thaliana; (ii) prediction of cis-regulatory elements in the 200 bp region upstream of the transcription start site to predict co-regulated genes amongst the co-expressed genes; and (iii) visual representation of expression patterns for individual genes. ATTED-II can thus help researchers to clarify the function and regulation of particular genes and gene networks.