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Institution

Nagoya Institute of Technology

EducationNagoya, Japan
About: Nagoya Institute of Technology is a education organization based out in Nagoya, Japan. It is known for research contribution in the topics: Thin film & Turbulence. The organization has 10766 authors who have published 19140 publications receiving 255696 citations. The organization is also known as: Nagoya Kōgyō Daigaku & Nitech.


Papers
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Proceedings ArticleDOI
02 Apr 1995
TL;DR: The proposed media synchronization mechanism consists of intra-stream and inter-stream synchronization mechanisms which adjusts the output timing among stored continuous media streams in multimedia communications and is enhanced to support real-time-inputted media streams as in TV conferencing.
Abstract: This paper proposes a media synchronization mechanism which adjusts the output timing among stored continuous media streams in multimedia communications. The proposed method consists of intra-stream and inter-stream synchronization mechanisms. The inter-stream synchronization control is performed after the intra-stream synchronization control. Then, whether the intra-stream synchronization is still maintained or not is checked. The mechanism con be used in networks which have unknown delay bounds, and it does not suppose periodical generation of media units such as video frames. It also deals with two types of media streams depending on how strictly to synchronize media streams: tightly-coupled media streams and loosely-coupled media streams. Furthermore, we enhance the mechanism to support real-time-inputted media streams as in TV conferencing.

135 citations

Journal ArticleDOI
TL;DR: A matrix-free implementation of the finite-element method with a geometric multigrid method that can potentially reduce the computation time to several seconds or less even when using an ordinary computer is presented.
Abstract: In transcranial magnetic stimulation (TMS), the distribution of the induced electric field, and the affected brain areas, depends on the position of the stimulation coil and the individual geometry of the head and brain. The distribution of the induced electric field in realistic anatomies can be modelled using computational methods. However, existing computational methods for accurately determining the induced electric field in realistic anatomical models have suffered from long computation times, typically in the range of tens of minutes or longer. This paper presents a matrix-free implementation of the finite-element method with a geometric multigrid method that can potentially reduce the computation time to several seconds or less even when using an ordinary computer. The performance of the method is studied by computing the induced electric field in two anatomically realistic models. An idealized two-loop coil is used as the stimulating coil. Multiple computational grid resolutions ranging from 2 to 0.25 mm are used. The results show that, for macroscopic modelling of the electric field in an anatomically realistic model, computational grid resolutions of 1 mm or 2 mm appear to provide good numerical accuracy compared to higher resolutions. The multigrid iteration typically converges in less than ten iterations independent of the grid resolution. Even without parallelization, each iteration takes about 1.0 s or 0.1 s for the 1 and 2 mm resolutions, respectively. This suggests that calculating the electric field with sufficient accuracy in real time is feasible.

135 citations

Journal ArticleDOI
TL;DR: In this paper, the mean velocity distributions and all six components of Reynolds stress are made for the two boundary layers developed on the rotating disk (rotor) and the stationary end wall (stator) for the turbulent flow due to an enclosed rotating disk and it is revealed that the velocity distributions in the respective boundary layers show a similarity at constant local Reynolds number.

134 citations

Journal ArticleDOI
TL;DR: In this article, the enhancement of device performance with AlN buffer thickness (200 and 300nm) is due to the reduction of electrically active defects from Si substrate, which is confirmed by x-ray rocking curve measurements.
Abstract: Enhancement of breakdown voltage (BV) with the increase of AlN buffer layer thickness was observed in AlGaN∕GaN high-electron-mobility transistors (HEMTs) grown by metalorganic chemical vapor deposition on 4in. Si. The enhancement of device performance with AlN buffer thickness (200 and 300nm) is due to the reduction of electrically active defects from Si substrate. The reduction of defects from Si with the increase of AlN thickness was confirmed by x-ray rocking curve measurements. Not much change has been observed in ON-state BV (BV:ON) values except in devices with 500‐nm-thick buffer layer. About 46% enhancement in OFF-state BV (BV:OFF) was observed on 200μm wide HEMTs with 300nm thick AlN buffer layer when compared to HEMTs with 8nm thick AlN buffer layer. The location of junction breakdown in the device was identified as GaN∕AlN∕Si interface. The measured specific on-resistance (Ron) values for 200 and 400μm wide HEMTs with 300nm thick buffer layers were 0.28 and 0.33mΩcm2, respectively. About an or...

134 citations

Journal ArticleDOI
TL;DR: A novel class of bit-flipping algorithm for decoding low-density parity-check (LDPC) codes is presented, which exhibit better decoding performance than known BF algorithms, such as the weighted BF algorithms or the modified weighted BF algorithm for several LDPC codes.
Abstract: A novel class of bit-flipping (BF) algorithm for decoding low-density parity-check (LDPC) codes is presented. The proposed algorithms, which are referred to as gradient descent bit flipping (GDBF) algorithms, can be regarded as simplified gradient descent algorithms. The proposed algorithms exhibit better decoding performance than known BF algorithms, such as the weighted BF algorithm or the modified weighted BF algorithm for several LDPC codes.

133 citations


Authors

Showing all 10804 results

NameH-indexPapersCitations
Luis M. Liz-Marzán13261661684
Hideo Hosono1281549100279
Shunichi Fukuzumi111125652764
Andrzej Cichocki9795241471
Kwok-Hung Chan9140644315
Kimoon Kim9041235394
Alex Martin8840636063
Manijeh Razeghi82104025574
Yuichi Ikuhara7597424224
Richard J. Cogdell7348023866
Masaaki Tanaka7186022443
Kiyotomi Kaneda6537813337
Yulin Deng6464116148
Motoo Shiro6472017786
Norio Shibata6357414469
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202316
202272
2021631
2020718
2019701
2018764