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Search Results: 1 - 10 of 522 matches for " Tohru Ohnuki "
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Measurement of Carbon Disulfide Anion Diffusion in a TPC
Tohru Ohnuki,Daniel P. Snowden-Ifft,C. J. Martoff
Physics , 2000, DOI: 10.1016/S0168-9002(01)00222-4
Abstract: A Negative Ion Time Projection Chamber was used to measure the field dependence of lateral and longitudinal diffusion for CS$_2$ anions drifting in mixtures of CS$_2$ and Ar at 40 Torr. Ion drift velocities and limits on the capture distance for electrons as a function of field and gas mixture are also reported.
Robust MPC Method for BMI Based Wheelchair  [PDF]
Tohru Kawabe
Intelligent Control and Automation (ICA) , 2011, DOI: 10.4236/ica.2011.24039
Abstract: In this paper, robust MPC (Model Predictive Control) with adaptive DA converter method for the wheelchair using EEG (Electroencephalogram) based BMI (Brain Machine Interface) is discussed. The method is developed to apply to the obstacle avoidance system of wheelchair. This paper is the 1st stage for the development of the BMI based wheelchair in practical use. The robust MPC method is realized by using the minimax optimization with bounded constraint conditions. Some numerical examples are also included to demonstrate the effectiveness of the proposed methodas the former stage of the real experiments.
A Theoretical Foundation for the Widely Linear Processing of Quaternion-Valued Data  [PDF]
Tohru Nitta
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.412219
Abstract:

In this paper, we will give a theoretical foundation for a quaternion-valued widely linear estimation framework. The estimation error obtained with the quaternion-valued widely linear estimation method is proved to be smaller than that obtained using the usual quaternion-valued linear estimation method.

Learning Dynamics of the Complex-Valued Neural Network in the Neighborhood of Singular Points  [PDF]
Tohru Nitta
Journal of Computer and Communications (JCC) , 2014, DOI: 10.4236/jcc.2014.21005
Abstract:

In this paper, the singularity and its effect on learning dynamics in the complex-valued neural network are elucidated. It has learned that the linear combination structure in the updating rule of the complex-valued neural network increases the speed of moving away from the singular points, and the complex-valued neural network cannot be easily influenced by the singular points, whereas the learning of the usual real-valued neural network can be attracted in the neighborhood of singular points, which causes a standstill in learning. Simulation results on the learning dynamics of the three-layered real-valued and complex-valued neural networks in the neighborhood of singularities support the analytical results.

Characterization of point transformations in quantum mechanics
Yoshio Ohnuki,Shuji Watanabe
Mathematics , 2012,
Abstract: We characterize point transformations in quantum mechanics from the mathematical viewpoint. To conclude that the canonical variables given by each point transformation in quantum mechanics correctly describe the extended point transformation, we show that they are all selfadjoint operators in $L^2(\mathbb{R}^n)$ and that the continuous spectrum of each coincides with $\mathbb{R}$. They are also shown to satisfy the canonical commutation relations.
Slip Suppression of Electric Vehicles Using Sliding Mode Control Method  [PDF]
Shaobo Li, Tohru Kawabe
Intelligent Control and Automation (ICA) , 2013, DOI: 10.4236/ica.2013.43038
Abstract: This paper presents a slip suppression controller using sliding mode control method for electric vehicles which aims to improve the control performance and the energy conservation by controlling the slip ratio of wheel. In this method, a robust sliding mode controller against the model uncertainties is designed to obtain the maximum driving force by suppressing the slip ratio. The numerical simulations for one wheel model under variations in mass of vehicle and road condition are performed and demonstrated to show the effectiveness of the proposed method.
A microfluidic device to acquire high-magnification microphotographs of yeast cells
Shinsuke Ohnuki, Satoru Nogami, Yoshikazu Ohya
Cell Division , 2009, DOI: 10.1186/1747-1028-4-5
Abstract: In this study, we developed a microfluidic chip designed to acquire successive microscopic images of yeast cells suitable for CalMorph image analysis. With the microfluidic chip, the morphology of living cells and morphological changes that occur during the cell cycle were successfully characterized.The microfluidic chip enabled us to acquire the images faster than the conventional method. We speculate that the use of microfluidic chip is effective in acquiring images of large-scale for automated analysis of yeast strains.Studies on cellular morphology have contributed to the discovery of factors involved in cell cycle control for various model organisms. In the yeast Saccharomyces cerevisiae, for example, many important findings related to cell cycle control have been reported, as yeast cell cycle progression is easily monitored via changes in cell morphology [1-3]. For growing yeasts, characteristic periodic morphological changes and structural rearrangements are observed morphologically such as bud emergence, bud formation, polarized actin localization, nuclear migration, karyokinesis, and cytokinesis [4-8]. During the G1 phase, yeast cell shape is a simple ellipsoid, and at the end of the G1 phase, the actin patches are localized at the presumed bud site [4]. When cells enter the S phase, DNA synthesis starts, and a bud emerges at the presumed bud site. During the S phase, the bud apically grows from the bud tip where actin patches are kept localized [4,5]. When the bud size becomes about two-thirds of that of mother, DNA synthesis ends and the bud is switched to isotropic growth with randomly redistributed actin patches in the bud [4,6,7]. Once the nucleus is localized at the neck and the actin patches are delocalized in the whole cell, the cell enters the M phase. During the M phase, the nucleus is divided to two nuclei and at the late M phase, the actin patches are localized again at the bud neck for cytokinesis [4,8]. A genetic approach for isolating and cha
Rainfall and Runoff Observations in the Subtropical Forest of Okinawa Island, Japan  [PDF]
Naoki Kabeya, Akira Shimizu, Takanori Shimizu, Hitoshi Ikuzawa, Takuya Arakaki, Hiroshi Furugen, Yashuhiro Ohnuki, Shiho Asano
Journal of Water Resource and Protection (JWARP) , 2014, DOI: 10.4236/jwarp.2014.66061
Abstract:

We set up two experimental catchments to provide an improved understanding of hydrological processes in a subtropical forested area in the northern part of Okinawa Island, Japan. We calculated runoff using water level data (recorded by a pressure-type water level gauge installed in a box culvert) and a discharge rating curve (derived from in situ observations). Water balance calculations for 2010 showed that the rainfall, runoff and evapotranspiration losses (= rainfall – runoff) were 3403.6 mm, 2285.7 mm and 1117.4 mm, respectively. This result was in agreement with previous results from other forested experimental catchments in this region. Direct runoff, as a proportion of event total rainfall, can be expressed by the empirical equation (Qdirect = 0.0048, Pevent 1.7971, R2 = 0.9599). When Pevent was 100 mm or less, the ratios of Qdirect to Pevent were less than 15% in general. When Pevent exceeded 100 mm, the ratios were 20% - 30%.

Dividing Genetic Computation Method for Robust Receding Horizon Control Design
Tohru Kawabe
Applied Computational Intelligence and Soft Computing , 2010, DOI: 10.1155/2010/168653
Abstract: A new robust Receding Horizon Control (RHC) design approach for the sampled-data systems is proposed. The approach is based on a dividing genetic computation of minimax optimization for a robust finite receding horizon control problem. Numerical example is given to show the effectiveness of the proposed method. 1. Introduction In last few decades, the Receding Horizon Control (RHC) has been widely accepted in the industries [1]. RHC is an online powerful control method which solves a control problem with respect to each sampling frequency [2]. A significant merit of RHC is easy handling of constraints during the design and implementation of the controller [2, 3]. In the standard RHC formulation, the current control action is derived by solving a finite or infinite horizon quadratic cost problem at every sample time using the current state of the plant as the initial state [1]. It is an online optimization with big calculation amount. Then, the RHC has been applied conventionally to systems with relatively slow-moving dynamics such as petrochemical plants and so on. However, recent advance of computer performance has made it possible to use it for systems with relatively fast-moving dynamics, for example, the mechatronics and so on. Therefore, it is important to develop a practical RHC method for such systems. Incidentally, a drawback of the standard RHC is explicitly lack of robust property with respect to model uncertainties or disturbances since the online minimized cost function is defined in terms of the nominal systems. A possible strategy for realizing the robust RHC is solving the so-called minimax optimization problem, namely, minimization problem over the control input of the performance measure maximized by plant uncertainties or disturbances. An earliest work was proposed by Campo and Morari [4] and Zheng and Morari [5]. Kothare et al. solve minimax RHC problems with state-space uncertainties through LMIs [6]. Cuzzola et al. improve Kothare's method [6] to reduce conservativeness in [7]. Other methods of minimax RHC for systems with model uncertainty can be found in [8–12]. However, the number of available work of the robust RHC is still limited compared with many methods of robust control synthesis for linear systems being proposed. Main reason of this fact is that the robust (minimax) RHC problem is hard to solve in real-time due to the trade-off with an objective function and constraint conditions in the problem generally. The issue of robust RHC therefore still deserves further attention [2, 3] and the effective approach for the robust
Molecular Mechanism for Various Pharmacological Activities of NSAIDS
Tohru Mizushima
Pharmaceuticals , 2010, DOI: 10.3390/ph3051614
Abstract: The anti-inflammatory action of non-steroidal anti-inflammatory drugs (NSAIDs) is mediated through their inhibitory effects on cyclooxygenase (COX) activity. On the other hand, NSAID use is often associated with gastrointestinal complications. The inhibition of COX by NSAIDs is not the sole explanation for the gastrointestinal side effects of NSAIDs. Furthermore, recent epidemiological studies have revealed that prolonged NSAID use reduces the risk of cancer and Alzheimer’s disease (AD) and a COX-independent unknown mechanism is suggested to be involved in these activities of NSAIDs. In this article, I review our recent work on the COX-independent mechanism involved in NSAID-induced gastric lesions and anti-tumor and anti-AD activities of NSAIDs. Using DNA microarray analysis, we found that NSAIDs affect expression of various genes in a COX-independent manner. We found that membrane permeabilization activity of NSAIDs and resulting NSAID-induced apoptosis are involved in NSAID-induced gastric lesions. On the other hand, induction of expression of tight junction-related genes and endoplasmic reticulum chaperones were suggested to be involved in anti-tumor and anti-AD, respectively, activities of NSAIDs. These results suggest that NSAIDs affect expression of various genes in a COX-independent manner, which is involved in various pharmacological activities of NSAIDs.
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