Implicit Formulation for SPH‐based Viscous Fluids

We propose a stable and efficient particle‐based method for simulating highly viscous fluids that can generate coiling and buckling phenomena and handle variable viscosity. In contrast to previous methods that use explicit integration, our method uses an implicit formulation to improve the robustness of viscosity integration, therefore enabling use of larger time steps and higher viscosities. We use Smoothed Particle Hydrodynamics to solve the full form of viscosity, constructing a sparse linear system with a symmetric positive definite matrix, while exploiting the variational principle that automatically enforces the boundary condition on free surfaces. We also propose a new method for extracting coefficients of the matrix contributed by second‐ring neighbor particles to efficiently solve the linear system using a conjugate gradient solver. Several examples demonstrate the robustness and efficiency of our implicit formulation over previous methods and illustrate the versatility of our method.     

Phase relationship on Mo-S system at high temperatures

Changing the partial pressure of sulfur Ps₂ at temperatures of 750° and 950°C, phase equilibria on the Mo-S system by solid-gas reaction were investigated. Hexagonal 2H-MoS₂ and monoclinic Mo₂S₃ phases were identified from the x-ray powder diffraction pattern. The 2H-MoS₂ had a slight homogeneity range, i.e. MoS_1.978 to MoS_2.0 at 950°C, MoS_1.983 to MoS_2.0 at 750°C. No remarkable variation of lattice parameters for the MoS₂ was observed. The composition of the Mo₂S₃ phase was not stoichiometric MoS_1.5 but MoS_1.457 at 950°C. At 750°C the composition of the Mo₂S₃ phase could not be determined since it was quite difficult to establish the equilibrium state between the gas and the condensed phases. This finding agreed well with the result of Morimoto and Kullerud.     

Reaction control of TiB2 formation from titanium metal and amorphous boron

TiB₂ powder was synthesized by a controlled formation reaction from titanium metal and amorphous boron. Precursory TiB₂ formed by the pretreatment of the mixed powder (mole ratio: B/Ti=2.0) at 600° C for 60 min in an argon stream. Hollow TiB₂ powder with an average grain size of 15m was obtained by subsequent heat treatment above 900° C for more than 60 min in an argon stream. The formation reaction of TiB₂ powder was further controlled by pretreatment of the mixed powder at 600° C for 60 min in a hydrogen and argon stream and subsequent heat treatment at 1000° C for 360 min in an argon stream, when hollow-free TiB₂ powder was formed by a milder formation reaction between amorphous boron and the reformed titanium metal with hydrogen diffused lattice.     

Toward Optimal Space Partitioning for Unbiased,Adaptive Free Path Sampling of Inhomogeneous Participating Media

Photo‐realistic rendering of inhomogeneous participating media with light scattering in consideration is important in computer graphics, and is typically computed using Monte Carlo based methods. The key technique in such methods is the free path sampling, which is used for determining the distance (free path) between successive scattering events. Recently, it has been shown that efficient and unbiased free path sampling methods can be constructed based on Woodcock tracking. The key concept for improving the efficiency is to utilize space partitioning (e.g., kd‐tree or uniform grid), and a better space partitioning scheme is important for better sampling efficiency. Thus, an estimation framework for investigating the gain in sampling efficiency is important for determining how to partition the space. However, currently, there is no estimation framework that works in 3D space. In this paper, we propose a new estimation framework to overcome this problem. Using our framework, we can analytically estimate the sampling efficiency for any typical partitioned space. Conversely, we can also use this estimation framework for determining the optimal space partitioning. As an application, we show that new space partitioning schemes can be constructed using our estimation framework. Moreover, we show that the differences in the performances using different schemes can be predicted fairly well using our estimation framework.     

Image compression sensor based on column parallel architecture

We propose a novel image sensor which has compression function on its sensor plane. The image compression sensor can significantly reduce the amount of pixel data output from the sensor. The proposed sensor is intended to overcome the communication bottle neck for high pixel rate imaging such as high frame rate imaging and high resolution imaging.

The compression algorithm is based on conditional replenishment. It detects motion and encodes only the pixels in moving areas. We have been investigating pixel parallel and column parallel architectures of the image compression sensor. In this paper, we present the column parallel architecture of the proposed sensor. In this architecture, fill factor and power dissipation are comparable to conventional MOS sensors in spite of integration of the processing circuits. We have fabricated a prototype chip based on the column parallel architecture. We describe the circuit and layout design and the results of some experiments using the prototype.     

A Modeling and Rendering Method for Snow by Using Metaballs

The display of natural scenes such as mountains, trees, the earth as viewed from space, the sea, and waves have been attempted. Here a method to realistically display snow is proposed. In order to achieve this, two important elements have to be considered, namely the shape and shading model of snow, based on the physical phenomenon. In this paper, a method for displaying snow fallen onto objects, including curved surfaces and snow scattered by objects, such as skis, is proposed. Snow should be treated as particles with a density distribution since it consists of water particles, ice particles, and air molecules. In order to express the material property of snow, the phase functions of the particles must be taken into account, and it is well-known that the color of snow is white because of the multiple scattering of light. This paper describes a calculation method for light scattering due to snow particles taking into account both multiple scattering and sky light, and the modeling of snow.     

语料资源缺乏的连续语音识别方法的研究

由于少数民族语言有其本身的特点, 不能简单地套用现有的连续语音识别的方法. 本文以蒙古语为例, 研讨了声学和语言模型的建立, 并在日本国际电气通信基础技术研究所的连续语音识别器上实现了蒙古语的语音识别系统. 本文侧重于语言模型的建立, 基于蒙古语黏着性语言特点, 提出用相似词聚类方法建立多类N-gram模型. 实验结果显示, 应用我们提出的语言模型, 识别精度比用传统的词的N-gram识别法提高了5.5%.     

Visual simulation of mixed-motion avalanches with interactions between snow layers

In the field of computer graphics, simulation of fluids, including avalanches, is an important research topic. In this paper, we propose a method to simulate a kind of avalanche, mixed-motion avalanche, which is usually large and travels down the slope fast, often resulting in impressive visual effects. The mixed-motion avalanche consists of snow smokes and liquefied snow which form an upper suspension layer and a lower dense-flow layer, respectively. The mixed-motion avalanche travels down the surface of the snow-covered mountain, which is called accumulated snow layer. We simulate a mixed-motion avalanche taking into account these three snow layers. We simulate the suspension layer using a grid-based approach, the dense-flow and accumulated snow layer using a particle-based approach. An important contribution of our method is an interaction model between these snow layers that enables us to obtain the characteristic motions of avalanches, such as the generation of the snow smoke from the head of the avalanche.     

Compressive multi-spectral imaging using self-correlations of images based on hierarchical joint sparsity models

We propose a novel multi-spectral imaging method based on compressive sensing (CS). In CS theory, the enhancement of signal sparsity is important for accurate signal reconstruction. The main novelty of the proposed method is the employment of a self-correlation of an image, that is a local intensity similarity and multi-spectral correlation, to enhance the sparsity of the multi-spectral image to be recovered. Local intensity similarity, which is based on the concept that spatial changes in intensity are likely to be similar within local regions, contributes to sparsity enhancement. Furthermore, we exploit multi-spectral correlation to improve the sparsity of the multi-spectral components to be recovered. In order to simultaneously exploit different types of characteristics (i.e., local intensity similarity and multi-spectral correlation) for representing a signal as sufficiently sparse, we introduce a hierarchical joint sparsity model in the CS image recovery process. Our experiments show that the use of a self-correlation significantly improves the performance of multi-spectral image reconstruction.     

Skylight for Interior Lighting Design

It is inevitable for indoor lighting design to render a room lit by natural light, especially for an atelier or an indoor pool where there are many windows. This paper proposes a method for calculating the illuminance due to natural light, i.e. direct sunlight and skylight, passing through transparent planes such as window glass. The proposed method makes it possible to efficiently calculate such illuminance accurately, because it takes into account both non-uniform luminous intensity distribution of skylight and the distribution of transparency of glass according to incident angles of light. Several examples including the lighting design in an indoor pool, are shown to demonstrate the usefulness of the proposed method.