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.     

A new optical elasticity resin for mobile LCD modules

Abstract— The display used in current cell phones has an air gap between the cover glass and the liquid‐crystal‐display (LCD) module to prevent the LCD glass from being damaged. Reflections at the boundaries of the air gap cause a reduction in the LCD luminance and contrast. To address this problem, a newly proposed LCD structure has been investigated. The “Super View Resin (SVR),” a transparent elastic resin which improves the shock resistance and visibility of the LCD, has been developed. Filling the air gap between the cover glass and LCD module with a refractive‐index‐matching resin solves the light‐reflection problem inherent in the use of a reinforced cover‐glass lens. Moreover, the elastic filler works as a damper, reducing any external shock, which prevents not only the cover glass and LCD module from being damaged, but also the glass from being shattered when it is broken.     

Superconductivity in the tetragonal phase of La1.9Bi0.1CuO4+δ annealed under high oxygen pressure

We have investigated the relation between the crystal structure and superconductivity in La_1.9Bi_0.1CuO₄₊ , in which the phase separation observed in La₂CuO₄₊ is suppressed. A phase diagram in theT– plane is given for La_1.9Bi_0.1CuO₄₊ with excess oxygen. For very small values, the crystal structure is orthorhombic, and an orthorhombic-tetragonal phase transition occurs markedly at 0.03 in the measured temperature range between 13 and 293 K. Superconductivity is observed in the range of 0.04<<0.11. This is clear evidence thathigh-T _c superconductivity also appears in the tetragonal phase.     

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.     

Theory of one-tape linear-time Turing machines

A theory of one-tape two-way one-head off-line linear-time Turing machines is essentially different from its polynomial-time counterpart since these machines are closely related to finite state automata. This paper discusses structural-complexity issues of one-tape Turing machines of various types (deterministic, nondeterministic, reversible, alternating, probabilistic, counting, and quantum Turing machines) that halt in linear time, where the running time of a machine is defined as the length of any longest computation path. We explore structural properties of one-tape linear-time Turing machines and clarify how the machines’ resources affect their computational patterns and power.     

Implementation of a decision support system using an interactive large-scale high-resolution display

In this research, we propose and evaluate a decision support system using an interactive large-scale high-resolution display. This decision support system supports the summarization and decision-making of a large amount of disaster information during the occurrence of a large-scale natural disaster. Municipal employees at the disaster control headquarters can display disaster information on the large-scale display with a touch or flick on a laptop or tablet. To evaluate the operability, readability, functionality, and necessity of the decision support system, we surveyed 23 municipal employees in the disaster prevention division using a questionnaire. The system received a great evaluation in all the evaluation items.     

Automatic transaction of signal via statistical modeling

The statistical information processing can be characterized by the likelihood function defined by giving an explicit form for an approximation to the true distribution. This mathematical representation, which is usually called a model, is built based on not only the current data but also prior knowledge on the object and the objective of the analysis. Akaike^2,3) showed that the log-likelihood can be considered as an estimate of the Kullback-Leibler (K-L) information which measures the similarity between the predictive distribution of the model and the true distribution. Akaike information criterion (AIC) is an estimate of the K-L information and makes it possible to evaluate and compare the goodness of many models objectively. In consequence, the minimum AIC procedure allows us to develop automatic modeling and signal extraction procedures. In this article, we give a simple explanation of statistical modeling based on the AIC and demonstrate four examples of applying the minimum AIC procedure to an automatic transaction of signals observed in the earth sciences. Genshiro, Kitagawa, Ph.D.: He is a Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He is currently Deputy Director of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University for Advanced Study. He obtained his Ph.D. from the Kyushu University in 1983. His primary research interests are in time series analysis, non-Gaussian nonlinear filtering, and statistical modeling. He has published over 50 research papers. He was awarded the 2nd Japan Statistical Society Prize in 1997. Tomoyuki Higuchi, Ph.D.: He is an Associate Professor in the Department of Prediction and Control at the Institute of Statistical Mathematics. He is currently an Associate Professor of Statistical Science at the Graduate University for Advanced Study. He obtained his Ph.D. from the University of Tokyo in 1989. His research interests are in statistical modeling of space-time data, stochastic optimization techniques, and data mining. He has published over 30 research papers.