Smoothness prior approach to explore mean structure in large-scale time series
This article is addressed to the problem of modeling and exploring mean value structure of large-scale time series data and time-space data. A smoothness prior modeling approach (Smoothness Prior Analysis of Time Series, ) is taken. In this approach, the observed series are decomposed into several components each of which are expressed by smoothness priors models. In the analysis of POS and GPS data, various useful information were extracted by this decomposition, and result in discoveries in these areas.

title: Automatic Transaction of Signal via Statistical Modeling
abstract: The statistical information processing can be characterized by using the likelihood function defined by giving an explicit form for an approximation to the true distribution from which the data are generated. This mathematical representation as an approximation, 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 ( and ) showed that the log-likelihood can be considered as an estimate of the Kullback-Leibler information which defines the similarity between the predictive distribution of the model and the true distribution and proposed the Akaike information criterion (AIC). By the use of this AIC, it becomes possible to evaluate and compare the goodness of many models objectively and it enables us to select the best model among many candidates. In consequence, the minimum AIC procedure allows us to develop automatic modeling and signal extraction procedures. In this study, 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. In each case, the AIC plays an important role in making the procedure automatic and objective, and promises to realize a detail examination of a large amount of data sets, which provides us with an opportunity to discover new information.

title: Detection of the Structure of Particle Velocity Distribution by Finite Mixture Distribution Model
abstract: From direct satellite observations of space plasma, we have obtained many significant results by means of velocity moments of particle velocity distribution functions (e.g. number density, bulk velocity and temperature). This fluid description assumes that the plasma is able to maintain local thermal equilibria. When plasma is in a state of thermal equilibrium, a distribution function of particle velocity is given as a normal distribution which is called Maxwellian in a field of the plasma physics. In the meantime, observational techniques has progressed notably and has made it possible to measure more detailed shape of distribution function in the three-dimensional velocity space. Those observations revealed that there are many cases where space plasmas have not reached a state of thermal equilibrium and their velocity distributions are not a single Maxwellian but consist of multiple peaks. This distribution may occur since space plasma such as in the solar wind is basically collisionless with large mean-free-path (about 1 AU). It may give the same velocity moments even if the shapes of distribution functions are different. For instance, when the plasma with two beam components whose velocity vectors are sunward and anti-sunward, respectively, and the numbers of particles composing each component are the same, bulk velocity would become zero from calculation. On the other hand, when stagnant plasma are observed, bulk velocity would also become zero. In the two-beam case, it would be necessary to separate into two beams and calculate the velocity moments for each beam. It has been difficult, however, to evaluate the shape of distribution function especially when more than one components partially overlap each other. It produces a serious problem especially when we treat many multi-component cases statistically. In this paper, we construct a method of representing three-dimensional distribution function by finite mixture distribution model in which the parameter values are obtained by EM (Expectation-Maximization) algorithm[1]. With this method, we can express the shape of the function and find a possible way to conduct a statistical analysis.

title: Estimating Gene Networks with cDNA Microarray Data Using State-Space Models
abstract: State-space model is used in this paper to analyze dynamics of gene expression profile data. State-space models describe dynamics that the observed measurements depend on some hidden state variables. Hidden state variables can capture effects that cannot be measured in gene expression profiling experiment, for example, genes that have not been included in the observation variables, levels of regulatory proteins or the effect of mRNA. System identification is achieved by EM algorithm that is based on the maximum likelihood method. We apply this method to a published yeast cell-cycle gene expression time-series data under the assumption that state variables and observation variables are generated by Gaussian white noise process, that produces the simplest and most reasonable model to explain of behaviors of the gene expression profiles.

title: Smoothness Prior Approach to Explore the Mean Structure in Large Time Series Data
abstract: This article is addressed to the problem of modeling and exploring time series with mean value structure of large scale time series data and time-space data. A smoothness priors modeling approach [11] is taken and applied to POS and GPS data. In this approach, the observed series are decomposed into several components each of which are expressed by smoothness priors models. In the analysis of POS and GPS data, various useful information were extracted by this decomposition, and result in some discoveries in these areas.

title: Separation of Photoelectrons via Multivariate Maxwellian Mixture Model
abstract: Electron velocity distribution obtained by direct spacecraft observation in space is contaminated by photoelectrons. The photoelectrons are generated due to the solar ultraviolet ray, and are regarded as artificial noise from a viewpoint of scientific research. We propose a method for separating photoelectron component from ambient electron component. Our method uses multivariate normal mixture model, whose parameters are determined via the Expectation-Maximization (EM) algorithm. Initial parameters of the EM algorithm are computed through the classification of the velocity space by a spherical surface of some arbitrary radius.

title: Pick and Place of Hard Disk Media using Electrostatic Levitation
abstract: This paper focuses on a practical application of handling contact sensitive objects such as silicon wafers or hard disk media without any contact using electrostatic levitation. Stable electrostatic levitation can be realized by controlling an electrostatic force on the basis of measured suspension air gaps. Two control approaches, namely centralized and decentralized control and the influence of an integrator in the controller, are discussed with regard to the specific tasks of Pick Up and Place. The final goal is to realize a handling tool that allows human operators to perform these object handling tasks. In this paper a linear motor is used to perform the pick up and place task to allow a controllable and reproducible motion. The experimental results show a stable pick up and place motion, where placing is realized without any external control commands.

title: Electrostatic tactile display with thin film slider and its application to tactile telepresentation systems
abstract: A new electrostatic tactile display is proposed to realize compact tactile display devices that can be incorporated with virtual reality systems. The tactile display of this study consists of a thin conductive film slider with stator electrodes that excite electrostatic forces. Users of the device experience tactile texture sensations by moving the slider with their fingers. The display operates by applying two-phase cyclic voltage patterns to the electrodes. The display is incorporated into a tactile telepresentation system to realize explorations of remote surface textures with real-time tactile feedback. In the system, a PVDF tactile sensor and a DSP controller automatically generate voltage patterns to present surface texture sensations through the tactile display. A sensor, in synchronization with finger motion on the tactile display, scans a texture sample and outputs information about the sample surface. The information is processed by a DSP and fed back to the tactile display in real time. The tactile telepresentation system was evaluated in texture discrimination tests and demonstrated a 79 percent correct answer ratio. A transparent electrostatic tactile display is also reported in which the tactile display is combined with an LCD to realize a visual-tactile integrated display system.

title: Surface Acoustic Wave (SAW) tactile display based on properties of mechanoreceptors
abstract: The authors first analyze dynamic properties of rapidly adapting mechanoreceptors in order to derive a principle of tactile displays. It is shown that Meissner corpuscles with coiled axons and Pacinian corpuscles with layered lamellae are suited to detect equivoluminal distortion of skin. Combining these analyses with a model of a contact and a relative motion between an object and the skin, it is shown that a prerequisite for tactile displays is to generate sources of shear stress that can be spatially dispersed at the skin surface and temporally modulated with a stick-slip frequency determined by parameters of the object to be displayed. As a device that satisfies this prerequisite, we propose a tactile display using Surface Acoustic Waves (SAW). The roughness of the surface can be changed continuously by controlling the burst frequency of the SAW.

title: Evaluation of an Electrostatic Film Motor Driven by Two-Four-Phase AC Voltage and Electrostatic Induction
abstract: This paper describes a voltage-induction type electrostatic film motor that operates by feeding electric power to the slider by electrostatic induction. In electrostatic film motors, feeding power to slider is important for better output capability and positioning performance. However, the power feeding using electric cables sometimes cause mechanical disturbance to the motor motions. In the new electrostatic motor, the power to the slider is fed by electrostatic induction, thus removing electric cables that can cause mechanical disturbances. The proposed motor has a two-phase electrode in the slider and a four-phase electrode in the stator. In addition, both stator and slider have the induction electrodes so that electric power is transferred to the slider through the induction electrodes. The paper first analyzes the thrust force characteristics of the proposed driving-electrode configuration, and then analyzes the characteristics of voltage induction, both based on capacitance-network analysis. The analyzed result is verified by experiments that showed good agreements with the provided analysis

title: Design and Control of a Fish-like Robot Using an Electrostatic Motor
abstract: This paper presents a project that aims at constructing a biologically inspired fish-like robot. The robot is designed to be capable of propelling itself through oscillations of a flexible caudal fin, like a real underwater fish. In particular, the caudal fin is driven by a mechanism actuated by a unique actuator called electrostatic film motor. In this paper, the dynamics of the electrostatic film motor are briefly introduced so as to well understand its characteristics and behavior. Based on the theoretical analysis and several design considerations inspired by biological concepts, we realize the fish-like robot actuated by an electrostatic film motor and propose swimming control methods for it. Experiments are carried out to confirm the validity of the original design and control. The current robot achieves fish-like maneuvering and approximate velocity of 0.018 m/s in dielectric liquid.