Magnetoencephalography (MEG) is a powerful and non-invasive technique for measuring human brain activity with a high temporal resolution. The motivation for studying MEG data analysis is to extract the essential features from measured data and represent them corresponding to the human brain functions. In this paper, a novel MEG data analysis method based on independent component analysis (ICA) approach with pre-processing and post-processing multistage procedures is proposed. Moreover, several kinds of ICA algorithms are investigated for analyzing MEG single-trial data which is recorded in the experiment of phantom. The analyzed results are presented to illustrate the effectiveness and high performance both in source decomposition by ICA approaches and source localization by equivalent current dipoles fitting method.

This paper presents a three-dimensional polarimetric detection result of targets buried in snowpack by synthetic aperture FM-CW radar system. Since the FM-CW radar is suitable for short range sensing and can be equipped with fully polarimetric capability, we further extended it to a polarimetric three-dimensional SAR system. A field experiment was carried out to image and detect targets in a natural snowpack of 280 cm deep. The polarimetric detection and identification schemes are the polarimetric filtering, three-component decomposition, and the power polarization anisotropy coefficient. These approaches to acquired data show the usefulness of three-dimensional polarimetric FM-CW SAR system.

The blind separation of sources is a recent and important problem in signal processing. Since 1984, it has been studied by many authors whilst many algorithms have been proposed. In this paper, the description of the problem, its assumptions, its currently applications and some algorithms and ideas are discussed.

Patterns exist in many contexts and can be considered the useful information for decision making. However, many patterns are not directly visible without careful presentation. Here, we describe an interactive visualization approach for browsing patterns in a history of interacting with a computer system. While a user is carrying out his/her business using computers, activities with respect to time and location are captured to determine the situational interactions. We first integrate the timeline and geographical map to create a structure to visualize spatiotemporal events in the interaction history. The spiral-based interactive visualization technique, presented in this paper, is then used to derive patterns according to the user-specified different spatial viewpoints on the map. In this study, we demonstrate how patterns can be used as visual statements for the analysis of a spatiotemporal data set in the information visualization.

A novel method is proposed to retrieve image sequences with the goal of forecasting complex and time-varying natural patterns. To that end, we introduce a framework called Memory-Based Forecasting; it provides forecast information based on the temporal development of past retrieved sequences. This paper targets the radar echo patterns in weather radar images, and aims to realize an image retrieval method that supports weather forecasters in predicting local precipitation. To characterize the radar echo patterns, an appearance-based representation of the echo pattern, and its velocity field are employed. Temporal texture features are introduced to represent local pattern features including non-rigid complex motion. Furthermore, the temporal development of a sequence is represented as paths in eigenspaces of the image features, and a normalized distance between two sequences in the eigenspace is proposed as a dissimilarity measure that is used in retrieving similar sequences. Several experiments confirm the good performance of the proposed retrieval scheme, and indicate the predictability of the image sequence.

Thin films of carbon (C)-sulfur (S) compound were formed by plasma CVD (PCVD) at the special chemical condition. The reactor has a parallel plate electrode system and was operated at a discharge frequency of 13.56 MHz with using a mixture gas of argon (Ar), methane (CH4) and SF6. The deposition was performed on a substrate placed on the grounded electrode. Atomic composition of the film was observed to depend on the gas mixture ratio. The sulfur atom density was increased up to 30% with using a mixture gas at a pressure of 0.1 Torr and at a flow rate of 20, 20 and 50 SCCM for Ar, CH4 and SF6, respectively. It was expected that the C-S compounds were deposited under the condition of F atom elimination by forming HF.

This paper theoretically analyzed the performance of the RAKE combining (in the time domain), maximal ratio combining (in the spatial domain), and two-dimensional RAKE combining (in the spatial and time domains) techniques for multipath fading environments, where multipath waves are distributed in the spatial and time domains. The analysis was based on a diversity combining technique that employed the eigenvalues of the covariance matrix between branch signals. It was found that the performance of the fading mitigation was normalized by the beamwidth of an array antenna, for various parameters such as the number of antenna elements, angular spread, and angle of arrival.

Saltiness elicited by salt is one of the basic tastes. However, components of salt on the market differ depending on manufacturing processes and its taste as well. Salt manufactured by ion-exchange membrane process is composed of more than 99% pure sodium chloride, while bay salt contains trace coexisting components. Despite reports on sensory evaluation, the differences in taste are still uncertain because of a small amount of coexisting components. We studied the taste of salt with trace coexisting components; the bittern ("nigari" in Japanese) was evaluated objectively and quantitatively using a multichannel taste sensor with lipid/polymer membranes. A taste sensor is comprised of several types of lipid/polymer membranes for transforming information of taste substances into electric signals. The model samples were composed of sodium chloride and trace coexisting components such as magnesium sulfate, magnesium chloride, calcium chloride and sodium chloride. The taste sensor clearly discriminated each sample according to the response patterns. Based on the sensor outputs, we evaluated the taste by means of the combination of principal component analysis and ionic strength. The results show the taste of salt with nigari has a correlation with ionic strength.

Reconfiguration of memory arrays using spare lines is known to be an NP-complete problem. In this paper, we present an algorithm that reconfigures a memory array without any faults by using spare lines effectively even if they contain faulty elements. First, the reconfiguration problem is transformed to an equivalent covering problem in which faulty elements are covered by imaginary fault-free spare lines. Next, the covering problem is heuristically solved by using the Dulmange-Mendelsohn decomposition. The experiments for recently designed memory arrays show that the proposed algorithm is fast and practical.

This paper proposes a model checking method for microcomputer programs. To deal with the state explosion problem, we adopt a compositional verification approach. Based on the proposed method, a microcomputer program for a real-life air-conditioner is verified. The program is large enough to cause state explosion. Among fourteen typical properties of the program, five properties are successfully verified by our method.

Software Composition is one of the major concerns in component based software development (CBSD). In this paper, we present a formal approach to construct software systems from requirements models using available components. We focus on the knowledge resides in the requirements and the components in order to deal with those heterogeneous concepts. This approach consists of three steps. The first step is selecting adaptable components to the requirements model. The requirements and the components are transformed into the form of Σ algebra, and the component adaptability is evaluated by Σ homomorphism. Rough Set Theory (RST) is used to make carriers of two Σ algebras common, which are derived from the requirements and the components. The second step is identifying the control structure of the requirements. Decision tables are used for representing the knowledge on the requirements, and RST is used to optimize the control structure. The third step is to implement the control structure as glue codes which would perform the components appropriately. This approach mainly focuses on enterprise back-office applications in this paper, however, it can be easily applied to other domains, since it assumes the requirements to be expressed in Colored Petri Nets (CPN), and CPN can express various problem domains other than enterprise back-office applications.

This paper presents an object-oriented model to handle the temporal relationship for all of the multimedia objects at the presentation platform. Synchronization of the composite media objects is achieved by ensuring that all objects presented in the upcoming "manageable" period must be ready for execution. To this end, the nature of overlays is first investigated for various types of objects. Critical overlaps which are crucial in synchronization are also defined. The objective of synchronization is to ensure that the media objects can be initiated precisely at the critical point of the corresponding critical overlap. The concept of manageable presentation interval is introduced and the irreducible media group is defined. The resource scheduling of each presentation group for media object pre-fetch time versus buffer occupancy is also examined. Accordingly, a new model called group cascade object composition Petri-net (GCOCPN) is proposed and an algorithm to implement this temporal synchronization scheme is presented.

This work presents a scalable and high performance prediction protocol for optical networks. In the proposed protocol, we develop a mathematical model to maintain the stability of a network system by prediction based on the traffic temporal locality property. All the critical factors, including transceiver tuning time, propagation delay, and processing time for dealing with control packets, are considered in the proposed prediction protocol. Furthermore, our protocol can resolve the bottlenecks attributed to control signaling and electronics processing. The performance evaluation reveals that the proposed scheme can yield the higher bandwidth efficiency and incur a lower packet delay than those of the TDM and conventional reservation schemes. Also, the proposed protocol can flexibly support any scaled network system such as MANs or LANs.

The construction of photo-realistic 3D scenes from video data is an active and competitive area of research in the fields of computer vision, image processing and computer graphics. In this paper we address our recent work in this area. Unlike most methods of 3D scene construction, we consider the generation of virtual environments from video sequence with a video-cam's forward motion. Each frame is decomposed into sub-images, which are registered correspondingly using the Levenberg-Marquardt iterative algorithm to estimate motion parameters. The registered sub-images are correspondingly pasted together to form a pseudo-3D space. By controlling the position and direction, the virtual camera can walk through this virtual space to generate novel 2D views to acquire an immersive impression. Even if the virtual camera goes deep into this virtual environment, it can still obtain a novel view while maintaining relatively high resolution.

A nonlinear multiple complex sinusoidal estimator (NMSE) is proposed, as an extended and improved version with system noise of the single sinusoidal estimator previously presented by the author, for extracting multiple complex sinusoids in white noise. This estimator is derived by applying an extended complex Kalman filter (ECKF) to a noisy multiple complex sinusoidal model with state-representation, where the model becomes a nonlinear stochastic system. Proof of the stability is given by using a structure of the state-space signal model and Lyapunov techniques. Also, computer simulations demonstrate the effectiveness of the NMSE from various points of view.

This paper describes how voltage fluctuation in the DC power supply of a digital IC can be reduced, by means of molding the package-pin in a ferrite-resin composite. The voltage fluctuation of the DC power supply, when the input terminal was driven by a 40 MHz, 5 Vp-p pulse wave, was measured using an oscilloscope. Simultaneously, the voltage spectrum of the fluctuation was measured using a spectrum analyzer. As a result, the voltage fluctuation was decreased by about 50 % when the IC package-pins were molded in a ferrite-resin composite, in which the µiac of the ferrite powder equalled 100, and the powder content was 80 weight-%. In the same IC, there was the reduction effect of the voltage spectrum of the fluctuation was recognized in the frequency range 40 MHz to 1 GHz.

An ATMS (Assumption-based Truth Maintenance System) has been widely used for maintaining the truth of an information by detecting and solving the contradictions in rule-based systems. However, the ATMS cannot correctly maintain the truth of the information in case that the generated information is satisfied within a time interval or includes data about temporal relations of events in time varying situations, because it has no mechanism manipulating temporal data. In this paper, we propose the extended ATMS that can maintain the truth of the information in the knowledge-based system using information changing over time or temporal relations of events. To maintain the contexts generated by relations of events, we modify the label representation method, the disjunction and conjunction simplification method in the label-propagation procedure and the nogood handling method of the conventional ATMS.

Causal message logging has many benefits such as nonblocking message logging and no rollback propagation. In this paper, we consider the problem of the recovery in causally-logged distributed system and give a condition for consistent recovery. We then show that, based on the impossibility of the consensus, the consistent causal recovery cannot be solved in asynchronous systems.

The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.

A data-parallel processing approach is promising for real-time volume rendering because of the massive parallelism in volume rendering. In data-parallel volume rendering, local results processing elements(PEs) generate from allocated subvolumes are integrated to form a final image. Generally, the integration causes an overhead unavoidable in data-parallel volume rendering due to communications among PEs. This paper proposes a data-parallel shear-warp volume rendering algorithm combined with an adaptive volume subdivision method to reduce the communication overhead and improve processing efficiency. We implement the parallel algorithm on a message-passing multiprocessor system for performance evaluation. The experimental results show that the adaptive volume subdivision method can reduce the overhead and achieve higher efficiency compared with a conventional slab subdivision method.