In this paper, we propose an extension of finite state tree automaton, called tree automaton with tree memory (TTA), and also define structure composing TTA (SC-TTA) and backward deterministic TTA (BD-TTA) as subclasses of TTA. We show that the classes of yield languages accepted by TTAs, SC-TTAs and BD-TTAs are equal to the class of recursively enumerable languages, the class of languages generated by tree-to-string finite state translation systems (TSFSTSs) and the class of languages generated by deterministic TSFSTSs, respectively. As a corollary, it is shown that the yield language accepted by an SC-TTA (resp. a BD-TTA) is linear space (resp. polynomial time) recognizable.

Requirements engineering refers to activities of gathering and organizing customer requirements and system specifications, making explicit representations of them, and making sure that they are valid and accounted for during the course of the design lifecycle of software. One very popular software development practice is the incremental development practice. The incremental development refers to practices that allow a program, or similarly specifications, to be developed, validated, and delivered in stages. The incremental practice is characterized by its depth-first process where focuses are given to small parts of the system in sequence to fair amounts of detail. In this paper, we present a development and validation of specifications in such an incremental style using a tool called ASADAL, a comprehensive CASE tool for real-time systems. ASADAL supports incremental and hierarchical refinements of specifications using multiple representational constructs and the evolving incomplete specifications can be formally tested with respect to critical real time properties or be simulated to determine whether the specifications capture the intended system behavior. In particular, we highlight features of ASADAL's specification simulator, called ASADAL/SIM, that plays a critical role in the incremental validation and helps users gain insights into the validity of evolving specifications. Such features include the multiple and mixed level simulation, real-value simulation, presentation and analysis of simulation data, and variety of flexible simulation control schemes. We illustrate the overall process using an example of an incremental specification development of an elevator control system.

When a set of objects is shared among several applications, multiple implementations for the set are required in order to suit each application as much as possible. Furthermore, if a set of objects could have multiple implementations, the following issues arise: (1) how to select the best implementation when processing queries on the set, and (2) how to propagate updates on an implementation of the set to the others. In this paper we propose a mechanism of multiple implementations for a set, and also give a solution for the latter issue. In the proposal a set can be of multiple types, and each of the types corresponds to an implementation already contained within the set. Update propagation can be achieved by a rewriting technique at compilation time. We also present a performance study in which the feasibility and effectiveness of our proposal were examined.

In this papers, we will discuss the different percentages of embedding certain subsystems successfully into a n-cube according to the fault model used. We will discuss two fault models: the first one assumes that, in a faulty node, the computational function of the node is lost while the communication function of the faulty node remains intact, and, in the second, the communication function is also lost. In this paper, 2 types of fault tolerable subsystem embedding schemes will be introduced. The first one embeds a complete binary tree into a n-cube with faulty nodes, and the second embeds two (n-1)-subcubes whose total number of faulty nodes is less than half the number of nodes. These schemes are divided into 4 types based on the above two models. First, we will discuss how different the successful percentages of embedding are for 2 of the different types of embedded binary trees that are based on the above two models. Then, we will analyze the possibility that the component nodes of an embedded binary tree can communicate via the faulty nodes that are located in the embedded binary tree. In the embedding process, each faulty node was replaced with a nonfaulty node that was located on another (n-1)-subcube and at a Hamming distance of 1 from the faulty node. The number of faults that led to the successful percentage of embedding will be presented as an upper bound. Next, we will discuss how different the successful embedding percentages are for the 2 types of irregular (n-1)-subcubes based on the two models; that is, if 2^n-2+1 or more of the nonfaulty nodes in both of the (n-1)-subcubes can communicate or not via faulty nodes. Here also, the number of faults that led to a successful embedding percentage will be presented as a critical value.

A field theory for geometrical pattern identification is developed based on the postulate that various modified patterns are identified via invariant characteristics of pattern transformations. The invariant characteristics of geometrical patterns are written as the functional of the light intensity distribution of pattern, its spatial gradient, and also its spatial curvature. Some definite expressions of the invariant characteristic functional for two dimensional linear transformation are derived, and their invariant and feature extracting property are examined numerically. It is also shown that the invariant property is conserved even when patterns are deformed locally by introducing a "gauge field" as new degree of freedom in the functional in form of a covariant derivative. Based on this idea, we discuss a field theoretical model for pattern identification performed in biological systems.

This paper presents a new scheme to estimate depth in a natural three-dimensional scene using a multi-viewpoint image set. In the conventional Multiple-Baseline Stereo (MBS) scheme for the image set, although errors of stereo matching are somewhat reduced by using multiple stereo pairs, the use of square blocks of fixed size sometimes causes false matching, especially, in that image area where occlusion occurs and that image area of small variance of brightness levels. In the proposed scheme, the reference image is segmented into regions which are capable of being arbitrarily shaped, and a depth value is estimated for each region. Also, by comparing the image generated by projection with the original image, depth values are newly estimated in a top-down manner. Then, the error of the previous depth value is detected, and it is corrected. The results of experiments show advantages of the proposed scheme over the MBS scheme.

In this paper, we develop a novel method for tuning parameters known as the sensitivity parameters of membership functions used in a fuzzy classifier. The proposed method performs tuning by solving a set of inequalities. Each inequality represents a range of the ratio of the sensitivity parameters between the corresponding pair of classes. The range ensures the maximum classification rate for data of the two corresponding classes used for tuning. First, we discuss how such a set of inequalities is derived. We then propose an algorithm to solve the derived set of inequalities. We demonstrate the effectiveness of the proposed tuning method using two classification problems, namely, classification of commonly used iris data, and recognition of vehicle licence plates. The results are compared with those obtained by using the existing tuning method and with those by neural networks.

This correspondence reports novel computationally efficient algorithms for multiplication of bicomplex numbers, which belong to hypercomplex numbers. The proposed algorithms require less number of real multiplications than existing methods. Furthermore, they give more effective implementation when applied to constant coefficient digital filters.

A method for generating circles and arcs is the general class of algorithms known as digital differential analyzers (DDA). However, there are some defects in the DDA algorithms. In this paper, a discrete form of the equation of a circle is revised and the defects in the DDA are removed.

We show that moving objects can be detected from optical flow without using any knowledge about the magnitude of the noise in the flow or any thresholds to be adjusted empirically. The underlying principle is viewing a particular interpretation about the flow as a geometric model and comparing the relative "goodness" of candidate models measured by the geometric AIC.

We implement a graphical interface that automatically transforms a figure input by a mouse into a regular figure which the system infers is the closest to the input. The difficulty lies in the fact that the classes into which the input is to be classified have inclusion relations, which prohibit us from using a simple distance criterion. In this letter, we show that this problem can be resolved by introducing the geometric AIC.