Wavelength Division Multiplexing (WDM) is a technology which multiplexes optical carrier signals on a single optical fiber by using different wavelengths. Lightwave networks based on WDM are promising ones for high-speed communication. If network nodes are equipped with tunable transmitters and receivers, a logical topology can be changed by reassigning wavelengths to tunable transceivers of nodes. Network performance is influenced by the logical node placements. Therefore, an efficient algorithm to obtain the optimal node placement to achieve the best network performance is necessary. In this paper, an iterated greedy algorithm is proposed for this node placement problem. The proposed iterated greedy algorithm consists of two phases, construction and destruction phases. As a local search algorithm, variable depth search is applied after the construction phase. The computational results showed that this iterated greedy algorithm outperformed the best metaheuristic algorithm for this problem.

In this paper, we proposed a method for solving the rectangle piece jigsaw puzzle assembly problem. A shape of a piece is a rectangle, and a puzzle image is RGB full color. The assembly of the puzzle is performed only using information of the pixel value on the border line of the piece. Pieces are connected by a matching function between two pieces. Not only the best matched piece is connected. The matching values to other pieces are used in the evaluation between two pieces. A simple method of puzzle assembly is that a single piece is connected to a block which is defined as a group of connected pieces. But types of piece combinations are restricted in the simple method. In the proposed method, each block is connected each other. Therefore, the best matched connection is selected from many types of combinations between pieces and blocks. The proposed method correctly assembled all pieces in 16 × 12-piece puzzles.

Taming chaos by weak harmonic perturbations has been a hot topic in recent years. This paper is the first report which clarifies the mechanism for taming chaos theoretically. The model we consider in this paper is a forced Raleigh oscillator with a diode. To simplify analyses, we consider the degenerate case where the diode in the circuit operates as a switch. In this case, the governing equation of the circuit is represented by a constrained equation and the Poincare map is derived rigorously as a one-dimensional map. By the analysis of the Poincare map, we clarify that taming chaos occurs by a saddle node bifurcation.

Various kinds of images, including bi-level documents, continuous-tone images and their compound images, are now present in a wide spectrum of digital image systems. A unified coding scheme is highly desired for such systems that deal with diversified images, and a scalable coding method is necessary for applications that exchange images between devices of different resolution or represent an image in multi-resolution levels, such as quick-look, image archiving and internet transmission. Though wavelet transforms have been proved to be a powerful analysis tool for multi-resolution image representation in scalable lossless coding, their compression performance for bi-level and compound images is not acceptable. However any discrete wavelet transform or two band sub-bandfiltering with finite filters can be decomposed into simple lifting filtering steps so that inverse transform can be easily constructed. In this paper by referencing the already transmitted low-pass band signals in each lifting step, we show how a proper filter is selected in each step to let the wavelet transform adaptive to different kinds of images. Furthermore, in the proposed adaptive wavelet transform, a proper mapping of the coefficients is employed so that bi-level document regions in a compound image can be transmitted prior to multi-level regions. Simulation results also show that the proposed scheme has high compression ratio for both bi-level and multi-level images.

In this paper, we propose a method of the model-based pose estimation in the 3D world from a 2D image. This process consists in searching for the best value of coordinates (x, y, z) and of rotating angles (/spl theta//sub x/, /spl theta//sub y/, /spl theta//sub z/) in which the model object matches most exactly the given input edge image. Taking the match of objects as an index on the six-parameter space, this process can be regarded as a maximum searching problem. We use a genetic algorithm in the estimation of those parameters, and propose a new concept of fitness which takes edge direction into consideration. Our experiments show the results of the proposed method on edge input images.

This paper presents a study on automatic diagnosis of pneumoconiosis by texture analysis of chest X-ray images. A pre-processing method for normalizing distribution of film density is proposed and its effectiveness is studied experimentally. Dominant causes of the deviations of texture features for evaluating the profusion of small opacities are excluded by the pre-processing. New texture features based on the distribution of gradient vectors are also proposed. Experiments to evaluate the proposed system are demonstrated.