Recently, several promising multiobjective evolutionary algorithms such as PESA, NSGA-II, and SPEA2 have been developed. In this paper, we also propose a new multiobjective evolutionary algorithm whose performance is comparable to or better than those promising algorithms. In the new algorithm proposed here, an age concept is introduced and utilized to make the efficiency of the offspring generation high. The performance of the proposed algorithm is superior to those of the promising algorithms mentioned above for several test functions. In this paper, the proposed algorithm will be explained only in two dimensional parameter and objective space to show manifestly the meaning of an age concept.

In recent years, information devices with network communication ability have become very popular, and many people actually own such kind of devices. Those information devices, however, do not share users' data in spite of their communication ability. This paper proposes "OCEAN: Object Communication Environment for Arbitrary Network" architecture, which provides liaison of objects stored in each device according to their profiles and situations. It eliminates redundant user operation on information devices, and enables novel communication scheme among users by sharing common objects in those devices. Furthermore, it maximizes the effective use of each device's limitation according to each environment. Finally, in this paper, we discuss our prototype of OCEAN.

This paper concerns recognizing 3-dimensional object using proposed multi-layer block model. In particular, we aim to achieve desirable recognition performance while restricting the computational load to a low level using 3-step feature extraction procedure. An input image is first precisely partitioned into hierarchical layers of blocks in the form of base blocks and overlapping blocks. The hierarchical blocks are merged into a matrix, with which abundant local feature information can be obtained. The local features extracted are then employed by the kernel based support vector machines in tournament for enhanced system recognition performance while keeping it to low dimensional feature space. The simulation results show that the proposed feature extraction method reduces the computational load by over 80% and preserves the stable recognition rate from varying illumination and noise conditions.

We describe in this paper our experience of developing a large-scale, highly distributed multi-agent system using wireless-networked sensors. We provide solutions to the problems of localization (position estimation) and dynamic, real-time mobile object tracking, which we call PET problems for short, using wireless sensor networks. We propose system architectures and a set of distributed algorithms for organizing and scheduling cooperative computation in distributed environments, as well as distributed algorithms for localization and real-time object tracking. Based on these distributed algorithms, we develop and implement a hardware system and software simulator for the PET problems. Finally, we present some experimental results on distance measurement accuracy using radio signal strengths of the wireless sensors and discuss future work.

This paper first presents robust algorithms to extract invariants of the linear Lie algebra model from 3D objects. In particular, an extended 3D Hough transform is presented to extract accurate estimates of the normal vectors. The Least square fitting is used to find normal vectors and representation matrices. Then an algorithm of segmentation for 3D objects is shown using the invariants of the linear Lie algebra. Distributions of invariants, both in the invariant space and on the object surface, are used for clustering and edge detection.

Software with design flaws increases maintenance costs, decreases component reuse, and reduces software life. Even well-designed software tends to deteriorate with time as it undergoes maintenance. Work on restructuring object-oriented designs involves estimating the quality of the designs using metrics, and automating transformations that preserve the behavior of the designs. However, these factors have been treated almost independently of each other. A long-term goal is to define transformations preserving the behavior of object-oriented designs, and automate the transformations using metrics. In this paper, we describe a genetic algorithm based restructuring approach using metrics to automatically modify object-oriented designs. Cohesion and coupling metrics based on abstract models are defined to quantify designs and provide criteria for comparing alternative designs. The abstract models include a call-use graph and a class-association graph that represent methods, attributes, classes, and their relationships. The metrics include cohesion, inheritance coupling, and interaction coupling based on the behavioral similarity between methods extracted from the models. We define restructuring operations, and show that the operations preserve the behavior of object-oriented designs. We also devise a fitness function using cohesion and coupling metrics, and automatically restructure object-oriented designs by applying a genetic algorithm using the fitness function.

Properly representation of the complexity of class structure will be useful in object oriented software developments. Although some class complexity metrics have been proposed, they have ignored directions of coupling relationships among methods and attributes, such as whether a method writes data onto an attribute or reads data from the attribute. In this paper, we use a directed graph model to represent such coupling relationships. Based on the directed graph model, we propose a metric of class structural complexity. The proposed metric satisfies necessary conditions of complexity metric suggested by Briand and others. The following fact is showed by experimental data of Java classes. While the proposed metric follows a conventional metric, the proposed metric can capture an aspect of class structural complexity which is lost by the conventional one.

This paper describes glyph representation, that is, shape representation of inheritance relationships between a superclass and subclasses in an object-oriented programming language. The inheritance relationships in object-oriented programming languages are usually represented in a visual programming environment by a diagram of a tree graph or a nested structure. That diagram is not integrated with a code view showing control and data flows. Using the proposed representation, one can understand the inheritance relationships of classes and the assignment compatibility or type conformance just by seeing the glyphs. One thus does not need to look at a hierarchy diagram in order to recognize them. The inheritance relationships are represented by inclusion relationships of glyphs. Methods for generating suitable glyphs from a class hierarchy are also described, as is a prototype system for glyph generation. Experiments using the Java 2 Standard Edition (J2SE), which has more than 1,500 classes, show that one can recognize inheritance relationships in the proposed representation faster than in the usual textual representation. Consequently the proposed representation can facilitate the understanding of inheritance in visual object-oriented programming environments.

In this paper we discuss the estimation of effort needed to update program codes according to given design specification changes. In the Object-Oriented incremental development (OOID), the requirement changes occur frequently and regularly. When a requirement change occurs, a design specification is changed accordingly. Then a program code is updated for given design specification change. In order to construct the development plan dynamically, a simple and fast estimation method of efforts for code updating is strongly required by both developers and managers. However, existing estimation methods cannot be applied to the OOID. We therefore try to propose a straightforward approach to estimate effort for code updating, which reflects the specific properties of the OOID. We list up following factors of the effort estimation for OOID: (1) updating activities consist of creation, deletion, and modification, (2) the target to be updated has four kinds of types (void type, basic type, library type, and custom type), (3) the degree of information hiding is classified into private, protected and public, and (4) the degree of inheritance affects updating efforts. We then propose a new formula E(P,σ) to calculate the efforts needed to update a program P according to a set of design specification changes σ. The formula E(P,σ) includes weighting parameters: Wupd, Wtype, Winf-h and Winht according to the characteristics (1), (2), (3) and (4), respectively. Finally, we conduct experimental evaluations by applying the formula E(P,σ) to actual project data in a certain company. The evaluation results statistically showed the validity of the proposed approach to some extent.

This paper addresses the problem to extract moving object from the moving background in the mixed domain (MixeD), which makes it possible to carry the filtering in one dimension. Since the velocities of moving object and background are necessary for moving object extraction, we first estimate the velocities based on the appropriate spatial frequency point selection method in the MixeD. Then an optimal filter used for 1-D signal filtering is designed. By filtering 1-D signals over all spatial frequencies, signals with certain velocity vector are extracted, while the extracted image is obtained by applying the 2-D IDFT to the filtered signals. The simulation results show that the method can extract moving object based both on the correctly estimated velocity and the proposed optimal 1-D filter.

We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.

Agent technology is widely recognized as a new paradigm for the design of concurrent software and systems. The aim of this paper is to give a mathematical foundation for the design and the analysis of multi-agent systems by means of a Petri-net-based model. The proposed model, called PN2, is based on place/transition nets (P/T nets), which is one of the simplest classes of Petri nets. The main difference of PN2's from P/T nets is that each token, representing an agent, is also a P/T net. PN2's are sufficiently simple for the mathematical analysis, such as invariant analysis, but have enough modeling power.

We often see reflection phenomenon in our life. For example, through window glass, we can see real objects, but reflection causes virtual objects to appear in front of the glass. Thus, it is sometimes difficult to recognize the real objects. Some works have been proposed to separate these real and virtual objects using an optical property called polarization. However, they have a restriction on one assumption: the angle of incidence. In this paper, we overcome this difficulty using independent component analysis (ICA). We show the efficiency of the proposed method, by experimental results.

A halftoning technique that uses a simple GA has proven to be very effective to generate high quality halftone images. Recently, the two major drawbacks of this conventional halftoning technique with GAs, i.e. it uses a substantial amount of computer memory and processing time, have been overcome by using an improved GA (GA-SRM) that applies genetic operators in parallel putting them in a cooperative-competitive stand with each other. The halftoning problem is a true multiobjective optimization problem. However, so far, the GA based halftoning techniques have treated the problem as a single objective optimization problem. In this work, the improved GA-SRM is extended to a multiobjective optimization GA to simultaneously generate halftone images with various combinations of gray level precision and spatial resolution. Simulation results verify that the proposed scheme can effectively generate several high quality images simultaneously in a single run reducing even further the overall processing time.

In this paper, we explore the possibility of applying associative memories for locating frontal views of human faces in complex scenes. An appealing property of the associative-memory-based face detection system is that learning of the associative memory may be achieved by using a simple Hebbian learning rule. In addition, a simple heuristic rule is used to quickly filter a certain amount of nonface images at the very beginning of the whole detection procedure. By using the rule, we won't waste unnecessary computational resources on those nonface images. A database consisting of 74 images was used to test the performance of our associative-memory-based human face detection system.

This paper presents an accurate method for finding the 3D control points of the B-Spline curves. This method can automatically fit a set of data points with piecewise geometrically continuous cubic B-Spline curves. Iterating algorithm has been used for finding the 2D control points. And a new approach for shape reconstruction based on the control points of the curves on the object's surface is proposed. B-Spline patch, the extension of the B-Spline curves to surface, provides recovering the shape of the object in 2D approach. The 3D control points of the cubic B-Spline curves are computed from the factor decomposition of the measurement matrix of 2D control points. The multiple object approach is also proposed to reconstruct the 3D shape of each curves of an object. Some experiments are demonstrated to confirm the effectiveness of our proposed method.

A new method for object search is proposed. Conventional template matching schemes tend to fail in presence of irregularities and ill-conditions like background variations, illumination fluctuations resulting from shadowing or highlighting etc. The proposed scheme is robust against such irregularities in the real world scenes since it is based on matching gradient information around each pixel, computed in the form of orientation codes, rather than the gray levels directly. A probabilistic model for robust matching is given and verified by real image data. Experimental results for real world scenes demonstrate the effectiveness of the proposed method for object search in the presence of different potential causes of mismatches.

We propose the architecture of efficiently and flexibly extensible solver system for electromagnetic wave simulations, that can load multi kinds of schemes such as Finite-Difference Time-Domain (FDTD) scheme, Finite Element Method (FEM), and a circuit simulator, with various boundary conditions in the system. Object-oriented approach is a promising method for efficient development of the flexible simulator. The primary object in the architecture is found through our object-oriented analysis as decomposed "region" from whole the simulation space. The decomposed region is considered to be the stage on which the electromagnetic fields play under the local rules. Developers who will extend the functionality of the system can add new classes inherited from the abstract classes in our design depending on the grid structure, the scheme, or the boundary processing method.

A knowledge gap between network operators and system developers in Network Management System (NMS) construction has widened. This has been caused by an expansion of supported business processes and increasingly sophisticated network management functions. This gap makes system development costly and time consuming. Function development, led by operators, is a promising solution to the problems caused by the gap. This type of development should not require an operator to know how to develop NMS. Standard objects may be used to meet this requirement and save time and the cost of NMS construction. However, they are not sufficient to design functions supporting some tasks that are for providing custom services. In this paper, we propose a partial extension package, composed of several object classes. This package is attached to the standard objects to design a custom function. Information processing in a new function can be added, and easily modified, using this package. This package specifies states that invoke the information processing. It also includes objects that add new data without changing standard objects. It makes use of several design patterns in order to weaken coupling to the standard objects. We have applied this package to two programs. One plans maintenance tasks schedules, the other sets threshold values for quality of service. We made use of software metrics to measure their performance in terms of flexibility. The results show that the proposed package continues to make it possible to reuse the standard objects, and makes it easy to modify the behavior of a new function.

MPEG-4 emphasizes on coding efficiency and allows for content-based access and transmission of arbitrary shaped object. It addresses the encoding of video object using shape coding, motion estimation, and texture coding for interactivity, high compression ratio, and scalability. In this letter, an advanced object-adaptive vertex-based shape coding method is proposed for encoding the shape of video objects. This method exploits octant-based representation to represent the relation of adjacent vertices and that relation can be used to improve coding efficiency. Simulation results demonstrate that the proposed method may reduce more bits for closely spaced vertices.