In this paper, we propose a hybrid fine-tuned multi-objective memetic algorithm hybridizing different solution fitness evaluation methods for global exploitation and exploration. To search across all regions in objective space, the algorithm uses a widely diversified set of weights at each generation, and employs a simulated annealing to optimize each utility function. For broader exploration, a grid-based technique is adopted to discover the missing nondominated regions on existing tradeoff surface, and a Pareto-based local perturbation is performed to reproduce incrementing solutions trying to fill up the discontinuous areas. Additional advanced feature is that the procedure is made dynamic and adaptive to the online optimization conditions based on a function of improvement ratio to obtain better stability and convergence of the algorithm. Effectiveness of our approach is shown by applying it to multi-objective 0/1 knapsack problem (MOKP).

Inference attacks mean that a user derives information on the execution results of unauthorized queries from the execution results of authorized queries. Most of the studies on inference attacks so far have focused on only inference of positive information (i.e., what value is the execution result of a given unauthorized query). However, negative information (i.e., what value is never the execution result of a given unauthorized query) is also sensitive in many cases. This paper presents the following results on the security against inference attacks on negative information in object-oriented databases. First, inference of negative information is formalized under a model of object-oriented databases called method schemas. Then, the following two types of security problems are defined: (1) Is a given database instance secure against inference attacks on given negative information? (2) Are all of the database instances of a given database schema secure against inference attacks on given negative information? It is shown that the first problem is decidable in polynomial time in the description size of the database instance while the second one is undecidable. A decidable sufficient condition for any database instance of a given database schema to be secure is also proposed. Finally, it is shown that for a monadic schema (i.e., every method has exactly one parameter), this sufficient condition is also a necessary one.

Petri nets are a well-known graphical and modeling tool for concurrent and distributed systems, and there have been many results on the theory, and also on practical applications. In the last decade, various Object-Oriented Petri nets (OO-nets) are proposed. As object orientation was adopted for programming languages, extension to OO-nets inspired from object-oriented programming is a natural flow. This article presents state-of-the-art on OO-nets.

This paper presents a Fault-Tolerant Object Group (FTOG) model that provides the group management service and the fault-tolerance service for consistency maintenance and state transparency. Through Intelligent Home Network Simulator, we verify that FTOG model supports both of reliability and the stability of the distributed system.

We are developing a helper robot that carries out tasks ordered by the user through speech. The robot needs a vision system to recognize the objects appearing in the orders. It is, however, difficult to realize vision systems that can work in various conditions. Thus, we have proposed to use the human user's assistance through speech. When the vision system cannot achieve a task, the robot makes a speech to the user so that the natural response by the user can give helpful information for its vision system. Our previous system assumes that it can segment images without failure. However, if there are occluded objects and/or objects composed of multicolor parts, segmentation failures cannot be avoided. This paper presents an extended system that tries to recover from segmentation failures using photometric invariance. If the system is not sure about segmentation results, the system asks the user by appropriate expressions depending on the invariant values. Experimental results show the usefulness of the system.

Though block-based motion estimation techniques are primarily designed for video coding applications, they are increasingly being used in other video analysis applications due to their simplicity and ease of implementation. The major drawback associated with these techniques is that noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors. Similar noises may further be introduced when the technique of global motion compensation is applied to obtain true object motion from video sequences where both the camera and object motions are present. This paper presents a new technique for capturing large number of true object motion vectors by eliminating the false motion vector fields, for use in the application of object motion based video indexing and retrieval applications. Experimental results prove that our proposed technique significantly increases the percentage of retained true object motion vectors while eliminating all false motion vectors for variety of standard and non-standard video sequences.

This paper proposes a model for access control within object-oriented systems. The model is based on RBAC (role-based access control) and is called DRBAC (dynamic RBAC). Although RBAC is powerful in access control, the original design of RBAC required that user-role assignments and role-permission assignments should be handled statically (i.e., the assignments should be handled by human beings). Nevertheless, the following dynamic features are necessary in access control within a software system: (a) managing dynamic role switching, (b) avoiding Trojan horses, (c) managing role associations, and (d) handling dynamic role creation and deletion. DRBAC offers the dynamic features. This paper proposes DRBAC.

The demand for intra- and interdomain routing for multilayered networks such as those using generalized multiprotocol label switching (GMPLS) is strong. One of the features that is peculiar to GMPLS networks is that because several different domains, such as those of IP, ATM, and optical fiber, are combined with each other hierarchically, various routing policies, which are sometimes independent from underlying domains and sometimes taking the underlying domains' policies into consideration, are required. For example GMPLS's lower layer LSPs like lambda LSP are expected to be established independently before the upper-layer LSPs, like IP and MPLS LSPs, are established in the underlying domains. Another requirement for the GMPLS interdomain routing is lightening the burden for selecting the interdomain route, because there are a lot of demands to interconnect many GMPLS domains. In order to satisfy these demands, we propose a path computation server (PCS) that is special for the intra/interdomain routing of GMPLS networks. As a counterpart of the proposed interdomain routing, it is now becoming popular to apply OSPF to the GMPLS interdomain routing. Therefore, we compared the proposed interdomain routing with OSPF, and show the applicability of the routing to GMPLS networks.

This paper presents a semi-automatic algorithm for video object segmentation. Our algorithm assumes the use of multiple key video frames in which a semantic object of interest is defined in advance with human assistance. For video frames between every two key frames, the specified video object is tracked and segmented automatically using Learning Vector Quantization (LVQ). Each pixel of a video frame is represented by a 5-dimensional feature vector integrating spatial and color information. We introduce a parameter K to adjust the balance of spatial and color information. Experimental results demonstrate that the algorithm can segment the video object consistently with less than 2% average error when the object is moving at a moderate speed.

Researches on millimeter wave imaging in State Key Lab of Millimeter Waves are described. The researches mainly focus on the analysis and design of optical components or various lenses of imaging system. It is a base for getting good imaging quality. The field distribution in focal space of various lens including refractive lens and diffractive lens are analyzed and computed to show their imaging performance. The approaches to reduce the aberration of lens and expand the field-of-view of imaging system are studied and ameliorative results are obtained. Imaging experiment of concealed object is carried out to show the imaging ability of diffractive lens.

Due to the continuous growth of wireless communication technology and mobile equipment, the need for storing and processing data of moving objects arises in a wide range of location-based applications. In this paper, we propose a new spatio-temporal index structure for moving objects, namely the TPKDB-tree, which supports efficient retrieval of future positions and reduces the update cost.

Larger object classes often become more costly classes in the maintenance phase of object-oriented software. Consequently class would have to be constructed in a medium or small size. In order to discuss such desirable size, this paper proposes a simple method for predictively discriminating costly classes in version-upgrades, using a class size metric, Stmts. Concretely, a threshold value of class size (in Stmts) is provided through empirical studies using many Java classes. The threshold value succeeded as a predictive discriminator for about 73% of the sample Java classes.

In this paper, a new error concealment algorithm for MPEG-4 object-based video is presented. The algorithm consists of a feature matching step to identify temporally corresponding features between video frames and an affine parameter estimation step to find the motion of the feature points. In the feature matching step, an efficient cross-radial search (CRS) method is developed to find the best matching points. In the affine parameter estimation step, a non-iterative least squares estimation algorithm is developed to estimate the affine parameters. An attractive feature of the algorithm is that the shape data and texture data are handled by the same method. Unlike previous methods, this unified approach works for the case where the video object undergoes a drastic movement, such as a sharp turn. Experimental results show that the proposed algorithm performs much better than previous approaches by about 0.3-2.8 dB for shape data and 1.6-5.0 dB for texture data.

In this paper, an algorithm for anchor frame detection in news video is proposed, which consists of four steps. First, the cumulative histogram method is used to detect shot boundaries in order to segment a news video into video shots. Second, skin color information is used to detect face regions in each video shot. Third, color information of upper body regions is used to extract anchor object. Then, a graph-theoretic cluster analysis algorithm is utilized to classify the news video into anchor-person shots and non-anchor shots. Experimental results have shown the effectiveness of the proposed algorithm.

The increasing complexity and shorter life cycle of software have made it necessary to reuse software. Object-oriented development has not facilitated extensive reuse of software and it has become difficult to manage and understand modern object-oriented systems which have become very extensive and complex. However, components, compared with objects, provide more advanced means of structuring, describing and developing systems, because they are more coarse grained and have more domain-specific aspects than objects. In addition, they are also suited to a current distributed environment due to their reusability, maintainability and granularity. In this paper, we present a process of extracting components from object-oriented systems. We define some static metrics and guidelines that can be applied to transform object-oriented systems into component-based systems. Our process consists of two parts. First, basic components are created based on composition and inheritance relationships between classes. Second, the intermediate system is refined into a component-based system with our proposed static metrics and guidelines.

In this paper, we present a novel framework for analyzing and segmenting point-sampled 3D objects. Our algorithm computes a decomposition of a given point set surface into meaningful components, which are delimited by line features and deep concavities. Central to our method is the extension of the scale-space theory to the three-dimensional space to allow feature analysis and classification at different scales. Then, a new surface classifier is computed and used in an anisotropic diffusion process via partial differential equations (PDEs). The algorithm avoids the misclassifications due to fuzzy and incomplete line features. Our algorithm operates directly on points requiring no vertex connectivity information. We demonstrate and discuss its performance on a collection of point sampled 3D objects including CAD and natural models. Applications include 3D shape matching and retrieval, surface reconstruction and feature preserving simplification.

This paper presents a deformable fast computation elastic model for real-time processing applications. 'Gradational element resolution model' is introduced with fewer elements for fast computation, in which small elements are laid around the object surface and large elements are laid in the center of the object. Elastic element layout is changed dynamically according to the deformation of cutting or tearing objects. The element reconstruction procedure is applied little by little for each step of the recursive motion generation process to avoid an increase in motion computation time.

This paper presents a new model which computes the deformation and the feedback force of high-resolution biomedical volumetric objects consisting of hundreds of thousands of volume elements. The main difficulty in the simulation of these high-resolution volumetric objects is to compute and generate stable feedback force from the objects within a haptic update time (1 msec). In our model, springs are used in order to represent material properties of volume elements and cylinders are used to activate corresponding springs according to the amount of deformation. Unlike in a mass-spring model, springs in our model have constraint conditions. In our model, the deformation is calculated locally and then is propagated outward through object's volume as if a chain is pulled or pushed. The deformed configuration is then used to compute the object's internal potential energy that is reflected to the user. The simple nature of our model allows the much faster calculation of the deformation and the feedback force from the volumetric deformable object than the conventional model (an FEM or a mass-spring model). Experiments are conducted with homogenous and non-homogenous volumetric cubic objects and a volumetric human liver model obtained from CT data at a haptic update rate of 1000 Hz and a graphic update rate of 100 Hz to show that our model can be utilized in the real-time volume haptic rendering. We verify that our model provides a realistic haptic feeling for the user in real time through comparative study.

This paper newly proposes a method to automatically decompose real scene images into multiple object-oriented component regions. First, histogram patterns of a specific image feature, such as intensity or hue value, are estimated from image sequence and stored up. Next, Gaussian distribution parameters which correspond to object components involved in the scene are estimated by applying the EM algorithm to the accumulated histogram. The number of the components is simultaneously estimated by evaluating the minimum value of Bayesian Information Criterion (BIC). This method can be applied to a variety of computer vision issues, for example, the color image segmentation and the recognition of scene situation transition. Experimental results applied for indoor and outdoor scenes showed the effectiveness of the proposed method.

Recently, wideband speech communication using 7 kHz-wideband speech coding, as described in ITU-T Recommendations G.722, G.722.1, and G.722.2, has become increasingly necessary for use in advanced IP telephony using PCs, since, for this application, hands-free communication using separate microphones and loudspeakers is indispensable, and in this situation wideband speech is particularly helpful in enhancing the naturalness of communication. An objective quality measurement methodology for wideband-speech coding has been studied, its essential components being an objective quality measure and an input test signal. This paper describes Wideband-PESQ conforming to the draft Annex to ITU-T Recommendation P.862, "Perceptual Evaluation of Speech Quality (PESQ)," as the objective quality measure, by evaluating the consistency between the subjectively evaluated MOS (Mean Opinion Score) and objectively estimated MOS. This paper also describes the verification of artificial voice conforming to Recommendation P.50 "Artificial Voices," as the input test signal for such measurements, by evaluating the consistency between the objectively estimated MOS using a real voice and that obtained using an artificial voice.