We suggest a new probe message structure and an efficient probe-based deadlock detection and recovery algorithm that can be used in distributed database systems. We determine the characteristics of the probe messages and suggest an algorithm that can reduce the communication cost required for deadlock detection and recovery.

Finding corresponding edges is considered being the most difficult part of edge-based stereo matching algorithms. Usually, correspondence for a feature point in the first image is obtained by searching in a predefined region of the second image, based on epipolar line and maximum disparity. Reduction of search region can increase performances of the matching process, in the context of execution time and accuracy. Traditionally, hierarchical multiresolution techniques, as the fastest methods are used to decrease the search space and therefore increase the processing speed. Considering maximum of directional derivative of disparity in real scenes, we formulated some relations between maximum search space in the second images with respect to relative displacement of connected edges (as the feature points), in successive scan lines of the first images. Then we proposed a new matching strategy to reduce the search space for edge-based stereo matching algorithms. Afterward, we developed some fast stereo matching algorithms based on the proposed matching strategy and the hierarchical multiresolution techniques. The proposed algorithms have two stages: feature extraction and feature matching. We applied these new algorithms on some stereo images and compared their results with those of some hierarchical multiresolution ones. The execution times of our proposed methods are decreased between 30% to 55%, in the feature matching stage. Moreover, the execution time of the overall algorithms (including the feature extraction and the feature matching) is decreased between 15% to 40% in real scenes. Meanwhile in some cases, the accuracy is increased too. Theoretical investigation and experimental results show that our algorithms have a very good performance with real complex scenes, therefore these new algorithms are very suitable for fast edge-based stereo applications in real scenes like robotic applications.

We present an efficiency improvement on an existing unlinkable divisible e-cash system. In the based e-cash system, an e-coin can be divided to spent, and thus the exact payments are available. Furthermore, to protect customer's privacy, the system also satisfies the unlinkability in all the payments, which is not satisfied in other existing divisible e-cash systems. The unlinkability means the infeasibility of determining whether two payments are made by the same customer. However, in the unlinkable divisible e-cash system, the payment protocol needs O(N) computations, and thus inefficient, where N indicates the divisibility precision. For example, in case of N=100,000, about 200,000 exponentiations are needed for the worst. We improve the payment protocol using the tree approach. In case of N=100,000, the protocol with our improvement needs only about 600 exponentiations for the worst. This good result can be obtained for other N which is more than about 100.

In this paper, we propose a new neural filter to which the features related to a given task are input, called a neural filter with features (NFF), to improve further the performance of the conventional neural filter. In order to handle the issue concerning the optimal selection of input features, we propose a framework composed of 1) manual selection of candidates for input features related to a given task and 2) training with automatically selection of the optimal input features required for achieving the given task. Experiments on the proposed framework with an application to improving the image quality of medical X-ray image sequences were performed. The experimental results demonstrated that the performance on edge-preserving smoothing of the NFF, obtained by the proposed framework, is superior to that of the conventional neural and dynamic filters.

A kind of online edge-coloring problems on bipartite graphs is considered. The input is a graph (typically with no edges) and a sequence of operations (edge addition and edge deletion) under the restriction that at any time the graph is bipartite and degree-bounded by k, where k is a prescribed integer. At the time of edge addition, the added edge can be irrevocably assigned a color or be left uncolored. No other coloring or color alteration is allowed. The problem is to assign colors as many times as possible using k colors. Two algorithms are presented: one with competitiveness coefficient 1/4 against oblivious adversaries, and one with competitiveness coefficient between 1/4 and 1/2 with the cost of requiring more random bits than the former algorithm, also against oblivious adversaries.

An English auction is the most familiar type of auctions. Generally, an electronic auction has mainly two entities, the registration manager (RM) who treats the registration of bidders, and the auction manager (AM) who holds auctions. Before starting an auction, a bidder who wants to participate in English auction is registered to RM with her/his information. An electronic English auction protocol should satisfy the following nine properties, (a) Anonymity, (b) Traceability, (c) No framing, (d) Unforgeability, (e) Fairness, (f) Verifiability, (g) Unlinkability among plural auctions, (h) Linkability in an auction, and (i) Efficiency of bidding. Furthermore from the practical point of view we add two properties (j) Easy revocation and (k) One-time registration. A group signature is adapted to an English auction in order to satisfy (a), (b), and (f). However such a direct adoption suffers from the most critical drawback of efficiency in group signatures. In this paper we propose more realistic electronic English auction scheme, which satisfies all of these properties without using a group signature. Notable features of our scheme are: (1) both of bidding and verification of bids are done quite efficiently by introducing a bulletin board, (2) both properties (j) Easy revocation and (k) One-time registration are satisfied.

Services that operate normally, independently, will behave differently when simultaneously initiated with another service. This behavior is called a feature interaction. A feature interaction, where the next state can not be determined uniquely for one event, is called a non-determinacy feature interaction. To detect the interaction, judgment has to be made as to whether the state, where the non-determinacy occurs, is reachable from the initial state or not. For the judgment, many methods have been proposed. But, still now, it is required huge computation time to judge the reachability. This paper proposes a new method to test the reachability using a little knowledge elicited beforehand. By using the proposed method computation time was reduced drastically. Besides, by applying the proposed method to a benchmark, the proposed method was confirmed to be effective and reasonable.

In this paper, we discuss noise reduction approaches to improving range images using a nonlinear 2D Kalman filter. First, we propose the nonlinear 2D Kalman filter, which can reduce noise in the range image using an estimated edge vector and a nonlinear function that does not distort sharp edges. Second, we evaluate reduction of the additive noise in a test range image using the mean square error (MSE). Third, we discuss the detection rate and the number of false detections in the estimated range image. Fourth, a simulation example demonstrating the performance of the proposed 2D Kalman filter for a real range image having abrupt changes is presented. Finally, simulation results are presented which show that the estimated image of the nonlinear 2D Kalman filter is effective in reducing the amount of noise, while causing minimal smoothing of the abrupt changes.

This paper presents the concepts and methodology of knowledge-based information modeling based on Cognitive Science for realizing the autonomous humanoid service robotic arm and hand system HARIS. The HARIS robotic system consists of model-based 3D vision, intelligent scheduler, computerized arm/hand controller, humanoid HARIS arm/hand unit and human interface, and aims to serve the aged and disabled on desk-top object manipulations. The world model, i.e., a shared knowledge base, is introduced to work as a communication channel among the software modules. The task scheduling as well as the 3D-vision is based on Cognitive Science, i.e., a human's way of vision and scheduling is considered in designing the knowledge-based software system. The key idea is to use "words" in describing a scene, scheduling tasks, controlling an arm and hand, and interacting with a human. The world model plays a key role in fusing a variety of distributed functions. The generalized frame-based knowledge engineering environment ZERO++ has been effectively used as a software platform in implementing the system. The experimental system is working within a limited situation successfully. Through the introduction of Cognitive Science-based information modeling we have learned useful hints for realizing human-robot symbiosis, that is our long term goal of the project.

Locating corner points from an edge detected image is very important in view of simplifying the post processing part of a system that utilizes a corner information. In this paper, we propose a robust geometrical approach for corner detection. Unlike classical corner detection methods, which idealize corners as junction points of two line segments, our approach considers the possibility of multiple line segments intersecting at a point. Moreover, junctions caused by two or more curved segments of different curvature are thought of as a corner point. The algorithm has been tested and proved competence with different types of images demonstrating its ability to detect and localize the corners in the image, though we found it to be best suited for images with relatively few curved segments. With the help of non-maximum response suppression technique our approach yields comparatively better result than any other method.

We fabricated ramp-edge junctions with barriers by modifying surface and integrating ground-planes. The fabricated junctions had current-voltage characteristics consistent with the resistive shunted-junction model. We also obtained a 1-sigma spread in the critical current of 7.9% for 100 junctions at 4.2 K. The ground-plane reduced the sheet inductance of a stripline by a factor of 3. The quality of the ground-plane was improved by using an anneal in oxygen atmosphere after fabrication. The sheet inductance of a counter-electrode with a ground-plane was 1.0 pH per square at 4.2 K.

In this paper, a new image synthesis model based on a set of wavelet bases is proposed. In the proposed model, images are approximated by the sum of synthesis functions that are translated to image edge positions. By applying the proposed model to sketch-based image coding, no iterative image recovery procedure is required for image decoding. In the design of the synthesis functions, we define the synthesis functions as a linear combination of wavelet bases. The coefficients for wavelet bases are obtained from an iterative procedure. The vector quantization is applied to the vectors of the coefficients to limit the number of the synthesis functions. We apply the proposed synthesis model to the sketch-based image coding. Image coding experiments by eight synthesis functions and a comparison with the orthogonal transform methods are also given.

Edge enhancement of noisy ultrasound images is important for medical diagnosis. Conventional edge enhancement methods are mainly directed to emphasizing the high-frequency components of the image. Because these methods emphasize also the noise of image, they are not suitable for noisy ultrasound images with speckle noise. In this paper, we propose an edge enhancement method using mathematical morphology based on a geometrical characteristics of the image, using locally variable structuring elements. We show that the proposed method enhances the edge of ultrasound images without noise emphasis.

This paper reports on clich and related mechanisms appearing in a process of human design of software. During studies on human design knowledge, the authors found frequent instance of same pattern of detailing, named clich. In our study, clich is an intermediate level of design knowledge, during a hierarchical detailing step, residing in between simple reuse and creation by micro design rules, which have already been reported. These three kinds of design knowledge are of various types and have different complexities. Discussions on them, focusing on clich type, with procedures of formation of a simple clich skeleton and generation of a clich are given. The studies show a working model of Zipf's principle, and are some trials to reveal a more detail of human designs.

The paper proposes a vision-based system for adaptively inferring the interactional intention of a person coming close to a robot, which plays an important role in the succeeding stage of human/robot cooperative handling of works/tools in production lines. Here, interactional intention is ranged in the meaning of the intention to interact/operate with the robot, which is proposed to be estimated by the human head moving path during an incipient period of time. To implement this intention inference capability, first, human entrance is detected and is modeled by an ellipse to supply information about the head position. Second, B-spline technique is used to approximate the trajectory with reduced control points in order that the system acquires information about the human motion direction and the curvature of the motion trajectory. Finally, Hidden Markov Models (HMMs) are applied as the adaptive inference engines at the stage of inferring the human interactional intention. The HMM algorithm with a stochastic pattern matching capability is extended to supply whether or not a person has an intention toward the robot at the incipient time. The reestimation process here models the motion behavior of an human worker when he has or doesn't have the intention to operate the robot. Experimental results demonstrate the adaptability of the inference system using the extended HMM algorithm for filtering out motion deviation over the trajectory.

Today software piracy is a major concern to electronic commerce since a digitized product such as software is vulnerable to redistribution and unauthorized use. This paper presents an enhanced electronic software distribution and software protection model. Authentication scheme of the proposed model is based on zero-knowledge (ZK) proof which requires limited computation. The proposed model considers post installation security using authentication agent. It prevents software piracy and illegal copy. It also provides secure and efficient software live-update mechanism based on traitor tracing scheme. Even if software or personal key is copied illegally, a merchant can trace back to its original owner from the electronic license and personal key. The proposed model provides security and reasonable performance and safety.

This paper describes the implementation of a proposed image filter into a Discrete-Time Cellular Neural Network (DT-CNN). The three stages that compose the filter are described, showing that the resultant filter is capable of (1) erasing or detecting several concentric shapes simultaneously, (2) thresholding and (3) thinning of gray-scale images. Because the DT-CNN has to fill certain conditions for this filter to be implemented, it becomes a modified version of a DT-CNN. Those conditions are described and also experimental results are clearly shown.

Beam reconfiguration by structural reconfigurable antenna, such as the small multi-panel reconfigurable reflector antenna, has an aspect of great concern, that is the effects due to the use of a number of small panels to form the reflecting surface. It is thus a matter of great interest to numerically investigate all possible factors affecting the performance of this type of antenna such as: neighboring panels blocking, diffraction. The "null-field hypothesis" and PTD are employed to account for the effects of both phenomena on the main beam steering ability and the cross-polar level. In addition, the transformation of the polygonal flat domains into the square domains is applied in calculating the PO radiation field due to the various irregular polygonal flat sections of the arbitrary initial approximate reflector e.g., the flat circular reflector and the paraboloidal reflector. It is found that the main contribution to the total cross polarization is depolarization due to the finite size of the panels. The maximum cross-polar gain predicted using PTD is around -30 dB. The blocking effect has minor influence on cross-polarization. Both effects cause distortion on the co-polar pattern for the observer far from boresight but blocking has more influence than edge diffraction. Both effects have minor influence on the co-polar gain. The co-polar gain has variation of less than or equal to 0.07 dB in the flat case and 0.16 dB in the paraboloid case.

Using Available Bit Rate (ABR) service of Asynchronous Transfer Mode (ATM) at a backbone link will provide a lossless network. It, however, causes congestion at an edge-router and is reported to show poor end-to-end TCP performance. We consider how to improve the performance of TCP over a backbone ABR network. By using ABR feedback information (ACR) at edge-routers, we can adjust intervals of TCP Acknowledgement packets. This adjustment couples the ABR rate-based control loop and the TCP window-based control loop. Based on this scheme, we can achieve a good end-to-end TCP performance as well as good ATM layer performance over backbone ABR. This paper describes comprehensive study on the proposed mechanism.

This paper propose a method for improving the image quality of motion estimation (ME) using low-bit images. By using edge-enhanced images for quantization, we can increase the accuracy of the ME and improve the image quality. It is known that using low-bit images for ME is effective for reducing power consumption but it slightly degrades image quality. The quality of the encoded image depends on the thresholds for data quantization, thus, algorithms for determining thresholds are studied. The proposed method uses linear quantization, which simply truncates the least significant bits. This method is simple without any complicated threshold calculations, and the resultant image quality is improved as much as the methods that use threshold calculations. To evaluate the effectiveness, we simulate results for image quality and estimate the power consumption using synthesis results from a VHDL model motion estimator.