bluuebunny/crossref_metadata_2025_split huggingface dataset:
A flow‐executing scheme for DOACROSS loops on dynamic dataflow machines
Authors: Ishii Yoshihiko , Yamana Hayato , Yasue Toshiaki , Muraoka Yoichi 
Published: July 2007

AbstractThis paper modifies a flow‐executing scheme of the color‐reuse type, using multiple initial loop control packets, and then proves that the flow‐executing scheme is best suited for executing DOACROSS loops on dynamic dataflow machines. Flow‐executing schemes can be divided into four categories: (1) those using a single initial loop control packet; (2) those using multiple initial loop packets; (a) the color overflow type; and (b) the color reuse type. Then the flow‐executing scheme can be classified into Classes (1‐a), (1b), (2‐a), and (2‐b) through the combination of Categories (1), (2), (a), and (b). This paper suggests that Class (2‐b) is best suited for executing DOACROSS loops, as it extracts full parallelism from DOACROSS loops, no sychronization overhead exists, and no memory access overhead exists after the synchronization.
A two‐step mutual multicast technique for n‐to‐n communication
Authors: Nakajima Amane 
Published: July 2007

AbstractMutual multicast is a communication pattern in which each node in a group sends a message to any other node in that group. This n‐to‐n communication pattern is required in various cases of distributed processing, and an efficient realization of the pattern is needed.This paper proposes a two‐stage mutual multicast technique in which mutual multicast is executed by two stages of the submulticasts through distributed control. Ordinary mutual multicast is executed in one stage. But two‐stage multicast can carry out a communication with fewer messages and in a shorter time if the submulticast destination node sets are approximately set in each stage.When there are n nodes, single‐stage multicast requires n(n‐1) messages and a time of 2(n‐1) if all communications are carried out as one‐to‐one message communications; but two‐stage mutual multicast requires only 2n⌈√n⌉ and a time of 4⌈√n⌉. In LANs, such as Ethernet, the multicast function is provided by the MAC sublayer. When this function is available, the two‐stage mutual multicast procedure can carry out a communication in a time of 2(⌈√n⌉+1), which compared with a time n in single‐stage mutual multicast.
Hierarchical redundancy for array‐structure wsis
Authors: Tsuda Nobuo 
Published: July 2007

AbstractThis paper proposes hierarchical redundancy configurations for defect tolerance of large‐area monolithic LSIs (wafer‐scale integrated circuits or WSIs) with array structures. It also specifies how much the integration scales can be increased by expanding hierarchical levels, based on four kinds of one‐dimensional/two‐dimensional array‐connection models. Hierarchical redundancy helps to extend the defect tolerance coverage to additional replacement circuits while maintaining a high level of spare effectiveness. An estimate based on the evaluation of nonredundant additional replacement‐circuit scales indicates that four‐level hierarchical redundancy configurations can increase integration scales by a factor of 64 to 1024 compared to nonredundant LSIs.
A graph editor for large trees with browsing and zooming capabilities
Authors: Matsuura Toshio , Taniguchi Kenichi , Masuda Sumio , Nakamura Tohru 
Published: July 2007

AbstractA library program is developed which makes it easy for users to observe a whole tree and some specified parts of the tree simultaneously, and also facilitates the input of commands for the tree by allowing direct manipulation on the display. This capability should be useful in a variety of application programs. By measuring the update time of large tree structures, the calculation of the layout algorithm, and the update time of the display, it is shown that VTM is usable in practice for large trees.
Object recognition by neural network using thickness data from acoustic image
Authors: Yoshizawa Nobuyuki , Tada Hidenobu , Yabuta Tetsuro 
Published: July 2007

AbstractMethods of inputting stereoscopic information to neural networks and of imaging by ultrasonic sensors were examined from the perspective of three‐dimensional object recognition, and a new recognition method was developed for depth images in neural networks. Because a perceptron neural network is used as the recognition stage and ultrasonic sensors arranged in an array for both reception and transmission are used as the shape measurement stage, this method performs compression of the stereoscopic information of an object into a frame of depth information by measuring the planar distribution of the distances to the object's surface (using a pulse echo method); it has the advantage of being able to efficiently recognize an object freely moving in any direction (forward and backward, right and left, and up and down) and having any orientation within a plane, by using depth information. Since a neural network is used, even when different features are extracted from the object, direct recognition is possible. In this paper, which addresses the issue of three‐dimensional object recognition using perceptrons, we describe a measurement and recognition system capable of preprocessing stereoscopic information that can be freely positioned in three dimensions to allow recognition by perceptrons, and we present the results of recognition tests. Finally, we propose a recognition algorithm that actively uses depth (which is not a feature in two dimensions), show that the algorithm can recognize both the position and orientation of the object, and demonstrate its practicality.
The ToM (thread on modules) microkernel
Authors: Hagino Tatsuya , Yamagishi Kinya 
Published: July 2007

AbstractThe authors have been developing a distributed operating system called Threads on Modules (ToM). It supports a programming model which is suited for distributed environments. For this purpose, modules, threads, houses, users, RPCs and capabilities are introduced.To make the ToM system as portable as possible, it was implemented using the microkernel technology. The ToM microkernel implements the minimal functionalities and the others are implemented as user level programs. Although the ToM microkernel is designed to support the ToM programming model, it has sufficient functionalities to implement other operating systems. This paper presents some of the main features of the ToM microkernel. A UNIX emulator also is presented.
A new design method of software based on state transition
Authors: Yokoi Naoko , Kaneko Takeshi , Iizuka Yoshinori 
Published: July 2007

AbstractAn understanding of state transitions is essential in real‐time software design. However, satisfactory research has not been performed on methodologies to list the necessary states. A method is needed to systematically identify necessary states in order to meet the given requirements. The two points that must be clarified when identifying necessary states are which states are necessary states and what causes lead to considering a state necessary. We begin this paper by clarifying the necessary states in software design that must be introduced into the software when elements other than state parameters external to the software are required to determine the correct response when multiple responses are obtained from the same input. Next, by focusing on the relationship between the input and the output, we illustrate that the software requirements have a hierarchical structure and selections from alternative realization methods based on the structure cause consideration on states. This requirement structure designates the logical structure of the requirements specified in the design process. Design and specification (implementation) of the requirements make is possible to list necessary states systematically.
Characteristics of minimum directional difference filter which extracts circumscribed shadows in chest X‐ray images
Authors: Shimizu Akinobu , Toriwaki Jun‐Ichiro , Hasegawa Jun‐Ichi 
Published: July 2007

AbstractOne of the most important steps in image processing for chest x‐ray images is the enhancement and extraction of abnormal shadows existing in the lung field. The authors have developed an automated screening system AISCR‐V3 for chest x‐ray images. The filter used in this system for enhancing abnormal shadows, however, does not have sufficient performance from the viewpoint of the suppression of the false‐positive and the false‐negative.This paper presents a new filter developed for enhancement of abnormal shadows. This filter, called the Min‐DD filter, is a combination of second‐order difference filters with variable directions through minimum‐value operation.In this paper, problems in the previous filters for enhancement of abnormal shadows are pointed out first, and then the Min‐DD filter is defined. The performance of the filter is evaluated using the artificial shadows and the actual chest x‐ray images and it is shown that the new filter has a higher performance than the previous ones.Assuming that the size, SN ratio and the accuracy of extraction (error probability) of abnormal shadows are specified, the best radius of the filter is derived, providing a design guide for the filter. Furthermore, the improvement of the performance in false‐positive suppression and the expansion of the filter function are reported.
Image processing for computer‐aided diagnosis of lung cancer by CT (LSCT)
Authors: Yamamoto Shinji , Tanaka Ippei , Senda Masahiro , Tateno Yukio , Iinuma Takeshi , Matsumoto Toru , Matsumoto Mitsuomi 
Published: July 2007

AbstractThis paper reports a special‐purpose CT for early detection of lung cancer and presents the basic idea. The parallel use of the following two systems is investigated as the diagnosis‐support image display method needed in such a system, and a satisfactory result is obtained.
The maximum intensity projection (MIP) is applied as a means to realize the two‐dimensional projection display from the three‐dimensional information composed of 40 slices of lung tissue while retaining the information concerning the pathological shadows. When the simple MIP is applied, there is a large disturbance due to unnecessary organ signals. Consequently, a method is developed in which unnecessary information is deleted by thresholding;
The automatic recognition of candidates for the pathological shadows is applied to each slice. Only the CT image containing a shadow candidate is displayed on CRT, which helps to reduce greatly the number of cross sections to be displayed. In the automatic recognition of the pathological shadow, the quoit filter recently developed by the authors is employed.
Local motion detection by hierarchical neural network
Authors: Atsumi Eiji , Takagi Mikio , Yokosawa Kazuhiko 
Published: July 2007

AbstractPerception of visual motion is thought to consist of two stages: generation of candidates and their interaction to determine true motion. In this paper, a three‐layered neural network is applied to detect local visual motion. The network, after learning, could categorize nine types of motion and obtained a motion detection algorithm that included the two states of perception. The internal representations for the first stage agree with the functions of one‐center and off‐center cells, and those for the second stage agree with the functions of lateral inhibition. We also tried to detect arbitrary motions by combining multi‐resolution representation of images with the neural network.
High‐precision γ‐ω hough transformation algorithm to detect arbitrary digital lines
Authors: Wada Toshikazu , Seki Makito , Matsuyama Takashi 
Published: July 2007

AbstractThe γ‐ω Hough transform we proposed earlier (a) does not lead to bias in the number of votes accumulated in the cell even when the parameter space is sampled in uniform cells and voting takes place over all pixels, and (b) the voting locus becomes a piecewise linear line composed of two segments so drawing and analyzing the curve is simple. These are significant advantages. In a conventional γ‐ω Hough transformation algorithm, however, votes from the pixel set included on one digital line spread over multiple cells in the parameter space and the number of pixels forming digital lines is not always taken as the correct number of votes. The reason is the conventional algorithm does not detect all of the target digital lines in the image space. In this research, for the γ‐ω Hough parameter space, we determine the cell configuration having a one‐to‐one correspondence with all of the digital lines in the image space and demonstrate an appropriate voting method for this cell configuration. By applying the “high‐precision γ‐ω Hough transformation algorithm” used in the cell configuration and voting method proposed in this paper, digital lines having any orientation and position can be stably and precisely detected.
Multimodal definite clause grammar
Authors: Shimazu Hideo , Takashima Yosuke 
Published: July 2007

AbstractThis paper describes the first reported grammatical framework for a multimodal interface. The authors have developed Multimodal Definite Clause Grammar (MM‐DCG), an extension of Definite Clause Grammar. The major features of MM‐DCG include the capability to handle an arbitrary number of modes and temporal information in grammar rules. Further, the techniques for translating MM‐DCG rules into Prolog predicates are described in detail.
Stability of solutions in hopfield neural network
Authors: Matsuda Satoshi 
Published: July 2007

AbstractTaking the traveling salesman problem as an example of a combinatorial optimization problem that can be solved by neural networks with symmetric connections (Hopfield neural networks), the asymptotic stability and instability conditions of solutions satisfying the constraints of the problem, and instability conditions of nonsolutions which do not satisfy those constraints are presented. From the results, it is shown that network properties such as the limitations of networks with multilinear energy function (wii = 0) and many other phenomena can be explained theoretically. Furthermore, from simulation it is confirmed that the optimal solution for the optimization problem can be obtained with high probability by setting the coefficients of the constraints and the optimization requirements so that they satisfy the presented conditions.
Genetic algorithms applied to bayesian image restoration
Authors: Takatsu Kazunori , Sawai Hidefumi , Watanabe Sumio , Yoneyama Masahide 
Published: July 2007

AbstractThis paper describes genetic algorithms (GAs) applied to Bayesian image restoration. Crossover operation is discussed as a method used to find new search points in GAs. A suitable genotype and an efficient crossover method for a Bayesian image restoration will be proposed. Due to the independency of GAs from objective function forms, it is easy to introduce ideas into the objective functions. The idea of line process proposed by S. Geman and D. Geman [12] is introduced into the objective function, which provides better restored images. As a comparison, a stochastic relaxation (SR) method is applied to the image restoration problem, and the convergence properties of SR and GAs are also discussed.
A recursive algorithm for edge intensity and gray‐level thresholds selection based on edge and contour evaluation
Authors: Gotoh Toshiyuki , Toriu Takashi 
Published: July 2007

AbstractA high‐speed recursive algorithm has been proposed for determining multiple thresholds for a gray level of an image based on edge and contour evaluation using a two‐dimensional histogram of the maximum and minimum values in a 2 × 2 window and providing that the edge map of the image is given [5]. Although it is possible in principle to determine both the edge and gray level thresholds simultaneously by expanding the previous method, this requires excessive computation (proportional to the cube of the gray levels).This paper proposes a method of simultaneously determining the thresholds for both the edge and gray level so that the coincidence between the edge and the contour is optimized. In this method, the edge intensity is defined as the difference between the maximum and minimum values in a window; conditions that each pixel in an image is a part of a contour and/or an edge are discussed; and a set of optimum thresholds is determined with a relatively small amount of computation (proportional to the square of the gray levels) by using only a 2‐D histogram of two gray levels of the images after the maximum and the minimum filter.
Connected character recognition in cursive handwriting using selective attention model with bend processing
Authors: Shuono Hayaru , Fukushima Kunihiko 
Published: July 2007

AbstractAs one of the systems to recognize the cursive handwritten English connected character sequence, Imagawa et al. proposed a system with the selective attention mechanism. The system of Imagawa et al., however, does not have a very high recognition ability. It is a relatively small‐scale system, where the character category to be recognized is composed of 5 characters.This study extends the recognition system proposed by Imagawa et. al., and a system with a higher recognition ability is constructed. One of the authors notes that a part of the “model for selective attention” is similar to the pattern recognition system “neocognitron.” With respect to the neocognitron, it is reported that the recognition ability is improved by introducing the bend detection circuit. Consequently, the authors constructed a system, where the bend processing circuit is introduced into the system by Imagawa et al. Various test patterns are given to the constructed system, and it is verified by executing a computer simulation that the proposed system is effective in the recognition of the handwritten connected character sequence.
An object extraction method using sampled active contour model
Authors: Hashimoto Masahiro , Sakai Yoshinori , Kinoshita Hirotsugu 
Published: July 2007

AbstractThis paper proposes a new method of contour extraction using active contour models for the purpose of image structuring. Active Contour Models, such as “snakes,” are based on energy minimization, which takes a great deal of computational time. In the proposed method, the active contour models consist of sampled contour points, and each sampled contour point is guided and moves in parallel by pressure exerted perpendicularly to the contour, attraction between neighbor boundary points, and repulsion from edge. Since each contour point is independently guided by a resultant force, the proposed method has the following characteristics: noise tolerance; parallel execution; and low computational cost. Experimental results on real pictures show the effectiveness of this method.
Visual solder inspection using neural network
Authors: Koji Yukichi , Takatsu Naoyoshi , Oh Masanari 
Published: July 2007

AbstractThis paper proposes a method optically to inspect the state of each soldered lead of a semiconductor package. The surface of the soldered lead is recorded using a CCD camera from a direction perpendicular to it and illuminated from the same direction as the camera. The features of the pattern and the distribution of the brightness on soldered lead are extracted from the recorded image, so that the quality of the soldering is judged from them. It has already been proven that the method is effective to inspect bumps on a soldered part. This paper proves experimentally that the method is also effective to inspect soldered leads. The images of soldered leads have more variations than those of bumps. Therefore, the determination of condition that correctly represent the features and sections of an image is the key in this experiment. After the best conditions have been found, the experimental results using 508 samples (including 175 defective samples) show a 100 percent detection rate for defective samples and 95.7 percent of normal solderings. These results agree with those gained from human visual inspections.
A speaker‐adaptation technique for context‐dependent models represented by hidden markov networks
Authors: Takami Jun‐Ichi , Sagayama Shigeki 
Published: July 2007

AbstractThis study aims at the realization of a speaker‐independent speech recognition system based on the speaker adaptation with a supervisor. This paper describes the highly accurate speaker‐adaptation technique using a small number of training samples. When a small number of speech samples are used for adaptation there arise problems that sufficient information cannot be obtained to update simultaneously a large number of model parameters, and an estimation error is included to the statistical bias of the samples.From such a viewpoint, this paper proposes a speaker‐adaptation technique using the hidden Markov network (HMnet), which employs a smaller number of model parameters than the mixed continuous‐distributed phoneme HMM, which is independent of the phoneme context, while realizing an equal or better recognition performance. As the adaptation technique, the moving vector field smoothing (VFS) method is used. This method can realize simultaneously the interpolation for the unadapted model parameters to cope with the small number of samples and the correction of the estimation in the speaker adaptation. The standard speaker pre‐selection method also is investigated in order to improve the accuracy of the speaker adaptation.
Self‐stabilizing ring orientation algorithm under the C‐Daemon
Authors: Katayama Yoshiaki , Masuzawa Toshimitsu , Tokura Nobuki 
Published: July 2007

AbstractA self‐stabilizing algorithm is a distributed algorithm that achieves its intended behavior regardless of the initial configuration.This paper discusses the self‐stabilizing algorithm for the ring orientation problem (ROP). ROP is a problem where all processors on a ring network are to be oriented either clockwise or counter clockwise. It is known up to now for the network composed of an even number of processors that there does not exist a deterministic self‐stabilizing algorithm to solve ROP under the D‐daemon or the R/W daemon. On the other hand, a probabilistic self‐stabilizing algorithm is known for ROP on a ring network with an arbitrary size under the D‐daemon. This paper also presents a self‐stabilizing algorithm for ROP on a ring network with an arbitrary size under the C‐daemon. The result indicates that the classes of problems that can be solved by the C‐daemon and the D‐daemon, respectively, are substantially different.
Offset adjustment to reduce coding error of interpolative DPCM
Authors: Machizawa Akihiko 
Published: July 2007

AbstractInterpolative DPCM has superior prediction capabilities compared to the commonly used extrapolative DPCM, but since quantization errors accumulate during decoding, and since quantization errors are expanded by expansive coefficients that are proportional to the image size, IDPCM has the weakness that coding errors become excessive. In this paper, offsets are added to the pixel values of the image that is to be coded, where a new method is proposed for the offset adjustments such that a transformed image with smaller quantization errors results. The effectiveness of this algorithm is confirmed by simulations with real images. Since the offset values are determined by the solution of a nonlinear minimization problem with an evaluation function that is the coding error derived from the function of the offsets values and quantization errors of the adjusted image, a minimization algorithm that combines a descent method with a one‐dimensional search and which exploits properties of the evaluation function is used. Furthermore, coded data rates are estimated, and rate‐distortion curves are determined with the use of a hypothesized image probability model. By combining this method with a previously proposed subsampling method, it is possible to improve the image quality by 3 [dB], or reduce the coded rate by 0.3 [bits/pixel].