bluuebunny/crossref_metadata_2025_split huggingface dataset:
Back propagation in time‐series forecasting
Authors: Lachtermacher Gerson , Fuller J. David 
Published: July 2007

AbstractOne of the major constraints on the use of back propagation neural networks as a practical forecasting tool is the number of training patterns needed. We propose a methodology that reduces the data requirements. The general idea is to use the Box‐Jenkins model in an exploratory phase to identify the 'lag components' of the series, to determine a compact network structure with one input unit for each lag, and then apply the validation procedure. This process minimizes the size of the network and consequently the data required to train the network. The results obtained in eight studies show the potential of the new methodology as an alternative to the traditional time‐series models.
High‐speed template matching algorithm using information of contour points
Authors: Hashimoto Manabu , Sumi Kazuhiko , Sakaue Yoshikazu , Kawato Shinjiro 
Published: July 2007

AbstractTemplate matching is a useful technique for matching images. This paper proposes a high‐speed template matching technique which is effective for images that have sharp contours. The method uses only the image contour parts as one‐dimensional templates. Although it can retain fine patterns, the data compression ratio and speed are very high. To improve reliability of matching, gray gradient information and intensity of contour points are used. Also, dilation of contours can reduce several errors due to disturbance of the contour or scaling. The algorithm herein can indicate differences between the template and the target image automatically after the alignment of images.The expanded algorithm applying the sequential similarity detection algorithm (SSDA) method also is discussed. Software simulation proved that the algorithm is 10 or 200 times faster than the conventional template matching technique which uses the cross‐correlation estimation between two‐dimensional (2‐D) template and the target image. This algorithm was applied to special hardware. It can align two 512 × 512 pixels images in 40 ms when the size of the search area is 64 × 64.
Generation of a hierarchical representation for graphic patterns based on grouping
Authors: Soga Masato , Toyoda Jun'Ichi , Nitta Yusuke , Imanaka Takeshi , Yanagida Masuzo 
Published: July 2007

AbstractThe ability to retrieve by similarity is one powerful way to improve the human interface in an image database. In this paper, graphic patterns constructed as a set of primitive patterns formed from closed regions are the target images. When recognizing this kind of graphic pattern, people perform grouping. The partial patterns formed by this grouping play a major role in the similarity between graphic patterns. Consequently, the partial patterns that result from grouping must be introduced into the image representation as search keys. Furthermore, it would be desirable to have this representation automatically generated. In this paper, we propose a method where a representation in the part‐of hierarchy of partial patterns is used as the graphic pattern representation; this representation is generated from the raw image of the graphic pattern. This method uses the rules for visual characteristics for grouping in humans. First, partial patterns are formed by bottom‐up processing. Then, by comparing the stability of the final partial patterns, partial patterns that do not match human perception are deleted and missing partial patterns are searched for and added. A prototype system was built based on this method, and the method's adequacy was verified.
Construction of a distributed computer network containing ring connections
Authors: Kanada Hajime 
Published: July 2007

AbstractAs a connection method for a LAN, which connects computers and various other equipment (called processors hereafter), a token ring system is currently used. Any two processors on a ring can communicate with each other directly. As one fundamental problem for distributed algorithms in a network of several rings connected by links, the problem of parallel data transmission between processors is discussed in this paper. In the parallel data transmission problem, a predetermined processor holding data with specified addresses sends the data to the specified addresses in parallel. Given the numbers of processors and rings, the minimum computation time for data exchange between the processors, and conditions on the network configuration to achieve that minimum are obtained while keeping the number of links minimum.
Robust object detection under various environmental conditions
Authors: Maeda Eisaku , Ishii Kenichiro , Takahashi Yasuko 
Published: July 2007

AbstractAn algorithm for object detection is presented. This method is robust against brightness variation and does not depend on the position, size, background pattern, shape, or color of target objects. The method consists of three processes: (1) normalize the brightness of the target and reference images; (2) calculate features, called the normalized principal component features; and (3) construct a classifier by statistical learning. The method is applied to car detection in a parking lot. Under various conditions, at least 98 percent of the cars were detected correctly. Application to moving‐car detection and person detection also is presented.
Reconstruction of emission tomographic images using the compound gauss‐markov random field
Authors: Kudo Hiroyuki , Saito Tsuneo 
Published: July 2007

AbstractStatistical quantum noise is a major factor causing degradation in emission computed‐tomography (ECT) images. The maximuma posterioriprobability (MAP) estimation has been used to mitigate the noise problem with limited success. The two major shortcomings are the oversmoothing of edges by the homogeneous random field used as the image model, and the lack of well‐defined procedure for estimating the parameters of the image model.This paper proposes a new algorithm for reconstructing the ECT images that will solve the problems of the existing methods. The proposed algorithm uses a compound Gauss‐Markov random field that can accurately model the sharp transition of edge regions as well as the smoothness of the bland regions. The image model parameters are derived from observed data using the maximum likelihood (ML) estimation, and the image reconstruction is based upon the joint MAP estimation. These two estimation problems are solved simultaneously in a joint MAP‐ML estimation scheme. The optimum solution of the joint MAP‐ML estimation problem is obtained using the generalized expectation‐maximization (GEM) algorithm.
An immune network model and its applications to process diagnosis
Authors: Ishida Yoshiteru 
Published: July 2007

AbstractImmune systems, like neural systems, have a highly sophisticated capability of pattern recognition. However, their recognition and learning mechanisms are quite different from those of a neural system. Neural network models (connectionist models) are information models, which derive partially from the study of the mechanism.In the same manner, an information model is proposed which derives partially from the recognition mechanism of immune systems, and the learning algorithms on the model are studied.This paper also proposes some extensions of the model so that it can be applied to process diagnostic problems. The instrumentation system with this immune network (sensor network) can eliminate abnormal information from faulty sensors autonomously. Other than diagnostic problems, the immune network model is potentially applicable to mutual/group test of a set of VLSI of the same type, computer network immune to the virus.
Optimum image restoration filters and generalized inverses of operators
Authors: Yamashita Yukihiko , Ogawa Hidemitsu 
Published: July 2007

AbstractAn optimal restoration filter is a restoration filter which meets some optimization criterion. It is known that a close relationship exists between optimal image restoration filters and generalized inverses of operators. By clarifying this relationship, the understanding of both optimal image restoration filters and generalized inverse is deepened.This paper clarifies the following points concerning the aforementioned relationship. First, the projection filter and averaged projection filter satisfy an optimal criterion in some restricted subspace. Furthermore, it is shown that whether that optimal criterion is evaluated in the original image space or the observed image space, the same result is achieved. Finally, it is shown clearly how the Wiener filter behaves as a generalized inverse.
Variable‐rate transform coding that controls quality of image using human visual model
Authors: Harada Haruyuki 
Published: July 2007

AbstractThis paper defines a quantitative measurement SNRq for the evaluation of image quality in the discrete cosine transform domain considering human visual characteristics. A new coding algorithm which minimizes the bit‐rate for a given target SNRq also is obtained. When coding the image using the proposed algorithm, the bit‐rate varies according to the image busyness, but this does not present a problem because the image is stored in memory. Furthermore, it is not a problem when transferring the image if only the packet‐switched networks are used. Using computer simulation, the value of this quantitative measurement (the target SNRq) is found so that the differences between the original and the processed images were negligible.
Construction of fault‐tolerant mesh‐connected highly parallel computer and its performance analysis
Authors: Takanami Itsuo , Inoue Katsushi , Watanabe Takahiro , Oka Minoru 
Published: July 2007

AbstractA reconfiguration scheme is proposed in which a mesh‐connected highly parallel computer is divided into groups of PEs with small mesh‐structures, a spare row is added to each group (in what follows, such a group with a spare row is called a plane), these planes are successively connected upward and downward, and finally the top and bottom groups are connected. The scheme has such features that: (1) although switchings for reconfiguration are done locally, compensations are done globally, considering the distribution of faults over the whole planes; and (2) switching algorithm and circuits are simple and hence our scheme is suitable for dynamic reconfiguration.First, a method for repairing faults is described, and the necessary and sufficient condition for repairability is given. Next, formulas for the reliabilities of systems are given. Using these formulas, an example of computing the improvement degree of MTTF is illustrated and the result is compared with those in the literature. The probabilities of system survivals against the number of faulty PE's also are analyzed and the results are compared with those in the literature. Finally, logic circuits for the reconfiguration are shown and the correctness of their behavior is proved.
A hierarchical method for block segmentation and classification of general document images
Authors: Park Young Seak , Ebina Tsuyosi , Ito Akira 
Published: July 2007

AbstractIn a document analysis system, block segmentation and block classification are very important. The former segments a particular document image into homogeneous rectangular blocks. The latter classifies the segmented blocks into categories. These classified blocks may then be processed by suitable recognition systems. In this paper, we formalize the structure styles of general documents, and then propose both a robust hierarchical method of block segmentation and a simple method of block classification. The proposed block segmentation method takes a top‐down hierarchical approach based on the spatial features and formalized concepts of document structure. This method is essentially independent of the document style, and can perform a type of structural analysis of the document image. The classification approach is based on a new scheme of statistical textual features, and classifies the segmented blocks into four categories: text blocks, title letter blocks, line drawing (or graphics) blocks, and halftone phonograph blocks. The proposed approaches were implemented using the C programming language in an X‐Window environment under the UNIX operating system. The performance of each approach was experimentally evaluated, for both effectiveness and computational efficiency, using actual test images.
Piecewise‐linear approximation of discontinuous contour images based on clustering procedure
Authors: Watanabe Takashi , Suzuki Kazuya , Yokoyama Ryuhzou , Tanba Sumio 
Published: July 2007

AbstractThis paper discusses the problem of the piecewise‐linear approximation of contour images. Almost all the piecewise‐linear approximation methods that have been proposed can be applied only for continuous contours. Methods that can work well for discontinuous contours, for instance, have not yet been found.In this paper, a new method is proposed based on clustering as a piecewise‐linear approximation method that can even be applied to discontinuous contour images. Specifically, the method uses hard clustering or fuzzy clustering, where the set of edge points in the image is partitioned into line segment groups and parameters of line segments are computed from the groups. Good results were obtained in the evaluation experiment to verify the effectiveness of the proposed method.
Load balancing method based on load vector
Authors: Ri Sotetsu , Ji Yusheng , Asano Shoichiro , Matsukata Jun 
Published: July 2007

AbstractIn the distributed processing applications, the dynamic load balancing is considered to be important. In most of the past studies concerning the dynamic load balancing, where the load is distributed based on the information during the job execution by the system, the load of a computer is defined as the number of jobs in execution on the computer. In other words, the computer resources are given little consideration. Even if the computer resources are considered, the model is defined as a homogeneous system composed of computers of the same performance, which seems to deviate from reality.From such a viewpoint, CPU and the input/output units such as disk are considered as the computer resources, and are represented by the load vector in this paper. A relatively simple dynamic load balancing algorithm using the load vector is proposed. The method is extended so that it is applicable to the non‐homogeneous system composed of computers with the same function but with different speeds.The proposed method is simulated by a model in which computers are connected through a bus‐type network. As a result, various effects were recognized, such as the decrease of the mean response time, the decrease of the variation of the response time, and the effective use of a high‐speed computer in the heterogeneous system.
Training neural net classifier to improve generalization capability
Authors: Kayama Masahiro , Abe Shigeo 
Published: July 2007

AbstractA training method for neural net classifiers is discussed from the viewpoint of improving their generalization capability. First, the conventional training method which minimizes the square sum of network output errors from training outputs is shown to be inappropriate. This is because category boundaries may be close to some specific clusters which decreases the generalization capability of the network. Then to obtain impartial boundaries to all clusters, a new method is proposed which adds appropriate random numbers to the training inputs and decreases their amplitude to zero as training proceeds. The effectiveness of this method is demonstrated by simulations of alphabet and practical number recognition systems. The proposed method is useful, especially when the quality and quantity of training data are not sufficient. This is particular for cases where a classification system should be constructed quickly with a few representative training data or considerable time or money is required to obtain voluminous training data.
Object surface construction from volume data with appropriate topology
Authors: Nagae Takanori , Agui Takeshi , Nagahashi Hiroshi 
Published: July 2007

AbstractThe reflection, diffusion, transparency and refraction of a ray on the surface of an object are essential elements to the object. Such optical interference by knowing each intersection of a ray and the surface of the object together with the normal vector at the intersection. In most conventional methods, the surface of an object is detected from a set of volume data, and a shading process is applied to it. This process has a difficulty in forming a continuous surface of an object since the volume data consist of discrete elements. The topology of an object surface also is important in a reconstruction of a 3‐dimensional model (e.g., by laser stereo lithography) in which the surface should be closed with no intersection.This paper proposes two types of algorithms for reconstruction of the surface of an object: the modified marching cubes algorithm (a modification of the marching cubes algorithm); and the deformed cubes algorithm. Each of the proposed algorithms reconstructs a sufficiently smooth and topologically appropriate surface of an object.
Continuous speech recognition by sentence spotting applying the vector continuous dynamic programming to output of partial matching method
Authors: Oka Ryuichi 
Published: July 2007

AbstractThis paper proposes a speaker‐independent continuous speech recognition system on sentence spotting. The system is composed of the following three parts: (1) construction of three‐connected demi‐phoneme standard patterns; (2) description of sentence set by demi‐phoneme network; and (3) sentence spotting by “Partial Matching Method” and “Vector Continuous DP.”A sentence spotting recognition experiment was conducted in which each of 10 open speakers uttered 11 sentences (110 sentences in total, which form a task of the average branching factor of 4.1 and the number of words 113). The sentence recognition rate of 76.4 percent was obtained (word recognition rate of 94.5 percent in the sentence).In the proposed system, three connected demi‐phoneme standard patterns are constructed using only 492 kinds of balanced word sets, and no training by the continuous speech is applied. The complete frame synchronization is established in the system from the waveform analysis to the sentence spotting.
High‐quality image magnification applying the gerchberg‐papoulis iterative algorithm with DCT
Authors: Shinbori Eiji , Takagi Mikio 
Published: July 2007

AbstractThis paper proposes an image magnification method “IM‐GPDCT,” which is an iterative application of the Gerchberg‐Papoulis (GP) algorithm with the discrete cosine transform (DCT), and its performance is evaluated. Conventional image magnification by interpolation has a problem in that degradation of image quality is inevitable since essentially it is impossible to restore the spatial high‐frequency components which are lost in the observation process. For this point, IM‐GPDCT improves image quality of a magnified image by utilizing a concept to restore the spatial high‐frequency components which are lost in the observation.IM‐GPDCT uses the GP algorithm as the basic principle for extending the frequency band. The spatial high‐frequency components are restored during the forward and inverse iterative transform process for the image by DCT, using two constraints that the spatial extent of an image is finite, and correct information is already known for the low‐frequency components. The proposed method is compared to three conventional interpolation methods from the viewpoints of a restoration error and image quality. Restoration error performance results show that IM‐GPDCT outperforms the interpolation methods from the viewpoint of the restoration error. Simulation results show also that the presented method improves the image quality of the magnified image by obtaining image sharpness, nonjagged edges and reproduction of the original texture.
Design and performance evaluation of flash memory back‐up systems
Authors: Takakura Hiroki , Kambayashi Yahiko , Kambayashi Yahiko 
Published: July 2007

AbstractMain memory databases are a promising approach to the realization of high‐performance systems since they do not require low‐speed secondary storages. One of the critical problems of such systems is the volatile nature of main memory. Hence, nonvolatile secondary storage cannot be removed for back‐up and recovery. The authors have developed continuous back‐up systems which realize low‐overhead back‐up procedures and quick recovery.A recent development has been flash memory, which can maintain its contents without electric power supply. It is expected that flash memory will realize high‐speed nonvolatile storage. There are, however, some characteristics which are different from disk storages. For example, in flash memory, the block size of a sequential access is very small, e.g., 256 bytes. Thus we cannot use sequential access to retrieve large amounts of data, although optimization to utilize sequential access need not be considered.Although flash memory seems to be a good choice for secondary storages, the number of rewrites to a memory cell determines its lifetime. Current flash memory cannot be used as conventional secondary storage. Therefore, this paper discusses system architectures which utilize flash memory as back‐up storage. Special consideration is given to reducing the number of rewrite operations. It is expected that in the proposed systems, flash memory storage can survive over 10 years. Performance evaluation is also discussed.
A solution for combinational optimization problems using a two‐layer random field model‐mean‐field approximation
Authors: Igarashi Harukazu 
Published: July 2007

AbstractIn the solution of the combinational optimization problem such as the traveling salesman problem, the usual approach is to define the energy function, which consists of the term representing the cost to be minimized and the terms representing the constraint for the solution. It is important at this stage to define adequately the weight coefficients for the constraint terms. For this purpose, a solution method based on the two‐layer random field model has already been proposed.However, it is desirable from the viewpoint of the processing speed to apply the deterministic annealing to the analog neuron system obtained by the mean‐ield approximation, rather than to apply directly the simulated annealing to the binary neuron system. In his case, it is important also to define adequately the weight coefficients in the energy function.This paper considers the already proposed method which automatically adjusts the weight coefficients using the two‐layer random field model. An elaboration is presented which applies the method to the search of the optimal solution by the deterministic nnealing. In this study, the connection machine CM‐2), which is a SIMD‐type parallel computer, is used to handle the relatively large‐scale problem composed of 64 cities.
Motion extraction by spatiotemporal filtering of analytic signal derived from images and moving area tracking
Authors: Tanaka Kyoji , Shirai Yoshiaki 
Published: July 2007

AbstractWe propose a method for tracking a moving object in a specified direction from time sequence images which include multiple moving objects, assuming that a camera rotates to look at the specified object. First, an image analytic signal is generated by spatial‐Hilbert transform. The horizontal and vertical motion of specific velocities are extracted by spatiotemporal filters applied to the analytic signal. Although the impulse response function of a temporal filter for the analytic signal is complex, that of a spatial filter becomes real. The 2‐D motion component is computed from the extracted horizontal motion and the vertical motion. The tracking window is set to the high motion component area. Object tracking is performed by estimating the motion through an α‐β‐γ filter on the window.