bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parallel processing on the multi‐PSI computer and its evaluation — a programming paradigm based on a small‐grain highly concurrent object model
Authors: Taki Kazuo , Ichiyoshi Nobuyuki 
Published: July 2007

AbstractMulti‐PSI is a distributed‐memory MIMD (multiple‐instruction, multiple‐data) computer that has 64 processors. Problems of knowledge processing, which are the object of the Multi‐PSI, must be divided into many partial problems in order to achieve a favorable load balance because a characteristic of the computation is the dynamic loss of uniformity. This, however, has the danger of increasing the communication overhead. Therefore, in order to constrain the communication overhead and achieve a favorable load balance, in this paper, we propose a programming method oriented to the above problem. In this methodology, the problem is formulated as multiple communicating objects and the degrees of freedom in the load allocation are maintained. On the other hand, when the load is allocated, the communication objects are estimated from the system performance and the objects' characteristics, and the processing granularity is adjusted so that it is within the tolerance. This program methodology was applied to the three program developments of the shortest path problem, the LSI routing problem, and logic simulation; each was implemented with high efficiency. For example, in the shortest path program, 260,000 small‐grained objects were distributed over 64 processors and reached about 75% efficiency. In addition, in the logic simulation composed of 12,000 objects (gates), a high absolute efficiency of 99 thousand events/second and a 48‐fold increase in speed with 64 processors were obtained. Along with confirming the effectiveness of this programming methodology, these results demonstrated. that high efficiency can be realized in parallel processing for some degree of granularity even in a distributed‐memory parallel computer.
Geometric reasoning with quantitative physical models
Authors: Okamota Yoshinori 
Published: July 2007

AbstractThis paper proposes a method of reasoning and of planning space and motion based on quantitative physical models.First, the particle‐collection representation (PCR) is proposed as a method of representing objects, and the robust simulation method of rigid‐body dynamics using PCR is discussed.Next, as a system which reasons and plans dynamic actions of rigid bodies based on this rigid‐body simulation, a planner (PCP) using physical simulation is proposed.For the planning method of PSP, the action improvement method is proposed which carries out a plan by gradually improving an original plan.To solve the problem of adjusting parameters for action in the action improvement method, the general parameter adjuster (GPA) is proposed. Moreover, the motion of bodies and carriage plannings by PSP are simulated. Furthermore, the robustness and extensibility of the PSP are investigated.
A speaker‐independent word recognition based on HMM using orthogonalized phonetic segment codebook
Authors: Matsuura Hiroshi , Nitta Tsuneo 
Published: July 2007

AbstractMatrix quantization (MQ) is a method which directly quantizes the spectrum‐time pattern. However, it has a problem in that the quantization error is relatively large compared to the vector quantization (VQ), since the dimension is large and the pattern variation is less.From such a viewpoint, this paper introduces the acoustic/phonetic structure called phonetic segment as the unit of MQ. The statistical matrix quantization (SMQ) is applied to the calculation of the error measure, where the subspace method, i.e., a statistical pattern recognition technique, is employed. The purpose of SMQ is to consider effectively the pattern variation by constructing the Orthogonalized phonetic segment codebook based on the eigenvector set representing the pattern variation for each phonetic segment. The training of HMM using the phonetic segment code sequence also is considered.The K‐best learning is proposed, where from the first to the K‐th phonetic segment sequences are equally handled. Even though the K‐best learning is much simpler than VQ, it has equal or better output probability smoothing power, and can suppress the effect of the error in the conversion of the speech to the phonetic segment code sequence.Using the (SMQ/HMM + K‐best learning) method, a high speaker‐independent word recognition performance of 96.0 percent is obtained for the 100 word data set containing similar word pairs uttered by 10 unknown speakers.
Inverse perspective projection of a line segment pair
Authors: Shakunaga Takeshi 
Published: July 2007

AbstractThis paper discusses how a line segment and segment pair in a 3‐dimensional space are constrained by an image obtained by their perspective projection. Also, it introduces the concept of polarity in the interpretation of a line‐segment image obtained under perspective projection and gives a definition of a spherical PAT curve. In addition, the relationship is explained between a PAT constraint [5], which is of an angle formed by two line segments on a plane, and the spherical PAT curve [7], which is a constraint of two line segments at an arbitrary position in a 3‐dimensional space (an extended idea of the former).Although the spherical PAT curve an be obtained formally by projecting a plane PAT curve onto a sphere, and this is justified for a semisphere, the meaning of this on the opposite semisphere has not been clarified with a justification. This paper justifies the sphere PAT curve by discussing the polarity of the segment interpretation, and explains its accurate meaning. This paper also describes the characteristics of a spherical PAT curve. The idea will have many applications to image understanding.
A method of shape description by a distribution function
Authors: Kimoto Tadahiko , Asai Motohiro , Yasuda Yasuhiko 
Published: July 2007

AbstractSome coding methods aimed at data compression for image communication and storage code the image by regions. This paper proposes a method for describing shapes of silhouette figures efficiently with a small amount of data in these coding methods. This method is one which represents the inside regions of a figure by a set of primitive structuring elements, and the primitive structuring elements are used whose contours are defined by a density distribution function.An algorithm, which automatically obtains a collection of primitive structuring elements approximating the contour of an objective region based on the thinned skeleton of the region has been designed. Moreover, based upon the multiple resolution representation of the region obtained by smoothing the contour with the Gaussian filter, the elements in the central part to the elements in the dilated parts are represented hierarchically by a tree structure.Simulations of the descriptive method were done to object regions in a natural image. Since each element has a property of mutually fusing compared to methods which decompose shapes with fixed‐shaped elements, this method can approximate the shape of the region well with less data. Moreover, by tree representation of elements, reproduction of the region at various degrees of approximation and resolution becomes possible.
A method of finding constraints by conjecture
Authors: Shimizu Hidehiro , Tahara Ikuo 
Published: July 2007

AbstractThis paper proposes a method of finding constraints by conjecture and its application to combinatorial problems. By the term conjecture is meant the strategy that people use when solving problems by trial‐and‐error, guessing the causes of failure. The problem of finding the maximal (or minimal) subsets whose elements satisfy (or do not satisfy) the conditions through selecting subsets and testing whether their elements satisfy the conditions is a typical combinatorial problem. In this case, the search process is considered to be a process of finding new constraints, and the search space can be represented by lattice.The conjecture that is based on experiences can be well formulated as the strategy for finding maximal (or minimal) constraints in such a lattice structure. The proposed method can be applied particularly to the problems such that the conditions are not given explicitly in advance.
Methods of searching lattice structure and their applications to constraint satisfaction problems
Authors: Shimizu Hidehiro , Tahara Ikuo 
Published: July 2007

AbstractThe lattice structure often is employed in the representation of the knowledge and the search space as a method to represent the combinatorial relations of concepts, attributes, conditions and facts. In the information processing based on the lattice structure, often it is required to specify the element or region in the lattice structure.This paper shows that the operations among the families of sets can be reduced to the operations among the sets, which are elements of the families. This is done by defining the new representation and the operation rules for the region in the lattice structure. Several methods for region search in the lattice structure are proposed based on the result.As a special case, the solution of the constraint satisfaction problem represented by the lattice structure is discussed. The proposed methods are not restricted by the number of elements in the whole set. They are advantageous in that the success of the search is guaranteed since the methods are independent of the order of the search.
Neural network model for generating subjective contours
Authors: Ishidera Eiki , Tsuchiya Masahiko , Takahashi Shinichi , Kurita Shouishi , Arai Hiroyuki , Miyauti Hiroko 
Published: July 2007

AbstractThe human visual system has the ability to recognize a virtual line even for a discrete object such as a dot pattern. Even if there is no difference in color or brightness, a clear subjective contour can still be perceived. This phenomenon can be formulated as an interpolation problem.This paper proposes a hierarchical visual information‐processing model based on physiological data. The model then is applied to the problem of interpolation, e.g., the perception of a virtual line and a subjective contour. To form the subjective contour, the actual outline of the visual object, the points comprising the subjective contour and the points that move to form a subjective contour must be determined. This is achieved by parallel processing in the proposed model which is composed of complex cells and hyper‐complex cells.The complex cells receive the outputs of two kinds of simple cells (S and L), and executes contour detection and interpolation of a dot pattern by global processing. The hypercomplex cell detects the end point and the point of large curvature through which the subjective contour is supposed to pass. All these processes are executed by parallel processing.When the results of processing are ready, the points comprising the subjective contour are determined by weighting. The model in this study is constructed to detect the subjective contour as well as the actual edge by assembling the information from these hierarchical processing.
Measurement of the spatial distribution of human electroretinogram with random dot pattern stimuli
Authors: Nagasaka Eiichiro , Hara Susumu , Yokota Yasunari , Usui Shiro 
Published: July 2007

AbstractThe conventional subjective perimetry has several essential problems. The establishment of a practical perimetry for objective evaluation of the visual function of the small area on the retina is desired.This paper proposes a method for measurement and analysis of the spatial distribution of the electro‐retinogram (ERG) by the random dot pattern (RDP) stimulation. The usefulness of the method as the objective perimetry is examined. In this method, multiple areas of the retina are stimulated simultaneously, which realizes a better SN ratio than the conventional local ERG method executed in the same recording time, and helps to reduce substantially the recording time.To verify the usefulness of the proposed method, RDP is constructed on the liquid crystal display, and ERG is recorded by processing the flash light. Examining the contrast, frequency of stimulation, intensity of stimulus light and background intensity of the pattern, the optimal condition for the measurement is derived. The cross‐correlation analysis for the multiinput single‐output system is applied to the obtained response, and the responses of various locations on the retina are derived.The spatial distribution of ERG determined from RDP‐ERG of the normal eye well corresponds to the known density distribution of the cones. It also is possible to determine the optic disk. Thus, the proposed method is concluded as a useful objective perimetry, which can detect a spatially small initial symptom of the retinal diseases.
An algorithm for generating dataflow diagrams
Authors: Yamamoto Shuichiro , Ohta Kenji 
Published: July 2007

AbstractVarious methods of generating dataflow diagrams use an algebraic transformation system for a given input‐output relationship. These methods require mutual transformations between the input‐output relationship and algebraic expressions, and also a consistency check between the generated dataflow diagram and input‐output relationship. This paper proposes a deterministic algorithm that uniquely generates a unique dataflow diagram with a minimal number of processes from a given input‐output relationship.
Piecewise‐linear division of region by neural networks with maximum detectors
Authors: Zhuang Jian , Amari Shun‐Ichi 
Published: July 2007

AbstractA neural network with maximum detectors divides a space which has n‐dimensions Rn into piece‐wise‐linear regions. However, there have been very limited theoretical researches concerning what kind of piecewise‐linear region divisions can be realized by a neural network, that is, concerning the formation capability of piecewise‐linear discriminate regions by a neural network.In this paper, this problem is considered theoretically. The concept of a k‐dividual region is introduced and then it is proved that a division can be realized by a piecewise‐linear machine if and only if it is k‐dividual.
A self‐recovering communication buffer based on the concept of cellular automaton
Authors: Wasaki Katsumi , Fuwa Yasushi , Nakamura Yatsuka , Eguchi Masayoshi 
Published: July 2007

AbstractThis paper presents a self‐recovering buffer memory for communication systems based on the concept of cellular automaton. The model proposed is a FIFO‐type (First‐in, First‐out‐type) memory which meets the conditions for a communication buffer and incorporates the principles of cellular automaton. By binding together a number of cells which can perform basic FIFO operations, it is found that each cell is capable of determining whether or not it is holding the first valid data in a queue based on information about its own status and it s neighboring cell.It also is observed that this model possesses a capacity for self recovery which always enables the buffer to return to a normal state in the event of an internal transient fault. Furthermore, by representing each cell with a sequential circuit, this buffer memory is prototyped with a gate array and its applicability is verified comparing it with existing FIFO design methods.
How to adjust the thresholds of feature‐extracting cells in the neocognitron
Authors: Tanigawa Masashi , Fukushima Kunihiko 
Published: July 2007

AbstractThe neocognitron is a hierarchical neural network model with pattern recognition ability. The intermediate layers of the neocognitron contain various kinds of cells (feature‐extracting cells) that extract partial features of the input patterns. The feature‐extracting cell has modifiable input connections, with the connecting weights depending on the kind of feature to be extracted. The connecting weight is determined by an unsupervised learning.When a standard pattern is given as a stimulus, the connecting weights are adjusted so that the cell exhibits the maximum output. The tolerance in deformation of the feature to be extracted by the cell (that is, feature selectivity) can be adjusted by the thresholds of the cell.This paper discusses how the thresholds of the feature‐extracting cell in the intermediate layers affect the recognition rate of the neocognitron. In the conventional neocognitrons, the same threshold values were used in both learning and recognition phases. This paper shows also that the recognition rate can be improved greatly by using higher threshold values in the recognition phase than in the learning phase.
Selection and consolidation of memorized information for distributed associative memories
Authors: Murakami Kenji , Izumida Masanori , Takechi Hirochika 
Published: July 2007

AbstractNumerous studies have been made on the method of constructing the distributed‐type associative memory. This paper discusses the method which selectively memorizes or memorizes by consolidation the information stored in multiple associative memories in a new associative memory.In the distributed associative memory, the information (vector) to be stored is memorized in a distributed way in the form of a matrix (called memorization matrix). Then, in general, it is difficult to know precisely the original memorized information from the already constructed associative memory.This paper proposes a method which can realize the selection and consolidation of the memorized information by constructing directly the memorization matrix of the new associative memory, using the memorization matrices of the already constructed multiple associative memories. The proposed method has the feature that it is not necessary to derive the information memories in each associative memory or to reconstruct the associative memory from the start using the memorized information (relearning). It is a requirement which arises frequently in the construction, update and use of the associative memory to memorize selectively or in a consolidated form the information memorized in multiple associative memories, in an associative memory. For such a purpose, the proposed method will be useful.
Application of object‐oriented attribute grammars (OOAG) to software development environments
Authors: Gondow Katsuhiko , Imaizumi Takashi , Hagiwara Takeshi , Katayama Takuya 
Published: July 2007

AbstractIt is recognized as necessary to have a software development environment that can simultaneously store software products and maintain their detailed relationships. There exists the cut & paste model based on attribute grammars, which is effective in maintaining consistency among software products and in automatically maintaining the derived values. This model has a problem however, namely the description of the dynamical aspect of the software development environment is difficult. From such a viewpoint, an object‐oriented attribute grammar type computation model OOAG has been proposed, which introduces the concept of the message passing into attribute grammars. The OOAG is defined with an extension and reorganization in regard to the dynamical description functions. Then, the problem in the cut & past model are discussed. As an example of the problems, it is pointed out that description is difficult for the case where the point of referral by the user and the point of modification are different. Such a situation is described by OOAG, demonstrating that OOAG can remedy the problem in the cut & paste model.
A method of post‐processing for character recognition based on syntactic and semantic analysis of sentences
Authors: Kise Koichi , Shiraishi Tadamichi , Takamatsu Shinobu , Fukunaga Kunio 
Published: July 2007

AbstractPost‐processing of character recognition refers to the processing used to correct the errors in character recognition. When the input is a string representing a sentence in the highly precise error correction, it is desired that the syntactic as well as semantic examinations should be made at the sentence level.This paper assumes that the morphemes, syntax and semantics of the input sentence can be analyzed, and proposes a method that uses the syntactic and semantic analysis in the post‐processing. The proposed method receives the list of candidate characters up to the fifth, and outputs the sentence that is adequate from the viewpoints of both syntax and semantics. The method features the following three points: (1) in word matching, it is examined also whether or not a sentence adequate from the viewpoints of syntax and semantics can be composed, and then the inadequate words extraction is inhibited; (2) characters having stronger syntactic and semantic constraints, such as the single‐character particle and the conjugational suffix, are estimated top‐down. Then, the case where the adequate character is not contained in the candidates can be handled; and (3) the words for which the adequateness cannot be determined from the syntactic or semantic viewpoint are selected by character re‐recognition processing. An experiment is executed for 50 sample sentences. The character recognition rate is improved from 83.0 percent to 98.0 percent, and the sentence recognition rate is improved from 10.0 percent to 94.0 percent. Compared to the method based only on word matching, the sentence recognition rate is improved by more than 20 percent. In other words, the effectiveness of the proposed method is demonstrated.
Influence of noises added to hidden units on learning of multilayer perceptrons and structurization of networks
Authors: Kurita Takio , Asoh Hideki , Umeyama Shinji , Akaho Shotaro , Hosomi Akitaka 
Published: July 2007

AbstractThis paper investigates the influence of noises added to hidden units of multilayer perceptrons. It is shown that a skeletal structure of the network emerges when independent Gaussian noises are added to inputs of hidden units during the error back‐propagation learning. By analyzing the average behavior of the backp‐ropagation learning to such noises, it is shown that the weights from hidden units to output units tend to be small and outputs of hidden units tend to be 0 or 1. This means that the network is automatically structurized by adding the noises. As the result, it is expected that the generalization ability of the network is improved. This network structurization was confirmed by experiments of pattern classification and logic Boolean function learning.
Processible video codec on camera operations
Authors: Miyamori Hisanishi , Taima Tohru , Tominaga Hideyoshi , Hanamura Tsuyoshi 
Published: July 2007

AbstractThis paper proposes processible video codec on camera operations (PVCC) which uses two video data (camera parameters and image contents) to improve the efficiency of video editing. Image data are separated in the coding; they are selected and synthesized in the decoding. Conditions are set for the relationship between the positions of a camera and its object so that data separation is simplified in the decoding. The system using test patterns shows that the system has an average SNR of about 50 [dB] with accurate camera parameters, the value being sharply deteriorated with an increase of errors in the parameters. Simulations of camera operation and data editing successfully confirm the expected effect of the proposed method. A simple language describing the camera improves the speed of video editing and increases content readability.