bluuebunny/crossref_metadata_2025 huggingface dataset:
Forecasting market potential and market penetration of residential water heater load control programs
Authors: Wood Lisa L. , Mauskopf Josephine A.
Published: July 2007

This paper presents a model which estimates market potential and forecasts market penetration for one demand‐side management (DSM) programwater heater load controlin the service territory of Virginia Power Corporation, a large electric utility in the south‐eastern United States. Water heater load control is a voluntary program where customers are paid a monthly incentive to allow the utility to shut off power to their electric water heaters during periods of peak demand. Reducing the level of peak demand through DSM programs is one way for utilities to avoid building new power plants. The current total energy (or demand) impact due to a load control program is the sum of the changes in energy (or demand) for all program participants. The projected energy and demand impact due to a load control program is the average change per participant multiplied by the number of participants or adopters of the program. While it is reasonably straightforward to measure the energy savings resulting from shutting off power to a water heater, the more difficult task for planning purposes is forecasting the number of customers who will actually join the program (i.e. the market penetration) for a given incentive. The customer decision process is divided into three stages: eligibility, awareness, and adoption. The responsiveness of market penetration to changes in advertising and incentive amounts is demonstrated. In addition, the impact of changing advertising and incentive amounts on the percentage of aware customers who adopt the program and on that of eligible customers who become aware of the program is estimated. This model can be used by utility planners and managers to forecast the market penetration of both new and existing load control programs. In addition, it can be employed to estimate the impact of various promotion and marketing schemes on both market potential and market penetration.
Criterion‐referenced judgemental forecasting models
Authors: Remus William E.
Published: July 2007

Human judgements are usually made with reference to a criteria such as cost or profit. When making a judgement model for such a decision, the ideal is for the model to yield near‐optimal results in terms of the criteria. This article starts with the theory behind concave criteria and then develops a mathematical argument which gives guidance to judgemental model building. This guidance departs from the conventional wisdom of using only R‐squared in model selection.
Forecasting for business planning: A case study of IBM product sales
Authors: Wu L. S.‐Y. , Ravishanker N. , Hosking J. R. M.
Published: July 2007

This is a case study of a closely managed product. Its purpose is to determine whether time‐series methods can be appropriate for business planning. By appropriate, we mean two things: whether these methods can model and estimate the special events or features that are often present in sales data; and whether they can forecast accurately enough one, two and four quarters ahead to be useful for business planning. We use two time‐series methods, Box‐Jenkins modeling and Holt‐Winters adaptive forecasting, to obtain forecasts of shipments of a closely managed product. We show how Box‐Jenkins transfer‐function models can account for the special events in the data. We develop criteria for choosing a final model which differ from the usual methods and are specifically directed towards maximizing the accuracy of next‐quarter, next‐half‐year and next‐full‐year forecasts. We find that the best Box‐Jenkins models give forecasts which are clearly better than those obtained from Holt‐Winters forecast functions, and are also better than the judgmental forecasts of IBM's own planners. In conclusion, we judge that Box‐Jenkins models can be appropriate for business planning, in particular for determining at the end of the year baseline business‐as‐usual annual and monthly forecasts for the next year, and in mid‐year for resetting the remaining monthly forecasts.
Conservatism and consensus‐seeking among economic forecasters
Authors: Batchelor Roy , Dua Pami
Published: July 2007

This paper uses the track records of a panel of US economic forecasters participating in a consensus forecasting service to test for conservatism and consensus‐seeking behaviour. The tests are based on a particular method‐of‐moments estimator, designed to allow for the heteroscedasticity and serial correlation which is inevitably present in errors from repeated forecasts for fixed target dates. Most forecasters prove to be conservative. When revising forecasts they give too much weight to their own past forecasts. Surprisingly, forecasters are not consensus‐seeking but ‘variety‐seeking’. When revising forecasts, they give too little weight to the known forecasts of other forecasters.
A note on diagrams for turning‐point diagnostics
Authors: Jarrell Stephen B. , Stanley T. D.
Published: July 2007

A new diagram for discriminating a forecasting technique's history with respect to the two types of turning‐point errors, missed turns and false signals is presented. This diagram extends Theil's original prediction‐realization (P‐R) presentation so that each of the four quadrants and the axes locates a distinct type of forecasting error or correct forecast, thus reducing much of the former ambiguity. This improvement is accomplished without the loss of any information.
Structural adjustment in the UK and Europe under the ERM
Authors: Meen Geoffrey P.
Published: July 2007

The paper has three main objectives; first, to explore in more detail the properties of the OEF world model; second, to examine within the context of that model the process of structural adjustment in Europe since the establishment of the ERM and, third, to ask whether there are differences between the UK and the rest of Europe that might make the adjustment process to ERM membership difficult for the former. Differences in the housing market are highlighted.
Oil shocks: How can OECD countries manage them best?
Authors: Delessy Henri , Harasty Hélène
Published: July 2007

As the 1990‐91 Gulf crisis has emphasized, the risk of new oil shocks remains high in the medium to long run. Although energy intensity has decreased in the major countries since the first two oil shocks, the simulation performed with the MIMOSA world model, which is described in this paper, shows that a permanent rise in oil prices still induces direct strong negative consequences in the OECD: a temporary recession, a durable loss in production and employment and a lasting rise in inflation. Moreover, according to the model and due to national dissimilarities, an oil shock in Europe has some asymmetrical effects which are pointed out here. Further simulations test two different economic policy responses in the OECD: a ‘beggar‐thy‐neighbor’ policy in which each country tries to ‘export’ its unemployment by curbing domestic inflation and wage growth; and a co‐ordinated policy supporting both supply and demand. The first leads to a general deflationist overshooting. The second ensures stabilization with a much lower cost in employment.
ARIMA models of the price level: An assessment of the multilevel adaptive learning process in the USA
Authors: Dua Pami , Ray Subhash C.
Published: July 2007

This paper estimates the ARIMA processes for the observed and expected price level corresponding to the three‐level adaptive expectations model proposed by Jacobs and Jones (1980). These univariate processes are then compared with the best‐fit ARIMA model. The results indicate that the best‐fit model for the observed price level is a restricted version of the two‐level adaptive learning process specified in terms of prices, suggesting a simple adaptive rule in the inflation rate. A comparison of the time‐series forecasts from the best‐fit model with the mean responses to the ASA‐NBER survey shows no significant difference in their accuracy. The time‐series forecasts are, however, conditionally efficient. The best‐fit ARIMA model for expected prices measured by the ASA‐NBER consensus forecasts does not correspond to any version of the Jacobs and Jones model.
The dynamic and stochastic instability of betas: Implications for forecasting stock returns
Authors: Lin Winston T. , Chen Yueh H. , Boot John C. G.
Published: July 2007

The purpose of this paper is to simultaneously investigate several important issues that feature the dynamic and stochastic behavior of beta coefficients for individual stocks and affect the forecasting of stock returns. The issues include randomness, nonstantionarity, and shifts in the mean and variance parameters of the beta coefficient, and are addressed within the framework of variable‐mean‐response (VMR) random coefficients models in which the problem of heteroscedasticity is present. Estimation is done using a four‐step generalized least squares method. The hypotheses concerning randomness and nonstationarity of betas are tested. The time paths, sizes, and marginal rates of mean shifts are determined. The issue of variance shift is examined on the basis of five special tests, called T*, B, S', G and W. Then the impacts of the dynamic and stochastic instability on the estimation of betas is tested by a nonparametric procedure. Finally, the VMR models' ability of forecasting stock returns is evaluated against the standard capital asset pricing model. The empirical findings shed new light on the continuing debate as to whether the beta coefficient is random and nonstationary and have important implications for modeling and forecasting the measurement of performance and the determination of stock returns.
The maximum and minimum of primary forecasts
Authors: Cain M. , Law D. , Peel D. A.
Published: July 2007

The purpose of this paper is to suggest that the maximum (or minimum) of a number of primary forecasts may make a valuable addition to the forecasting accuracy of a combination of forecasts. Such forecasts are readily computable. Theoretical results are presented for two unbiased forecasts with correlated normally distributed errors, showing that the maximum (minimum) of two forecasts can have a smaller error variance than either of the primary forecasts and the forecast error can have low correlation with the primary errors. Empirical results are obtained for two different sets of forecasts available in the literature, and it is observed that a combination forecast including the maximum and/or minimum has attractive forecasting properties.
Modeling expert forecasting knowledge for incorporation into expert systems
Authors: Hamm Robert M.
Published: July 2007

The use of continuous multivariate models to represent experts' knowledge of relations among a set of variables is reviewed. Such knowledge models can be incorporated into expert systems, complementing contingent rules, especially when representing experts' knowledge of functional relations among entities in noisy domains. Past work has most commonly involved linear averaging models in static domains, although nonlinear models and dynamic domains are also possible. Detecting errors in continuous multivariate models requires a different approach from detecting errors in collections of if‐then rules. Methods for eliciting expert knowledge include modeling judgments made in real or hypothetical situations and using expert's self‐insight directly to assist in construction of the model. Procedures for managing each of these methods have been computerized and could be included as elicitation tools in expert system building environments.
Composite forecasts, non‐stationarity and the role of survey information
Authors: Holly S. , Tebbutt S.
Published: July 2007

In this paper, using composite predictors we examine whether the use of survey information on consumer confidence would have helped to predict fluctuations in economic activity. We also consider the implications of the new literature on time‐series modelling when the underlying processes are not stationary. We then examine what implications this has for the construction of composite predictors. We find that it is essential that any forecast—used as part of a composite predictor—is co‐integrated with the outcome. It is likely that this will hold in practice, but if it does not then the forecast errors will be non‐stationary and the interpretation of the composite predictor hazardous.
Forecast intervals of net migration: The case of the netherlands
Authors: Beer Joop De
Published: July 2007

In the Netherlands, as in many other countries, annual fluctuations in net migration are larger than those in births and deaths. As a result, forecasts of net migration are an important source of errors in population forecasts, particularly in the short run. In order to make it possible for the user to judge the usefulness of a population forecast, the forecaster should give an indication of the degree of uncertainty of the forecast of net migration. An ARIMA model can be used for specifying a statistical forecast interval. As the width of forecast intervals for migration in single years differs strongly from that of an interval for average migration during the forecast period, it is important that the forecaster indicates which type of interval is presented. A comparison of forecast intervals for net migration obtained from an ARIMA model to intervals in official Dutch national population forecasts shows that the uncertainty on migration has been underestimated in past official forecasts.
Discretization of stochastic differential equations and econometric forecasting: An application to time‐varying autoregressions
Authors: Neftci Salih N.
Published: July 2007

Continuous time versions of time varying Vector Autoregressions are stochastic differential equations. Optimal discretization of Stochastic Differential Equations cannot be obtained by replacing all differentials by the corresponding first differences. In this paper we obtain the optimal discretization for time varying VARS. The results are applied to predicting the consumer price index.
A smart automated macroeconometric forecasting system
Authors: Moss Scott , Artis Michael , Ormerod Paul
Published: July 2007

A smart, automated forecasting system is a kind of expert system for generating forecasts wholly or partly without human intervention. A pilot‐scale system is reported in this paper. The interventions are made by a rulebase which describes the actual intervention procedures of the London Business School Centre for Economic Forecasting on one of the major macroeconometric forecasting models for the U.K. economy. The rulebase is sufficiently general as to be applicable to any forecasting model. One difference of the pilot model reported in this paper from conventional models is that policy behaviour is described entirely by rules rather than equations. This allows the use of thresholds, floors, ceilings, and discontinuities.
Forecasting us home sales using bvar models and survey data on households' buying attitudes for homes
Authors: Dua Pami , Smyth David J.
Published: July 2007

This study uses Bayesian vector autoregressive models to examine the usefulness of survey data on households' buying attitudes for homes in predicting sales of homes. We find a negligible deterioration in the accuracy of forecasts of home sales when buying attitudes are dropped from a model that includes the price of homes, the mortgage rate, real personal disposable income, and die unemployment rate. This suggests that buying attitudes do not add much to the information contained in these variables. We also find that forecasts from the model that includes both buying attitudes and the aforementioned variables are similar to those generated from a model that excludes the survey data but contains the other variables. Additionally, the variance decompositions suggest that the gain from including the survey data in the model that already contains other economic variables is small.
An estimation model of figure segregation based on human visual perception
Authors: Shimaya Akira , Yoroizawa Isamu , Kosugi Makoto
Published: July 2007

When observing an overlapped figure, a human tends to interpret the figure by decomposing it into simpler subfigures. In psychology, this attitude is called figure segregation. In general, an overlapped figure can be segregated in many ways, depending on the observer. In the engineering realization of the figure segregation, the frequency of selection for each segregation candidate must be estimated.

Up to now, such factors as symmetry and continuity have been considered qualitatively as the factors affecting the decision about the segregation of the figure. This paper presents first a method to describe quantitatively those factors. Then the significance of the decision factor is determined by comparing the characteristic values of the decision factor in the segregation candidate and the selection frequency of that candidate in the psychological experiment. Furthermore, it is shown that the figure segregation characteristics can be estimated accurately, based on the prediction expression derived from the linear multiple regression analysis.
Analysis of the data concentration function of a four‐layer neural network in terms of the autoassociation and PPN models
Authors: Yonekura Tatsuhiro , Miyazaki Shin‐Ya , Toriwaki Jun‐Ichiro
Published: July 2007

This paper presents a systematic discussion of the relationship between classical multivariate analysis and various data compression methods arising from the nonlinear mapping capability of multilayer neural networks. The important points of a geometrical interpretation for the case of four or more layers are set down using the well known autoassociation model and the pulse‐input/pattern‐output network (PPN) model proposed by the authors. Next, the previously unused four‐layer autoassociative model is investigated and its effectiveness is demonstrated. Then, the four‐layer autoassociative mapping model and the four‐layer PPN are compared using a method based on multivariate analysis. That is, it is shown that each method can be related in an approximate fashion to piecewise‐linear data compression models as well as to factor analysis models. Finally, to back up these studies, several example experiments are described; a five‐layer autoassociative mapping model is then examined, and the data compression capabilities of all three models are compared.
Progressive coding of color‐quantized images
Authors: Kumazawa Hiroyuki , Tomita Satoru
Published: July 2007

Progressive coding of color‐quantized images, a technique that allows a progressive increase in the number of image colors transmitted, is described. In most color‐quantized image coding techniques, the representative colors are assigned indices that bear no logical relationship to them. In this paper, algorithms that assign indices logically related to the representative colors are presented and it is shown that bitplane transmission with the indices assigned in this manner allows progressive transmission of color‐quantized images. Two coding algorithms are proposed: runlength coding of independent bitplanes and predictive coding based on the correlation between neighboring pixels and on interbitplane correlation. The coding efficiencies of the two methods for various kinds of color‐quantized images are evaluated. Predictive coding can reduce entropy by 10 percent for photographic images and by 30 percent for computer graphic images.
Construction of an environment model with sequential stereo images
Authors: Tsudo Akihiro , Yachida Masahiko
Published: July 2007

This paper proposes a sequentially updated environment model for a mobile robot equipped with a stereo camera. Information obtained from the visual sensors on the robot is used to construct a model for the area surrounding the path of the robot. The model is sequentially updated as environmental data is acquired, and relationships between multiple image frames are observed. The principle of trinocular stereo is applied to the sequential images occurring before and after movement. Line segments are constructed on the frames showing spatial and temporal relationships, and from these, a three‐dimensional geometric wire‐frame model is constructed. The model also uses efficient relationships to allow rapid processing and continual updating of the model.
A test‐path determination method based on define‐use chains: Test conditions and program fault overlooks
Authors: Nakajo Takeshi , Yamaguchi Ichiro , Kume Hitoshi
Published: July 2007

When selecting the set of conditions to be tested in modular white‐box testing of fundamental program functions, various kinds of criteria are available, including the branch coverage criterion and the all‐uses criterion. But there has been very little research on the relationship of these criteria to the overlooking of program faults, and as a consequence many program faults have been discovered only in the later phases of development or at customer sites, where conditions not covered by the original testing occurred. In this paper, an attempt is made to identify the relationship between test conditions and program fault overlooks by expressing the data flows of the program as chains of define‐use relationships between two variables. The approach is tested on commercial software products for the control of measuring equipment. The results are used to develop a method of choosing test paths so as to prevent the principal overlook types, and the detection ability and computational efficiency are compared with those of conventional selection criteria. The number of tests required in the new method is comparable with that in the all‐uses method, and it is capable of preventing almost all of the overlooks that arise from the method used for test path selection.
Design of testing circuit and test generation for built‐in current testing
Authors: Miura Yukiya , Wada Yasushi , Kinoshita Kozo
Published: July 2007

Recently current testing is beginning to be noticed as a testing method for CMOS circuits. However, since CMOS circuits cause the dynamic current due to switching, it has been pointed out that testing at a fast clock rate by current testing is difficult. To cope with this problem a built‐in current testing circuit is proposed in this paper. It is a circuit which measures the value of the dynamic current integrated over a unit time. Next a test sequence generation method for the proposed circuit is presented. In this method test sequences are generated so that the numbers of changes in the gate output values for two consecutive test vectors are almost equal. As a result the dynamic current does not change much between consecutive vectors. Finally the results of test generation for ISCAS'85 benchmark circuits are shown.
Magnetic field imaging using ct technique — roi reconstruction system
Authors: Saito Hideo , Fujita Ken'Ichi , Makajima Masato
Published: July 2007

This paper proposes a method to visualize the spatial distribution of the magnetic field in the region of interest (ROI), using CT technique. An experimenal system is constructed to visualize the magnetic field in ROI. In the reconstruction of the distribution in general by the CT technique, the projection data should not contain data outside the region of reconstruction. In the visualization of the magnetic field by CT techniques proposed up to the present, however, the projection data containing the magnetic field distribution outside the region of reconstruction are contained in the measurement. Consequently, the technique has been applied only to the case where the magnetic field exists only inside ROI.

This paper proposes the following method. Wires for detecting the magnetic field are placed in the region of reconstruction. It is noted that the projection data obtained from the induced voltage does not contain the magnetic field distribution outside the region of reconstruction. This property is utilized in the visualization of the magnetic field distribution in the region of reconstruction.

This paper describes also the principle of the fore‐mentioned methods, as well as the ROI visualization system constructed based on the principle. Using the proposed method, result of visualization is shown for magnetic field distribution produced by a permanent magnet.
PQL: Modal logic for compositional verification of concurrent programs
Authors: Uchihira Naoshi
Published: July 2007

The temporal logic model checking method is very useful for verification of concurrent programs that can be expressed by finite state transition systems. However, a major drawback to using this method is that as the scale of the programs increases, the computation costs for verification increase exponentially. An effective solution for this problem is compositional verification. Compositional verification is a method in which the bisimulation equivalence of concurrent programs is used to extract from each construction element (subprocess) only that abstract information necessary to verify each query, thereby avoiding an explosion in cost.

In this paper, PQL (Process Query Language) is proposed as an improved method in the solution of this problem. PQL is based on modal logic which is the union of temporal and process logic. Also in this paper, the compositional verification method is proposed by using PQL with consideration of the “divergence by internal transition”.
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

Multi‐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

This 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

Matrix 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

This 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

Some 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

This 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

The 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

The 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

The 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

Various 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

A 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

This 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

The 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

Numerous 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

It 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

Post‐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

This 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.