bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new environment for improving legacy software on embedded systems
Authors: Sakai Makoto , Kubota Masunori , Okita Masaya , Matsumoto Ken‐ichi , Torii Koji 
Published: June 2004

AbstractIn this paper, the authors propose a method of evaluating the module structure of programs for embedded software in which maintainability has deteriorated due to repeated revisions and also describe a software improvement support tool that was developed based on the proposed method. The proposed evaluation method supports the improvement of a module structure that includes the exchange of data according to external variables, which is often used in embedded software, by applying the concepts of intermodule coupling and module cohesion from structured analysis. The support tool also has the following special features: (1) by displaying the exchange of data according to external variables as an interface with a higher‐level function, it can display the “data flow between hierarchically related modules,” which could not be displayed by conventional tools, (2) by using open source tools, it can be implemented with relatively few man‐hours, and (3) it provides design guides and checklists that enable the software improvement method to be learned in a short period without regard to user expertise. From the results obtained when this tool was introduced in actual projects, it was apparent that the tool was effective in discovering and improving program structures that caused a deterioration of maintainability. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 81–91, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10023
Robust object detection and segmentation by peripheral increment sign correlation image
Authors: Satoh Yutaka , Kaneko Shun'ichi , Igarashi Satoru 
Published: June 2004

AbstractThis paper proposes the peripheral increment sign correlation image, which can be used to evaluate sign changes of the neighborhood brightness. Based on the technique, a robust method is presented for detection and separation of the object emerging from the image time sequence, with the following features. (1) The result is not affected by the brightness distribution of the emerging object. (2) The result is not affected by brightness change of the background. The peripheral increment sign correlation image is constructed from only the trend of the brightness changes in the neighborhood of the pixel under consideration. Consequently, the image is highly robust to brightness changes over the sequence, and the similarity of the original texture pattern can be detected even if there is a brightness change. Furthermore, it does not require complex preprocessing or parameter setting, and a high‐density difference image can be directly derived. Through experiments using real images with various conditions, it is verified that difference extraction which is robust to brightness change can be realized, indicating the effectiveness of the approach. An application experiment is performed to extract the emerging object area in a scene, and it is verified that segmentation can be performed while retaining good contours and continuity by adding a relatively simple filter sequence as postprocessing. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 70–80, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10241
Monte Carlo analysis of near‐infrared light propagation in a neonatal head model
Authors: Eda Shuhei , Okada Eiji 
Published: June 2004

AbstractIn brain function measurement using near‐infrared light, it is very important to make a theoretical analysis of light propagation in the head tissue, since it is impossible to measure the effect of optical fiber arrangement on the region of measurement or its sensitivity. The Monte Carlo method is widely used in the analysis of near‐infrared light propagation in biological tissue, since it allows light propagation analysis of heterogeneous tissue by a relatively simple algorithm. In this study, a model simulating the cross‐sectional structure of the neonatal head is constructed by using square elements, and the light propagation is analyzed. First, the variance‐reduction (VR) method and the delta‐scattering (DS) method, which are typical algorithms of the Monte Carlo method, are applied to the model composed of square elements, and the results of the analysis and the computation time for light propagation are compared and discussed. It is shown that the DS method is useful for a model composed of small square elements, since the computation time depends little on the size of the elements. As a result of analysis of light propagation in the neonatal head model using the DS method, we see that light propagation is greatly affected by the heterogeneity of the head tissue. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 60–69, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10246
Optical flow detection using segmentation and MDL criterion
Authors: Tsuchiya Hideaki , Uemura Noburu , Itoh Shuichi 
Published: June 2004

AbstractKanatani applied the concept of noise to optical flow calculation using the constraint equation proposed by Horn, and presented a renormalization method which estimates the flow and the noise components simultaneously. In the renormalization method, the image is segmented into blocks, and the constraint that flows of the pixels in a block remain the same is assumed. This paper applies MDL criterion to the renormalization method and proposes an optical flow estimation algorithm that segments the image self‐organizationally. It is assumed that the sender has a pair of images from time‐ordered sequence and the receiver has one of these images. In this assumption, the image segmentation is determined by using MDL criterion so that the intensity gradient vectors generated from the image pair are encoded most efficiently. Each intensity gradient vector is encoded to two components, namely, the flow vector and the error. The image segmentation and the flow vectors obtained by this procedure are defined as the estimated optical flows. As an experiment, the algorithm is applied to artificial image pairs and a real image pair and the results are presented. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 51–59, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10335
A system for supporting collaborative learning with networked sensing boards
Authors: Sugimoto Masanori , Kusunoki Fusako , Inagaki Shigenori , Takatoki Kuniyoshi , Yoshikawa Atsushi 
Published: June 2004

AbstractThe authors have used sensing boards based on RFID technology to construct a face‐to‐face group learning support system integrating the physical world and the virtual world. The system is shown to be useful through performance in that a learner without sufficient skill in using a computer can easily participate in learning, and knowledge acquired through textbooks and the like can be tested in the physical world. On the other hand, some problems have been pointed out: the utterances depend more strongly on the leader, and learning support with a higher degree of realism is desired. Consequently, in the system proposed in this paper, multiple sensing boards are placed at different sites so that the learner groups can communicate face‐to‐face. The sensing boards are connected through a network so that the operations on the board can influence each other. The learners in the group gather around the board and try to solve the problem face‐to‐face. They also interact with the learners in another group through a chat system. The learners in a primary school classroom used the system to study city design and environmental problems, and the effectiveness of the proposed system was demonstrated. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 39–50, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10502
Estimation of true Mahalanobis distance from eigenvectors of sample covariance matrix
Authors: Iwamura Masakazu , Omachi Shinichiro , Aso Hirotomo 
Published: June 2004

AbstractIn statistical pattern recognition, the Bayesian decision theory gives a decision that minimizes the expected probability of misclassification as long as the true distributions are given. However, in most practical situations, the true distributions are unknown, and the parameters of the distributions are usually estimated from training sample vectors. It is well known that estimated parameters contain estimation errors when the sample size is small, and the errors have a negative influence on recognition performance. Among the estimation errors of parameters, the estimation errors of eigenvectors have not been sufficiently considered. In this paper, we present a method to estimate the true Mahalanobis distance from the sample eigenvectors (the eigenvectors of sample covariance matrix) by considering the estimation errors of eigenvectors. Recognition experiments show that the true Mahalanobis distance can be estimated, and better recognition accuracy is achieved by applying the proposed method without many training samples and any hyperparameters. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 30–38, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10519
Curved document imaging with eye scanner
Authors: Amano Toshiyuki , Abe Tsutomu , Nishikawa Osamu , Iyoda Tetsuo , Sato Yukio 
Published: June 2004

AbstractIn conventional document imaging by a copying machine, the item to be copied must be held flat at a specified position. In addition, distortion or blurring can be produced when an object with three‐dimensional undulations is imaged. Consequently, we developed a next‐generation document imaging device (Eye Scanner) which can image characters or photographs on a curved sheet from an arbitrary viewpoint, without contact and without distortion, by utilizing shape information. This paper gives an outline of the Eye Scanner device and proposes a method of eliminating texture distortion of a curved object imaged from an arbitrary viewpoint. A divided imaging and connection method by using a pan‐tilt stage is presented. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 20–29, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10558
Object detection/classification by probabilistic local matching
Authors: Yamaoka Megumi , Nagao Kenji 
Published: June 2004

AbstractA new method for object detection and classification based on their shapes in images is presented. In the new method, to describe objects and match them with the models, local photometric features are incorporated with global shape features in a probabilistic framework, which is an extension of conventional approaches to geometric object recognition. Results demonstrate the effectiveness of the proposed method in vehicle detection in road images with background clutter, as well as in face detection under varying lighting conditions. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 10–19, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10641
Robust feature extraction method based on run‐length compensation for degraded character recognition
Authors: Mori Minoru , Sawaki Minako , Hagita Norihiro , Murase Hiroshi , Mukawa Naoki 
Published: June 2004

AbstractConventional features are robust for recognizing either deformed or degraded characters. Most conventional character recognition methods address either one or the other. This paper proposes a feature extraction method that is robust for both of them. Run‐length compensation is introduced for approximately extracting directional run‐lengths of strokes from degraded handwritten characters. This technique is applied to the conventional feature vector based on directional run‐lengths. Experiments for handwritten characters with additive or subtractive noise show that the proposed feature is superior to conventional ones over a wide range of the degree of noise. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 1–9, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10643
A neural net architecture for hardware implementation of a temporal pattern discrimination model
Authors: Takahashi Sei , Sekine Yoshifumi 
Published: June 2004

AbstractThis paper proposes a neural net architecture for hardware implementation of a temporal pattern discrimination model. The elements constituting the hardware have the characteristics of delays, thresholds, and refractoriness that are useful for implementing a model in hardware. First, it shows that a temporal pattern short‐term memory structure, similar to TDNN, can be implemented by connecting the hardware elements only serially. Next, it constructs a neocognitron‐type temporal data recognition model (Neo‐TDRM) using this short‐term memory structure by using a neocognitron that is robust with respect to pattern positional lags or shape changes as a discrimination model. Results of computer simulation of single‐channel mouse brain wave discrimination experiments show that the system can correctly discriminate even waveforms that are extended or contracted temporally or spatially. In addition, the proposed model is shown to be suitable for hardware implementation compared with the neocognitron constructed for similar discrimination experiments from the point of view of the number of cells or the number of wires required, since the number of cells of the Neo‐TDRM can be reduced to about 1/4 and the number of wires to about 1/18. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(9): 104–112, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20075
A new approach for interval estimation and hypothesis testing of a certain intraclass correlation coefficient: the generalized variable method
Authors: Tian Lili , Cappelleri Joseph C. 
Published: June 2004

AbstractWe consider the problems of interval estimation and hypothesis testing for the intraclass correlation coefficient in an interrater reliability study when both raters and subjects are assumed to be randomly selected from populations of raters and subjects, respectively. We propose a novel approach for the confidence interval estimation and hypothesis testing using the concepts of generalized confidence interval (GCI) and generalizedP‐values. A simulation study is conducted to investigate the coverage probabilities of the GCI approach relative to the modified large sample (MLS) approach. Both methods tend to provide somewhat conservative coverage. Relative to the MLS approach, the GCI approach is closer to the correct (nominal) coverage for a two‐sided interval, but farther to the correct coverage for a one‐sided lower interval. Unlike the MLS approach, the GCI approach can also easily provideP‐values. The fact that the GCI approach is suitable for confidence interval estimation and obtainingP‐values makes the GCI approach a suitable candidate for making inference about interrater reliability. Copyright© 2004 John Wiley & Sons, Ltd.
Adjusting SIDS rates by seasonality in births in Minnesota
Authors: Wall Melanie M. 
Published: June 2004

AbstractThis paper is concerned with the formation of sudden infant death syndrome (SIDS) rates over time. Because of differential numbers of births throughout the year, a new SIDS rate is developed that takes into account the changing number of infants at risk and in particular the changing age distribution throughout the year. Differences between this newly adjusted rate and the commonly used unadjusted rates will be presented. Data from Minnesota linked birth–death records from 1990–1998 will be used for analysis. Copyright 2004 John Wiley & Sons, Ltd.
Consequences of event rate heterogeneity across non‐randomized study sub‐groups
Authors: Eberly Lynn E. 
Published: June 2004

AbstractAnalyses to compare non‐randomized groups are more and more common in bothpost hocanalyses of randomized clinical trials data and in analyses of long‐term observational data. In such cases, it is quite likely that there are unknown or uncollected sources of heterogeneity in event rates. Research has shown that an underlying source of heterogeneity in event rates which is not included in proportional hazards regression models leads to biased estimates for included covariate effect estimates and lower power to test them whether the source of heterogeneity is assumed to be fixed or random.We demonstrate here using severalpost hocanalyses of clinical trials data that a potentially common problem may be that the non‐randomized groups which are to be compared have differential variability in their event rates. We then show through simulation that such underlying heterogeneity which varies across the groups, when ignored in the modelling, can lead to an attenuated regression effect estimate for comparing the two groups to each other, lower rejection rates for the effect, and Wald‐based confidence intervals with potentially much lower coverage than nominal. When the groups are not significantly different, but heterogeneity differs between them, an analysis ignoring the heterogeneity can even result in a significant negative comparison. Copyright © 2004 John Wiley & Sons, Ltd.
13C‐urea breath test for Helicobacter pylori in young children: cut‐off point determination by finite mixture model
Authors: X. Du Joanna , Watkins Terry , Bravo Luis E. , Fontham Elizabeth T. H. , Camargo M. Constanza , Correa Pelayo , Mera Robertino 
Published: June 2004

AbstractThe 13C‐urea breath test (UBT) is currently regarded as one of the most important noninvasive diagnostic methods for detecting Helicobacter pylori (H. pylori) infection in adults and children. However, for infants and young children, the standard for UBT interpretation has not been validated, and its reliability has not been established for diagnosing H. pylori infection in this group. The primary outcome data from UBT consist of mixture data, which come from subjects whose H. pylori infection classifications are unconfirmed. In this paper, we propose the finite mixture distribution method to identify a reliable UBT cut‐off value in a large baseline sample in which gastric biopsy is not available to confirm the H. pylori infection in younger children. Maximum likelihood estimators of the parameters in the mixture model were obtained using an expectation maximization (EM) algorithm. The standard deviation of the cut‐off point was estimated by bootstrap methods. We applied the same analytical methods to the UBT results yielded from the follow up, as well as the overall UBT results in the longitudinal cohort data. The cut‐off points from those UBT data sets are similar. The advantage of the finite mixture model is that it may be used to calculate sensitivity and specificity in the absence of other diagnostic tests. Copyright © 2004 John Wiley & Sons, Ltd.
Estimating episode lengths when some observations are probably censored
Authors: Goodman Allen C. , Peng Yingwei , Hankin Janet R. , Kalist David E. , Spurr Stephen J. 
Published: June 2004

AbstractThis paper analyses a case in censored failure time data problems where some observations are potentially censored. The traditional models for failure time data implicitly assume that the censoring status for each observation is deterministic. Therefore, they cannot be applied directly to the potentially censored data. We propose an estimator that uses resampling techniques to approximate censoring probabilities for individual observations. A Monte Carlo simulation study shows that the proposed estimator properly corrects biases that would otherwise be present had it been assumed that either all potentially censored observations are censored or that no censoring has occurred. Finally, we apply the estimator to a health insurance claims database. Copyright © 2004 John Wiley & Sons, Ltd.
Concomitant‐based rank set sampling proportion estimates
Authors: Terpstra Jeff T. , Liudahl Lindsey A. 
Published: June 2004

AbstractThis paper discusses the rank set sampling (RSS) protocol as it pertains to the estimation of a population proportion. The ranking process is based on a concomitant variable. The concomitant‐based RSS estimate is asymptotically normal so standard inference procedures can still be implemented. This is illustrated using a real data set from the medical literature. The performance of the estimator is studied in terms of relative efficiency. Generally speaking, the concomitant‐based RSS estimator is more efficient than the proportion of successes in a simple random sample. The greatest gains in efficiency are obtained when the correlation between the Bernoulli and concomitant variable is large in absolute value. Copyright 2004 John Wiley & Sons, Ltd.
A test for informative censoring in clustered survival data
Authors: Huang Xuelin , Wolfe Robert A. , Hu Chengcheng 
Published: June 2004

AbstractFrailty models are frequently used to analyse clustered survival data. The assumption of non‐informative censoring is commonly used by these models, even though it may not be true in many situations. This article proposes a test for this assumption. It uses the estimated correlation between two types of martingale residuals, one from a model for failure and the other from a model for censoring. It distinguishes two types of censoring, namely withdrawal and the end of the study. Simulation studies show that the proposed test works well under various scenarios. For illustration, the test is applied to a data set for kidney disease patients from multiple dialysis centres. Copyright © 2004 John Wiley & Sons, Ltd.
Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation
Authors: Pencina Michael J. , D'Agostino Ralph B. 
Published: June 2004

AbstractThe assessment of the discrimination ability of a survival analysis model is a problem of considerable theoretical interest and important practical applications. This issue is, however, more complex than evaluating the performance of a linear or logistic regression. Several different measures have been proposed in the biostatistical literature. In this paper we investigate the properties of the overall C index introduced by Harrell as a natural extension of the ROC curve area to survival analysis. We develop the overall C index as a parameter describing the performance of a given model applied to the population under consideration and discuss the statistic used as its sample estimate. We discover a relationship between the overall C and the modified Kendall's τand construct a confidence interval for our measure based on the asymptotic normality of its estimate. Then we investigate via simulations the length and coverage probability of this interval. Finally, we present a real life example evaluating the performance of a Framingham Heart Study model. Copyright © 2004 John Wiley & Sons, Ltd.