• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.57-63
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• 2012

The ordinary least square (OLS) regression model is assumed that the relationship between distribution of longevity population and environmental factors to be identical. Therefore, the OLS regression analysis can't explain sufficiently the spatial characteristics of longevity phenomenon and related variables. The geographically weighted regression (GWR) model can be representing the spatial relationship of adjacent area using geographically weighted function. It also characterized which can locally explain the spatial variation of distribution of longevity population by environmental characteristics. From this point of view, this study was performed the comparative analysis between OLS and GWR model for ecological factors of longevity existing studies. In the results, GWR model has higher corresponded to model than OLS model and can be accounting for spatial variability about effect of specific environmental variables.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.57-58
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• 2007

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.1
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• pp.97-102
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• 2008

The Natural Resource Conservation Service Curve Number(NRCS-CN) method is one of the widely used methods for computation of runoff from a basin. However, NRCS-CN method has a weak point in that the spatial land use distribution characteristics are ignored by using area-weighted CN value. This study developed a runoff estimation algorithm which can reflect the spatial land-use distribution. The algorithm consists of Moglen's theory and a developed flow accumulation estimation program in FORTRAN. Comparisons between the results from area-weighted CN method and this study showed reasonably good agreement with measured data of experimental watersheds. The developed program predicted lower runoff than the conventional NRCS-CN method. As a conclusion, this study proposes a new design direction which can simulate real runoff phenomena. And the developed program could be applied into runoff minimization design for a basin development.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4487-4491
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• 2014

Objective: To explore the clinical manifestations and imaging characteristics of gliomatosis cerebri to raise the awareness and improve its diagnostic accuracy for patients. Materials and Methods: Clinical data, imaging characteristics and pathological examination of 12 patients with GC from Jan., 2008 to Jan., 2012 were analyzed retrospectively. Results: Patients with GC were clinically manifested with headache, vomiting, repeated seizures, fatigue and unstable walking, most of whom had more than 2 lesions involving in parietal lobe, followed by temporal lobe, frontal lobe, periventricular white matter and corpus callosum. Magnetic resonance imaging (MRI) showed diffuse distribution, T1-weighted images (T1WI) with equal and low signals and T2-weighted images (T2WI) with bilateral symmetrical high diffuse signals. There was no reinforcement by enhancement scanning and signals were different in diffusion-weighted images (DWI). The higher the tumor staging, the stronger the signals. Pathological examination showed neuroastrocytoma in which tumor tissues were manifested by infiltrative growth in blood vessels and around neurons. Conclusions: In clinical diagnosis of GC, much attention should be paid to the diffuse distribution of imaging characteristics, incomplete matching between clinical and imaging characteristics and confirmation by combining with histopathological examination.

• Ocean Science Journal
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• v.42 no.2
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• pp.69-79
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• 2007

A vertical transect with 4 km length was established for the macrofaunal survey on the Chokchon macrotidal flat in Kyeonggi Bay, Incheon, Korea, 1994. Tidal elevation (m) and sediment mean grain size $(\phi)$ were inversely predicted by the transfer functions from the faunal assemblages. Three methods: weighted average using optimum value (WA), tolerance weighted version of the weighted average (WAT) and maximum likelihood calibration (MLC) were employed. Estimates of tidal elevation and mean grain size obtained by using the three different methods showed positively corresponding trends with the observations. The estimates of MLC were found to have the minimum value of sum of squares due to errors (SSE). When applied to the previous data $(1990\sim1992)$, each of three inference models exhibited high predictive power. This result implied there are visible relationships between species composition and faunas' critical environmental factors. Although a potential significance of the two major abiotic factors was re-affirmed, a weak tendency of biological interaction was detected from faunal distribution patterns across the flat. In comparison to the spatial and temporal patterns of the estimates, it was suggested that sediment characteristics were the primary factors regulating the distribution of macrofaunal assemblages, rather than tidal elevation, and the species composition may be sensitively determined by minute changes in substratum properties on a tidal flat.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.73-80
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• 1987

Various procedures for evaluation of traffic noise annoyance have been proposed. However, most of the studies of this type are restricted for improving traffic flow. In this paper, a method to predict the road traffic noise is proposed in terms of equivalent continuous A-Weighted sound pressure level (Leq), based on a probability model. First, distribution of the road traffic noise level are investigated. second, the weibull distribution parameters are estimated by using the quantification theory. Finally, a prediction model of the road traffic noise is proposed based on the weibull distribution model The predicted values of the Leq are closely matched the measured data.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.365-372
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• 2013

The essential aim of this paper is to define weighted $q$-Hardylittlewood-type maximal operator by means of $p$-adic $q$-invariant distribution on $\mathbb{Z}_p$. Moreover, we give some interesting properties concerning this type maximal operator.

• Journal of the Korean Statistical Society
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• v.18 no.2
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• pp.135-148
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• 1989

Cumulative sum schemes based on a weighted score are considered for controlling the mean of a continuous production process; in which both the one-sided and two-sided schemes are proposed. The average run lengths and the run length distributions for the proposed schemes are obtained by the Markov chain approach. Comparisons by the average run length show that the proposed schemes perform nearly as well as the standard cumulative sum schemes in detecting changes in the process mean. Comparisons of the one-sided schemes by the run length distribution are also presented.

• Journal of the Korean Mathematical Society
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• v.44 no.3
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• pp.525-539
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• 2007

Consider the regression model $Y_i=g(x_i)+e_i\;for\;i=1,\;2,\;{\ldots},\;n$, where: (1) $x_i$ are fixed design points, (2) $e_i$ are independent random errors with mean zero, (3) g($\cdot$) is unknown regression function defined on [0, 1]. Under $Y_i$ are censored randomly, we discuss the asymptotic normality of the weighted kernel estimators of g when the censored distribution function is known or unknown.