• The Pure and Applied Mathematics
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• v.1 no.1
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• pp.19-24
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• 1994

Let P be a probability measure on the real line with Lebesque-density f. The usual estimator of the distribution function (≡df) of P for the sample $\chi$$_1$,…, $\chi$$\_$n/ is the empirical df: F$\_$n/(t)=(equation omitted). But this estimator does not take into account the smoothness of F, that is, the existence of a density f. Therefore, one should expect that an estimator which is better adapted to this situation beats the empirical df with respect to a reasonable measure of performance.(omitted)

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.147-154
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• 1999

Using a noninformative prior and an inverted gamma prior, the Bayesian predictive density and the prediction intervals for a future observation or the p - th order statistic of n' future observations from the censord Pareto model have been obtained. In additions, numerical examples are given in order to illustrate the proposed predictive procedure.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.31-37
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• 1995

We consider density estimates of the usual type generated by a kernel function. By using the limit theorems for the maximum of normalized deviation of the estimate from its expected value, we propose to use data dependent bandwidth in the tests of goodness of fit based on these statistics. Also a small sample Monte Carlo simulation is conducted and proposed method is compared with Kolmogorov-Smirnov test.

• International Journal of High-Rise Buildings
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• v.12 no.1
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• pp.75-82
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• 2023

By limiting population and land resources, a high-density urban form has become the inevitable choice for central cities in the rapid growth of many large cities in China. Due to the shift in urban growth and focus, high-density urban areas require restoration and improvement. This study intends to combine ancient and new districts, establish strategies for enhancing urban function, spatial utility, industry, and transportation, and thus enhance regional holistic effectiveness, by performing in-depth research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.37-44
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• 2009

Density is the most important congestion indicator among the three fundamental flow variables, flow, speed and density. Measuring density in the field has two different ways, direct and indirect. Taking photos with wide views is one of direct ways, which is not widely used because of its cost and lacking of proper positions. Another direct density measuring method using two spot detectors has been introduced with the concept of instantaneous density, average density and measurement interval. The relationship between accuracy and measurement interval has been investigated using the simulation data produced by Paramics API function. Finally, density measurement algorithm has been suggested including exponential smoothing for device development.

• Investigative Magnetic Resonance Imaging
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• v.15 no.1
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• pp.57-66
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• 2011

Purpose : A new inhomogeneity correction method based on two-point Dixon sequence is proposed to obtain water and fat images at 0.35T, low field magnetic resonance imaging (MRI) system. Materials and Methods : Joint phase-magnitude density function (JPMF) is obtained from the in-phase and out-of-phase images by the two-point Dixon method. The range of the water signal is adjusted from the JPMF, and 3D inhomogeneity map is obtained from the phase of corresponding water volume. The 3D inhomogeneity map is used to correct the inhomogeneity field iteratively. Results : The proposed water-fat imaging method was successfully applied to various organs. The proposed 3D inhomogeneity correction algorithm provides good performances in overall multi-slice images. Conclusion : The proposed water-fat separation method using JPMF is robust to field inhomogeneity. Three dimensional inhomogeneity map and the iterative inhomogeneity correction algorithm improve water and fat imaging substantially.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.629-637
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• 2013

Chaos communication systems have the characteristics such as non-periodic, wide-band, non-predictability of signals and easy implementation. There have been many studies about chaos communication systems because of these advantages. But, chaos communication systems have low BER(Bit Error Rate) compare to general digital communication system. Existing researches on chaos communication systems only analyze BER performance according to various chaos maps. There are no studies on analysis of BER performance according to PDF(Probability Density Function) of chaos maps. In this paper, we analyze the BER performance according to changing parameter, equation, and initial values of chaos map's PDF. In addition, we propose new chaos map to improve BER performance. Simulation results show that BER performance of CDSK(Correlation Delay Shift Keying) is changed when PDF of chaos map changed. And the proposed chaos map has a better BER performance compare to previous chaos maps such as Tent map, Logistic map, and Henon map.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1341-1350
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• 2019

This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.

• Nuclear Engineering and Technology
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• v.16 no.4
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• pp.181-194
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• 1984

The in-core fuel management problem was studied by use of the calculus of variations. Two functions of interest to a public power utility, the profit function and the cost function, were subjected to the constraints of criticality, the reactor turnup equations and an inequality constraint on the maximum allowable power density. The variational solution of the initial profit rate demonstrated that there are two distinct regions of the reactor, a constant power region and a minimum inventory or flat thermal flux region. The transition point between these regions is dependent on the relative importance of the profit for generating power and the interest charges for the fuel. The fuel cycle cost function was then used to optimize a three equal volume region reactor with a constant fuel enrichment. The inequality constraint on the maximum allowable power density requires that the inequality become an equality constraint at some points in the reactor. and at all times throughout the core cycle. The finite difference equations for reactor criticality and fuel burnup in conjunction with the equality constraint on power density were solved, and the method of gradients was used to locate an optimum enrichment. The results of this calculation showed that standard non-linear optimization techniques can be used to optimize a reactor when the inequality constraints are properly applied.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.164-171
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• 2007

This research used GIS spatial analysis model and Huff probability model and achieved trade area analysis of area center. we constructed basic maps that were surveyed according to types of business, number of households etc. using a land registration map of LMIS(Land Management Information System) in Bokdae-dong, Cheongju-si. Kernel density function and NNI(Nearest Neighbor Index) was used to estimate store distribution center area in neighborhood life zones. The center point of area and scale were estimated by means of the center area. Huff probability model was used in abstracting trade areas according to estimated center areas, those was drew map. Therefore, this study describes method that can apply in Huff probability model through kernel density function and NNI of GIS spatial analysis techniques. A trade area was abstracted more exactly by taking advantage of this method, which will can aid merchant for the foundation of small sized enterprises.