• Korean Journal of Crystallography
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• v.11 no.4
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• pp.241-246
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• 2000

Structure factor는 위치를 포함한 electron density를 알면 계산되고 역으로 electron density는 phase를 포함한 structure factor를 알면 작도할수 있으므로 structure factor와 electron density는 서로 Fourier transform이다.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.211-220
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• 2011

TOD(Transit Oriented Development) has recently been active, which presents that TOD planning elements should be comprehensively taken into consideration in order to enhance domestic transit ridership by changing environments in rail station areas and an empirical analysis on the type of rail station areas and transportation demand should be a prerequisite for usage of future development planning. This study aims to grasp a variety of TOD of influence factors in Seoul rail station area and to perform analysis to identify relationship between public transportation demand and these TOD design factors. To make it come true, we gathered data with respect to Density, Diversity, and Accessibility as representative TOD planning elements and carried out factorial and regression analysis. Consequently, we drew 7 influence factors base on factorial analysis: Factor 1(Diversity/ -Use Mix(LUM)), Factor 2(Density/development density), Factor 3(Accessibility/public transportation facility supply), Factor 4(Design/street design), Factor 5(Green/access mode (pedestrian, bike), Factor 6(Design/subway size), Factor 7(Accessibility/Public transit operation) As the result of model development by using factorial and regression analysis, positive influence factors on passenger flow in rail station area are Factor 1(Diversity : Land-Use Mix), Factor 3(Accessibility : public transportation facility supply), Factor 2(Density : development density), Factor 5(Design/ access mode) and Factor 6(subway size) Next, negative influence factor on passenger flow in rail station area shows Factor 7(Accessibility/Public transit operation) as the most influential factor. This is because the growth of service interval of linked subway and bus leads to reduced demand.

• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.420-429
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• 2004

The local power density should be estimated accurately to prevent fuel rod melting. The local power density at the hottest part of a hot fuel rod, which is described by the power peaking factor, is more important information than the local power density at any other position in a reactor core. Therefore, in this work, the power peaking factor, which is defined as the highest local power density to the average power density in a reactor core, is estimated by fuzzy neural networks using numerous measured signals of the reactor coolant system. The fuzzy neural networks are trained using a training data set and are verified with another test data set. They are then applied to the first fuel cycle of Yonggwang nuclear power plant unit 3. The estimation accuracy of the power peaking factor is 0.45% based on the relative $2_{\sigma}$ error by using the fuzzy neural networks without the in-core neutron flux sensors signals input. A value of 0.23% is obtained with the in-core neutron flux sensors signals, which is sufficiently accurate for use in local power density monitoring.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.385-396
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• 1998

A computing method of fractional Bayes factor (FBF) for a point null hypothesis is explained. We propose alternative form of FBF that is the product of density ratio and a quantity using the generalized Savage-Dickey density ratio method. When it is difficult to compute the alternative form of FBF analytically, each term of the proposed form can be estimated by MCMC method. Finally, two examples are given.

• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.44-51
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• 2001

One of the recent issues in design of the spot-welded structure such as the automobile body is to develop an economical prediction method of the fatigue design criterion without additional fatigue test. In this paper, as one of basic investigation for developing such methods, fracture mechanical approach was investigated. First, the Model I, Mode II and Mode III, stress intensity factors were analyzed. Second, strain energy density factor (S) synthetically including them was calculated. And finally, in order to decide the systematic fatigue design criterion by using this strain energy density factor, fatigue data of the ΔP-N(sub)f obtained on the various in-plane bending type spot-welded lap joints were systematically re-arranged in the ΔS-N(sub)f relation. And its utility and reliability were verified by the theory of Weibull probability distribution function. The reliability of the proposed fatigue life prediction value at 10(sup)7 cycles by the strain energy density factor was estimated by 85%. Therefore, it is possible to decide the fatigue design criterion of spot-welded lap joint instead of the ΔP-N(sub)f relation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.5
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• pp.203-210
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• 2003

This paper describes high voltage and high energy density capacitor developed for pulsed power applications. The rated voltage of the developed capacitor is DC 22 [kV], the capacitance is 206 [$\mu$F] and the energy density is about 0.7 [kJ/kg]. Polypropylene film and kraft paper were used as the dielectrics. The ratio of the thickness of each dielectric material which consists of the composite dielectric structure, stacking factor and the termination method were determined by the charging and discharging tests on model capacitors. In terms of energy density, the developed capacitor has higher energy density compared with the products of foreign leading companies. In addition, it has been proved that the life expectancy can be more over 2000 shots through the charging and discharging test. The voltage reversal factor was 20%. This capacitor can be used as numerous discharge applications such as military, medical, industrial fields.

• Journal of the Korean Geosynthetics Society
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• v.16 no.1
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• pp.9-17
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• 2017

In this study, the field density test was conducted as a volume conversion factor for the design of the excavation soil of the blasting rock. As a result of the field density test, the average volume conversion factor of rock was 1.001, which was smaller than the volume conversion factor of weathered rock 1.1. In the case of rock filled soil, the causes of the increase and decrease of the volume of the soil are provided by various phenomena. However, the specific techniques such as investigation and test methods are insufficient. Therefore, it was confirmed that the method of field density test is very useful method.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.470-470
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• 2010

Negative ions are generated in fusion edge plasmas, material processing plasmas, ionospheric plasmas. Analytic formulas for the deduction of the absolute density of negative ions was given by using the current-voltage(IV) characteristics of two electric probes at two different pressures [1], and negative ion density has been measured by one electric probe using the current-voltage characteristics of three different pressures [2]. Ratios of ion and electron saturation currents and electron temperatures and sheath areas of different pressures are usually incorporated into two equations with two unknowns for the negative ion density. In the previous publications, the sheath factor(sheath area, sheath density, sheath velocity) and effective masses of background ions with different pressures are qualitatively incorporated for the deduction of negative density. In this presentation, the quantitative and detailed relation of negative ion density with sheath factor and effective masses are going to be given. The effect of these parameters on the change of IV characteristics will be addressed.

• Fashion & Textile Research Journal
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• v.21 no.5
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• pp.597-605
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• 2019

This paper examined the garment formability and appearance of perspiration absorption, fast dry, and breathable fabrics. The mechanical properties and seam pucker properties of these fabrics were measured and regression analysis was conducted between fabric structural parameters and their mechanical and seam pucker properties. The superior total appearance value (TAV) of fast dry knitted fabrics for sports-wear was achieved in fabrics with high extensibility and bending rigidity; consequently, it increased with increasing stitch density and tightness factor. The formability of the fast dry knitted fabric also improved with an increasing stitch density and tightness factor. The seam pucker was influenced by bending rigidity and a good seam pucker was exhibited in the fast dry knitted fabrics with low stitch density and tightness factor. However, the formability (F) of the breathable fabric improved by increasing extensibility and bending rigidity that decreased with an increasing cover factor and the thickness of the breathable fabric. In addition, seam pucker deteriorated with an increasing cover factor and the thickness of the breathable fabric, which was similar to the results of the formability predicted in fabric mechanical properties. A superior seam pucker was achieved in fabrics with high extensibility and low bending rigidity.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.