• Biomedical Science Letters
• /
• v.13 no.4
• /
• pp.287-291
• /
• 2007

The factors and mechanisms by infection of Oriental Tsutsugamushi caused disease are not well understood. The onset of tsutsugamushi disease is characterized by chilliness, fever, malaise, headache and generalized aching. Infection of tsutsugamushi is the cause of impairment of function of a major organ often complicate the picture and immediately change the prognosis for the worse. Tsutsugamushi disease is reported that this disease is characterized by the histopathogenesis of liver, kidney, heart, and lung, but the variation of biochemical components in serum of tsutsugamushi disease patient are not clear. We analyzed total protein (TP), albumin (AL), aspartic aminotranferase (AST), alanine aminotransferase (ALT), alkaline phosphotase (ALP), urea nitrogen (UN), creatinine (CRE), glucose (GLD), cholesterol (CHOL) and total bilirubin (TB) in sera of patients with tsutsugamushi disease. In comparison with reference, total protein and albumin were abnormally decreased in 19.6% and 39.2% of patients, respectively. AST, ALT, ALP, creatinine, UN, glucose, cholesterol and total bilirubin were abnormally increased in 94.1 %, 72.5%, 25.5%, 15.7%, 9.8%, 62.7%, 25.5% and 6.0% of patients, respectively. The patients showed abnormal relative rate of protein electrophoretic fractions to total protein in serum compared to them of reference were 43.1% (albumin), 12.9% ($\alpha_1$-globulin), 58.8% ($\alpha_2$-globulin), 60.8% ($\beta$-globulin) and 70.6% ($\gamma$-globulin), respectively. These data suggest that infection of Oriental Tsutsugamushi causes impairment of function of a major organ and abnormal serum protein electrophoresis fractions to tsutsugamushi patients.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1244-1244
• /
• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1042-1042
• /
• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• Steel and Composite Structures
• /
• v.28 no.3
• /
• pp.389-401
• /
• 2018

An isoparametric six-node triangular element is utilized for geometrically nonlinear analysis of functionally graded (FG) shells. To overcome the shear and membrane locking, the element is improved by using strain interpolation functions. The Total Lagrangian formulation is employed to include the large displacements and rotations. Finding the nonlinear behavior of FG shells via laminated modeling is also the goal. A power function is employed to formulate the variation of elastic modulus through the thickness of shells. The results are presented in two ways, including the general FGM formulation and the laminated modeling. The equilibrium path is obtained by using the Generalized Displacement Control Method. Some popular benchmarks, including hyperbolical shell structures are solved to declare the correctness and accuracy of proposed formulations.

• Architectural research
• /
• v.19 no.4
• /
• pp.89-94
• /
• 2017

In Korea, it is necessary to improve the performance of buildings with respect to the energy efficiency while improving the quality of occupants' lives through a sustainable built environment. During the design and development process, building projects must have a comprehensive, integrated perspective that seeks to reduce heating, cooling and lighting loads through climate-responsive designs. The aim of this study is to assess the optimal window-to-wall ratio of multi-rise residential units in the early design phase in Korea. The study analyzed the variation of annual heating and cooling energy load in two apartment prototype units located in Seoul city using different WWRs. The analysis was conducted using Autodesk Ecotect Analysis 2011 tool. The study found for total annual building load reductions WWR on the south and north face should be studied independently based on the room function. It also found reducing the WWR for bedrooms and windows on the northern façade resulted in reduced total annual building load.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.25 no.2
• /
• pp.67-76
• /
• 2000

We consider the determinant of the most economical target value through the sampling inspection by two consecutive machines. The machine sequence is fixed as products have to be processed by machine 1 first and then by machine 2 next, In this paper we assume that if quality of a unit is lower than inspection lower specification limited then the goods is not accepted, otherwise it is accepted. And we assume that the quality characteristics is larger-the-better characteristics and its distribution is the normal distribution whose standard deviation is known. This paper ends up with an numerical example by using the total expected profit function model that consider the scales profits inspection costs and material costs. And we analyze the variation of the total expected profit by changing coefficients of the functions.

• Journal of the Society of Naval Architects of Korea
• /
• v.44 no.5
• /
• pp.542-550
• /
• 2007

A geometry modification is one of main keys in achieving a successful optimization. The optimized hull form generated from the geometry modification should be a realistic, faired form from the ship manufacturing point of view. This paper presents a practical hull optimization procedure using a parametric modification function. In the parametric modification function method, the initial ship geometry was easily deformed according to the variations of design parameters. For example, bulbous bow can be modified with several parameters such as bulb area, bulb length, bulb height etc. Design parameters are considered as design variables to modify hull form, which can reduce the number of design variables in optimization process and hence reduce its time cost. To verify the use of the parametric modification function, optimization for KCS was performed at its design speed (FN=0.26) and the wave making resistance is calculated using a well proven potential code with fully nonlinear free surface conditions. The design variables used are key design parameters such as Cp curve, section shape and bulb shape. This study shows that the hull form optimized by the parametric modification function brings 7.6% reduction in wave making resistance. In addition, for verification and comparison purpose, a direct geometry variation method using a bell-shape modification function is used. It is shown that the optimal hull form generated by the bell-shaped modification function is very similar to that produced by the parametric modification function. However, the total running time of the parametric optimization is six times shorter than that of the bell shape modification method, showing the effectiveness and practicalness from a designer point of view in ship yards.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.11 no.3
• /
• pp.174-182
• /
• 2008

As the survey and the analysis the research can offer the characteristic methods for regeneration in the city of Busan. To figure out the functional regions of city center the research has analyzed 15 Dongs in city center and 12 Dongs in sub centers to find out the donut phenomenon and the regeneration of city center. The survey has chosen 22 variation factors using factor analysis. Major factors in each year are shown 4 factors, presenting 80.4% of the accumulated explanation rate. These factors explain residental centered, commercial centered, management centered, and development centered factor. The donut phenomenon emerges in the city centers as a residential function, and the phenomenon occurs in the sub centers as commercial or managerial function. So it is necessary to plan the regeneration of the total city center owing to the total donut phenomenon regarding the functions. And the methods to regenerate city centers should be established according to the various regional characterizations.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.21 no.6
• /
• pp.323-330
• /
• 1988

The spatial distribution of sea water temperature variation pattern in the South-eastern coastal region of Korea was studied by empirical orthogonal function (E. O. F) analysis in several depths from surface to 300m using the monthly mean water temperature averaged for 23 years, water mass analysis by T. S diagram and sectional diagram of water temperature. Typical type of water temperature variation in this area can be divided into surface (0m-50m), subsurface (100m-150m) and intermediate (200m-300m) layer. The first mode value of water temperature change on the surface layer showed $99\%$ of total variation, and decreased with the increase of the depth. It is deduced to be in the range of $60-70\%$ on the 300m layer. The representative type of water temperature fluctuation by the first mode in each layer is as follows. Water temperature change in the surface layer showed a seasonal variation. In the subsurface layer, it is governed by the interaction of the Tsushima Warm Current water with the cold water and by the heat transfer process from the upper layer. In the intermediate layer, water temperature variation seems to be governed by the advection of the bottom cold water.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.14 no.4
• /
• pp.427-435
• /
• 2014

Segmented-channel MOSFETs (SegFETs) can achieve both good performance and variation robustness through the use of $HfO_2$ (a high-k material) to create the shallow trench isolation (STI) region and the very shallow trench isolation (VSTI) region in them. SegFETs with both an HTI region and a VSTI region (i.e., the STI region is filled with $HfO_2$, and the VSTI region is filled with $SiO_2$) can meet the device specifications for high-performance (HP) applications, whereas SegFETs with both an STI region and a VHTI region (i.e., the VSTI region is filled with $HfO_2$, and the STI region is filled with $SiO_2$) are best suited to low-standby power applications. AC analysis shows that the total capacitance of the gate ($C_{gg}$) is strongly affected by the materials in the STI and VSTI regions because of the fringing electric-field effect. This implies that the highest $C_{gg}$ value can be obtained in an HTI/VHTI SegFET. Lastly, the three-dimensional TCAD simulation results with three different random variation sources [e.g., line-edge roughness (LER), random dopant fluctuation (RDF), and work-function variation (WFV)] show that there is no significant dependence on the materials used in the STI or VSTI regions, because of the predominance of the WFV.