• Korean Journal of Microbiology
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• v.39 no.3
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• pp.128-134
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• 2003

Transformation-associated recombination (TAR) cloning is based on co-penetration into yeast spheroplasts of genomic DNA along with TAR vector DNA that contains 5'- and 3'-sequences (hooks) specific for a gene of interest, followed by recombination between the vector and the human genomic DNA to establish a circular YAC. Typically, the frequency of recombinant insert capture is 0.01-1% for single-copy genes by TAR cloning. To further refine the TAR cloning technology, we determined the effect of GC content on target hooks required for gene isolation utilizing the $Tg\cdot\AC$ mouse transgene as the targeted region. For this purpose, a set of vectors containing a B1 repeated hook and Tg AC-specific hooks of variable GC content (from 18 to 45%) was constructed and checked for efficiency of transgene isolation by radial TAR cloning. Efficiency of cloning decreased approximately 2-fold when the TAR vector contained a hook with a GC content ～${\leq}23$% versus ～40%. Thus, the optimal GC content of hook sequences required for gene isolation by TAR is approximately 40%. We also analyzed how the distribution of high GC content (65%) within the hook affects gene capture, but no dramatic differences for gene capturing were observed.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.26-32
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• 2007

Although the Java bytecode has numerous advantages, it also has certain shortcomings such as its slow execution speed and difficulty of analysis. In order to overcome such disadvantages, a bytecode analysis and optimization must be performed. The control flow of the bytecode should be analyzed; next, information is required regarding where the variables are defined and used to conduct a dataflow analysis and optimization. There may be cases where variables with an identical name contain different values at different locations during execution, according to the value assigned to a given variable in each location. Therefore, in order to statically determine the value and type, the variables must be separated according to allocation. In order to achieve this, variables can be expressed using a static single assignment form. After transformation into a static single assignment form, the type information of each node expressed by each variable and expression must be configured to perform a static analysis and optimization. Based on the basic type information, this paper proposes a method for finding the related equivalent nodes, setting nodes with strong connection components, and efficiently assigning each node type.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.8-13
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• 2015

The experimental design methodology was applied in the drop tube furnace (DTF) to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of DTF. The dependent variables such as burnout ratios (BOR) of coal and $CO/CO_2$ ratios were mathematically described as a function of three independent variables (coal particle size, carrier gas flow rate, wall temperature) being modeled by the use of the central composite design (CCD), and evaluated using a second-order polynomial multiple regression model. The prediction of BOR showed a high coefficient of determination (R2) value, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the simulation data. However, $CO/CO_2$ ratio had a big difference between calculated values and predicted values using conventional RSM, which might be mainly due to the dependent variable increses or decrease very steeply, and hence the second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, $CO/CO_2$ ratio was taken as common logarithms and worked again with RSM. The application of logarithms in the transformation of dependent variables showed that the accuracy was highly enhanced and predicted the simulation data well.

• International Journal of Contents
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• v.3 no.1
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• pp.1-8
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• 2007

The distributions of the minimum correlated F-variable arises in many applied statistical problems including simultaneous analysis of variance (SANOVA), equality of variance, selection and ranking populations, and reliability analysis. In this paper, negative binomial sampling technique is employed to derive the distributions of the minimum of chi-square variables and hence the distributions of the minimum correlated F-variables. The work presented in this paper is divided in two parts. The first part is devoted to develop some combinatorial identities arised from the negative binomial sampling. These identities are constructed and justified to serve important purpose, when we deal with these distributions or their characteristics. Other important results including cumulants and moments of these distributions are also given in somewhat simple forms. Second, the distributions of minimum, chisquare variable and hence the distribution of the minimum correlated F-variables are then derived within the negative binomial sampling framework. Although, multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of the distributions. The computation methods we adopted are exact and no interpolations are involved.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.369-386
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• 2005

Various aspects of structural optimization techniques under transient loads are extensively reviewed. The main themes of the paper are treatment of time dependent constraints, calculation of design sensitivity, and approximation. Each subject is reviewed with the corresponding papers that have been published since 1970s. The treatment of time dependent constraints in both the direct method and the transformation method is discussed. Two ways of calculating design sensitivity of a structure under transient loads are discussed - direct differentiation method and adjoint variable method. The approximation concept mainly focuses on re- sponse surface method in crashworthiness and local approximation with the intermediate variable Especially, as an approximated optimization technique, Equivalent Static Load method which takes advantage of the well-established static response optimization technique is introduced. And as an application area of dynamic response optimization technique, the structural optimization in flexible multibody dynamic systems is re- viewed in the viewpoint of the above three themes

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.1
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• pp.41-48
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• 1999

This paper presents a production method to GRM coefficients which is consists of 3n polarities to n variables over GF(3). General production method is searching for transformation matrix for a single variable and then kronecker products for n times. This paper presents a production method of GRM coefficients using DD(Decision Diagrma). Change of coefficients to a single variable are apply to DD and extended to n variables.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.6
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• pp.521-532
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• 2007

In the derivation of mild slope equation, a Galerkin method is used to rigorously form the Sturm-Liouville problem of depth dependent functions. By use of the canonical transformation to the dependent variable of the equation a reduced Helmholtz equation is obtained which exclusively consists of terms proportional to wave number, bottom slope and bottom curvature. Through numerical studies the behavior of terms is shown to play an important role in wave transformations over variable depth and it is proved that their relative magnitudes limit applicability of the mild slope equation(MSE) against the modified mild slope equation(MMSE).

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1260-1263
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• 2000

Vector control of a single phase induction machine(SPIM) is usually employed by mechanical methods than electrical ones. The disadvantage of a SPIM has large noise at the starting. Using auxiliary winding which is only utilized for starting, the SPIM can be controlled with the vector control method. Regarding a auxiliary winding one phase, the SPIM is analyzed by the unsymmetrical two phase motor and phase transformation is unnecessary such as three phase IM. Including a auxiliary winding, SPIM is modeled by mathematical getting by component of turns ratio with main to auxiliary winding. It will be take with complicated resultant formula, by comparison to symmetrical three phase TM. For using the vector control theory, it must be decoupled of rotor flux and torque component. stator current is controlled and decoupled. This paper presents a variable-speed control system of SPIM, which to decoupled with flux and torque component and to use machine equivalent circuit referred to rotor, conventionally three phase IM by similar method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.31-39
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• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.403-410
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• 2014

Binary logistic regression analysis is a statistical technique that explains binary response variable by quantitative or qualitative explanatory variables. In the binary logistic regression model, the probability that the response variable equals, say 1, one of the binary values is to be explained as a transformation of linear combination of explanatory variables. This is one of big barriers that non-statisticians have to overcome in order to understand the model. In this study, an educational tool is developed that explains the need of the binary logistic regression analysis using Excel VBA. More precisely, this tool explains the problems related to modeling the probability of the response variable equal to 1 as a linear combination of explanatory variables and then shows how these problems can be solved through some transformations of the linear combination.