• Journal of Microbiology and Biotechnology
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• v.7 no.5
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• pp.299-304
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• 1997

Expression in the periplasm of Escherichia coli of cloned heavy and light chain cDNAs for Fab fragment of a murine monoclonal antibody MabB9 (${\gamma}2b$, K), specific for human plasma apolipoprotein B-100 of LDL, was studied. For the purpose, a vector for two-cistronic expression of the heavy chain cDNA, at the 5' terminus, and light chain cDNA, at the 3' terminus, was constructed using the signal sequences, pelB (for heavy chain) and ompA (for light chain) in a pET vector system. The constructed vector was transformed into E. coli BL21(DE3). The expressed heavy chain (25 kDa) and light chain (23 kDa) of the antibody molecule were detected in total cell extracts as well as in the periplasmic extracts of E. coli.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1867-1873
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• 2000

Function approximation from a set of input-output pairs has numerous applications in scientific and engineering areas. Support vector machine (SVM) is a new and very promising classification, regression and function approximation technique developed by Vapnik and his group at AT&TG Bell Laboratories. However, it has failed to establish itself as common machine learning tool. This is partly due to the fact that this is not easy to implement, and its standard implementation requires the use of optimization package for quadratic programming (QP). In this appear we present simple iterative Kernel Adatron (KA) algorithm for function approximation and compare it with standard SVM algorithm using QP.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.481-490
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• 2013

Classification is an important research area as data can be easily obtained even if the number of predictors becomes huge. The support vector machine(SVM) is widely used to classify a subject into a predetermined group because it gives sound theoretical background and better performance than other methods in many applications. The SVM can be viewed as a penalized method with the hinge loss function and penalty functions. Instead of $L_2$ penalty function Fan and Li (2001) proposed the smoothly clipped absolute deviation(SCAD) satisfying good statistical properties. Despite the ability of SVMs, they have drawbacks of non-robustness when there are outliers in the data. We develop a robust SVM method using a weight function with the SCAD penalty function based on the local quadratic approximation. We compare the performance of the proposed SVM with the SVM using the $L_1$ and $L_2$ penalty functions.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• Journal of the Korean Mathematical Society
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• v.61 no.3
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• pp.547-564
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• 2024

We study totally real and complex subsets of a right quarternionic vector space of dimension n + 1 with a Hermitian form of signature (n, 1) and extend these notions to right quaternionic projective space. Then we give a necessary and sufficient condition for a subset of a right quaternionic projective space to be totally real or complex in terms of the quaternionic Hermitian triple product. As an application, we show that the limit set of a non-elementary quaternionic Kleinian group 𝚪 is totally real (resp. commutative) with respect to the quaternionic Hermitian triple product if and only if 𝚪 leaves a real (resp. complex) hyperbolic subspace invariant.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.75-85
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• 2010

This paper presents a robust 3D model hashing based on object feature vector for 3D content authentication. The proposed 3D model hashing selects the feature objects with highest area in a 3D model with various objects and groups the distances of the normalized vertices in the feature objects. Then we permute groups in each objects by using a permutation key and generate the final binary hash through the binary process with the group coefficients and a random key. Therefore, the hash robustness can be improved by the group coefficient from the distance distribution of vertices in each object group and th hash uniqueness can be improved by the binary process with a permutation key and a random key. From experimental results, we verified that the proposed hashing has both the robustness against various mesh and geometric editing and the uniqueness.

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2002.11a
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• pp.99-99
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• 2002

The hormone resistin is associated with typeII diabetes mellitus in rodent model. Resistin impairs glucose tolerance and insulin action. A new class of anti-diabetic drugs were called thiazolidinediones (TZDs) downregulates a resistin which is induced during adipocyte differentiation. But the connection between increased adiposity and resistin remains unknown. The objectives of this study was to clone a mouse resistin cDNA and to generate transgenic mice overexpressing mouse resistin gene. The 555 bp of mouse resistin was amplified from mob cDNAS by polymerase chain reaction (PCR) and cloned into pCR$\^$(R)/ 2.1 TOPO T-vector. Mouse resistin mRNA on the basis of Genbank sequence (acession no. AF323080). Then, the PCR product was cloned into pTargeT$\^$TM/ mammalian expression vector that has pCMV promoter and chimeric intron. Restriction enzyme analysis with BamH I and Not I was carried out to determine an orientation of the insert in the vector. The pCMV-mus/resistin gene was prepared from previous recombinant pTargeT$\^$TM/-mus/resistin by digestion of Bgl II, and has used for microinjection into pronuclei of one cell embryos. The microinjected embryos were transfered to pseudopregnant foster-mother. Mouse resistin expression was detected in transgenic F1 mice by Reverse Transcriptase- Polymerase Chain Reaction (RT-PCR). Resistin gene expression mouse has heavier body weight which was measured higher level of plasma glucose than that of normal mouse. And in diet-induced experiments, the abdominal fat pads were isolated from each 24h starvation and re-feeding after fasting group mice that were assessed by RT-PCR analysis. In fasting group mice, resistin expression was higher than that of re-feeding group mice. This result suggests that the resistin gene overexpressing mice may be became to obesity and be useful as an animal disease model to be diabetes mellitus caused by insulin resistance of resistin.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.3-19
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• 2017

The purpose of this paper is to analyze the impacts of regional industrial diversity on regional business cycle response to national volatility. We employed mean group and pooled mean group estimators of panel vector error-correction models in order to control unobserved heterogeneity of the port cities, such as Pusan, Ulsan and Incheon. The results show that in various industrial regions, short-term fluctuations in the unemployment rate are small compared to other regions. On the contrary, long-term volatility of manufacturing production index is low in those regions.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.307-309
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• 2007

SVDD의 scale prob1em을 해결하기 위하여, 학습 데이터를 sub-groupings하여 group 단위로 SVDD를 통해 학습함으로써 학습 시간을 줄이는, K-means clustering을 이용한 SVDD 방범(KMSVDD)이 제안되었다. 하지만 KMSVDD는 K-means clustering 알고리즘의 본질상 최적의 K값을 정하기 힘들다는 문제와, 동일한 데이터를 학습할지라도 clustered group이 램덤하게 형성되기 때문에 매번 학습의 결과가 달라지는 문제점이 있었다. 또한 데이터의 분포 상태와 관계없이 무조건 타원(dlliptic) 형태의 K개의 cluster로 나누기 때문에 각각의 나눠진 cluster들은 데이터 분포에 대한 특징을 나타내기 힘들게 된다. 이러한 문제점을 해결하기 위하여 본 논문에서는 데이터 분포에서 mode를 먼저 찾은 후 이 mode를 기준으로 clustering하는 Mean Shift clustering 방법을 이용한 SVDD를 제안하고자 한다. 제안된 알고리즘은 KMSVDD와 비교해 데이터 학습 속도에서는 큰 차이가 없으면서도 데이터의 분포 상태를 고려한 형태로 clustering 한 sub-group을 학습하므로 학습의 정확도가 일정하게 되며, 각각의 cluster는 데이터 분표의 특징을 포함하는 효과가 있다. 또한 Mean Shift Kernel의 bandwidth의 결정은 K-Means의 K와는 달리 어느 정도 여유를 갖고 결정되어도 학습 결과에는 차이가 없다. 다양한 데이터들을 이용한 모의실험을 통하여 위의 내용들을 검증하도록 한다.

• The Korean Journal of Physiology
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• v.19 no.1
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• pp.61-72
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• 1985

In order to compare the cardiac function of various groups of athletes, the resting electrocardiographic time intervals, amplitudes and vectors were analyzed in high school athletes of throwing(n=7), jumping(n=11), short track(n=8), long track(n=14), boxing(n=7), volleyball(n=8) and baseball(n=9), and nonathletic control students(n= 19). All athletic groups showed a significantly longer R-R interval(0.96-1.09 sec) than the controls (0.78 sec). Therefore, the heart rate was significantly slower in atheletes than in the control, but was not different among the different athletic groups. R-R interval is the sum of intervals of P-R, 0-T and T-P: P-R and Q-T intervals showed no difference among the control and athletic groups, but T-P interval in the jump, short track, long track and boxing groups was significantly higher than the control. R-B interval showed a significant correlation with T-P or Q-T intervals but no correlation with P-R or QRS complex. Comparing the amplitude of electrocardiographic waves, the athletic groups showed a lower trend in P wave than the controls. T wave in lead $V_5\;(Tv_5)$ was similar in the athletic and control groups. The long track group showed a significantly higher waves of $Rv_5$, $Sv_1$, and the sum of $Rv_5$ and $Sv_1$ than not only the controls but also the other athletic group. The angles of P, QRS, and T vector in the frontal and horizontal planes were not different among the control and all the athletic groups. Each athletic group stowed a lower trend in amplitude of P vector in the frontal plane, but in horizontal plane, throwing, jump, short track and baseball groups showed a significantly lower than the controls. The amplitude of QRS and T vector was similar in the athletic and control groups, but only the baseball group showed a significantly higher QRS vector in the frontal plane. In taken together, all the athletic groups showed a slower heart rate than the controls, mainly because of elongated T-P interval. Comparing the electrocardiographic waves and vector, the athletic groups showed lower amplitudes of P wave and P vector than the controls. Values of $Rv_5$ and $Sv_1$ strongly suggest that only the long distance runners among the various athletic groups developed a left ventricular hypertrophy.