• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.207-212
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• 2000

본 연구는 최근의 사회조사와 선거자료를 이용하여 한국사회의 지역주의의 특징을 살펴보고자 한다. 첫째, 최근의 선거결과에 보이는 지역주의적 투표는 지역간 사회적 거리를 잘 보여주고 있다. 둘째, 이러한 사회적 거리는 '편견과 차별'의 형태로 다양한 일상생활에서 존재하고 있다. 많은 사람들은 이러한 편견을 믿고 있으며, 편견에 의한 지역적 차별을 경험하고 있다. 특히 이러한 경험은 특정지역(호남)과 관련되어 있다. 셋째, 이러한 정치적 측면(지역주의적 투표)과 사회적 측면(지역간 편견)을 선거제도와 연결하여 살펴봄으로써, 앞으로 한국사회의 정치제도의 변화에 대한 전망을 할 수 있다. 연구의 잠재적인 가정은 선거에 있어서 지역적인 투표가 무조건 '나쁜' 것만은 아니라는 것이다. 한국 정치에서 나타나는 지도자나 이데올로기의 편향은 많은 사람들로 하여금 투표나 선거에서 출신지를 중요한 요소로 삼게 하였다. 이러한 요소는 쉽게 사라지지는 않을 것이며, 앞으로 선거제도의 변화에 중요한 역할을 할 것이다. 이러한 예측은 세 가지 중요한 요소에 근거하고 있다. 첫째, 유권자들의 지역주의에 대한 믿음과 예측은 쉽게 사라지지 않을 것이다. 둘째, 정치지도자들은 지역주의를 선거와 관련한 자신의 이익을 위해서 최대한 이용할 것이다. 셋째, 지역주의에 근거한 유권자들의 성향은 최근 선거와 투표에서 더욱 강화되고 있다. 정치엘리트들이 지역적인 기반을 중심으로 결합하려는 경향이 강해지고 있다. 이러한 경향은 이들 정치엘리트 사이의 내각중심제에 대한 선호도와 지역당의 출현 가능성을 증가시킬 것이다.도 설치행위의 처분성과 관련하여 횡단보도의 설치행위와 같은 일반적인 명령을 항고소송의 대상으로 할 필요성이 존재한다면 이른바 독일에서의 일반처분이라는 개념을 무리하게 받아들여 이를 행정행위의 한 유형으로 한다거나 우리 판례와 같이 "직접적이고 구체적인 법적 효과"를 미치는 명령이라는 명확치 않은 기준에 의하여 처분성을 인정하기보다는 일반적인 명령과 개별적인 행정행위를 구분하고 명령에 대하여도 취소소송의 대상으로 삼도록 하는 보다 명확하고 일관성 있는 논의전개를 제안하였다.수 있었다.로 첨가하여 48시간 배양한 후 암항원 유전자 발현성을 측정한 결과 세포주에 따라 다소 차이는 있으나 대개 0.2 uM농도에서도 유전자 발현이 유도되었으며 1, 5 uM농도에서 매우 강하게 유도되었다. ADC 처리가 페암세포주의 MHC와 B7 발현을 증가시키는가를 알아보기 위해 1 uM 농도의 ADC를 72시간 처치한 후 FACS 분석을 실시한 결과 4개의 페암세포주에서 MHC 및 B7분자의 발현은 유도되지 않았다. 또 ADC농도가 세포성장에 미치는 영향을 알아보기 위하여 ADC를 0.2, 1, 5 uM농도로 96시간 처치 후 세포수를 측정하여 상대성장지수를 알아본 결과 ADC 처치 농도가 증가함에 따라 세포의 성장은 매우 감소하였다. 결론: 폐암세포주에서 ADC처치는 MAGE, GAGE 및 NY-ESO-1과 같은 세포독성 T 림프구 반응을 유도할 수 있는 암항원의 발현을 증가시킬 수 있으며, ADC의 세포독성과 항원 발현 유발시간을 분석할 때 1 uM 농도에서 48시간 처치한 후 ADC가 없는 배지에서

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.15-26
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• 2006

Although numerous investigations have been performed over the years to predict the behavior and bearing capacity of piles, the mechanisms are not yet entirely understood. The prediction of bearing capacity is a difficult task, because large numbers of factors affect the capacity and also have complex relationship one another. Therefore, it is extremely difficult to search the essential factors among many factors, which are related with ground condition, pile type, driving condition and others, and then appropriately consider complicated relationship among the searched factors. The present paper describes the application of Artificial Neural Network (ANN) in predicting the capacity including its components at the tip and along the shaft from dynamic load test of the driven piles. Firstly, the effect of each factor on the value of bearing capacity is investigated on the basis of sensitivity analysis using ANN modeling. Secondly, the authors use the design methodology composed of ANN and genetic algorithm (GA) to find optimal neural network model to predict the bearing capacity. The authors allow this methodology to find the appropriate combination of input parameters, the number of hidden units and the transfer structure among the input, the hidden and the out layers. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the bearing capacity of driven piles.

• Journal of Oral Medicine and Pain
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• v.30 no.3
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• pp.287-300
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• 2005

Squamous cell carcinoma (SCC) in head and neck show a variability in the response to chemotherapy, even when it present with similar histological tumor type, grade, and clinical stage. The purpose of present study it to identify predictive bio-marker for the sensitivity or resistance to conventional chemotherapeutic agents, 5-fluorouracil (5-FU) and Cisplatin Oral cancer cell lines were used in present study. MTT assay was performed to evaluate the sensitivity and/or resistance to 5-FU and Cisplatin. And RT-PCR was carried out for evaluation of the mRNA expressions of various genes associated with mutation, inflammation (COX pathway), cell cycle, senescence and extracellular matrix (ECM). The molecules which are correlated with the sensitivity to 5-FU are XPA, XPC, OGG, APEX, COX-2, PPAR, Cyclin E, Cyclin B1, CDC2, hTERT, hTR, TIMP-3, TIMP-4 and HSP47. And the molecules are correlated with the sensitivity to Cisplatin are COX-1, iNOS, eNOS, PCNA, collagen 1 and MMP-9. Taken together, when choosing the appropriate chemotherpeutic agents for patients, considering the molecules which are correlated or reversely correlated is helpful to choose the resonable agents for cancer patients.

• Childhood Kidney Diseases
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• v.3 no.2
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• pp.209-216
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• 1999

Purpose : Nephrogenic diabetes insipidus (NDI) is a rare X-linked disorder associated with renal tubule resistance to arginine vasopressin (AVP). The hypothesis that the defect underlying NDI might be a dysfunctional renal AVPR2 has recently been proven by the identification of mutations in the AVPR2 gene in NDT patients. To investigate the association of mutations in th AVPR2 gene with NDI, we analyzed the AVPR2 gene located on the X chromosome. Methods : We have analyzed the AVPR2 gene in a kindred with X-linked NDI. The proband and proband's mother were analyzed by polymerase chain reaction-single strand conformational polymorphism(PCR-SSCP) and DNA sequencing of the AVPR2 gene. We also have used restriction enzyme analysis of genomic PCR product to evaluate the AVPR2 gene. Results : C to T transition at codon 202, predictive of an exchange of tryptophan 202 by cysteine(R202C) in the third extracellular domain was identified. This mutation causes a loss of Hae III site within the gene. Conclusion : We found a R202C missense mutation in the AVPR2 gene causing X-linked NDI, and now direct mutational analysis is available for carrier screening and early diagnosis.

• Clinical and Experimental Pediatrics
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• v.52 no.1
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• pp.36-43
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• 2009

urpose : The renin-angiotensin system (RAS) has been demonstrated to play a major role in regulating blood pressure. Therefore, components of the RAS are likely candidate genes that may predispose an individual to essential hypertension and cardiovascular complications. Among them, the M235T polymorphism of the angiotensinogen gene has been speculated to be associated with elevated circulating angiotensinogen concentrations and essential hypertension. This study aimed to analyze the angiotensinogen M235T polymorphism in hypertensive adolescents and investigate its relationship with cardiovascular risks. Methods : Forty Korean hypertensive adolescents (aged 16-17, systolic $BP{\geq}140 mmHg$ and/or diastolic $BP{\geq}90 mmHg$) and fifty seven normal adolescents were included. Obesity index (OI), body mass index (BMI) were calculated. BP was measured by oscillometric methods in resting state. Polymerase chain reaction (PCR) technique was performed on DNA from the hypertensives subjects to analyze the M235T polymorphism. Serum homocysteine, insulin, renin, aldosterone and angiotensin converting enzyme (ACE) were tested according to each genotype. The carotid intima-media thickness (IMT) and carotid artery diameter, Pulse wave velocity (PWV) and ankle-brachial index (ABI) were measured according to each genotype. Results : Genotype frequencies of T/T, M/T and M/M were 62.5%, 35.0%, 2.5%, respectively in hypertensive adolescents. The results were not significantly different compared to control group. Serum insulin, renin levels, BMI and OI were significantly higher in thoses with the M/M genotype as compared to those with the T/T of M/T genotype. Conclusion : This study showed that the M235T polymorphism was not associated with essential hypertension or any cardiovascular risks. Further clinical research is required to ascertain the relationship between this polymorphism and cardiovascular complications in Korean hypertensive adolescents.

• Clinical and Experimental Reproductive Medicine
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• v.36 no.3
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• pp.163-174
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• 2009

Objectives: Members of the immortalization-upregulated protein (IMUP) family are nuclear proteins implicated in SV40-mediated immortalization and cellular proliferation, but the mechanisms by which their expression is regulated are still unknown in placenta. To investigate to expression and functions of IMUPs in placenta, we conducted to compare IMUPs expression in normal and preeclamptic placenta tissues and analyzed the function of IMUP-2 in HTR-8/SVneo trophoblast cells after IMUP-2 gene transfection. Methods: The expression of IMUPs was analyzed in placental tissues from the following groups of patients (none underwent labor): 1) term normal placenta (n=15); 2) term with preeclamptic placeneta (n=15); and 3) pre-term with preeclamptic placenta (n=11) using semi-quantitative RT-PCR, RNA in situ hybiridization, immunohistochemistry, and Western blot. In order to evaluate the function of IMUP-2 in HTR-8/SVneo trophoblast cells, IMUP-2 plasmids were transfected into HTR-8/SVneo trophoblast cells for 24 hours. Results: We observed that IMUPs are mainly expressed in the syncytiotrophoblasts and syncytial knot of placental villi. The expression of IMUP-1 was not differences between normal and preeclamptic placenta tissues. However, IMUP-2 expression was significantly higher in preterm preeclamptic placenta tissues than in normal placenta tissues without labor (p<0.001). Furthermore, we confirmed overexpression of IMUP-2 induced apoptosis in HTR-8/SVneo trophoblast cells through up-regulation of pro-apoptotic proteins. Conclusions: These results suggest that the expression of IMUP-2 is involved in placental development as well as increased IMUP-2 expression is associated with preeclampsia through the inducing of trophoblast apoptosis.

• Journal of Life Science
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• v.31 no.3
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• pp.356-365
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• 2021

Recently, we sequenced the entire genome of a freshwater agar-degrading bacterium Cellvibrio sp. KY-GH-1 (KCTC13629BP) to explore genetic information encoding agarases that hydrolyze agarose into monomers 3,6-anhydro-L-galactose (L-AHG) and D-galactose. The KY-GH-1 strain appeared to possess nine β-agarase genes and two α-neoagarobiose hydrolase (α-NABH) genes in a 77-kb agarase gene cluster. Based on these genetic information, the KY-GH-1 strain-caused agarose degradation into L-AHG and D-galactose was predicted to be initiated by both endolytic GH16 and GH86 β-agarases to generate NAOS (NA4/NA6/NA8), and further processed by exolytic GH50 β-agarases to generate NA2, and then terminated by GH117 α-NABHs which degrade NA2 into L-AHG and D-galactose. More recently, by employing E. coli expression system with pET-30a vector we obtained three recombinant His-tagged GH50 family β-agarases (GH50A, GH50B, and GH50C) derived from Cellvibrio sp. KY-GH-1 to compare their enzymatic properties. GH50A β-agarase turned out to have the highest exolytic β-agarase activity among the three GH50 isozymes, catalyzing efficient NA2 production from the substrate (agarose, NAOS or AOS). Additionally, we determined that GH117A α-NABH, but not GH117B α-NABH, could potently degrade NA2 into L-AHG and D-galactose. Sequentially, we examined the enzymatic characteristics of GH50A β-agarase and GH117A α-NABH, and assessed their efficiency for NA2 production from agarose and for production of L-AHG and D-galactose from NA2, respectively. In this review, we describe the benefits of recombinant GH50A β-agarase and GH117A α-NABH originated from Cellvibrio sp. KY-GH-1, which may be useful for the enzymatic hydrolysis of agarose for mass production of L-AHG and D-galactose.

• The Korean Journal of Malacology
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• v.30 no.2
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• pp.155-163
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• 2014

Serpins are a group of proteins involved in the regulation of serine and other type of proteases, and have been identified in many kinds of organisms from invertebrates to vertebrates. Serpins are known to regulate the proteolytic cascades of the innate immune pathways in addition to their roles in blood coagulation, angiogenesis, fibrinolysis, inflammation and tumor suppression. In this study, we have isolated two partial serpin gene fragments from expressed sequence tags (ESTs) of Nesiohelix samarangae. Dotplot analysis indicates that they are of two different types, Ns-serpin type 1 and Ns-serpin type 2. Ns-serpin type 1 has 819 bp coding region (272 amino acids), whereas Ns-serpin type 2 has 555 bp coding region (185 amino acids). Molecular phylogenetic analysis shows that the identified serpins have high similarities to their counterparts in the California see slug, Aplysia californica. Yet, the precise biological and immunological roles of these Ns-serpins remain to be further investigated using RNA interference and other molecular techniques.