• Journal of the Korean Society of Radiology
• /
• v.83 no.1
• /
• pp.149-161
• /
• 2022

Purpose To investigate the correlation between computer-aided diagnosis (CAD) parameters in 3-tesla (T) MRI and pathologic immunohistochemical (IHC) markers in invasive carcinoma of no special type (NST). Materials and Methods A total of 94 female who were diagnosed with NST carcinoma and underwent 3T MRI using CAD, from January 2018 to April 2019, were included. The relationship between angiovolume, curve peak, and early and late profiles of dynamic enhancement from CAD with pathologic IHC markers and molecular subtypes were retrospectively investigated using Dwass, Steel, Critchlow-Fligner multiple comparison analysis, and univariate binary logistic regression analysis. Results In NST carcinoma, a higher angiovolume was observed in tumors of higher nuclear and histologic grades and in lymph node (LN) (+), estrogen receptor (ER) (-), progesterone receptor (PR) (-), human epidermal growth factor 2 (HER2) (+), and Ki-67 (+) tumors. A high rate of delayed washout and a low rate of delayed persistence were observed in Ki-67 (+) tumors. In the binary logistic regression analysis of NST carcinoma, a high angiovolume was significantly associated with a high nuclear and histologic grade, LN (+), ER (-), PR (-), HER2 (+) status, and non-luminal subtypes. A high rate of washout and a low rate of persistence were also significantly correlated with the Ki-67 (+) status. Conclusion Angiovolume and delayed washout/persistent rate from CAD parameters in contrast enhanced breast MRI correlated with predictive IHC markers. These results suggest that CAD parameters could be used as clinical prognostic, predictive factors.

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

• Korean Chemical Engineering Research
• /
• v.55 no.3
• /
• pp.322-331
• /
• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• 한국노년학
• /
• v.40 no.4
• /
• pp.707-727
• /
• 2020

This study aims to empirically analyze the role that perception of the probability of lonely death among the elderly people living alone plays in the relationship between perceived social support and preference for institutional care based on Andersen's expanded Behavioral Model (2002). The subjects (n=676) of this study were the elderly people living alone, extracted from the "2018 Seoul Aging Survey." With "perceived social support" as an independent variable, "preference for institutional care" as a dependent variable, and "perception of the probability of lonely death" as a mediator variable, we conducted a Binary Logistic Regression to follow the three steps of analyzing mediation effect, as suggested by Baron and Kenny (1986). The results showed that perceived social support has a negative effect on the preference for institutional care and perception of the probability of lonely death among the elderly people living alone; at the same time, perception of the probability of lonely death was found to have a positive effect on their preference for institutional care. Lastly, perception of the probability of lonely death was found to partially mediate the effect of perceived social support among the elderly people living alone in terms of their preference for institutional care. Based on these findings, the practical implications of this study can be summarized as follows. First, various programs and support should be provided to the elderly people living alone in order to enhance the level of perceived social support, a factor that has been confirmed to increase preference for institutional care among the elderly people living alone. Second, as the perception of the probability of lonely death was confirmed to be a psychosocial factor of the preference for institutional care, we need to promote education and support for older people living alone to prepare them for lonely death. These efforts are expected to form a foundations for implementing a community-based integrated care system, "Aging in Place," which is the policy direction required for older people care.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.5
• /
• pp.77-90
• /
• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• 한국노년학
• /
• v.37 no.1
• /
• pp.83-102
• /
• 2017

Expending on a life course perspective, this study explores the long-term and short-term reciprocity in parent-child relationships in Korean context. Since the reasons for providing filial support are believed to differ by gender, we focused on how a child's gender affects both types of reciprocity. Data were collected from middle-aged sons (N=726) and daughters (N=883) with at least one surviving parent. Logistic regression was then conducted in order to examine the relations between the support a child currently provides to parents and the current or previous support received from the parents. Dependent variables are financial and instrumental support that middle-aged child currently provide to the parents. The financial and instrumental support a child received from the parents within a year are included in the model as an independent variable to assess short-term reciprocity. The level of financial support a child has received during the transition to adulthood process is included in the model as a independent variable to explore long-term reciprocity. Result supports the existence of gender differences in the long-term reciprocity. Daughters provided instrumental support in response to the financial support that they had received from parents during the transition to adulthood process. However, for sons, this tendency was not found. When it comes to financial support, long-term reciprocity was observed neither for the sons nor for the daughters. Both sons and daughters are prone to provide financial support to the aged parents regardless of the level of financial support they had received during the transition to adulthood process. Short-term reciprocity was found both in sons and daughters. when they have been receiving a financial or an instrumental support from the aged parents within a year, they tend to provided instrumental support to the parents. This study shows that the aged parents still fulfill the reciprocal relationship to a certain degree. Secondly, we can conclude that the norm of reciprocity interplays with the norm of filial responsibility in contemporary Korea.

• 한국노년학
• /
• v.39 no.1
• /
• pp.127-144
• /
• 2019

The purpose of this study is to compare the perceptions of loneliness, death anxiety, and social capital among older adults living in urban and rural communities and to examine the moderating effects of social capital on the relationship between loneliness and death anxiety. Utilizing the survey data collected by the Aging Society and Social Capital Research Center in 2018, we analyzed 839 older adults living in urban areas and 322 rural older adults living in rural areas. We used descriptive statistics, results from t-tests, and χ² tests to compare the rates of loneliness, social capital, and death anxiety perceived by older adults across urban and rural areas. The moderating effects of social capital on the relationship between loneliness and death anxiety were tested by logistic regression analyses for each group of urban and rural older adults. Compared to older adults living in rural areas, a greater number of older adults in urban areas reported death anxiety and higher levels of loneliness. However, the perceived levels of social capital were higher among rural older adults. The moderating effects of social capital on the relationship between loneliness and death anxiety were not found among older adults living in urban area, but, for older adults living in rural areas, social capital including social cohesion and social support moderated the relationship between loneliness and death anxiety. The results of this study suggest that regional differences shown in the perceptions of loneliness, death anxiety, and social capital should be addressed, when considering extensions of social capital and related interventions to deal with loneliness and death anxiety among older adults.