• Korean Journal of Culture and Social Issue
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• v.17 no.1
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• pp.19-49
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• 2011

In this study, multilateral conceptualizations of underemployment were measured in terms of wages, social status, skill utilization and permanence of the job, and then the effects of antecedents on underemployment and the effects of underemployment on organizational adaptation were examined. Data obtained by a longitudinally designed survey at intervals of 18 months with the reemployed(N = 153) after job loss were used. The underemployment measures include 1) the ratio of wage change 2) the ratio of status change 3) the ratio of education 4) the occurrence of change from the permanent job to temporary job, 5) overqualification - growth opportunity, 6) overqualification - mismatch. The first four measures are social-economic and objective measures and the last two measures are psychological and self-reported ones. Demographic variables(sex, age, education level, and period of unemployed), circumstantial variables(economic hardship, number of dependents), and psychological variables(job-seeking self-efficacy, depression/anxiety, latent function) are included in antecedents. In the effects of antecedents on underemployment, age increases the level of underemployment in the aspects of wage and job status. Economic hardship increases the possibility of underemployment in the aspects of education and number of dependents increases the possibility of underemployment in the aspects of job status. Job seeking self-efficacy decreases the possibility of underemployment in the overqualification - no growth. Retention of latent function during the period of unemployment lowers the possibility of underemployment in the overqualification - no growth. The level of depression and anxiety during the period of unemployment raises the possibility of underemployment in terms of education and in the overqualification - mismatch. In the effects of underemployment on organizational adaptation, the higher the level of underemployment in the aspect of education is, the lower the level of person-organization fit, emotional commitment, and job satisfaction are. And the transition from permanent job to temporary job makes emotional commitment and job satisfaction lower. No growth and mismatch exerted a significant influence on organizational adaptation generally.

• Korean Journal of Culture and Social Issue
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• v.9 no.1
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• pp.115-137
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• 2003

This study aims to investigate the related variables of self-esteem and depression among the Korean elderly people living alone and examine the relationships or interactions between those variables. Participants were 676 elderly men and women who were at least 65 years of age(M=76.17, sd=7.60) and lived in Seoul, Korea. Three hundred seventy eight participants of this study were living alone. Participants completed questionnaires and psychological tests including: Rosenberg's Self-Esteem Scale, Zung's Self-Rating Depression Scale, The Index of Activities of Daily Living(IADL), Social Support Index(SSI), and Life Satisfaction in the Elderly Scale(LSES). Main statistical designs were 2(gender)×2(residential types), Pearson-product moment and regression analysis. Results indicated that the elderly living alone recognized their health poorer, have lower economic status, and received less social supports than the elderly lived with others. The elderly men who had children were more likely to lived alone. And the elderly men living alone received less social supports than the elderly women living alone, and significant gender difference was found in the reason of living alone. The elderly men living alone had lower self-esteem than the elderly women living alone, while the elderly living alone showed more depressive symptoms than the elderly living with others. There were 2-way interactions both in self-esteem and depression by gender and residential types. There was highly significant gender difference in self-esteem only for the elderly living alone, and it was found that there was no significant difference in depression between elderly men living alone and women living with others. Regression analysis revealed that physical function and self-reported health are predictors of self-esteem, and physical function, self-reported health, and social support are predictors of depression for the Korean elderly living alone. These findings reiterate the role of physical function, social support, health in self-esteem and depession among the elderly and suggest the gender role for quality of life among the Korean elderly living alone.

• Journal of the Korean Society of Radiology
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• v.83 no.5
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• pp.1059-1070
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• 2022

Purpose To compare the sensitivity of tumor detection and inter-observer agreement between acquired diffusion-weighted imaging (aDWI) b2000 and computed DWI (cDWI) b2000 in patients with prostate cancer (PCa). Materials and Methods Eighty-eight patients diagnosed with PCa by radical prostatectomy and having undergone pre-operative 3 Tesla-MRI, including DWI (b, 0, 100, 1000, 2000 s/mm²), were included in the study. cDWI b2000 was obtained from aDWI b0, b100, and b1000. Two independent reviewers performed a review of the aDWI b2000 and cDWI b2000 images in random order at 4-week intervals. A region of interest was drawn for the largest tumor on each dataset, and a Prostate Imaging-Reporting and Data System (PI-RADS) score based on PI-RADS v2.1 was recorded. Histologic topographic maps served as the reference standard. Results The study population's Gleason scores were 6 (n = 16), 7 (n = 53), 8 (n = 9), and 9 (n = 10). According to the reviewers, the sensitivities of cDWI b2000 and aDWI b2000 showed no significant differences (for reviewer 1, both 94% [83/88]; for reviewer 2, both 90% [79/88]; p = 1.000, respectively). The kappa values of cDWI b2000 and aDWI b2000 for the PI-RADS score were 0.422 (95% confidence interval [CI], 0.240-0.603) and 0.495 (95% CI, 0.308-0.683), respectively. Conclusion cDWI b2000 showed comparable sensitivity with aDWI b2000, in addition to sustained moderate inter-observer agreement, in the detection of PCa.

• Journal of the Daesoon Academy of Sciences
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• v.48
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• pp.269-303
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• 2024

Donghak's teaching, In-nae-cheon, means "humans are divine." It is said, "When humans were formed, God's blessing was required for their formation." Donghak's Sincerity, Respectfulness, and Faithfulness is based on believing in God, respecting God, and practicing His teachings with utmost sincerity. These are key to implementing In-nae-cheon. On the other hand, the Three Essential Attitudes in Daesoon Thought, also Sincerity, Respectfulness, and Faithfulness, appear in a religious sense. These can be distinguished from Sincerity, Respectfulness, and Faithfulness in the Donghak moral sense. Sincerity, Respectfulness, and Faithfulness in the context of the Three Essential Attitudes in Daesoon Thought goes beyond moral awareness, and calls for belief in God as the Absolute. Accordingly, Sincerity, Respectfulness, and Faithfulness in this context, that of Daesoon Thought, aims at the realization of an Earthly Paradise wherein God's will can be achieved. Humans participating in the construction of Earthly Paradise value the practice of Sincerity, Respectfulness, and Faithfulness. In Daesoon Thought, it is said that when one exerts sincerity, respect, and faith in God (Sangje), all the blessings and fortune of the Later World, even those of longevity, will be endowed through transformation via effortless action (無爲而化). Accordingly, Sincerity, Respectfulness, and Faithfulness in the context of the Three Essential Attitudes in Daesoon Thought is based on God's descent into the world and His Reordering Works of Heaven and Earth (天地公事). This is a religious faith that worships Sangje and is based on the doctrinal dimension of 'guarding against self-deception (毋自欺)' and the philosophical dimension of Sincerity, Respectfulness, and Faithfulness in the context of the Three Essential Attitudes in Daesoon Thought. Donghak's In-nae-cheon and the Three Essential Attitudes in Daesoon Thought can be compared and analyzed. Therefore, in order to clearly compare and analyze the moral significance of Donghak history and the religious meaning of Daesoon Thought, Roderick Ninian Smart's method of religious phenomenology can be actively used. In this way, the ethical and legal dimensions of Donghak's In-nae-cheon and the doctrinal and philosophical dimensions of the Three Essential Attitudes in Daesoon Thought can be compared and analyzed. From this style of research, it can be concluded that the realization of commonly shared spirituality can be an opportunity for greater human dignity.

• Journal of the Korean Society of Radiology
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• v.84 no.2
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• pp.427-440
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• 2023

Purpose This study aimed to investigate the correlation between the fat signal fraction (FF) of the fat-dominant bone tissue of the knee joint, measured using the MRI Dixon method (DIXON) technique, and bone mineral density (BMD). Materials and Methods Among the patients who underwent knee DIXON imaging at our institute, we retrospectively analyzed 93 patients who also underwent dual energy X-ray absorptiometry within 1 year. The FFs of the distal femur metaphyseal (Fm) and proximal tibia metaphyseal (Tm) were calculated from the DIXON images, and the correlation between FF and BMD was analyzed. Patients were grouped based on BMD of lumbar spine (L), femoral neck (FN), and common femur (FT) respectively, and the Kruskal-Wallis H test was performed for FF. Results We identified a significant negative correlation between TmFF and FN-BMD in the entire patient group (r = -0.26, p < 0.05). In female patients, TmFF showed a negative correlation with FN-BMD, FT-BMD, and L-BMD (r = -0.38, 0.28 and -0.27, p < 0.05). In male patients, FmFF was negatively correlated with only FN-BMD and FT-BMD (r = -0.58 and -0.42, p < 0.05). There was a significant difference in the TmFF between female patients grouped by BMD (p < 0.05). In male patients, there was a significant difference in FmFF (p < 0.05). Conclusion Overall, we found that FF and BMD around the knee joints showed a negative correlation. This suggests the potential of FF measurement using DIXON for BMD screening.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.1
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• pp.65-82
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• 2008

Statement of problem : Today's market economy has been changed more and more to consumer concerned. It is owing to not only consumers ' rising standard of living and education, but also purchasers' easy accessibilities to products through various mass media. The consumer centered market system, where customer can choose items with diverse alternatives to satisfy their self esteem, is also applied to the field of medical business, and accelerated by an increasing income level of shoppers and introducing the whole nations' medical insurance system. Today, the medical industry has become competitive due to increasing number of medical institutions and medical personnel, and this offers wide choices to consumers in the medical market place. At this point of time, it is essential to survey on the primary factor of gratification for the patient in the Dental clinic, as well as on the problems and suggestions in medical service. Purpose : The analysis in this study shows essential factors and expected influential elements in satisfaction of the patient in the Dental Hopsital, and strategic suggestions for the provider of dental service, which can be of benefit to the prospective customer as well as can make improvement in the quality of dental treatment service. Material and method : This study had been researched by collecting and analyzing the organized questionnaires, which were filled in directly from 784 patients, who visit Dental Hospital, Yonsei University in Seoul, from January 23rd to April 15th. Result : It can be summarized like the followings. 1. The social and demographical peculiarities of respondents are as follows. Samples of gender and marital status are adequately extracted, but data on occupation and treatment are are under a bias toward students, undergraduates and graduate students, and orthodontics. 2. 74% of patients who answer the questionnaire were highly satisfied with the service of dental clinic in the section of overall satisfaction. 3. The survey result about specific service of dental treatment, within sections of independent variables, is like the followings; Patients are highly gratified with service system, kindness, explanation, explanation on expected waiting hours, reservation system, emergency measures, expert treatment, existence of knowledge of dentistry, size of hospital, disinfection, equipment and parking, but lowly satisfied with expense of treatment, preparatory hours for treatment, waiting hours, treatment hours and the period of subscription. 4. The correlation analysis showed that there is no significant linear relationship between the independent variables. 5. The probit regression analysis showed that 8 out of 34 independent variables explained the dependent variables at the level of 0.01. 6. It shows that 8 independent variables, which can affect customers 'satisfaction, are clearing up of inconvenience, service system, kindness, explanation, treatment hours per attendance, reservation system, existence of knowledge of dentistry, and contentment of equipment in the hospital. Conclusion : The consumer's satisfaction totally relies on subjective evaluations of customers. Providing appropriate service, which can meet the criteria for the customer who demands various wares, pursues luxury goods, and expects high quality of medical service, is essential to fulfill patients' satisfaction. Many medical institutions do their best to satisfy their customer, touch their consumer, and offer patience centered services, and it is also applied to the field of dentistry. Establishing brand new strategic managements and elevating the quality of dental service based on this survey are required to improve the satisfaction of patience in the Dental Hospital.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.8-19
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• 2008

Purpose : To investigate the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar nuclear Overhauser effect/enhancement (NOE) interaction through 2D- correlation spectroscopy (COSY) and 2D- NOE spectroscopy (NOESY) techniques. Materials and Methods : All 2D experiments were performed on Bruker Avance 500 (11.8 T) with the zshield gradient triple resonance cryoprobe at 298 K. Human brain metabolites were prepared with 10% $D_2O$. Two-dimensional spectra with 2048 data points contains 320 free induction decay (FID) averaging. Repetition delay was 2 sec. The Top Spin 2.0 software was used for post-processing. Total 7 metabolites such as N-acetyl aspartate (NAA), creatine (Cr), choline (Cho), lutamine (Gln), glutamate (Glu), myo-inositol (Ins), and lactate (Lac) were included for major target metabolites. Results : Symmetrical 2D-COSY and 2D-NOESY pectra were successfully acquired: COSY cross peaks were observed in the only 1.0-4.5 ppm, however, NOESY cross peaks were observed in the 1.0-4.5 ppm and 7.9 ppm. From the result of the 2-D COSY data, cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methylene protons (CH2(3,$H{\alpha}$)) at 2.50ppm and methylene protons ($CH_2$,(3,$H_B$)) at 2.70 ppm were observed in NAA. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. From the result of 2-D NOESY data, cross peaks between the NH proton at 8.00 ppm and methyl protons ($CH_3$) were observed in NAA. Cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methyl protons (CH3) at 3.03 ppm and methylene protons (CH2) at 3.93 ppm were observed in Cr. Cross peaks between the methylene protons ($CH_2$(3)) at 2.11 ppm and methylene protons ($CH_2$(4)) at 2.35 ppm, and between the methylene protons($CH_2$ (3)) at 2.11 ppm and methine proton (CH(2)) at 3.76 ppm were observed in Glu. Cross peaks between the methylene protons (CH2 (3)) at 2.14 ppm and methine proton (CH(2)) at 3.79 ppm were observed in Gln. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. Conclusion : The present study demonstrated that in vitro 2D-COSY and NOESY represented the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar NOE interaction. This study could aid in better understanding the interactions between human brain metabolites in vivo 2DCOSY study.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.381-391
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• 1997

In an epidemiological study of metal workers exposed to metalworking fluids (MWF), the prevalence time of Evolution, seasonal occurrence and clinical type of contact dermatitis were investigated. Compostional analysis of MWF with HPLC, dermatological examination and two consecutive questionnaire surveys were conducted. Study population was divided into two groups ; workers contact to cutting oil and workers contact to rust preventive oil. In the analysis of MWF, aliphatic hydrocarbons, having 12-20 carbons, was most common composition(49.04%) of cutting oil otherwise, major contents (90.99%) of the rust preventives oil were aliphatic hydrocarbons composed of 6-9 carbons. The frequency (point prevalence) of contact dermatitis(CD) was 7(12.7 per 100 subjects) in the dermatological examination of 55 workers. As the result of second survey for contact dermatitis, cumulative prevalence of oil working full-time and recent 1 year prevalence in two groups were 28.0, 16.7 and 15.1, 12.5 per 100 subjects. There were no difference in the prevalence of CD by oil, age, oil contact duration. Summer is the most common evolution season in workers exposed to cutting oil, but not in workers exposed to rust preventive oil. Major clinical type of CD was erythematous papules in both groups. It presents the importance of preventive measures that 51.1% suffer from contact dermatitis had medical care at their own expense, and 47.1% of them felt serious about their contact dermatitis. From the fact that 68.6% think cotton gloves protective apparatus, we emphasize the need for health education.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.