• Journal of Chest Surgery
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• v.37 no.8
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• pp.684-690
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• 2004

Background: Primary thymic epithelial neoplasm is a type of mediastinal tumors that have various biologic and morphologic features. In this study, we reclassified 59 cases of thymic epithelial tumors by the new WHO classification. We inquired whether the new WHO classification has independent prognostic relevance by analyzing clinical characteristics of thymic epithelial tumors including Masaoka's clinical stage. Material and Method: From December 1986 to August 2003, 59. patients who underwent surgery in the Keimyung University Dongsan Medical Center with definite diagnosis of thymic epithelial tumor were studied. We analyzed the histologic subtype (WHO classification). clinical stage (Masaoka's clinical stage) and patient's characteristics (sex, age, myasthenia gravis, tumor size, invasion. recurrence, metastasis) as prognostic factors. We analyzed the relationship between histologic subtype and clinical stage. Result: 32 patients were male and 27 were female. Mean age was 50.1$\pm$14.2. From WHO A to C, all thymic epithelial tumors were reclassified by the new WHO classification. Six patients (10.2%) had Type A, 7 (11.9%) had Type AB, 7 (11.9%) had Type B$_1$, 10 (16.9%) had Type B$_2$ and 7 (11.9%) had Type B$_3$, 22 (37.3%) had Type C. Two factors were shown by multivariate analysis to be associated with a favorable prognosis: completeness of resection (p=0.003) and non-invasiveness (p=0.001). The overall 5-year survival of the 59 patients was 53%, subtype A and AB were 92.3%, B$_1$ and B$_2$ were 70.2%, and B$_3$ and C were 26.1%. The association between histologic subtype and invasive behavior (stage) was statistically significant (p<0.001). Conclusion: The WHO classfication is not only a histologic classfication of the thymic epithelial tumors but also a significant prognostic factor that influence the survival of thymic epithelial tumors.

• Journal of Food Hygiene and Safety
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• v.18 no.3
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• pp.139-145
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• 2003

The purpose of this study was to investigate the awareness and practice of Korean consumer on food safety. A telephone survey was conducted from 1,040 adults randomly selected from each province and large city of Korea. Therefore, 12.4% of the subjects experienced foodborne illness at least once a year and 0.3% was hospitalized due to the illness. General restaurant (37.2%) and home (21.2%) were the main causative place of foodborne illness, and the most frequently associated foods were meat and meat products (41.7%) and fish and fish products (18.7%). Regarding the causative agent of foodborne illness, the respsondents were aware of Cholera (75.5%), Vibrio gastroenteritis (73%), Shigellosis (65.5%), Bacillary dysentery (65.5%) and Salmonellosis (47.5%) very well; however very few were aware of Listeriosis (9.9%) and brucellosis (8.3%) and ever believed they were not food-related illness. When the survey data were analyzed based on 3 models (Model 1: Knowledge about the pathogens associated food and water, Model 2: The awareness of food safety, Model 3: Attitudes and behavior about foodborne disease prevention and measure) by Multiple regression analysis. The results showed that the awareness of the causative agent of foodborne illness was significantly related with the previous experience of foodborne illness (OR: 1.714) followed by education level (OR: 0.536) and married status (OR: 0.527). The awareness of food safety was significatly related with education level (OR: 0.702). Education (OR: 0.816) and gender (OR:0.650) were the main factors affecting the awareness of the practice to prevent foodborne illness. However, the previous experience of foodborne illness and food safety education, and the awareness of food safety did not show any correlation, suggesting that the experience and awareness of foodborne illness do not affect the real practice of food safety.

• Sleep Medicine and Psychophysiology
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• v.20 no.2
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• pp.63-68
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• 2013

Objectives: Several evidence has been suggested that the circadian gene variants contribute to the pathogenesis of seasonal affective disorder. In this study, we aimed to investigate the polymorphism in RORA (Retinoid-related orphan receptor A) gene in relation to seasonal variations among healthy young adults in Seoul, Korea. Methods: A total of 507 young healthy adult subjects were recruited by advertisement. Seasonal variations were assessed by the Seasonality Pattern Assessment Questionnaire (SPAQ). Single-nucleotide polymorphism in the RORA rs11071547 gene was genotyped by PCR in 507 individuals. Considering summer type as confounding factor, we conducted analysis 478 subjects except 29 subjects of summer type. The Chi-square test was conducted to compare differences between groups of seasonals and non-seasonals. Association between genotypes and Global Seasonality Score (GSS) were tested using ANCOVA (Analysis of covariance). Results: In this sample, the prevalence of SAD was 12.1% (winter type 9.3%, summer type 2.8%). There is no significant difference in genotyping distribution of RORA rs11071547 between groups of seasonals and non-seasonals. Global seasonality score (GSS) and scores of all subscales except body weight and appetite were not significantly different between the group with C allele homozygote and the group with T allele homozygote and heterozygote (p-value 0.138). Scores of body weight and appetite were significantly higher in group with C allele homozygotes. Conclusion: These results suggest that RORA gene polymorphism play a role in seasonal variations in appetite and body weight and is associated with susceptibility to seasonal affective disorder in some degree in the population studied.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.53-78
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• 2008

Foreign investors who invest in the Korean stock markets are exposed to two kinds of foreign exchange rate risk, the economic exposure and the translation exposure. The former is the foreign exchange rate exposure in return generating process of the assets invested and the latter is the foreign exchange rate exposure in the translation of domestic return into foreign investors' currency. Domestic investors, however, are exposed only to foreign exchange rate exposure in the asset invested. This different situation on foreign exchange rate exposure between foreign investors and domestic investors can induce different response to exchange rate change by investor groups. Previous studies on foreign exchange rate exposure of Korean firms reported that quite a few Korean firms are exposed to foreign exchange risks and suggested to manage the foreign exchange risks. Also, many studies on the market segmentation showed that a market can be practically segmented according to the characteristics of investor groups. These studies support the hypothesis that the Korean stock market can be practically segmented by the foreign investors' attitude to the foreign exchange rate exposure. This study examines the response of both foreign investors and domestic investors to the foreign exchange rate exposures in Korean stock markets. Test results show that foreign investors increase their sell transactions when the foreign exchange rate exposure of the previous day is negative. This result can be possible when foreign investors attempt to actively manage the decrease in value of their assets due to rising of exchange rate. Analysis on the sell order data is also supportive to this interpretation. Foreign investors also increase their buy transactions when the foreign exchange rate exposure of the previous day is negative. This result can be possible when foreign investors use actively the relation between the increase in asset value and the translation gain due to declining of exchange rate. Analyses on buy order data, however, do not show the same result as the analyses on transaction data. This difference may come from the difference of information contained in transaction data and order data. In summary, the result of the paper supports the hypothesis that foreign investors response differently to foreign exchange rate exposure compared with domestic, Korean investors. Two groups do not show different response when exchange rate exposure is positive, i.e., as foreign exchange rate is increase (decrease), the asset value is increase (decrease). However, foreign investors' response is different from that of domestic investors when exchange rate exposure is negative, i.e., as foreign exchange rate is increase (decrease), the asset value is decrease (increase). These results mean that foreign investors and domestic investors are placed in different situations related to foreign exchange rate exposure, and these differences are reflected in the Korean stock markets. And domestic investors need to consider foreign investors' different attitude to the foreign exchange rate exposure when they analysis foreign investors' trading behavior.

• The korean journal of orthodontics
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• v.36 no.6
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• pp.412-421
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• 2006

Objective: The result of finite element analysis depends on material properties, structural expression, density of element, and boundar or loading conditions. To represent proper elastic behavior, a finite element model was made using Hounsfield unit (HU) values in CT images. Methods: A 13 year 6 month old male was used as the subject. A 3 dimensional visualizing program, Mimics, was used to build a 3D object from the DICOM file which was acquired from the CT images. Model 1 was established by giving 24 material properties according to HU. Model 2 was constructed by the conventional method which provides 2 material properties. Protraction force of 500g was applied at a 45 degree downward angle from Frankfort horizontal (FH) plane. Results: Model 1 showed a more flexible response on the first premolar region which had more forward and downward movement of the maxillary anterior segment. Maxilla was bent on the sagittal plane and frontal plane. Model 2 revealed less movement in all directions. It moved downward on the anterior part and upward on the posterior part, which is clockwise rotation of the maxilla. Conclusion: These results signify that different outcomes of finite element analysis can occur according to the given material properties and it is recommended to use HU values for more accurate results.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of the Korean Magnetics Society
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• v.19 no.3
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• pp.89-93
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• 2009

Amorphous $Ge_{1-x}Mn_x$ semiconductor thin films grown by low temperature vapor deposition were annealed, and their electrical and magnetic properties have been studied. The amorphous thin films were $1,000{\sim}5,000\;{\AA}$ thick. Amorphous $Ge_{1-x}Mn_x$ thin films were annealed at $300^{\circ}C$, $400^{\circ}C$, $500^{\circ}C$, $600^{\circ}C$ and $700^{\circ}C$ for 3 minutes in high vacuum chamber. X-ray diffraction analysis reveals that as-grown $Ge_{1-x}Mn_x$ semiconductor thin films are amorphous and are crystallized by annealing. Crystallization temperature of amorphous $Ge_{1-x}Mn_x$ semiconductor thin films varies with Mn concentration. Amorphous $Ge_{1-x}Mn_x$ thin films have p-type carriers and the carrier type is not changed during annealing, but the electrical resistivity increases with annealing temperature. Magnetization characteristics show that the as-grown amorphous $Ge_{1-x}Mn_x$ thin films are ferromagnetic and the Curie temperatures are around 130 K. Curie temperature and saturation magnetization of annealed $Ge_{1-x}Mn_x$ thin films increase with annealing temperature. Magnetization behavior and X-ray analysis implies that formation of ferromagnetic $Ge_3Mn_5$ phase causes the change of magnetic and electrical properties of annealed $Ge_{1-x}Mn_x$ thin films.

• The Journal of Information Systems
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• v.25 no.1
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• pp.1-23
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• 2016

Purpose Self-congruity deals with the effect of symbolic value-expressive attributes on consumer decision and behavior, which is the theoretical foundation of the "non-utilitarian destination positioning". Functional congruity refers to utilitarian evaluation of a product or service by consumers. In addition, recent years, social network services, especially mobile social network services have created many opportunities for e-WOM communication that enables consumers to share personal consumption related information anywhere at any time. Moreover, self-construal is a hot and popular topic that has been discussed in the field of modem psychology as well as in marketing area. This study aims to examine the moderating effect of self-construal on the relationship between self-congruity, functional congruity and tourists' positive electronic word of mouth (e-WOM). Design/methodology/approach In order to verify the hypotheses, we developed a questionnaire with 32 survey items. We measured all the items on a five-point Likert-type scale. We used Sojump.com to collect questionnaire and gathered 218 responses from whom have visited Korea before. After a pilot test, we analyzed the main survey data by using SPSS 20.0 and AMOS 18.0, and employed structural equation modeling to test the hypotheses. We first estimated the measurement model for its overall fit, reliability and validity through a confirmatory factor analysis and used common method bias test to make sure that whether measures are affected by common-method variance. Then we tested the hypotheses through the structural model and used regression analysis to measure moderating effect of self-construal. Findings The results reveal that the effect of self-congruity on tourists' positive e-WOM is stronger for tourists with an independent self-construal compared with those with interdependent self-construal. Moreover, it shows that the effect of functional congruity on tourists' positive e-WOM becomes salient when tourists' self-construal is primed to be interdependent rather than independent. We expect that the results of this study can provide important implications for academic and practical perspective.