• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Korean Journal of Environment and Ecology
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• v.28 no.5
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• pp.542-549
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• 2014

This study was conducted to investigate the body size, sexual size dimorphism (SSD), and related environmental factors between Red-tongued viper snakes (Gloydius ussuriensis) inhabiting two different places, i.e., Jeju Island and its islet Gapado, and to provide data required to maintain species diversity from May, 2006 until June, 2009. The snout-vent length of the Red-tongued viper snake population inhabiting Jeju Island was found to be 242-532 mm ($422.0{\pm}46.7mm$, n = 100) in females and 296-580 mm ($434.5{\pm}51.7mm$, n = 63) in males. In contrast, the snout-vent length was observed to be 205-395 mm ($335{\pm}43.6mm$, n = 55) in female and 215-430 mm ($328{\pm}39.4mm$, n = 73) in male Red-tongued viper snakes inhabiting Gapado. These data demonstrated the snout-vent length of both female and male Red-tongued viper snakes on Jeju Island to be larger than those on Gapado (Female t = 17.343, df = 115, P<0.001; Male = 19.128, df = 101, P<0.001). SSD was measured to be -0.03 in the Red-tongued viper snake population on Jeju Island, with more or less larger sizes in the males, while it was 0.02 in the Red-tongued viper snake population in the Gapado, with a little larger sizes in the females. The reason for this difference in the snake populations between Jeju Island and Gapado may be due to adaption to the different ecological environments. In addition, as SSD, the snout-vent length of the Red-tongued viper snake populations and in young vipers was somewhat higher in the males than in the females on Jeju Island (t = -2.011, df = 117, P<0.05). However, no significant differences were observed in the snout-vent length of the young and the general Red-tongued viper snake populations on Gapa Island. For the population on Jeju island, the head length (F = 6.318, $df_{1,2}$=1,117, P<0.05), head width (F=8.090, $df_{1,2}$=1,117, P<0.01), inter eye length (F=15.898, $df_{1,2}$=1,117, P<0.001), and tail length (F=238.488, $df_{1,2}$=1,111, P<0.001) were all larger in the males, while females showed higher body mass (F=64.111, $df_{1,2}$=1,114, P<0.001). In the case of the Gapa Island population, no significant differences in the head length, head width, and inter eye length between females and males were observed, while the males had a longer tail length (F=168.555, $df_{1,2}$=1,74, P<0.001) and the females were heavier (F=17.812, $df_{1,2}$=1,76, P<0.001). Though no significant differences were found in the head length, head width, and inter eye length, the tail length (F=67.793, $df_{1,2}$=1,72, P<0.001) and body mass (F=4.558, $df_{1,2}$=1,72, P<0.05) were higher in the young male Red-tongued viper snakes than in the females. The snout-vent length, head length, head width, and inter eye length, which did not display SSD in the young Red-tongued viper snake populations, were higher in the male Red-tongued viper snake populations than in the female population from Jeju Island, implying that SSD in the Red-tongued viper snake population on Jeju Island is expressed due to environmental effects during their growth.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.1
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• pp.57-65
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• 2015

Objectives:Within the normal reproductive cycles of women, dramatic fluctuations of sexual hormones occur in the premenstrual and menopausal periods. In both periods, women are vulnerable to mood disturbances and show several somatic complaints. Based on these common clinical profiles and physiological changes, a relationship between vasomotor symptoms and the premenstrual syndrome has been suggested. However, attempts to establish such a link have yielded inconclusive results. The purpose of this study was to investigate the association between histories of premenstrual syndrome and menopausal vasomotor symptoms within different menopausal stages. Methods:This cross-sectional study recruited Korean women aged 45-64 years who were perimenopausal and postmenopausal from 16 branch offices of the Korean Association of Health Promotion. All subjects completed self-report questionnaires that asked about a history of premenstrual syndromes, vasomotor symptoms, and several other variables. Results:A total of 1054 participants(361 perimenopausal women and 693 postmenopausal women) completed the study. Severity of premenstrual symptoms significantly correlated with postmenopausal vasomotor symptoms, only in late perimenopausal(r=0.213, p=0.010) and early postmenopausal women(r=0.246, p<0.001). After adjusting for several factors related to vasomotor symptoms, a history of premenstrual syndrome was a significant predictor of moderate to very severe vasomotor symptoms in late perimenopausal(OR=5.197, p=0.005) and early postmenopausal women(OR=3.017, p=0.010). Conclusions:This study suggests that a history of premenstrual syndrome/premenstrual dysphoric disorder is differentially associated with vasomotor symptoms in the menopausal stage. Prospective studies with larger population are needed to confirm these findings

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.630-642
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• 1997

The purpose of this study was to examine the mortality risk associated with cognitive impairment among the rural elderly. The subjective of study was 558 of 'A Study on the Depression and Cognitive Impairment in the Rural Elderly' of Jung Ae Rhee and Hyang Gyun Jung's study(1993). Cognitive impairment and other social and health factors were assessed in 558 elderly rural community residents. For this study, a Korean version of the Mini-Mental State Examination(MMSEK) was used as a global indicator of cognitive functioning. And mortality risk factors for each cognitive impairment subgroup were identified by univariate and multivariate Cox regression analysis. At baseline 22.6% of the sample were mildly impaired and 14.2% were severely impaired. As the age increased, the cognitive function was more impaired. Sexual difference was existed in the cognitive function level. Also the variables such as smoking habits, physical disorders had the significant relationship with cognitive function impairment. Across a 3-year observation period the mortality rate was 8.5% for the cognitively unimpaired, 11.1% for the mildly impaired, and 16.5% for the severly impaired respendents. And the survival probability was .92 for the cognitively unimpaired, .90 for the mildly impaired, and .86 for the severly impaired respondents. Compared to survival curve for the cognitively unimpaired group, each survival curve for the mildly and the severely impaired group was not significantly different. When adjustments models were not made for the effects of other health and social covariates, each hazard ratio of death of mildly and severely impaired persons was not significantly different as compared with the cognitively unimpaired. But, as MMSEK score increased, significantly hazard ratio of death decreased. Employing Cox univariate proportional hazards model, statistically other significant variables were age, monthly income, smoking habits, physical disorders. Also when adjustments were made for the effects of other health and social covariates, there was no difference in hazard ratio of death between those with severe or mild impairment and unimpaired persons. And as MMSEK score increased, significantly hazard ratio of death did not decrease. Employing Cox multivariate proportional hazards model, statistically other significant variables were age, monthly income, physical disorders. Employing Cox multivariate proportional hazards model by sex, at men and women statistically significant variable was only age. For both men and women, also cognitive impairment was not a significant risk factor. Other investigators have found that cognitive impairment is a significant predictor of mortality. But we didn't find that it is a significant predictor of mortality. Even though the conclusions of our study were not related to cognitive impairment and mortality, early detection of impaired cognition and attention to associated health problems could improve the quality of life of these older adults and perhaps extend their survival.