• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.14-20
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• 2014

Objectives: Several studies suggest that nocturia may be related to obstructive sleep apnea syndrome (OSAS). The mechanism by which OSAS develops nocturia has not been determined. The present study aimed to determine the prevalence of nocturia among adults with OSAS and to identify factors that may be predictive in this regard. Methods: Retrospective review of clinical and polysomnographic data obtained from patients evaluated at the sleep clinics of the St. Paul's Hospital between 2009 and 2012. The urinary symptoms were assessed on the basis of the International Prostate Symptom Score (IPSS). Pathologic nocturia was defined as two or more urination events per night. OSAS was defined as apnea-hypopnea index (AHI) ${\geq}5$. A multivariate analysis using logistic regression was performed to examine the relationship between polysomnographic variables and the presence of pathologic nocturia, while controlling for confounding factor. Results: A total of 161 men >18 years of age (mean age $46.7{\pm}14.1$), who had been referred to a sleep laboratory, were included in the present study. Among these, 27 patients with primary snoring and 134 patients with obstructive sleep apnea were confirmed by polysomnography. Nocturia was found in 53 patients with OSAS (39.6%) and 8 patients with primary snoring (29.6%). The AHI was higher in patients with nocturia than in those without nocturia (p=0.001). OSAS patients with nocturia had higher arousal index (p=0.044), and lower nadir oxyhemoglobin saturation (p=0.001). Multiple regression analysis showed that age (${\beta}$=0.227, p=0.003), and AHI (${\beta}$=0.258, p=0.001) were associated with nocturia, and that the presence of pathologic nocturia was predicted by age (OR 1.04 ; p=0.004) and AHI (OR 1.02 ; p=0.001). Conclusion: Nocturia is common among patients with OSAS. The strongest predictors of nocturia are age and AHI in patients with OSAS.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.5-13
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• 2014

Objectives: Depression, sleep complaints and cognitive impairments are commonly observed in the elderly. Elderly subjects with depressive symptoms have been found to show both poor cognitive performances and sleep disturbances. However, the relationship between sleep complaints and cognitive dysfunction in elderly depression is not clear. The aim of this study is to identify the association between sleep disturbances and cognitive decline in late-life depression. Methods: A total of 282 elderly people who underwent nocturnal polysomnography in a sleep laboratory were enrolled in the study. The Korean version of the Neuropsychological Assessment Battery developed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-K) was applied to evaluate cognitive function. Depressive symptoms were assessed with the geriatric depression scale (GDS) and subjective sleep quality was measured using the Pittsburg sleep quality index (PSQI). Results: The control group ($GDS{\leq}9$) when compared with mild ($10{\leq}GDS{\leq}16$) and severe ($17{\leq}GDS$) depression groups, had significantly different scores in the Trail making test part B (TMT-B), Benton visual retention test part A (BVRT-A), and Stroop color and word test (SCWT)(all tests p<0.05). The PSQI score, REM sleep duration, apnea-hypopnea index and oxygen desaturation index were significantly different across the three groups (all indices, p<0.05). A stepwise multiple regression model showed that educational level, age and GDS score were predictive for both TMT-B time (adjusted $R^2$=35.6%, p<0.001) and BVRT-A score (adjusted $R^2$=28.3%, p<0.001). SCWT score was predicted by educational level, age, apnea-hypopnea index (AHI) and GDS score (adjusted $R^2$=20.6%, p<0.001). Poor sleep quality and sleep structure alterations observed in depression did not have any significant effects on cognitive deterioration. Conclusion: Older adults with depressive symptoms showed mild sleep alterations and poor cognitive performances. However, we found no association between sleep disturbances (except sleep apnea) and cognitive difficulties in elderly subjects with depressive symptoms. It is possible that the impact of sleep disruptions on cognitive abilities was hindered by the confounding effect of age, education and depressive symptoms.

• 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.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.129-136
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• 2010

This study was initiated to investigate thatch accumulation in several turfgrasses grown under two soil systems. The 45 centimeter deep USGA system was constructed with rootzone, intermediate and drainage layers. The mono-layer system, however, was made with only a 30cm rootzone layer. Turfgrasses used in the study were comprised of 3 varieties from Korean lawngrass of Warm-Season Grass(WSG) and 3 blends and 3 mixtures from Cool-Season Grass(CSG). A total of 9 turfgrass treatments were replicated three times in RCBD in both systems. Cultural practices for the research plot followed a typical maintenance program for highly managed turf. Treatment differences for thatch accumulation were observed among the turfgrasses in both soil systems. Thatch under the USGA system was 9% greater than under the mono-layer system due to its more favorable conditions for turf growth. Higher thatch depth was found with Korean lawngrass, 34~87% in the USGA system and 16~75% in the mono-layer system when compared with CSG. Among WSG, the Joongji variety was the highest in thatch layer under both the USGA and mono-layer systems. Kentucky bluegrass(KB) was the greatest among CSG, since it is a rhizomatous-type in growth habit, resulting in faster production of organic matter over bunch-type of tall fescue and perennial ryegrass. Proper depth in the thatch layer was known to be beneficial by enhancing the resiliency and wear tolerance of the turf in athletic fields. Thus, KB was considered to be a very excellent turfgrass in terms of turf quality, environmental performance, physical properties and soccer player safety. However, disadvantages such as poor water-holding properties, more inclined to injury from environmental stresses and severe diseases and insect injury were also expected where thatch was excessively accumulated. Therefore, these results demonstrate that more frequent measures for controlling thatch such as vertical mowing, topdressing or coring should be employed for soccer fields with Korean lawngrass and KB over other turfgrasses.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.2
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• pp.223-229
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• 2005

The chemical components of barley (Jinmichapssal, Seodunchal, and Dusan No.8) and wheat (Alchanmil, Tapdongmil, and Olgeurumil) varieties were determined in terms of proximate compositions, minerals, fatty acids, amino acids and vitamin. There are significant differences in protein and lipid (p<0.00l, respectively), fiber (p<0.05) of barleys. There are significant differences in lipid contents (p<0.00l) of wheats. The major minerals of barley were Ca 24∼31 mg%, P 117∼129 mg%, Fe 1.7∼2.9 mg%, Na 13∼18 mg%, K 227∼73 mg%, Zn 1.1∼1.2 mg%, and Mg 38∼45 mg%. The content of Ca in Jinmichapssal was significantly higher than those in the other varieties (p<0.00l). The mineral contents of wheat were Ca 39∼67 mg%, P 172∼270 mg%, Fe 3.7∼5.6 mg%, Na 15∼17 mg%, K 537∼558 mg%, Zn 2.1∼2.3 mg% and Mg 106∼127 mg%. There are significant differences in Ca, P, Fe and Mg of 3 kinds of wheat. The barleys contain vitamin B$_1$ 0.27∼0.36 mg%, vitamin B$_2$ 0.07∼0.11 mg% and niacin 1.21∼1.44 mg%. The content of vitamin B$_1$ in Jinmichapssal and Seodunchal was significantly higher than that in Dusan No.8 (p<0.0l). The content of vitamin B$_2$ in Seodunchal (0.11 mg%) was significantly higher than those in the other varieties (p<0.0l). The content of niacin in barleys was no significant differences. The wheats contain vitamin B$_1$ 0.41∼0.52 mg%, vitamin B$_2$ 0.29∼0.39 mg% and niacin 1.86∼2.81 mg%. The contents of vitamin B$_2$ in Olgeurumil (0.39 mg%) and niacin in Tapdongmil (2.81 mg%) were considerably higher than those in the other varieties. The contents of vitamin B$_1$, B$_2$, niacin in wheats were higher than those of barleys. Major fatty acids in barley and wheat varieties were linoleic acid, palmitic acid and oleic acid, which comprised of about 90%∼92% of total fatty acid. The contents of lysine, valine, and tryptophan in Dusan No.8 were significantly higher than those in the other varieties. The contents of lysine, isoleucine in Tapdongmil were significantly lower than those in the other varieties. The content of amino acid in wheat was higher than those of barleys.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.3
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• pp.379-389
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• 2008

This study was conducted to assess the microbiological quality of raw and cooked foods served in the elementary school food service. Raw and cooked food samples were collected from 11 selected elementary schools in both June to July and September to October of 2005. Petrifilm plates were used to determine (in duplicate) total aerobic colony counts (PAC), Enterobacteriaceae (PE), coliform counts (PCC), and E. coli counts (PEC). Heavy contamination of Enterobacteriaceae (from 0.08 to 7.40 log CFU/g) and total coliform (0.50 to 6.52 log CFU/g) were observed in raw materials and cooked foods. Escherichia coli (E. coli) were detected in the sample of currant tomato (3.70 log CFU/g), sesame leaf (3.59 log CFU/g), dropwort (0.20 log CFU/g), crown daisy (3.15 log CFU/g), parsley (3.00 log CFU/g), peeled green onion (1.74 log CFU/g), frozen pork (0.65 log CFU/g), frozen beef (0.20 or 1.50 log CFU/g), chicken (1.78 log CFU/g), and young radish leaf seasoned with soybean paste (1.24 log CFU/g). Multiplex PCR system was used to determine the food-borne pathogens: Salmonella spp., Bacillus cereus (B. cereus), E. coli O157:H7, Staphylococcus aureus, Listeria monocytogenes (L. monocytogenes), Vibrio parahaemolyticus, Campylobacter jejuni (C. jejuni), Shigella spp., B. cereus was detected in 19 samples of raw materials and 8 samples of cooked foods. With regard to quantitative analysis, B. cereus counts exceeded 5.46, 3.48 and 1.79 log CFU/g in sesame leaf, peeled green onion and seasoned mungbean jelly, respectively. E. coli O157:H7 was detected on 2 samples of frozen beefs, and its biochemical characteristics of one beef sample was confirmed with API 20E kit (93.7%). L. monocytogenes was detected in fried rice paper dumpling, but the presumptive colonies were not detected onto the conventional plate. C. jejuni was detected in peeled & washed onion.

• Management & Information Systems Review
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• v.36 no.3
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• pp.37-49
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• 2017

This study investigates the dynamic relationship between KOSPI200 stock index and stock index futures and stock index option markets which is its derived from KOSPI200 stock index. We use 5-minutes rate of return data from 2012. 06 to 2014. 12. To empirical analysis, this study use autocorrelation and cross-correlation analysis as a preliminary analysis and then following Stoll and Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the stock index and stock index futures and option markets by Newey and West's(1987) Empirical results of our study shows as follows. First, there exist a strong autocorrelation in the KOSPI200 stock index before 10minutes but a very weak autocorrelation in the stock index futures and option markets. Second, there is a strong evidence that stock index future and option markets lead KOSPI200 stock index in the cross-correlation analysis. Third, based on the multiple regression, the stock index futures and option markets lead the stock index prior to 10-15 minutes and weak evidence that the stock index leads the future and option markets. This results show that the market efficient of KOSPI200 stock index market is improved as compared to the early stage of stock index future and option market.

• Journal of dental hygiene science
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• v.11 no.6
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• pp.543-551
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• 2011

Critical thinking is recognized as core competency for dental hygiene practice. The purpose of this study was to investigate relationship between critical thinking disposition and grade, types of educational programs and satisfaction with interpersonal relationship, major, clinical practice. Total 909 students in associate and baccalaureate dental hygiene educational program completed self-reported questionnaire on critical thinking disposition inventory developed by Yoon(2004). The mean score for critical thinking disposition was 3.38~3.39 on a 5 point scale. There was no difference in critical thinking disposition scores between students of associate and baccalaureate programs. There was no difference in critical thinking disposition scores between grade of students. The results showed a statistically significant relationship between critical thinking disposition and satisfaction with interpersonal relationship and major. Multivariate analysis of variance(MANOVA) revealed that all subscales for three groups according to satisfaction with interpersonal relationship were significantly different(Pillai's trace=0.075, F(14,1782)=4.979, p<0.001) and all subscales for three groups according to satisfaction with major were significantly different(Pillai's trace=0.035, F(14,1728)=2.257, p=0.005).