• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.147-165
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• 1992

This paper analyzes the macroeconomic effects of elections on the Korean economy and their future ramifications. It measures the shocks to the Korean economy caused by elections by taking the average of sample forecast errors from four major elections held in the 1980s. The seven variables' Bayesian Vector Autoregression Model which includes the Monetary Base, Industrial Production, Consumption, Consumer Price, Exports, and Investment is based on the quarterly time series data starting from 1970 and is updated every quarter before forecasts are made for the next quarter. Because of this updating of coefficients, which reflects in part the rapid structural changes of the Korean economy, this study can capture the shock effect of elections, which is not possible when using election dummies with a fixed coefficient model. In past elections, especially the elections held in the 1980s, $M_2$ did not show any particular movement, but the currency and base money increased during the quarter of the election was held and the increment was partly recalled in the next quarter. The liquidity of interest rates as measured by corporate bond yields fell during the quarter the election and then rose in the following quarter, which is somewhat contrary to the general concern that interest rates will increase during election periods. Manufacturing employment fell in the quarter of the election because workers turned into campaigners. This decline in employment combined with voting holiday produce a sizeable decline in industrial production during the quarter in which elections are held, but production catches up in the next quarter and sometimes more than offsets the disruption caused during the election quarter. The major shocks to price occur in the previous quarter, reflecting the expectational effect and the relaxation of government price control before the election when we simulate the impulse responses of the VAR model, imposing the same shocks that was measured in the past elections for each election to be held in 1992 and assuming that the elections in 1992 will affect the economy in the same manner as in the 1980s elections, 1992 is expected to see a sizeable increase in monetary base due to election and prices increase pressure will be amplified substantially. On the other hand, the consumption increase due to election is expected to be relatively small and the production will not decrease. Despite increased liquidity, a large portion of liquidity in circulation being used as election funds will distort the flow of funds and aggravate the fund shortage causing investments in plant and equipment and construction activities to stagnate. These effects will be greatly amplified if elections for the head of local government are going to be held this year. If mayoral and gubernatorial elections are held after National Assembly elections, their effect on prices and investment will be approximately double what they normally will have been have only congressional and presidential elections been held. Even when mayoral and gubernatorial elections are held at the same time as congressional elections, the elections of local government heads are shown to add substantial effects to the economy for the year. The above results are based on the assumption that this year's elections will shock the economy in the same manner as in past elections. However, elections in consecutive quarters do not give the economy a chance to pause and recuperate from past elections. This year's elections may have greater effects on prices and production than shown in the model's simulations because campaigners' return to industry may be delayed. Therefore, we may not see a rapid recall of money after elections. In view of the surge in the monetary base and price escalation in the periods before and after elections, economic management in 1992 should place its first priority on controlling the monetary aggregate, in particular, stabilizing the growth of the monetary base.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.387-398
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• 1996

The objective of this study was to clarify whether there are any differences between normal and over-weight middle-aged(40∼59yrs)women in their perceived weight, health status, health conception and health behavior choices. The sample consisted of 39 normal weight and 55 over-weight (11％ above on the Body Index Scale) women who live in Juan, Inchon. The Participants were randomly selected in each weight group considering socio-demographic factors. The findings from this study are summarized below. 1) Among the 55 overweight middle-aged women, 16 were above 20％ on the Body Index Scale and 14 were above 30％. Twenty-five(45.5％) of the overweight group and 12(30.8％) of the normal weight group had one disease, and there were 12(21.8％) in the overweight group and 8(20.5％) in the normal weight group where one of the family members had a disease, but these differences were not statistically significant. The average monthly family income for the overweight group was ￦l,880,000 compared to ￦2,140, 000 for the normal weight group, but this difference was also not significant. The age range for the whole group was between 40 and 59(mean＝46.8 for total, 48.6 for overweight and 45.7 for normal weight group). Again no significant difference found. Occupations were housemaker 53(56.4％), private business(13.8％), salarywoman(9.6％), and teacher (2.1％). Thirty housemaker(54.5％) from the overweight group and 23(59％) from the normal group did not constitute a statistically significant different. For the educational status, 34(61.8％) of the overweight women and 33(84.6％)of the normal weight group finished high school or more educational courses, but there was no significant statistical difference. Eleven(20.0％) of the overweight women and 5(12. 8％) of the normal weight group were single, but again no significant statistical difference was found. 2) A test for difference in health characteristics between two weight groups indicated that two groups do not show statistical differences in their perceived health status, health conception or health behavior choice. That is, the overweight group, also perceive their health status as good as the normal group, and regard ‘Health’ as a state that enables them to carry out social roles and functions rather than as the traditional concept of health as no disease or no symptoms. Moreover. the overweight group selected their health behaviors not for the prevention of diseases or maintenance of health but for promotion of health. To determine if no statistical difference might be related to the overweight group's failure of perceive themselves as overweight, the perceived and objective overweight status were compared by the chi-square analysis, and no difference was found（X/sup²＝49.37, df＝1, p＝.000）. However, 7(17.9％) of the normal group perceived themselves as being overweighted and 7(12.7％) of the overweight group thought they were of normal weight. Even though the overweight group employed in this study perceived themselves as being overweight, they regarded themselves as healthy as those in the normal weight group. It was shown that there was no statistical difference between two groups in health conception, and that they chose health behaviors to promote health status. 3) Perceived health conception was shown to be significantly related to health behavior choice （r＝ .28, p＝.006 for whole group : r＝.33, p＝.014 for overweight group : and r＝.12. p＝.463 for normal group） .There was an indication that the more complicated the perceived health conception was, the more the trend of health behavior choice to promote health. This was especially true for the overweight group. But, the perceived health status did not related to health behavior choice statistically（r＝.13, p＝.202）, and it was thought that reasons for selecting health behaviors were not related to their health status. That is, the overweight group perceive themselves as healthy as the normal weight group or thought that overweight itself does not incur any risk on their health. Data from two groups were combined and analyzed with multiple regression methodology, because the relationship pattern of the two groups was similar. The analysis showed that health behavior has a significant relationship with age and the perceived health conception（r/sup²＝.1517, p=.05, F＝8.133）. It means they come to health behavior along with their health conception and their age rather than their weights, perceived weight, health status or other social characteristics. This study was intended to understand how overweight middle-aged women perceive ‘weight’ and ‘health’, and how they meet their health related needs in comparison with normal weight middle-aged women. Other factors related to the health behavior in overweight middle-aged woman need to be determined through further descriptive studies outlined in the following recommendations. a) Reseach with the study area expanded. b) Reseach with grouping more detailed : much more overweight and underweight group c) Reseach on restricted relationship between overweight and age or profession. d) Reseach on what overweight middle-aged women do to reduce their weight and what factors motivate them to do it

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7509-7515
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• 2013

To assess the risk of cancers associated with sleep duration using meta-analysis of published cohort studies, we performed a comprehensive search using PubMed, Embase and Web of Science through October 2013. We combined hazard ratios (HRs) from individual studies using meta-analysis approaches. A random effect dose-response analysis was used to evaluate the relationship between sleep duration and cancer risk. Subgroup analyses and sensitivity analyses were also performed. Publication bias was evaluated using Funnel plots and Begg's test. A total of 13 cohorts from 12 studies were included in this meta-analysis, which included 723, 337 participants with 15, 156 reported cancer outcomes during a follow-up period ranging from 7.5 to 22 years. The pooled adjusted HRs were 1.06 (95% CI: 0.92, 1.23; P for heterogeneity =0.003) for short sleep duration, 0.91 (95% CI: 0.78, 1.07; P for heterogeneity <0.0001) for long sleep duration. In subgroup analyses stratified by cancer type, long duration of sleep showed an inverse relation with hormone-related cancer (HR=0.79; 95% CI: 0.65, 0.97; P for heterogeneity =0.009) and a greater risk of colorectal cancer (HR=1.29; 95% CI: 1.09, 1.52; P for heterogeneity =0.346). Further meta-analysis on dose-response relationships showed that the relative risks of cancer were 1.00 (95% CI: 0.99, 1.01; P for linear trend=0.9151) for one hour of sleep increment per day, and 1.00 (95% CI: 0.98, 1.01; P for linear trend=0.7749) for one hour of sleep increment per night. No significant dose-response relationship between sleep duration and cancer was found on non-linearity testing (P=0.5053). Our meta-analysis suggests a positive association between long sleep duration and colorectal cancer, and an inverse association with incidence of hormone related cancers like those in the breast. Studies with larger sample size, longer follow-up times, more cancer types and detailed measure of sleep duration are warranted to confirm these results.

• Journal of Oral Medicine and Pain
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• v.33 no.3
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• pp.257-267
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• 2008

The mentophysical disease causes diseases in digestive, respiratory, circulating systems, including chronic pain, through combined reactions from different individual characteristics, mental stress and temperamental factors. The most common symptom related to orofacial area is pain and the contributive factors include biological, behavioral, environmental, social, emotional, recognitive factors. These factors affect the course of the symptom according to individual's character and human nature. In pain, sleep acts as a contributive factor, and pain could bring about sleep disturbance and vice versa. Deterioration of sleep quality would act as a factor that aggravates mental stress. Therefore, relatively accurate and simple mental examinations and sleep quality test should be carried out for the patients with symptoms related to orofacial area. This study evaluated the mental state in relation to the sleep quality which could affect orofacial pain. The number of poor sleeper was 18 in male subjects, and 1 in female subjects and PSQI global index was higher in male($6.11{\pm}2.38$) than female($4.67{\pm}2.18$). SCL-90-R index showed no sex difference. Poor sleeper showed significantly high value in SOM, O-C, I-S, ANX, PHOB, PSY, GSI, PST. When SCL-90-R T scores were compared according to sleep quality, higher the subjective sleep quality score, O-C and I-S showed significant increase. As sleep disturbances score increased, PAR, PSY, PST showed statistically significant increase. In comparison of SCL-90-R T score according to daytime dysfunction, statistically significant increase in DEP, ANX, HOS, PHOB, PAR, GSI was observed. Therefore, the quality of sleep and psychological status have a high correlation. This is likely to influence chronic pain in the orofacial field. As a result, clinicians treating orofacial pain should evaluate the sleep quality and psychological status of the patient. Further studies of larger sample sizes including various age, occupation, and pain groups are necessary in order to apply the results to clinical practice.

• Research in Plant Disease
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• v.17 no.2
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• pp.191-195
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• 2011

This experiment was attempted to investigate a cause of the scion death in green pepper grafting system. A tobamovirus particle examined in the rootstock of the sample but not in the scion showing necrosis. The virus isolated from the rootstock was identified as Pepper mild mottle virus (PMMoV), pepper tobamovirus pathotype P1.2. (PMMoV-2), by nucleotide sequence analysis and host plant reaction. The virus isolate infected systematically in 6 commercial rootstock varieties using for green pepper grafting seedling production. Green pepper varieties 'Long green mart' and 'Daechan' represented resistance to the virus showing local lesions only on the inoculated leaves and 'Manitda' was systematically infected. In the experiment with grafting 'Long green mart' or 'Daechan' onto the those rootstocks, the upper leaves of the scions first showed vein necrosis and wilt symptoms 7 days after inoculation with PMMoV-2 on the cotyledon of the rootstock, following to the scion stem necrosis and then only the scion death. The virus was detected in the rootstock but not in the scion. However, 'Manitda' of susceptible variety in the grafting system showed mottle symptom on the leaves of the scion but not necrosis on the plant. PMMoV-3 isolate, pepper tobamovirus pathotype P1.2.3, did not cause the scion death in the grafting system. All of the varieties were susceptible to PMMoV-3. These results suggest that the scion death is caused by infecting with pepper tobamovirus pathotype P1.2. in the green pepper grafting system combined with the susceptible rootstock and the resistance scion to the virus pathotype.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.183-196
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• 2017

Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

• Korean Journal of Soil Science and Fertilizer
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• v.12 no.1
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• pp.1-14
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• 1979

The fertility which is the combined factor is one of the important capability determiants of paddy soils. In this study, we aimed at attaining a quantitative evaluation of soil fertility and further establishing an objective fertility classification on the basis of the fertility evaluation. The samples used in this series studies were collected from Korean paddy field. They include deltas, flood plains, coastal plains, valley plains, fans and low terraces. On the basis of correlation analysis, factor analysis was applied to a set of 15 variables. As a result of factor analysis, five mutually independent and clearly definable fertility component factors were extracted from the 15 variables for the whole 90 surface soil samples. The fertility status of each sample soil could be objectively designated by the score of the five factors. As a means of summarizing the information obtained, taxonomic distances between all pairs of the samples were computed from these five factor scores further to be subjected to numerical taxonomy. Seven fertility groups were formulated, each of which was characterized by one or more of the fertility components. As this fertility classification was based on the present state of soil properties, it would be useful in pointing to the proper direction of further fertility amelioration and improvement for each group to enhance potential productivity of Korean paddy fields.

• Journal of Korean Society of Forest Science
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• v.58 no.1
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• pp.8-16
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• 1982

To study the comparison of aboveground biomass of paulownia coreana Uyeki of 6-year-old, located in Seongju of non-attacked forest and Ulsan of damaged forest by the air pollution were selected. Ten sample trees in Seongju district and seven trees in Ulsan selected taking account of DBH were measured for 16 trees in total within a $10{\times}10m$ experimental plot. The diagram of oven-dry weight distribution of stem, branch and needle for each 1m segment was constructed. The logarithmic regression equations between dry weight of each component and the two-variables, DBH and tree height, combined term were presented. IF the estimations are extended to a hectare area stand, it contains 47.49 tons of aboveground biomass in Seongju district and 19.05 tons of it in Ulsan. The annual net productions were 11.64 tons of above 2.29 kg/kg/yr in Ulsan and the efficiency of leaf to produce stem was 2.99kg/kg/yr in Seongju and 0.83kg/kg/yr in Ulsan.