• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.562-574
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• 2012

Simulation validation techniques which have been employed in most studies are statistical analysis, which validate a model with mean or variance of throughput and resource utilization as an evaluation object. However, these methods have not been able to ensure the reliability of individual elements of the model well. To overcome the problem, the weighted F-measure method was proposed, but this technique also had some limitations. First, it is difficult to apply the technique to complex system environment with numerous values of interarrival time because it assigns a class to an individual value of interarrival time. In addition, due to unbounded weights, the value of weighted F-measure has no lower bound, so it is difficult to determine its threshold. Therefore, this paper propose weighted F-measure technique with cluster analysis to solve these problems. The classes for the technique are defined by each cluster, which reduces considerable number of classes and enables to apply the technique to various systems. Moreover, we improved the validation technique in the way of assigning minimum bounded weights without any lack of objectivity.

• Journal of muscle and joint health
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• v.8 no.1
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• pp.27-50
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• 2001

Rheumatoid arthritis is a chronic systemic autoimmune disease. Although the joints are the major loci of the disease activity, fatigue is a common extraarticular symptom that exists in all gradations of rheumatoid arthritis. Fatigue is defined as a subjective sense of generalized tiredness or exhaustion and has multiple dimensions. Therefore fatigue is a common and frequent problem for those with rheumatoid arthritis. In fact, 88-100% of individuals with rheumatoid arthritis experience fatigue. Especially the degree of fatigue is higher in women than men with rheumatoid arthritis. Despite the importance of fatigue among the patients with rheumatoid arthritis, the mechanism that leads to fatigue in rheumatoid arthritis is not completely understood. This study was intended to test and validate a model to predict fatigue in women with rheumatoid arthritis. Especially it was intended to identify the direct and indirect effects of the variables of pain, disability, depression, sleep disturbance, morning stiffness, and symptom duration to fatigue. Data were collected by questionnaires including Multidimensional Assesment of Fatigue(Tack, 1991), numeric scale of pain, graphic scale of joints, Ritchie Articular Index, Korean Health Assessment Questionnaire(Bae, et al., 1998), Inventory of Function Status(Tulman, et al., 1991), Center for Epidemiologic Studies-Depression, and Korean Sleep Scale(Oh, et al 1998). The sample consisted of 345 women with a mean duration of rheumatoid arthritis for 10.06 years and a mean age of 49.64 years. SPSS win and Win LISREL were used for the data analysis. Structural equation modeling revealed the overall fit of the model. Pain predicted fatigue directly and indirectly through disability, depression, and sleep disturbance. Disability, sleep disturbance predicted fatigue only directly, while depression only indirectly through disability and sleep disturbance. Also morning stiffness and symptom duration predicted fatigue through disability and depression. All predictors accounted for 65% of the variance of fatigue. Depression, pain, and disability predicted sleep disturbance. Depression had reciprocal relationship with disability and they both were predicted by pain directly and indirectly. In summary, pain, depression, disability, sleep disturbance, morning stiffness, and symptom duration contributed to the fatigue of patients with rheumatoid arthritis. The best predictor of fatigue was pain. This finding indicates that the modification of pain, depression, disability, sleep disturbance, morning stiffness could be nursing intervention for relief or prevention of fatigue.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.269-281
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• 2022

The prediction of changes regarding the distribution of vegetation and plant species according to climate changes is important for ecosystem management. In this study, we attempted to develop an assessment method to evaluate the possibility of the potential distribution of warm-temperate woody plant species of East Asia in Korea. To begin with, a list of warm-temperate woody plants distributed in China and Japan, but not in Korea, was prepared, and a database consisting their global distribution and bioclimatic variables was constructed. In addition, the warm-temperate vegetation zone in Korea was delineated using the coldness index and relevant bioclimatic data were collected. After the exclusion of multicollinearity among bioclimatic variables using correlation analysis, mean temperature of the coldest quarter, mean temperature diurnal range, and annual precipitation were selected as the major variables that influence the distribution of warm-temperate plants. A multivariate environment similarity surfaces (MESS) analysis was conducted to calculate the similarity scores between the distribution of these three bioclimatic variables in the global distribution sites of the East Asian warm-temperate woody plants and the Korean warm-temperate vegetation zone. Finally, using stepwise variable-selection regression, the mean temperature of the coldest quarter and annual precipitation were selected as the main bioclimatic variables that affect the MESS similarity index. The mean temperature of the coldest quarter accounted for 88% of the total variance. For a total of 319 East Asian warm-temperate woody plant species, the possibility of their potential distribution in Korea was evaluated by applying the constructed multivariate regression model that calculates the MESS similarity index.

• Journal of Korean Academy of Nursing
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• v.39 no.5
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• pp.700-708
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• 2009

Purpose: This study was done to test the validity and reliability of the Adolescent Mental Problem Questionnaire (AMPQ) for Korean high school students. Methods: The AMPQ was designed to assess adolescents', mental health status and problem behavior (Ahn, 2006). A methodological study design was used with exploratory factor analysis, Pearson's correlation coefficients, and a fitness of the modified model for validity. Also, Cronbach's alpha coefficients and alternative-form method for reliability were used. AMPQ was tested with a sample of 36,313 high school students. The participants consisted of 18,701 males and 17,612 females. Results: Seven factors were extracted through factor analysis: 'Psychiatric problems', 'Delinquency', 'Academic troubles', 'Family problems', 'Hazardous behavior', 'Harmful circumstance', 'Eating problems'. These factors explained 51.1% of the total variance. The fitness of the modified model was good ($X^2$=38,413.76, Goodness of Fit Index [GFI]=.94, Adjusted Goodness of Fit Index [AGFI]=.93, Comparative Fit Index [CFI]=.95, Root Mean Square Error of Approximation [RMSEA]=.05), and concurrent validity with Korea-Youth Self-Report [K-YSR] was .63. Cronbach's alpha coefficient of the 31 items was .85. Conclusion: The results of present study suggest that the modified AMPQ instrument may be useful for efficiently assessing mental health status and problem behavior in late adolescent, high school students.

• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.83-90
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• 2008

Two hundred and sixty Korean soybean landrace accessions were analyzed for polymorphism at 92 simple sequence repeat(SSR) loci. The 995 identified alleles served as raw data for estimating genetic diversity and population structure. The number of alleles at a locus ranged from three to 27 with a mean of 10.4 alleles per locus. $F_{ST}$ values estimated by analysis of molecular variance(AMOVA) using SSR data set were 0.018, 0.027, and 0.016 for usage, collection site and maturity groups, respectively, indicating little genetic differentiation. The model-based clustering analysis placed the accessions into three clusters(K=3) with 0.0503 of $F_{ST}$, indicating moderate genetic differentiation. Duncan's Multiple Range Test at K = 3 on the basis of 18 quantitative traits revealed that one cluster was mainly differentiated from the other two clusters by seed related traits and the other two clusters were differentiated from each other by biochemical traits. Genetic structure of Korean soybean landraces was differentiated by model-based clustering and supported by their phenotypic traits in part. This preliminary study could be the first step towards more efficient germplasm management and utilization of soybean landraces and helpful in association studies between genotypic and phenotypic traits in Korean soybean landraces.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.748-760
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• 2012

In case brightness distribution is concentrated in a region, it is difficult to classify the image features. To solve this problem, we apply global histogram equalization and local histogram equalization to images. In case of global histogram equalization, it can be too bright or dark because it doesn't consider the density of brightness distribution. Thus, it is difficult to enhance the local contrast in the images. In case of local histogram equalization, it can produce unexpected blocks in the images. In order to enhance the contrast in the images, this paper proposes a local histogram equalization based on the Gaussian Mixture Models(GMMs) in regions of histogram. Mean and variance parameters in each regions is updated EM-algorithm repeatedly and then ranges of equalization on each regions. The experimental results performed with image of various contrasts show that the proposed algorithm is better than the global histogram equalization.

• Journal of Korean Public Health Nursing
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• v.12 no.2
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• pp.107-121
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• 1998

The purpose of this study was to test the revised Health Promotion Model of Pender and to determine the factors to promote health behavior for adolescents' smoking behavior. The subjects of the study was 783 boys of 4 high school students. among 39. schools locating in Daejeon metropolitan city. The data was collected from July 1st to 15th. 1997 by school health nurse The research tool were HPLP of Walker. Pender. General self-efficacy scale of Sherer. control scale was measured by subconcept of hardiness scale of Pollock. and perceived barrier. perceived benefit. activity-related-affect tool were made by researcher via literature review The data were analyzed by SAS program using frequency. t-test. ANOVA. Schefee test. regression. The results were as follows 1. The mean of total health promoting behavior was $2.27\pm.35$. Among sub domain of health promoting behavior, the highest score was interpersonal support$(2.72\pm.60)$. and the lowest was health responsibility $(1.58\pm.44)$. 2. There were statistically significant difference in total health promoting behavior according to religion. parenting style. school performance. girl friend. father's smoking of individual characteristics. 3. The socioeconomic status. smoking, parent pattern. family structure of individual characteristics and experience domain associated with perceived benefit. perceived barrier. activity-related affect. interpersonal influence of behavior-specific cognition and affect domain. The perceived barrier. self-efficacy. girl friend and father's smoking of interpersonal influence. and control explained $25.8\%$ of variance of health promoting behavior. From above results school health nurse has to emphasize on health responsibility for health promotion of adolescent. But they couldn't intervene for parent pattern. socioeconomic status. family structure of individual characteristics and experience domain. it could be possible for school health nurse to promote health of adolescents through improving perceived barrier. also develop program to increase self-efficacy and through parent health class for fathers. Above results point to the importance of including parents in smoking prevention effort targeting adolescents. Because increasing control also promotes health of adolescents. it should be studied further about the specific measure. To verify the variables for increasing the fitness of health promoting model. it needs further replication of the research.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.65.1-65.1
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• 2012

MIRIS (Multipurpose Infra-Red Imaging System) is the first Korean Infrared Space Telescope developed by KASI (Korea Astronomy and Space Science Institute), and is the main payload of STSAT-3 (Science and Technology Satellite-3). The FM (fight model) of MIRIS has been recently completed, and various performance tests have been made to measure system parameters such as readout noise, system gain, linearity, and dark current. Final thermal-vacumm test of the MIRIS and the vibration test of the electronics box have been performed. Band response tests showed good agreement with the initial design requirements. No significant dark difference was measured within the expected temperature variation range during observation in orbit. Using Pa-alpha band from a uniform source, the readout noise and system gain were measured by mean variance test. To obtain uniform flat image, flat fielding tests were made for each band, and the data will be compared to that obtained in orbit for calibration. The final version of MIRIS FM will be delivered in March, and it will be integrated into the satellite system for the AIT (Assembly Integration, Test) procedure. The launch of MIRIS is expected in November 2012.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.66-75
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• 2017

Priority disciplines are an important scheme for service systems to differentiate their services for different classes of customers. (N, n)-preemptive priority disciplines enable system engineers to fine-tune the performances of different classes of customers arriving to the system. Due to this virtue of controllability, (N, n)-preemptive priority queueing models can be applied to various types of systems in which the service performances of different classes of customers need to be adjusted for a complex objective. In this paper, we extend the existing (N, n)-preemptive resume and (N, n)-preemptive repeat-identical priority queueing models to the (N, n)-preemptive repeat-different priority queueing model. We derive the queue-length distributions in the M/G/1 queueing model with two classes of customers, under the (N, n)-preemptive repeat-different priority discipline. In order to derive the queue-length distributions, we employ an analysis of the effective service time of a low-priority customer, a delay cycle analysis, and a joint transformation method. We then derive the first and second moments of the queue lengths of high- and low-priority customers. We also present a numerical example for the first and second moments of the queue length of high- and low-priority customers. Through doing this, we show that, under the (N, n)-preemptive repeat-different priority discipline, the first and second moments of customers with high priority are bounded by some upper bounds, regardless of the service characteristics of customers with low priority. This property may help system engineers design such service systems that guarantee the mean and variance of delay for primary users under a certain bounds, when preempted services have to be restarted with another service time resampled from the same service time distribution.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.585-596
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• 2013

The objective of this study is to evaluate the hybrid downscaling method combined Step-Wise Scaling (SWS) method with Regional Climate Model (RCM) simulation data for climate change impact study on hydrology area. The SWS method is divided by 3 categories (extreme event, dry event and the others). The extreme events, wet-dry days and the others are corrected by using regression method, quantile mapping method, mean & variance scaling method. The application and evaluation of SWS method with 3 existing and popular statistical techniques (linear scaling method, quantile mapping method and weather generator method) were performed at the 61 weather stations. At the results, the accuracy of corrected simulation data by using SWS are higher than existing 3 statistical techniques. It is expected that the usability of SWS method will grow up on climate change study when the use of RCM simulation data are increasing.