• Korean Journal of Biological Psychiatry
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• v.16 no.2
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• pp.69-75
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• 2009

Objectives : The detrended fluctuation analysis is one of the nonlinear methods for the investigation of biological time series. It quantifies the fractal scaling properties and is known to be useful in the evaluation of long-range correlations in time series. The heart rate variability(HRV) of obstructive sleep apnea syndrome (OSAS) patients during nighttime was analyzed by detrended fluctuation analysis to assess its relationship with the severity of the symptoms. Methods : Fifty nine untreated male OSAS patients with moderate to severe symptoms(mean age=45.4${\pm}$11.7 years, apnea-hypopnea index, AHI${\geq}$15) underwent nocturnal polysomnography. Moderate(AHI=15-30, N=22) and severe(AHI>30, N=37) OSAS patients were compared for the indices derived from detrended fluctuation analysis and frequency domain analysis of HRV. Results : In the detrended fluctuation analysis, the alpha values were 0.75${\pm}$0.11 and 0.82${\pm}$0.07 for the severe and the moderate OSAS groups respectively. The difference was significant(p<.01). The alpha value had negative correlation with AHI(r=-.425, p=.001). Negative correlation coefficients were also found in the relationships between the alpha values and very low frequency(VLF)(r=-.425, p=.001), low frequency(LF)(r=-.633, p= <.001) and the LF/HF ratio(r=-.305, p=.019) respectively. LF/HF ratio(p=.005) was higher in the severe OSAS group compared to that of the moderate OSAS group. Conclusion : In this study, the detrended fluctuation analysis showed the significant difference between the two OSAS groups classified according to their severity of symptoms. The scaling exponent showed the negative correlation with AHI and indicies of frequency domain analysis. This result suggests that detrended fluctuation analysis can be helpful to estimate the severity of OSAS.

• Korea Journal of Hospital Management
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• v.22 no.4
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• pp.50-60
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• 2017

Purposes: The purpose of this study was to identify the preferred types of the hospital reservation cancellation management to help reduce the reservation cancellations. Methodology: This study sampled 327 outpatients or their guardians who had reserved a university hospital and a general hospital located in the southwestern part of Seoul, and the responses from 300 of them were used for the final analysis. The subjects' preferences of reservation cancellation management types were analyzed in reference to their demographic variables. The timing and frequency of pre-notification preferred by the subjects were examined. A multidimensional scaling methods and correspondence analysis was used to identify preference for management methods of no-show and type of reservation guide. Findings: As a result, 77.3% of the respondents were perceived that the reservation cancellation was a habit. The most preferred method of managing the reservation cancellation would be refusal to refund the reservation deposit (61.7%), followed by payment for cancellation (16.0%), limit of future reservations (16.0%) and penalty (6.3%) in their order. 186 of the subjects (62.0%) preferred the texting for prevention of reservation cancellations, and 102 of the subjects (34.0%) preferred the phone calls. The preferred timing and frequency of the SMS were twice 3 days before, once a day before and three times 7 days before, while the preferred timing and frequency of phone call was once a day before. Practical Implications: The no-show rate can be improved by enhancing SMS pre-notification and by improving afterwards telephone counseling. For other factors, it needs to study on the service differentiation with the characteristics of each patient group.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• Journal of dental hygiene science
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• v.20 no.4
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• pp.187-199
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• 2020

Background: Korean dental hygienists perform various tasks under the supervision of dentists in addition to the tasks listed in the law. Many meaningful studies have been conducted to determine the actual tasks of dental hygienists, but these studies did not show common results due to the differences in research methods or designs. Hence, this study aimed to review the reported data on the tasks of dental hygienists in Korea and to clarify them based on a systematic literature review. Methods: For the literature search, the COre, Standard, and Ideal model presented by the National Library of Medicine was referenced. Seven databases were searched for literatures published in Korea, including PubMed, and Google Scholar. Of the 352 studies found using key words, titles, and abstracts, 46 were finally extracted based on the first and second exclusion criteria. After confirming the tasks of Korean dental hygienists in 46 literatures, 136 tasks were listed and calculated as appearance rate in the literature. Results: The most common tasks in 46 studies were fluoride application (67.2%), radiography (65.4%), scaling (65.4%), sealant (60.7%), patient management and counseling (56.7%), tooth-brushing education (52.2%), impression taking with alginate (50.1%), and making temporary crowns (47.9%). The most mentioned tasks of dental hygienists in public health centers were fluoride application (100%), sealant (100%), oral health education (71.4%), public oral health program evaluation (71.4%), school fluoride mouth-rinsing program (71.4%), water fluoridation (57.1%), tooth-brushing education (57.1%), school oral health programs (57.1%), and public elderly oral health programs (57.1%). Conclusion: This study showed that Korean dental hygienists had 136 tasks by reviewing 46 related studies and that the main job of Korean dental hygienists was oral disease prevention including scaling, sealant, and fluoride application.

• Journal of Periodontal and Implant Science
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• v.32 no.2
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• pp.415-428
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• 2002

Periodontal disease is a complex infectious disease caused by bacteria in the oral mucosa, which results in gingival inflammation, breakdown of periodontal tissues, bone resorption, and finally tooth loss. Mechanical plaque control methods-scaling and root planing are effective methods to stop the progression of such periodontal disease. It was reported that subantimicrobial dose of doxycycline(SDD) regimen could improve clinical conditions of periodontal tissues without causing the overgrowth of opportunistic organisms that was a typical antibiotic side effect. Therefore pharmacological therapy, used in conjunction with mechanical therapy could be considered a useful treatment modality in the treatment of chronic periodontal disease. In this study, 30 patients diagnosed as moderate to advanced chronic periodontitis were divided into 2 groups. In this double-blind, placebo-controlled study, the patients were administered 20mg doxycycline capsule or placebo capsule b.i.d. for 4months, after scaling and root planing. Clinical parameters-bleeding on probing, pocket depth and clinical attachment level were compared and evaluated between these groups at periods of first visit, 1 month, 2 months, 3 months, 4 months. The results were as follows ; 1. In case of moderate periodontitis, pocket depth showed significant reduction after treatment in both the control & experiment groups, when compared with the baseline values(p<0.01), but in case of advanced periodontitis, only the experiment group showed significant reduction after treatment when compared with the baseline values(p<0.05). Statistically significant reduction in pocket depth was observed in the experiment group compared to the control group(p<0.05). 2. In case of moderate periodontitis, clinical attachment level showed significant reduction after treatment in both the control & experiment groups, when compared with the baseline values(p<0.01), but in case of advanced periodontitis, only the experiment group showed significant reduction after treatment when compared with the baseline values(p<0.05). Statistically significant reduction in clinical attachment level was observed in the experiment group compared to the control group(p<0.05). 3. Bleeding on probing improved after treatment in both the groups. In case of moderate periodontitis, the experiment group showed statistically significant reduction of bleeding on probing when compared with the control group at 1 and 4 months after treatment(p<0.05). In case of advanced periodontitis, treatment resulted in statistically significant reduction of bleeding on probing in both the groups(p<0.05). These results indicate that the use of subantimicrobial dose of doxycycline is a useful supplement to mechanical treatment for periodontal patients in ameliorating the clinical parameters such as periodontal pocket, attachment level, and bleeding on probing.

• Journal of the Korean Society of Safety
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• v.32 no.4
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• pp.89-99
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• 2017

The purpose of this study is to analyze safety and health managers' perceptual maps on the effective educational contents and its methods of workplace safety and health education. Self-administered survey was successfully conducted to 582 workers who were 339 in manufacturing, 68 in construction, and 175 in service & others by industry classification. Survey sites were recruited based on business size, incidence of occupational accident, and compliance of workplace safety and health education regulation. Questionnaire included personal factors, workplace factors, and needs of safety and health education at work. Male workers were 85.3% and more than 50% were in their 30s and had university education. Overall needs of educational contents and its methods were greater in manufacturing and services than construction. Two dimensional properties of effective educational contents perceived were 'knowledge structure' which divided to safety and health, and 'behavior outcomes' which divided to indirect and direct. Two dimensional properties of educational methods were 'class activity' which divided to experience-based and verbal-based and 'class participation' which divided to passive and active. Effective educational contents and its methods perceived by safety and health managers commonly included the characteristics of direct, case-based, and participation.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Korean Journal of Ecology and Environment
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• v.41 no.spc
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• pp.1-10
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• 2008

We patterned water quality of agricultural reservoirs according to the differences of six physico-chemical environmental factors (TN, TP, DO, BOD, COD, and SS) using four different ordination methods: Principal Components Analysis (PCA), Detrended Correspondence Analysis (DCA), Nonmetric Multidimensional Scaling (NMS), and Isometric Feature Mapping (Isomap). The data set was obtained from the water quality monitoring networks operated by the Ministry of Agriculture and Forestry and the Ministry of Environments. Chlorophyll-${\alpha}$ displayed the highest correlation with COD, followed by TP, BOD, SS, and TN (p<0.01), while negatively correlated with altitude and bank height of the reservoirs (p<0.01). Although four different ordination methods similarly patterned the reservoirs according to the gradient of nutrient concentration, PCA and NMS appeared to be the most efficient methods to pattern water quality of reservoirs based on the explanation power. Considering variable scores in the ordination map, the concentration of nutrients was positively correlated with Chl-${\alpha}$, while negatively correlated with altitude and bank height. These ordination methods may help to pattern agricultural reservoirs according to their water quality characteristics.

• Journal of Environmental Science International
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• v.29 no.1
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• pp.25-32
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• 2020

The determination of soil parameters is important in predicting the simulated surface runoff using either a distributed or a lumped rainfall-runoff model. Soil characteristics can be collected using remote sensing techniques and represented as a digital map. There is no universal agreement with respect to the determination of a representative parameter from a gridded digital map. Two representative methods, i.e., arithmetic and predominant, are introduced and applied to both FLO-2D and HEC-HMS to improve the model's accuracy. Both methods are implemented in the Yongdam catchment, and the results show that the former seems to be more accurate than the latter in the test site. This is attributed to the high conductivity of the dominant soil class, which is A type.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.264-267
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• 1998

We are dealing with the preliminary diagnosis from the information of headache interview chart. We quantify the qualitative information based on the interview chart by dual scaling. Prototype of fuzzy diagnostic sets and the neural linear regression methods are established with these quantified data, These new methods can be used to classify new patient's tone of diseases with certain degrees of belief and its concerned symptoms. We call these procedures as neural Fuzzy Differential Diagnosis of Headache (NFDDH-1). Also we investigate three measures to medical diagnosis, where relations between symptoms and diseases are described by intutionistic fuzzy set (IFS) data. Two measures are described by nin-max and max-min IFS operators, respectively. Another measure is the similarity degree, i.e., IFS distance between patient's symptoms and prototypes of diseases. We consider some reasonable criteria for three measures in order to determine the label of headache, We will establish hree measures in NFDDH-2 and combine two packages as NFDDH