• Title/Summary/Keyword: Regression Analysis Model

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The Clinical study of Su-Gi therapy's Effects on Bell's palsy by observing of DITI (DITI로 관찰한 Bell's palsy에 미치는 수기요법의 영향에 관한 임상적 연구)

  • Hong, Seung Cheol;Ahn, Hun Mo;Lee, Jae Heung;Ha, Jeong-A
    • Journal of Korean Medical Ki-Gong Academy
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    • v.15 no.1
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    • pp.44-60
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    • 2015
  • Objective : The purpose of this study is to investigate the effect of Su-Gi therapy for Bell's palsy by using DITI. Methods : We investigated 16 patients with Bell's palsy who had visited in the H Korean medicine hospital in Gyeonggi Province from December 27th, 2010 to April 8th, 2015. The Su-Gi therapy was done by 1 times daily. We evaluated the change of them by using Digital Infrared Thermographic Imaging and Yanagihara's unweighted grading system. Results : There aren't meaningful differences in values for the meridian points in pretest and posttest which were observed by DITI of abnormal side and normal side. There are meaningful differences in values, for abnormal side and normal side of the meridian points in pretest and posttest of DITI. It was of significance that pretest Y and average ΔT of each the meridian points in the type of hyperthermia but not in the type of hypothermia. In the Correlation analysis of values of pretest and posttest, chaotic aspects of body heat distribution in the pretest change as a relatively consistent aspects in the posttest. It wasn't of significance that Correlation Analysis of Ups and downs in temperature of TE17 and Recovery speed observed by ΔY. In simple regression analysis of posttest's Y-system values against absolute ΔT by subtracting ΔTE17 from ΔST6, we didn't predict in the pretest, but could predict significantly in the posttest(Regression coefficient : -2.11) In the regression analysis result of the meridian points' ||pretest ΔT|-|posttest ΔT||, 陽白(GB14) and 頰車(ST6) are of significance (Total R-Square=0.447). But we couldn't obtain final regression analysis model. Conclusions: These results suggest that Su-Gi therapy may be effective for Bell's palsy.

A Measurement and Analysis of AIS Level in SMBs using Nolan Model (Nolan 모형을 이용한 중소기업 회계정보시스템 수준과 성과분석)

  • Lim, Kyu-Chan
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.245-253
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    • 2020
  • The purpose of the research was to identify the level of accounting information system for SMBs and environmental factors, and to analyze whether the level of accounting information system affects system performance. The research method measured the AIS level using Nolan's growth phase model, and the verification of the factors affecting the situation, AIS level, and performance was verified using the regression analysis model. The results of the study are summarized as follows: In measuring the level of an accounting information system, it was found that it was in the stage of integration, which is Step 4, and the analysis of the factors influencing the level of an accounting information system showed that the uncertainty in the environment was absolutely affected.

A Study on the Determinants of Goodwill's Road shop (상가권리금의 결정요인에 관한 연구)

  • Lim, Jae-Hyon;Jeong, Seung-Young
    • Journal of Cadastre & Land InformatiX
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    • v.45 no.2
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    • pp.191-201
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    • 2015
  • There has been few researches on the variables that influence on goodwill of the store. The purpose of this study is to identify the determined variables which affect goodwill of the store in seoul empirically by examining the interaction between goodwill and risk sharing in the commercial lease contract. We have analyzed 1,463 retail unite of goodwill over August, 2015. A regression analysis model is constructed to test the significance of the variables on the goodwill per $m^2$ in Seoul. The results indicate that rent to total start-up cost of ratio and retail property characteristics variables explain a significant portion of the variability of goodwill. The results suggest that retail rents is comparatively more important than size of store. The study suggests that monthly rents to total start-up cost of ratio is the key variable affecting the goodwill of the store.

Model setup and optimization of the terminal rise velocity of microbubbles using polynomial regression analysis (다항식 회귀분석을 이용한 마이크로 버블의 종말상승속도 모델식 구축 및 운전조건 최적화)

  • Park, Gun-Il;Kim, Heung-Rae;Cho, Il Hyoung
    • Journal of the Korean Applied Science and Technology
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    • v.35 no.4
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    • pp.1393-1406
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    • 2018
  • In this study, three parameters (Pressure ($X_1$), Airflow rate ($X_2$), Operation time ($X_3$)) were experimentally designed and the predicted model and optimal conditions were established by using the terminal rise velocity of the microbubbles as the response value. The polynomial regression analysis showed that the optimum value for the terminal rise velocity at the Pressure ($X_1$) of 4.5 bar, Airflow rate ($X_2$) of 3.3 L/min and Operation time ($X_3$) of 2.2 min was 5.14 cm/min ($85.7{\mu}m/sec$). Also, the highest microbubble diameter size distribution in the range of 2 to $5{\mu}m$ and 25 to $50{\mu}m$ was confirmed by using a laser particle counting apparatus.

Decommissioning Cost Estimation of Kori Unit 1 Using a Multi-Regression Analysis Model (회귀 분석 모델을 이용한 고리 1호기 해체 비용 추정)

  • Joo, Han Young;Kim, Jae Wook;Jeong, So Yun;Moon, Joo Hyun
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.18 no.2_spc
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    • pp.247-260
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    • 2020
  • A multi-regression model was developed to estimate the decommissioning cost for Kori unit 1 using foreign nuclear power plant (NPP) decommissioning cost data. First, the decommissioning cost data were collected for 13 boiling water reactors and 16 pressurized water reactors and converted into the values as of November 2019. Then, for the regression model, the decommissioning cost was chosen as the dependent variable, and two variables were selected as independent variables: a contamination factor that was designed to reflect the operational characteristics of the decommissioned NPP and the decommissioning period. A statistical package in the R language was used to derive the regression model. Finally, the regression model was applied to estimate the decommissioning cost for Kori unit 1. The estimated decommissioning cost for Kori unit 1 was 663.40~928.32 million US dollars (782,812~1,095,418 million Korean won).

The Association between Obesity and Periodontal Disease on Convergence Study (비만과 치주질환간의 관련성에 관한 융합연구)

  • Kim, Ji Hyun
    • Journal of the Korea Convergence Society
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    • v.9 no.8
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    • pp.71-76
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    • 2018
  • The aim of this study was to evaluate the association between obesity and periodontal diseases in Korea adults. The date from the 2015 Korean National Health and Nutrition Survey were used, and 4,827 subjects over 19 years were included in the analysis. Periodontal disease was assessed using the Community Periodontal Index. Obesity was measured according to body mass index. Odd ratios (ORs) were estimated using binary logistic regression analysis model. The stratification variables were smoking and diabetes, and also adjusted for sex, age, and education level. The adjusting variables included sex, age, and education level. The ORs of obesity for periodontal disease were 0.78 (95% CI = 0.51-1.22) for the category of <18.5 of BMI and 1.29 (95% CI = 1.11-1.49) for the ${\geq}25$ BMI category (both compared to the 18.5 to 24.9 category). In a subgroup analysis, the OR of BMI among those who were both non-smoking and no diabetes was 1.20 (95% CI = 1.02-1.48) for those with BMI levels ${\geq}25$. This study implies that obesity intolerance may be an independent risk factor for periodontal diseases. Obesity should also be considered when managing periodontal disease to improve oral health.

A Study on the Characteristics of Prematurely Discharged Patients and Establishing a Model for Predicting Prematurely Discharged Patients -Using Data Mining- (환자이탈군 특성요인과 이탈환자 예측모형에 관한 연구 -데이터마이닝을 활용하여-)

  • Kim, Kwang-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.11
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    • pp.3480-3486
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    • 2009
  • This research was based on the purpose of establishing predicted model of prematurely discharged patients using the mandatory information data, recorded in the medical institutes based on discharged patients of a University Hospital for the period of 1 year, from July. The result showed that the regression analysis model was the most excellent method of application model for preventing discharged patients, and when this is applied to discharged patients who are outpatients, the possibility of discharge can be less than staying in the emergency room. In addition, based on threshold 0.7, when we expect the discharged patients, out of 920 discharged patients, the actual patients who are discharged can become 136, showing the extract effectiveness of 14.78%. Based on the perspective of lift value, compared to random extract, this is 2.9 times (14.78/5.15) more effective.

Factors affecting antibiotic prescription in dental outpatients - A nation-wide cohort study in Korea - (치과 외래 치료에서 항생제 처방에 영향을 주는 요인 - 한국 국민건강보험 표본코호트 연구 -)

  • Lee, Kyeong-Hee;Choi, Yoon-Young
    • Journal of Korean society of Dental Hygiene
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    • v.19 no.3
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    • pp.409-419
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    • 2019
  • Objectives: The purpose of this study was to analyze the factors affecting antibiotic prescription in dental outpatients. Methods: The present study was conducted using data from the National Health Insurance Service - National Sample Cohort. We analyzed prescriptions issued in the dental outpatient department in 2015, for adults over 19 years of age. Antibiotic prescription rates and mean prescription days were analyzed by sex, age, insurance type, presence of diabetes mellitus and hypertension, season in treatment, type of dental institution, and location of dental institution. Multivariate logistic regression was also performed to analyze the factors affecting antibiotic prescription in dental outpatients. Results: A total of 257,038 prescriptions were analyzed. The mean prescription days of antibiotics in dental outpatients were $3.04{\pm}1.08days$, and the prescription rate was 93.0%. Two variables (presence of diabetes mellitus and insurance type) were excluded from the multivariate logistic regression analysis model because they did not significantly affect antibiotic prescription. The possibility of antibiotic prescription was higher in men ${\geq}61years$ of age and those with hypertension. Furthermore, antibiotics were most frequently prescribed in dental clinics rather than dental hospitals, and more frequently in Busan compared to other areas (p<0.001). Conclusions: Several factors were determined to affect antibiotic prescription, and detailed guidelines for consistent antibiotic prescription are needed.

Forecasting Technique of Downstream Water Level using the Observed Water Level of Upper Stream (수계 상류 관측 수위자료를 이용한 하류 홍수위 예측기법)

  • Kim, Sang Mun;Choi, Byungwoong;Lee, Namjoo
    • Ecology and Resilient Infrastructure
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    • v.7 no.4
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    • pp.345-352
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    • 2020
  • Securing the lead time for evacuation is crucial to minimize flood damage. In this study, downstream water levels for heavy rainfall were predicted using measured water level observation data. Multiple regression analysis and artificial neural networks were applied to the Seom River experimental watershed to predict the water level. Water level observation data for the Seom River experimental watershed from 2002 to 2010 were used to perform the multiple regression analysis and to train the artificial neural networks. The water level was predicted using the trained model. The simulation results for the coefficients of determination of the artificial neural network level prediction ranged from 0.991 to 0.999, while those of the multiple regression analysis ranged from 0.945 to 0.990. The water level prediction model developed using an artificial neural network was better than the multiple-regression analysis model. This technique for forecasting downstream water levels is expected to contribute toward flooding warning systems that secure the lead time for streams.

Data visualization of airquality data using R software (R 소프트웨어를 이용한 대기오염 데이터의 시각화)

  • Oh, Youngchang;Park, Eunsik
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.399-408
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    • 2015
  • This paper presented airquality data through data visualization in several ways and described its characteristics related to statistical methods for analysis. Software R was used for visualization tools. The airquality data was measured in New York city from May to September of year 1973. First, simple, exploratory data analysis was done in terms of both data visualization and analysis to find out univariate characteristics. Then through data transformation and multiple regression analysis, model for describing the airquality level was found. Also, after some data categorization, overall feature of the data was explored using box plot and three-dimensional perspective drawing and scatter plot.