• Title/Summary/Keyword: Models, statistical

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Impact of oral health behaviors on the presence or absence of periodontal diseases and missing tooth (당뇨환자의 구강건강행태가 치주질환 및 상실치 유무에 미치는 영향)

  • Ju, On-Ju
    • Journal of Korean society of Dental Hygiene
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    • v.11 no.4
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    • pp.511-522
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    • 2011
  • Objectives : The purpose of this study was to provide some information on the development of oral health care programs geared toward diabetics and ways of promoting their oral health. Methods : The subjects in this study were 586 diabetics who were selected from the 2009 third-year raw data of the 4th(2007~2009) National Health & Nutrition Survey. The data were analyzed with the statistical package SPSS 12.0 to grasp the influence of their sociodemographic characteristics and oral health behaviors on the presence or absence of periodontal diseases and missing tooth. Results : 1. Periodontal diseases were twofold more prevalent among the men than the women(p<0.01). By age, those who were in their 60s had 1.11-fold more periodontal diseases than those who were in their 70s and up(p<0.05). 2. The men and women were similar to each other in the number of missing tooth. By age, the number of missing tooth got smaller in proportion to decrease in age. By income, the number of missing tooth was 1.48-fold larger among the patients who earned an income of one million won or less than those who earned an income of two million won or more(p<0.01). Conclusions : The above-mentioned findings suggest that prospective cohort studies should be implemented to present prediction models of periodontal diseases and diabetes instead of merely sticking to cross-sectional studies. And oral health programs should be developed based on the findings of cohort studies to encourage diabetics to care about their oral health, and in which way they should be helped to promote their oral health should carefully be considered.

Algorithmic Generation of Self-Similar Network Traffic Based on SRA (SRA 알고리즘을 이용한 Self-Similar 네트워크 Traffic의 생성)

  • Jeong HaeDuck J.;Lee JongSuk R.
    • The KIPS Transactions:PartC
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    • v.12C no.2 s.98
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    • pp.281-288
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    • 2005
  • It is generally accepted that self-similar (or fractal) Processes may provide better models for teletraffic in modem computer networks than Poisson processes. f this is not taken into account, it can lead to inaccurate conclusions about performance of computer networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A generator of pseudo-random self similar sequences, based on the SRA (successive random addition) method, is implemented and analysed in this paper. Properties of this generator were experimentally studied in the sense of its statistical accuracy and the time required to produce sequences of a given (long) length. This generator shows acceptable level of accuracy of the output data (in the sense of relative accuracy of the Hurst parameter) and is fast. The theoretical algorithmic complexity is O(n).

Context Recognition Using Environmental Sound for Client Monitoring System (피보호자 모니터링 시스템을 위한 환경음 기반 상황 인식)

  • Ji, Seung-Eun;Jo, Jun-Yeong;Lee, Chung-Keun;Oh, Siwon;Kim, Wooil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.343-350
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    • 2015
  • This paper presents a context recognition method using environmental sound signals, which is applied to a mobile-based client monitoring system. Seven acoustic contexts are defined and the corresponding environmental sound signals are obtained for the experiments. To evaluate the performance of the context recognition, MFCC and LPCC method are employed as feature extraction, and statistical pattern recognition method are used employing GMM and HMM as acoustic models, The experimental results show that LPCC and HMM are more effective at improving context recognition accuracy compared to MFCC and GMM respectively. The recognition system using LPCC and HMM obtains 96.03% in recognition accuracy. These results demonstrate that LPCC is effective to represent environmental sounds which contain more various frequency components compared to human speech. They also prove that HMM is more effective to model the time-varying environmental sounds compared to GMM.

The Electrical Insulation Characteristics of HTS SMES (초고온초전도 SMES의 절연특성)

  • Cheon, Hyeon-Gweon;Choi, Jae-Hyeong;Kim, Hae-Jong;Seong, Ki-Chul;Kim, Sang-Hyun
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2005.07a
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    • pp.623-626
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    • 2005
  • Toward the practical applications, on operation of conduction-cooled HTS SMES at temperatures well below 77 K should be investigated, in order to take advantage of a greater critical current density of HTS and considerably reduce the size and weight of the system. Recently, research and development concerning application of the conduction-cooled HTS SMES that is easily movement are actively progressing in Korea. Electrical insulation under cryogenic temperature is a key and an important element in the application of this apparatus. Using multi wrapped copper by polyimide film for HIS SMES, the breakdown characteristics of models for turn-to-turn, that is surface contact model, were investigated under ac and impulse voltage at 77 K. A material that is Polyimide film (Kapton) 0.025 mm thickness is used for multi wrapping of the electrode. Statistical analysis of the results using Weibull distribution to examine the wrapping number effects on breakdown voltage under ac and impulse voltage in $LN_2$ was carried.

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Investigation of Impacts of Truck Lane Restrictions on Multilane Highways Using Micro Traffic Simulation (미시적 시뮬레이션을 이용한 화물차 차로이용제한 영향분석)

  • Yang, Choong-Heon;Son, Young-Tae;Kwon, Yong-Suk
    • International Journal of Highway Engineering
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    • v.9 no.4
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    • pp.75-82
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    • 2007
  • This study was performed to investigate impacts of truck lane restrictions on multilane highways on traffic flow variables such as average speed, the frequency of lane changes, and change in traffic volume and also to verify whether or not different lane restriction scenarios were proper. Two types of hypothetical highway networks and OD demands were developed for traffic simulation models in order to conduct the experimental study. Three types of scenarios were also developed according to the number of restricted lanes for trucks. The PARAMICS microscopic traffic simulation software package was used as the primary analytical tool. Statistical analysis was conducted with simulation outputs. Results showed that truck lane restrictions may lead to positive impacts on traffic flow on multilane highways. In addition, this study demonstrated that the number of restricted lanes can be very an important factor to lead successful implementation of truck lane restrictions.

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Bayesian Analysis and Mapping of Elderly Korean Suicide Rates (베이지안 모형을 활용한 국내 노인 자살률 질병지도)

  • Lee, Jayoun;Kim, Dal Ho
    • The Korean Journal of Applied Statistics
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    • v.28 no.2
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    • pp.325-334
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    • 2015
  • Elderly suicide rates tend to be high in Korea. Suicide by the elderly is no longer a personal problem; consequently, further research on risk and regional factors is necessary. Disease mapping in epidemiology estimates spatial patterns for disease risk over a geographical region. In this study, we use a simultaneous conditional autoregressive model for spatial correlations between neighboring areas to estimate standard mortality ratios and mapping. The method is illustrated with cause of death data from 2006 and 2010 to analyze regional patterns of elderly suicide in Korea. By considering spatial correlations, the Bayesian spatial models, mean educational attainment and percentage of the elderly who live alone was the significant regional characteristic for elderly suicide. Gibbs sampling and grid method are used for computation.

A Study on Domestic Drama Rating Prediction (국내 드라마 시청률 예측 및 영향요인 분석)

  • Kang, Suyeon;Jeon, Heejeong;Kim, Jihye;Song, Jongwoo
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.933-949
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    • 2015
  • Audience rating competition in the domestic drama market has increased recently due to the introduction of commercial broadcasting and diversification of channels. There is now a need for thorough studies and analysis on audience rating. Especially, a drama rating is an important measure to estimate advertisement costs for producers and advertisers. In this paper, we study the drama rating prediction models using various data mining techniques such as linear regression, LASSO regression, random forest, and gradient boosting. The analysis results show that initial drama ratings are affected by structural elements such as broadcasting station and broadcasting time. Average drama ratings are also influenced by earlier public opinion such as the number of internet searches about the drama.

Squared Log-return and TGARCH Model : Asymmetric Volatility in Domestic Time Series (제곱수익률 그래프와 TGARCH 모형을 이용한 비대칭 변동성 분석)

  • Park, J.A.;Song, Y.J.;Baek, J.S.;Hwang, S.Y.;Choi, M.S.
    • The Korean Journal of Applied Statistics
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    • v.20 no.3
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    • pp.487-497
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    • 2007
  • As is pointed out by Gourieroux (1997), the volatility effects in financial time series vary according to the signs of the return rates and therefore asymmetric Threshold-GARCH (TGARCH, henceforth) processes are natural extensions of the standard GARCH toward asymmetric volatility modeling. For preliminary detection of asymmetry in volatility, we suggest graphs of squared-log-returns for various financial time series including KOSPI, KOSDAQ and won-Euro exchange rate. Next, asymmetric TGARCH(1,1) model fits are provided in comparisons with standard GARCH(1.1) models.

Bayesian analysis of finite mixture model with cluster-specific random effects (군집 특정 변량효과를 포함한 유한 혼합 모형의 베이지안 분석)

  • Lee, Hyejin;Kyung, Minjung
    • The Korean Journal of Applied Statistics
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    • v.30 no.1
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    • pp.57-68
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    • 2017
  • Clustering algorithms attempt to find a partition of a finite set of objects in to a potentially predetermined number of nonempty subsets. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet prior distribution calculates posterior probabilities when the number of clusters was known. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. Examples are given to show how these models perform on real data.

Reliability Analysis of Fatigue Truck Model Using Measured Truck Traffic Statistics (통행차량 특성을 반영한 강교량 피로설계트럭의 피로파괴 신뢰도해석)

  • Shin, Dong Ku;Kwon, Tae Hyung;Park, Young Suk
    • Journal of Korean Society of Steel Construction
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    • v.19 no.2
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    • pp.211-221
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    • 2007
  • A structural reliability analysis of fatigue truck model for fatigue failure of highway steel bridges was performed by applying the Miner's fatigue damage rule expressed as a function of various random variables affecting fatigue damage. Among the variables, the statistical parameters for equivalent moment, impact factor, and loadometer were obtained by analyzing recently measured domestic traffic data, whereas the parameters on fatigue strength, girder distribution factor, and headway factor of the measured data available in the literature were used. The effects of various fatigue truck models, fatigue life, ADTT, fatigue detail category, loadometer, and gross vehicle weight of fatigue truck on the reliability index of fatigue damage were analyzed. It is expected that the analytical results presented herein can be used as a basic background material in the calibration of both fatigue design truck and fatigue load factor of LRFD specification.