• 대한화학회지
• /
• 제63권2호
• /
• pp.78-84
• /
• 2019

High-resolution $^1H$ NMR spectroscopic technique has been widely used as one of the most powerful analytical tools in food chemistry as well as to define molecular structure. The $^1H$ NMR spectra-based metabolomics has focused on classification and chemometric analysis of complex mixtures. The principal component analysis (PCA), an unsupervised clustering method and used to reduce the dimensionality of multivariate data, facilitates direct peak quantitation and pattern recognition. Using a combination of these techniques, the various green teas and black teas brewed were investigated via metabolite profiling. These teas were characterized based on the leaf size and country of cultivation, respectively.

• Smart Structures and Systems
• /
• 제22권6호
• /
• pp.711-725
• /
• 2018

Most of the practical engineering structures exhibit nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. Hence, it is highly desirable to detect and characterize the nonlinearity present in the system in order to assess the true behaviour of the structural system. Further, these identified nonlinear features can be effectively used for damage diagnosis during structural health monitoring. In this paper, we focus on the detection of the nonlinearity present in the system by confining our discussion to only a few selective time-frequency analysis and multivariate analysis based techniques. Both damage induced nonlinearity and inherent structural nonlinearity in healthy systems are considered. The strengths and weakness of various techniques for nonlinear detection are investigated through numerically simulated two different classes of nonlinear problems. These numerical results are complemented with the experimental data to demonstrate its suitability to the practical problems.

• Communications for Statistical Applications and Methods
• /
• 제26권5호
• /
• pp.519-526
• /
• 2019

Response dimension reduction in a sufficient dimension reduction (SDR) context has been widely ignored until Yoo and Cook (Computational Statistics and Data Analysis, 53, 334-343, 2008) founded theories for it and developed an estimation approach. Recent research in SDR shows that a semi-parametric approach can outperform conventional non-parametric SDR methods. Yoo (Statistics: A Journal of Theoretical and Applied Statistics, 52, 409-425, 2018) developed a semi-parametric approach for response reduction in Yoo and Cook (2008) context, and Yoo (Journal of the Korean Statistical Society, 2019) completes the semi-parametric approach by proposing an unstructured method. This paper theoretically discusses and provides insightful remarks on three versions of semi-parametric approaches that can be useful for statistical practitioners. It is also possible to avoid numerical instability by presenting the results for an orthogonal transformation of the response variables.

• 응용통계연구
• /
• 제31권4호
• /
• pp.517-528
• /
• 2018

다변량 자료에서 특이점을 검출하고, 검출된 특이점을 시각화와 연결한 R 스크립트를 제공한다. 개발된 R 스크립트는 특이점을 검출하는 방법으로서 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) Density-based approach 방법을 이용하였다. 특이점을 연결하면서 데이터 구조를 파악하기 위한 시각화 방법으로는 1) multidimensional scaling (MDS)와 minimal spanning tree (MST)를 K-means 군집분석과 연결하여 표시하는 방법, 2) MDS를 fviz cluster와 연결하는 방법, 3) principal component analysis (PCA)를 fviz cluster와 연결한 방법을 이용하였다. 사례분석의 예로서는 Major League Baseball (MLB) 자료에서 류현진이 적극적으로 활동하던 2013년, 2014년 투수자료를 이용하였다. 개발된 R 스트립트는 "http://www.knou.ac.kr/~sskim/ddpoutlier.html (R 스크립트와 R 패키지도 다운로드 받을 수 있다. 실행방법도 설명되어 있다.)"에서 다운받으면 된다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권1호
• /
• pp.216-238
• /
• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• 대한인간공학회지
• /
• 제25권2호
• /
• pp.107-118
• /
• 2006

Recently, Korean's 3-D foot data have been extensively collected through 5th national anthropometric survey known as 'Size Korea'. In this study, Korean foot shape was investigated and subsequently classified, based on the existing standard for foot shaping. This study analyzed and categorized Korean foot shapes through the following methods. Although the data used in this study were limited to those of Korean adults, major factors affecting the foot shape were deduced and then categorically grouped by the multivariate statistical analysis. For those whose age ranged from 14 to 70, major factors affecting the foot shape for the male were related to foot breadth, ankle thickness, 1st toe shape, malleolus height, heel to top of the foot length, the ratio between toe-side and heel-side and 5th toe shape. For the female, the ball of foot height was added to the above factors. From the factors extracted, the Korean foot shape was categorized into three groups for the male and four groups for the female. They were the ladder type, the inverted triangle type and the square type. For the female, the triangular type was added to the three types. These findings will serve as useful information for the footwear production industry in Korea.

• 지역사회간호학회지
• /
• 제28권3호
• /
• pp.302-312
• /
• 2017

Purpose: The purpose of this study was to identify associated factors of chewing discomfort among community-dwelling elderly. Methods: The study was cross-sectional design and secondary data analysis using the 6th Korea National Health and Nutrition Examination Survey. Among the total of 7,550 participants, data was analyzed with 1,126 adults aged 65 years and over. Chewing discomfort was assessed by the perceived chewing discomfort. Multivariate logistic regression analysis was used to find the associated factors of chewing discomfort. Results: Along with 61.7% of the participants reported having chewing discomfort, 85.2% reported to perceive poor oral health and 35.0% had oral pain. In multivariate logistic regression, perceived oral health (OR 3.22, 95% CI 2.24~4.63), oral pain (OR 2.46, 95% CI 1.76~3.43), activity limitation (OR 1.71, 95% CI 1.05~2.80), teeth requiring treatment (OR 1.61, 95% CI 1.14~2.26), number of remaining teeth (OR 1.60, 95% CI 1.22~2.10) and educational level (OR 1.56, 95% CI 1.15~2.12) were the significant predictors of chewing discomfort. Conclusion: The prevalence in chewing discomfort was high in elderly Koreans and various factors were associated with chewing discomfort. To improve chewing ability, it is suggested that the national level of policies offer strategical oral health programs in this population.

• Journal of Korean Biological Nursing Science
• /
• 제16권4호
• /
• pp.259-266
• /
• 2014

Purpose: The purpose of this study was to analyze risk factors in predicting medical patients transferred to Intensive Care Unit (ICU) on the general ward. Methods: We reviewed retrospectively clinical data of 120 medical patients on the general ward and a Modified Early Warning Score (MEWS) between ICU group and general ward group. Data were analyzed with multivariate logistic regression and the area under the receiver operating characteristic curves using SPSS/WIN 18.0 program. Results: Fifty-two ICU patients and 68 general ward patients were included. In multivariate logistic regression, the MEWSs (Odds Ratio [OR], 1.91; 95% confidence interval [CI], 1.32-2.76), sequential organ failure assessment score (OR, 1.28; 95% CI, 1.10-1.72), $PaO_2/FiO_2$ ratio (OR, 0.98; 95% CI, 0.98-0.99), and saturation (OR, 0.93; 95% CI, 0.88-0.99) were predictive of ICU transfer. The sensitivity and the specificity of the MEWSs used with a cut-off value of six were 80.8% and 70.6% respectively for ICU transfer. Conclusion: These findings suggest that early prediction and treatment of patients with high risk of ICU transfer may improve the prognosis of patients.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권12호
• /
• pp.7133-7136
• /
• 2013

Background: We studied Surveillance, Epidemiology and End Results (SEER) breast cancer data of Georgia USA to analyze the impact of socio-economic factors on the disparity of breast cancer treatment outcome. Materials and Methods: This study explored socio-economic, staging and treatment factors that were available in the SEER database for breast cancer from Georgia registry diagnosed in 2004-2009. An area under the receiver operating characteristic curve (ROC) was computed for each predictor to measure its discriminatory power. The best biological predictors were selected to be analyzed with socio-economic factors. Survival analysis, Kolmogorov-Smirnov 2-sample tests and Cox proportional hazard modeling were used for univariate and multivariate analyses of time to breast cancer specific survival data. Results: There were 34,671 patients included in this study, 99.3% being females with breast cancer. This study identified race and education attainment of county of residence as predictors of poor outcome. On multivariate analysis, these socio-economic factors remained independently prognostic. Overall, race and education status of the place of residence predicted up to 10% decrease in cause specific survival at 5 years. Conclusions: Socio-economic factors are important determinants of breast cancer outcome and ensuring access to breast cancer treatment may eliminate disparities.

• 한국방재학회 논문집
• /
• 제1권2호
• /
• pp.115-121
• /
• 2001

실측자료가 충분하지 못한 단기간의 유출량 자료로부터 추계학적 모형에 의해 장기간의 자료를 모의발생시키는 목적은 수공구조물의 설계에 필요한 설계홍수량의 산정 및 수자원 시스템의 운영조작 방침을 결정하기 위한 풍부한 입력자료를 제공하는데 있다. 특히 본 연구에서는 단일지점이 아닌 다지점에 대한 지점간 서로의 연관성을 고려한 하천유량의 추계학적인 모의 발생기법인 다변량 자기회귀 모형을 적용하고자 한다. 따라서 본 연구에서는 낙동강유역의 2개 지점에 대하여 다변량 모형을 적용하여 모의 발생된 월유량과 실측치를 통계적으로 비교, 분석하였다. 모의발생된 월유량과 실측치를 평균, 분산, 왜곡도, 상관관계 등에 의해 비교, 분석한 결과 모의발생된 월유량과 실측치는 통계적으로 매우 유사하게 나타났다.