• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.311-315
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• 2013

본 논문에서는 주성분 회귀법과 부분최소자승 회귀법을 비교하여 보여준다. 이 비교의 목적은 선형형태를 보유한 근적외선 분광 데이터의 분석에 사용할 수 있는 적합한 예측 방법을 찾기 위해서이다. 두 가지 데이터 마이닝 방법론인 주성분 회귀법과 부분최소자승 회귀법이 비교되어 질 것이다. 본 논문에서는 부분최소자승 회귀법은 주성분 회귀법과 비교했을 때 약간 나은 예측능력을 가진 결과를 보여준다. 주성분 회귀법에서 50개의 주성분이 모델을 생성하기 위해서 사용지만 부분최소자승 회귀법에서는 12개의 잠재요소가 사용되었다. 평균제곱오차가 예측능력을 측정하는 도구로 사용되었다. 본 논문의 근적외선 분광데이터 분석에 따르면 부분최소자승회귀법이 선형경향을 가진 데이터의 예측에 가장 적합한 모델로 판명되었다.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.253-263
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• 2018

Internet addiction in adolescents is an important social issue. In this study, sparse partial least-squares regression (SPLS) was applied to internet addiction data in Korean adolescent samples. The internet addiction score and various clinical and psychopathological features were collected and analyzed from self-reported questionnaires. We considered three PLS methods and compared the performance in terms of prediction and sparsity. We found that the SPLS method with the hierarchical likelihood penalty was the best; in addition, two aggression features, AQ and BSAS, are important to discriminate and explain latent features of the SPLS model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.89-96
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• 2012

The Falling Weight Deflectormeter has been widely used in evaluating the structural adequacy of pavement structures. The deflections measured from the FWD are capable of estimating the stiffness of pavement layers and measuring the pavement responses in the pavement structure. The objective of paper is to develop the pavement response model using a partial least square regression technique based on the FWD deflection data. The partial least square regression method enables to solve the multicollinearity problem occurred in multiple regression model. It is also found that the pavement response model can be developed using the raw data when a partial least square regression was used.

• Journal of the Korean Wood Science and Technology
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• v.49 no.3
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• pp.213-225
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• 2021

In this paper, we investigated the carbonization characteristics of lignin hydrochar prepared by hydrothermal carbonization and established a model for predicting the carbonization degree using near-infrared spectroscopy and partial least squares regression. The carbon content of the hydrothermally carbonized lignin at the temperature of 200 ℃ was higher by approximately 3 wt% than that of the untreated sample, and the carbon content tended to gradually increase as the heating time increased. Hydrothermal carbonization made lignin more carbon-intensive and more homogeneous by eliminating the microparticles. The discriminant and predictive models using near-infrared spectroscopy and partial least squares regression approppriately determined whether hydrothermal carbonization has been applied and predicted the carbon content of hydrothermal carbonized lignin with high accuracy. In this study, we confirmed that we can quickly and nondestructively predict the carbonization characteristics of lignin hydrochar manufactured by hydrothermal carbonization using a partial least squares regression model combined with near-infrared spectroscopy.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.805-836
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• 2017

China has become the group of two (G2) in almost fields including the scientific technology following the economic growth and joining the WTO in 2001. The main reason is that the government had strong intention for the industrialization of the scientific technology and connected the scientific technology and the economy. Typically, for analyzing the cause of the meteoric rise of China, the competitiveness of the scientific technology was analyzed by the entire score of the nation. However, in the case of China, there are differences in the pattern of the development between the eastern, central, and western province. Also, the industrialization and the competitiveness of the scientific technology are difference because each province established the decentralization of power. Therefore, it is more meaningful to analyze the main factors of Chinese economic growth on a province unit. In this study, therefore, we analyzed the competitive of R&D in China by 124 indexes in 31 areas. The data was analyzed by Partial least squares regression analysis. In conclusion, the scale of the area and the ability of R&D of the company are very important factors for total amount of production in the area. And the journals, patents, the transfer of technical know-how and the investment of R&D are main factors of the amount of export on the high-tech product. According to these results, the factors which make the difference in the industrialization and the competitiveness of the scientific technology in China were analyzed. Finally, it will be helpful to establish the policy for the development of the industrialization and the scientific technology in Korea.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1075-1083
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• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.

• Journal of the Korean Chemical Society
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• v.49 no.6
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• pp.531-536
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• 2005

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.513-525
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• 2020

Purpose: The purpose of this study is to analyze the characteristics of local factors affecting number of tuberculosis death by urban and rural areas. Method: The Partial Least Square(PLS) Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The number of tuberculosis deaths in urban and rural areas is about three times as large. As a result of analysis about Regional Characteristics Factor, In general, children, elderly people, and economically vulnerable populations are more likely to be exposed to tuberculosis. In differential results, it shows that environmental factors such as ultrafine dust and sulfur dioxide have a significant impact on the number of tuberculosis deaths in urban areas and social factors such as depression experience rate in rural areas. Conclusion: The Tuberculosis prevention and management policies that reflect the characteristics of urban and rural areas are needed in the future.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.672-686
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• 2022

Purpose: This study derived the planning factors affecting the evacuation route of facilities for the disabled and to identify the planning factors that affect each facility. Method: The PLS(Partial Least Square)Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The most important planning elements for each facility were derived as door: closing time (1.131), corridor: ramp for wheelchairs (1.227), stairs: emergency lighting for stairs (1.117), and evacuation space: evacuation space convenience facilities (1.106). Conclusion: In order to plan an effective evacuation route for the disabled, a universal design should be applied to consider the perception, needs, and satisfaction of the disabled, rather than a comprehensive reflection.