• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.449-461
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• 2016

If students are not aware of the information security, they easily let others know their information or they use others' information with no sense of guilt. The information security education is necessary to protect and prevent students from cyber crime. However, South Korea's information curriculum has no specific information security education course and it has led a school or teacher to teach contents of information ethics superficially. The purpose of this paper is to find the factors affecting the information security practice of the elementary school students. For an empirical analysis, questionnaire survey was conducted and the Partial Least Square(PLS) was used to analyze the research model. The analysis results show that the information ethics awareness and the information security awareness have a positive impact on the information security practice. The results of this study are expected to help choose the specific information security curriculum required for the information security practice of elementary school students.

• Journal of dental hygiene science
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• v.15 no.6
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• pp.807-814
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• 2015

The purpose of this study is to create a hypothetical model that explains and predicts oral health promotion behavior of adolescents by reviewing preceding literature on Pender's Health Promotion Model, and to verify the model's validity and proposed hypothesis through PLS (partial least square) structural equation model analysis. This study was cross-sectional survey consisted of self-administration questionnaires. The subjects in this study were a total of 293 alternative high school students in Jeollabuk-do Province. They were selected by convenience sampling. In alternative high school students, perceived benefit, locus of control, self-efficacy, and self-esteem had an effect on their oral health promoting behavior. As a result of the indirect effects in black is subjectively good subjective oral health, oral health related behaviors well past the more oral health promotion behavior showed a high. The prediction model of oral health promotion for adolescences, which was made using Pender's Health Promotion Model, was considered to be useful in explaining and predicting alternative high school students oral health promotion behavior.

• Journal of Information Management
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• v.42 no.1
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• pp.137-156
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• 2011

In this paper, our goal is to examine the factors of user's satisfaction and information sharing in Social Network Services(SNS). Based on the theoretical framework like attachment theory and self-presentation theory, we develop and test a theoretical model, propose hypotheses and analyze the effects of emotional attachment and self-presentation on the satisfaction and information sharing of SNS users. For this research, questionnaire survey was conducted with literature study and the PLS(Partial Least Square) was used to analyze the measurement model and hypotheses testing. The PLS analysis results indicate that emotional attachment affects SNS users' satisfaction and information sharing. Further, information sharing is influenced by self-presentation of SNS users. Practical implications of these findings and future research implications are also discussed.

• Animal Bioscience
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• v.37 no.5
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• pp.918-928
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• 2024

Objective: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Methods: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. Results: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R² >0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). Conclusion: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1625-1625
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• 2001

The calibration equations for Brix value determination of intact mango were developed using the NIR spectra in a short wavelength region from 700 to 1100 nm. Multiple linear regression (MLR) and partial least square regression (PLS) was used for the calibration. It was found that the best wavelength region for PLS calibration from 900 to 1000 nm was similar to the wavelength region selected by MLR from 906 nm to 996 nm. Both MLR and selected region PLS provided sufficiently accurate prediction equations for Brix determination of intact mango. For MLR, the prediction results were SEP = 0.45 Brix and Bias = -0.04 Brix while PLS prediction results were SEP : 0.46 Brix and Bias = -0.2 Brix. It was concluded that MLR and PLS would have similar abilities in making calibration equation for Brix determination of intact mango if the appropriate wavelengths or wavelength region were selected. The appropriate wavelength region for PLS regression could be assumed by using the wavelength region selected by MLR in place of random selection, The relationship between calibration results of MLR and PLS regression is discussed.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Korean Journal of Pharmacognosy
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• v.44 no.4
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• pp.332-335
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• 2013

Geographical classification of A. gigas was performed in the present study using UHPLC-DAD combined with multivariate data analysis techniques. Six active constituents were isolated from A. gigas; nodakenin, marmesin, decursinol, demethylsuberosin, decursin and decursinol angelate. One hundred sixty eight A. gigas samples were simultaneously determined using UHPLC-DAD. A principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) was used to classify the samples according to geographical origins (Korea and China). The origins of A. gigas from Korea and China were correctly classified by 81.6% and 93.8% using PLS-DA Y prediction. This result demonstrates the potential use of UHPLC-DAD combined with multivariate analysis techniques as an accurate and rapid method to classify A. gigas according to their geographical origin.

• 한국벤처창업학회:학술대회논문집
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• 2017.04a
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• pp.17-17
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• 2017

구조방정식모델(Structural Equation Modeling: SEM)은 변수들 간의 인관관계 및 상관관계를 검증하기 위한 통계기법으로 사회학 및 심리학 분야에서 개발되었지만 현재는 경영학, 광고학, 교육학, 생물학, 체육학, 의학, 정치학 등 여러 학문분야에서 광범위하게 사용되고 있다. Amos는 기본적으로 그래픽(Amos graphics)과 베이직(Amos basic)을 제공하기 때문에 정확한 프로그램의 작성이나 행렬에 대한 지식이 없는 초보자들도 아이콘을 이용하여 복잡한 연구모델이나 다중집단분석모델을 분석할 수 있다. PLS(Partial Least Square)는 모형 추정과정에서 발생하는 잔차 또는 예측오차를 최소화하여 예측력을 극대화하기 위한 프로그램이며, 즉, PLS-SEM는 표본 수가 적고 자료가 정규분포를 보이지 않거나 조형지표 모델이거나 복잡한 연구모델 분석에 유용하다. 최근 빅데이터의 열풍으로 자료들을 분석을 위한 도구로 R이 실무 현장에서 인기를 끌고 있다. R은 통계 프로그래밍 언어이자 오픈 소프트웨어 환경으로 통계, 그래픽, 데이터마이닝 등의 다양하고 방대한 양의 패키지들을 지원한다. R에서 제공되는 패키지들이 오픈 소스이고 선형 및 비선형 모델링, 고전적인 통계분석, 시 계열 분석, 분류 및 군집분석 등의 다양한 통계 패키지들을 제공한다는 측면에서 R은 실무는 물론 학문적인 측면에서도, 특히 통계를 기반으로 실증분석을 수행하는 사회과학연구들에서 중요한 역할을 할 수 있을 것으로 기대된다.

• Journal of Hydrogen and New Energy
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• v.25 no.5
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• pp.491-499
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• 2014

It is important to accurately measure and control the relative humidity of humidified gas entering a PEM (polymer electrolyte membrane) fuel cell stack because the level of humidification strongly affects the performance and durability of the stack. Humidity measurement devices can be used to directly measure the relative humidity, but they cost much to be equipped and occupy spaces in a fuel cell system. We present soft sensors for predicting the relative humidity without actual humidity measuring devices. By combining FIR (finite impulse response) model with PLS (partial least square) and SVM (support vector machine) regression models, DPLS (dynamic PLS) and DSVM (dynamic SVM) soft sensors were developed to correctly estimate the relative humidity of humidified gases exiting a planar-type membrane humidifier. The DSVM soft sensor showed a better prediction performance than the DPLS one because it is able to capture nonlinear correlations between the relative humidity and the input data of the soft sensors. Without actual humidity sensors, the soft sensors presented in this work can be used to monitor and control the humidity in operation of PEM fuel cell systems.

• Analytical Science and Technology
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• v.25 no.4
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• pp.214-222
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• 2012

ASTM (American Society for Testing and Materials) D6751-10 suggests analytical methods as well as specifications for biodiesel quality. However, it is expensive and time-consuming to follow the ASTM testing methods to analyze biodiesel and various impurities. This paper develops a quantitative analysis system for biodiesel and impurities based on Infrared spectroscopy and a multivariate statistical method, PLS (partial least squares). In addition, four different pre-processing techniques were compared for spectrum correction and noise reduction. Savitzky-Golay pre-processing showed the best performance.