• Title/Summary/Keyword: PLS analysis

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Non-linear PLS based on non-linear principal component analysis and neural network (비선형 주성분해석과 신경망에 기반한 비선형 PLS)

  • 손정현;정신호;송상옥;윤인섭
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.394-394
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    • 2000
  • This Paper proposes a new nonlinear partial least square method that extends the linear PLS. Proposed nonlinear PLS uses self-organizing feature map as PLS outer relation and multilayer neural network as PLS inner regression method.

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Loss Analysis of Pulse Type Inverter Circuit for PLS (PLS용 펄스형 인버터 회로의 손실분석)

  • Jung, Yong-Chae;Jung, Yun-Chul
    • The Transactions of the Korean Institute of Power Electronics
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    • v.11 no.6
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    • pp.489-493
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    • 2006
  • The aim of the paper is to design the PLS(Plasma Lighting System) driving inverter circuit with optimal efficiency. In general, it is known that the PLS driven by a pulse has a higher light-conversion efficiency. There are the Class-E type resonant inverter and the semi-bridge inverter as a circuit which can make a pulse with low duty ratio. In this paper, we analyze the losses of the above two circuits. To verify the loss analysis, the inverter circuit with 220V 380W input consumption is manufactured and tested. Throughout the experimental results, the high efficiency PLS system has confirmed.

A Tutorial on PLS Structural Equating Modeling using R: (Centering on) Exemplified Research Model and Data (R을 이용한 PLS 구조방정식모형 분석 튜토리얼: 예시 연구모형 및 데이터를 중심으로)

  • Yoon, Cheolho;Kim, Sanghoon
    • Information Systems Review
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    • v.16 no.3
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    • pp.89-112
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    • 2014
  • This tutorial presents an approach to perform the PLS structural equation modeling using the R. For this purpose, the practical guide defines the criteria for the PLS structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "plspm" which is the R package for the performing PLS path analysis against the criteria. This practical guide will be useful for the study of the PLS model analysis for new researchers and will provide the knowledge base for in-depth analysis through the new PLS structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the PLS structural equation modeling.

Phospholipid Analysis by Nanoflow Liquid Chromatography-Tandem Mass Spectrometry

  • Moon, Myeong Hee
    • Mass Spectrometry Letters
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    • v.5 no.1
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    • pp.1-11
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    • 2014
  • Lipids play important roles in biological systems; they store energy, play a structural role in the cell membrane, and are involved in cell growth, signal transduction, and apoptosis. Phospholipids (PLs) in particular have received attention in the medical and lipidomics research fields because of their involvement in human diseases such as diabetes, obesity, atherosclerosis, and many cancers associated with lipid metabolic disorders. Here I review experimental strategies for PL analysis based on nanoflow liquid chromatography-electrospray ionization-tandem mass spectrometry (nLC-ESI-MSn). In particular, discussed are lipid extraction methods, nanoflow LC separation of PLs, effect of ionization modifiers on the ESI of PLs, influence of chain lengths and unsaturation degree of acyl chains of PLs on MS intensity, structural determination of the molecular structure of PLs and their oxidized products, and quantitative profiling of PLs from biological samples such as tissue, urine, and plasma in relation to cancer and coronary artery disease.

PLS Path Modeling to Investigate the Relations between Competencies of Data Scientist and Big Data Analysis Performance : Focused on Kaggle Platform (데이터 사이언티스트의 역량과 빅데이터 분석성과의 PLS 경로모형분석 : Kaggle 플랫폼을 중심으로)

  • Han, Gyeong Jin;Cho, Keuntae
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.2
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    • pp.112-121
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    • 2016
  • This paper focuses on competencies of data scientists and behavioral intention that affect big data analysis performance. This experiment examined nine core factors required by data scientists. In order to investigate this, we conducted a survey to gather data from 103 data scientists who participated in big data competition at Kaggle platform and used factor analysis and PLS-SEM for the analysis methods. The results show that some key competency factors have influential effect on the big data analysis performance. This study is to provide a new theoretical basis needed for relevant research by analyzing the structural relationship between the individual competencies and performance, and practically to identify the priorities of the core competencies that data scientists must have.

Prediction of Soluble Solid and Firmness in Apple by Reflectance Spectroscopy

  • Park, Chang-Hyun;Judith.A.Abbott
    • Near Infrared Analysis
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    • v.1 no.1
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    • pp.23-26
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    • 2000
  • The objectives of this study were to examine the ability to predict soluble solid and firmness in intact apple based on the visible/near-infrared spectroscopic technique. Two cultivars of apples, Delicious and Gala, were handled, tested and analyzed. Reflectance spectra, Magness-Taylor (MT) Firmness, and soluble solids in apples were measured sequentially. Maximum and minimum diameters, height, and weight of apples were recorded before the MT firmness tests. Apple samples were divided in to a calibration set and a validation set. The method of partial least squares (PLS) analysis was used. a unique set of PLS loading vectors (factors) was development for soluble solid and firmness. The PLS model showed good relationship between predicted and measured soluble solids in intact apples in the wavelength range of 860∼1078 nm. However, the PLS analysis was not good enough to predict the apple firmness.

The Structural Equation Modeling in MIS : The Perspectives of Lisrel and PLS Applications (경영정보학 분야의 구조방정식모형 적용분석 : Lisrel과 PLS 방법을 중심으로)

  • Kim, In-Jai;Min, Geum-Young;Shim, Hyoung-Seop
    • Journal of Information Technology Services
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    • v.10 no.2
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    • pp.203-221
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    • 2011
  • The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

Analysis of Success Factors for Mobile Commerce using Text Mining and PLS Regression

  • Kim, Yong-Hwan;Kim, Ja-Hee;Park, Ji hoon;Lee, Seung-Jun
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.11
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    • pp.127-134
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    • 2016
  • In this paper, we propose factors that influence on the mobile commerce satisfaction conducted by data mining and a PLS regression analysis. We extracted the most frequent words from mobile application reviews in which there are a large number of user's requests. We employed the content analysis to condense the large number of texts. We took a survey with the categories by which data are condensed and specified as factors that influence on the mobile commerce satisfaction. To avoid multicollinearity, we employed a PLS regression analysis instead of using a multiple regression analysis. Discovered factors that are potential consequences of customer satisfaction from direct requests by customers, the result may be an appropriate indicator for the mobile commerce market to improve its services.

A Comparison Analysis among Structural Equation Modeling (AMOS, LISREL and PLS) using the Same Data (동일 데이터를 이용한 구조방정식(AMOS, LISREL and PLS) 툴 간의 비교분석)

  • Nam, Soo-tai;Kim, Do-goan;Jin, Chan-yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.131-134
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    • 2018
  • Structural equation modeling is pointing to statistical procedures that simultaneously perform path analysis and confirmatory factor analysis. Today, this statistical procedure is an essential tool for researchers in the social sciences. There are as (AMOS, LISREL and PLS) representative tools that can perform structural equation modeling analysis. AMOS provides a convenient graphical user interface for beginners to use. PLS has the advantage of not having a constraint on normal distribution as well as a graphical user interface. Therefore, we compared and analyzed the three most commonly used tools in social sciences. This study suggests practical and theoretical implications based on the results.

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A Study on Factor Analytical Methods and Procedures for PLS-SEM (Partial Least Squares Structural Equation Modeling)

  • YIM, Myung-Seong
    • The Journal of Industrial Distribution & Business
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    • v.10 no.5
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    • pp.7-20
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    • 2019
  • Purpose - This study provides appropriate procedures for EFA to help researchers conduct empirical studies by using PLS-SEM. Research design, data, and methodology - This study addresses the absolute and relative sample size criteria, sampling adequacy, factor extraction models, factor rotation methods, the criterion for the number of factors to retain, interpretation of results, and reporting information. Results - The factor analysis procedure for PLS-SEM consists of the following five stages. First, it is important to look at whether both the Bartlett test of sphericity and the KMO MSA meet the qualitative criteria. Second, PAF is a better choice of methodology. Third, an oblique technique is a suitable method for PLS-SEM. Fourth, a combined approach is strongly recommended to factor retention. PA should be used at the onset. Next, it is recommended using the K1 criterion. In addition, it is necessary to extract factors that increase the total variance explanatory power through the PVA-FS. Finally, it is appropriate to select an item with a factor loading into 0.5 or higher and a communality of 0.5. Conclusions - It is expected that the accurate factor analysis processed for PLS-SEM as previously presented will help us extract more precise factors of the structural model.