• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.87-92
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• 2007

Recently, developments of process monitoring system in order to detect and diagnose process abnormalities has got the spotlight in process systems engineering. Normal data obtained from processes provide available information of process characteristics to be used for modeling, monitoring, and control. Since modern chemical and environmental processes have high dimensionality, strong correlation, severe dynamics and nonlinearity, it is not easy to analyze a process through model-based approach. To overcome limitations of model-based approach, lots of system engineers and academic researchers have focused on statistical approach combined with multivariable analysis such as principal component analysis (PCA), partial least squares (PLS), and so on. Several multivariate analysis methods have been modified to apply it to a chemical process with specific characteristics such as dynamics, nonlinearity, and so on.This paper discusses about missing value estimation and sensor fault identification based on process variable reconstruction using dynamic PCA and canonical variate analysis.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.153-165
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• 2012

The purpose of this study is to analyze the acceptance about new seed of Chinese cabbage and to analyze the factors affecting continuous use. Research model was derived based on the Technology Acceptance Model(TAM), the analysis was performed using Partial Least Squares(PLS). The factors significantly affecting the use of new seed of Chinese cabbage are innovativeness and seed promotion in antecedent variables and perceived usefulness in parameter variables, which have strong positive relationship among them. Therefore, efforts such as development and diffusion of high quality seed and securing a market for Chinese cabbage of new seed are necessary for improving perceived usefulness. Since these efforts including seed promotion can enhance the farmers' acceptance of new seed and reduce the risk that farmers would face in introducing new seed, these can also be very helpful in enhancing the farmers' innovativeness.

• Knowledge Management Research
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• v.22 no.2
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• pp.269-288
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• 2021

In a rapidly changing corporate environment, the relationship among organizational justice, job attitude, and cynicism as factors influencing exit, voice, loyalty, and neglect that can promote the performance improvement of organizational members was analyzed with the PLS (Partial Least Squares) structural equation in two stage approach. Organizational justice constitutes a formative secondary factor by the first order of distributional justice, procedural justice, and interactional justice, and job attitude is a formative secondary factor of job satisfaction and organizational commitment. We analyze the direct and indirect effects by mediating relationships of cynicism and job attitude on the factors such as exit, voice, loyalty, and neglect. From the perspectives of knowledge management, we analyzed how the perception of organizational justice affects the overall performance of the organization through the improvement of the employees' performance.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.335-340
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• 2004

This study was conducted to evaluate the internal quality of Korean red ginseng using VIS/NIR transmittance spectra. To classify the internal qualities, partial least squares(PLS) regression was conducted. The main results are as follows: To develop the PLS model, several wave bands were divided and incorporated into the model. Among the bands, the wavelength range of 550-1,020nm, excluded noise signal, showed the best evaluation results. Effect of step size on the performance of quality evaluation showed optimal at 15 steps. In order to enhance the accuracy of quality evaluation, the abnormal spectrum shape was considered first and then the PLS model was applied. Among the 150 samples, 12 samples were evaluated by the spectrum shape. In this study, to develop the optimal PLS regression model, among the 150 samples, 138 samples was used with exception of 12 samples which could evaluate the spectrum shape. The result of quality evaluation was promising as SEC and correlation coefficient were 1.09 and 0.967, respectively, and SEP and correlation coefficient were 1.04 and 0.958, respectively.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.145-156
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• 2021

Forest fires have frequently occurred around the world, and the damages are increasing. In Korea, most forest fires are initiated by human activities, but climate factors such as temperature, humidity, and wind speed have a great impact on combustion environment of forest fires. In this study, therefore, based on statistics of forest fires in Gyeonggi-do over the past five years, meteorological and hydrological factors (i.e., temperature, humidity, wind speed, precipitation, and drought) were selected in order to quantitatively investigate causal relationships with forest fire. We applied a partial least squares structural equation model (PLS-SEM), which is suitable for analyzing causality and predicting latent variables. The overall results indicated that the measurement and structural models of the PLS-SEM were statistically significant for all evaluation criteria, and meteorological factors such as humidity, temperature, and wind speed affected by amount of -0.42, 0.23 and 0.15 of standardized path coefficient, respectively, on forest fires, whereas hydrological factor such as drought had an effect of 0.23 on forest fires. Therefore, as a practical method, the suggested model can be used for analyzing and evaluating influencing factors of forest fire and also for planning response and preparation of forest fire disasters.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.295-298
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• 1996

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.533-538
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• 2007

Since the Internet has been widespread all over the world, it has been getting more popular. Almost every bank that runs offline business has its own Web site to provide online banking service. In this study, we developed a research model based on the Technology Acceptance Model (TAM). We added the concepts of trust and cost to evaluate our model because trust is a major concept in adopting online service, and cost is one of the main strategies to attract customers to use online banking service. To see the validation of the model, we used partial least squares (PLS). A survey was done to gather data. The result was drawn from the model test, and we discuss it and conclude the study.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.63-68
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• 2008

This study was carried out to find a useful method to predict hardness of tomato using optical spectrum data. Optical spectrum of reflectance and transmittance data were collected processed by 9 kind of preprocessing methods-normalizations of mean, maximum and range, SNV (standard normal variate), MSC (multiplicative scatter correction), the first derivative and second derivative of Savitzky-Golay and Norris-Gap. With the preprocessed and non-processed original spectrum data, prediction models of hardness of tomato were developed using analytical tools of PLS (partial least squares) and MLR (multiple linear regression) and tested for their validation. The test of validation resulted that the analytical tools of PLS and MLR output similar performances while the transmittance spectra showed much better result than the reflectance spectra.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06a
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• pp.167-172
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• 2006

High-yield Pinus radiate kraft pulps with various Kappa number were produced from flow-through laboratory pulping. The samples were prepared and scanned using a rapid scan photoacoustic Fourier transform infrared (PAS-FTIR) spectrometer. A partial-least-squares (PLS) model was established based on the spectral data collected at different mirror velocities. The model was used to predict the Kappa number of the pulps and its robustness was statistically evaluated. The outcomes indicate that the PLS model can be used to predict the Kappa number of Pinus radiata kraft pulps with a high degree of accuracy provided that the moving mirror velocity is ${\leq}\;0.5cm/s$.

• Environmental Engineering Research
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• v.10 no.2
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• pp.88-103
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• 2005

In this paper, data-driven modeling and multiresolution analysis (MRA) are applied for a full-scale wastewater treatment plant (WWTP). The proposed method is based on modeling by partial least squares (PLS) and multiscale monitoring by a generic dissimilarity measure (GDM), which is suitable for nonstationary and non-normal process monitoring such as a biological process. Case study in an industrial plant showed that the PLS model could give good modeling performance and analyze the dynamics of a complex plant and MRA was useful to detect and isolate various faults due to its multiscale nature. The proposed method enables us to show the underlying phenomena as well as to filter out unwanted and disturbing phenomena.