• Korean Chemical Engineering Research
• /
• v.45 no.1
• /
• pp.67-72
• /
• 2007

An efficient method for identification of MIMO state space model has been developed by combining partial least squares (PLS) regression, balanced realization, and balanced truncation. In the developed method, a MIMO system is decomposed into multiple MISO systems each of which is represented by a high-order ARX model and the parameters of the ARX models are estimated by PLS. Then, MISO state space models for respective MISO ARX transfer function are found through realization and combined to a MIMO state space model. Finally, a minimal balanced MIMO state space model is obtained through balanced realization and truncation. The proposed method was applied to the design of model predictive control for temperature control of a high pressure $CO_2$ solubility measurement system.

• Clean Technology
• /
• v.18 no.1
• /
• pp.31-37
• /
• 2012

Biomass has become a major feedstock for bioenergy and other bio-based products because of its renewability and environmental benefits. Various researches have been done in the prediction of crucial characteristics of biomass, including the active utilization of spectroscopy data. Near infrared (NIR) spectroscopy has been widely used because of its attractive features: it's non-destructive and cost-effective producing fast and reliable analysis results. This work developed the multivariate statistical scheme for predicting weight loss profiles based on the utilization of NIR spectra data measured for six lignocellulosic biomass types. Wavelet analysis was used as a compression tool to suppress irrelevant noise and to select features or wavelengths that better explain NIR data. The developed scheme was demonstrated using real NIR data sets, in which different prediction models were evaluated in terms of prediction performance. In addition, the benefits of using right pretreatment of NIR spectra were also given. In our case, it turned out that compression of high-dimensional NIR spectra by wavelet and then PLS modeling yielded more reliable prediction results without handling full set of noisy data. This work showed that the developed scheme can be easily applied for rapid analysis of biomass.

• Management & Information Systems Review
• /
• v.31 no.3
• /
• pp.141-160
• /
• 2012

This study investigate the relationship between embeddedness of supply chain on supply chain performance. The development of research model is based on network embeddedness that the literature of strategic management and sociology. To examine the research model and hypotheses, we have used an empirical method based on field survey in which most of measurements used and verified in previous studies are selected as measurements. The data from survey was analyzed using Partial Least Squares(PLS). The result from empirical model suggest as follow; First, relational embeddedness of supply chain effects on supply chain performance. Especially, reciprocal dependance affects interfirm relation performance. Also trust and tie strength of relational embeddedness affects interfirm relation performance. Second, interfirm relation performance affects financial performance.

• Journal of Korea Port Economic Association
• /
• v.35 no.3
• /
• pp.109-124
• /
• 2019

Corporate social responsibility (CSR) is gaining significance in various industries and academic research. However, shipping companies have a relatively less interest in CSR. Considering the International Maritime Organisation's (IMO) 2020 model and its focus on sustainability, it is time for shipping companies to consider the active use of CSR initiatives. This study aims to examine the leading factors influencing CSR implementation and job satisfaction. The analysis was conducted using partial least squares and statistical package for social sciences 18.0 to achieve the research objectives. The results showed that the internal and external factors of shipping companies play a positive role in CSR implementation, which was found to play a positive role in enhancing job satisfaction. The implications of this study are to identify factors that drive shipping companies to improve their CSR performance.

• Journal of Digital Convergence
• /
• v.13 no.5
• /
• pp.151-158
• /
• 2015

The purpose of this study to understand collaborative process and the capabilities of the firm impact on innovation performance in convergence environment. To achieve the purpose, research model was empirically tested with a survey from 162 employees from 4 Korea manufacturing companies and 1 USA company. The data obtained from the survey were analyzed using Partial Least Squares (PLS). As a result, collaboration process, learning capability and operation capability have significant and positive impact on innovation performance. It is a meaningful result that the collaboration process improve the innovation performance of firms through the operation capability and the learning capability.

• Journal of Digital Convergence
• /
• v.18 no.7
• /
• pp.149-156
• /
• 2020

This study investigated the key factors affecting online relational intimacy in the context of SNS. Based on the use and gratification theory, self-presentation, relationship formation and information searching were identified as the main needs of SNS usage. These needs were expected to influence online relational intimacy through user satisfaction, subjective well-being, and disclosing information behaviors. The theoretical framework was validated by a longitudinal method. Hypotheses were tested by using the partial least squares to data from 199 Facebook users. Self-presentation and information searching had a significant impact on both user satisfaction and subjective well-being. However, relationship formation did not significantly affect both user satisfaction and subjective well-being. User satisfaction had a significant direct effect only on online relational intimacy. Subjective well-beings played a significant role in enhancing both disclosing information behaviors and online relational intimacy. Finally, it has been found that disclosing information behaviors are a key factor in enhancing online relational intimacy. The results of this study are expected to provide academic and practical implications for the key antecedents of online relational intimacy.

• Korean Journal of Agricultural Science
• /
• v.47 no.3
• /
• pp.645-655
• /
• 2020

Bacteria are a very common cause of food poisoning. Moreover, bacteria form biofilms to protect themselves from harsh environments. Conventional detection methods for foodborne bacterial pathogens including the plate count method, enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) assays require a lot of time and effort. Hyperspectral imaging has been used for food safety because of its non-destructive and real-time detection capability. This study assessed the feasibility of using hyperspectral imaging and machine learning techniques to detect biofilms formed by Escherichia coli. E. coli was cultured on a high-density polyethylene (HDPE) coupon, which is a main material of food processing facilities. Hyperspectral fluorescence images were acquired from 420 to 730 nm and analyzed by a single wavelength method and machine learning techniques to determine whether an E. coli culture was present. The prediction accuracy of a biofilm by the single wavelength method was 84.69%. The prediction accuracy by the machine learning techniques were 87.49, 91.16, 86.61, and 86.80% for decision tree (DT), k-nearest neighbor (k-NN), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA), respectively. This result shows the possibility of using machine learning techniques, especially the k-NN model, to effectively detect bacterial pathogens and confirm food poisoning through hyperspectral images.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.2
• /
• pp.187-195
• /
• 2015

In this paper, we examined the effect of positive affect and negative affect on the life satisfaction in the workplace. Also, this study focused on an empirical test of the role of work self-efficacy and work meaningfulness in the subjective well-being of office worker. To achieve this purpose, we suggested a research model consisting of factors such as work self-efficacy, work meaningfulness, positive affect, negative affect, life satisfaction. Data was collected using the survey method, and analyzed using structural equation model. According to PLS analysis, first, lower negative affect was associated with higher life satisfaction. Secondly, work meaningfulness was a very important predictor for the subjective well-being of office worker.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.57 no.1
• /
• pp.29-34
• /
• 2012

The objective of this study was to rapidly evaluate fatty acids in a collection of millet (Panicum miliaceum subsp. miliaceum) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour ($n$=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.89, 0.89, 0.89, and 0.92 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2$=0.64, 0.90, 0.79, and 0.89 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). Standard deviation/standard errors of cross-validation (SD/SECV) values were close to 3 (2.62, 2.40, 1.85, and 2.23 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic and total fatty acids characterizing millet germplasm. Among the samples, IT153514 showed an especially high content of fatty acids ($48.14mg\;g^{-1}$), whereas IT123909 had a very low content ($34.44mg\;g^{-1}$).

• Analytical Science and Technology
• /
• v.11 no.1
• /
• pp.47-53
• /
• 1998

This study is to improve the diagnosis of diabetes mellitus and the self-monitoring of blood glucose in people with diabetes by providing a non-invasive method of monitoring blood glucose. A near-infrared (NIR) spectrophotometer was used to measure absorption spectra of 80 glucose samples ranges from 1 mg/dL to 200 mg/dL, and shows the standard error of prediction 1.8 mg/dL. Also, to investigate the effect of interference in blood, NaCl and sand were added in glucose and found the standard error of prediction of 2.8 mg/dL and 3.8 mg/dL, respectively. A new and more accurate calibration system for the spectrophotometer was developed from systematic study of light scattering, which cause nonlinear spectrophotometer response.