• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.681-692
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• 2018

This study was performed to select the significant wavelengths for predicting the chlorophyll content of grafted cucumber seedlings using hyperspectral images. The visible and near-infrared (VNIR) images and the short-wave infrared images of cucumber cotyledon samples were measured by two hyperspectral cameras. A correlation coefficient spectrum (CCS), a stepwise multiple linear regression (SMLR), and partial least squares (PLS) regression were used to determine significant wavelengths. Some wavelengths at 501, 505, 510, 543, 548, 619, 718, 723, and 727 nm were selected by CCS, SMLR, and PLS as significant wavelengths for estimating chlorophyll content. The results from the calibration models built by SMLR and PLS showed fair relationship between measured and predicted chlorophyll concentration. It was concluded that the hyperspectral imaging technique in the VNIR region is suggested effective for estimating the chlorophyll content of grafted cucumber leaves, non-destructively.

• Journal of the Korean Society of Tobacco Science
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• v.35 no.1
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• pp.20-27
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• 2013

An Electronic Nose(E-Nose) and Gas Chromatography/Mass Spectroscopy (GC/MS) are meanwhile conventional technique to analyze volatile materials in many industries (e.g., food, medicine, environment) and have broad acceptance in the analysis of tobacco products. In this study, an experiment where tin oxide gas sensor array responses and GC/MS profiles are used to characterize the volatile compounds of different cigarettes at the same time is performed and the measurements of two instruments are compared for cigarette samples with a known chemical information. E-Nose and GC/MS were employed to differentiate and match flavored cigarettes with commercial tobacco flavoring agents (lavender, vanilla, peppermint, orange, star anise). For verifying reliability of two systems, the analyses were conducted in terms of amount of flavors in each cigarettes using partial least squares (PLS) and with the principal components analysis (PCA). Various chemical sensors and GC/MS data was reduced into two principal factors (PC1, PC2) for being distinguished with visualized regions. Both systems provided adequate results for odor characteristics of cigarettes in this study with each instrument having its own advantages and disadvantages.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.209-219
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• 2019

This study analyzed the impacts and factors of the government's local industry upbringing policy on business growth. We analyzed the effect of product innovation and technological innovation on business competence, external cooperation level, R&D investment, and corporate growth using PLS(Partial Least Squares) structural equation. The results show that management competence and external cooperation level have a significant effect on firm growth and that there is a moderating effect between beneficiaries and non-beneficiaries. Management competence affects product innovation. Product innovation was analyzed to have mediating effects on firm growth. Finally, the policy direction of increasing managerial capacity is presented, and the limitations and future research directions are suggested.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.139-148
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• 2013

With the launch of Apple iPhone, platform and contents and design characteristics were highlights of the new factors. In addition, Smartphone users have increased explosively. In this research, we aim to analyze factors affecting on repurchase intention of a Smartphone based on Technology Acceptance Model(TAM). External factors such as platform, contents and design are identified through literature review and the influences of these factors on repurchase intention are assessed. A questionnaire survey was conducted to those who lived in Busan and Gyeongnam province. This research used Smart PLS(partial least squares) to analyze the structural relationship between those factors and repurchase intention. Analytical results show that all paths except path from platform to perceived ease of use are significant. This study suggests practical and theoretical implications based on the results.

• Information Systems Review
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• v.25 no.2
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• pp.163-180
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• 2023

Based on the Technology-Organization-Environment (TOE) model, this study proposed a research model that explains the continuance intention of users in the with Covid-19 era considering the technical, organizational, and environmental aspects of Remote Work Solution (RWS). To verify the research model and hypothesis, an online survey was conducted on domestic RWS users. Partial least squares (PLS) were utilized to analyze the collected 411 data. As a result of the analysis, it was found that functionality and security level had positive impacts on both productivity improvement and satisfaction. However, it was also confirmed that organizational readiness had a positive effect on productivity improvement but did not affect satisfaction. Furthermore, the results revealed that government support had a positive relationship with continuance intention, but the health concerns did not. Finally, the correlations between productivity improvement, satisfaction, and continuous intention were confirmed to be significant. Therefore, 9 out of a total of 11 hypotheses were supported.

• Journal of Korean Critical Care Nursing
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• v.17 no.1
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• pp.30-43
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• 2024

Purpose : Post-intensive care syndrome (PICS) is characterized by a constellation of mental health, physical, and cognitive impairments, and is recognized as a long-term sequela among survivors of intensive care units (ICUs). The objective of this study was to explore the impact of intensive care experience (ICE) on the development of PICS in individuals surviving critical care. Methods : This secondary analysis utilized data derived from a prospective, multicenter cohort study of ICU survivors. The cohort comprised 143 survivors who were enrolled between July and August 2019. The original study's participants completed the Korean version of the ICE questionnaire (K-ICEQ) within one week following discharge from the ICU. Of these, 82 individuals completed the PICS questionnaire (PICSQ) three months subsequent to discharge from hospital. The influence of ICE on the manifestation of PICS was examined through Partial Least Squares-Structural Equation Modeling (PLS-SEM). Result : The R² values of the final model ranged from 0.35 to 0.51, while the Q² values were all greater than 0, indicating adequacy for prediction of PICS. Notable pathways in the relationship between the four ICE dimensions and the three PICS domains included significant associations from 'ICE-awareness of surroundings' to 'PICS-cognitive', from 'ICE-recall of experience' to 'PICS-cognitive', and from 'ICE-frightening experiences' to 'PICS-mental health'. Analysis found no significant moderating effects of age or disease severity on these relationships. Additionally, gender differences were identified in the significant pathways within the model. Conclusion : Adverse ICU experiences may detrimentally impact the cognitive and mental health domains of PICS following discharge. In order to improve long-term outcomes of individuals who survive critical care, it is imperative to develop nursing interventions aimed at enhancing the ICU experience for patients.

• Journal of the Korean Wood Science and Technology
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• v.44 no.6
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2076-2082
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• 2017

Users of Smartphone in Korea are using the majority of the economically active population over 99% and experts have seen that they have reached saturation after the initial formation stages. The purpose of this study is to investigate the influencing factors of dominant design attributes on the intention of continuous use of Smartphone users. Predictor factors were selected perceived usefulness and perceived ease of use suggested on extended the technology acceptance model. The concept model was completed by selecting the dominant design attribute as a mediator. Participants of this study were 135 Smartphone users in Busan Gyeongnam and Iksan Jeonbuk province in accordance with convenience sampling. IBM SPSS Statistics 19 were employed for descriptive statistics, Smart PLS (partial least squares) was employed for confirmatory factor analysis and path analysis of casual relationship among variables. Therefore, when moderating mediated factor of dominant design and attitude, factor of continuous usage intention showed 76% explanatory power.