• The Journal of Information Systems
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• v.21 no.1
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• pp.173-203
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• 2012

In this paper, we arrange the concept of 'Green' in SCM after literature study of Green SCM and investigate causal relationships between influencing factors, practice level and environmental performance focused on Korean firms empirically and conduct path analysis for hypothesis test using partial least squares regression with bootstrap. Firstly, we divide influencing factors of Green SCM into environmental and organizational factors through the previous studies of innovation diffusion theory and environmental management theory, and then we selected 'uncertainty', 'competitiveness' as the environmental factors and 'top management support', 'perceived benefit', 'training' as the organizational factors. Secondly, we classify practice level of Green SCM into 'internal environmental management', 'green purchasing', 'eco-design'. Finally, we selected 'financial performance', 'environmental performance' as the organizational performance. We conducted a survey on the middle manager of manufacturing companies implementing SCM and an empirical analysis. The results of analysis show that there exist causal relationships between influencing factors, practice level, and environmental performance of Green SCM. We expect that the result of this study will suggest useful information to managers who are responsible for SCM to design and execute Green SCM in strategic perspectives.

• YAKHAK HOEJI
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• v.47 no.6
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• pp.461-468
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• 2003

A method is described for measuring clinically relevant levels of glucose in a pH 7.4 phosphate buffer by nearinfrared (NIR) absorption spectroscopy. Three types of NIR spectrometer, dispersive type, photo-diode array (PDA) type, and fourier transform (FT) type spectrometer were used and the performance was compared. Spectra were collected with a cuvette cell or quartz liquid fiber of 1 mm or 2 mm optical pathlength as transmittance method. Glucose absorption band appeared at second overtone, first overtone, and combination region for all systems. By use of the multivariate technigue of partial least squares (PLS) regression, glucose concentrations can be determined with a 16, 44, and 9.1 mg/d l standard error of prediction for dispersive type, photo-diode array type, and fourier transform type system, respectively. Sensitivity of spectrometer was evaluated by absorbance for the difference of 10 mg/d l glucose. Three absorption bands, second overtone, first overtone, and combination region were suited to three types systems, dispersive type, photo-diode array type, and fourier transform type systems, respectively. This investigation showed that three types NIR spectrometer were proper method for identification and quantitative analysis of glucose and possible for noninvasive blood glucose monitoring.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.497-502
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• 2001

Influence of other blond components on measuring glucose concentration was analyzed B)food phantom containing five major components was made. The prediction model was developed based on the measurement of absorption spectra including the first overtone glucose band, i.e.. 1500 ∼ 1850 nm. The concentrations were Predicted using the Partial least squares regression. Factor analysis based on Design of Experiment was Performed to study the influence of other components in predicting glucose concentration. Triglyceride does not influence. Albumin and globulin haute minor effects. However, hemoglobin showed substantial response and the compensation of hemoglobin concentration appears to be required for the model of glucose measurement.

• 한국벤처창업학회:학술대회논문집
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• 2018.11a
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• pp.269-275
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• 2018

Electronic commerce, the act of trading online, with its myriad of potential has been seldom looked at within the context of developing countries. E-commerce presents SMEs in developing economies the opportunity to adequately compete on a global stage. The exponential growth of e-commerce in developed economies further widens the financial gap between developed and developing economies. This study looks at a practical e-commerce adoption framework for Ghanaian SMEs and by extension, developing economies and looks at the net benefits that are available to current adopters. The study uses structural equation modeling, using Partial least squares (PLS) regression to analyze the data in the research. Using PLS algorithms as well as bootstrapping calculations. It combines the use of surveys (154) and interviews (38) as means of data collection. The findings of the research indicate that there is a need for legislation on e-commerce trading to regulate the trade in Ghana, with policies such as e-contracting and e-signature laws among others. Also, a current call for an expansion of the mobile payment methods within the country. For the private investor, a ripe market for logistics services. The study also proposes a simple guideline for SMEs looking to adopt or expand their e-commerce usage, that considers technological, organizational and environmental factors that come to play within e-commerce adoption.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.73-78
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• 2022

The aim of this paper is to investigate the prevalence of Deep Learning in the literature on Fire & Rescue Service. It is found that deep learning techniques are only beginning to benefit the firefighters. The popular areas where deep learning techniques are making an impact are situational awareness, decision making, mental stress, injuries, well-being of the firefighter such as his sudden fall, inability to move and breathlessness, path planning by the firefighters while getting to an fire scene, wayfinding, tracking firefighters, firefighter physical fitness, employment, prediction of firefighter intervention, firefighter operations such as object recognition in smoky areas, firefighter efficacy, smart firefighting using edge computing, firefighting in teams, and firefighter clothing and safety. The techniques that were found applied in firefighting were Deep learning, Traditional K-Means clustering with engineered time and frequency domain features, Convolutional autoencoders, Long Short-Term Memory (LSTM), Deep Neural Networks, Simulation, VR, ANN, Deep Q Learning, Deep learning based on conditional generative adversarial networks, Decision Trees, Kalman Filters, Computational models, Partial Least Squares, Logistic Regression, Random Forest, Edge computing, C5 Decision Tree, Restricted Boltzmann Machine, Reinforcement Learning, and Recurrent LSTM. The literature review is centered on Firefighters/firemen not involved in wildland fires. The focus was also not on the fire itself. It must also be noted that several deep learning techniques such as CNN were mostly used in fire behavior, fire imaging and identification as well. Those papers that deal with fire behavior were also not part of this literature review.

• Food Science and Preservation
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• v.30 no.2
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• pp.224-234
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• 2023

We analyzed the major quality characteristics of red pepper powders from various regions and predicted these characteristics nondestructively using shortwave infrared hyperspectral imaging (HSI) technology. We conducted partial least squares regression analysis on 70% (n=71) of the acquired hyperspectral data of the red pepper powders to examine the major quality characteristics. R_c² values of ≥0.8 were obtained for the ASTA color value (0.9263) and capsaicinoid content (0.8310). The developed quality prediction model was validated using the remaining 30% (n=35) of the hyperspectral data; the highest accuracy was achieved for the ASTA color value (R_p²=0.8488), and similar validity levels were achieved for the capsaicinoid and moisture contents. To increase the accuracy of the quality prediction model, we conducted spectrum preprocessing using SNV, MSC, SG-1, and SG-2, and the model's accuracy was verified. The results indicated that the accuracy of the model was most significantly improved by the MSC method, and the prediction accuracy for the ASTA color value was the highest for all the spectrum preprocessing methods. Our findings suggest that the quality characteristics of red pepper powders, even powders that do not conform to specific variables such as particle size and moisture content, can be predicted via HSI.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1075-1083
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• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.

• 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 Biosystems Engineering
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• v.36 no.1
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• pp.33-39
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• 2011

An optical sensing approach based on diffuse reflectance has shown potential for rapid and reliable on-site estimation of soil properties. Important sensing ranges and the resulting regression models useful for soil property estimation have been reported. In this study, a similar approach was applied to investigate the potential of reflectance sensing in estimating soil properties for Korean paddy fields. Soil cores up to a 65-cm depth were collected from 42 paddy fields representing 14 distinct soil series that account for 74% of the total Korean paddy field area. These were analyzed in the laboratory for several important physical and chemical properties. Using air-dried, sieved soil samples, reflectance data were obtained from 350 to 2500 nm on a 3 nm sampling interval with a laboratory spectrometer. Calibrations were developed using partial least squares (PLS) regression, and wavelength bands important for estimating the measured soil properties were identified. PLS regression provided good estimations of Mg ($R^2$ = 0.80), Ca ($R^2$ = 0.77), and total C ($R^2$ = 0.92); fair estimations of pH, EC, $P_2O_5$, K, Na, sand, silt, and clay ($R^2$ = 0.59 to 0.72); and poor estimation of total N. Many wavelengths selected for estimation of the soil properties were identical or similar for multiple soil properties. More important wavelengths were selected in the visible-short NIR range (350-1000 nm) and the long NIR range (1800-2500 nm) than in the intermediate NIR range (1000-1800 nm). These results will be useful for design and application of in-situ close range sensors for paddy field soil properties.

• Journal of Environmental Science International
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• v.33 no.3
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• pp.193-203
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• 2024

This study aims to determine the factors affecting the level of satisfaction with the Cell Broadcast Service (CBS) among citizens in Incheon. Partial least squares (PLS) regression, instead of multiple regression, was used for the analysis because it can solve multicollinearity and sample size issues. The analysis results are as follows: The factor with the greatest effect on satisfaction with CBS among Incheon citizens, was the elimination of redundancies (VIP=1.185). Therefore, local governments, government agencies, and public organizations must coordinate their ideas and collectively create guidelines to eliminate redundancies. The second most influential factor was the expansion in the broadcast medium from legal, institutional, and policy aspects (VIP=1.087). This is because differences in generation, age, gender, and personal characteristics were not considered. Therefore, it is necessary to devise a customized messaging tool through the expansion of broadcast media. The broadcast criteria of the legal, institutional, and policy perspectives comprised the third most influential factor, with a high VIP value of 1.053. Consequently, it is essential to devise a plan to avoid distributing unnecessary cell broadcast services, by establishing criteria for areas and sections, time, and the direct and indirect impact zones of a disaster. In the future, this study could be used as base data to develop policies, guidelines, and response measures for Incheon CBS. Given the lack of research on the diverse characteristics of each social class and the city traits of each region, and a lack of concrete empirical research on each factor, continuous and in-depth studies are required in the future.