• Journal of the Ergonomics Society of Korea
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• v.20 no.1
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• pp.45-62
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• 2001

This study suggests a genetic algorithm-based partial least squares (GA-based PLS) method to select the design variables for building a usability model. The GA-based PLS uses a genetic algorithm to minimize the root-mean-squared error of a partial least square regression model. A multiple linear regression method is applied to build a usability model that contains the variables seleded by the GA-based PLS. The performance of the usability model turned out to be generally better than that of the previous usability models using other variable selection methods such as expert rating, principal component analysis, cluster analysis, and partial least squares. Furthermore, the model performance was drastically improved by supplementing the category type variables selected by the GA-based PLS in the usability model. It is recommended that the GA-based PLS be applied to the variable selection for developing a usability model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.469-481
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• 2012

The demand for small-sized housing has been increasing due to the recession of real-estate price and the increase of small-sized households. Especially, the demand for affordable housing has been increasing since the style of housing and the location fits the lifestyle of small-sized household. In addition, many investors have been buying it because it has advertised as an investment property holding high-return ratio. However, an empirical analysis about the selling price and the return ratio has not been done yet. Therefore, the purpose of the research is having the empirical analysis based on the selling price and return ration by examining the affordable housing in Seoul. The urban-life housing more than 50 generations of the Seoul was irradiated for the analysis. And the linear regression analysis and PLS(Partial Least Square Regression) analysis was used for the empirical analysis. The result of analysis, based on the linear regression analysis, showed that factors including neighboring housing price and subway catchment area have a significant effect to the determinant factors of housing price. The analysis for return ratio showed neighboring housing price, subway catchment area and amenities affects the ratio. Especially, the fault of using small sample was covered by using the partial least square regression in this research.

• Toxicological Research
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• v.34 no.2
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• pp.127-132
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• 2018

Alcohol consumption triggers toxic effect to organs and tissues in the human body. The risks are essentially thought to be related to ethanol content in alcoholic beverages. The identification of ethanol in blood samples requires rapid, minimal sample handling, and non-destructive analysis, such as Raman Spectroscopy. This study aims to apply Raman Spectroscopy for identification of ethanol in blood samples. Silver nanoparticles were synthesized to obtain Surface Enhanced Raman Spectroscopy (SERS) spectra of blood samples. The SERS spectra were used for Partial Least Square (PLS) for determining ethanol quantitatively. To apply PLS method, $920{\sim}820cm^{-1}$ band interval was chosen and the spectral changes of the observed concentrations statistically associated with each other. The blood samples were examined according to this model and the quantity of ethanol was determined as that: first a calibration method was established. A strong relationship was observed between known concentration values and the values obtained by PLS method ($R^2=1$). Second instead of then, quantities of ethanol in 40 blood samples were predicted according to the calibration method. Quantitative analysis of the ethanol in the blood was done by analyzing the data obtained by Raman spectroscopy and the PLS method.

• Journal of Navigation and Port Research
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• v.45 no.2
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• pp.42-53
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• 2021

The port space can be considered to be the space in which the characteristics of the port city are best expressed. Also, since it acts as a representative gateway along with the airport, it can have a direct impact on the image of the region and country. However, the harbor hinterland has been a refuge during the war in the past, and it has been concentrating on development related to the port industry; hence, it has a poorer residential environment. Therefore, in this study, in order to ensure equal development in space and equal access to basic urban services, urban design directions were suggested for the harbor hinterland based on the concept of an inclusive city'. To this end, through factor analysis, urban planning elements that can be applied to urban design were derived, and through PLS(Partial Least Square)regression analysis, based on the opinions of residents and experts, urban design directions for the port hinterland were presented. The study site was Gamcheon Port, one of the Busan Ports in Korea, the hinterland of Gamcheon Port was a high slope, and the residential environment was relatively poor due to the dense concentration of older residential areas.

• Food Science and Biotechnology
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• v.18 no.3
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• pp.724-731
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• 2009

Anthocyanins are considered one of the main color determinants in aged red wine. The anthocyanins in aged red wine made from 'Cabernet Gernischet' (Vitis vinifera L. cv.) grape were investigated by high performance liquid chromatography- electronic spray ionization- mass spectrometry (HPLC-ESI-MS) and their color presented in aqueous solution were evaluated using partial least square regression (PLS). The results showed that there were 37 anthocyanins identified in this wine, including 22 pyranoanthocyanins. The analysis of PLS indicated that different anthocyanins showed distinct color values: malvidin 3-O-(6-O-acetyl)-glucoside-4-vinylguaiacol (Mv3-acet-glu-vg) presented the highest color values, while malvidin 3-O-glucoside (Mv3-glu) showed least. Among the free non-acylated anthocyanins, peonidin 3-O-oglucoside (Pn3-glu) showed the highest color values; the coumarylated anthocyanins presented higher color values than their corresponding acetylated anthocyanins and parent anthocyanins; pyranoanthocyanins presented also higher color values than their original anthocyanins; the color of anthocyanins depended on their structure. This work will be helpful to reveal evolution in aged red wine.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.513-525
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• 2020

Purpose: The purpose of this study is to analyze the characteristics of local factors affecting number of tuberculosis death by urban and rural areas. Method: The Partial Least Square(PLS) Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The number of tuberculosis deaths in urban and rural areas is about three times as large. As a result of analysis about Regional Characteristics Factor, In general, children, elderly people, and economically vulnerable populations are more likely to be exposed to tuberculosis. In differential results, it shows that environmental factors such as ultrafine dust and sulfur dioxide have a significant impact on the number of tuberculosis deaths in urban areas and social factors such as depression experience rate in rural areas. Conclusion: The Tuberculosis prevention and management policies that reflect the characteristics of urban and rural areas are needed in the future.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.672-686
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• 2022

Purpose: This study derived the planning factors affecting the evacuation route of facilities for the disabled and to identify the planning factors that affect each facility. Method: The PLS(Partial Least Square)Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The most important planning elements for each facility were derived as door: closing time (1.131), corridor: ramp for wheelchairs (1.227), stairs: emergency lighting for stairs (1.117), and evacuation space: evacuation space convenience facilities (1.106). Conclusion: In order to plan an effective evacuation route for the disabled, a universal design should be applied to consider the perception, needs, and satisfaction of the disabled, rather than a comprehensive reflection.

• Journal of Biosystems Engineering
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• v.40 no.4
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• pp.335-344
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• 2015

Purpose: Soybean growth is adversely affected by environmental stresses such as drought, extreme temperatures, and nutrient deficiency. The objective of this study was to develop a method for rapid measurement of drought stress in soybean plants using a hyperspectral fluorescence imaging technique. Methods: Hyperspectral fluorescence images were obtained using UV-A light with 365 nm excitation. Two soybean cultivars under drought stress were analyzed. A partial least square regression (PLSR) model was used to predict drought stress in soybeans. Results: Partial least square (PLS) images were obtained for the two soybean cultivars using the results of the developed model during the period of drought stress treatment. Analysis of the PLS images showed that the accuracy of drought stress discrimination in the two cultivars was 0.973 for an 8-day treatment group and 0.969 for a 6-day treatment group. Conclusions: These results validate the use of hyperspectral fluorescence images for assessing drought stress in soybeans.