• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.6
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• pp.8-22
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• 1978

Recently developed Computed Topography (CT) reconstruction algorithms are reviewed in a more generalized sense and a few reconstruction examples are given for illustration. The construction of an image function from the physically measured projections of some object is Discussed with reference to the least squares optimum filters, originally derived to enhance the signal-to-noise ratio in communications theory. The computerifed image processing associated with topography is generalized so as to include 3 distinct parts: the construction of an image from the projection, the restoration of a blurred, noisy image, degraded by a known space-invariant impulse response, and the further enhancement of the image, e.g. by edge sharpening. In conjunction with given versions of the popular convolution algorithm, n6t 19 be confused with filtering by a 2-diminsional convolution, we consider the conditions under which a concurrent construction, restoration, and enhancement are possible. Extensive bibliographical limits are given in the references.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1151-1156
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• 2013

In this study, to clearly establish the concept of a geometric modeling I apply for the concept of Pushbroom, limited to two-dimensional radiation Locator to provide a three-dimensional information purposes. Respect to the radiation scanner Pushbroom modeling techniques, geometric modeling method was presented introduced to extract three-dimensional information as long as the rotational component of the Gamma-Ray Linear Pushbroom Stereo System, introduced the two-dimensional and three-dimensional spatial information in the matching relation that can be induced. In addition, the pseudo-inverse matrix by using the conventional least-squares method, GCP(Ground Control Point) to demonstrate compliance by calculating the key parameters. Projection transformation matrix is calculated for obtaining three-dimensional information from two-dimensional information can be used as the primary relationship, and through the application of a radiation image matching technology will make it possible to extract three-dimensional information from two-dimensional X-ray imaging.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.205-215
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• 2012

Due to a rapid change of business environment, many firms are eager to find the competitiveness by information technology adoption and diffusion. In this exploratory study, we examined the applicability of a previously proposed model to evaluate IT competitiveness based on the innovativeness and verified it's propriety with empirical data. As suggested by previous studies, the proposed model considers a variety of corporate and market characteristics concerned with IT adoption, and it consists of several internal and external impacting factors, which have influence on technology diffusion and its performance. For the empirical analysis, the survey data of domestic ERP adoption cases were adopted from 128 small and medium-sized enterprises(: SMEs) in IT and electrical engineering industry, and analyzed by partial least squares(: PLS) - a popular structural modeling and multivariate projection technique to latent variables. The results indicated positive supports for the research model of external and internal IT adoption factors' influences on innovativeness' performances. However, there are a couple of limitations not to show the reliability of selected measurement items and the generality of model proposed in this exploratory study.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.82-91
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• 2011

In this paper, a planar model for mechanics of a vehicle/pedestrian collision incorporating road gradient is derived to evaluate the pre-collision speed of vehicle. It takes into account a few physical variables and parameters of popular wrap and forward projection collisions, which include horizontal distance traveled between primary and secondary impacts with the vehicle, launch angle, center-of-gravity height at launch, distance from launch to rest, pedestrian-ground drag factor, the pre-collision vehicle speed and road gradient. The model including road gradient is derived analytically for reconstruction of pedestrian collision accidents, and evaluates the vehicle speed from the pedestrian throw distance. The model coefficients have physical interpretations and are determined through direct calculation. This work shows that the road gradient has a significant effect on the evaluation of the vehicle speed and must be considered in accident cases with inclined road. In additions, foreign/domestic empirical cases and multibody dynamic simulation results are used to construct a least-squares fitted model that has the same structure of the analytical one that provides an estimate of the vehicle speed based on the pedestrian throw distance and the band within which the vehicle speed would be expected to be in 95% of cases.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.685-688
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• 2003

In this paper, a performance comparison between two blind signal estimation algorithms in a LTI channel is considered. The two algorithms, Iterative Least-Squares with Projection (ILSP) and a modified ILSP, are based on the finite-alphabet property of input symbols. This case typically arises in a multiple access system with a sensor array antenna at the receiving end. We start with the formulation of a maximum-likelihood (ML) estimation problem under an additive white Gaussian noise assumption. A blind ML estimator is derived with its iterative algorithm for calculation. Then we narrow down the consideration of this problem to QPSK case so that a modified algorithm is proposed for $\pi$/4-QPSK case. The modified version is compared with the original ILSP algorithm in terms of the rate of the convergence to global minima. A computer simulation shows that the modified algorithm gives a better performance. This result implies that the performance of the blind separation algorithms may be greatly improved by adopting a smart coding scheme with rich structure.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.23-30
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• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.559-570
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• 2017

A partial least squares regression (PLSR) model was developed to map the internal soluble solids content (SSC) of apples using a ground-based hyperspectral scanner that could simultaneously acquire outdoor data and capture images of large quantities of apples. We evaluated the applicability of various preprocessing techniques to construct an optimal prediction model and calculated the optimal band through a variable importance in projection (VIP)score. From the 515 bands of hyperspectral images extracted at wavelengths of 360-1019 nm, 70 reflectance spectra of apples were extracted, and the SSC ($^{\circ}Brix$) was measured using a digital photometer. The optimal prediction model wasselected considering the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP) and coefficient of determination of prediction $r_p^2$. As a result, multiplicative scatter correction (MSC)-based preprocessing methods were better than others. For example, when a combination of MSC and standard normal variate (SNV) was used, RMSECV and RMSEP were the lowest at 0.8551 and 0.8561 and $r_c^2$ and $r_p^2$ were the highest at 0.8533 and 0.6546; wavelength ranges of 360-380, 546-690, 760, 915, 931-939, 942, 953, 971, 978, 981, 988, and 992-1019 nm were most influential for SSC determination. The PLSR model with the spectral value of the corresponding region confirmed that the RMSEP decreased to 0.6841 and $r_p^2$ increased to 0.7795 as compared to the values of the entire wavelength band. In this study, we confirmed the feasibility of using a hyperspectral scanner image obtained from outdoors for the SSC measurement of apples. These results indicate that the application of field data and sensors could possibly expand in the future.

• Journal of Ginseng Research
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• v.44 no.6
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• pp.775-783
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• 2020

Background: The reports about valuable oligosaccharides in ginseng are quite limited. There is an urgent need to develop a practical procedure to detect and analyze ginseng oligosaccharides. Methods: The oligosaccharide extracts from ginseng were permethylated by solid-phase methylation method and then were analyzed by ultra-high-performance liquid chromatography-Q-Orbitrap/MS. The sequence, linkage, and configuration information of oligosaccharides were determined by using accurate m/z value and tandem mass information. Several standard references were used to further confirm the identification. The oligosaccharide composition in white ginseng and red ginseng was compared using a multivariate statistical analysis method. Results: The nonreducing oligosaccharide erlose among 12 oligosaccharides identified was reported for the first time in ginseng. In the comparison of the oligosaccharide extracts from white ginseng and red ginseng, a clear separation was observed in the partial least squares-discriminate analysis score plot, indicating the sugar differences in these two kinds of ginseng samples. The glycans with variable importance in the projection value large than 1.0 were considered to contribute most to the classification. The contents of oligosaccharides in red ginseng were lower than those in white ginseng, and the contents of maltose, maltotriose, maltotetraose, maltopentaose, maltohexaose, maltoheptaose, maltooctaose, maltononaose, sucrose, and erlose decreased significantly (p < 0.05) in red ginseng. Conclusion: A solid-phase methylation method combined with liquid chromatography-tandem mass spectrometry was successfully applied to analyze the oligosaccharides in ginseng extracts, which provides the possibility for holistic evaluation of ginseng oligosaccharides. The comparison of oligosaccharide composition of white ginseng and red ginseng could help understand the differences in pharmacological activities between these two kinds of ginseng samples from the perspective of glycans.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.257-271
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• 2019

The use of food grade hexane (FGH) for edible oil extraction is responsible for the presence of benzene in the crude oil. Benzene is a Group 1 carcinogen and could pose a serious threat to the health of consumer. However, its detection still depends on classical methods using chromatography which requires a rapid non-destructive detection method. Hence, the aim of this study was to investigate the feasibility of using Fourier transform infrared (FTIR) spectroscopy combined with multivariate analysis to detect and quantify the benzene residue in edible oil (sesame and cottonseed oil). Oil samples were adulterated with varying quantities of benzene, and their FTIR spectra were acquired with an attenuated total reflectance (ATR) method. Optimal variables for a partial least-squares regression (PLSR) model were selected using the variable importance in projection (VIP) and the selectivity ratio (SR) methods. The developed PLS models with whole variables and the VIP- and SR-selected variables were validated against an independent data set which resulted in $R^2$ values of 0.95, 0.96, and 0.95 and standard error of prediction (SEP) values of 38.5, 33.7, and 41.7 mg/L, respectively. The proposed technique of FTIR combined with multivariate analysis and variable selection methods can detect benzene residuals in edible oils with the advantages of being fast and simple and thus, can replace the conventional methods used for the same purpose.