• Journal of Pharmaceutical Investigation
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• v.41 no.6
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• pp.377-380
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• 2011

The Artemisia princeps (Compositae) has been used in traditional Korean medicine for the treatment of microbial infections and inflammatory diseases. Since A. princeps is generally difficult to be discriminated from A. capillaris, A. caplillaris has been misused in place of A. princeps. To solve this problem, a rapid and nondestructive method for discrimination of A. princeps and A. capillaris samples was developed using near infrared spectroscopy (NIRS) in the present study. A principal component analysis (PCA) and a partial least squares discrimination analysis (PLS-DA) were performed to discriminate two species. As a result, with the use of PLS-DA, A. princeps and A. capillaris were clustered according to their genus. These outcomes indicated that the NIRS could be useful for the discrimination between Artemisia princeps and Artemisia capillaris.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.1
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• pp.97-103
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• 2016

The sensitivity of interior noise that the passengers perceive is comparatively high in the train, and structure-borne and air-borne types of noises come into the train. In this paper, to analyze contributions of these noise sources operational transfer path analysis(OTPA) is used. OTPA has some advantages of executing the contribution rates of several sources simultaneously, and in this work, 29 points are measured while running. Transfer functions between reference measurement points and response measurement points are calculated by the singular value decomposition(SVD) and Principal component analysis(PCA) method, and the frequency characteristics of the noise source are successfully derived. Also the interior noise is predicted and compared with measurement data to show the reliability.

• Korean journal of food and cookery science
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• v.28 no.6
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• pp.741-751
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• 2012

This study was conducted to understand sensory characteristics of commercial functional beverages, to analyze and the drivers of liking and disliking of it by Korean consumers. Descriptive analysis and consumer taste testing were conducted with ten commercial products of functional beverages. Samples were consisted of good for beauty, relieving hangovers, and health tonics. For the descriptive analysis, 45 attributes were developed by ten panelists and it shows differences among the all samples. For the consumer testing, 81 panels evaluated the overall liking, acceptance of appearance, odor, flavor, and texture of 10 samples. As a result, attributes of brightness, yellow color, Nurungji flavor, roasted bean power flavor, and milky texture of functional beverages were positive drivers of liking, but attributes of astringent texture, bitter taste, and viscosity were negative drivers of liking on the commercial functional beverages.

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.286-291
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• 2013

This paper presents to analyze patterns from single and complex malodors using gas sensor array based on metal oxide semiconductors. The aim of research is to identify and discriminate single malodors such as $NH_3$, $CH_3SH$ and $H_2S$ and their mixtures according to concentration levels. Measurement system for analyzing patterns from malodors is constructed by an array of metal oxide semiconductor sensors which are available commercially together with associate electronics. The patterns from sensory system are analyzed by Principal Component Analysis (PCA) which is simple statistical pattern recognition technique. Throughout the experimental trails, we confirmed the experimental procedure for measurement system such as sensors calibration time and gas flow rate, and discriminated malodors using pattern analysis technique.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.

• Journal of the Korean Society of Food Culture
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• v.31 no.6
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• pp.624-633
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• 2016

This study identified the sensory properties of samples of pizza dough at three pizza companies and three masonry oven pizzerias from Seoul, Korea and compared consumer acceptability among panels of university students. Six pizza dough samples were prepared (pan pizzas from Pizza Hut, Mr.pizza, and Dominos pizza, masonry oven baked pizzas from Appleteen, Mr.Lee's, and Pizza factory). Consumer tests were employed involving 97 Korean consumers. Consumers evaluated overall liking (OL), liking of appearance (APPL), odor (ODL), flavor (FLL), and texture (TXTL), willing to try (WT), and willing to recommend (WR) for the samples using a nine-point hedonic scale. Analysis of variance (ANOVA) indicated that HutP, MrP, and DomP samples had significantly (p<0.05) high scores for roughness, porosity, crust color, grain size, brownness, dairy food aroma, savory taste, and yeast aroma, which had the highest OL, ODL, and FLL scores. LeeP, ATeenP, and PFacP samples had high elasticity, cohesiveness, and adhesiveness. Consumers favored the appearance characteristics and color, dairy product flavor, and savory flavor of the pan pizza and preferred cohesiveness, toughness, and stickiness of masonry oven baked pizza.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2239-2246
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• 2024

The present study aimed to assess the radioactive hazards associated with the application of granitoid rocks in building materials. An HPGe spectrometer was used to detect the levels of the radioactive elements uranium-238, thorium-232, and potassium-40 in the granitoid rocks. The results showed that the levels of these elements were lower (38.32 < 33 Bq kg^-1), comparable (47.19-45 Bq kg^-1) and higher (992.26 ≫> 412 Bq kg^-1) than the worldwide limits for ²³⁸U, ²³²Th, and ⁴⁰K concentration, respectively. The exposure to gamma radiation of granitoid rocks was studied by various radiological hazard variables like the absorbed dose rate (D_air), the outdoor and indoor annual effective dose (AED_out and AED_in), and excess lifetime cancer risk (ELCR). A variety of statistical methods, including Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA) was used, to study the relationship between the radioactive elements and the radiological hazards. According to statistical analysis, the main radioactive risk of granitoid rocks is contributed to by the elements uranium-238, thorium-232, and potassium-40. Granitoid rocks can be applied in building materials, but under control to prevent risk to the public.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.303-303
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• 2022

The purpose of this study was to evaluate agronomic characteristics and identify the useful traits to utilize the wheat genetic resources for breeding programs by understanding the phenotypic variation among germplasm through multivariate analysis. In this study, a total of 394 wheat accessions were characterized for 15 agronomic traits using the National Agrobiodiversity Center (NAC) descriptor list, of which 31 accessions from 6 species and 363 unidentified accession (Triticum spp.) available at the NAC, Rural Development Administration (RDA), Korea. Growth characteristics such as leaf width, culm length, spike length, spikelet length, solid stemmed, days to heading, days to maturity, grain-filing period, and also seed characteristics such as width, height, area, perimeter, circle, solidity, and germination percent were studied. Among the 15 agronomic characteristics, the germination percent showed the smallest variation between resources (CV = 0.4%), and the spikelet length (CV = 66.5%) showed the highest variation. A strong positive correlation was found between seed traits such as seed height and seed area (r = 0.90), seed height and seed perimeter (r = 0.87) and seed length and width (r = 0.80). Principal component analysis (PCA) was conducted and the first five principal components comprised 76.7% of the total variance. Among the first five PCs, PCI accounted for 28.5% and PC2 for 20.0%. Wheat resources (394) were classified into four clusters based on cluster analysis, consisting of 215 resources(I), 117 resources(II), 48 resources(III), and 14 resources(IV). Among the clusters, the resources belonging to Cluster III showed the lowest seed width, height, area, and perimeter characteristics compared to other clusters. The wheat resources belonging to cluster IV had small seed width and low germination percent, but took longer to form heads and mature than resources in other clusters. These results will serve as the basis for further genetic diversity studies, and important agronomic characteristics will be used for improving wheat, including developing high-yielding and resistant varieties to biotic and abiotic stresses via breeding programs.

• Food Science of Animal Resources
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• v.24 no.3
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• pp.260-265
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• 2004

This study was carried out to investigate aroma patterns of Hanwoo (Korean cattle) beef using electronic nose during refrigerated storage, and to compare these results with chemical quality (pH, TBARS). The M. longissimus muscle from Hanwoo carcasses after 24 hrs postmortem was obtained and stored at 5${\pm}$1$^{\circ}C$ for 7 days. Sensitivity (dR/RO) values among electronic nose data were changed differently during refrigerated storage, and showed significant difference on the 7th day of storage (p<0.01). The dR/RO from SY/G, SY/AA, SY/Gh, SY/gCTl, SY/gCT decreased but those from SY/LG, T30/1, P10/1, P10/2, P40/1, T70/2, PA2 increased during storage for 7 days. Mapping these data using PCA (principal component analysis) showed that the 1st day data were present in the middle of the right side, the 3rd day data were present in bottom part of this area and the 7th day data spread out more widely on the left side. In case of DFA (discriminant factor analysis), the flock clustered round and located in different side clearly comparing with PCA plot. In analysis of correlation coefficients among electronic nose data and chemical quality data, there was significant correlation among sensor data (p<0.001). But pH and TBARS were not significantly correlated with electronic nose data. Consequently, PCA and DFA plot by electronic nose data showed difference during refrigerated storage and there were significant correlations among sensors. Therefore it will be possible to detect separate aroma patterns of Hanwoo beef using electronic nose.