• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.625-637
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• 2020

In order to decide the naval ship weapon system acquisition for national policy/market economy activities, the decision makers can determine policy based on current technology level/concentration/utilization. For this, the decision makers apply the major common technology field analysis using patents data. As a method for collecting patent data, we can collect patent data of domestic mobile carriers through the Korea Intellectual Property Rights Information System of Korean Intellectual Property Office. As a result, we collected 14,964 patents/352 International Patent Classification(IPC) types. Based on these data, we performed three analysis processes (SNA, PCA, ARIMA, Text Mining) and got each result from extracting 58 IPC types of SNA and 7 IPC types of PCA. Based on the analysis results, we have confirmed that 7 IPC(B63B, H01M, F03D, B01D, H02K, B23K, H01H) types are the Major Common Technology Distribution of domestic Defense Companies.

• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1791-1798
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• 2006

When ginsenoside Rg5, a main component isolated from red ginseng, was incubated with three human fecal microflora for 24 h, all specimens showed hydrolyzing activity: all specimens produced ginsenoside Rh3 as a main metabolite, but a minor metabolite $3{\beta},12{\beta}$-dihydroxydammar-21(22),24-diene (DD) was observed in two specimens. To evaluate the antiallergic effect of ginsenoside Rg5 and its metabolites, the inhibitory effect of ginsenoside Rg5 and its metabolite ginsenoside Rh3 against RBL-2H3 cell degranulation, mouse passive cutaneous anaphylaxis (PCA) reaction induced by the IgE-antigen complex, and mouse ear skin dermatitis induced by 12-O-tetradecanoilphorbol-13-acetate (TPA) were measured. Ginsenosides Rg5 and Rh3 potently inhibited degranulation of RBL-2H3 cells. These ginsenosides also inhibited mRNA expression of proinflammatory cytokines IL-6 and $TNF-{\alpha}$ in RBL-2H3 cells stimulated by IgE-antigen. Orally and intraperitoneally administered ginsenoside Rg3 and orally administered ginsenoside Rg5 to mice potently inhibited the PCA reaction induced by IgE-antigen complex. However, intraperitoneally administered ginsenoside Rg5 nearly did not inhibit the PCA reaction. These ginsenosides not only suppressed the swelling of mouse ears induced by TPA, but also inhibited mRNA expression of cyclooxygenase-2, $TNF-{\alpha}$, and IL-4 and activation of transcription factor NF-kB. These inhibitions of ginsenoside Rh3 were more potent than those of ginsenoside Rg5. These findings suggest that ginsenoside Rg5 may be metabolized in vivo to ginsenoside Rh3 by human intestinal microflora, and ginsenoside Rh3 may improve antiallergic diseases, such as rhinitis and dermatitis.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.93-99
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• 2017

A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

• Culinary science and hospitality research
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• v.21 no.1
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• pp.235-249
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• 2015

This study was carried out to investigate the flavor changes of Lentinus edodes at different storage temperatures, time and natural additives using an electronic nose with six metal oxide sensors. To preserve good quality of modified atmosphere packaged Lentinus edodes, Four natural additives(Artemisia princeps, Artemisia capillaries, green tea, and activated charcoal) were used. The mushrooms were packaged in polyethylene films with each treatment and were stored at 5, 10 and $20^{\circ}C$. Increase in storage temperature and storage time decreased the ratio of resistance in the electronic nose as well as first principal component scores. In addition, indicating quality of mushroom reduced at high temperature and long storage time. The results of the electronic nose and the principal component analysis(PCA) in the mushrooms with Artemisia princeps and Artemisia capillaries that were stored at $5^{\circ}C$, and green tea and activated charcoal which were stored at $10^{\circ}C$ showed the good effects to maintain the freshness along with reducing off-flavor. However, there were no differences between control and treatment groups at $20^{\circ}C$.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.694-698
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• 2008

In hydrology, it is a difficult task to deal with multivariate time series such as modeling streamflows of an entire complex river system. Normal distribution based model such as MARMA (Multivariate Autorgressive Moving average) has been a major approach for modeling the multivariate time series. There are some limitations for the normal based models. One of them might be the unfavorable data-transformation forcing that the data follow the normal distribution. Furthermore, the high dimension multivariate model requires the very large parameter matrix. As an alternative, one might be decomposing the multivariate data into independent components and modeling it individually. In 1985, Lins used Principal Component Analysis (PCA). The five scores, the decomposed data from the original data, were taken and were formulated individually. The one of the five scores were modeled with AR-2 while the others are modeled with AR-1 model. From the time series analysis using the scores of the five components, he noted "principal component time series might provide a relatively simple and meaningful alternative to conventional large MARMA models". This study is inspired from the researcher's quote to develop a multivariate simulation model. The multivariate simulation model is suggested here using Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Three modeling step is applied for simulation. (1) PCA is used to decompose the correlated multivariate data into the uncorrelated data while ICA decomposes the data into independent components. Here, the autocorrelation structure of the decomposed data is still dominant, which is inherited from the data of the original domain. (2) Each component is resampled by block bootstrapping or K-nearest neighbor. (3) The resampled components bring back to original domain. From using the suggested approach one might expect that a) the simulated data are different with the historical data, b) no data transformation is required (in case of ICA), c) a complex system can be decomposed into independent component and modeled individually. The model with PCA and ICA are compared with the various statistics such as the basic statistics (mean, standard deviation, skewness, autocorrelation), and reservoir-related statistics, kernel density estimate.

• The Korean Journal of Food And Nutrition
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• v.34 no.1
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• pp.1-14
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• 2021

This study evaluated the antioxidant activity and quality characteristics of rice cookie with added butterbur powder in a ratio of 0, 5, 10, 15, and 20% to confirm the possibility of butterbur as a functional food. The moisture content, spread factor, leavening rate, and hardness of rice cookies increased with an increase in the amount of butterbur powder; whereas a decrease in the pH and baking loss rate was observed. The L and b values decreased as the amount of butterbur powder increased, but the value was the lowest when 5% of butterbur powder was added. The sensory liking score showed the highest preference for 10% butterbur powder regarding appearance, flavor, taste, texture, and overall preference. In the principal component analysis (PCA), the addition of 10% butterbur powder positively affected the measure of food acceptance in terms of organoleptic properties of butterbur. Besides, as the amount of added butterbur powder increased, the antioxidant activity of rice cookies increased. Based on these results, it appears that the addition of butterbur powder to rice cookies in a 10% ratio can produce rice cookies with excellent antioxidant activity, overall quality, and high preference.

• The Journal of Bigdata
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• v.6 no.2
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• pp.29-38
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• 2021

Deviation of route in aviation safety management is a dangerous factor that can lead to serious accidents. In this study, the anomaly score is calculated by classifying the tracks through clustering and calculating the distance from the cluster center. The study was conducted by extracting tracks within 100 km of the airport from the ADS-B track data received for one year. The wake was vectorized using linear interpolation. Latitude, longitude, and altitude 3D coordinates were used. Through PCA, the dimension was reduced to an axis representing more than 90% of the overall data distribution, and k-means clustering, hierarchical clustering, and PAM techniques were applied. The number of clusters was selected using the silhouette measure, and an abnormality score was calculated by calculating the distance from the cluster center. In this study, we compare the number of clusters for each cluster technique, and evaluate the clustering result through the silhouette measure.

• The Korean Journal of Food And Nutrition
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• v.27 no.2
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• pp.287-293
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• 2014

The physicochemical characteristics of 4 domestic wheat flour products were compared to those of 4 imported wheat flour products marketed in Korea. The contents of moisture, ash, protein, total dietary fiber (TDF), color (L, a, b), whiteness, solvent retention capacity (SRC), water absorption index (WAI), water soluble index (WSI), pasting characteristics by rapid visco analyzer (RVA), and principle component analysis (PCA) were analyzed. The domestic wheat flour products were composed of higher content in ash and protein, compared to the imported wheat flour products. The domestic wheat flour products had lower SRC and WSI characteristics than the imported wheat flour products. The values of lactic acid SRC (LASRC) in the imported wheat flour products showed an increasing trend as the protein content increased. The differences in viscosity were observed in the domestic wheat flour products. However, no major significant differences of viscosity were found among the imported wheat flour products. The result of PCA showed a consistent trend in the imported wheat flour (strong, medium, and weak), while a consistent trend was not shown in the domestic wheat flour products. Therefore, further research is needed to standardize the different types of domestic wheat flour products.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4469-4475
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• 2015

Transient receptor potential melastain 7 (TRPM7) is a bifunctional protein with dual structure of both ion channel and protein kinase, participating in a wide variety of diseases including cancer. Recent researches have reported the mechanism of TRPM7 in human cancers. However, the correlation between TRPM7 and prostate cancer (PCa) has not been well studied. The objective of this study was to investigate the potential the role of TRPM7 in the apoptosis of PC-3 cells, which is the key cell of advanced metastatic PCa. In this study, we demonstrated the influence and potential function of TRPM7 on the PC-3 cells apoptosis induced by TNF-related apoptosis inducing-ligand (TRAIL). The study also found a novel up-regulated expression of TRPM7 in PC-3 cells after treating with TRAIL. Suppression of TRPM7 by TRPM7 non-specific inhibitors ($Gd^{3+}$ or 2-aminoethoxy diphenylborate (2-APB) ) not only markedly eliminated TRPM7 expression level, but also increased the apoptosis of TRAIL-treated PC-3 cells, which may be regulated by the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway accompany with up-regulated expression of cleaved Caspase-3, (TRAIL-receptor 1, death receptors 4) DR4, and (TRAIL-receptor 2, death receptors 5) DR5. Taken together, our findings strongly suggested that TRPM7 was involved in the apoptosis of PC-3 cells induced by TRAIL, indicating that TRPM7 may be applied as a therapeutic target for PCa.