• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.988-992
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• 2009

In this paper, we attempted to extract binary relations between terminologies using composite kernels consisting of convolution parse tree kernels and WordNet verb synset vector kernels which explain the semantic relationships between two entities in a sentence. In order to evaluate the performance of our system, we used three domain specific test collections. The experimental results demonstrate the superiority of our system in all the targeted collection. Especially, the increase in the effectiveness on KREC 2008, 8% in F1, shows that the core contexts around the entities play an important role in boosting the entire performance of relation extraction.

• Journal of Microbiology and Biotechnology
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• v.11 no.1
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• pp.85-91
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• 2001

To construct an efficient Bacillus subtilis expression vector, strong promoters were isolated from the chromosomal DNA libraries of Clostridium acetobutylicum ATCC 4259, Thermoactinomyces sp. E79, and Bacillus thermoglucosidasius KCTC 3400. The $P_{C27}$ promoter cloned from the clostridial chromosmal DNA showed a 5-fold higher promoter strength than the $P_{SP02}$ promoter in the expression of the cat gene, and its sequence was estimated as an upstream region of the predicted hypothetical gene (tet-R family bacterial transcription regulator gene) in C. acetobutylicum. As a promoter element, $P_{C27}$ exhibited putative nucleotide sequences that can bind with bacterial RNAP and the 3'end of the 16S rRNA just upstream of the start codon. In addition, the promoter activity of $P_{C27}$ was distinctively repressed in the presence of glucose. Using $P_{C27}$ as the promoter element, a glucose controllable B. subtilis expression vector was constructed and the lipase gene from Staphylococcus haemolyticus KCTC 8957P was expressed in B. subtilis. When compared with the lipase expression by the T7 promoter induced by IPTG in E. coli, the $P_{C27}$ promoter showed about a 1.5-fold higher expression level in B. subtilis than that without induction.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.721-731
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• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.21-27
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• 1991

This paper outlines the method of formulating the bi-cubic B-spline surface of ship hull, employing the open uniform knot vector as well as the periodic uniform knot vector. An appropriate set of B-spline control vertices to generate the B-spline surface is determined by obtaining the pseudoinverse matrix of basis functions. The comparison between the given offsets and the resulting coordinates from the generated ship hull surface shows a good agreement. To check the fairness of the surface Gaussian curvature is calculated on many small subpatches and displayed on the black-and-white plot of the isoparametric net of the surface.

• Journal of Astronomy and Space Sciences
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• v.34 no.1
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• pp.19-30
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• 2017

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.2
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• pp.5-12
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• 2015

The authors calculate the long-term predictability of GDP, domestic demand, investment, and net exports for Guangdong province, P.R. China from 2000 to 2013. A vector autoregressive (VAR) model with quarterly data for this period is first co-integrated then the Granger causality test is applied to empirically assess the relationships among gross domestic product (GDP), consumption, investment, and net exports. There is a strong causality effect between investment and net exports in Guangdong province. However, the variance decomposition results indicate that exports respond to foreign shocks rather than domestic ones, making their impact on the Guangdong economy to predict. Results show the stimulating effect of domestic demand on GDP is larger than the stimulating effect of net exports and much larger than even the stimulating effect of investment. The analysis suggests that there are dynamic influences with various levels of persistence between GDP, consumption, investment, and net exports. Macroeconomic policy adjustments are urgently required to expand domestic demand and thereby stimulate economic growth in Guangdong province.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.463-473
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• 2022

Purpose - The purpose of this study is to examine the effect of the North Korea's net export to China and Liaoning on the North Korean economic growth. Design/methodology/approach - This study collects the data on the net export of North Korea to China and Liaoing from General Administration of Customs, People's Republic of China. Vector Autoregression(VAR) is also employed for the analysis. Findings - First, North Korea's net export to all of China and Liaoning gives the positive effect on North Korean economic growth. Second, the nuclear test of North Korea gives the negative effect on the North Korean economic growth. Third, the net export to China and Liaoning granger causes the North Korean economic growth. Lastly, the nuclear test of North Korea also granger causes the North Korean economic growth. Research implications or Originality - The estimation results show the net export of North Korea to China as well as Liaoning is important to the economic growth. Therefore, we need to examine North Korea's trades with specific region as well as all of China in order to enhance the North Korean economic growth.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.237-244
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• 2022

Onions are a significant crop in Korea, and cultivation is increasing every year along with high demand. Onions are planted in the fall and mainly harvested in June, the rainy season, therefore, physiological changes in onion bulbs during long-term storage might have happened. Onions are stored in cold room and at adequate relative humidity to avoid quality loss. In this study, bio-yield stress and weight loss were measured as the quality parameters of net packaged onions during 10 weeks of storage, and the storage environmental conditions are monitored using sensor networks systems. Quality estimation of net packaged onion during storage was performed using the storage environmental condition data through machine learning approaches. Among the suggested estimation models, support vector regression method showed the best accuracy for the quality estimation of net packaged onions.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1165-1171
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• 2017

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup due to vectorization as a function of the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size to achieve vector efficiency greater than 90%. When the execution times for events are allowed to vary, the vector speedup is also limited by differences in the execution time for events being carried out in a single event-iteration.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.837-839
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• 2001

This paper presents dynamic characteristic of a 2 phase hybrid stepping motor which includes pull-out torque with constant voltage drive and one step response. In order to analyze this characteristics, vector diagram of a synchronous motor and torque-voltage equation are used. Analytic results are good agreement with experimental results.