• BMB Reports
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• v.51 no.7
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• pp.338-343
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• 2018

Transcription termination factor-1 (TTF-I) is an RNA polymerase 1-mediated transcription terminator and consisting of a C-terminal DNA-binding domain, central domain, and N-terminal regulatory domain. This protein binds to a so-called 'Sal box' composed of an 11-base pair motif. The interaction of TTF-I with the 'Sal box' is important for many cellular events, including efficient termination of RNA polymerase-1 activity involved in pre-rRNA synthesis and formation of a chromatin loop. To further understand the role of TTF-I in human immunodeficiency virus (HIV)-I virus production, we generated various TTF-I mutant forms. Through a series of studies of the over-expression of TTF-I and its derivatives along with co-transfection with either proviral DNA or HIV-I long terminal repeat (LTR)-driven reporter vectors, we determined that wild-type TTF-I downregulates HIV-I LTR activity and virus production, while the TTF-I Myb-like domain alone upregulated virus production, suggesting that wild-type TTF-I inhibits virus production and trans-activation of the LTR sequence; the Myb-like domain of TTF-I increased virus production and trans-activated LTR activity.

• Journal of the Chungcheong Mathematical Society
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• v.23 no.4
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• pp.705-710
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• 2010

Let $C_1(X)$ be a normed linear space over ${\mathbb{R}}^m$, and S be an n-dimensional subspace of $C_1(X)$ with spaned by {$s_1,{\cdots},s_n$}. For each ${\ell}$- tuple vectors F in $C_1(X)$, the two-sided best simultaneous approximation problem is $$\min_{s{\in}S}\;\max\limits_{i=1}^\ell\{{\parallel}f_i-s{\parallel}_1\}$$. A $s{\in}S$ attaining the above minimum is called a two-sided best simultaneous approximation or a Chebyshev center for $F=\{f_1,{\cdots},f_{\ell}\}$ from S. This paper is concerned with algorithm for calculating two-sided best simultaneous approximation, in the case of continuous functions.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.245-258
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• 2023

This study proposes a modification to the objective function of the support vector machine for the linearly non-separable case of a binary classifier y_i ∈ {-1, 1}. The modification takes into account the position of each data item x_i from its corresponding class centroid. The resulting optimization function involves the centroid mean vector, and the spread of data besides the support vectors, which should be minimized by the choice of hyper-plane β. Theoretical assumptions have been tested to derive an optimal separable hyperplane that yields the minimal misclassification rate. The proposed method has been evaluated using simulation studies and real-life COVID-19 patient outcome hospitalization data. Results show that the proposed method performs better than the classical linear SVM classifier as the sample size increases and is preferred in the presence of correlations among predictors as well as among extreme values.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.423-429
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• 2014

This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.455-462
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• 2006

Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Korean Journal of Plant Tissue Culture
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• v.27 no.1
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• pp.39-45
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• 2000

Two maize transposable elements, immobilized Ac (iAc) and Ds, have been introduced into the genome of a diploid potato clone (Solanum tuberosum Group Phureja clone 1.22). The iAc is a modified Ac that is supposed to be unable to transpose but is expected to trans-activate the transposition of a Ds that is unable to transpose by itself. When the leaf and stem explants of in vitro shoots of the clone 1.22 were inoculated with Agrobacterium tumefaciens strains harboring binary vectors containing the iAc and the Ds, calli were formed from the explants on media containing 50 mg/L of kanamycin, and shoots were regenerated from the calli. The regenerated shoots formed roots when cultured on media containing 100 mg/L of kanamycin, whereas untransformed shoots did not form roots on the same media. The PCR amplification of the DNA's from the transgenic plants confirmed that the iAc and the Ds elements were introduced into the potato genome of 1.22.

• Parasites, Hosts and Diseases
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• v.59 no.4
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• pp.427-432
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• 2021

The infection status of zoonotic trematode metacercariae (ZTM) was investigated in total 568 freshwater fishes (19 species) from the irrigation canal of Togyo-jeosuji (Reservoir) in Cheorwon-gun, Gangwon-do, the Republic of Korea for 3 years (2018-2020). All fishes were examined using the artificial digestion method. The metacercariae of Clonorchis sinensis (CsMc) were detected in 180 (43.8%) out of 411 fish of positive species, and their infection intensity was 38 per fish infected (PFI). Especially, in 2 fish species, i.e., Pseudorasbora parva and Puntungia herzi, the prevalence was 82.1% and 31.3%, and the infection intensity with CsMc was 88 and 290 PFI, respectively. Metagonimus spp. metacercariae (MsMc) were found in 403 (74.1%) out of 544 fish of positive species, and their infection intensity was 62 PFI. In the pale chub, Zacco platypus, the prevalence of MsMc was 98.6%, and their infection intensity was 144 PFI. Centrocestus armatus metacercariae were detected in 171 (38.9%) out of 440 fish of positive species, and their infection intensity was 1,844 PFI. Echinostoma spp. metacercariae were found in 94 (19.6%) out of 479 fish of positive species, and their infection intensity was 3 PFI. Metorchis orientalis metacercariae were detected in 43 (29.3%) out of 147 fish of positive species, and their infection intensity was 4 PFI. By the present study, it has been confirmed that some species of ZTM, including CsMc and MsMc, are prevalent in fishes from the irrigation canal of Togyo-jeosuji in Cheorwon-gun, Gangwon-do, Korea.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.958-964
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• 2016

In this paper, we propose an i-vector based language recognition system to identify the spoken language of the speaker, which uses multiple discriminative deep neural network (DNN) models analogous to the multi-class support vector machine (SVM) classification system. The proposed model was trained and tested using the i-vectors included in the NIST 2015 i-vector Machine Learning Challenge database, and shown to outperform the conventional language recognition methods such as cosine distance, SVM and softmax NN classifier in open-set experiments.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.25-36
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• 2023

Nuclear power plants have recognized the importance of nuclear cybersecurity. Based on regulatory guidelines and security-related standards issued by regulatory agencies around the world including IAEA, NRC, and KINAC, nuclear operating organizations and related systems manufacturing organizations, design companies, and regulatory agencies are considering methods to prepare for nuclear cybersecurity. Cryptographic algorithms have to be developed and applied in order to meet nuclear cybersecurity requirements. This paper presents methodologies for validating cryptographic algorithms that should be continuously applied at the critical control system of I&C in NPPs. Through the proposed schemes, validation programs are developed in the PLC, which is a critical system of a NPP's I&C, and the validation program is verified through simulation results. Since the development of a cryptographic algorithm validation program for critical digital systems of NPPs has not been carried out, the methodologies proposed in this paper could provide guidelines for Cryptographic Module Validation Modeling for Control Systems in NPPs. In particular, among several CMVP, specific testing techniques for ECB mode-based block ciphers are introduced with program codes and validation models.