• Horticultural Science & Technology
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• v.29 no.2
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• pp.116-122
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• 2011

In this study, we report the generation and analysis of 1,392 expressed sequence tags (ESTs) from Korean Stewartia (Stewartia koreana Nakai). A cDNA library was generated from the young leaf tissue and a total of 1,392 cDNA were partially sequenced. EST and unigene sequence quality were determined by computational filtering, manual review, and BLAST analyses. Finally, 1,301 ESTs were acquired after the removal of the vector sequence and filtering over a minimum length 100 nucleotides. A total of 893 unigene, consisting of 150 contigs and 743 singletons, was identified after assembling. Also, we identified 95 new microsatellite-containing sequences from the unigenes and classified the structure according to their repeat unit. According to homology search with BLASTX against the NCBI database, 65% of ESTs were homologous with known function and 11.6% of ESTs were matched with putative or unknown function. The remaining 23.2% of ESTs showed no significant similarity to any protein sequences found in the public database. Annotation based searches against multiple databases including wine grape and populus sequences helped to identify putative functions of ESTs and unigenes. Gene ontology (GO) classification showed that the most abundant GO terms were transport, nucleotide binding, plastid, in terms biological process, molecular function and cellular component, respectively. The sequence data will be used to characterize potential roles of new genes in Stewartia and provided for the useful tools as a genetic resource.

• Journal of Life Science
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• v.24 no.1
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• pp.1-7
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• 2014

Eukaryotic gene expression is an important process, which is initiated by several transcription factors and RNA polymerases that occupy the promoter region of genomic DNA. Although there are many experiments to identify the promoter region in a gene, it is time and labor consuming to finalize it. In this study, we utilized bioinformatic programs, including Ensembl, NCBI, and CpG plots, to identify the cloning promoter region in SETDB1 genomic DNA. We performed PCR amplification to obtain the SETDB1 promoter on an approximately 2 kb region upstream from the TSS named SETDB1-P1. The PCR product was ligated with TA cloning vectors, and we confirmed the insert size using restriction enzyme digestion. Sequentially, the insert was subcloned into a pGL3-luc vector to produce pGL3-SETDB1- P1-luc and then confirmed by DNA sequencing. We also obtained a fragmented PCR product called P2 and P3 and performed a luciferase assay using pGL3-SETDB1-P1-luc transfection. We found that several anticancer drugs, including taxol, 4-FU, and doxorubicin, decreased the promoter activity of SETDB1. We obtained consistent data on the regulation of SETDB1 gene expression after anticancer drug treatment using Western blot analysis and RT-PCR. Our results suggest that promoter cloning of the human SETDB1 gene utilizing bioinformatics is a very useful and timesaving approach to study gene expression.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.112-124
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• 2010

Studies that can find resolutions to problems of subjective psychiatric analysis must be performed and indeed they are in the process. However there still lies many problems in researches of mentality examination, which should be the foundation of finding potential resolutions. One of the biggest problems in the conventional system is that there are many different opinions by psychiatrists depending on their educations and experiences. There is no objective standard on the subjects and there is no effective psychiatric analysis method. Also, the characteristic of such examinations is that it cannot be applied to disabilities, foreigners and infants alyce the examination is ch examinconversation. The objective of this atudy is to standardize TAT(Thematic Apperception Test)analysiBallken index method so that subjective data from the examination can be excluded and the examination thus maklysithe examination objectified. Furthermore, objective result and patients' brain wave pattern is read with BCI(Brain Computer Interface) ch exaTherenvironment to Alsare it to brain wave characteristics vectors to reate brain-wave characteristics vector DB. Therefore, such DB can be utilize durlysithe examination and diagnosis to reate objective examination method and standardized diagnosis system. Thus, mentality examination can be performed only with brain-wave scans with BCI based TAT system.

• KSBB Journal
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• v.20 no.3
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• pp.220-227
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• 2005

Doxorubicin is an anthracycline-family polyketide compound with a very potent anti-cancer activity, typically produced by Streptomyces peucetius. To understand the potential target biosynthetic genes critical for the doxorubicin everproduction, a doxorubicin-specific DNA microarray chip was fabricated and applied to reveal the growth-phase-dependent expression profiles of biosynthetic genes from two doxorubicin-overproducing strains along with the wild-type strain. Two doxorubicin-overproducing 5. peucetius strains were generated via over-expression of a dnrl (a doxorubicin-specific positive regulatory gene) and a doxA (a gene involved in the conversion from daunorubicin to doxorubicin) using a streptomycetes high expression vector containing a strong ermE promoter. Each doxorubicin-overproducing strain was quantitatively compared with the wild-type doxorubicin producer based on the growth-phase-dependent doxorubicin productivity as well as doxorubicin biosynthetic gene expression profiles. The doxorubicin-specific DNA microarray chip data revealed the early-and-steady expressions of the doxorubicin-specific regulatory gene (dnrl), the doxorubicin resistance genes (drrA, drrB, drrC), and the doxorubicin deoxysugar biosynthetic gene (dnmL) are critical for the doxorubicin overproduction in S. peucetius. These results provide that the relationship between the growth-phase-dependent doxorubicin productivity and the doxorubicin biosynthetic gene expression profiles should lead us a rational design of molecular genetic strain improvement strategy.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.139-150
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• 2017

Open economy tightly works with foreign economy. This paper investigates the effect of the shock of foreign bond yield on the credit spreads of domestic corporate bonds in Korea. Foreign bond is referred to as US treasury bond. Credit spreads are defined with the difference between log yields of domestic corporate bonds and log yield of Korea treasury bond. With the data of monthly three-year AA- and BBB- corporate bond yields- ratings, monthly three-year Korean treasury bond yields, monthly US dollar foreign exchange rates, and monthly three-year US Treasury bond yields during the period from October 2000 to September 2014 including global financial crisis period, the paper documents the results as follow. First of all, the yield of Korean treasury and the credit spreads are very sensitive to the increase in the level and the volatility of the yield of the US treasury bond. Changes in the level and the volatility little affect the change of the exchange rate. Second, the change in the level and the volatility negatively affect the level of Korean treasury bond yields but lead to the increase in the level of Korean treasury bond yields at the same time. Third, there exist time lags of the increases of credit spreads by the increase in the level and the volatility. These imply that credit spreads and bond yields are very sensitive to the change in the yields of foreign bonds such as US treasury bond.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.55-62
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• 2005

In this paper, we propose the face recognition system using HNMA(Hippocampal Neuron Modeling Algorithm) which can remodel the cerebral cortex and hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature-vector of the face images very fast and construct the optimized feature each image. The system is composed of two parts. One is feature-extraction and the other is teaming and recognition. In the feature extraction part, it can construct good-classified features applying PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis) in order. In the learning part, it cm table the features of the image data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in the dentate gyrus region and remove the noise through the associate memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are face changes, pose changes and low quality image. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.255-263
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• 2014

Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.