• Journal of Embryo Transfer
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• v.30 no.1
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• pp.45-50
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• 2015

The purpose of this study is to produce wanted sex progeny of genetically confined White Hanwoo (albinism) with preselected sex sperm. One bull of White Hanwoo was chosen for semen donor and X sperm was sorted by MoFlo XDP cell sorter. To compare the pregnancy and birth rates, KPN straw was used as control, total number of unsorted sperm was $20{\times}10^6/straw$. Sexed X frozen semen with $20{\times}10^6$ cells or $4{\times}10^6$ cells per straw were in seminated twice on Hanwoo heifers. The abnormality of the sexed X semen was $24.9{\pm}7.31%$ and distal reflex abnormality of mid piece was significantly (p<0.05) higher (11.7%) compared with that of KPN 768 (5.6%). There were no differences on the pregnancy and birth rates between $2{\times}10^6$ cells or $4{\times}10^6$ cells of X-sperm but KPN semen showed significant differences (p<0.05). The pregnancy rates of KPN 768, $2{\times}10^6$ cells and $4{\times}10^6$ cells X-sperm of White Hanwoo cattle were 85.0%, 26.3% and 50%. The birth rates were 80.0%, 15.8% and 21.4%, respectively. The female offspring rates of KPN 768, $2{\times}10^6$ cells and $4{\times}10^6$ cells X-sperm of White Hanwoo cattle were 43.8%, 100% and 100% (p<0.05). These results indicated that sex sorted White Hanwoo could be used for the production of wanted progeny with $2{\times}10^6$ cells/straw for AI. To increase the efficiency of calf production, the sperm number of sex sorted semen will be optimized for sex selection of White Hanwoo progeny.

• Journal of Yeungnam Medical Science
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• v.10 no.1
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• pp.48-57
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• 1993

The purpose of this study was to investigate the characteristics of personality dimensions of schizophrenics. Subjects in this study were 71 chronic schizophrenics, 59 acute schizophrenics, and 87 normal persons. All subjects was asked to respond to EPQ(Korean Version Eysenck Personality Questionnaire). Collected data were analyzed by using the statistical techniques of discriminant function analysis, t-test and one-way variable analysis. The results were as follows : Acute and chronic schizophrenics were higher than normal persons on psychoticism score. However, there was no significant difference between chronic and acute schizophrenics on the psychoticism score. Discriminant analysis was adopted to identify the scales in EPQ that were most effective in discriminating between normals and schizophrenics. Psychoticism of EPQ function was the most effective variable that discriminates between the normals and the schizophrenics.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.99-104
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• 2019

Recently, modern people are increasing the incidence of various musculoskeletal diseases due to wrong posture. Prevention is possible through proper posture habit, but it is not easy to recognize posture by oneself. Various studies have been conducted to monitor persistent posture in daily life, but most studies using constrained measurement methods and high-cost measurement equipment are not suitable for daily life. In this paper, we implemented a posture discrimination system using a FSR sensor array that can induce posture correction spontaneously through sitting posture monitoring in daily life. The implemented system is designed as a cushion type so it is easy to apply to existing chair. In addition, it can identify five most common postures in everyday life, and can monitor real-time through Android-based smart-phone monitoring application. For the performance evaluation of the implemented system, each posture was measured 50 times repeatedly. As a result, 97.6% accuracy was confirmed.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.13-22
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• 2008

This paper proposes an efficient ROI code block discrimination algorithm for dynamic ROI coding. The proposed algorithm calculates the girth of the ROI only with some mask information in consideration of the characteristics of the shape of the ROI for reducing a ROI code block discrimination time, and this proposed algorithm discriminates whether there is a ROI code block by the girth and the critical value of the ROI. Also, this discrimination algorithm is capable of treating the coefficients of the background within a ROI code block preferentially and controlling a loss by controlling the threshold value of the ROI. In order to demonstrate the utility of the proposed method, this paper conducted a comparative experiment of the proposed method with the existing methods. As a result of this experiment, it was confirmed that the proposed method was superior to the conventional methods in terms of quality and speed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.427-430
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• 2007

Many victims and property damages are caused in fires every year. In this paper, flame and smoke detection algorithm by using image processing technique is proposed to early alarm fires. The first decision of proposed algorithms is to check candidate of flame region with its unique color distribution distinguished from artificial lights. If it is not a flame region then we can check to candidate of smoke region by measuring difference of brightness and chroma at present frame. If we just check flame and smoke with only simple brightness and hue, we will occasionally get false alarms. Therefore we also use motion information about candidate of flame and smoke regions. Finally, to determine the flame after motion detection, activity information is used. And in order to determine the smoke, edges detection method is adopted. As a result of simulation with real CCTV video signal, it is shown that the proposed algorithm is useful for early fire recognition.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.867-876
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• 2017

Datasets with small n and large p are often found in various fields and the analysis of the datasets is still a challenge in statistics. Discriminant analysis models for such datasets were recently developed in classification problems. One approach of those models tries to detect dimensions that distinguish between groups well and the number of the detected dimensions is typically smaller than p. In such models, the number of dimensions is important because the prediction and visualization of data and can be usually determined by the K-fold cross-validation (CV). However, in sparse data scenarios, the CV is not reliable for determining the optimal number of dimensions since there can be only a few observations for each fold. Thus, we propose a method to determine the number of dimensions using a measure based on the standardized distance between the mean values of each group in the reduced dimensions. The proposed method is verified through simulations.

• Korean Journal of Food Science and Technology
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• v.35 no.4
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• pp.653-659
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• 2003

A 20 MHz pulsed NMR systems was employed to discriminate the geographical origin of soybeans and black beans (yak-kong) from Korea and foreign countries. Crude fat contents measured by soxhlet method were significantly (p<0.05) different between domestic and imported soybeans. Moisture and crude protein contents, measured by AOAC, were significantly different between domestic and imported black beans. In soybeans, values by solid fat content method and Carr-Purcell-Meiboom-Gill (CPMG) method using 20 MHz pulsed NMR showed the significant difference among soybeans from various the geographical origins. In black beans (yak-kong), NMR values measured by NMR except $T_1$ SR pulse sequence revealed the significant difference by the geographical origins. The habitat of soybeans and black beans could be identified by canonical discriminant analysis of chemical composition with $70{\sim}91.7\;%$ accuracy. Low field NMR data followed by discriminant analysis, however, granted the 100% of accuracy for classification of soybeans.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1010-1015
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• 2008

The choice of RFID system is recently progressing(being) rapidly at various field. For the sake of RFID system popularization, However, We should solve privacy invasion to gain the pirated information of RFID tag. There is the safest M Ohkubos's skill among preexistent studying to solve these problems. But, this skill has a problem that demands a immense calculation capability caused an increase in tag number when we discriminate tags. So, This paper proposes the way of transplant to Grid environment for keeping Privacy Protection up and reducing the Tag Identification Time. And, We propose the Tag Identification Process Model to apply Even Division Algorithm to separate SP with same site in each node. If the proposed model works in Grid environment at once, it would reduce the time to identify tags to 1/k.

• The Journal of Bigdata
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• v.3 no.2
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• pp.11-18
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• 2018

This study is a study on domain automatic classification for domain - based quality diagnosis which is a key element of big data quality diagnosis. With the increase of the value and utilization of Big Data and the rise of the Fourth Industrial Revolution, the world is making efforts to create new value by utilizing big data in various fields converged with IT such as law, medical, and finance. However, analysis based on low-reliability data results in critical problems in both the process and the result, and it is also difficult to believe that judgments based on the analysis results. Although the need of highly reliable data has also increased, research on the quality of data and its results have been insufficient. The purpose of this study is to shorten the work time to automizing the domain classification work which was performed from manually to using machine learning in the domain - based quality diagnosis, which is a key element of diagnostic evaluation for improving data quality. Extracts information about the characteristics of the data that is stored in the database and identifies the domain, and then featurize it, and automizes the domain classification using machine learning. We will use it for big data quality diagnosis and contribute to quality improvement.

• Journal of Life Science
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• v.27 no.11
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• pp.1331-1339
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• 2017

DNA barcoding is the identification of a species based on the DNA sequence of a fragment of the cytochrome C oxidase subunit I (COI) gene in the mitochondrial genome. It is widely applied to assist with the sustainable development of fishery-product resources and the protection of fish biodiversity. This study attempted to verify horse-head fish (Branchiostegus japonicus) and fake horse-head fish (Branchiostegus albus) species, which are commonly consumed in Korea. For the validation of the two species, a real-time PCR method was developed based on the species' mitochondrial DNA genome. Inter-species variations in mitochondrial DNA were observed in a bioinformatics analysis of the mitochondrial genomic DNA sequences of the two species. Some highly conserved regions and a few other regions were identified in the mitochondrial COI of the species. In order to test whether variations in the sequences were definitive, primers that targeted the varied regions of COI were designed and applied to amplify the DNA using the real-time PCR system. Threshold-cycle (Ct) range results confirmed that the Ct ranges of the real-time PCR were identical to the expected species of origin. Efficiency, specificity and cross-reactivity assays showed statistically significant differences between the average Ct of B. japonicus DNA ($21.85{\pm}3.599$) and the average Ct of B. albus DNA ($33.49{\pm}1.183$) for confirming B. japonicus. The assays also showed statistically significant differences between the average Ct of B. albus DNA ($22.49{\pm}0.908$) and the average Ct of B. japonicus DNA ($33.93{\pm}0.479$) for confirming B. albus. The methodology was validated by using ten commercial samples. The genomic DNA-based molecular technique that used the real-time PCR was a reliable method for the taxonomic classification of animal tissues.