• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.422-427
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• 1997

Breeding efficiency was investigated to reveal crucial factors for constructing effective breeding system with subdivided populations under equal genetic level. Simulation study of selection experiment was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systems; single population scheme and two population scheme, each of which had the same genetic parameters. Genetic correlations (-0.5 to 0.5) were assumed to be caused only by pleiotropic effect of a gene. Phenotypes of the two traits generated by polygenic effect with additive 36 loci and residuals distributed normally were selected by two traits selection index procedure. Comparing between the single population scheme and the two population scheme, the single population scheme showed higher genetic gain with lower inbreeding coefficient. This result was confirmed particularly for the situation of high selection intensity, high heritability and high degree of unevenness for economic weight. Genetic correlations in the single population scheme were significantly lower than the two population scheme when initial genetic correlation was negative. When terminal crossbreeding for the two population scheme is taken into account, superiority of the two population scheme was suggested. The terminal crossbreeding was effective under the situation of long term selection, existence of moderate inbreeding depression and use of less extreme economic weight.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

• Korean Journal of Plant Resources
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• v.19 no.6
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• pp.677-679
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• 2006

The objectives of this study were to examine the genetic variation of 20-year-old tree height and to estimate heritabilities and genetic gains of Korean white pine. Analysis of variance showed that families and family x block interaction had the significant (p=0.01) effects on tree height. However, family variation appears to be much greater than the variation due to family x block interaction. Individual tree heritability was higher ($h_I^2=0.73$) than family heritability, ($h_F^2=0.83$) therefore, combined selection showed the largest genetic gain (17.76%) in a given equal intensity of selection.

• Bulletin of the Korean Chemical Society
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• v.10 no.3
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• pp.298-302
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• 1989

The strengths of two-photon transitions from the ground state to excited vibronic states in benzene are calculated by using the CNDO/2-U wave functions. The role of vibronic coupling in two-photon absorption process is discussed. The $A_{1{\bar{g}}}-A_{2g}^+$ two-photon transitions, which are forbidden by the identity-forbidden selection rule in single frequency two-photon absorption, are too weak to be experimentally observed even when two photons of different energies are used. It is because the transitions are forbidden also by the pseudo-parity selection rule which are applicable for alternant hydrocarbons such as benzene. It is also shown that the vibronic coupling is not very effective in altering the pseudo-parity property of the electronic state. The strength of the vibronically induced two-photon absorption is strongly affected by the presence of an electronic state from which two-photon absorption can borrow the intensity. It is pointed out that the pseudo-parity selection rule may be violated in such cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.721-726
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• 2004

The image binarization is applied frequently as one part of the preprocessing phase for a variety of image processing techniques such as character recognition and image analysis, etc. The performance of binarization algorithms is determined by the selection of threshold value for binarization, and most of the previous binarization algorithms analyze the intensity distribution of the original images by using the histogram and determine the threshold value using the mean value of Intensity or the intensity value corresponding to the valley of the histogram. The previous algorithms could not get the proper threshold value in the case that doesn't show the bimodal characteristic in the intensity histogram or for the case that tries to separate the feature area from the original image. So, this paper proposed the novel algorithm for image binarization, which, first, segments the intensity range of grayscale images to several intervals and calculates mean value of intensity for each interval, and next, repeats the interval integration until getting the final threshold value. The interval integration of two neighborhood intervals calculates the ratio of the distances between mean value and adjacent boundary value of two intervals and determine as the threshold value of the new integrated interval the intensity value that divides the distance between mean values of two intervals according to the ratio. The experiment for performance evaluation of the proposed binarization algorithm showed that the proposed algorithm generates the more effective threshold value than the previous algorithms.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.25-30
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• 2018

It is extremely lacking and urgently required that the method of constructing the Gene Regulatory Network (GRN) from RNA-Sequencing data (RNA-Seq) because of Big-Data and GRN in Big-Data has obtained substantial observation as the interactions among relevant featured genes and their regulations. We propose newly the computational comparative feature patterns selection method by implementing a minimum-redundancy maximum-relevancy (MRMR) filter the support vector machine-recursive feature elimination (SVM-RFE) with Intensity-dependent normalization (DEGSEQ) as a preprocessor for emphasizing equal preciseness in RNA-seq in Big-Data. We found out the proposed algorithm might be more scalable and convenient because of all libraries in R package and be more improved in terms of the time consuming in Big-Data and minimum-redundancy maximum-relevancy of a set of feature patterns at the same time.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1839-1845
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• 2016

Detecting remote targets is important to active protection system (APS) or infrared search and track (IRST) applications. In normal situation, the well-known constant false alarm rate (CFAR) detector works properly. However, decoys in APS or closely spaced targets in IRST degrade the detection capability by increasing background noise level in the CFAR detector. This paper presents a context aware CFAR detector by the intensity sorting and selection of background region to reduce the effect of neighboring targets that lead to incorrect estimation of background statistics. The existence of neighboring targets can be recognized by intensity sorting where neighboring targets usually show highest ranks. The proposed background statistics (mean, standard deviation) estimation method from median local pixels can be aware of the background context and reduce the effects of the neighboring targets, which increase the signal-to-clutter ratio. The experimental results on the synthetic APS sequence, real adjacent target sequence, and remote pedestrian sequence validated that the proposed method produced an enhanced detection rate with the same false alarm rate compared with the hysteresis-CFAR (H-CFAR) detection.

• Atmosphere
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• v.23 no.4
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• pp.413-424
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• 2013

Urban Heat Island (UHI) intensity is one of vital parameters in studying urban boundary layer meteorology as well as urban planning. Because the UHI intensity is defined as air temperature difference between urban and rural sites, an objective sites selection criterion is necessary for proper quantification of the spatial variations of the UHI intensity. This study quantified the UHI intensity and its spatial pattern, and then analyzed their connections with urban structure and metabolism in Seoul metropolitan area where many kinds of land use and land cover types coexist. In this study, screen-level temperature data in non-precipitation day conditions observed from 29 automatic weather stations (AWS) in Seoul were analyzed to delineate the characteristics of UHI. For quality control of the data, gap test, limit test, and step test based on guideline of World Meteorological Organization were conducted. After classifying all stations by their own local climatological properties, UHI intensity and diurnal temperature range (DTR) are calculated, and then their seasonal patterns are discussed. Maximum UHI intensity was $4.3^{\circ}C$ in autumn and minimum was $3.6^{\circ}C$ in spring. Maximum DTR appeared in autumn as $3.8^{\circ}C$, but minimum was $2.3^{\circ}C$ in summer. UHI intensity and DTR showed large variations with different local climate zones. Despite limited information on accuracy and exposure errors of the automatic weather stations, the observed data from AWS network represented theoretical UHI intensities with difference local climate zone in Seoul.

• Journal of Korean Academy of Nursing
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• v.21 no.3
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• pp.339-348
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• 1991

The study problem was to determine the reliability of the Stewart pain circle measurement tool with Korean subjects. The purpose was to assess the tool for potential use in research in Korea. The subjects were 95 primary school students and 103 university students in Seoul. The study was conducted from May to June 1990, using Stewart's pain color circle tool. To determine the difference in the rated intensity of the order of the pain color circles, statistical mean and standard deviation were employed. Item reliability and test - retest reliability were used to test for reliability. ANOVA and t-test were used to explore for differences in the rated intensity of the order of the pain color circles according to the subjects' general characteristics. The findings were as follows ; 1. Higher level pain intensity was assigned to color circle numbers 2, 4, and 6 (These contain large amounts of color). Lower level pain intensity was assigned to numbers 1, 3, and 5(These contain small amounts of color). Higher and lower levels of pain intensity selection patterns were the same as Stewart's but the highest rating of pain was different. The highest pain intensity rating was given to the color red in this study instead of black as in Stewart's test. 2. University students and primary school students' ratings were not very difteferent. 3. Pain color circle reliability was $\alpha$＝0.3468, Test - retest reliability was supported (t＝0.02~0.97, p＝0.337~0.988) 4. Differences in the rating of the pain intensity order were related to the subjects' age and sex, but not to religion. It was concluded that the pain color circle measurement tool is worth for further study as a research instrument with both Korean adult and child clients for validity and reliability.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.