• Molecules and Cells
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• v.20 no.3
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• pp.385-391
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• 2005

As a first step towards identifying genes involving in the signal transduction pathways mediating rice blast resistance, we isolated 3 mutants lines that showed enhanced susceptibility to rice blast KJ105 (91-033) from a T-DNA insertion library of the japonica rice cultivar, Hwayeong. Since none of the susceptible phenotypes co-segregated with the T-DNA insertion we adapted a map-based cloning strategy to isolate the gene(s) responsible for the enhanced susceptibility of the Hwayeong mutants. A genetic mapping population was produced by crossing the resistant wild type Hwayeong with the susceptible cultivar, Nagdong. Chi-square analysis of the $F_2$ segregating population indicated that resistance in Hwayeong was controlled by a single major gene that we tentatively named Pi-hy. Randomly selected susceptible plants in the $F_2$ population were used to build an initial map of Pi-hy. The SSLP marker RM2265 on chromosome 2 was closely linked to resistance. High resolution mapping using 105 $F_2$ plants revealed that the resistance gene was tightly linked, or identical, to Pib, a resistance gene with a nucleotide binding sequence and leucine-rich repeats (NB-LRR) previously isolated. Sequence analysis of the Pib locus amplified from three susceptible mutants revealed lesions within this gene, demonstrating that the Pi-hy gene is Pib. The Pib mutations in 1D-22-10-13, 1D-54-16-8, and 1C-143-16-1 were, respectively, a missense mutation in the conserved NB domain 3, a nonsense mutation in the 5th LRR, and a nonsense mutation in the C terminus following the LRRs that causes a small deletion of the C terminus. These findings provide evidence that NB domain 3 and the C terminus are required for full activity of the plant R gene. They also suggest that alterations of the resistance gene can cause major differences in pathogen specificity by affecting interactions with an avirulence factor.

• Water for future
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• v.15 no.2
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• pp.23-32
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• 1982

This study is to clarify the relation between the maximum 24 hour rainfall and the daily rainfall of a designated time 10 A.M., using the 506 rainfall datum from 32 rain-guage stations on the Han river basin covering a period of 7 years and trying to estimate the ratio of two data in accordance with the amount of rainfall respectively. The Mononobe's formula, which is widely used in this country, has the value of 2/3 power in it. The "n" was considered instead of 2/3 and derivated for each guaging station. The results make it possible to establish the Ison-n value map, and show that the n value is affected mainly by the topographical conditions. The daily rainfall of a designated time can be modified by the results of this study and expressed as Y(%)=218.25/R$$. But in the case of exceeding 200mm/day, it is recommended to use the 110% for safety. On the problems of intensity-duration concerned with the planning of public works, the formula can be expressed as r$$=fRday/24.(24/t)$$, where "f" is Y(%) divided by 100. As this study was done with the datum within shor period, it is necessary to study more about the "n" and "f" value so as to get previse value in the future.o as to get previse value in the future.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.154-158
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• 1999

Purpose : The purpose of this study was to find the optimum TE value for enhancing $T_2^{*}$ weighting effect and minimizing the SNR degradation and to compare the BOLD effects according to the changes of TE in 1.5T and 3.0T MRI systems. Materials and Methods : Healthy normal volunteers (eight males and two females with 24-38 years old) participated in this study. Each volunteer was asked to perform a simple finger-tapping task (sequential opposition of thumb to each of the other four fingers) with right hand with a mean frequency of about 2Hz. The stimulus was initially off for 3 images and was then alternatively switched on and off for 2 cycles of 6 images. Images were acquired on the 1.5T and 3.0T MRI with the FLASH (fast low angle shot) pulse sequence (TR : 100ms, FA : $20^{\circ}$, FOV : 230mm) that was used with 26, 36, 46, 56, 66, 76ms of TE times in 1.5T and 16, 26, 36, 46, 56, 66ms of TE in 3.0T MRI system. After the completion of scan, MR images were transferred into a PC and processed with a home-made analysis program based on the correlation coefficient method with the threshold value of 0.45. To search for the optimum TE value in fMRI, the difference between the activation and the rest by the susceptibility change for each TE was used in 1.5T and 3.0T respectively. In addition, the functional $T_2^{*}$ map was calculated to quantify susceptibility change. Results : The calculated optimum TE for fMRI was $61.89{\pm}2.68$ at 1.5T and $47.64{\pm}13.34$ at 3.0T. The maximum percentage of signal intensity change due to the susceptibility effect inactivation region was 3.36% at TE 66ms in 1.5T 10.05% at TE 46ms in 3.0T, respectively. The signal intensity change of 3.0T was about 3 times bigger than of 1.5T. The calculated optimum TE value was consistent with TE values which were obtained from the maximum signal change for each TE. Conclusion : In this study, the 3.0T MRI was clearly more sensitive, about three times bigger than the 1.5T in detecting the susceptibility due to the deoxyhemoglobin level change in the functional MR imaging. So the 3.0T fMRI I ore useful than 1.5T.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.9
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• pp.1184-1191
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• 2011

We attempted to generate a linkage map using Illumina Porcine 60K SNP Beadchip genotypes of the $F_2$ offspring from Korean native pig (KNP) crossed with Yorkshire (YS) pig, and to identify quantitative trait loci (QTL) using the line-cross model. Among the genotype information of the 62,136 SNPs obtained from the high-density SNP analysis, 45,308 SNPs were used to select informative markers with allelic frequencies >0.7 between the KNP (n = 16) and YS (n = 8) F0 animals. Of the selected SNP markers, a final set of 500 SNPs with polymorphic information contents (PIC) values of >0.300 in the $F_2$ groups (n = 252) was used for detection of thirty meat quality-related QTL on chromosomes at the 5% significance level and 10 QTL at the 1% significance level. The QTL for crude protein were detected on SSC2, SSC3, SSC6, SSC9 and SSC12; for intramuscular fat and marbling on SSC2, SSC8, SSC12, SSC14 and SSC18; meat color measurements on SSC1, SSC3, SSC4, SSC5, SSC6, SSC10, SSC11, SSC12, SSC16 and SSC18; water content related measurements in pork were detected on SSC4, SSC6, SSC7, SSC10, SSC12 and SSC14. Additional QTL of pork quality traits such as texture, tenderness and pH were detected on SSC6, SSC12, SSC13 and SSC16. The most important chromosomal region of superior pork quality in KNP compared to YS was identified on SSC12. Our results demonstrated that a QTL linkage map of the $F_2$ design in the pig breed can be generated with a selected data set of high density SNP genotypes. The QTL regions detected in this study will provide useful information for identifying genetic factors related to better pork quality in KNP.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.767-788
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• 2010

The purpose of this study was to examine emotional characteristics and to provide information about the special needs of counselling of science gifted in Korea. The subjects were 143 science gifted high school students in Busan that had been tested MBTI and MMPI-A. The distribution map of MBTI type was examined and Pearson's correlation, one-way ANOVA, multiple regression analysis were used to analyse the relation between MBTI and MMPI-A through SPSS 17.0 program. The results showed as follows: first, ENTP, INTP, ISTJ personality types and NT temperament type were the most frequently from the distribution map of MBTI type. Second, F1, F2, F, Hs, D, Pt, Sc and Si scales of MMPI-A were positively related to I preference of MBTI and K and Ma scales of MMPI-A were significantly related to E preference of MBTI from Pearson's correlation. Third, The score of IN group was significantly more high in F1, Hs, D, SC and Si scales of MMPI-A than other group in the relation between two combination preferences of MBTI and scale of MMPI-A. The following results were same; IS group in D, Si scales, EN group in Ma scale, IT group in Hs, D, Pt and S scales, IF group in VRIN, D and Si scales, ET in Ma scale, IJ group in D and Si, IP group in F1, F, Hs, D, Hy, Pt, Sc and Si scales, EJ and EP groups in Ma scale. Finally, I preference of MBTI by F1, F2, F, Hs, D, Pt, Sc and Si scales of MMPI-A, E preference of MBTI by Ma scale of MMPI-A, F preference of MBTI by K scale of MMPI-A and P preference of MBTI by Hy scale of MMPI-A were significantly predicted from multiple regression analysis. Limitations of the current study and the suggestions for further research were offered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.755-778
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• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.2
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• pp.155-160
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• 2008

Several studies have reported quantitative trait loci (QTL) for meat quality on porcine chromosome 2 (http://www.animalgenome.org/QTLdb/pig.html). For application of the molecular genetic information to the pig industry through marker-assisted selection, single nucleotide polymorphism (SNP) markers were analyzed by comparative re-sequencing of polymerase chain reaction (PCR) products of 13 candidate genes with DNA from commercial pig breeds such as Berkshire, Yorkshire, Landrace, Duroc and Korean Native pig. A total of 34 SNPs were identified in 15 PCR products producing an average of one SNP in every 253 bp. PCR restriction fragment length polymorphism (RFLP) assays were developed for 11 SNPs and used to investigate allele frequencies in five commercial pig breeds in Korea. Eight of the SNPs appear to be fixed in at least one of the five pig breeds, which indicates that different selection among pig breeds might be applied to these SNPs. Polymorphisms detected in the PTH, CSF2 and FOLR genes were chosen to genotype a Berkshire-Yorkshire pig breed reference family for linkage and association analyses. Using linkage analysis, PTH and CSF2 loci were mapped to pig chromosome 2, while FOLR was mapped to pig chromosome 9. Association analyses between SNPs in the PTH, CSF2 and FOLR suggested that the CSF2 MboII polymorphism was significantly associated with several pork quality traits in the Berkshire and Yorkshire crossed F2 pigs. Our current findings provide useful SNP marker information to fine map QTL regions on pig chromosome 2 and to clarify the relevance of SNP and quantitative traits in commercial pig populations.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.11
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• pp.1507-1510
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• 2012

Quantitative trait loci (QTL) associated with fat deposition traits in pigs are important gene positions in a chromosome that influence meat quality of pork. For QTL study, a three generation resource population was constructed from a cross between Korean native boars and Landrace sows. A total of 240 F2 animals from intercross of F1 were produced. 80 microsatellite markers covering chromosomes 1 to 10 were selected to genotype the resource population. Intervals between adjacent markers were approximately 19 cM. Linkage analysis was performed using CRIMAP software version 2.4 with a FIXED option to obtain the map distances. For QTL analysis, the public web-based software, QTL express (http://www.qtl.cap.ed.ac.uk) was used. Two significant and two suggestive QTL were identified on SSC 6, 7, and 8 as affecting body fat and IMF traits. For QTL affecting IMF, the most significant association was detected between marker sw71 and sw1881 on SSC 6, and a suggestive QTL was identified between sw268 and sw205 on SSC8. These QTL accounted for 26.58% and 12.31% of the phenotypic variance, respectively. A significant QTL affecting IMF was detected at position 105 cM between markers sw71 and sw1881 on SSC 6.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.414-423
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• 2020

In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).

• The Mathematical Education
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• v.16 no.2
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• pp.22-26
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• 1978

It is shown that a map having an extension to an open map between the Alex-androff base compactifications of its domain and range has a unique such extension. J.S. Wasileski has introduced the Alexandroff base compactifications of Hausdorff spaces endowed with Alexandroff bases. We introduce a definition of morphism between such spaces to obtain a category which we denote by ABC. We prove that the Alexandroff base compactification on objects can be extended to a functor on ABC and that the compact objects give an epireflective subcategory of ABC. For each topological space X there exists a completely regular space $\alpha$X and a surjective continuous function $\alpha$$_{x}$ : Xlongrightarrow$\alpha$X such that for each completely regular space Z and g$\in$C (X, Z) there exists a unique g$\in$C($\alpha$X, 2) with g=g$^{\circ}$$\beta$$_{x}$. Such a pair ($\alpha$$_{x}$, $\alpha$X) is called a completely regularization of X. Let TOP be the category of topological spaces and continuous functions and let CREG be the category of completely regular spaces and continuous functions. The functor $\alpha$ : TOPlongrightarrowCREG is a completely regular reflection functor. For each topological space X there exists a compact Hausdorff space $\beta$X and a dense continuous function $\beta$x : Xlongrightarrow$\beta$X such that for each compact Hausdorff space K and g$\in$C (X, K) there exists a uniqueg$\in$C($\beta$X, K) with g=g$^{\circ}$$\beta$$_{x}$. Such a pair ($\beta$$_{x}$, $\beta$X) is called a Stone-Cech compactification of X. Let COMPT$_2$ be the category of compact Hausdorff spaces and continuous functions. The functor $\beta$ : TOPlongrightarrowCOMPT$_2$ is a compact reflection functor. For each topological space X there exists a realcompact space (equation omitted) and a dense continuous function (equation omitted) such that for each realcompact space Z and g$\in$C(X, 2) there exists a unique g$\in$C (equation omitted) with g=g$^{\circ}$(equation omitted). Such a pair (equation omitted) is called a Hewitt's realcompactification of X. Let RCOM be the category of realcompact spaces and continuous functions. The functor (equation omitted) : TOPlongrightarrowRCOM is a realcompact refection functor. In [2], D. Harris established the existence of a category of spaces and maps on which the Wallman compactification is an epirefiective functor. H. L. Bentley and S. A. Naimpally [1] generalized the result of Harris concerning the functorial properties of the Wallman compactification of a T$_1$-space. J. S. Wasileski [5] constructed a new compactification called Alexandroff base compactification. In order to fix our notations and for the sake of convenience. we begin with recalling reflection and Alexandroff base compactification.