• Journal of Animal Science and Technology
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• v.46 no.1
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• pp.1-6
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• 2004

This study was conducted to investigate novel genetic variations of MCIR^*3 allele. In general, white spotting or white belt on a black backgroud in pigs is determined by the E$^p$ allele at the MCIR/Extention locus. E$^p$ shares a frameshift mutation with the E$^{D2}$ allele for dominant black color. An oligonucleotide primer set was designed to amplify complete coding sequence of the porcine MCIR gene. The MCIR coding sequences obtained from five breeds those were Landrace(white). Yorkshire(white), Hampshire(belt), Berkshire(spot) and Jeju native black pigs(black), were used for this study. A multiple sequence alignment of the MCIR coding region using Clustal W was performed. The total length of the MCIR coding sequence ranged from 963 to 966 base pairs(bp) among the selected breeds. The sequence analysis of the complete coding region of MCIR was revealed that Hampshire and Jeju native black pig have 3 cytosines deletion and Birkshire has 2 cytosines deletion at codon 23(nt68) in Extention loci. Besides the finding, there were three different missense mutations and a frameshift mutation in the MCIR coding region.

• Journal of Internet of Things and Convergence
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• v.4 no.2
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• pp.21-28
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• 2018

I investigated that ALK receptor tyrosine kinase (ALK) gene polymorphisms were contributed to susceptibility to ICH in Korean population. I recruited 156 ICH patients and 425 healthy controls for this study, respectively. rs1881421, rs1881420, rs3795850, and rs2246745 single nucleotide polymorphisms (SNPs) were genotyped. The genotype and allele distributions of tested four SNPs was analyzed using the SNPStats, SPSS 22.0, and the Haploview v.4.2 software. The Odd's ratios (OR), 95% confidence intervals (CI), and P values were calculated in allele and genotype models. I found that rs1881421, rs1881420, rs3795850, and rs2246745 SNPs of ALK gene (rs1881421, OR=2.02, 95% CI=1.54-2.64, p<0.001; rs1881420, OR=0.53, 95% CI=1.16-2.01, p=0.003; rs3795850, OR=1.54, 95% CI=1.17-2.02, p=0.002; rs2246745, OR=1.95, 95% CI=1.46-2.60, p<0.001 in each allele analysis). And distributions of CC, GT, and GC haplotypes between the ICH group and the control group also showed significant association with ICH (CC haplotype, p<0.001; GT haplotype, p=0.006; GC haplotype, p<0.001). These minor alleles of tested four SNPs in ALK gene were contributed to increased risk of development for ICH. Our findings suggested that the ALK gene may be a risk factor for susceptibility to ICH.The Korea Internet of Things Society.

• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.69-78
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• 2004

In this study, the back analysis program was developed by applying the genetic algorithm, one of artificial intelligence fields, to the direct method. The optimization process which has influence on the efficiency of the direct method was modulated with genetic algorithm. On conditions that the displacement computed by forward analysis for a certain rock mass model was the same as the displacement measured at the tunnel section, back analysis was executed to verify the validity of the program. Usefulness of the program was confirmed by comparing relative errors calculated by back analysis, which is carried out under the same rock mass conditions as analysis model of Gens et at (1987), one of back analysis case in the past. We estimated the total displacement occurring by tunnelling with the crown settlement and convergence measured at the working faces in three tunnel sites of Kyungbu Express railway. Those data measured at the working face are used for back analysis as the input data after confidence test. As the results of the back analysis, we comprehended the tendency of tunnel behaviors with comparing the respective deformation characteristics obtained by the measurement at the working face and by back analysis. Also the usefulness and applicability of the back analysis program developed in this study were verified.

• Korean Journal of Microbiology
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• v.32 no.4
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• pp.264-270
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• 1994

A gene coding for a novel putative $\sigma$ factor of RNA polymerase has been identified from Streptomyces coelicolor A3(2) using Escherichia coli rpoS gene fragment as a probe. The 486 bp rpoS gene fragment was amplified from E. coli genomic DNA by PCR with two synthetic oligonucleotides, the sequences of which were deduced from the amino acid sequences in the regions 2.3 and 4.2 conserved among various bacterial factors. When E. coli genomic DNA fragments were hybridized with cloned rpoS probe, only one band corresponding to rpoS gene (3.2 kb PvuII fragment or 2.3 kb KpnI fragment) was detected. In S. coelicolor, however, two bands were detected both in PvuII digested DNA and SalI digested DNA. 3.5 kb PvuII fragment which binds the rpoS gene probe was cloned (pMS1) from the sublibrary, and the nucleotide sequences of 1.0 kb BamH'/HincII subclone (pBH2) was partially determined. The nucleotide sequences revealed extensive similarity to other $\sigma$ factor genes of S. coelicolor (hrdA, hrdB, hrdC, hrdD), S. aureofaciens (hrdA, hrdB, hrdC, hrdD), Synechococcus species, Pseudomonas aeruginosa, Stigmatella aurantiaca, and Anabaena species. The nucleotide sequences in regions 1.2 and 4 were compared with the corresponding regions of 5 known ${\sigma}$ factor genes of S. coelicolor by multiple alignment. It turned out that the cloned gene is most closely related to hrdA showing 88% amino acid similarity in region 1.2 and 75% in region 4.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.69-88
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• 2000

One of the most important factors on the performance of the distributed systems is the effective distribution of the software components, There have been a lot of researches on partitioning and allocating the task-based system, while the studies on the allocating the objects of the object-oriented system into the distributed object environments are very little relatively. In this paper. we defines the graph model for partitioning the existing C++ application and allocating the C++ objects into CORBA-base distributed system, In addition, we propose a distributed object allocation algorithm based on this graph model. The performance of distributed systems is determined by the concurrency between objects, the load balance among the processors and the communication cost on the networks. To search for the solutions optimizing the above three factors simultaneously, the object allocation algorithm of this paper is based on the Niched Pareto Genetic Algorithm (NPGA). We performed the experiment on the typical C++ application and CORBA system to prove the effectiveness of our graph model and our object allocation algorithm.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.1
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• pp.73-81
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• 2002

This study is performed to evaluate and design the vibration characteristics of the onboard machinery with resilient mountings. To reduce the vibration revel of onboard machinery with resilient mountings, it is important to evaluate and, if necessary modify vibration characteristics of the resilient mountings. In this study we have developed a program to calculate natural frequencies of the machinery with resilient mountings, forced vibration levels due to internal excitation force of the machinery itself and external excitation forces of the main engine and the propeller, and the force and motion transmissibility of the resilient mountings. The developed program can be also applied to optimal design of the resilient mountings for obtaining a target natural frequency and for achieving a minimum forced vibration level at the center of gravity of the machinery.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.167-174
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• 2007

This study proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the and the life-cycle cost and performance as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

• Composites Research
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• v.21 no.1
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• pp.1-7
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• 2008

Composite vessels for high pressure gas storage are commonly used these days because of their competitive weight reduction ability maintaining strong mechanical properties. To supplement permeability of composite under high pressure, it is usually lined by metal, which is called a Type 3 vessel. However, it has many difficulties to design the Type 3 vessel because of its complex geometry, fabrication process variables, etc. In this study, therefore, GUI (graphic user interface) optimal design code for Type 3 vessels was developed based on semi-geodesic algorithm in which various factors of geometry and fabrication variables are considered and genetic algorithm for optimization. In addition, hydrogen vessels for 350/700 bar that can be applied to FCVs(fuel cell vehicles) were designed using this code for verification.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.104-104
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• 2022

임진강 수계는 북측 지역이 다수를 차지하는 유역 특성으로 예고 없는 상류 급방류, 강우 등으로 인해 댐 운영에 근본적 어려움이 있으며, 이에 따라 홍수조절지 및 댐 하류 계측 가능 지역의 취득 자료를 고려한 하천 수위 변화에 대한 사전 예측을 필요로 하고 있다. 홍수기 하천 도달시간 및 수위예측 기법으로는 물리 기반 및 데이터 기반 모델들이 다양하게 연구되어 왔으며, 일부 연구성과들은 현업에 활용하고 있다. 물리기반 모델은 하천 지형 변화에 대한 자료 취득 및 분석에 많은 시간을 요하는 단점은 있으나, 설명 가능한 모델을 구현할 수 있을 것으로 사료 된다. 반면, 데이터 기반 인공지능 모델은 짧은 시간 및 비용으로 모델을 개발할 수 있으나, 복잡한 알고리즘구현 시 설명이 불가하여 일관성을 의심 받을 수 있다. 본 논문에서는 홍수 도달시간과 하류 수위 상승에 대하여 설명 가능한 인공지능 알고리즘 및 시뮬레이션 프로그램을 개발하고자 하였다. 홍수 도달시간 예측은 기존 조견표 방식에서 고려하지 않았던 홍수파의 영향을 추가 변수화 하고, 데이터의 전후처리를 통하여 도달시간을 예측하였다. 실시간 하류 수위 예측은 댐 방류량, 주변 강우, 조위 등을 고려하여 도달시간 후 수위를 예측할 수 있도록 구현하였으며, 자료 동화 기술을 일부 적용하였다. 미래 방류조건에 대한 시뮬레이션을 위해서는 미래 방류량, 예상 강우 입력 시 하천 지점별 수위 상승을 예측할 수 있도록 알고리즘 및 프로그램을 개발하였다. 이를 구현하기 위하여 다양한 인공지능 알고리즘을 이용한 학습, 유전자 알고리즘을 이용한 가중치 학습 제한 조건내 최적화, 수위파와 조위파의 중첩의 정리 등을 이용하여 예측 정확도 및 신뢰성을 제고 하였다. 인공지능 분석결과의 현업활용성 제고를 위하여 시뮬레이터 프로그램을 개발하여 현업에 적용하였다.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.73-82
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• 2002

It is difficult to find the shortest paths using existing algorithms (Dijkstra, Floyd-Warshall algorithm, and etc) in high complex and large size real traffic networks The objective of this paper is to develop an evolution program to find the multiple shortest paths within reasonable time in these networks including turn-restrictions, U-turns, and etc.