• Journal of Information Processing Systems
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• 제13권5호
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• pp.1089-1102
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• 2017

In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

• International journal of thyroidology
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• 제11권2호
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• pp.123-129
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• 2018

Background and Objectives: Hypermethylation of the tumor suppressor gene RASSF1A and activating mutation of BRAF gene have been recently reported in thyroid cancers. To investigate the role of these two epigenetic and genetic alterations in thyroid tumor progression, methylation of RASSF1A and BRAF mutation were examined in thyroid tumors. Materials and Methods: During 2007 to 2017, 69 papillary carcinomas, 18 nodular hyperplasia, 3 follicular carcinomas, and 13 follicular adenomas were selected. The methylation-specific polymerase chain reaction (MSP) technique was used in detecting RASSF1A methylation and polymerase chain reaction (PCR)-single-stranded conformation polymorphism and sequencing were used for BRAF gene mutation study. Results: The hypermethylation of the RASSF1A gene was found in 84.6%, 100% and 57.9% of follicular adenomas, follicular carcinomas, and papillary carcinomas, respectively. Nodular hyperplasia showed a hypermethylation in 33.3%. The BRAF mutation at V600E was found in 60.7% of papillary carcinoma and 27.0% of nodular hyperplasia, but none of follicular neoplasms. The BRAF mutation was correlated with the lymph node metastasis and MACIS clinical stage. There is an inverse correlation between RASSF1A methylation and BRAF mutation in thyroid lesions. Conclusion: Epigenetic inactivation of RASSF1A through aberrant methylation is considered to be an early step in thyroid tumorigenesis, and the BRAF mutation plays an important role in the carcinogenesis of papillary carcinoma, providing a genetic marker.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (3)
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• pp.744-746
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• 1998

외판원(Traveling Salesman Problem)는 계산 복잡도가 매우 높으므로 이를 해결하려는 다양한 방법들이 제시되어 왔다. 최근에는 특히 휴리스틱(Heuristic) 에 기반한 유전 알고리즘(Genetic Algorithm)에 위한 방법이 관심을 집중시키고 있고, 이를 위한 다양한 교잡(Crossiver)연산자와 돌연변이(Mutation) 연산자들이 발표되고 있다. 돌연변이연산자는 지역해에 빠지는 것을 방지하며, 유용한 유전 특성을 잃어버릴 위험이 있는 교잡 연산자의 단점을 보완할 수 있다. 본 논문에서는 새로운 돌연변이 연산자를 개발하여 적용한 유전 알고리즘으로 외판원 문제를 해결한다.

• Clinical and Experimental Pediatrics
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• 제59권sup1호
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• pp.116-120
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• 2016

Congenital hyperinsulinism (CHI) is a rare condition that can cause irreversible brain damage during the neonatal period owing to the associated hypoglycemia. Hypoglycemia in CHI occurs secondary to the dysregulation of insulin secretion. CHI has been established as a genetic disorder of islet-cell hyperplasia, associated with a mutation of the ABCC8 or KCNJ11 genes, which encode the sulfonylurea receptor 1 and the inward rectifying potassium channel (Kir6.2) subunit of the ATP-sensitive potassium channel, respectively. We report the case of a female newborn infant who presented with repetitive seizures and episodes of apnea after birth, because of hypoglycemia. Investigations revealed hypoglycemia with hyperinsulinemia, but no ketone bodies, and a low level of free fatty acids. High dose glucose infusion, enteral feeding, and medications could not maintain the patient's serum glucose level. Genetic testing revealed a new variation of ABCC8 mutation. Therefore, we report this case of CHI caused by a novel mutation of ABCC8 in a half-Korean newborn infant with diazoxide-unresponsive hyperinsulinemic hypoglycemia.

• 한국정보통신학회논문지
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• 제8권7호
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• pp.1553-1557
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• 2004

임베디드 하드웨어 유전자 알고리즘을 위한 실시간 처리 시스템을 설계하였다. 제안된 시스템은 유전자 알고리즘의 기본 모듈인 selection, crossover, 및 mutation과 evaluation을 병행적으로 동작시키기 위해서 이중 프로세서로 구현하였다. 구현된 시스템은 두개의 Xscale 프로세서와 진화 하드웨어가 내장된 FPGA 로 구성되었다. 또한 본 시스템은 유전자 알고리즘의 기본 모듈 수행이 두 개의 프로세서에 자동으로 균등 배분되는 구조를 지니고 있어, 유전자 알고리즘 처리의 효율성을 극대화 할 수 있다. 제안된 임베디드 하드웨어 유전자 알고리즘 처리 시스템은 임베디드 리눅스 운영체제에서 수행되며 진화 하드웨어에서 실시간으로 처리된다. 또한 제안된 이중 프로세서의 각 프로세서 모듈은 동일한 구조로 가지고 있으므로 여러 개의 모듈을 직렬 연결하여 빠른 하드웨어 유전자 알고리즘 실시간 처리에 그대로 사용될 수 있다.

• 한국CDE학회논문집
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• 제1권3호
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2005년도 생물공학의 동향(XVI)
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• pp.17-17
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• 2005

In this presentation, we will discuss several recent achievements developed in my laboratory for microarray-based diagnosis of human genetic mutations including HNF-1 and BRCA1 mutations. To determine the presence of the genetic mutations in a human sample, we prepared allele-specific oligonucleotide chips from selected mutation sites and generated target probes using a tow-step method for Cy-3 DNA $samples^{1)}$ or in vitro transcription of promoter-tagged PCR products for Cy-3 RNA $samples^{2)}$. Hybridization of the target probes to the chips successfully identified all of the genotypes for the tested sites. For more reliable diagnosis, we also employed single base extension (SBE) reaction and zip-code microarray technique for our strategy. Particularly we developed an efficient PNA zip-code microarray for the detection of $HNF-1{\alpha}$ $mutations^{3)}$. Using multiplex SBE reactions and zip-code strategy, we were able to correctly diagnose several mutation sites in exon 2 of $HNF-1{\alpha}$ with a wild-type and mutant including a MODY3 patient. These works represent successful applications of DNA microarray technology for the diagnosis of human genetic mutations.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.233-236
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• 2007

A new evolution method for strong exploration and strong exploitation termed queen-bee and mutant-bee evolution is proposed based on the previous queen-bee evolution [1]. Even though the queen-bee evolution has shown very good performances, two parameters for strong mutation are added to the genetic algorithms. This makes the application of genetic algorithms with queen-bee evolution difficult because the values of the two parameters are empirically decided by a trial-and-error method without a systematic method. The queen-bee and mutant-bee evolution has no this problem because it does not need additional parameters for strong mutation. Experimental results with typical problems showed that the queen-bee and mutant-bee evolution produced nearly similar results to the best ones of queen-bee evolution even though it didn't need to select proper values of additional parameters.

• Genomics & Informatics
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• 제16권1호
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• pp.14-20
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• 2018

Despite the importance of mutation rate, some difficulties exist in estimating it. Next-generation sequencing (NGS) data yields large numbers of single-nucleotide polymorphisms, which can make it feasible to estimate substitution rates. The genetic substitution rates of Hanwoo and Holstein cattle were estimated using NGS data. Our main findings was to calculate the gene's substitution rates. Through estimation of genetic substitution rates, we found: diving region of altered substitution density exists. This region may indicate a boundary between protected and unprotected genes. The protected region is mainly associated with the gene ontology terms of regulatory genes. The genes that distinguish Hanwoo from Holstein in terms of substitution rate predominantly have gene ontology terms related to blood and circulatory system. This might imply that Hanwoo and Holstein evolved with dissimilar mutation rates and processes after domestication. The difference in meat quality between Hanwoo and Holstein could originate from differential evolution of the genes related to these blood and circulatory system ontology terms.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권4호
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.