• Interdisciplinary Bio Central
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• 제5권4호
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• pp.8.1-8.3
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• 2013

Unlike the traditional view, it is not mysterious about how G. Mendel chose the seven characters of the pea, Pisum sativum, that he studied. He first chose the pea that met three conditions he set up and repeated experiments for two years. Apparently, he knew that those characters were controlled by countable elements. Then, he derived the prediction on the basis of his idea about the elements, and selected the seven characters that satisfied the prediction. He knew "no prediction no science". In population genetics the Hardy-Weinberg principle is well known and cited in many papers and books. However, Mendel already derived the same principle in his paper, because he was acquainted also with physics and mathematics. Actually, the principle was trivial when they derived, but not at all when Mendel did. It is also well known that Mendel's laws were forgotten and rediscovered at the term of the 19th century. That may not be true either. His laws were internationally well known before the rediscovery. In fact, the 1881-year version of the Encyclopedia Britannica contains his laws.

• Interdisciplinary Bio Central
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• 제5권4호
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• pp.7.1-7.3
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• 2013

This essay describes G. Mendel's life and his law of inheritance. He was born in a poor family in 1822 in a hamlet in Czechs. At that time the Habsburg Empire dominated over the East Europe in which Vienna was the capital. Vienna had thus been the center of culture and learning, and attracted many artists and scholars such as W. Mozart (1756- 1791), L. Beethoven (1770-1827), C. Doppler (1803-1853), S. Freud (1856-1939), G. Mahler (1860-1911), G. Klimt (1862-1918) and E. Schiele (1890-1918). Beethoven came to Vienna to learn from Mozart. Klimt was influence by Schilele. When Mahler consulted Freud about his mental problem, Freud said to him "Your mental condition was not normal, but the condition made you creative. So, do not worry too much about it." Like that, there were many interactions among them, and Mendel was no exception. Though Mendel was poor, he was fortunate in his education and scientific research, because he could have excellent supporters in his family and out of it. He learned mathematics and physics at Vienna University under the guidance of C. Doppler. He was not totally alone when he discovered his law of inheritance. It may not be true either that his law was neglected and rediscovered in the year of 1900. As his one and only paper indicates, he was one of the earliest interdisciplinary scientists.

• 영재교육연구
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• 제21권4호
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• pp.1033-1053
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• 2011

본 연구는 역사적 발견을 이루어낸 과학자 가운데 멘델(Mendel, Gregor Johann, 1822-1884)의 과학적 사고과정을 활용하여 과학영재교육프로그램을 개발하고, 이 프로그램을 학습한 학생들의 문제발견 및 가설설정 능력의 변화를 측정하여, 프로그램의 효과성을 검증하는데 목적을 두었다. 이를 위해 먼저, 멘델이 유전법칙을 확립하는 과정에서 나타낸 과학적 사고과정을 분석하여 특징적 탐구요소를 추출하였다. 추출된 탐구요소 가운데 문제발견과 가설설정을 적용한 프로그램으로서 완두를 활용한 모의실험탐구중심의 과학영재교육프로그램을 개발하였다. 개발한 과학영재교육프로그램은 대학교 부설 과학영재교육원 소속 중학교 1, 2학년 학생 19명(남학생 11명, 여학생 8명)을 대상으로 적용되었다. 적용한 결과, 학생들은 문제발견 능력의 하위요소 융통성, 정교성, 독창성이 신장되었고, 가설설정 능력의 논리성도 신장되었다. 이에 개발된 과학영재교육프로그램은 중학교 과학영재로 선발된 학생들의 문제발견 및 가설 설정 능력을 향상시키는데 효과가 있는 것으로 고찰되었다.

• 한국수학교육학회지시리즈A:수학교육
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• 제58권3호
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• pp.383-401
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• 2019

고등학교의 통합 교육에서는 각 교과 간의 공통 개념이나 아이디어를 중심 내용으로 다루어야 하기 때문에, 본 연구는 이미 학습한 과학적 개념인 'Mendel의 유전 법칙'을 이용하여 수학을 중심으로 한 통합 수업이 진행될 수 있도록 자료를 개발하고, 개발된 자료에 대하여 CVR 검증을 통하여 전문가 타당성을 확인한 연구이다. 선행연구에 의하면 중학교에서 학습한 과학 개념 중에서 수학과 연계가 비교적 적은 것으로 알려진 내용 중 Mendel의 유전 법칙을 대상으로 하여 연구를 진행하였다. 수학과 다른 과목을 통합한 수업에서는 두 과목 사이의 공통 연결고리가 풍부할수록 수업효과가 좋기 때문에, 본 연구에서는 확률 영역 이외에도 통계 영역의 개념까지 포함하여 조사를 진행하였으며, 이에 근거하여 1차시(100분) 수업에 해당하는 수업 자료를 개발할 수 있었다.

• 한국균학회소식:학술대회논문집
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• 한국균학회 2009년도 춘계학술대회 및 임시총회
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• pp.21-25
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• 2009

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.376-378
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• 2004

Genetic algorithm was motivated by biological evaluation and has been applied to many industrial applications as a powerful tool for mathematical optimizations. In this paper, a new genetic optimization algorithm is proposed. The proposed method is based on Mendel's law, especially dominance and recessive property. Homologous chromosomes are introduced to implement dominance and recessive property compared with the standard genetic algorithm. Because of this property of suggested genetic algorithm, homologous chromosomes looks like the chromosomes for the standard genetic algorithm, so we can use most of existing genetic operations with little effort. This suggested method searches the larger solution area with the less probability of the premature convergence than the standard genetic algorithm.

• Animal Bioscience
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• 제35권5호
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• pp.670-676
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• 2022

Objective: This study was conducted to examine influence of skimmed milk-based extender (SM), INRA 96 extender and BotuSemen Gold extender on parameters of stallions' ejaculate during storage. Methods: In this study, 14 stallions between 4 and 20 years of age were monitored. Total and progressive motility, viability and morphology of sperm were evaluated at time intervals of 24, 48, and 72 hours after collection. Results: The total motility, progressive motility, and values of sperm with normal morphology were significantly higher in the INRA 96 and BotuSemen Gold extenders than in the SM (p<0.01). The sperm viability differed significantly in all extenders (p<0.01). The highest value of sperm viability was in INRA 96 (64.69%±0.67%) and lowest in SM (59.70%±0.81%). The highest differences occurred at 72 hours of storage. Values of total motility, progressive motility and sperm viability decreased over time (p<0.01). In case of sperm morphology there was no statistically significant decrease between 48- and 72-hour time intervals. Conclusion: It can be concluded that the extenders with a chemically defined composition have shown better indicators of insemination capabilities in ejaculates than the SM. The BotuSemen Gold extender is a suitable alternative to the INRA 96, when used within 48 hours; after 72 hours of storage, however, the INRA 96 showed a higher share of viable spermatozoa.

• 한국균학회소식:학술대회논문집
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• 한국균학회 2006년도 추계학술대회 및 정기총회
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• pp.3-6
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• 2006

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1061-1069
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• 2000

In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendels genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.

• Animal Bioscience
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• 제34권6호
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• pp.949-956
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• 2021

Objective: This study was focused on the estimation of parameters of Wood's model and description of the lactation curve using the cows which were lactated over 24 months on the first lactation. Methods: The database included 1,333 pure-bred dairy Simmental primiparous cows which lactated for 24 months (732 days). The initial dataset entering the procedure of assessment of parameters of Wood's function included 35,826 milk yield records. Milk yield was recorded throughout lactation, with the earliest record taken on day 6 and the latest on day 1,348 of lactation. This dataset was used for the assessment of parameters a, b, c of Wood's model using the non-linear statistical procedure. These parameters were estimated for different length of lactation. The assessed parameters were used for calculation of some characteristics of lactation curves. Results: The lowest value of a parameter (15.2317) of Wood's model of lactation curve was found out in lactations up to 305 days long, contrary to b and c parameters which were highest in those lactations (0.1029 and 0.0015, respectively). The maximum value of a parameter (17.4329) was found out in lactations up to 640 days long, unlike b and c parameters which were minimal in those lactations (0.0603 and 0.0010, respectively). Conclusion: It can be concluded that the parameters of Wood's model and the shape of lactation curve are changing with the growing number of milk yield records. Also, the assessed parameters revealed a significant milk production potential after 305 days of lactation.