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강태훈(Tae-Hoon Kang),이은진(Eun-Jin Lee),김인범(In-Beom Kim) 대한해부학회 2003 Anatomy & Cell Biology Vol.36 No.4
VIP는 신경활성물질로서 포유류 및 비포유동물의 망막에 널리 분포한다. 본 연구는 유전자조작에 널리 이용되며 그 이 용이 비교적 용이하여, 최근 포유동물의 망막의 구조와 기능연구의 중요성이 높아지고 있는 생쥐의 망막에서, VIP를 함유하는 신경원을 면역세포화학법으로 동정하고 이들의 특징을 밝히고자 수행되었다. VIP 면역반응성은 속핵층에 위치한 무축삭세포의 세포체와 속얼기층의 층판 1과 3에 분지하는 돌기에서 관찰되었고, VIP 면역반응성 무축삭세포는 망막의 중심부에서 430 cells/mm2의 최고 밀도로 분포하였으며 주변부로 갈수록 그 밀도가 낮아져 50 cells/mm2의 수치로 최저밀도를 나타내었다. 또한 이중면역염색법을 시행한 결과, 모든 VIP 면역반응성 무축삭세포는 GABA 면역반응성을 나타내었다. 이상의 결과는 생쥐 망막의 VIP 면역반응성 무축삭세포는 신경화학적으로 그리고 형태학적으로 구별되는 GABA성 무축삭세포의 한 아형임을 의미한다. Vasoactive intestinal polypeptide (VIP) is a neuroactive substance that is widely expressed in both non-mammalian and mammalian retinas. In this study, we immunocytochemically identified and investigated the VIP-containing neurons in the mouse retina, which has become an important model for the study of the structure and function of the mammalian retina, mainly because of the wide availability of transgenic animals. VIP immunoreactivity was observed in the somata of the amacrine cells in the inner nuclear layer (INL) and their varicose processes ramifying in strata 1 and 3 of the inner plexifrom layer (IPL). The distribution of VIP-immunoreactive (IR) amacrine cells showed a peak of 430 cells/mm2 in the central retina and minimum values of 50 cells/mm2 in the peripheral one. Double-label experiments demonstrated that all VIP-IR amacrine cells possessed GABA immunoreactivity. These results demonstrate that VIP-IR amacrine cells of the mouse retina make up a neurochemically and morphologically distinct subpopulation of the GABAergic amacrine cell population.
임베디드 시스템 테스팅을 위한 체크리스트로부터 테스트 스크립트 자동 생성 방안
강태훈 ( Tae Hoon Kang ),김대준 ( Dae Joon Kim ),정기현 ( Ki Hyun Chung ),최경희 ( Kyung Hee Choi ) 한국정보처리학회 2016 정보처리학회 논문지 Vol.5 No.12
This paper proposes a method to generate test scripts in an automatic manner, based on checklist used for testing embedded systems in the fields. The proposed method can reduce the mistakes which may be introduced during manual generation. In addition, it can generate test scripts to test various mode combinations, which is not possible to be tested by the typical checklist. The test commands in a checklist are transformed into a test script suit referencing the signal values defined in a test command dictionary. In addition, the method to generate test scripts in sequential, double permutation and random manners is proposed useful to test the inter-operations between modes, a series of operations for a specific behavior. The proposed method is implemented and the feasibility is shown through the experiments.
강태훈 ( Tae Hoon Kang ) 한국식품유통학회 2011 식품유통연구 Vol.28 No.2
If prices in the later (earlier) stage of marketing channel respond faster or deeper to the price increases in the earlier (later) stage of marketing channel than to decreases, we call it the positive (negative) APT. This paper considers four major livestock prices such as beef, hog, chicken, and egg prices in Korea. Potential APTs are tested for the stages from farm to wholesale as well as from wholesale to retail using daily prices. Since the prices in each marketing stages are cointegrated each other, the asymmetric error correction model is used. Beef market shows the positive APT in both cases, that is, farm to wholesale and wholesale to retail. Hog and egg markets show the positive APT in wholesale to retail case, while chicken market shows no APT. These results support for the customers` complains thus far that retail price rises fast when farm price rises but doesn`t fall or falls slow when farm price falls.
몬데카를로시뮬레이션방법을 이용한 옵션가격 수렴성에 관한 실증연구
강태훈(Tae-Hoon Kang) 한국국제회계학회 2006 국제회계연구 Vol.0 No.15
본 연구의 목적은 옵션가치평가의 한 방법인 블랙-숄즈 옵션가격결정모형과 몬테카를로 시뮬레이션을 이용한 옵션가치평가의 비교를 통하여 전통적인 모형인 블랙-숄즈 옵션가격결정모형과 별다른 차이가 없음을 보이고자 하는 논문이다. 블랙-숄즈 옵션가격결정모형은 1973년에 제시되어진 모형으로서, 현재까지 옵션의 가치를 평가하는데 일반화 되어진 모형이며 최근 들어 만들어지고 있는 다양한 옵션의 가치를 평가하는데도 유용하게 사용되고 있다. 하지만 블랙-숄즈 옵션가격결정모형은 이론적으로는 가장 완벽한 모형으로 간주되지만 모형을 위한 가정이 비현실적이고 개별요소의 특성을 달리 나타낼 수 있는 여지가 많다. 그리고 각 변수들의 양이 많아져 복잡한 식으로 된다면 해결하는데 많은 시간과 노력이 소요되는 단점이 있다. 이러한 단점을 보완하기 위한 방법이 Monte Carlo Simulation이다. 몬테카를로 시뮬레이션은 블랙-숄즈모형의 기초가 되는 여러 가정들이 완화되어 옵션가격을 결정하는 공식의 적용이 불가능하고 옵션가격을 결정하는 변수의 앙이 많아서 일반식 형태로 풀기 난해한 경우 옵션가격을 산출하는 방법이다. 본 논문의 실증분석결과 t-검정 값들이 모두 귀무가설을 채택하여 결론적으로 블랙-숄즈 가격결정모혈과 몬테카를로 시뮬레이션을 이용한 옵션가격결정모형의 관측 값은 유의적으로 같음을 알 수 있다. This paper uses a Monte Carlo simulation for option valuation problem, compares the solutions by a Monte Carlo simulation with those by a closed-form function based on the Black-Scholes option pricing model and prove that the method is efficient as well as simple and flexible in the sense that it can be easily modified to accommodate different processes governing the underlying instruments movements. Designed by Black and Scholes in 1973, the option pricing model succeeded in drawing general formulas with relatively simple assumptions and thereby various option pricing models were developed. The option pricing model, Black-Scholes Model has developed by the repetitive relaxation and alternation of assumptions. meanwhile, the output of integration has become too complex to draw an analytic solution. To solve such problem, numerical approaches were introduced. One of the typical numerical approach is the Monte Carlo Simulation. The simulation can include various stochastic processes which determine the profit of underlying assets, and thus the simulation is commonly used to the option pricing. The paper shows that some conditions are needed in order to converge random prices into a stable status in the simulation. The drawback of the Monte Carlo method lies in the fact that the standard deviation error of estimate is inversely proportional to the square-root of the number of simulation trials. Technique for improving the efficiency of the method is the antithetical method that can reduce variances. The total standard error is significantly reduced using the antithetical method. The antithetical method calculates two values of option price, one being calculated in the normal way and the other calculated through changing the sign of the all the samples from standard normal distribution. The average of the two values is considered as the value of the option price from the sample. The final estimate of the value of the option price is the average of all the average of the pairs of values.