• Asian-Australasian Journal of Animal Sciences
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• 제18권8호
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• pp.1088-1097
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• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• 한국정밀공학회지
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• 제15권12호
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• pp.162-168
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• 1998

The traditional robot manipulators are actuated by continuous range of motion actuators such as motors or hydraulic cylinders. However, there are many applications of mechanisms and robotic manipulators where only a finite number of locations need to be reached, and the robot's trajectory is not important as long as it is bounded. Binary manipulator uses actuators which have only two stable states. As a result, binary manipulators have a finite number of states. The number of states of a binary manipulator grows exponentially with the number of actuators. This kind of robot manipulator has some advantage compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. And this kind of robot manipulator has a fault tolerant mechanism because of kinematic redundancy. This paper develops algorithms for kinematics and workspace analysis of a binary manipulator.

• Management Science and Financial Engineering
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• 제3권1호
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• pp.39-56
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• 1997

This paper applies the binary tree classifier and discriminant analysis methods to predicting failures of banks and insurance companies. In this study, discriminant analysis is generally better than the binary tree classifier in the classification of bank defaults; the binary tree is generally better than discriminant analysis in the classification of insurance company defaults. This situation can be explained that the performance of a classifier depends on the characteristics of the data. If the data are dispersed appropriately for the classifier, the classifier will show a good performance. Otherwise, it may show a poor performance. The two data sets (bank and insurance) are analyzed to explain the better performance of the binary tree in insurance and the worse performance in bank; the better performance of discriminant analysis in bank and the worse performance in insurance.

• 한국컴퓨터정보학회논문지
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• 제16권6호
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• pp.51-59
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• 2011

국내에는 바이너리 코드에 대한 분석 기술이 많이 부족한 상태이다. 일반적으로 컴퓨터에 설치되는 실행 파일은 소스 코드 없이 단지 바이너리로 된 실행 파일만 주어지는 경우가 대부분이다. 따라서 위험하거나 알 수 없는 동작이 수행되는 경우가 발생할 수 있다. 따라서 이 논문에서는 바이너리 수준에서 정적으로 프로그램 분석을 수행할 수 있는 프레임워크를 설계 및 구현한다. 이 논문에서는 바이너리 실행 파일로부터 실행 순서 및 제어 흐름 등의 정보를 표현할 수 있는 제어 흐름 그래프를 작성하여 실행 흐름과 위험한 함수의 호출 여부를 동시에 파악하고 개발된 프레임워크를 통해 바이너리 파일에 대한 분석을 용이하게 한다.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.589-598
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• 2015

In longitudinal studies missing data are common and require a complicated analysis. There are two popular modeling frameworks, pattern mixture model (PMM) and selection models (SM) to analyze the missing data. We focus on the PMM and we also propose Bayesian pattern mixture models using generalized linear mixed models (GLMMs) for longitudinal binary data. Sensitivity analysis is used under the missing not at random assumption.

• 한국지능시스템학회논문지
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• 제19권4호
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• pp.592-594
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• 2009

In this paper we consider voting analysis in the political science in connection with $B_n$(or $M_n${0, 1}), the semigroup of the binary relations on X with n elements. We also consider it in connection with $M_n$(F) (or $B_n$(F)), the semigroup of all fuzzy binary relations on X. Also we establish a possibility theorem and an impossibility theorem in voting analysis based on preferences in $B_n$ and $M_n$(F).

• 한국콘텐츠학회논문지
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• 제10권5호
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• pp.70-79
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• 2010

바이너리 코드 수준에서 정적인 프로그램 분석을 수행한다. 소스 코드가 아닌 바이너리 코드 수준에서 분석을 수행하는 이유는 일반적으로 로컬 컴퓨터에 설치하는 실행 파일은 소스 코드 없이 단지 바이너리로 된 실행 파일만 주어지는 경우가 대부분이기 때문이다. 또한 정적으로 분석을 수행하려는 이유는 정적인 제어 흐름 분석을 통해 프로그램이 수행 시 어떤 동작을 수행하게 될지를 수행 전에 파악하기 위해서이다. 본 논문에서는 바이너리 실행 파일로부터 함수간의 실행 순서 및 제어 흐름 등의 정보를 표현할 수 있는 실행 흐름 그래프를 작성하여 사용자가 바이너리 파일의 실행 흐름과 위험한 함수의 호출 여부를 동시에 파악할 수 있도록 하며, 그래프를 통해 바이너리 파일의 분석을 용이하게 한다. 또한 실행 흐름에 대한 자동 탐색 방법을 제공하여 수행될 프로그램의 안전성을 보장하고, 수행 전에 외부에서 다운받아 설치할 프로그램이 안전한지를 판단할 수 있도록 한다.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.211-218
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• 1999

The traditional robot manipulators are actuated by continuous range of motion actuators such as motors or hydraulic cylinders. However, there are many applications of mechanisms and robotic manipulators where only a finite number of locations need to be reached, and the robot’s trajectory is not important as long as it is bounded. Binary manipulator uses actuators which have only two stable states. As a result, binary manipulators have a finite number of states. The number of states of a binary manipulator grows exponentially with the number of actuators. This kind of robot manipulator has some advantage compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. And this kind of robot manipulator has a fault tolerant mechanism because of kinematic redundancy. In this paper, we solve the inverse kinematic problem of a binary parallel robot manipulator using neural network and test the validity of this structure using some arbitrary points m the workspace of the robot manipulator. As a result, we can show that the neural network can find the nearest feasible points and corresponding binary states of the joints of the robot manipulator

• 정보과학회 논문지
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• 제44권10호
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• pp.1019-1025
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• 2017

바이너리 유사도 분석은 취약점 분석, 악성코드 분석, 표절 탐지 등에서 사용되고 있는데, 분석대상 함수가 알려진 안전한 함수와 동일하다는 것을 증명해주면 바이너리 코드의 악성행위 분석, 취약점 분석 등의 효율성을 높이는 데에 도움이 될 수 있다. 하지만 기존에는 동일 함수의 서로 다른 버전에 대한 유사도 분석에 대해서 별도로 이루어진 연구가 거의 없었다. 본 논문에서는 바이너리로부터 추출 가능한 함수 정보들을 바탕으로 다양한 방법을 통해 함수 단위의 유사도를 분석하고 적은 시간으로 효율적으로 분석할 수 있는 방안을 모색한다. 특히 OpenSSL 라이브러리의 서로 다른 버전을 대상으로 분석을 수행하여 버전이 다른 경우에도 유사한 함수를 탐지하는 것을 확인한다.

• International Journal of Precision Engineering and Manufacturing
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• 제2권1호
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• pp.76-80
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• 2001

A binary parallel robot manipulator uses actuators that have only two stable states being built by stacking variable geometry trusses on top of each other in a long serial chain. Discrete characteristics of the binary manipulator make it impossible to analyze an inverse kinematic problem in conventional ways. We therefore introduce new definitions of workspace and inverse kinematic solution, and the apply a genetic algorithm to the newly defied inverse kinematic problem. Numerical examples show that our genetic algorithm is very efficient to solve the inverse kinematic problem of binary robot manipulators.