• 한국경영과학회지
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• 제33권2호
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• 반도체디스플레이기술학회지
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• 제8권2호
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• pp.23-29
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• 2009

To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2008년도 제7회 추계학술대회 및 정기총회
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• pp.351-354
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• 2008

• Journal of the Korean Data and Information Science Society
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• 제12권2호
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• pp.83-93
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• 2001

We investigate a kernel approach to discriminant analysis for binary classification as a machine learning point of view. Our view of the kernel approach follows support vector method which is one of the most promising techniques in the area of machine learning. As usual discriminant analysis, the kernel method can discriminate an object most likely belongs to. Moreover, it has some advantage over discriminant analysis such as data compression and computing time.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권7호
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• pp.452-461
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• 2008

바이너리 코드의 차이점 분석은 보안 패치와 같은 매우 유사한 두 프로그램 사이의 차이점을 구별해 주는 방법이다. 이전의 연구에서는 분석을 위하여 프로그램의 구조 또는 명령어의 세부 사항만을 각각 이용하였다. 프로그램의 구조를 이용하는 차이점 분석 방법은 제어 흐름의 변화는 잘 탐지해 낼 수 있지만, 버퍼 크기 변화와 같은 상수 값의 변화는 잘 찾아낼 수 없다. 명령어 기반의 차이점 분석 방법은 세부적인 값의 변화는 발견할 수 있으나 명령어 재배치와 같은 컴파일러에 의해 생성되는 불필요한 차이점을 결과로 낸다는 단점이 있다. 이 연구에서는 프로그램 구조를 이용한 비교 분석 방법에 상수 값의 변화를 함께 추적할 수 있는 방법을 제안하고 바이너리 차이점 분석 도구를 구현하였다. 구현된 도구는 윈도 보안 업데이트를 이용하여 평가하였다. 실험 결과 제안된 방법은 구조적인 차이점 분석과 같이 빠른 속도로 구조적인 변화를 찾아낼 뿐 아니라 상수 값의 변화까지 추적할 수 있다는 것을 보였다.

• ETRI Journal
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• 제32권4호
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• pp.638-641
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• 2010

With the growth of memory capacity and density, memory testing and repair with the goal of yield improvement have become more important. Therefore, the development of high efficiency redundancy analysis algorithms is essential to improve yield rate. In this letter, we propose an improved built-in redundancy analysis (BIRA) algorithm with a minimized binary search tree made by simple calculations. The tree is constructed until finding a solution from the most probable branch. This greatly reduces the search spaces for a solution. The proposed BIRA algorithm results in 100% repair efficiency and fast redundancy analysis.

• 대한산업공학회지
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• 제40권3호
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• pp.342-357
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• 2014

The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."

• 한국정밀공학회지
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• 제16권4호통권97호
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• pp.205-212
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• 1999

A three dimensional binary parallel robot manipulator uses actuators which have only two stable states and its structure is variable geometry truss. As a result, it has a finite number of states and fault tolerant mechanism because of kinematic redundancy. This kind of robot manipulator has some advantages compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. Because the number of states of a binary robot manipulator grows exponentially with the number of actuators it is very difficult to solve and inverse kinematic problem. The goal of this paper is to develop an efficient algorithm to solve an inverse kinematic problem of three dimensional binary parallel robot manipulator using a backbone curve when the number of actuators are too much. We first derive the coordinate transformations associated with a three degree of freedom in-parallel actuated robot manipulator. The backbone curve is generated optimally by considering the maximum roll and pitch angles of the robot manipulator configuration and length of link. Then, the robot manipulator is fitted along the backbone curve with some criterion.

• Journal of Astronomy and Space Sciences
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• 제29권2호
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• pp.115-121
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• 2012

Existing but largely unused binary star model capabilities are examined. An easily implemented scheme is parameterization of starspot growth and decay that can stimulate work on outer convection zones and their dynamos. Improved precision in spot computation now enhances analysis of very precise data. An existing computational model for blended spectral line profiles is accurate for binary system effects but needs to include damping, thermal Doppler, and other intrinsic broadening effects. Binary star ephemerides had been found exclusively from eclipse timings until recently, but now come also from whole light and radial velocity curves. A logical further development will be to expand these whole curve solutions to include eclipse timings. An attenuation model for circumstellar clouds, with several absorption and scattering mechanisms, has been applied only once, perhaps because the model clouds have fixed locations. However the clouds could be made to move dynamically and be combined into moving streams and disks. An area of potential interest is polarization curve analysis, where incentive for modeling could follow from publication of observed polarization curves. Other recent advances include direct single step solutions for temperatures of both stars of an eclipsing binary and third body kinematics from combined light and velocity curves.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.403-410
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• 2014

이분형 로지스틱 회귀분석은 양적 혹은 질적 설명변수를 이용해서 이분형 반응변수를 설명하는 하나의 통계적인 기법이다. 이 모형에서는 반응변수가 1이 될 확률을 설명변수들의 선형결합의 변환(혹은 함수)으로 설명하고자 한다. 이 개념에 대한 이해가 비통계학자들이 이분형 로지스틱 회귀모형을 이해하는데 있어서 넘어야 할 커다란 장벽 중의 하나이다. 이 연구에서는 이분형 로지스틱 회귀모형의 필요성을 엑셀 VBA를 이용하여 설명하는 교육도구를 개발하고자 한다. 반응변수가 1이 될 확률을 설명변수의 선형함수로 모형화 할 때의 문제점과 선형결합에 대한 변환을 통해 이 문제점이 어떻게 해소되는지 보여준다.