• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.756-761
• /
• 1998

This paper describes an in-line lossless data compression method using adaptive binary arithmetic coding. To achieve better compression efficiency , we employ an adaptive fuzzy -tuning modeler, which uses fuzzy inference to deal with the problem of conditional probability estimation. The design is simple, fast and suitable for VLSI implementation because we adopt the table -look-up approach. As compared with the out-comes of other lossless coding schemes, our results are good and satisfactory for various types of source data.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.2
• /
• pp.58-69
• /
• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.11a
• /
• pp.135-138
• /
• 2005

Java Virtual Machine이 기반이 되는 플랫폼 사용으로 모바일 폰 Java는 C/C++로 컴파일 된 Binary File에 비해 속도가 떨어지고 고성능의 프로세서를 필요로 하기 때문에 가격이 비싸질 수밖에 없다. Native Binary를 사용하는 Nano-X Window System Graphic Engine은 저 사양 프로세서에서 사용가능한 모바일 플랫폼으로써 Java Virtual Machine 보다 빠른 속도를 구현할 수 있고 GPL License를 따르기 때문에 생산단가도 절약할 수 있어 저가형 핸드폰의 대량 생산으로 인해 현재 떠오르고 있는 신흥시장에서 보다 경쟁력을 높일 수 있을 것으로 기대된다. 본 논문에서는 기존의 모바일 플랫폼과 Nano-X window System을 비교해보고 모바일 플랫폼으로써의 개발 방향에 대해 논해 보려 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.1
• /
• pp.56-62
• /
• 2004

This research attempts to suggest a detecting method for cutting position of an object using the neural network, which is one of intellectual methods, and the digital image processing method. The extraction method of object information using the image data obtained from the CCD camera as a replacement of traditional analog sensor thanks to the development of digital image processing. Accordingly, this research determines the threshold value in binary-coding of an input image with the help of image processing method and the neural network for the real-time gray-leveled input image in substitution for lighting; as a result, a specific position is detected from the processed binary-coded image and an actual system designed is suggested as an example.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2418-2423
• /
• 2005

Hard Disk Drive (HDD) test system is the equipment for the final test of HDD product by iterative read/write/seek test. This paper proposes an expert system for the fault diagnosis of HDD test systems. The purposed expert system is composed with two cascade inference, fuzzy logic and conventional binary logic. The fuzzy logic determines the possibility of the system fault using the test history data, then, the binary logic inferences the fault location of the test system. The proposed expert system is tested in SAMSUNG HDD product line, KUMI, KOREA, and shows satisfactory results.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2424-2429
• /
• 2005

Hard Disk Drive (HDD) test system is the equipment for the final test of HDD product by iterative read/write/seek test. This paper proposes an expert system for the fault diagnosis of HDD test systems. The purposed expert system is composed with two cascade inference, fuzzy logic and conventional binary logic. The fuzzy logic determines the possibility of the system fault using the test history data, then, the binary logic inferences the fault location of the test system. The proposed expert system is tested in SAMSUNG HDD product line, KUMI, KOREA, and shows satisfactory results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.8
• /
• pp.767-773
• /
• 2008

This paper presents a localization system based on the use of electric compass and tracking IR light source. Digital RGB(Red, Green, Blue)signal of digital CMOS Camera is sent to CPLD which converts the color image to binary image at 30 frames per second. CMOS camera has IR filter and UV filter in front of CMOS cell. The filters cut off above 720nm light source. Binary output data of CPLD is sent to DSP that rapidly tracks the IR light source by moving Camera tilt DC motor. At a robot toward north, electric compass signals and IR light source angles which are used for calculating the data of the location system. Because geomagnetic field is linear in local position, this location system is possible. Finally, it is shown that position error is within ${\pm}1.3cm$ in this system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.287-290
• /
• 1997

신경회로망은 높은 정확도의 학습 결과를 제시하는 장점을 가지고 있어서 패턴 인식을 포함한 여러 분야에서 널리 사용되어지고 있다. 그러나 신경회로망의 설계에 있어 최적의 뉴런과 층의 개수, 그리고 그 연결 등의 기하학적 해답을 제시하기가 어렵고, 서은이 우수하다고 알려진 역전파 학습 알고리즘도 오차가 없는 완벽한 학습 결과를 제시하지 못하며, 상당히 많은 학습 시간이 걸린다는 단점들을 가지고 있다. 이러한 단점들을 극복하기 위해 선형 신경회로망을 합성하는 새로운 방법을 제안하는데, 이진 함수 최소화(binary function minimization)과정을 거친 minimal-sum-of-product(MSP)를 통해서 이진 클래스 패턴(binary class pattem)을 표현 함으로써 오차가 없는 학습 결과를 얻을 수 있으며, 학습에 필요한 패턴과 학습에 걸리는 시간도 대폭 줄일수 있다. 본 논문에서는 유전자 알고리즘을 이용하여 선형 신경회로망을 합성하는 방법을 제안하며, 여러 가지 예제를 통해 제안한 방법의 우수성을 보인다.

• The Journal of Information Systems
• /
• v.18 no.3
• /
• pp.375-399
• /
• 2009

In this study, we propose a integrated model of logistic regression, artificial neural networks, support vector machines(SVM), with case-based reasoning(CBR). To predict respondents in the direct marketing is the binary classification problem as like bankruptcy prediction, IDS, churn management and so on. To solve the binary problems, we employed logistic regression, artificial neural networks, SVM. and CBR. CBR is a problem-solving technique and shows significant promise for improving the effectiveness of complex and unstructured decision making, and we can obtain excellent results through CBR in this study. Experimental results show that the classification accuracy of integration model using CBR is superior to logistic regression, artificial neural networks and SVM. When we apply the customer response model to predict respondents in the direct marketing, we have to consider from the view point of profit/cost about the misclassification.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.5
• /
• pp.390-395
• /
• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.