• 산업공학
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• 제25권4호
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• pp.422-430
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• 2012

In this article, we introduced the estimation method by 'Safety Integrity Level'(SIL) for the criterion of safety assurance and performed a case study on a flame scanner. SIL requires probabilistic evaluation of each set of equipment used to reduce risk in a safety related system. FMEDA(Failure Modes, Effects and Diagnostic Analysis) method is widely used to evaluate the safety levels and provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a part or a component. Basically, two parameters resulting from FMEDA are used for SIL classification of the device : SFF(Safe Failure Fraction) and PFD(Probability of Failure on Demand). In this case study, it is concluded that the flame scanner is designed to fulfill the condition of SIL 3 in the aspect of SFF and PFD.

• 대한산업공학회지
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• 제39권5호
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• pp.342-350
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• 2013

Dual response surface optimization (DRSO), inspired by Taguchi's philosophy, attempts to optimize the process mean and variability by using response surface methodology. Researches on DRSO were extensively done in 1990's and have been matured recently. This paper reviews the existing DRSO methods from the decision making perspective. More specifically, this paper classifies the existing DRSO methods based on the optimization criterion and the timing of preference articulation. Also, some of case studies are reviewed. Extension to multiresponse optimization, triple response surface optimization, and application of data mining method are suggested as future research issues.

• Journal of Biosystems Engineering
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• 제23권4호
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• pp.343-350
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• 1998

Spectroscopic analysis of soybean kernels were made in the wavelength range of 400 to 1100 nm to find effective discrimination factors which are required for developing an opitical soybean sorter. Soybean samples used for the test were the sound and five classes of the defective kernels such as the immature, discolored(brown and violet), damaged by insect and diseased. Effective discrimination factors to classify the soybean kernels into the sound and the defective were found to be $R_{640}$, $R_{580}$/ $R_{990}$, $R_{600}$- $R_{820}$ and ( $R_{590}$- $R_{820}$)/ $R_{990}$. with classification error of less than 4%. Mahalanobis distance was used as a criterion to select significant wavelengths involved in the discrimination factors.s.

• 한국정보통신학회논문지
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• 제5권3호
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• pp.443-449
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• 2001

잡음환경에서의 음성인식은 실제의 환경에서의 음성인식에서 매우 중요한 애로기술로써 이를 해결하기 위한 연구는 꾸준히 연구되고 있다. 따라서 본 연구는 음성인식분야에서 가장 많이 사용하고 있는 HMM처리 시잡음처리의 문제점을 주파수 가중치 부가 HMM으로 해결하는 방법을 제안하고 그 성능을 인식실험을 통하여 검토하였다. 그 결과 SS처리를 함께 사용하는 $MCE-\mu$, MCE-$\rho$가 가장 잡음에 강한 방식임을 알 수 있었다.

• 대한전자공학회논문지
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• 제27권8호
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• pp.1275-1283
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• 1990

Perception of surfaces from range images plays a key role in 3-D object recognition. Recognition of 3-D objects from range images is performed by matching the perceived surface descriptions with stored object models. The first step of the 3-d object recognition from range images is image segmentation. In this paper, an approach for segmenting 3-D range images into symbolic surface descriptions using spatial Gabor filter is proposed. Since the phase of data has a lot of important information, the phase information with magnitude information can effectively segment the range imagery into regions satisfying a common homogeneity criterion. The phase and magnitude of Gabor filter can represent a unique featur vector at a point of range data. As a result, range images are trnasformed into feature vectors in 3-parameter representation. The methods not only to extract meaningful features but also to classify a patch information from range images is presented.

• The Journal of the Acoustical Society of Korea
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• 제15권4E호
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• pp.21-27
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• 1996

In this paper, we propose a discriminative training algorithm for the stochastic segment model (SSM) in continuous speech recognition. As the SSM is usually trained by maximum likelihood estimation (MLE), a discriminative training algorithm is required to improve the recognition performance. Since the SSM does not assume the conditional independence of observation sequence as is done in hidden Markov models (HMMs), the search space for decoding an unknown input utterance is increased considerably. To reduce the computational complexity and starch space amount in an iterative training algorithm for discriminative SSMs, a hybrid architecture of SSMs and HMMs is programming using HMMs. Given the segment boundaries, the parameters of the SSM are discriminatively trained by the minimum error classification criterion based on a generalized probabilistic descent (GPD) method. With the discriminative training of the SSM, the word error rate is reduced by 17% compared with the MLE-trained SSM in speaker-independent continuous speech recognition.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.400-405
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• 2001

This paper addresses an effective approach of training neural networks classifiers for credit card fraud detection. The proposed approach uses evolutionary programming to trails the neural networks classifiers based on maximization of the detection rate of fraudulent usages on some ranges of the rejection rate, loot minimization of mean square error(MSE) that Is a common criterion for neural networks learning. This approach enables us to get classifier of satisfactory performance and to offer a directive method of handling various conditions and performance measures that are required for real fraud detection applications in the classifier training step. The experimental results on "real"credit card transaction data indicate that the proposed classifiers produces classifiers of high quality in terms of a relative profit as well as detection rate and efficiency.

• Journal of information and communication convergence engineering
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• 제6권1호
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• pp.94-99
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• 2008

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the HSI model. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The fuzzy C-means clustering algorithm is employed to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• 대한전자공학회논문지TE
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• 제37권3호
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• pp.16-20
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• 2000

대부분의 음성인식 시스템이 확률 모델을 기반으로 한 HMM 방법을 가장 많이 사용하고 있다. 한국어 고립 전화 숫자음 인식인 경우에 만약 충분한 학습 데이터가 주어지면 HMM 방법을 사용해도 높은 인식률을 얻는다 그러나 한국어 연속 전화 숫자음 인식인 경우에 비슷하게 발음되는 전화 숫자음들에 대해서는 HMM방법이 한계를 가지고 있다. 본 논문에서는 한국어 연속 전화 숫자음 인식에서 HMM 방법의 한계를 극복하기 위해 discriminant 학습 방법을 제시한다. 실험결과는 우리가 제시한 discriminant 학습 방법이 비슷하게 발음되는 전화 숫자음들에 대해서 높은 인식률을 갖는 것을 보여준다.

• 한국대기환경학회지
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• 제9권4호
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• pp.278-287
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• 1993

In order to calssify smog type durnig the summer season in Seoul, air Quality and meterorological data were analyzed by multivariate analysis. Among 15 variables relating to visibility, 10 variables were selected by multiple regression analysis for clustering of smog types; total suspended particle, sulfur dioxide, ozone, ntrogen dioxide, total hydrocarbon, south-north wind component, ralative humidity, precipitable water, mixing height and air temperature. Somg types were grouped into three clusters using cubic clustering criterion and the mumbers of days in each cluster were contained 74, 28 and 16 days. Each cluster was seperated clearly by sulfur dioxide, precipitable water and air teperature. The first cluster was representative of high ozone concentration and prevailing meterological conditions for ozone formation. Therefore, visibility in the first cluster was considered to be affected by photochemical smog. The third cluster showed characteristics of sulphurous smog type due to the higher concentration of primary pollutant, based on the dry condition than that in another cluster. On the other hand, the characteristic of the second cluster was not relatively clear, but considered to be in an intermediate characteristic between photochemical smog and sulphurous smog type.