• 전기학회논문지
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• 제57권12호
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• pp.2313-2321
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• 2008

In order to develop reliable on-site partial discharge(PD) pattern recognition algorithm, the fuzzy neural network based on fuzzy set(FNN) and the polynomial network pattern classifier based on fuzzy Inference(PNC) were investigated and designed. Using PD data measured from laboratory defect models, these algorithms were learned and tested. Considering on-site situation where it is not easy to obtain voltage phases in PRPDA(Phase Resolved Partial Discharge Analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithms. As input vectors of the algorithms, PRPD data themselves were adopted instead of using statistical parameters such as skewness and kurtotis, to improve uncertainty of statistical parameters, even though the number of input vectors were considerably increased. Also, results of the proposed neuro-fuzzy algorithms were compared with that of conventional BP-NN(Back Propagation Neural Networks) algorithm using the same data. The FNN and PNC algorithms proposed in this study were appeared to have better performance than BP-NN algorithm.

• 한국ITS학회 논문지
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• 제13권2호
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• Journal of Electrical Engineering and Technology
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• 제2권1호
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• pp.118-122
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• 2007

In this work, experimental investigation is carried out in order to design and fabricate the UHF sensor that is able to detect the partial discharges produced from 10 artificial defects introduced into the real scale 70kV GIS mock-up under high voltage within a well shielded room. As well, in order to verify the on-site applicability of our method, the newly proposed CAPD (chaos analysis of partial discharge) is combined with spectral analysis for identifying the nature of 10 artificial defects under investigation. The PD pattern recognition of each defect has been fulfilled by applying our ANN software. The result indicates that the recognition rate reaches up to 80% by the newly proposed method while the traditional PRPD analysis method allows us to obtain 41%. In consequence, it can be pointed out that the proposed method seems likely to be applicable to the real GIS at the site.

• 한국국방경영분석학회지
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• 제33권1호
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• pp.93-103
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• 2007

현재 적용되고 있는 선박의 식별체계들은 대부분 사용자의 판단을 도울 수 있는 수중 음파의 주파수 분석, 분석 자료의 보관 및 데이터베이스, 그리고 비교기능 등의 사용자 인터페이스를 제공하고 있으나, 선박고유의 특성 추출부터 식별까지 전적으로 사용자의 정보인식능력에 의존하고 있다. 그러므로 이러한 식별방법들의 신뢰성은 사용자의 전문성에 크게 의존하고 있으며, 분석 장비 역시 고가의 장비를 사용하고 있다. 본 논문에서는 선박식별의 자동화로 가기위한 기초 자료를 제공할 목적으로 수중에서 들려오는 소리를 일반 PC에서 획득하여 수중 음파 특성을 도출하고 패턴인식 통하여 선박들을 클래스 별로 분류함으로써 식별 가능성을 보이고자 한다. 이를 위해 Matlab을 이용한 주변소음 제거 및 신호 처리를 통한 음파 특성을 추출하고 패턴인식을 이용하여 추출된 클래스에 대해 분류하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Fisheries and Aquatic Sciences
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• 제25권11호
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• pp.559-571
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• 2022

Galectins, a family of ß-galactoside-binding lectins, have emerged as soluble mediators in infected cells and pattern recognition receptors (PRRs) responsible for evoking and regulating innate immunity. The present study aimed to evaluate the role of galectin-1 in the host immune response of redlip mullet (Liza haematocheilia). We established a cDNA database for redlip mullet, and the cDNA sequence of galectin-1 (LhGal-1) was characterized. In silico analysis was performed, and the spatial and temporal expression patterns in gills and blood in response to lipopolysaccharide polyinosinic:polycytidylic acid, and Lactococcus garvieae were estimated via quantitative real-time PCR. Functional assays were conducted using recombinant protein to investigate carbohydrate binding, bacterial binding, and bacterial agglutination activity. LhGal-1 was composed of 135 amino acids. Conserved motifs (H-NPR, -N- and -W-E-R) within the carbohydrate recognition domain were found in LhGal-1. The tissue distribution revealed that the healthy stomach expressed high levels of LhGal-1. The temporal monitoring of LhGal-1 mRNA expression in the gill and blood showed its significant upregulation in response to immune challenges with different stimulants. rLhGal-1 exhibited binding activity in response to carbohydrates and bacteria. Moreover, the agglutination of rLhGal-1 against Escherichia coli was observed. Collectively, our findings suggest that LhGal-1 may function as a PRR in redlip mullet. Furthermore, LhGal-1 can be considered a significant gene to play a protective role in redlip mullet immune system.

• 한국축산식품학회지
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• 제32권5호
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• pp.669-677
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• 2012

본 연구는 전자코를 이용하여 한국에서 시판되는 피자용 모짜렐라 치즈 슈레드 제품과 슈레드 제품 혼합용 원료 치즈에 해당하는 모짜렐라 치즈 블록, 체다 치즈, 흰 곰팡이 숙성 치즈 등 3종류의 국내산 및 수입산 치즈를 대상으로 단기간 저장 및 가열처리에 의한 풍미패턴의 변화를 분석하였고 국내 임실치즈농협에서 새로 개발한 임실 치즈 제품이 국내산 및 수입산 치즈의 향미패턴과의 차이 유무에 대해 접근하여 보고자 하였다. 치즈 종류뿐만 아니라 조리온도 및 저장유무에 따른 향기패턴을 판별함수 분석을 이용하여 통계처리 후 비교 분석한 결과, 피자용 모짜렐라 슈레드 제품의 경우 저장유무보다는 조리온도에 따라 풍미패턴의 차이가 더 구분되었으며 피자용 모짜렐라 슈레드 제품에 혼합용으로 사용되는 치즈의 종류 및 원산지에 따라서 풍미패턴이 각각 다른 것으로 나타났다. 또한 새로 개발된 국내산 임실 치즈는 기타 국내산 치즈와 외국산 치즈와 비교하였을 때 이들의 중간 향에 해당하면서도 독특한 향미를 지니는 것으로 판별되었다.

• 한국정밀공학회지
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• 제17권7호
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1670-1673
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• 2002

For pattern recognition on high-dimensional data, such as images, the dimensionality reduction as a preprocessing is effective. By dimensionality reduction, we can (1) reduce storage capacity or amount of calculation, and (2) avoid "the curse of dimensionality" and improve classification performance. Popular tools for dimensionality reduction are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Independent Component Analysis (ICA) recently. Among them, only LDA takes the class labels into consideration. Nevertheless, it, has been reported that, the classification performance with ICA is better than that with LDA because LDA has restriction on the number of dimensions after reduction. To overcome this dilemma, we propose a new dimensionality reduction technique based on an information theoretic measure for difference of distribution. It takes the class labels into consideration and still it does not, have restriction on number of dimensions after reduction. Improvement of classification performance has been confirmed experimentally.

• 한국의류학회지
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• 제22권1호
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• pp.127-138
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• 1998

Through the recognition and the satisfaction of the lower part of the women body from age 30 to age 49 we studied 211 respondents of the women to analyze what lower part shape they want. The results are as follows. 1. The recognition of the lower Part showed certain degrees of differences in waist girth, abdomen girth, and weight according to the age. 2. The female of the 40s showed higher satisfaction of their lower part considering that of the 30s 3. The cluster analysis of the lower part shape of the 30s and 40s was classified into 5 types.