• 한국전기전자재료학회논문지
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• 제29권1호
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• pp.58-61
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• 2016

Degradation in power cables used in distribution lines to the material of the wire, manufacturing method, but also the line of the environment, generates a variety of degradation depending upon the type of load. The local wire deterioration weighted wire breakage accident can occur frequently, causing significant proprietary damage can lead to accidents and precious. In this study, the signal detected by the eddy current aim to develop algorithms capable of determining the signals for the top part and at least part of the signal by using a signal processing technique called K-means algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1395-1397
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• 1996

Many of the existing neural associative memories are trained and recalled in separate modes and are not suitable for temporal pattern storage and classification in that user must specify the time and length of input patterns. In this paper, a new on-line temporal associative memory model is presented. This memory is structured in layers of neurons and each neuron has limited number of weights so that calculation complexity can be considerably reduced and processing of patterns can be achieved in real time.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1101-1104
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• 1995

Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• 한국레이저가공학회지
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• 제18권3호
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• pp.6-8
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• 2015

Finishing process includes deburring, polishing and edge radiusing. It improves the surface profile of specimen and eliminates the alien substance on surface. Deburring is the elimination process for debris of edges. Polishing lubricates surfaces by rubbing or chemical treatment. There are two types for electron finishing. The one is using pulse beam. The other is using the convergent and scanning electron beam. Pulse type device appropriates the large area process. But it does not control the beam dosage. Scanning type device has advantages for dosage control and edge deburring. We design the convergence and scan type. It has magnetic lenses for convergence and scan device for scanning beam. Magnetic lenses consist of convergent and objective lens. The lenses are designed by the specification(beam size and working distance). In this paper, we evaluate the convergence performance by pattern process. Also, we analysis the results and important factors for process. The important factors for process are beam size, pressure, stage speed and vacuum. These results will be utilized into systematizing pattern shape and the factors.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1392-1405
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• 2019

The cathode voltage of aluminum electrolytic cell is relatively stable under normal conditions and fluctuates greatly when it has an anomaly. In order to detect the abnormal range of cathode voltage, an anomaly detection algorithm based on sliding window was proposed. The algorithm combines the time series segmentation linear representation method and the k-nearest neighbor local anomaly detection algorithm, which is more efficient than the direct detection of the original sequence. The algorithm first segments the cathode voltage time series, then calculates the length, the slope, and the mean of each line segment pattern, and maps them into a set of spatial objects. And then the local anomaly detection algorithm is used to detect abnormal patterns according to the local anomaly factor and the pattern length. The experimental results showed that the algorithm can effectively detect the abnormal range of cathode voltage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권6호
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• pp.1546-1564
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• 2012

Pattern-based query processing has not attracted much attention in wireless sensor network though its counterpart has been studied extensively in data stream. The methods used for data stream usually consume large memory and much energy. This conflicts with the fact that wireless sensor networks are heavily constrained by their hardware resources. In this paper, we use piece wise representation to represent sensor nodes' collected data to save sensor nodes' memory and to reduce the energy consumption for query. After getting data stream's and patterns' approximated line segments, we record each line's slope. We do similar matching on slope sequences. We compute the dynamic time warping distance between slope sequences. If the distance is less than user defined threshold, we say that the subsequence is similar to the pattern. We do experiments on STM32W108 processor to evaluate our strategy's performance compared with naive method. The results show that our strategy's matching precision is less than that of naive method, but our method's energy consumption is much better than that of naive approach. The strategy proposed in this paper can be used in wireless sensor network to process pattern-based queries.

• 대한전자공학회논문지SD
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• 제45권1호
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• pp.20-27
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• 2008

본 논문에서는 비선형 패턴 분류를 위해 FPGA 칩에 신경회로망을 구현하였다. 병렬처리 연산을 위해 순방향 신경회로망이 구현 되었다. 신경망의 학습을 off-line으로 한 다음에 가중치 값들을 저장하여 사용한다. 예로서, AND와 XOR 논리의 패턴 구분이 수행된다. 실험결과를 통해 FPGA에 구현된 신경회로망이 잘 작동하는 것을 검증하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 춘계학술대회
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• pp.805-807
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• 2011

본 논문에서는 라인스캔 기술을 이용하여 자동차 사출성형 부품의 결함을 검사하는 방법을 제안한다. 검사대상의 결함을 검사하기 위한 검사 알고리즘은 라인 검출 알고리즘, 결함 분석 알고리즘으로 구성된다. 라인 검출 알고리즘은 레이저 선의 중심점에 해당하는 픽셀의 좌표를 결정한다. 검사 알고리즘은 해당 검사대상 모델에 대한 패턴 데이터와 라인 검출 알고리즘으로부터 얻은 데이터를 이용하여 제품의 불량 유무를 결정한다. 검사 정확도, 처리 시간 등의 평가를 통해 제안하는 검사 방법이 유효함을 확인하였다.

• 한국가정과학회지
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• 제1권2호
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• pp.113-118
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• 1998

Clothing shape is principally described in seven factors that are composed of clothing design, clothing material, clothing size, pattern design, sewing method and body motion etc.. The aims of this study was to measurement out-line space-shape variation of clothing fitness with somato type by using the image processing. The subjects for direct anthropometric measurements were 248 female college students aged from 19 to 22. The data were statistically analyzed by principal analysis and cluster analysis. The results were obtained three somato type. Also I made skirts in order to analyzed to the out-line space-shape variation of clothing fitness with body. The effect of somato type on the shape of flare skirts was determined by the out-line space-shape variation of clothing fitness with body. The out-line space-shape variation of clothing fitness with body was observed between the node number and amplitudes of clothing wave form and node number was determined at the maxim of space-shape amplitude, and the space-shape amplitudes have related with aspect ratio of cross-sectional shape. Results for flare skirts show changes in amplitude and mean with fabrics, somato type. therefore gray-level histogram are correlated with changes out-line space-shape, differences in drape spacing and related fabric properties and their somato type. (Korean J Human Ecology 1(2):113∼110 1998)

• ETRI Journal
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• 제32권3호
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• pp.395-405
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• 2010

A novel multiclassifier system (MCS) strategy is proposed and applied to a text-dependent speaker verification task. The presented scheme optimizes the linear combination of classifiers on an on-line basis. In contrast to ordinary MCS approaches, neither a priori distributions nor pre-tuned parameters are required. The idea is to improve the most accurate classifier by making use of the incremental information provided by the second classifier. The on-line multiclassifier optimization approach is applicable to any pattern recognition problem. The proposed method needs neither a priori distributions nor pre-estimated weights, and does not make use of any consideration about training/testing matching conditions. Results with Yoho database show that the presented approach can lead to reductions in equal error rate as high as 28%, when compared with the most accurate classifier, and 11% against a standard method for the optimization of linear combination of classifiers.