• 한국영어학회지:영어학
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• 제1권4호
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• pp.651-671
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• 2001

There are several English constructions in which a certain constituent appears to the left of its canonical position, typically sentence-initially, leaving its canonical position empty. Such constructions involve Left-dislocation and Y-movement. These operations are called ‘Preposing.’ The preposed constituent of such constructions is generally regarded as the topic of the sentence which involves that constituent. Topics must have at least two features; ‘aboutness’ and ‘givenness.’ The feature ‘aboutness’ defines the range of comment, and the feature ‘givenness’ means ‘informationally old or given.’ The purpose of this paper is to show that the function of Preposing is to reinforce the aboutness of the preposed constituent of a sentence and that most preposed constituents have givenness. We examined Preposing for this purpose. Tough-movement and Passivization were examined also, because they have characteristics informationally similar to those of Preposing.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2000년도 춘계학술발표논문집
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• 한국주거학회논문집
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• 제8권2호
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• pp.135-145
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• 1997

The purpose of this study was to investigate the space feature of private kindergarten in Taegu city. This study was conducted by means of the observation on the equipments, the actual measurement of space of kindergarten and environment, and the questionnaire survey by the chief of kindergarten. The samples for analysis were 20 kindergartens on Taegu city. The Major findings were as follows :1) The chiefs of kindergartens were generally satisfied with the whole range of institutions and it's management.2) Generally the environmental coditions were satisfactory, but the design of the equipments had no consideration for children's body size.3) According to observation on the equipment, it was found that generally environment of kindergarten were desireable.

• 한국멀티미디어학회논문지
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• 제12권6호
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• pp.794-803
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• 2009

In this paper, we will present a container auto-landing system, the system use the stereo camera to measure the container depth information. And the container region can be detected by using its hough line feature. In the line feature detection algorithm, we will detect the parallel lines and perpendicular lines which compose the rectangle region. Among all the candidate regions, we can select the region with the same aspect-ratio to the container. The region will be the detected container region. After having the object on both left and right images, we can estimate the distance from camera to object and container dimension. Then all the detect dimension information and depth inform will be applied to reconstruct the virtual environment of crane which will be introduce in this paper. Through the simulation result, we can know that, the container detection rate achieve to 97% with simple background. And the estimation algorithm can get a more accuracy result with a far distance than the near distance.

• Ocean and Polar Research
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• 제23권4호
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• pp.433-440
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• 2001

Marine organisms in Antarctica live in an environment which exhibits variability in physical processes over a wide range of temporal scales, from seconds to millennia. This time scale tends to be correlated with the spatial scale over which a given process operates, though this relationship is influenced by biology. The way organisms respond to variability in the physical environment depends on the time-scale of that variability in relation to life-span. Short-term variations are perceived largely as noise and probably have little direct impact on ecology. Of much greater importance to organisms in Antarctica are seasonal and decadal variations. Although seasonality has long been recognised as a key feature of polar environments, the realization that decadal scale variability is important is relatively recent. Long-term change has always been a feature of polar environments and may be a key factor in the evolution of the communities we see today.

• 제어로봇시스템학회논문지
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• 제4권6호
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• pp.765-771
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• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권9호
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• pp.547-553
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• 2003

In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.

• 대한안전경영과학회지
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• 제12권3호
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• pp.333-339
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• 2010

Data mining is the process of finding and analyzing data from a big database and summarizing it into useful information for a decision-making. A variety of data mining techniques have been being used for wide range of industries. One application of those is especially so for gathering meaningful information from process data in manufacturing factories for quality improvement. The purpose of this paper is to provide a methodology to improve manufacturing quality of fuel tanks which are auto-parts. The methodology is to analyse influential attributes and establish a model for optimal manufacturing condition of fuel tanks to improve the quality using decision tree, association rule, and feature selection.

• ETRI Journal
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• 제45권5호
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• pp.862-873
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• 2023

Determining whether an autonomous self-driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one camera to train a three-camera model, which would enable us to more easily compile a variety of training data to endow our model with improved generalizability. In this work, we provide three separate fusion methods (feature, early, and late) of combining the information from three cameras. Extensive pedestrian-view intersection classification experiments show that our feature fusion model provides an area under the curve and F1-score of 82.00 and 46.48, respectively, which considerably outperforms contemporary three- and one-camera models.

• 전자공학회논문지
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• 제49권9호
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• pp.113-127
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• 2012

영상처리 기법을 이용한 얼굴검출에 관한 많은 다양한 방법들이 제시되어 왔다. 일반적으로 가장 많이 쓰이는 얼굴 검출 방식은 Viola와 Jones이 제안한 Adaboost 방식이다. 이 방식은 Haar-like feature을 이용하여 얼굴영상을 선행 학습하고, 검출 성능은 학습된 DB에 의존한다. 이는 일정 거리 범위 안의 학습된 얼굴 크기에서는 얼굴 검출을 잘 수행하지만, 카메라에서 객체(얼굴)의 거리가 멀어지면 얼굴 크기가 작아져 기존에 학습한 Haar-like feature로 얼굴 검출을 하지 못하는 경우가 발생한다. 이에 본 논문에서는 생물학 기반의 선택적 주의집중 기반의 Haar-like feature 정보를 이용한 Adaboost 모델과 사용자의 시선 응시 점 정보를 이용하여, 사용자의 관심영역 확장을 통한 원거리 얼굴 검출 모델을 제안한다. 생물학적 기반의 선택적 주의 집중 모델인 돌출맵(Saliency map) 정보를 이용하여 입력 영상에 대하여 얼굴 후보 영역을 검출하고, 검출된 얼굴 후보 영역 중에서 선행 학습된 Haar-like feature 정보로 Adaboost 알고리즘을 이용하여 최종 얼굴 영상을 검출한다. 그리고 사용자의 시선 응시 점 정보는 관심영역을 선택 하는데 이용된다. 피 실험자가, 카메라로부터 멀리 거리 떨어져 얼굴의 크기가 얼굴검출이 힘들더라도 사용자 시선 응시 점 영역을 선형 보간법으로 확대하여 입력영상으로 재사용함으로써 얼굴 검출 성능을 높일 수 있다. 제안된 방법이 기존의 Adaboost 방법보다 얼굴 검출 성능과 수행시간 면에서 우수함을 실험을 통해 확인하였다.