• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2001년도 학술논문발표회
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• pp.99-117
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• 2001

In the past, The selection of individual method of construction was done by head of construction site or an experienced person very frequently. By doing this, The wrong selection of construction method without exact adjudication of construction site situation lead to increasing of cost and extension of construction term. Finally it will effect all over the construction process. Especially, In case of Underground construction in the beginning, there are a lot of a variable factor and it also effect on the entire construction process and it need rely careful process. The purpose of this study is to present the best suitable methodology fer selection of construction method by considering potential risk of construction method and variables together with external condition for Underground construction. The purpose of this study is to select the most suitable construction method by analysing potential conditions(Construction site situation and Client. Request in designing) To do this, We prepared arrangement rule to arrangement conditions for construction method. And then make Checklist the analyzing construction method. Though above process, To expect the risk of individual construction method using above risk checklist and using Analytic Hierarchy Process among Multiple-Criteria Decision Making, the professional opinions is to be adapted. By doing this, It can lead and select the most suitable considering method considering the data which get from risk density test.

• 한국가스학회지
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• 제18권2호
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• pp.1-9
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• 2014

석탄층 메탄가스 저류층의 개발을 위해서는 석탄층 특성에 부합하는 생산방법을 적용하는 것이 중요하지만 대부분의 개발현장에서는 경험적인 판단에 의존하여 생산방법을 선정하고 있어 결과에 대한 신뢰도가 떨어질 뿐만 아니라 복잡한 시뮬레이션 해석을 통해 최적 생산방법을 규명해야 하는 등의 많은 시간과 노력이 필요하다는 문제점이 있다. 이에 본 연구에서는 인공신경망을 활용하여 석탄층 메탄가스 최적 생산방법을 선정하기 위한 지능형 시스템을 개발하였다. 시스템 개발에 앞서 문헌 조사를 통해 석탄층 메탄가스 생산방법 선정 가이드라인을 분석하였고, 이를 활용하여 시추 방법과 유정완결법 선정 시스템, 수압파쇄공법 수행시 파쇄액 선정 시스템을 개발하였다. 개발된 생산방법 선정 시스템의 타당성 평가 결과, 높은 정확도를 나타냄으로써 본 연구에서 개발된 생산방법 선정 시스템은 향후 석탄층 메탄가스의 개발에 앞서 석탄층 특성에 부합하는 생산방법을 선정할 수 있는 효율적인 도구로 활용될 것으로 판단된다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2003년도 춘계학술대회
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• pp.1-5
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• 2003

We purpose a decision model to select the optimal facilities for the Decision Making problems with multiple characteristics(nominal-is-best characteristics, larger-is -better characteristics, smaller- is -better characteristics). Using this model, concept of the loss function is used in this comprehensive method of for select the optimal preferred facilities. To solve the issue on the optimal preferred facilities for multiple characteristics, this study propose the loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.213-216
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• 2001

Key frame extraction is an important method of summarizing a long video. This paper propose a technique to automatically extract several key frames representative of its content from video. We use the color layout descriptor to select key frames from video. For selection of key frames, we calculate similarity of color layout features extracted from video, and extract key frames using similarity. An important aspect of our algorithm is that does not assume a fixed number of key frames per video; instead, it selects the number of appropriate key frames of summarizing a long video Experimental results show that our method using color layout descriptor can successfully select several key frames from a video, and we confirmed that the processing speed for extracting key frames from video is considerably fast.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.314-319
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• 1998

In this paper, for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theroy is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band usin indiscernibility relation of Rough sets theory from analysis results. Proposed method is applied to LAMDSAT TM data on 2, June, 1992. Among them, normal distributive data were experimented, mainly. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.211-216
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• 2006

The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

• 대한수학회보
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• 제53권1호
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• pp.1-20
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• 2016

The general number field sieve (GNFS) is asymptotically the fastest known factoring algorithm. One of the most important steps of GNFS is to select a good polynomial pair. A standard way of polynomial selection (being used in factoring RSA challenge numbers) is to select a nonlinear polynomial for algebraic sieving and a linear polynomial for rational sieving. There is another method called a nonlinear method which selects two polynomials of the same degree greater than one. In this paper, we generalize Montgomery's method [12] using geometric progression (GP) (mod N) to construct a pair of nonlinear polynomials. We also introduce GP of length d + k with $1{\leq}k{\leq}d-1$ and show that we can construct polynomials of degree d having common root (mod N), where the number of such polynomials and the size of the coefficients can be precisely determined.

• JSTS:Journal of Semiconductor Technology and Science
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• 제6권4호
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• pp.240-245
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• 2006

Viterbi decoder is composed of BMU(Branch metric Unit), ACSU(Add Compare Select Unit), and SMU(Survivor path Memory Unit). For high speed viterbi decoders, ACSU is the main bottleneck due to the compare-select and feedback operation. Thus, many studies have been advanced to solve the problem. For example, M-step look ahead technique and Minimized method are typical high speed algorithms. In this paper, we designed a bit-level ACSU(K=3, R=1/2, 4bit soft decision) based on those algorithms and switched the matrix product order in the backward direction of Minimized method so as to apply Code-Optimized-Array in order to reduce the area complexity. For experimentation, we synthesized our design by using SYNOPSYS Design compiler, with TSMC 0.18 um library, and verified the timing by using CADENCE verilog-XL.

• 한국컴퓨터정보학회논문지
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• 제20권12호
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• pp.29-36
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• 2015

In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.295-299
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• 2002

This paper presents an image contrast enhancement technique for improving low contrast images. We applied fuzzy logic to develop an image contrast enhancement technique in the viewpoint of considering that the low pictorial information of a low contrast image is due to the vaguness or fuzziness of the multivalued levels of brightness rather than randomness. The fuzzy image contrast enhancement technique consists of three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. In the stage of image fuzzification, we need to select a crossover point. To select the crossover point automatically the K-means algorithm is used. The problem of crossover point selection can be considered as the two-category, object and background, classification problem. The proposed method is applied to an experimental image with 256 gray levels and the result of the proposed method is compared with that of the histogram equalization technique. We used the index of fuzziness as a measure of image quality. The result shows that the proposed method is better than the histogram equalization technique.