• Title/Summary/Keyword: select method

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A Study on the Selection of Underground Construction Method by Risk Analysis (리스크 분석을 통한 지하 구조체 공법 선정에 관한 연구)

  • 윤여완;양극영;홍성휘
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2001.11a
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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.

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Development of Intelligent System to Select Production Method in Coalbed Methane Reservoir (석탄층 메탄가스 저류층의 생산방법 선정을 위한 지능형 시스템 개발)

  • Kim, Chang-Jae;Kim, Jung-Gyun;Lee, Jeong-Hwan
    • Journal of the Korean Institute of Gas
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    • v.18 no.2
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    • pp.1-9
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    • 2014
  • To develop a coalbed methane(CBM) reservoir, it is important to apply production methods such as drilling, completion, and stimulation which coincide with coal properties. However, the reliability of the selected resulted in most of CBM field is not enough to accept because the selection of production method has been done by empirical decision. As the result, the empirical decision show inaccurate results and need to prove using simulation whether it was true exactly. In this study, the intelligent system has been developed to assist the selection of CBM production method using artificial neural network(ANN). Before the development of the system, technical screening guideline was analyzed by literature survey and the system to select drilling and completion method, and hydraulic fracture fluid was developed by utilizing the guideline. The result as a validation of the developed system showed a high accuracy. In conclusion, it has been confirmed that the developed system can be utilized as a effective tool to select production method in CBM reservoir.

Selecting the Optimal Facilities using Multiple Characteristics Loss Function (다특성치 손실함수를 이용한 최적설비 결정)

  • 허준영;서장훈;조용욱;박명규
    • Proceedings of the Safety Management and Science Conference
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    • 2003.05a
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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.

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The Extracting Method of Key-frame Using Color Layout Descriptor (컬러 레이아웃을 이용한 키 프레임 추출 기법)

  • 김소희;김형준;지수영;김회율
    • Proceedings of the IEEK Conference
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    • 2001.06c
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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.

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Band Feature Extraction of Normal Distributive Multispectral Image Data using Rough Sets

  • Chung, Hwan-mook;Won, Sung-Hyun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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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.

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Unsupervised Endmember Selection Optimization Process based on Constrained Linear Spectral Unmixing of Hyperion Image (Hyperion 영상의 제약선형분광혼합분석 기반 무감독 Endmember 추출 최적화 기법)

  • Choi Jae-Wan;Kim Yong-Il;Yu Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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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.

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ON NONLINEAR POLYNOMIAL SELECTION AND GEOMETRIC PROGRESSION (MOD N) FOR NUMBER FIELD SIEVE

  • Cho, Gook Hwa;Koo, Namhun;Kwon, Soonhak
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.1
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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.

A Bit-level ACSU of High Speed Viterbi Decoder

  • Kim, Min-Woo;Cho, Jun-Dong
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.6 no.4
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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.

The horizontal line detection method using Haar-like features and linear regression in infrared images

  • Park, Byoung Sun;Kim, Jae Hyup
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.12
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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.

A Fuzzy Image Contrast Enhancement Technique using the K-means Algorithm (K-means 알고리듬을 이용한 퍼지 영상 대비 강화 기법)

  • 정준희;김용수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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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.