• Title/Summary/Keyword: 축소비

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SPVD based Dimension Reduction Algorithm using Vector Angle of Spectral Curve for Material Classification (물질분류를 위한 분광곡선의 벡터 각을 이용한 SPVD 차원축소 알고리즘)

  • Yu, Jae-Hwan;Kim, Deok-Hwan
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06b
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    • pp.387-389
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    • 2012
  • 초분광영상은 사람이 볼 있는 가시광선 영역부터 자외선 파장 대역까지 수십에서 수천 개의 데이터를 가지고 있는 고차원 데이터이다. 그렇기 때문에 초분광영상을 이용한 연구에는 많은 저장 공간과 고사양의 성능을 필요로 한다. 따라서 초분광영상의 차원을 감소시켜 데이터용량을 줄이고, 처리속도를 향상시키기 위한 연구들이 이루어지고 있다. 기존에 자주 사용되던 방법인 PCA와 ICA는 차원축소를 위하여 고유벡터를 계산하고 이를 이용하여 축을 변경하여 차원축소를 한다. 하지만 초분광영상에서는 이러한 방법으로 차원을 축소할 시 정확도가 감소한다. 따라서 본 논문에서는 특징 밴드를 추출하고 이를 이용하여 차원축소를 하는 SPVD 알고리즘을 제안한다. SPVD(Spectral pair vector decomposition) 알고리즘은 d개의 그룹으로 나누고 각 그룹들의 양벡터 각과 음벡터 각을 계산한 후 이를 이용하여 차원축소를 한다. 실험 결과 PCA는 61차원에서 70.05%, ICA는 71차원에서 63.03% 정확도를 보이는데 비해 SPVD 알고리즘은 3차원에서 83% 정확도를 보였다.

Using noise filtering and sufficient dimension reduction method on unstructured economic data (노이즈 필터링과 충분차원축소를 이용한 비정형 경제 데이터 활용에 대한 연구)

  • Jae Keun Yoo;Yujin Park;Beomseok Seo
    • The Korean Journal of Applied Statistics
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    • v.37 no.2
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    • pp.119-138
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    • 2024
  • Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

A Sentence Reduction Method using Part-of-Speech Information and Templates (품사 정보와 템플릿을 이용한 문장 축소 방법)

  • Lee, Seung-Soo;Yeom, Ki-Won;Park, Ji-Hyung;Cho, Sung-Bae
    • Journal of KIISE:Software and Applications
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    • v.35 no.5
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    • pp.313-324
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    • 2008
  • A sentence reduction is the information compression process which removes extraneous words and phrases and retains basic meaning of the original sentence. Most researches in the sentence reduction have required a large number of lexical and syntactic resources and focused on extracting or removing extraneous constituents such as words, phrases and clauses of the sentence via the complicated parsing process. However, these researches have some problems. First, the lexical resource which can be obtained in loaming data is very limited. Second, it is difficult to reduce the sentence to languages that have no method for reliable syntactic parsing because of an ambiguity and exceptional expression of the sentence. In order to solve these problems, we propose the sentence reduction method which uses templates and POS(part of speech) information without a parsing process. In our proposed method, we create a new sentence using both Sentence Reduction Templates that decide the reduction sentence form and Grammatical POS-based Reduction Rules that compose the grammatical sentence structure. In addition, We use Viterbi algorithms at HMM(Hidden Markov Models) to avoid the exponential calculation problem which occurs under applying to Sentence Reduction Templates. Finally, our experiments show that the proposed method achieves acceptable results in comparison to the previous sentence reduction methods.

A Column Shortening on High-Rise Building and Structural Effect under seismic load (초고층 건물의 기둥축소와 지진하중에 대한 구조적 영향)

  • 정은호;김희철
    • Journal of the Earthquake Engineering Society of Korea
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    • v.1 no.3
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    • pp.59-68
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    • 1997
  • The necessity of a high-rise building in big cities gave a new problem to structural engineers. The shortening effect of vertical members needs special considerstion in the desigh and construction of high-rise buildings. The shortening of each column transfers load to nonstructural members such as partitions, cladding, and M/E systems which are not designed to carry gravity loads. Also, the slabs and beams will tilt due to the cumulative differential shortening of adjacent vertical members. The main purpose of estimating the total shortening of vertical structural members is to compensate the differential shortening between adjacent members. This paper presents the structural effect of differential shortening between in main structural members. Lateral earthquake load is applied to the 52 story concrete structure which has an initial vertical displacement due to the gravity load. Shortening amount for each vertical member was estimated using the computerized column shortening software. Comparison of stresses between the shortening corrected structure and the uncorrecated structure due to earthquake load was discussed.

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실례를 통한 초고층 건물 기둥의 부등축소량 예측 및 시공오차 보정

  • 송진규
    • Computational Structural Engineering
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    • v.10 no.1
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    • pp.62-69
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    • 1997
  • 본 고에서는 고층건물의 건설과정에서 발생하는 시간의 진행에 따른 기둥의 (장기)변형을 정확히 예측하고 이를 시공중에 보정하도록 함으로써 비구조요소의 강도와 사용을 만족시키기 위한 방법론을 제시하였다. 이 방법론은 실험적 통계치를 기초로 한 약산해법으로서 실무에 쉽게 적용할 수 있다. 52층 RC 건물에 대한 적용 결과 기둥에 발생하는 축소량에 가장 큰 영향을 미치는 것은 탄성변형이며, 건조수축의 효과가 가장 미세한 것으로 나타났다. 그러나, 2년 이상의 장기 변형이 지속될 경우 크립변형의 영향이 탄성변형에 비해 더욱 증가할 것으로 판단된다. 고층의 RC건물인 경우 기둥간 부등축소량의 최대치(=최대 시공오차)는 중간층 근처에서 발생하는 것으로 나타났다.

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Features Reduction and Baysian Networks Learning for Efficient Medical Data Mining (효율적인 의료데이터마이닝을 위한 특징축소와 레이지안망 학습)

  • 정용규;김인철
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.258-265
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    • 2002
  • 베이지안망은 기존의 방법에 비해 불확실한 상황에서도 지식을 표현하고 결론을 추론하는데 유용한 것으로 알려져 있다. 본 논문에서는 대표적인 베이지안망 분류기들을 제시하고, 동일 임상데이터에 대해 서로 다른 유형별 베이지안망 분류기들을 학습하였다. 베이지안망을 적용할 때 변수의 수가 많아짐에 따라 베이지안망의 구조를 학습하는데 탐색공간이 넓어져 어려움이 있다. 본 연구에서는 이런 탐색공간을 효율적으로 줄이기 위하여 클래스 노드의 Markov blanket에 속한 특징들로 집합을 축소하는 것을 제안하고, 실험을 통해 이 특징 축소방법이 베이지안망 분류기들의 성능을 높여 줄 수 있는지 알아보았다. 분류기들의 성능에서는 축소한 특징집합으로부터 얻은 베이지안망으로 확장한 나이브 베이지안망 분류기가 가장 우수한 정확도를 가짐을 실험을 통해 알 수 있었다.

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기선권현망어업의 어구 개량과 자동화 조업시스템 개발 - IX - 자동화 조업시스템 개발 -

  • 장충식;김광홍;안영수
    • Proceedings of the Korean Society of Fisheries Technology Conference
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    • 2001.10a
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    • pp.43-44
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    • 2001
  • 권현망어업은 어구 규모의 비대로 인해 조업자동화가 타 어업에 비해 매우 지연되고 있는 실정이며, 최근 들어 어획량감소로 인해 어업경영에 어려움이 가중되고 조업 경비 중 인건비가 50% 정도를 차지하고 있어 조업자동화가 시급히 요구되는 어업이다. 따라서, 권현망어업의 경영합리화를 위해서는 현재보다 축소된 어구의 개발과 더불어 선단규모의 축소를 통한 조업자동화방안이 구축되어야만 할 것이다. (중략)

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A fast decoding algorithm using data dependence in fractal image (프래탈 영상에서 데이타 의존성을 이용한 고속 복호화 알고리즘)

  • 류권열;정태일;강경원;권기룡;문광석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.10
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    • pp.2091-2101
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    • 1997
  • Conventional method for fractal image decoding requires high-degree computational complexity in decoding propocess, because of iterated contractive transformations applied to whole range blocks. In this paper, we propose a fast decoding algorithm of fractal image using data depence in order to reduce computational complexity for iterated contractive transformations. Range of reconstruction image is divided into a region referenced with domain, called referenced range, and a region without reference to domain, called unreferenced range. The referenced range is converged with iterated contractive transformations, and the unreferenced range can be decoded by convergence of the referenced range. Thus the unreferenced range is called data dependence region. We show that the data dependence region can be deconded by one transformation when the referenced range is converged. Consequently, the proposed method reduces computational complexity in decoding process by executing iterated contractive transformations for the referenced range only.

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Collapse Behavior of Small-Scaled RC Structures Using Felling Method (전도공법에 의한 축소모형 철근콘크리트 구조물의 붕괴거동)

  • Park, Hoon;Lee, Hee-Gwang;Yoo, Ji-Wan;Song, Jeung-Un;Kim, Seung-Kon
    • Tunnel and Underground Space
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    • v.17 no.5
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    • pp.381-388
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    • 2007
  • The regular RC structures have been transformed into irregular RC structures by alternate load of RC structures during explosive demolition. Numerical simulation programs have contributed to a better understanding of large displacement collapse behavior during explosive demolition, but there remain a number of problems which need to be solved. In this study, the 1/5 scaled 1, 3 and 5 stories RC structures were designed and fabricated. To consider the collapse possibility of upper dead load, fabricated RC structures were demolished by means of felling method. To observe the collapse behavior of the RC structures during felling, displacement of X-direction (or horizontal), displacement of Z-direction (or vertical) md relative displacement angle from respective RC structures were analyzed. Finally explosive demolition on the scaled RC structures using felling method are carried out, collapse behavior by felling method is affected by upper dead load of scaled RC structures. Displacement of X and Z direction increases gradually to respective 67ms and 300ms after blasting. It is confirmed that initial collapse velocity due to alternate load has a higher 3 stories RC structures than 5 stories.