• Title/Summary/Keyword: 공간 분할 기법

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Three-Phase English Syntactic Analysis for Improving the Parsing Efficiency (영어 구문 분석의 효율 개선을 위한 3단계 구문 분석)

  • Kim, Sung-Dong
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.1
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    • pp.21-28
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    • 2016
  • The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.

Cross-Validation of SPT-N Values in Pohang Ground Using Geostatistics and Surface Wave Multi-Channel Analysis (지구통계기법과 표면파 다중채널분석을 이용한 포항 지반의 SPT-N value 교차검증)

  • Kim, Kyung-Oh;Han, Heui-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.10
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    • pp.393-405
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    • 2020
  • Various geotechnical information is required to evaluate the stability of the ground and a foundation once liquefaction occurs due to earthquakes, such as the soil strength and groundwater level. The results of the Standard Penetration Test (SPT) conducted in Korea are registered in the National Geotechnical Information Portal System. If geotechnical information for a non-drilled area is needed, geostatistics can be applied. This paper is about the feasibility of obtaining ground information by the Empirical Bayesian Kriging (EBK) method and the Inverse Distance Weighting Method (IDWM). Esri's ArcGIS Pro program was used to estimate these techniques. The soil strength parameter of the drilling area and the level of groundwater obtained from the standard penetration test were cross-validated with the results of the analysis technique. In addition, Multichannel Analysis of Surface Waves (MASW) was conducted to verify the techniques used in the analysis. The Buk-gu area of Pohang was divided into 1.0 km×1.0 km and 110 zones. The cross-validation for the SPT N value and groundwater level through EBK and IDWM showed that both techniques were suitable. MASW presented an approximate section area, making it difficult to clearly grasp the distribution pattern and groundwater level of the SPT N value.

A Study on Land Cover Map of UAV Imagery using an Object-based Classification Method (객체기반 분류기법을 이용한 UAV 영상의 토지피복도 제작 연구)

  • Shin, Ji Sun;Lee, Tae Ho;Jung, Pil Mo;Kwon, Hyuk Soo
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.4
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    • pp.25-33
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    • 2015
  • The study of ecosystem assessment(ES) is based on land cover information, and primarily it is performed at the global scale. However, these results as data for decision making have a limitation at the aspects of range and scale to solve the regional issue. Although the Ministry of Environment provides available land cover data at the regional scale, it is also restricted in use due to the intrinsic limitation of on screen digitizing method and temporal and spatial difference. This study of objective is to generate UAV land cover map. In order to classify the imagery, we have performed resampling at 5m resolution using UAV imagery. The results of object-based image segmentation showed that scale 20 and merge 34 were the optimum weight values for UAV imagery. In the case of RapidEye imagery;we found that the weight values;scale 30 and merge 30 were the most appropriate at the level of land cover classes for sub-category. We generated land cover imagery using example-based classification method and analyzed the accuracy using stratified random sampling. The results show that the overall accuracies of RapidEye and UAV classification imagery are each 90% and 91%.

Application of Spatial Data Integration Based on the Likelihood Ratio Function nad Bayesian Rule for Landslide Hazard Mapping (우도비 함수와 베이지안 결합을 이용한 공간통합의 산사태 취약성 분석에의 적용)

  • Chi, Kwang-Hoon;Chung, Chang-Jo F.;Kwon, Byung-Doo;Park, No-Wook
    • Journal of the Korean earth science society
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    • v.24 no.5
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    • pp.428-439
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    • 2003
  • Landslides, as a geological hazard, have caused extensive damage to property and sometimes result in loss of life. Thus, it is necessary to assess vulnerable areas for future possible landslides in order to mitigate the damage they cause. For this purpose, spatial data integration has been developed and applied to landslide hazard mapping. Among various models, this paper investigates and discusses the effectiveness of the Bayesian spatial data integration approach to landslide hazard mapping. In this study, several data sets related to landslide occurrences in Jangheung, Korea were constructed using GIS and then digitally represented using the likelihood ratio function. By computing the likelihood ratio, we obtained quantitative relationships between input data and landslide occurrences. The likelihood ratio functions were combined using the Bayesian combination rule. In order for predicted results to provide meaningful interpretations with respect to future landslides, we carried out validation based on the spatial partitioning of the landslide distribution. As a result, the Bayesian approach based on a likelihood ratio function can effectively integrate various spatial data for landslide hazard mapping, and it is expected that some suggestions in this study will be helpful to further applications including integration and interpretation stages in order to obtain a decision-support layer.

Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern (사용자 행동 패턴 선호도 학습을 위한 퍼지 귀납 학습 시스템)

  • Lee Hyong-Euk;Kim Yong-Hwi;Park Kwang-Hyun;Kim Yong-Su;Jung Jin-Woo;Cho Joonmyun;Kim MinGyoung;Bien Z. Zenn
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.175-178
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    • 2005
  • 스마트 홈과 같은 유비쿼터스 환경은 다양한 센서 및 제어 네트워크가 밀집되어 있는 복잡한 시스템이다. 본 논문에서는 이러한 환경하에서 복잡한 인터페이스의 사용에 대한 사용자의 인지 부담(cognitive load)를 줄이고 개인화된(personalized) 서비스를 자율적으로 제공하기 위한 사용자 행동 패턴 선호도 학습 기법을 제안한다. 이를 위해 지식 발견(Knowledge Discovery)을 위한 평생 학습(life-long learning)의 관점에서 퍼지 귀납(Fuzzy Inductive)학습 방법론을 제안하며, 이것은 수치 데이터로부터 입력 공간에 대한 효율적인 퍼지 분할(fuzzy partition)을 얻어내고 일관성있는(consisitent) 퍼지 상관 룰(fuzzy association rule)을 얻어내도록 한다.

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The Binary Tree Vector Quantization Using Human Visual Properties (인간의 시각 특성을 이용한 이진 트리 벡터 양자화)

  • 유성필;곽내정;박원배;안재형
    • Journal of Korea Multimedia Society
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    • v.6 no.3
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    • pp.429-435
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    • 2003
  • In this paper, we propose improved binary tree vector quantization with consideration of spatial sensitivity which is one of the human visual properties. We combine weights in consideration with the responsibility of human visual system according to changes of three primary color in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. Also we propose the novel quality measure of the quantization images that applies MTF(modulation transfer function) to luminance value of quantization error of color image. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get less quantized level images and can reduce the resource occupied by the quantized image.

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The Design of Technique Based on Partition for Acceleration of ATPG (ATPG 가속화를 위한 분할 기법의 설계)

  • 허덕행
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.2
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    • pp.69-76
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    • 1998
  • To test all internal faults in the case that the number of Primary Input is N, we need patterns that are composed of PI's of maximum 2N. In this paper, we proposed the method to reduce a search space by dividing the multiple output circuit into subcircuit that is related with output. And this method, called PBM(Partition-Based Method), can generate a set of test pattern. The method can effectively generate a test pattern for evaluating all fault of circuit, because the length of input pattern is smaller than that of full circuit and PBM doesn't search any signal line that is not concerned with detecting fault.

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3D Cloth Simulation System based on 2D Cloth Pattern Design (2D 옷감 패턴 디자인 기반 3D 의복 시뮬레이션 시스템)

  • Kim, Ju-Ri;Cho, Jin-Ei;Han, Sung-Kook;Lee, Yong-Ju;Joung, Suck-Tae;Jung, Sung-Tae
    • Annual Conference of KIPS
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    • 2005.11a
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    • pp.1399-1402
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    • 2005
  • 본 논문은 여러 옷감 조각들을 이용하여 가상의 3차원 인체 모델에 옷을 입히기 위한 의복 시뮬레이션 시스템을 제안한다. 본 논문에서 의상 제작 과정에 사용한 방법은 2차원 옷감 조각을 디자인하는 과정과 옷감 조각을 재봉하고 여기에 제약점을 정하여 3차원 인체 모델에 의상을 입히는 과정으로 구성된다. 제안된 시스템은 3차원 인체 모델 파일과 2차원 재단 패턴 파일을 읽어 들인 다음 질량-스프링 모델에 기반한 물리적 시뮬레이션에 의해 의복을 착용한 3D 모델을 생성한다. 본 논문의 시스템은 사실적인 시뮬레이션을 위하여 인체 모델을 구성하는 삼각형과 의복을 구성하는 삼각형 사이의 충돌을 검사하고 반응 처리를 수행하였다. 인체를 구성하는 삼각형의 수가 매우 많으므로, 이러한 충돌 검사 및 반응 처리는 많은 시간을 필요로 한다. 이 문제를 해결하기 위하여, 본 논문에서는 Octree 공간 분할 기법을 이용하여 충돌 검사 및 반응 처리 수를 줄이는 방법을 이용하여 사실적인 영상을 생성할 수 있었고, 수초 이내에 가상 인체 모델에 의복을 입힐 수 있었다.

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A Hashing Method Using PCA-based Clustering (PCA 기반 군집화를 이용한 해슁 기법)

  • Park, Cheong Hee
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.6
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    • pp.215-218
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    • 2014
  • In hashing-based methods for approximate nearest neighbors(ANN) search, by mapping data points to k-bit binary codes, nearest neighbors are searched in a binary embedding space. In this paper, we present a hashing method using a PCA-based clustering method, Principal Direction Divisive Partitioning(PDDP). PDDP is a clustering method which repeatedly partitions the cluster with the largest variance into two clusters by using the first principal direction. The proposed hashing method utilizes the first principal direction as a projective direction for binary coding. Experimental results demonstrate that the proposed method is competitive compared with other hashing methods.

Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern (사용자 행동 패턴 선호도 학습을 위한 퍼지 귀납 학습 시스템)

  • Lee Hyong-Euk;Kim Yong-Hwi;Park Kwang-Hyun;Kim Yong-Su;June Jin-Woo;Cho Joonmyun;Kim MinGyoung;Bien Z. Zenn
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.805-812
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    • 2005
  • Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.