• Title/Summary/Keyword: Grouping Method

검색결과 611건 처리시간 0.044초

Reverse Engineering 기술을 적용한 복합면의 재구성 정보 추출을 위한 연구 (The Study on Reconstruction of Composite Surfaces by Reverse Engineering Techniques)

  • 서지한;이홍철;손영태;박세형
    • 산업공학
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    • 제12권2호
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    • pp.205-209
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    • 1999
  • In reverse engineering area, the reconstruction of surfaces from scanned or digitized data is being developed, but geometric model of existing objects is not available in industries. This paper presents the new approach to the reconstruction of surface technique. A proposed methodology finds base geometry and blends surface between them. Each based geometry is divided by tri-angular patches which are compared with their normal vector for face grouping. Each group is categorized analytical surface such as a part of cylinder, sphere and cone, and plane shapes to represent the based geometry surface. And then, each based geometry surface is implemented to the infinitive surface. Infinitive surface's intersections are trimmed by boundary representation model reconstruction. This method has several benefits such as time efficiency and automatic functional modeling system in reverse engineering. Especially, it can be directly applied 3D fax and 3D copier.

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신경망을 이용한 GT 부품군 형성의 자동화 (Grouping Parts Based on Group Technology Using a Neural Network)

  • 이성열
    • 산업공학
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    • 제11권2호
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    • pp.119-124
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    • 1998
  • This paper proposes a new part family classification system (IPFACS: Image Processing and Fuzzy ART based Clustering System), which incorporates image processing techniques and a modified fuzzy ART neural network algorithm. IPFACS can classify parts based on geometrical shape and manufacturing attributes, simultaneously. With a proper reduction and normalization of an image data through the image processing methods and adding method in the modified Fuzzy ART, different types of geometrical shape data and manufacturing attribute data can be simultaneously classified in the same system. IPFACS has been tested for an example set of hypothetical parts. The results show that IPFACS provides a good feasible approach to form families based on both geometrical shape and manufacturing attributes.

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Development of the forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data

  • Sasakawa, Hiroshi;Tsuyuki, Satoshi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.467-469
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    • 2003
  • This research aimed to develop forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data. QuickBird data was used as satellite data. The method of this research was to extract satellite data for every single tree crown using image segmentation technique, then to evaluate the accuracy of classification by changing grouping criteria such as tree species, families, coniferous or broad-leaved species, and timber prices. As a result, the classification of tree species and families level was inaccurate, on the other hand, coniferous or broad-leaved species and timber price level was high accurate.

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빅데이터 환경에서 학습 정확도 향상을 위한 의미 계층 기반 속성 집단화 기법 (A Method of Grouping Features from Big Data based on Semantic Hierarchy for Accuracy Enhancement)

  • 이건선;이건수;강병권
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2019년도 추계학술발표대회
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    • pp.892-894
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    • 2019
  • 빅데이터 기반의 기계학습은 대규모 데이터를 이용하여, 숨겨진 패턴을 찾아내는 학습과정과, 그렇게 찾아낸 패턴을 이용하여 새로운 데이터를 해석하는 추론과정으로 이루어진다. 이 과정을 통해 학습된 패턴은 데이터를 구성하는 속성들과 긴밀한 연관성을 갖고 있다. 학습에 사용된 데이터의 원 데이터를 구성하는 각각의 속성과 추론 결과가 동일한 계층 관계를 갖고 있다면, 모든 속성을 동일하게 처리할 수 있지만, 그렇지 않은 경우, 속성들 사이의 계층 정보를 고려하는 것이, 추론 결과의 정확도를 높일 수 있다. 이에 본 연구에서는 속성들 사이의 계층 관계를 고려한 추론 기법을 제안하고, 사례연구를 통해 제안 방법을 실제 상황에 적용하는 방법을 제시한다.

안드로이드 앱의 랜덤 인텐트 테스트에서 동일한 에러 로그를 자동으로 그룹화하는 방법 (An Automatic Method for Grouping Identical Error Logs in Random Intent Testing on Android Apps)

  • 김현순;윤성빈;최지선;고명필;최광훈
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2015년도 추계학술발표대회
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    • pp.1007-1010
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    • 2015
  • 안드로이드 앱의 인텐트 취약점을 테스트하는 인텐트 퍼저에서 에러 확인 방법을 효율적으로 개선한 새로운 아이디어를 제안한다. 인텐트 퍼저는 랜덤 인텐트를 생성하여 앱을 실행한 다음 앱이 비정상 종료되는지 확인하는 테스트 도구이다. 이 논문에서 동일한 에러로 인해 발생한 다수의 비정상 종료 로그들을 하나의 그룹으로 만드는 자동 분류 방법을 제안한다. 테스터는 각 그룹의 대표 로그만 확인하면 된다. 최장 공통 부분 수열을 구하는 알고리즘을 응용하여 이 방법을 설계하였고, 이 방법을 상용 안드로이드 앱 10개에 적용해 실험하였다. 모든 로그를 분석하는 대신 대표 로그를 분석하는 것으로 대체할 수 있음을 확인하였다. 그 결과 분석 대상 로그의 수가 크게 줄었다.

제조 셀 구현을 위한 군집분석 기반 방법론 (Cluster Analysis-based Approach for Manufacturing Cell Formation)

  • 심영학;황정윤
    • 산업경영시스템학회지
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    • 제36권1호
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    • pp.24-35
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    • 2013
  • A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

PPI 네트워크를 이용한 SNP 군집화 및 질병 연관성 분석 (SNP Grouping Method Based on PPI Network Information)

  • 이규범;이선원;강재우
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2012년도 춘계학술발표대회
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    • pp.923-925
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    • 2012
  • 대용량 고차원의 생물학 데이터가 매우 빠른 속도로 생산되는 현재, 단순히 고전적인 알고리즘들로는 풀 수 없는 문제들을 맞이하게 되었다. 이러한 문제들의 경우 시스템 생물학의 관점으로 다양한 생물 데이터의 융합을 통하여 접근할 경우 효율적으로 Computational Infeasibility(계산 불가능)를 해결함은 물론 그 해석 및 새로운 정보 획득에 매우 유리하다. 인간 DNA의 고차원 SNP 정보들의 군집화 및 질병 발현 패턴 분석은 그 조합의 수가 입력 데이터의 차원수에 따라 지수적(Exponentially)으로 증가하지만 PPI(단백질 상호작용) 네트워크 정보에 결합하여 필요한 중요부위를 선택적으로 이용할 경우 효율적으로 필요 SNP들의 선택 및 이로 인한 공간 축소가 가능하다.

Genetic Diversity of Seven Strawberry mottle virus Isolates in Poland

  • Cieslinska, Miroslawa
    • The Plant Pathology Journal
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    • 제35권4호
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    • pp.389-392
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    • 2019
  • The studies on detection of the Strawberry mottle virus (SMoV) have been conducted in Poland for breeding programme purpose and for producers of strawberry plant material. Leaf samples collected from infected strawberry plants were grafted on Fragaria sp. Indicators which were maintained in greenhouse for further study. Seven Fragaria vesca var. semperflorens 'Alpine' indicators infected by SMoV were used for the study aimed on molecular characterization of virus isolates. Partial RNA2 was amplified from total nucleic acids using the RT-PCR method. The obtained amplicons separately digested with BfaI, FauI, HaeIII, HincI, and TaqI enzymes showed different restriction profiles. The nucleotide sequences analysis of RNA2 fragment confirmed the genetic diversity of the SMoV isolates as their similarity ranged from 94.7 to 100%. Polish isolates shared 75.7-99.2% identity with sequence of the virus strains from the Czech Republic, the Netherlands, and Canada. Phylogenetic analysis resulted in grouping of the isolates found in Poland together with one of the Czech strain whereas two other from the Czech and the strains from the Netherlands and Canada created the separate cluster.

Feasibility study of improved particle swarm optimization in kriging metamodel based structural model updating

  • Qin, Shiqiang;Hu, Jia;Zhou, Yun-Lai;Zhang, Yazhou;Kang, Juntao
    • Structural Engineering and Mechanics
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    • 제70권5호
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    • pp.513-524
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    • 2019
  • This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

Practical method to improve usage efficiency of bike-sharing systems

  • Lee, Chun-Hee;Lee, Jeong-Woo;Jung, YungJoon
    • ETRI Journal
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    • 제44권2호
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    • pp.244-259
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    • 2022
  • Bicycle- or bike-sharing systems (BSSs) have received increasing attention as a secondary transportation mode due to their advantages, for example, accessibility, prevention of air pollution, and health promotion. However, in BSSs, due to bias in bike demands, the bike rebalancing problem should be solved. Various methods have been proposed to solve this problem; however, it is difficult to apply such methods to small cities because bike demand is sparse, and there are many practical issues to solve. Thus, we propose a demand prediction model using multiple classifiers, time grouping, categorization, weather analysis, and station correlation information. In addition, we analyze real-world relocation data by relocation managers and propose a relocation algorithm based on the analytical results to solve the bike rebalancing problem. The proposed system is compared experimentally with the results obtained by the real relocation managers.