• 제목/요약/키워드: product matching

검색결과 127건 처리시간 0.023초

가중치를 고려한 자동차 서브프레임의 인증 알고리즘 구현 (Development of Registration Algorithm considering Coordinate Weights for Automobile Sub-Frame Assembly)

  • 이광일;양승한;이영문
    • 한국기계가공학회지
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    • 제3권4호
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    • pp.7-12
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    • 2004
  • Inspection and analysis are essential process to determine whether a completed product is in given specification or not. Analysis of products with very complicated shape is difficult to carry out direct comparison between inspected coordinate and designed coordinates. So process called as matching or registrations is needed to solve this problem. By defining error between two coordinates and minimizing the error, registration is done. Registration consists of translation, rotation and scale transformations. Error must be defined to express feature of inspected product. In this paper, registration algorithm is developed to determine pose of sub-frame at assembly with body of automobile by defining error between two coordinates considering geometric feature of sub-frame.

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Structural results and a solution for the product rate variation problem : A graph-theoretic approach

  • 최상웅
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2004년도 추계학술대회 및 정기총회
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    • pp.250-278
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    • 2004
  • The product rate variation problem, to be called the PRVP, is to sequence different type units that minimizes the maximum value of a deviation function between ideal and actual rates. The PRVP is an important scheduling problem that arises on mixed-model assembly lines. A surge of research has examined very interesting methods for the PRVP. We believe, however, that several issues are still open with respect to this problem. In this study, we consider convex bipartite graphs, perfect matchings, permanents and balanced sequences. The ultimate objective of this study is to show that we can provide a more efficient and in-depth procedure with a graph theoretic approach in order to solve the PRVP. To achieve this goal, we propose formal alternative proofs for some of the results stated in the previous studies, and establish several new results.

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구매자 카테고리 기반 지능형 e-Commerce 메타 서치 엔진 (Buyer Category-Based Intelligent e-Commerce Meta-Search Engine)

  • 김경필;우상훈;김창욱
    • 산업공학
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    • 제19권3호
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    • pp.225-235
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    • 2006
  • In this paper, we propose an intelligent e-commerce meta-search engine which integrates distributed e-commerce sites and provides a unified search to the sites. The meta-search engine performs the following functions: (1) the user is able to create a category-based user query, (2) by using the WordNet, the query is semantically refined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user’s search intention by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

Learning-to-export Effect as a Response to Export Opportunities: Micro-evidence from Korean Manufacturing

  • HAHN, CHIN HEE;CHOI, YONG-SEOK
    • KDI Journal of Economic Policy
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    • 제43권4호
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    • pp.1-21
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    • 2021
  • This paper aims to investigate whether there is empirical evidence supporting the learning-to-export hypothesis, which has received little attention in the literature. By taking full advantage of plant-product level data from Korea during 1990-1998, we find some evidence for the learning-to-export effect, especially for the innovated product varieties with delayed exporters: their productivity, together with research and development and investment activity, was superior to their matched sample. On the other hand, this learning-to-export effect was not significantly pronounced for industries protected by import tariffs. Thus, our empirical findings suggest that it would be desirable to implement certain policy tools to promote the learning-to-export effect, whereas tariff protection is not justifiable for that purpose.

인공위성 기반 토양 수분 자료들(AMSR2, ASCAT, and ESACCI)의 한반도 적절성 분석: 동결과 융해 기간을 구분하여 (Analysis on Adequacy of the Satellite Soil Moisture Data (AMSR2, ASCAT, and ESACCI) in Korean Peninsula: With Classification of Freezing and Melting Periods)

  • 백종진;조성근;이슬찬;최민하
    • 대한원격탐사학회지
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    • 제35권5_1호
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    • pp.625-636
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    • 2019
  • 토양수분은 수문순환에 핵심적인 역할을 하는 대표적인 인자로써 대기와 지표 사이의 상호작용에 관여하며, 농업, 수자원, 대기 등의 분야에서 활용되고 있다. 한반도 영역의 위성기반 토양수분의 적용성 및 불확실성 분석을 위하여 Advanced Microwave Scanning Radiometer 2 (AMSR2), Advanced SCATterometer (ASCAT), European SpaceAgency Climate Change Initiative (ESACCI) 데이터가 사용되었다. 상기 데이터를 사용한 Cumulative Distribution Function (CDF) Matching과 Triple collocation (TC) 분석을 수행하여 위성 토양수분 데이터 보정 및 불확실성에 관한 연구를 진행하였다. 보정 전의 인공위성 기반 토양수분자료를 Automated Agriculture Observing System (AAOS) 관측지점과 비교한 결과, ESACCI와 ASCAT자료는 AAOS의 경향을 잘 반영하였다. 그에 비해 AMSR2 위성 자료는 동결기간에 과대 산정되었다. CDF Matching을 이용하여 인공위성 토양수분 자료를 보정한 결과, 보정 전보다 오차 및 상관성이 개선되었다. 마지막으로, TC 방법을 이용하여 토양수분 자료의 불확실성 분석을 실시하였다. CDF Matching 보정을 실시한 인공위성 토양수분의 불확실성이 동결과 융해 기간에서 확연하게 개선되는 것을 확인할 수 있었다. 한반도에서는 보정을 실시하였을 때, AMSR2 토양수분 자료보다 ASCAT과 ESACCI를 활용하는 것이 보다 정확한 토양수분 결과를 나타낼 수 있을 것으로 나타났다.

인플루언서를 위한 딥러닝 기반의 제품 추천모델 개발 (Deep Learning-based Product Recommendation Model for Influencer Marketing)

  • 송희석;김재경
    • Journal of Information Technology Applications and Management
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    • 제29권3호
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    • pp.43-55
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    • 2022
  • In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.

Product-Service System(PSS) 성공과 실패요인에 관한 탐색적 사례 연구 (Exploratory Case Study for Key Successful Factors of Producy Service System)

  • 박아름;진동수;이경전
    • 지능정보연구
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    • 제17권4호
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    • pp.255-277
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    • 2011
  • PSS(Product Service System) 시스템은 제품과 서비스가 하나로 통합되어 고객에게 차별화된 가치를 제공하고, 기업이 경쟁력을 가지고 지속적인 성장을 할 수 있게 지원하는 시스템이다. 본 논문에서는 PSS 시스템으로 성공한 Amazon의 Kindle과 Apple의 iPod, 실패한 Microsoft의 Zune과 Sony의 e-book reader를 채택하여 중다 사례연구 방법론을 통해 성공요인과 실패요인을 도출하고자 한다. 이를 위하여, 사례 분석을 통해 가설을 도출하고, 연관 문헌연구와의 비교 및 분석을 통하여 PSS 시스템에서 상업적으로 성공하기 위한 전략적 시사점을 제시하였다.

화상처리 기법을 이용한 디버링 시스템에 관한 연구 (A Study of Deburring System Using The Image Processing Technique)

  • 배준영;주윤명;최상균;이상룡
    • 한국정밀공학회지
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    • 제19권6호
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    • pp.128-135
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    • 2002
  • Burr is a projected part of finished workpiece. It is unavoidable and undesirable by-product of most metal cutting or shearing process. Also, it must be removed to improve the fit of machined parts, safety of workers, and the effectiveness of finishing operation. But deburring process Is one of manufacturing processes that have not been successfully automated, so deburring automation is strongly needed. This paper focused on developing a basic algorithm to find edge of workpiece and match two different image data for deburring automation which includes automatic recognition of parts, generation of deburring tool paths and edge/comer finding ability by analyzing the DXF drawing file which contains information of part geometry. As an algorithm fur corner finding, SUSAN method was chosen. It makes good performance in finding edge and corner in suitable time. And this paper suggested a simple algorithm to find matching point between CCD image and drawing file.

Complexity and Algorithms for Optimal Bundle Search Problem with Pairwise Discount

  • Chung, Jibok;Choi, Byungcheon
    • 유통과학연구
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    • 제15권7호
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    • pp.35-41
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    • 2017
  • Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

시공간 EPC 데이터 처리를 위한 선택률 기반 효율적인 연속질의 처리 기법 (Efficient continuous query processing technique based on selectivity for EPC data with time and location)

  • 추병조;홍봉희;김기홍
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2008년도 공동추계학술대회
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    • pp.100-105
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    • 2008
  • EPCglobal은 기업 간의 물류 활동 촉진과 글로벌 유통물류 시스템 구축을 위하여 EPCglobal Architecture Framework을 제시 하였다. EPCglobal Architecture Framework의 한 구성 요소인 EPCIS(Electronic Product Code Information Services)는 EPC, 시간, 위치와 같은 물류 관련 정보에 대해 저장 및 검색 서비스를 제공한다. EPCIS는 단발성 질의(poll)와 연속 질의(subscribe) 검색 서비스를 제공한다. EPCIS의 연속 질의는 시스템 자동화 및 재고 관리, 공급망 관리를 위해 다양한 응용에서 활용이 가능하다. 일반적으로 연속 질의 처리를 위해서는 등록된 연속 질의와 입력된 데이터를 순차적으로 비교하는 Sequential Matching 기법을 사용한다. Sequential Matching기법은 등록된 연속 질의 수가 증가 할 경우 많은 부하를 발생 시키고, 이로 인해 시스템 처리 지연이 발생한다. 본 논문에서는 EPCIS의 시공간 EPC 데이터의 연속질의 처리 성능 향상을 위해 선택률 기반 효율적인 연속질의 처리 기법을 제안한다. 13차원의 도메인을 여러 개의 질의 색인으로 구성하고, 등록된 질의 정보를 기반으로 선택률을 계산한다. 선택률에 의해 변경되는 동적 질의 실행 계획을 제안함으로써, EPCIS에서 시공간 EPC 데이터의 연속질의 처리에 대해 평균 60%의 성능이 향상이 가능하도록 하였다.

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