• 제목/요약/키워드: Similarity Model

검색결과 1,498건 처리시간 0.028초

근사 상사 이론을 이용한 비축대칭 등온 단조의 가공하중 예측 (Prediction of the Forming Load of Non-Axisymmetric Isothermal Forging using Approximate Similarity Theory)

  • 최철현
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 1999년도 춘계학술대회논문집
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    • pp.71-75
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    • 1999
  • An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity geometrical size and die velocity of model materials are different from those of real materials. Actually the forming load of yoke which is an automobile part made of aluminum alloys(Al-6061) is predicted by using this approximate similarity theory. Firstly upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061) and a suitable model material is selected for model material test of Al-6061 And then and forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material which has been selected from above upset forging tests, The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

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A Method of Service Refinement for Network-Centric Operational Environment

  • Lee, Haejin;Kang, Dongsu
    • 한국컴퓨터정보학회논문지
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    • 제21권12호
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    • pp.97-105
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    • 2016
  • Network-Centric Operational Environment(NCOE) service becomes critical in today's military environment network because reusability of service and interaction are being increasingly important as well in business process. However, the refinement of service by semantic similarity and functional similarity at the business process was not detailed yet. In order to enhance accuracy of refining of business service, in this study, the authors introduce a method for refining service by semantic similarity and functional similarity in BPMN model. The business process are designed in a BPMN model. In this model, candidated services are refined through binding related activities by the analysis result of semantic similarity based on word-net and functional similarity based on properties specification between activities. Then, the services are identified through refining the candidated service. The proposed method is expected to enhance the service identification with accuracy and modularity. It also can accelerate more standardized service refinement developments by the proposed method.

Dynamic gesture recognition using a model-based temporal self-similarity and its application to taebo gesture recognition

  • Lee, Kyoung-Mi;Won, Hey-Min
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권11호
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    • pp.2824-2838
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    • 2013
  • There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

Empirical Comparison of Word Similarity Measures Based on Co-Occurrence, Context, and a Vector Space Model

  • Kadowaki, Natsuki;Kishida, Kazuaki
    • Journal of Information Science Theory and Practice
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    • 제8권2호
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    • pp.6-17
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    • 2020
  • Word similarity is often measured to enhance system performance in the information retrieval field and other related areas. This paper reports on an experimental comparison of values for word similarity measures that were computed based on 50 intentionally selected words from a Reuters corpus. There were three targets, including (1) co-occurrence-based similarity measures (for which a co-occurrence frequency is counted as the number of documents or sentences), (2) context-based distributional similarity measures obtained from a latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), and Word2Vec algorithm, and (3) similarity measures computed from the tf-idf weights of each word according to a vector space model (VSM). Here, a Pearson correlation coefficient for a pair of VSM-based similarity measures and co-occurrence-based similarity measures according to the number of documents was highest. Group-average agglomerative hierarchical clustering was also applied to similarity matrices computed by individual measures. An evaluation of the cluster sets according to an answer set revealed that VSM- and LDA-based similarity measures performed best.

근사 상사 이론을 이용한 비축대칭 등온 단조의 가공하중 예측 (Prediction of the Forming Load of Non-Axisymmetric Isothermal Forging using Approximate Similarity Theory)

  • 한정영;최철현;배원병;김영호;이종헌
    • 한국정밀공학회지
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    • 제17권1호
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    • pp.204-208
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    • 2000
  • An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity, geometrical size, and die velocity of model materials are different from those of real materials. Actually, the forming load of yoke, which is an automobile part made of aluminum alloys(Al-6061), is predicted by using this approximate similarity theory. Firstly, upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061), and a suitable model material is selected for model material test of Al-6061. And then hot forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material, which has been selected from above upset forging tests. The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

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CAD 모델 재사용을 위한 특징형상기반 유사도 측정에 관한 연구 (Feature-based Similarity Assessment for Re-using CAD Models)

  • 박병건;김재정
    • 한국CDE학회논문집
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    • 제16권1호
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    • pp.21-30
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    • 2011
  • Similarity assessment of a CAD model is one of important issues from the aspect of model re-using. In real practice, many new mechanical parts are designed by modifying existing ones. The reuse of part enables to save design time and efforts for the designers. Design time would be further reduced if there were an efficient way to search for existing similar designs. This paper proposes an efficient algorithm of similarity assessment for mechanical part model with design history embedded within the CAD model. Since it is possible to retrieve the design history and detailed-feature information using CAD API, we can obtain an accurate and reliable assessment result. For our purpose, our assessment algorithm can be divided by two: (1) we select suitable parts by comparing MSG (Model Signature Graph) extracted from a base feature of the required model; (2) detailed-features' similarities are assessed with their own attributes and reference structures. In addition, we also propose a indexing method for managing a model database in the last part of this article.

Continuous Conditional Random Field에 의한 인터넷 쇼핑몰 신규 고객등급 예측 (Prediction of New Customer's Degree of Loyalty of Internet Shopping Mall Using Continuous Conditional Random Field)

  • 안길승;허선
    • 대한산업공학회지
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    • 제41권1호
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    • pp.10-16
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    • 2015
  • In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

Style-Specific Language Model Adaptation using TF*IDF Similarity for Korean Conversational Speech Recognition

  • Park, Young-Hee;Chung, Min-Hwa
    • The Journal of the Acoustical Society of Korea
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    • 제23권2E호
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    • pp.51-55
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    • 2004
  • In this paper, we propose a style-specific language model adaptation scheme using n-gram based tf*idf similarity for Korean spontaneous speech recognition. Korean spontaneous speech shows especially different style-specific characteristics such as filled pauses, word omission, and contraction, which are related to function words and depend on preceding or following words. To reflect these style-specific characteristics and overcome insufficient data for training language model, we estimate in-domain dependent n-gram model by relevance weighting of out-of-domain text data according to their n-. gram based tf*idf similarity, in which in-domain language model include disfluency model. Recognition results show that n-gram based tf*idf similarity weighting effectively reflects style difference.

상사성을 이용한 model 사류펌프의 성능 예측 (Performance Prediction of Model Mixed Flow Pump Using Similarity)

  • 이덕형
    • 유체기계공업학회:학술대회논문집
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    • 유체기계공업학회 2005년도 연구개발 발표회 논문집
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    • pp.393-400
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    • 2005
  • As one of the useful and powerful methods for designing the optimum pump is using model pump, it is based on the similarity characteristics of turbomachinery. With this theory, we can predict the performance of various pumps. In fact we have performed huge pumps using this, the experimental results were to be sufficient to prove the similarity characteristics. In this study, we predicted the performance of the huge proto-type pump that cannot be installed and made a test. First of all, we had calculated the model ratio between proto-type and model. There were two ways to estimate the performance. One was the application of CFD code, and the other way was model field test. So We selected both of them to guarantee the dependable data and evaluated each other.

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원심모형시험기를 이용한 사면의 침투 및 파괴에 관한 상사법칙의 검토 (Similarity rule of Seepage failure by Centrifuge model test)

  • 김재영;동전순
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2004년도 춘계학술발표회
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    • pp.313-318
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    • 2004
  • 필 댐이나 제방의 침투에 의한 파괴현상을 원심모형실험으로 모사하는 경우, 지금까지는 물을 이용해 파괴시키는 원심모형실험이 실시되고 있었다. 그리고 점성유체를 사용한 원심모형실험도 실시되고 있지만, 상사법칙의 검증이 이루어지지 않은 상태에서의 실험결과에는 의문이 남아있다. 본 연구에서는, 물의 n배 점성용액을 사용해 상사법칙을 성립시켜 Modeling of Models의 방법에 따라 검증하였다.

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