• 제목/요약/키워드: Vector representation

검색결과 288건 처리시간 0.032초

Relaxation을 이용한 2차원 물체의 형상매칭에 관한 연구 (A Study on Shape Matching of Two-Dimensional Object using Relaxation)

  • 곽윤식;이대령
    • 한국통신학회논문지
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    • 제18권1호
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    • pp.133-142
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    • 1993
  • 본 논문은 2차원 물체의 형상 매칭에 관한것으로 다각근사화된 단순 2차원 물체에 적용하였다. 많은 형상 매칭 방법론이 수학적 벡터의 의현에 기초를 두고 확솔적인 패턴 인식을 사용하고 있다. 유출된 형상의 다양성과 많은 데이타량은 형상의 전체적인 구조의 관계를 나타내는데 단점을 갖고 있다. 본 논문에서는 영상을 다 각근사적 과정를 통하여 Relaxation 라벨링 기술을 이용함으로써 형상 매칭의 지점을 해결하였다.

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Dynamic response of layered hyperbolic cooling tower considering the effects of support inclinations

  • Asadzadeh, Esmaeil;Alam, Mehtab;Asadzadeh, Sahebali
    • Structural Engineering and Mechanics
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    • 제50권6호
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    • pp.797-816
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    • 2014
  • Cooling tower is analyzed as an assembly of layered nonlinear shell elements. Geometric representation of the shell is enabled through layered nonlinear shell elements to define the different layers of reinforcements and concrete by considering the material nonlinearity of each layer for the cooling tower shell. Modal analysis using Ritz vector analysis and nonlinear time history analysis by direct integration method have been carried out to study the effects of the inclination of the supporting columns of the cooling tower shell on its dynamic characteristics. The cooling tower is supported by I-type columns and ${\Lambda}$-type columns supports having the different inclination angles. Relevant comparisons of the dynamic response of the structural system at the base level (at the junction of the column and shell), throat level and at the top of the tower have been made. Dynamic response of the cooling tower is found to be significantly sensitive to the change of the inclination of the supporting columns. It is also found that the stiffness of the structure system increases with increase in inclination angle of the supporting columns, resulting in decrease of the period of the structural system. The participation of the stiffness of the tower in structural response of the cooling tower is fund to be dependent of the change in the inclination angle and even in the types of the supporting columns.

교차로의 특성을 고려한 도로선형최적화 (Alignment Optimization Considering Characteristics of Intersections)

  • KIM, Eungcheol;SON, Bongsoo;CHANG, Myungsoon
    • 대한교통학회지
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    • 제20권4호
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    • pp.109-122
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    • 2002
  • 본 연구에서는 교차로의 비용 및 특성을 고려한 도로선형최적화 모형을 유전자 알고리즘(Genetic Algorithms)을 이용하여 개발하였다. 기존의 도로선형최적화 모형은 교차로 특성을 고려하지 못해서 실제 적용에 심대한 문제점을 내재하고 있다. 본 논문에서는 특정 도로선형에 교차로 건설의 필요가 있을 경우, 민감(Sensitive)하고 지배적인(Dominating) 교차로 비용 항목들 즉, 토공비용, 보상비, 포장비, 사고비용, 지체 및 연료소모비용 등의 산정이 시도되었다. 또한 비교적 우수한 도로선형 대안을 유전자 알고리즘을 이용한 탐색과정 중에서 비효율적으로 강제 퇴화시키는 단점 보완을 위한 교차로 국소 최적화 방법(Local Optimization of Intersections)이 개발되어 기존 모형을 보완하였다. 공간상의 도로선형은 매개변수적 묘사(Parametric Representation)를 통하여 구현하였으며 벡터운영(Vector Manipulation)을 통해 교차로비용 산정의 근간인 교차점과 다른 중요점들의 좌표를 찾을 수 있었다. 개발된 교차로 비용산정 모형이 보다 정밀하게 교차로 비용을 산정함이 증명되었으며 궁극적으로는 기존의 최적화 모형의 단점을 보완할 수 있음이 제시되었다. 또한, 새로이 제시된 교차로 국소 최적화 방법이 최적대안 탐색과정의 유연성을 증대하였으며, 결과적으로 효율적인 교차로의 유지에 기여함을 알 수 있었다. 제시된 교차로 국소 최적화 방법은 추후 단일노선이 아닌 도로망 최적화시의 기초를 제시함은 주목할 만 하다. 두개의 예제에서 도출된 최적노선 및 교차로 비용 등의 검토 결과, 도로상의 교차로 건설비용은 도로선형 최적화에 큰 영향을 미치는 실질적이며 민감한 비용 항목임이 검증되었으며 이는 도로선형최적화 모형이 교차로 비용을 반드시 검토 및 평가할 수 있어야 함을 반증한다.

열병합발전시스템에서 유전알고리즘을 적용한 단기운전계획 수립 (Short-term Operation Scheduling of Cogeneration Systems Using Genetic Algorithm)

  • Park, Seong-Hun;Jung, Chang-Ho;Lee, Jong-Beom
    • 에너지공학
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    • 제6권1호
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    • pp.11-18
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    • 1997
  • 본 논문은 에너지 효율이 높은 열병합발전시스템을 대상으로 유전알고리즘을 적용하여 단기운전계획을 수립하였다. 특히 열병합발전시스템의 효율은 약 70%이지만 효율이 일정하지 않을 뿐만 아니라 비선형적인 특징을 가지므로 실제 산업체의 열병합발전소의 데이터를 기초로 하여 적합한 가변효율방정식을 구하였다. 또한 본 논문에서 적용된 유전알고리즘은 계산시간의 감소와 높은 정밀도를 가진 실변수 유전알고리즘으로 시뮬레이션 하였다. 그 결과로 가변효율을 가진 열병합발전시스템의 단기운전계획이 유전알고리즘을 적용하여 적절하게 운전계획이 수립되고 있음을 나타내었으며 각종 보조설비가 유연성 있게 협력하며 필요시마다 효율적으로 운전되고 있음을 확인하였다.

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레이저 홈가공에서 편광빔의 다중반사 효과 (Effects of Multiple Reflections of Polarized Beam in Laser Grooving)

  • 방세윤;성관제
    • Journal of Welding and Joining
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    • 제23권2호
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    • pp.81-89
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    • 2005
  • A numerical model for multiple reflection effects of a polarized beam on laser grooving has been developed. The surface of the treated material is assumed to reflect laser irradiation in a fully specular fashion. Combining electromagnetic wave theory with Fresnel's relation, the reflective behavior of a groove surface can be obtained as well as the change of the polarization status in the reflected wave field. The material surface is divided into a number of rectangular patches using a bicubic surface representation method. The net radiative flux far these patch elements is obtained by standard ray tracing methods. The changing state of polarization of the electric field after reflection was included in the ray tracing method. The resulting radiative flux is combined with a set of three-dimensional conduction equations governing conduction losses into the medium, and the resulting groove shape and depth are found through iterative procedures. It is observed that reflections of a polarized beam play an important role not only in increasing the material removal rate but also in forming different final groove shapes. Comparison with available experimental results for silicon nitride shows good agreement for the qualitative trends of the dependence of groove shapes on the electric field vector orientation.

RNN을 이용한 Expressive Talking Head from Speech의 합성 (Synthesis of Expressive Talking Heads from Speech with Recurrent Neural Network)

  • 사쿠라이 류헤이;심바 타이키;야마조에 히로타케;이주호
    • 로봇학회논문지
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    • 제13권1호
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    • pp.16-25
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    • 2018
  • The talking head (TH) indicates an utterance face animation generated based on text and voice input. In this paper, we propose the generation method of TH with facial expression and intonation by speech input only. The problem of generating TH from speech can be regarded as a regression problem from the acoustic feature sequence to the facial code sequence which is a low dimensional vector representation that can efficiently encode and decode a face image. This regression was modeled by bidirectional RNN and trained by using SAVEE database of the front utterance face animation database as training data. The proposed method is able to generate TH with facial expression and intonation TH by using acoustic features such as MFCC, dynamic elements of MFCC, energy, and F0. According to the experiments, the configuration of the BLSTM layer of the first and second layers of bidirectional RNN was able to predict the face code best. For the evaluation, a questionnaire survey was conducted for 62 persons who watched TH animations, generated by the proposed method and the previous method. As a result, 77% of the respondents answered that the proposed method generated TH, which matches well with the speech.

Novel Method for Face Recognition using Laplacian of Gaussian Mask with Local Contour Pattern

  • Jeon, Tae-jun;Jang, Kyeong-uk;Lee, Seung-ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권11호
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    • pp.5605-5623
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    • 2016
  • We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

Feature Voting for Object Localization via Density Ratio Estimation

  • Wang, Liantao;Deng, Dong;Chen, Chunlei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권12호
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    • pp.6009-6027
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    • 2019
  • Support vector machine (SVM) classifiers have been widely used for object detection. These methods usually locate the object by finding the region with maximal score in an image. With bag-of-features representation, the SVM score of an image region can be written as the sum of its inside feature-weights. As a result, the searching process can be executed efficiently by using strategies such as branch-and-bound. However, the feature-weight derived by optimizing region classification cannot really reveal the category knowledge of a feature-point, which could cause bad localization. In this paper, we represent a region in an image by a collection of local feature-points and determine the object by the region with the maximum posterior probability of belonging to the object class. Based on the Bayes' theorem and Naive-Bayes assumptions, the posterior probability is reformulated as the sum of feature-scores. The feature-score is manifested in the form of the logarithm of a probability ratio. Instead of estimating the numerator and denominator probabilities separately, we readily employ the density ratio estimation techniques directly, and overcome the above limitation. Experiments on a car dataset and PASCAL VOC 2007 dataset validated the effectiveness of our method compared to the baselines. In addition, the performance can be further improved by taking advantage of the recently developed deep convolutional neural network features.

퍼지와 신경회로망을 이용한 유도전동기의 속도 추정 및 제어 (Estimation and Control of Speed of Induction Motor using Fuzzy and Neural Network)

  • 최정식;이정철;이홍균;남수명;고재섭;김종관;정동화
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.152-154
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    • 2005
  • This paper is proposed a fuzzy control and neural network based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability Also, this paper is proposed estimation and control of speed of Induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

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축소모델 기반 구조물의 동적해석 연구 (Study on the Dynamic Analysis Based on the Reduced System)

  • 김현기;조맹효
    • 한국전산구조공학회논문집
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    • 제21권5호
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    • pp.439-450
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    • 2008
  • 잘 구축된 축소시스템은 동하중을 받는 구조물의 거동을 정확하게 계산할 수 있으며, 유한요소 기반 동적해석에서 문제가 될 수 있는 계산시간과 전산자원의 문제를 해결할 수 있다. 본 연구에서는 축소모델 기반 동적해석 알고리즘을 개발하였고, 동적 축소모델의 구축을 위한 주자유도 선정방법을 제안하였다. 이 과정에서 기존 연구에서 신뢰성이 검증된 2단계 축소기법을 사용하여 중요 자유도를 선정하고, IRS 방법에 의해 최종 축소모델을 구축하였다. 이를 임의의 동하중을 받는 수치예제에 적용하고 전체시스템의 동적해석 결과와 비교하여 제안 방법의 신뢰성을 검증하였다.