• Title/Summary/Keyword: intrinsic feature

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Conceptual Differences between the Relation-Based Approach and the Feature-Based Approach in Noun-Noun Conceptual Combination (개념결합 처리과정에 대한 관계 - 기반 접근과 차원- 기반 접근의 조망 차이)

  • Choi, Min-Gyung;Shin, Hyun-Jung
    • Korean Journal of Cognitive Science
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    • v.21 no.1
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    • pp.199-231
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    • 2010
  • This study tried to contrast the relation-based and the dimension-based explanations and to suggest its implications on the noun-noun conceptual combination. In experiment 1, we investigated whether the dimension-based approach and intra-conceptual explanation can explain both thematic relational and property interpretations of conceptual combinations based upon the intrinsic and extrinsic features of constituent concepts. We defined intrinsic(or extrinsic) concepts according to the degree of dependency on intrinsic(or extrinsic) features. Property interpretation was facilitated when modifiers were the intrinsic concepts. This result implies that processing of conceptual combination can be influenced by the structures and information of constituent concepts. In experiment 2, exocentricity of the concepts used in Gagne(2000) was examined to reanalyze her data according to the dimension-based approach. The exocentricity was higher when the concepts were combined by their relational connections. Results of experiment 1 and 2 suggest the possibility that both approaches can be integrated through the diversities of information involved during interpreting conceptual combination. Implications and future directions of this study were discussed.

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Idiopathic Hypertropic Subaortic Stenosis with Mitral Regurgitation -Report of 3 Cases- (특발성 비후성 대동맥판하 협착증 및 승모판 폐쇄부전증 -3례 보고-)

  • 강청희
    • Journal of Chest Surgery
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    • v.27 no.4
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    • pp.313-317
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    • 1994
  • Surgical treatment is possible for the obstructive form of hypertrophic cardiomyopathy and transaortic left ventricular septal myectomy and myotomy has been the procedure of choice. If coexisting intrinsic mitral valve disease exists, mitral valve replacement has been performed. But abnormal systolic anterior motion of anterior mitral leaflet[SAM] with intrinsic normal mitral valve disease is the typical feature of IHSS and we prefer not to replace mitral valve. 3 patients underwent transaortic myotomy and myectomy for IHSS with mitral regurgitation. 2 patients of them have coexisting intrinsic mitral valve diseases such as mitral valve vegetation and chorda rupture. Concomittent mitral valve replacement were performed. 1 patient shows SAM of mitral anterior leaflet but has intrinsic normal mitral valve morphologically and transepicardial echocardiogram and direct monitoring of pressure gradient during the operative procedure gives better information for subsided mitral regurgitation. Post operative course during the 12 months follow-up was uneventful.

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Pose Tracking of Moving Sensor using Monocular Camera and IMU Sensor

  • Jung, Sukwoo;Park, Seho;Lee, KyungTaek
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.8
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    • pp.3011-3024
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    • 2021
  • Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

Part Similarity Assessment Method Based on Hierarchical Feature Decomposition: Part 2 - Using Negative Feature Decomposition (계층적 특징형상 정보에 기반한 부품 유사성 평가 방법: Part 2 - 절삭가공 특징형상 분할방식 이용)

  • 김용세;강병구;정용희
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.1
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    • pp.51-61
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    • 2004
  • Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes.. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the second one of the two companion papers, describes the similarity assessment method using NFD.

Part Similarity Assessment Method Based on Hierarchical Feature Decomposition: Part 1 - Using Convex Decomposition and Form Feature Decomposition (계층적 특징형상 정보에 기반한 부품 유사성 평가 방법: Part 1 - 볼록입체 분할방식 및 특징형상 분할방식 이용)

  • 김용세;강병구;정용희
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.1
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    • pp.44-50
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    • 2004
  • Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.

Discrimination of Multi-PD sources using wavelet 2D compression for T-F distribution of PD pulse waveform (부분방전 펄스파형의 시간-주파수분포의 웨이블렛 2D 압축기술을 이용한 복합부분방전원의 식별)

  • Lee, K.W.;Kim, M.Y.;Baik, K.S.;Kang, S.H.;Lim, K.J.
    • Proceedings of the KIEE Conference
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    • 2004.07c
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    • pp.1784-1786
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    • 2004
  • PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency. STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33${\times}$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13${\times}$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources.

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Discrimination of Air PD Sources Using Time-Frequency Distributions of PD Pulse Waveform (부분방전 펄스파형의 시간-주파수분포를 이용한 기중부분방전원의 식별)

  • Lee Kang-Won;Kang Seong-Hwa;Lim Ki-Joe
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.54 no.7
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    • pp.332-338
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    • 2005
  • PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33$\times$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13$\times$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources in the air.

Multiscale Spatial Position Coding under Locality Constraint for Action Recognition

  • Yang, Jiang-feng;Ma, Zheng;Xie, Mei
    • Journal of Electrical Engineering and Technology
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    • v.10 no.4
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    • pp.1851-1863
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    • 2015
  • – In the paper, to handle the problem of traditional bag-of-features model ignoring the spatial relationship of local features in human action recognition, we proposed a Multiscale Spatial Position Coding under Locality Constraint method. Specifically, to describe this spatial relationship, we proposed a mixed feature combining motion feature and multi-spatial-scale configuration. To utilize temporal information between features, sub spatial-temporal-volumes are built. Next, the pooled features of sub-STVs are obtained via max-pooling method. In classification stage, the Locality-Constrained Group Sparse Representation is adopted to utilize the intrinsic group information of the sub-STV features. The experimental results on the KTH, Weizmann, and UCF sports datasets show that our action recognition system outperforms the classical local ST feature-based recognition systems published recently.

Uncalibrated Visual Servoing through the Efficient Estimation of the Image Jacobian for Large Residual

  • Kim, Gon-Woo
    • Journal of Electrical Engineering and Technology
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    • v.8 no.2
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    • pp.385-392
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    • 2013
  • An uncalibrated visual servo control method for tracking a target is presented. We define the robot-positioning problem as an unconstrained optimization problem to minimize the image error between the target feature and the robot end-effector feature. We propose a method to find the residual term for more precise modeling using the secant approximation method. The composite image Jacobian is estimated by the proper method for eye-to-hand configuration without knowledge of the kinematic structure, imaging geometry and intrinsic parameter of camera. This method is independent of the motion of a target feature. The algorithm for regulation of the joint velocity for safety and stability is presented using the cost function. Adaptive regulation for visibility constraints is proposed using the adaptive parameter.

A Study on Emotion Recognition Systems based on the Probabilistic Relational Model Between Facial Expressions and Physiological Responses (생리적 내재반응 및 얼굴표정 간 확률 관계 모델 기반의 감정인식 시스템에 관한 연구)

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.6
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    • pp.513-519
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    • 2013
  • The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.