• Title/Summary/Keyword: Frame-based Model

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Modeling, Dynamics and Control of Spacecraft Relative Motion in a Perturbed Keplerian Orbit

  • Okasha, Mohamed;Newman, Brett
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.1
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    • pp.77-88
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    • 2015
  • The dynamics of relative motion in a perturbed orbital environment are exploited based on Gauss' and Cowell's variational equations. The inertial coordinate frame and relative coordinate frame (Hill frame) are used, and a linear high fidelity model is developed to describe the relative motion. This model takes into account the primary gravitational and atmospheric drag perturbations. Then, this model is used in the design of a navigation, guidance, and control system of a chaser vehicle to approach towards and to depart from a target vehicle in proximity operations. Relative navigation uses an extended Kalman filter based on this relative model to estimate the relative position/velocity of the chaser vehicle with respect to the target vehicle. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system. The corresponding measurement models, process noise matrix, and other filter parameters are provided. Numerical simulations are performed to assess the precision of this model with respect to the full nonlinear model. The analyses include the navigation errors and trajectory dispersions.

Scen based MPEG video traffic modeling considering the correlations between frames (프레임간 상관관계를 고려한 장면기반 MPEG 비디오 트래픽 모델링)

  • 유상조;김성대;최재각
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.9A
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    • pp.2289-2304
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    • 1998
  • For the performance analysis and traffic control of ATM networks carrying video sequences, need an appropriate video traffic model. In this paper, we propose a new traffic model for MPEG compressed videos which are widely used for any type of video applications at th emoment. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlation between frames of consecutiv GOPs. Using a simple scene detection algorithm, scene changes are modeled by state transitions and the number of GOPs of a scene state is modeled by a geometric distirbution. Frames of a scene stte are modeled by mean I, P, and B frame size. For more accurate traffic modeling, quantization errors (residual bits) that the state transition model using mean values has are compensated by autoregressive processes. We show that our model very well captures the traffic chracteristics of the original videos by performance analysis in terms of autocorrelation, histogram of frame bits genrated by the model, and cell loss rate in the ATM multiplexer with limited buffers. Our model is able to perrorm translations between levels (i.e., GOP, frame, and cell levels) and to estimate very accurately the stochastic characteristics of the original videos by each level.

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Nonlinear structural finite element model updating with a focus on model uncertainty

  • Mehrdad, Ebrahimi;Reza Karami, Mohammadi;Elnaz, Nobahar;Ehsan Noroozinejad, Farsangi
    • Earthquakes and Structures
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    • v.23 no.6
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    • pp.549-580
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    • 2022
  • This paper assesses the influences of modeling assumptions and uncertainties on the performance of the non-linear finite element (FE) model updating procedure and model clustering method. The results of a shaking table test on a four-story steel moment-resisting frame are employed for both calibrations and clustering of the FE models. In the first part, simple to detailed non-linear FE models of the test frame is calibrated to minimize the difference between the various data features of the models and the structure. To investigate the effect of the specified data feature, four of which include the acceleration, displacement, hysteretic energy, and instantaneous features of responses, have been considered. In the last part of the work, a model-based clustering approach to group models of a four-story frame with similar behavior is introduced to detect abnormal ones. The approach is a composition of property derivation, outlier removal based on k-Nearest neighbors, and a K-means clustering approach using specified data features. The clustering results showed correlations among similar models. Moreover, it also helped to detect the best strategy for modeling different structural components.

Experimental and analytical evaluation of a low-cost seismic retrofitting method for masonry-infilled non-ductile RC frames

  • Srechai, Jarun;Leelataviwat, Sutat;Wongkaew, Arnon;Lukkunaprasit, Panitan
    • Earthquakes and Structures
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    • v.12 no.6
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    • pp.699-712
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    • 2017
  • This study evaluates the effectiveness of a newly developed retrofitting scheme for masonry-infilled non-ductile RC frames experimentally and by numerical simulation. The technique focuses on modifying the load path and yield mechanism of the infilled frame to enhance the ductility. A vertical gap between the column and the infill panel was strategically introduced so that no shear force is directly transferred to the column. Steel brackets and small vertical steel members were then provided to transfer the interactive forces between the RC frame and the masonry panel. Wire meshes and high-strength mortar were provided in areas with high stress concentration and in the panel to further reduce damage. Cyclic load tests on a large-scale specimen of a single-bay, single-story, masonry-infilled RC frame were carried out. Based on those tests, the retrofitting scheme provided significant improvement, especially in terms of ductility enhancement. All retrofitted specimens clearly exhibited much better performances than those stipulated in building standards for masonry-infilled structures. A macro-scale computer model based on a diagonal-strut concept was also developed for predicting the global behavior of the retrofitted masonry-infilled frames. This proposed model was effectively used to evaluate the global responses of the test specimens with acceptable accuracy, especially in terms of strength, stiffness and damage condition.

Moment-curvature hysteresis model of angle steel frame confined concrete columns

  • Rong, Chong;Tian, Wenkai;Shi, Qingxuan;Wang, Bin;Shah, Abid Ali
    • Structural Engineering and Mechanics
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    • v.83 no.1
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    • pp.19-29
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    • 2022
  • The angle steel frame confined concrete columns (ASFCs) are an emerging form of hybrid columns, which comprise an inner angle steel frame and a concrete column. The inner angle steel frame can provide axial bearing capacity and well confining effect for composite columns. This paper presents the experimental and theoretical studies on the seismic behaviour of ASFCs. The experimental study of the 6 test specimens is presented, based on the previous study of the authors. The theoretical study includes two parts. One part establishes the section analysis model, and it uses to analyze section axial force-moment-curvature. Another part establishes the section moment-curvature hysteresis model. The test and analysis results show that the axial compression ratio and the assembling of steel slabs influence the local buckling of the angle steel. The three factors (axial compression ratio, content of angle steel and confining effect) have important effects on the seismic behaviour of ASFCs. And the theoretical model can provide reasonably accurate predictions and apply in section analysis of ASFCs.

On the Use of a Frame-Correlated HMM for Speech Recognition (Frame-Correlated HMM을 이용한 음성 인식)

  • 김남수
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06c
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    • pp.223-228
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    • 1994
  • We propose a novel method to incorporate temporal correlations into a speech recognition system based on the conventional hidden Markov model. With the proposed method using the extended logarithmic pool, we approximate a joint conditional PD by separate conditional PD's associated with respective components of conditions. We provide a constrained optimization algorithm with which we can find the optimal value for the pooling weights. The results in the experiments of speaker-independent continuous speech recognition with frame correlations show error reduction by 13.7% with the proposed methods as compared to that without frame correlations.

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Effects of Edge Detection on Least-squares Model-image Fitting Algorithm

  • Wang, Sendo;Tseng, Yi-Hsing;Liou, Yan-Shiou
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.159-161
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    • 2003
  • Fitting the projected wire-frame model to the detected edge pixels on images by using least-squares approach, called Least-squares Model-image Fitting (LSMIF), is the key of the Model-based Building Extraction (MBBE). It is implemented by iteratively adjusting the model parameters to minimize the squares sum of distances from the extracted edge pixels to the projected wire-frame. This paper describes a series of experiments and studies on various factors affect the fitting results, including the edge detectors, the weighting rules, the initial value of parameters, and the number of overlapped images. The experimental result is not only helpful to clarify the influences of each factor, but is also able to enhance the robustness of the LSMIF algorithm.

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Models for Social Media-Based Governments

  • Khan, Gohar Feroz
    • Asia pacific journal of information systems
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    • v.25 no.2
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    • pp.356-369
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    • 2015
  • Public sectors around the world utilize social media tools and technologies in their daily activities for a variety of purposes, including disseminating useful information, fostering mass collaboration, and enforcing laws and regulations. A number of social media-based government stage models have emerged to document this use. In this chapter, we conducted a qualitative meta-synthesis of four social media-based government models. These models include 1) the open government maturity model, 2) the social media utilization model, 3) the adoption process for social media, and 4) the social media-based engagement model. The concepts, metaphors, and themes contained in these developmental models are extracted through a series of in-depth semantic analyses of descriptions, resulting in a common frame of reference.

A Position/Force Control of Robotic Manipulators with Parameter Adaptation (파라미터 적응을 이용하는 로보트 매니퓰레이터의 위치/힘 제어)

  • Yu, Dong-Young;Kim, Eung-Seok;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.408-410
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    • 1992
  • An adaptive hybrid position/force controller for constrained manipulator with uncertain dynamic model parameters and environment stiffness is presented. In this paper, the compliance frame model is constructed by independent positions and forces to be controlled. The adaptive controller based on this compliance frame dynamic model is designed. Lyapunov theory is used for controller design and Stability analysis.

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Model Parameter-based Rate Control Algorithm for Constant Quality Real-Time Video Coding (실시간 부호화를 위한 모델 파라미터 기반 일정 화질 비트율 제어 기법)

  • Jeong, Jin-Woo;Cho, Kyung-Min;Choe, Yoon-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.93-102
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    • 2008
  • In this paper, we propose a rate control algorithm for constant quality real time video coding. To achieve constant quality, previous algorithm exploit mean absolute of difference(MAD) as measure of frame complexity. However, if scene is abruptly changed or if quantization parameter is not constant, encoder produces various output bits with same MAD. Therefore we know that MAD does not appropriately reflect characteristic of frame. To solve this problem, we exploit model parameter as measure of frame complexity. Because model parameter means slope between output bits and MAD, it reflects correctly complexity of frame. And because previous model, R-MAD model, is not considered quantization parameter, as quantization parameter increases or decreases, model parameter of frame also vary. So model parameter obtained using previous model cannot reflect internal characteristic of video. We solve this problem using proposed model, which is considered quantization parameter. Experiment results show that our algorithm provide better performance, in terms of quality smoothness than previous algorithm. Especially, when scene is abruptly changed, our algorithm alleviates quality drop.