This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extrac...
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Place recognition is an important perceptual robotic problem, especially in the navigation process. Previous place-recognition approaches have been used for solving 'global localization' and 'kidnapped rob...
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Through the estimated method for constraint-tuning modified-mode (CTMM), an innovative thin-disc piezoelectric ultrasonic actuator is used to drive an optical sled in this study. With four screws positioned on the thi...
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In order to practically examine a new type of class, in which cooperative learning is taken into consideration, we designed and built a classroom. This classroom, in which furniture and a flexible ICT basis are both d...
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In order to practically examine a new type of class, in which cooperative learning is taken into consideration, we designed and built a classroom. This classroom, in which furniture and a flexible ICT basis are both designed reconfigurable, supports much more complex interactions between learners than in a traditional classroom. Two months' observation of the activities in the classroom shows that many aspects of the reconfigurations have encouraged complex interactions within cooperative learning.
Under the given operation condition, the operating parameters of large-scale fan vary according to certain rule. With the fan aging, the rule is changing. In order to find the rule of deterioration of condition parame...
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The nonlinear model predictive control (MPC) needs to solve a two-point boundary-value problem (TP-BVP) at every sample time based on the receding horizon control strategy. However, solving a nonlinear algebraic equat...
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This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extrac...
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ISBN:
(纸本)9781612844879
This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extracted from previous LBP are compared with those features found from the current LBP with a block matching approach so that the corresponding feature points from the successive image frames can be identified. If multiple correspondences exist between feature points, the motion vectors of each feature points are then calculated to determine the best corresponding features on the current LBP. Finally, with clustering of motion vectors, all the moving objects on image frames can be successfully detected and identified. Experimental results show that the average matching accuracy rate is 95.12%, and the average processing time for moving object detection is 46.2ms.
The paper analyzed and model of a fault tolerant electromechanical controlled worm gear driven fuel shut off valve for aerospace application. The analysis is mainly on design a reduced order fractional controller. Thi...
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With the development of online communities, there has been a dramatic increase in the number of members using Enterprise Communities (ECs) over the past few years. Many join ECs with the objective of sharing their kno...
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With the development of online communities, there has been a dramatic increase in the number of members using Enterprise Communities (ECs) over the past few years. Many join ECs with the objective of sharing their knowledge on the specific issue and seeking relative knowledge from others. Despite the eagerness of sharing knowledge and receiving knowledge through ECs, there is no standard of assessing ones knowledge sharing capabilities and prospects of knowledge sharing in order to get great level of efficiency of knowledge sharing collaboration. This paper developed evaluation model to assess knowledge relationship behavior among ECs members with the aim of Vector Space Model.
The nonlinear model predictive control (MPC) needs to solve a two-point boundary-value problem (TP-BVP) at every sample time based on the receding horizon control strategy. However, solving a nonlinear algebraic equat...
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The nonlinear model predictive control (MPC) needs to solve a two-point boundary-value problem (TP-BVP) at every sample time based on the receding horizon control strategy. However, solving a nonlinear algebraic equation for the TP-BVP requires high computational load, so developing an efficient computation method of the control law in real-time is a significant issue on the research of the nonlinear model predictive control. This paper proposes an efficient calculation method of the control law for nonlinear MPC. The proposed approach searches an optimal step-type input signal for a given performance index beforehand, then the input signal is successively updated using a continuation method. Hence, it can reduce the computation load because the number of the parameter to be optimized becomes one in the SISO case or the number of the inputs in the MIMO case, and solving TP-BVP can be avoided by a continuation method. In addition, the accuracy of the nonlinear algebraic equation, which gives the optimal condition, keeps well by analytically deriving the updating law of the MPC control law. A numerical example shows that the proposed method can reduce the computation load of the nonlinear MPC, while the accuracy of the optimal conditions given by the nonlinear algebraic equations keeps a tolerance level.
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