124,989 research outputs found

    Hamiltonian Monte Carlo Without Detailed Balance

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    We present a method for performing Hamiltonian Monte Carlo that largely eliminates sample rejection for typical hyperparameters. In situations that would normally lead to rejection, instead a longer trajectory is computed until a new state is reached that can be accepted. This is achieved using Markov chain transitions that satisfy the fixed point equation, but do not satisfy detailed balance. The resulting algorithm significantly suppresses the random walk behavior and wasted function evaluations that are typically the consequence of update rejection. We demonstrate a greater than factor of two improvement in mixing time on three test problems. We release the source code as Python and MATLAB packages.Comment: Accepted conference submission to ICML 2014 and also featured in a special edition of JMLR. Since updated to include additional literature citation

    Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories

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    Human action recognition (HAR) is at the core of human-computer interaction and video scene understanding. However, achieving effective HAR in an unconstrained environment is still a challenging task. To that end, trajectory-based video representations are currently widely used. Despite the promising levels of effectiveness achieved by these approaches, problems regarding computational complexity and the presence of redundant trajectories still need to be addressed in a satisfactory way. In this paper, we propose a method for trajectory rejection, reducing the number of redundant trajectories without degrading the effectiveness of HAR. Furthermore, to realize efficient optical flow estimation prior to trajectory extraction, we integrate a method for dynamic frame skipping. Experiments with four publicly available human action datasets show that the proposed approach outperforms state-of-the-art HAR approaches in terms of effectiveness, while simultaneously mitigating the computational complexity

    Understanding mechanisms of change in the development of antisocial behavior: The impact of a universal intervention

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    The association between the development of antisocial behavior, affiliation with deviant friends, and peer rejection was tested with a preventive intervention; 664 boys and girls were randomly assigned to a universal classroom-based intervention targeting disruptive behavior or a control condition. Peer nominations of antisocial behavior, friends' antisocial behavior, and peer rejection were assessed annually for 4 years. A high, a moderate, and a stable low antisocial behavior trajectory were identified. Large reductions in antisocial behavior were found among intervention children who followed the high trajectory. These reductions coincided with affiliations with nondeviant peers and with decreases in peer rejection. The affiliation between deviant and nondeviant peers was initiated by nondeviant children. The results support a causal role of deviant friends and peer rejection in the development of antisocial behavior. The implications for our understanding of the mechanisms leading to reductions in antisocial behavior are discussed

    An Omnidirectional Aerial Manipulation Platform for Contact-Based Inspection

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    This paper presents an omnidirectional aerial manipulation platform for robust and responsive interaction with unstructured environments, toward the goal of contact-based inspection. The fully actuated tilt-rotor aerial system is equipped with a rigidly mounted end-effector, and is able to exert a 6 degree of freedom force and torque, decoupling the system's translational and rotational dynamics, and enabling precise interaction with the environment while maintaining stability. An impedance controller with selective apparent inertia is formulated to permit compliance in certain degrees of freedom while achieving precise trajectory tracking and disturbance rejection in others. Experiments demonstrate disturbance rejection, push-and-slide interaction, and on-board state estimation with depth servoing to interact with local surfaces. The system is also validated as a tool for contact-based non-destructive testing of concrete infrastructure.Comment: Accepted submission to Robotics: Science and Systems conference 2019. 9 pages, 12 figure

    Probes and monitors for the study of solidification of molten semiconductors

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    The purpose is to examine solidification in the LiCl-KCl system to determine if phenomena such as solute rejection can be obseved by laser schlieren imaging. Molten salts have attributes that make them attractive as physical models in solidification studies. With optical techniques of investigation such as schlieren imaging, it is possible to study fluid flow phenomena in molten salts and to watch the trajectory of the solid-liquid interface

    Experimental investigation of a SMC high precision control

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    In this paper a discrete-time Sliding-Mode (SM) based controller for high accuracy position control is investigated. The controller is designed for a general SISO system with nonlinearity and external disturbance. It will be shown that application of the proposed controller forces the state trajectory to be within an O(Ts 2). The proposed controller is applied to a stage driven by a piezo drive that is known to suffer from nonlinearity. As a separate idea to enhance the accuracy of the closed loop system a combination of disturbance rejection method and the SMC controller is explored and its effectiveness is experimentally demonstrated. Closed-loop experiments are presented using PID controller with and without disturbance compensation and Sliding-Mode Controller with and without disturbance compensation for the purpose of comparison

    Robust nonlinear generalized predictive control of a permanent magnet synchronous motor with an anti-windup compensator

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    This paper presents a robust nonlinear generalized predictive control (RNGPC) strategy applied to a permanent magnet synchronous motor (PMSM) for speed trajectory tracking and disturbance rejection. The nonlinear predictive control law is derived by using a newly defined design cost function. The Taylor series expansion is used to carry out the prediction in a finite horizon. No information about the external perturbation and parameters uncertainties are needed to ensure the robustness of the proposed RNGPC. Moreover, to maintain the phase current within the limits using saturation blocks, a cascaded structure is adopted and an anti-windup compensator is proposed. The validity of the proposed control strategy is implemented on a dSPACE DS1104 board driving in real-time a 0.25 kW PMSM. Experimental results have demonstrated the stability, robustness and the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection
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