For a cone-beam three-dimensional computed tomography （3D-CT） scanning system, voxel size is an important indicator to guarantee the accuracy of data analysis and feature measurement based on 3D-CT images. Meanwhile...
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For a cone-beam three-dimensional computed tomography （3D-CT） scanning system, voxel size is an important indicator to guarantee the accuracy of data analysis and feature measurement based on 3D-CT images. Meanwhile, the voxel size changes with the movement of the rotary stage along X-ray direction. In order to realize the automatic calibration of the voxel size, a new and easily-implemented method is proposed. According to this method, several projections of a spherical phantom are captured at different imaging positions and the corresponding voxel size values are calculated by non-linear least-square fitting. Through these interpolation values, a linear equation is obtained that reflects the relationship between the voxel size and the rotary stage translation distance from its nominal zero position. Finally, the linear equation is imported into the calibration module of the 3D-CT scanning system. When the rotary stage is moving along X-ray direction, the accurate value of the voxel size is dynamically exported. The experimental results prove that this method meets the requirements of the actual CT scanning system, and has virtues of easy implementation and high accuracy.
A new approach is proposed in this paper to recover the original image of an underwater scene from a given sequence distorted by water fluctuation. The contribution of our method is to use a motion field-based kernel ...
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In search auctions, when the total budget for an advertising campaign during a certain promotion period is determined, advertisers have to distribute their budgets over a series of sequential temporal slots (e.g., dai...
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In search auctions, when the total budget for an advertising campaign during a certain promotion period is determined, advertisers have to distribute their budgets over a series of sequential temporal slots (e.g., daily budgets). However, due to the uncertainties existed in search markets, advertisers can only obtain the value range of budget demand for each temporal slot based on promotion logs. In this paper, we present a stochastic model for budget distribution over a series of sequential temporal slots during a promotion period, considering the budget demand for each temporal slot as a random variable. We study some properties and present feasible solution algorithms for our budget model, in the case that the budget demand is characterized either by uniform random variable or normal random variable. We also conduct some experiments to evaluate our model with the empirical data. Experimental results show that the budget demand is more likely to be normal distributed than uniform distributed, and our strategy can outperform the baseline strategy commonly used in practice.
A novel adaptive cruise control (ACC) system is proposed in this paper. A hierarchical control framework is adopted for the adaptive cruise control problem. For the upper level, a supervised actor-critic (SAC) reinfor...
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A novel adaptive cruise control (ACC) system is proposed in this paper. A hierarchical control framework is adopted for the adaptive cruise control problem. For the upper level, a supervised actor-critic (SAC) reinforcement learning approach is presented to obtain the desired acceleration controller. In the lower level, throttle and brake controllers calculate the required throttle and/or brake signals based on the desired longitudinal acceleration. Feed-forward neural networks are used to implement the actor and critic components of the SAC learning algorithm. An online learning mechanism is introduced to implement the SAC training process. dSPACE simulator is used to verify the effectiveness of the ACC system. Typical emergency braking scenario is simulated to test the adaptability of the ACC system. Road condition change (e.g. wintry or wet conditions) simulation is first investigated to evaluate the robustness of the ACC system. Performance of the proposed ACC system is proved to be very practical.
Human flesh search(HFS), a Web-enabled crowdsourcing phenomenon, originated in China a decade ago. In this article, we present the first comprehensive empirical analysis of HFS, focusing on the scope of HFS activities...
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Human flesh search(HFS), a Web-enabled crowdsourcing phenomenon, originated in China a decade ago. In this article, we present the first comprehensive empirical analysis of HFS, focusing on the scope of HFS activities, the patterns of HFS crowd collaboration process, and the characteristics of HFS participant networks. A survey of HFS participants was conducted to provide an in-depth understanding of the HFS community and various factors that motivate these participants to contribute. This article also advocates a new stream of Web science and social computing research that will be important in predicting the future growth and use of the World Wide Web.
The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate...
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We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered...
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ISBN:
(纸本)9781479978878
We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered measurement information available to the estimator, analytical expressions for the conditional probability distributions of the states are obtained, based on which the minimum mean square error event-based state estimates are further calculated. We show that the results also cover the case of packet dropout, under a special parameterization of the event-triggering conditions. With the results on state estimation, a closed-form expression of the average sensor-to-estimator communication rate is also presented. The effectiveness of the proposed results is illustrated by a numerical example and comparative simulations.
It is well known that vertical take-off and landing(VTOL) aircraft system is a complex multi-variable nonlinear system with large disturbances. In order to control the VTOL aircraft system ef ciently, it is necessary ...
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ISBN:
(纸本)9781479947249
It is well known that vertical take-off and landing(VTOL) aircraft system is a complex multi-variable nonlinear system with large disturbances. In order to control the VTOL aircraft system ef ciently, it is necessary to explore new optimal control methods to stabilize the system states. In this paper, we apply dual heuristic programming(DHP) to design the optimal controller for VTOL aircraft system. As a framework of approximate dynamic programming(ADP) algorithm, DHP consists of three modules: model, critic and actor. The critic module output partial derivatives of cost function with respect to state. It has many advantages such as good dynamics, fast convergence rate, and high control resolution. Simulation and experimental results demonstrate the effectiveness of optimal controller for VTOL aircraft system based on the DHP algorithm.
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