This paper investigates synchronization between two delayed chaotic systems with parameter mismatches. Based on Lyapunov functional approach and generalized Halanay inequality, some delay-dependent criteria are derive...
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A novel robust least squares constant modulus algorithm (LSCMA) is proposed for blind adaptive beamforming, which is based on explicit modeling of uncertainty in the desired signal array. To improve robustness, the we...
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The topology structure of social contacts network has a big impact on dynamic patterns of epidemic spreading and effectiveness of non-pharmaceutical interventions. Corresponding to individuals' behavioral or funct...
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In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intel...
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In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intelligent traffic. A block-based Gaussian mixture background modeling method for object detection is presented to reduce the computational complexity of moving vehicle object abstraction. An adaptive tracking algorithm fused with color features and texture features is described to better adapt the traffic scene variation. The experimental results show that the proposed algorithm can effectively deal with the complex urban traffic conditions and the tracking performance is better than the conventional particle filter method and single feature based non-adaptive object tracking method.
Road traffic load balancing can avoid network congestion and improve traffic efficiency. This paper proposes a method of dynamic route guidance based on Maximum Flow Theory to balance traffic load of road network. A m...
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Road traffic load balancing can avoid network congestion and improve traffic efficiency. This paper proposes a method of dynamic route guidance based on Maximum Flow Theory to balance traffic load of road network. A modified Ford-Fulkerson algorithm is used for searching the optimal route. In addition, the algorithm is implemented by using MapReduce primitives, which introduces Cloud Computing Platform for large-scale traffic network guidance. Computational experimental environment is built by integrating Artificial Transportation systems (ATS) and Hadoop. Results in ATS and performances on Hadoop show that the method proposed can improve the traffic situation effectively.
It's an important need for a large chemical plant to roundly and deeply evaluate the design prototype of plant human machine interaction (HMI) using in the control room. To meet this need, we propose an evaluation...
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It's an important need for a large chemical plant to roundly and deeply evaluate the design prototype of plant human machine interaction (HMI) using in the control room. To meet this need, we propose an evaluation method based on the ACP (Artificial system, Computational experiment, and Parallel execution) theory. A plant operator agent is created in the method and it is composed of perception, cognition, and execution processors, short-term memory, and long-term memory. The operator agent is used as a virtual subject, and the HMI can be evaluated by behavior simulation, from the viewpoints of shortening fault detection and isolation (FDI) track and decreasing operator's physical and mental workloads. The proposed method shows that the ACP theory is useful for the HMI evaluation.
Automatic service composition is a key issue of cooperative resource utilization in component-based networked robot system. In this paper, a semantic-based automatic service composition method is proposed. The semanti...
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Automatic service composition is a key issue of cooperative resource utilization in component-based networked robot system. In this paper, a semantic-based automatic service composition method is proposed. The semantic representation and composition of service is achieved by semantic descriptions of service functions and formulating a set of I/O parameters matching rules. Based on this, a bidirectional breadth-first traversal search algorithm inspired by the maze problem is proposed. As a result, the proposed method is capable of automatically generating plans to compose the functions according to the task requirement. Experimental results validate the effectiveness and the flexibility of the proposed method.
Multiple-target tracking in complex scenes is one of the most complicated problems in computer vision. Handling the occlusion between objects is the key issue in multiple target tracking. This paper presents an occlus...
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Multiple-target tracking in complex scenes is one of the most complicated problems in computer vision. Handling the occlusion between objects is the key issue in multiple target tracking. This paper presents an occlusion segmentation-based method to track multiple people in complex situations which are captured by static monocular cameras. In the proposed method, we calculate the probabilistic histogram of each object's optical flow vector, then use this motion statistic information along with the color and appearance information to construct a new expression of pixel distance. Finally, a stepwise classification and K-means clustering method are taken advantages of to accomplish occlusion segmentation. Object tracking is handled by a particle filter-based tracking framework, and a probabilistic appearance model is used to find the best particle. Experiments are conducted using public challenging data set PETS 2009. Results show that our approach can improve the performance of the existing tracking approach and handle dynamic occlusions better.
This paper proposes a novel method to evaluate Traffic Signal control System(TSCS) based on Artificial Transportation systems(ATS). Using this method, we can generate travel demand based on individual's activities...
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This paper proposes a novel method to evaluate Traffic Signal control System(TSCS) based on Artificial Transportation systems(ATS). Using this method, we can generate travel demand based on individual's activities and construct artificial traffic scenarios using basic rules. While interacting with ATS, TSCS can be evaluated by observing and analyzing the traffic status that emerged. The cost of the evaluation is decreased as artificial traffic environment can be constructed in the laboratory to substitute real environment and the evaluation can be carried out before the installation on site. Furthermore, as reasonable travel demand can be generated based on individual's activities, the reliability of evaluation results can be guaranteed. Finally, the effectiveness of this method is verified by experiments.
This paper illustrates a compositional deformable model for detecting vehicle and recognizing vehicle-contours. To overcome the difficulties that vehicles in an image have various sizes, shapes, colors and poses, this...
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This paper illustrates a compositional deformable model for detecting vehicle and recognizing vehicle-contours. To overcome the difficulties that vehicles in an image have various sizes, shapes, colors and poses, this model has two main characteristics: first, the model is made up of constituent parts which shared by vehicles. The locality of parts give the model the ability to recognize vehicles with different types (e.g., although vehicles have various sizes and shapes, they are usually composed by roof, windscreen, windows, etc.). Second, the spatial relationships of these parts are represented by Markov Random Field (MRF). The model is deformable to adapt to vehicles of different shapes and poses because of the appropriately changing of combinations of these parts in the MRF. Experimental results with real world images show that this method is effective in vehicle detection and vehicle-contours recognition.
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