The problem of developing an control algorithm for a queuing system is considered. This system has a finite number of states the dynamics of which is described by a conditional Markov chain;the system is observed usin...
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The problem of developing an control algorithm for a queuing system is considered. This system has a finite number of states the dynamics of which is described by a conditional Markov chain;the system is observed using indicators whose readings are error prone. Optimal and approximately optimal solutions based on the theory of systems with random jump structure are found. By way of example, the problem of synthesis of an approximately optimal algorithm for the recognition of state and for control of aviation raids on a military facility that is alternatively damaged and restored in the course of air combat operations.
Text plays an important role in daily life because of its rich information, thus automatic text detection in natural scenes has many attractive applications. However, detecting and recognising such text is always a ch...
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Text plays an important role in daily life because of its rich information, thus automatic text detection in natural scenes has many attractive applications. However, detecting and recognising such text is always a challenging problem. In this study, the authors propose a method which extends the widely-used stroke width transform by two steps of edge analysis, namely candidate edge recombination and edge classification. A new method that recognises text through candidate edge recombination and candidate edge recognition is also proposed. In the step of candidate edge recombination, they use the idea of over-segmentation and region merging. To separate text edge from background, the edge of the input image is first divided into small segments. Then, neighbour edge segments are merged, if they have similar stroke width and colour. Through this step, each character is described by one candidate boundary. In the step of boundary classification, candidate boundaries are aggregated into text chains, followed by chain classification using character-based and chain-based features. To recognise text, the grey image is extracted based on the location of each candidate edge after the step of candidate edge recombination. Then, histogram of gradient features and a classifier are used to recognise each character. To evaluate the effectiveness of their method, the algorithm is run on the ICDAR competition dataset and Street View Text database. The experimental results show that the proposed method provides promising performance in comparison with the existing methods.
Based on a graph-theoretic concept of a cluster, dominant sets clustering has been shown to be an attractive clustering algorithm with many useful properties. In this study, the authors conduct a comprehensive study o...
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Based on a graph-theoretic concept of a cluster, dominant sets clustering has been shown to be an attractive clustering algorithm with many useful properties. In this study, the authors conduct a comprehensive study of related issues in dominant sets clustering, in an endeavour to explore the potential of this algorithm and obtain the best clustering results. Specifically, they empirically investigate how similarity parameters, similarity measures and game dynamics influence the dominant sets clustering results. From experiments on eight datasets, they conclude that distance-based similarity measures perform evidently better than cosine and histogram intersection similarity measures potentially, and they need to find the best-performing similarity parameter to make use of this advantage. They then study the effect of similarity parameter on dominant sets clustering results and induce the range of the best-performing similarity parameters. Furthermore, they find that the recently proposed infection and immunisation dynamics performs better than the replicator dynamics in most cases while being much more efficient than the latter. These observations are helpful in applying dominant sets clustering to practical problems, and also indicate directions for further improvement of this algorithm.
A set of explicit finite difference schemes with large stencil was optimized to obtain maximum resolution characteristics for various spatial truncation orders. The effect of integral interval range of the objective f...
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A set of explicit finite difference schemes with large stencil was optimized to obtain maximum resolution characteristics for various spatial truncation orders. The effect of integral interval range of the objective function on the optimized schemes' performance is discussed. An algorithm is developed for the automatic determination of this integral interval. Three types of objective functions in the optimization procedure are compared in detail, which show that Tam's objective function gets the best resolution in explicit centered finite difference scheme. Actual performances of the proposed optimized schemes are demonstrated by numerical simulation of three CAA benchmark problems. The effective accuracy, strengths, and weakness of these proposed schemes are then discussed. At the end, general conclusion on how to choose optimization objective function and optimization ranges is drawn. The results provide clear understanding of the relative effective accuracy of the various truncation orders, especially the trade-off when using large stencil with a relatively high truncation order.
Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper t...
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Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs) with artificial neural networks (ANNs). Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines;nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier;ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.
In the paper, taint analysis problem is considered. To solve it, static interprocedural context-, flow-, and object-sensitive algorithm is proposed. Characteristics of the algorithm are evaluated, and specific feature...
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In the paper, taint analysis problem is considered. To solve it, static interprocedural context-, flow-, and object-sensitive algorithm is proposed. Characteristics of the algorithm are evaluated, and specific features of the implementation of the algorithm on the basis of the LLVM compiler infrastructure are discussed. Results of evaluation are presented.
Recently, Unmanned Aerial Vehicles (UAVs) have emerged as relay platforms to maintain the connectivity of ground mobile ad hoc networks (MANETs). However, when deploying UAVs, existing methods have not consider one si...
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Recently, Unmanned Aerial Vehicles (UAVs) have emerged as relay platforms to maintain the connectivity of ground mobile ad hoc networks (MANETs). However, when deploying UAVs, existing methods have not consider one situation that there are already some UAVs deployed in the field. In this paper, we study a problem jointing the motion control of existing UAVs and the deployment of new UAVs so that the number of new deployed UAVs to maintain the connectivity of ground MANETs can be minimized. We firstly formulate the problem as a Minimum Steiner Tree problem with Existing Mobile Steiner points under Edge Length Bound constraints (MST-EMSELB) and prove the NP completeness of this problem. Then we propose three Existing UAVs Aware (EUA) approximate algorithms for the MST-EMSELB problem: Deploy-Before-Movement (DBM), Move-Before-Deployment (MBD), and Deploy-Across-Movement (DAM) algorithms. Both DBM and MBD algorithm decouple the joint problem and solve the deployment and movement problem one after another, while DAM algorithm optimizes the deployment and motion control problem crosswise and solves these two problems simultaneously. Simulation results demonstrate that all EUA algorithms have better performance than non-EUA algorithm. The DAM algorithm has better performance in all scenarios than MBD and DBM ones. Compared with DBM algorithm, the DAM algorithm can reduce at most 70% of the new UAVs number.
This paper shows the analysis of the thin film flow of fourth-grade fluid on the outer side of a vertical cylinder. Solution of the governing nonlinear equation is obtained by Rational Homotopy Perturbation Method (RH...
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This paper shows the analysis of the thin film flow of fourth-grade fluid on the outer side of a vertical cylinder. Solution of the governing nonlinear equation is obtained by Rational Homotopy Perturbation Method (RHPM);comparison with exact solution reflects the reliability of the method. Analysis shows that this method is reliable for even high nonlinearity. Graphs and tables strengthen the idea.
By considering the complex networks, the cooperative game based optimal consensus (CGOC) algorithm is proposed to solve the multi-UAV rendezvous problem in the mission area. Firstly, the mathematical description of th...
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By considering the complex networks, the cooperative game based optimal consensus (CGOC) algorithm is proposed to solve the multi-UAV rendezvous problem in the mission area. Firstly, the mathematical description of the rendezvous problem is established, and the solving framework is provided based on the coordination variables and coordination function. It can decrease the transmission of the redundant information and reduce the influence of the limited network on the task. Secondly, the CGOC algorithm is presented for the UAVs in distributed cooperative manner, which can minimize the overall cost of the multi-UAV system. The CGOC control problem and the corresponding solving protocol are given by using the cooperative game theory and sensitivity parameter method. Then, the CGOC method of multi-UAV rendezvous problem is proposed, which focuses on the trajectory control of the platform rather than the path planning. Simulation results are given to demonstrate the effectiveness of the proposed CGOC method under complex network conditions and the benefit on the overall optimality and dynamic response.
During drive off maneuvers from stand still with high torque unpleasant longitudinal oscillations of the vehicle occur, commonly referred to as the power hop phenomenon. This effect especially arises in vehicles with ...
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ISBN:
(纸本)9781509007561
During drive off maneuvers from stand still with high torque unpleasant longitudinal oscillations of the vehicle occur, commonly referred to as the power hop phenomenon. This effect especially arises in vehicles with manual transmission in a maneuver with abrupt release of the clutch, also known as snap start. Traction control on the engine control unit provides a cheap and easy way to reduce power hop and thus to improve the comfort for the passengers. In this paper two methods for estimation of tire road friction coefficient during snap start are presented with regard to road condition dependent parametrization of a Sliding Mode traction control. Since the road conditions can change in every maneuver, a fast but also accurate estimation algorithm is necessary. The first method is based on a vehicle model and uses an Extended Kalman Filter to estimate the current maximum friction coefficient. The second method uses only wheel speed measurements to deduce information about the road condition. These methods can be used to adapt the parameters of the control algorithm to different road surfaces and thus improve the performance. Experimental results on different road surfaces are presented.
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