In wireless sensor networks, the traditional intrusion detection can not detect the compromised nodes immediately. In this paper, we propose a secure routing protocol (Secure Relay Grid Routing Protocol) based on prob...
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In wireless sensor networks, the traditional intrusion detection can not detect the compromised nodes immediately. In this paper, we propose a secure routing protocol (Secure Relay Grid Routing Protocol) based on probability prediction to solve this problem. In the protocol, the network is divided into different small grids. Utilizing the geographic information and intrusion detection information, the proposed protocol is designed with a routing metric which is based on a mathematical prediction model. The routing metric could guarantee that the message detours those compromised grids that have not been detected by the intrusion detection. Theoretical analysis and OPNET simulation results show that the proposed protocol can provide a high delivery ratio and decrease the number of the compromised packets.
BitTorrent(BT) has emerged as one of the most popular protocols for content sharing in recent years. Most BT applications are network-oblivious which brings great challenges to traffic engineering. As basic input info...
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When the input signals are strongly correlated, the adaptive algorithm performance of Volterra filter deteriorates. Meanwhile, the correlativity of linear input signals of Volterra filter is different from that of non...
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This paper describes the work of designing a fully-digital shunt active power filter controlsystem based on digital signal processor TMS320F2812. The control algorithm for controlsystem of shunt active power filter ...
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In order to improve the function of soft sensor to conduct variable selection, fault detection and model structure identification in the case of faulty state, a design method of new soft sensor is studied though the v...
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In order to improve the function of soft sensor to conduct variable selection, fault detection and model structure identification in the case of faulty state, a design method of new soft sensor is studied though the variable selection algorithm. A non-stationary time serial is introduced to describe the process output not being reflected by sensor variables and to detect whether the process enters the faulty state. A non-negative garrote method is adopted to identify the model structure and a modeling method for new soft sensors is presented. The obtained model can be used for both prediction, and detection of structural model change and the emergence of disturbance. Compared with the ordinary soft sensor based on partial least square algorithm, the advantages of the proposed method are demonstrated by a simulation example and an industrial application to temperature prediction of a blast furnace hearth.
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.
Arterial stiffness is an effective parameter for monitoring sub-clinical arterial stiffness, and can tell effectively the cardioArterial health condition of human body. Elastic expansion coefficient of blood vessel (n...
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In distributed systems, the server placement problem in which a new server has to compete with existing servers for user requests is important in planning of constructing new business service sites. In addition to min...
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A recent development in molecular imaging is in vivo fluorescence molecular imaging with near-infrared light, which has extraordinary significance in early diagnosis of the disease. This paper presents a method of rec...
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Sparsity adaptive matching pursuit algorithm(SAMP) is a compressed sensing signal reconstruction algorithm with good performance. However, as the support set expands one time, the backward pursuit should be processed ...
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Sparsity adaptive matching pursuit algorithm(SAMP) is a compressed sensing signal reconstruction algorithm with good performance. However, as the support set expands one time, the backward pursuit should be processed for many times, in which redundant update calculations are included. To solve the problem, this paper presents a fast sparsity adaptive matching pursuit algorithm(FSAMP). During the operation of the FSAMP, the backward pursuit is performed only once when the support set expands. After the support set is fixed, the backward pursuit shall be executed for multi times to guarantee the reconstruction precision. Simulation results for signal reconstruction show that the FSAMP has the slight higher reconstruction precision and the much faster reconstruction speed compared with the SAMP.
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