Ideal interpolation is a generalization of the univariate Hermite interpolation. It is well known that every univariate Hermite interpolant is a pointwise limit of some Lagrange ***, a counterexample provided by Shekh...
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Ideal interpolation is a generalization of the univariate Hermite interpolation. It is well known that every univariate Hermite interpolant is a pointwise limit of some Lagrange ***, a counterexample provided by Shekhtman Boris shows that, for more than two variables,there exist ideal interpolants that are not the limit of any Lagrange interpolants. So it is natural to consider: Given an ideal interpolant, how to find a sequence of Lagrange interpolants(if any) that converge to it. The authors call this problem the discretization for ideal interpolation. This paper presents an algorithm to solve the discretization problem. If the algorithm returns "True", the authors get a set of pairwise distinct points such that the corresponding Lagrange interpolants converge to the given ideal interpolant.
Image transmission is one of the biggest challenges in wireless sensor networks because of the limited resource on sensor nodes. We proposed two image transmission schemes driven by reliability and real time considera...
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Image transmission is one of the biggest challenges in wireless sensor networks because of the limited resource on sensor nodes. We proposed two image transmission schemes driven by reliability and real time considerations in order to transfer JPEG images over Zigbee-based sensor networks. By adding two bytes counter in the header of data packet, we can easily solve the repeated data reception problem caused by retransmission mechanism in traditional Zigbees network layer. We proposed an efficient retransmission and acknowledgment mechanism in Zigbees application layer. By classifying different data reception response events, we can provide data packets with differential responses and ensure that image packets can be transferred quickly even with large maximum number of retransmission. Practical results show the effectiveness of our solutions to make image transmission over Zigbee-based sensor networks efficient.
Query on uncertain data has received much attention in recent years, especially with the development of Location-based services(LBS). Little research is focused on reverse k nearest neighbor queries on uncertain data....
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Query on uncertain data has received much attention in recent years, especially with the development of Location-based services(LBS). Little research is focused on reverse k nearest neighbor queries on uncertain data. We study the Probabilistic reverse k nearest neighbor(PRkN N) queries on uncertain data. It is succinctly shown that, PRkN N query retrieves all the points that have higher probabilities than a given threshold value to be the Reverse k-nearest neighbor(RkN N) of query data *** previous works on this topic mostly process with k > *** algorithms allow the cases for k > 1, but the efficiency is inefficient especially for large k. We propose an efficient pruning algorithm — Spatial pruning heuristic with louer and upper bound(SPHLU) for solving the PRkN N queries for k > 1. The experimental results demonstrate that our algorithm is even more efficient than the existent algorithms especial for a large value of k.
Local binary patterns was used to distinguish the Photorealistic Computer Graphics and Photographic Images, however the dimension of the extracted features is too high. Accordingly, the Local Ternary Count based on th...
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The rapid development of cyber-physical systems(CPS)had a tremendous impact on human behavior and *** human involvement,CPS has naturally evolved into cyberphysical social systems(CPSS)[1].The top five technology brea...
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The rapid development of cyber-physical systems(CPS)had a tremendous impact on human behavior and *** human involvement,CPS has naturally evolved into cyberphysical social systems(CPSS)[1].The top five technology breakthroughs of 2013 were closely related to CPSS and peripherals according to Mc Kinsey’s report[2].
The introduction ofproportional-integral-dorivative （PID） controllers into cooperative collision avoidance systems （CCASs） has been hindered by difficulties in their optimization and by a lack of study of their ef...
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The introduction ofproportional-integral-dorivative （PID） controllers into cooperative collision avoidance systems （CCASs） has been hindered by difficulties in their optimization and by a lack of study of their effects on vehicle driving stability, comfort, and fuel economy. In this paper, we propose a method to optimize PID controllers using an improved particle swarm optimization （PSO） algorithm, and to bettor manipulate cooperative collision avoidance with other vehicles. First, we use PRESCAN and MATLAB/Simulink to conduct a united simulation, which constructs a CCAS composed of a PID controller, maneuver strategy judging modules, and a path planning module. Then we apply the improved PSO algorithm to optimize the PID controller based on the dynamic vehicle data obtained. Finally, we perform a simulation test of performance before and after the optimization of the PID controller, in which vehicles equipped with a CCAS undertake deceleration driving and steering under the two states of low speed （≤50 km/h） and high speed （≥100 km/h） cruising. The results show that the PID controller optimized using the proposed method can achieve not only the basic functions of a CCAS, but also improvements in vehicle dynamic stability, riding comfort, and fuel economy.
The detection of structural changes is an important task in analyzing network evolution, especially for interactions between people, that may be driven by external events. Existing work relies on snapshot data and mis...
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The vehicles' driving safety plays an important role in the transportation safety's development, and it's a necessary requirement in intelligent transportation and intelligent vehicle. The point that is su...
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ISBN:
(纸本)9781510838451
The vehicles' driving safety plays an important role in the transportation safety's development, and it's a necessary requirement in intelligent transportation and intelligent vehicle. The point that is suggested in this paper is that vehicles' collision warning system which is based on computer vision, and the system is built on computer vision, pattern recognition, machine learning and some other artificial intelligent theory and techniques, discerning the vehicles which is in front of your vehicle and measure the security range, warning the possible danger timely to make sure your drive safe. We use the characteristic which is called haar of the samples to train in the classifier to get a cascaded classifier named Boosted, loading the classifier and image of the vehicles marked and calculating the distance and relative speed. In the last, we do a lot of system simulation experiments, verifying the accuracy and the effectiveness of the system from vehicle outline detection results and safe vehicle determination.
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