We present a path planning algorithm for virtual maintenance of aircraft components. Component disassembly is a troublesome challenge of aircraft maintenance due to contact collision happened inevitably in disassembly...
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ISBN:
(纸本)9783642542367;9783642542350
We present a path planning algorithm for virtual maintenance of aircraft components. Component disassembly is a troublesome challenge of aircraft maintenance due to contact collision happened inevitably in disassembly process, which makes maintenance work difficult and inefficient. We study component disassembly in virtual environment: first a hierarchical and associative relation model is constructed through component analysis. Relation model contains connection information for components in any level. We adopt matrix representation for relation model that makes it convenient for computation. Finally, dijkstras algorithm is used to find the optimum disassembly path. The test on full-size model of Osprey airplane motor propeller shows our algorithm is effective and efficient.
We present queueing-based algorithms to calculate the bandwidth required for a video stream so that the three main Quality of Service constraints, i.e., end-to-end delay, jitter and packet loss, are ensured. Conversat...
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ISBN:
(数字)9781119073178
ISBN:
(纸本)9781848217461
We present queueing-based algorithms to calculate the bandwidth required for a video stream so that the three main Quality of Service constraints, i.e., end-to-end delay, jitter and packet loss, are ensured. Conversational and streaming video-based applications are becoming a major part of the everyday Internet usage. The quality of these applications (QoS), as experienced by the user, depends on three main metrics of the underlying network, namely, end-to-end delay, jitter and packet loss. These metrics are, in turn, directly related to the capacity of the links that the video traffic traverses from its source to destination. The main problem that this book addresses is how much bandwidth we should allocate on the path from source to destination of a video traffic flow such that the end-to-end delay, jitter and packet loss of the video packets are within some expected required bounds.
We experimentally compare two distributed algorithms based on Dijkstra's algorithm for the single-source shortest path problem. The algorithms are intended for asynchronous distributed systems with a small number ...
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We experimentally compare two distributed algorithms based on Dijkstra's algorithm for the single-source shortest path problem. The algorithms are intended for asynchronous distributed systems with a small number of processors without shared memory, and specifically address the situation where communication is costly. Variations of the algorithms have been implemented in OCCAM, and results from experiments on a 16 processor transputer system with randomly generated graphs of different types and densities with up to 20000 vertices and 250000 edges are reported. The distributed algorithms exploit the two obvious sources of parallelism in Dijkstra's algorithm. In the update-driven algorithm several vertices may be selected and scanned simultaneously. Since not all selected vertices can be guaranteed to be correct, the achievable speed-up depends on the problem instance, and no worst-case guarantee better than the sequential algorithm can be given. In contrast the minimum-driven algorithm performs the scanning in parallel but from only one selected vertex at a time. Ideally this algorithm has linear speed-up for dense graphs. Implemented naively both algorithms perform poorly, but can be improved by relaxations and approximations which reduce communication volume. In all cases the theoretically less attractive update-driven algorithm turns out to perform much better than the apparently preferable minimum-driven algorithm.
In this paper we present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here converts the decoding problem into a search problem through a graph tha...
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In this paper we present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here converts the decoding problem into a search problem through a graph that is a trellis for an equivalent code of the transmitted code. A generalized Dijkstra's algorithm, which uses a priority-first search strategy, is employed to search through this graph. This search is guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of the transmitted code. This function f is used to reduce drastically the search space and to make the decoding efforts of this decoding algorithm adaptable to the noise level. For example, for most real channels of the 35 000 samples tried, simulation results for the (128,64) binary extended BCH code show that the proposed decoding algorithm is fifteen orders of magnitude more efficient in time and in space than that proposed by Wolf. Simulation results for the (104, 52) binary extended quadratic residue code are also given.
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