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This paper considers the optimization of a class of joint source-channel codes described by finite-state encoders (FSEs) generating variable-length codes. It focuses on FSEs associated to joint source-channel integer arithmetic codes, which are uniquely decodable codes by design. An efficient method for computing the free distance of such codes using Dijkstra's algorithm is proposed. To facilitate...
An efficient solution for a single-source problem called Thorup's algorithm has been proposed, whose computational complexity, O(N), is smaller than that of Dijkstra's algorithm, O(N log N). In this paper, we compare the performance of Dijkstra's algorithm and Thorup's algorithm for large-scale network simulation. Through extensive experiments, we show that Thorup's algorithm is slightly faster with...
This paper applies Robust Optimization method to optimize the airline network planning process. The Dijkstra's Algorithm is firstly introduced to improve the initial solution and neighborhood structure. And the Robust Optimization method is applied to the problem of selecting the hub aerodromes in the airline network to help the decision making process. Furthermore, a hub-and-spoke network among 15...
This paper presents an approach to the shortest path problem in time-dependent multimodal networks. The approach derives, from the initial graph, a more simplified and non-time-dependent structure, called abstract graph, by using ant colony optimization. Then, a time-dependent Dijkstra's algorithm is used to compute the shortest path on the new structure. This approach improves two previous solutions...
We describe the first attempt to define an absolute energy efficiency figure that can be applied to any data network or ICT device to provide an understanding of its absolute energy efficiency. The resulting equation can be used as an objective comparative tool to assist in comparing the energy-efficiency performances of equivalently functional systems. More importantly, it also gives a guide as to...
Neurobiologists are collecting large amounts of electron microscopy image data to gain a better understanding of neuron organization in the central nervous system. Image analysis plays an important role in extracting the connectivity present in these images; however, due to the large size of these datasets, manual analysis is essentially impractical. Automated analysis, however, is challenging because...
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