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Titlebook: Computer and Information Sciences; 32nd International S Tadeusz Czachórski,Erol Gelenbe,Ricardo Lent Conference proceedings 2018 Springer N

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Sergio C. Figueiredo,Jeffrey D. Greene TCP/IP traffic flow control. The impact of the self-similarity of the traffic on the controller parameters is investigated with the use of discrete event simulation. We analyze the influence of these parameters on the length of the queue, the number of rejected packets and waiting times. The result
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Writing to Gaming Audiences: A Case Study adequate for the hyperspectral dimension reduction (DR), classification or detection process. Moreover, only local neighboring data point’s properties are conserved in the LE method. To resolve these limitations, an improved feature extraction technique called modified Laplacian Eigenmaps (MLE) for
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Stephen Darwall,William Darwallarget . where some edges . are blocked. At the beginning, the traveller does not know which edges are blocked. He discovers them when arriving at one of their endpoints. The objective is to minimize the distance traversed to reach ...Westphal proved that no randomized strategy has a competitive rati
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https://doi.org/10.1007/978-3-319-97770-6 for meteorological big data applications. The architecture is designed with the recent advances in the field of spatial data warehousing (SDW) and spatial and temporal big data analytics. Measured meteorological data is stored in a big database (NoSQL database) and analyzed using Hadoop big data en
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https://doi.org/10.1057/9780230239555 hubness statistic as a measure of a relation between new samples and the existing training set. This allows to estimate the upper limit of neighbours that vote for the label of the new instance. This estimation improves the classifier performance in situations where some classes are locally under-r
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https://doi.org/10.1057/9780230239555el should be assigned to documents. When the number of labels is big, it is difficult to obtain required multi-label classification accuracy. Efficient label space dimension reduction may significantly improve classification performance. In the paper, we consider applying graph-based semi-clustering
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The Ethics of Rapid Tissue Donation (RTD)es most of the variance of the data arriving sequentially in a stream. We assume the data stream is evolving and hence the target subspace is changing over time. We cast this problem as a prediction problem, where the goal is to minimize the total compression loss on the data sequence. We review the
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