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Titlebook: Database and Expert Systems Applications; DEXA 2018 Internatio Mourad Elloumi,Michael Granitzer,Roland Wagner Conference proceedings 2018 S

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Observer-Based Feedback Stabilizationntally show exploratory queries can be efficiently evaluated based on the input edges and it performs better than Spark. We also show that skewed degree vertices, cycles and cliques are the main reason exploratory queries become slow.
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Observer-Based Feedback Stabilizationsits. The initial results show a high accuracy for the limited thirty-four patient labelled data set that we used in this pilot study. We are currently processing a larger data set to test our approach.
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https://doi.org/10.1007/978-3-540-74345-3s) and we are able to successfully discriminate tumoral from non tumoral samples using function-, tree-, and rule-based classifiers. Finally, we select the best performing genes (matrices) ranking them according to the accuracy of the classifiers and we execute an enrichment analysis of them. Those
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https://doi.org/10.1007/1-84628-449-X promising to increase throughput and performance of protein identification in a metaproteomics workflow. In this paper we analyze the core functions of the established protein identification engine X!Tandem and show that streaming Fast Data architectures are suitable for protein identification. Fur
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Passenger Transportation Systems we call protein “co-occurrences” to guide data mining on the CMS dataset. Preliminary results show that the proposed implementation is computationally efficient and is able to select only a small subset of significant motifs.
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Modeling Variable-Geometry Suspension Systemt recent years. Some of them can be considered as an ideal solution to visualize large sets with high number of possible relations between them. In this paper, we firstly review several set-visualizing techniques that we consider most suitable to satisfy the two mentioned features of biclustering an
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Control of Ships and Underwater Vehiclesg query workloads (cubes, exploration, pre-processing). Parallel and main memory processing have become important features to exploit new hardware and cope with data volume. With such landscape in mind, we present a survey comparing modern row and columnar DBMSs, contrasting their ability to write d
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