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Big Data and Cognitive Computing, Volume 2, Issue 3

2018 September - 15 articles

Cover Story: With the increasing computational power of smartphones and smaller devices with high connectivity forming Internet of Things (IoT), we witness a golden opportunity to enable smart environments. Machine learning is set to play a significant role in such enablement through the deployment of predictive and descriptive models closer to the source (edge), so to reduce cloud and network latency and associated costs. We tested the edge deployed of state-of-the-art machine learning models for accuracy, latency and energy consumption. Moreover, these methods were tested for model construction at the edge, increasing the independence from cloud services. Based on the results of the conducted experiments, recommendations were given on which method to use depending on the applications’ requirements. View this paper
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Articles (15)

  • Article
  • Open Access
12 Citations
5,929 Views
16 Pages

Traffic Sign Recognition based on Synthesised Training Data

  • Alexandros Stergiou,
  • Grigorios Kalliatakis and
  • Christos Chrysoulas

To deal with the richness in visual appearance variation found in real-world data, we propose to synthesise training data capturing these differences for traffic sign recognition. The use of synthetic training data, created from road traffic sign tem...

  • Review
  • Open Access
111 Citations
26,889 Views
13 Pages

Digitalisation and Big Data Mining in Banking

  • Hossein Hassani,
  • Xu Huang and
  • Emmanuel Silva

Banking as a data intensive subject has been progressing continuously under the promoting influences of the era of big data. Exploring the advanced big data analytic tools like Data Mining (DM) techniques is key for the banking sector, which aims to...

  • Article
  • Open Access
3 Citations
4,417 Views
14 Pages

Ring aggregation networks are often employed by network carriers because of their efficiency and high fault tolerance. A fairness scheme is required in ring aggregation to achieve per-flow throughput fairness and bufferbloat avoidance, because frames...

  • Article
  • Open Access
39 Citations
11,725 Views
19 Pages

Astonishing progress is being made in the field of artificial intelligence (AI) and particularly in machine learning (ML). Novel approaches of deep learning are promising to even boost the idea of AI equipped with capabilities of self-improvement. Bu...

  • Article
  • Open Access
7 Citations
4,477 Views
18 Pages

Adaptive Provisioning of Heterogeneous Cloud Resources for Big Data Processing

  • Maarten Kollenstart,
  • Edwin Harmsma,
  • Erik Langius,
  • Vasilios Andrikopoulos and
  • Alexander Lazovik

Efficient utilization of resources plays an important role in the performance of large scale task processing. In cases where heterogeneous types of resources are used within the same application, it is hard to achieve good utilization of all of the d...

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Big Data Cogn. Comput. - ISSN 2504-2289