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Machine Learning

IEEE 802.11ac performance dataset contains information regarding normalized throughput achieved under five link configuration parameters and a channel condition measured by SNR. The five link configuration parameters are channel bandwidth, multiple-input multiple output (MIMO) antenna, modulation and coding schemes (MCS), guard interval and frame aggregation. In the dataset, there are seven columns: SNR value, MIMO, channel bandwidth, MCS, guard interval, frame aggregation and normalized throughput.

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The dataset contains the signal recording acquired on vehicle (car) drivers (ten experienced drivers and ten learner drivers) on the same 28.7 km route in the Silesian Voivodeship (in Polish województwo śląskie) in southern Poland. Experienced drivers performed the tasks in their own cars whereas the learner drivers performed the tasks under a supervison of a driving instructor in a specially marked cars (with L sign).

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Intelligent Hybrid model to Enhance Time Series Models for Predicting Network Traffic, the proposed research has used the clustering approach to handle the ambiguity from the entire network data for enhancing the existing time series models.

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This dataset contains multispectral high resolution 1627 image patches of size 10 x 10 pixels with each pixel size of 10mx10m. These patches are generated from the Sentinel-2 (A/B) satellite images acquired during the period of October 2018 to May 2019. It covered one life cycle (12 months) of the sugarcane crop in the region of the Karnataka, India. Many parameters like plantation season, soil type, plantation type, crop variety and irrigation type that affects the growth of the sugarcane crop are considered while generating the samples.

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Giemsa-stained thin blood smear slides from 150 P. falciparum-infected and 50 healthy patients were collected and photographed at Chittagong Medical College Hospital, Bangladesh. The smartphone’s built-in camera acquired images of slides for each microscopic field of view. Initially, the images were manually annotated by an expert slide reader at the Mahidol-Oxford Tropical Medicine Research Unit in Bangkok, Thailand (the originals can be found at NLM, ftp://lhcftp.nlm.nih.gov/Open-Access-Datasets/Malaria/).

 

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