Artificial Intelligence

Multi-label event classification label of each sample-document is done with nine bits. The first bit signifies whether an event is present or absent with 1 or 0 respectively. The remaining eight bits signifies presence or absence of (i) covid, (ii) flood, (iii) storm, (iv) heavy rain, (v) cloudburst, (vi) landslide, (vii) earthquake, (viii) Tsunami with 1 or 0. The location and the impact sentence classification labeling are similar.

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A synthetic data for low power (P ≤10 mW) InGaAsP MQW-DFB lasers operating at a wavelength (λ) ranging from 1.53 to 1.57 µm at a case temperature  laying between -40 ℃ to 85 ℃ with side mode suppression ratio of more than 35 dB is generated and can be used for laser lifetime prediction using machine learning based approaches. 

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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization. 

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3335 Views

Filtered NGSIM and Artificial Datasets used in the paper "A Compositional Paradigm for Read-time systems".

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81 Views

Data Description:

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10166 Views

This benchmark dataset accompanies an article paper titled ``Learning to Reuse Distractors to support Multiple Choice Question Generation in Education''. It contains a test of 298 educational questions covering multiple subjects & languages and a 77K multilingual pool of distractor vocabulary. The goal is for a given question to propose a list of relevant candidate distractors from the pool of distractors. 

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358 Views

In this paper, we develop a hierarchical aerial computing framework composed of high altitude platform (HAP) and unmanned aerial vehicles (UAVs) to compute the fully offloaded tasks of terrestrial mobile users which are connected through an uplink non-orthogonal multiple access (UL-NOMA).

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This dataset contains pathloss and ToA radio maps generated by the ray-tracing software WinProp from Altair. The dataset allows to develop and test the accuracies of pathloss radio map estimation methods and localization algorithms based on RSS or ToA in realistic urban scenarios. More details on the datasets can be found in the dataset paper: https://arxiv.org/abs/2212.11777.

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4136 Views

The provided dataset is created is created by using European Commission Rapid Alert System's data for Salmonella cases. The dataset composed by 5 variables and all data is providet in categorical format. it is possible to use the dataset predict the salmonella cases based on type of food, month, country and warmth.

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