Machine Learning

Nowadays road accident in Bangladesh is a buzzword due to its lack of carefulness of the driver of the vehicle where some parameter exists. The traffic safety of the roadway is an essential concern not only for transportation governing agencies but also for citizens of our country. For safe driving suggestions, the important thing is to find the variables that are tensed to relate to the fatal accidents that are occurring often. In this dataset, we provides a detailed account of the road accidents that covers the year of 2016 to 2019.

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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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This is the dataset we collected for the article "Scalable Undersized Dataset RF Classification: Using Convolutional Multistage Training". 17 objects were collected in the laboratory and scanned using a 'cw radar' setup featuring 2x UWB antennas (1 transmit antenna, 1 receive antenna), inside anechoic chamber. There was no clutter added in the experiment.

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This dataset containg EMG data recorded with a sample rate of 1kHz. Data was collected from  the brachioradialis, flexor carpi ulnaris and common extensor digitorum muscles.

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Several fields of study can benefit from a large, structured, and accurate dataset of historical figures. Due to a lack of such a dataset, in this paper, we aim to use machine learning and text mining models to collect, predict, and cleanse online data with a focus on age and gender. We developed a five-step method and inferred birth and death years, binary gender, and occupation from community-submitted data to all language versions of the Wikipedia project.

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This dataset includes the rotor geometrical parameters (*.csv) and motor parameters (*.csv) of interior permanent magnet synchronous motors. The rotor geometry covers three structures: 2D-, V-, and Nabla-structures. The motor parameters are generated by machine learning based on the finite element analysis results. The software JMAG Designer 19.1 was used for the finite element analysis.

 

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The dataset provided contains the invariants in the form of antecedent and consequent mined using Association Rule Mining with implicit measures such as Confidence, Support, Lift, etc. from an EPIC Plant (Electrical Power and Intelligent Control System).

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Nowadays, with the rapid increase in the number of applications and networks, the number of cyber multi-step attacks has been increasing exponentially. Thus, the need for a reliable and acceptable Intrusion Detection System (IDS) solution is becoming urgent to protect the networks and devices. However, implementing a robust IDS needs a reliable and up-to-date dataset in order to capture the behaviors of the new types of attacks, especially multi-step attacks. In this work, a new benchmark Multi-Step Cyber-Attack Dataset (MSCAD) is introduced.

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This repository contains code to apply the ESPER method to quasi-continuum models of biomolecules exhibiting multiple degrees of freedom, as described in Seitz et al. (2022, IEEE TCI). As inputs into ESPER, detailed instructions are also provided for generating custom synthetic datasets with increasing complexity to mirror known cryo-EM image attributes.

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