Machine Learning

Industrial Internet of Things (IIoTs) are high-value cyber targets due to the nature of the devices and connectivity protocols they deploy. They are easy to compromise and, as they are connected on a large scale with high-value data content, the compromise of any single device can extend to the whole system and disrupt critical functions. There are various security solutions that detect and mitigate intrusions.

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The IEEE 24 bus system is modelled in Digsilent’s Power factory, and normal operating data points are generated under quasi dynamic simulation and N-2 contingencies.  An optimization problem to generate false data injection attack vectors are then modelled using MATLAB. This data contains normal, contingency and attack data points for the necessary variables in a power network. The attack data has 5 parts, with each part generated by a different type of attack.

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Brain-Computer Interface (BCI) has become an established technology to interconnect a human brain and an external device. One of the most popular protocols for BCI is based on the extraction of the so-called P300 wave from EEG recordings. P300 wave is an event-related potential with a latency of 300 ms after the onset of a rare stimulus. In this paper, we used deep learning architectures, namely convolutional neural networks (CNNs), to improve P300-based BCIs.

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This is dataset I use in creating recommendation. I get it from bukalapak, one of the marketplace in Indonesia, which specific keyword "Gegep Tekiro". This dataset contains only 240 records / data.

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This document describes the details of the BON Egocentric vision dataset. BON denotes the initials of the locations where the dataset was collected; Barcelona (Spain); Oxford (UK); and Nairobi (Kenya). BON comprises first-person video, recorded when subjects were conducting common office activities. The preceding version of this dataset, FPV-O dataset has fewersubjects for only a single location (Barcelona). To develop a location agnostic framework, data from multiple locations and/or office settings is essential.

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Several experimental measurement campaigns have been carried out to characterize Power Line Communication (PLC) noise and channel transfer functions (CTFs). This dataset contains a subset of the PLC CTFs, impedances, and noise traces measured in an in-building scenario.

The MIMO 2x2 CTFs matrices are acquired in the frequency domain, with a resolution of 74.769kHz, in the frequency range 1 - 100MHz. Noise traces, in the time domain with a duration of about 16 ms, have been acquired concurrently from the two multi-conductor ports. 

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The Android Malware Detection Dataset consists of different flavors and diversity of malware APK files that can be used for malware detection using machine learning. It is my research work and if you use this dataset please cite my work in your research papers.

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With the motivation of no good data sources available for all diseases (from generic to chronic) and their treatment courses, a new dataset is synthesized by exploring several medical websites and resources. It provides the precaution list corresponding to over 1000+ diaganosis. prec\_t.csv : (did, diagnose, pid) = (Disease identifier, Disease name, treatment course). This dataset can be utilized for many machine learning or deep learning based healthcare applications.

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6358 Views

Depressive/Non-depressive tweets  between December 2019 and December 2020 originated largely from India and parts of Indian subcontinent. Sentiment Scores alloted using text blob. Tweets are extracted specifically keeping in mind the top 250 most frequently used negative lexicons and positive lexicons accesed using SentiWord and various research publications.

Tweet Amount : 1.4 Lakhs

 

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