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This dataset is benchmark dataset we use in our research for Intrusion Detection System.
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It is possible to construct "aerosol cytometers" based on different types of Zhulanov's laser aerosol counters | diffusion aerosol spectrometers (DAS) [1-8] and "hydrosol cytometers" based on hydrosol particle counters (adopted for ocean marine, ocean and hydrothermal conditions [9,10]).
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These datasets were generated in a computer network environment where eXfiltration Advanced Persistent Threats were launched against a number of high-value targets.
It is the alert log of the Security Onion SIEM which aggregates alerts from network and host-based intrusion detection systems that are securing the network environment.
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This folder contains the code and datasets necessary for performing experiments on the Steimann and Defects4J coverage matrices detailed in "Doric: Foundations for Statistical Fault Localisation". See the README.txt inside the folder for further details.
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There are two types of data: raw EEG data recorded from the Brain-Vision system and Mat file converted by BBCI-Tool Box.
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Supplementary material for article "An Efficient Meta-Heuristic for Multi-objective Flexible Job Shop Inverse Scheduling Problem"
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The fifth-generation cellular networks (5G)has been proposed as a solution for the accelerating growth in data traffic. As part of 5G, millimetre-wave (mmWave) is suggested as one of the potential spectrum candidates due to the vastly available bandwidth. Accordingly, both indoor and outdoor propagation measurements on mmWave have been widely conducted over the recent years. These field measurements were heavily dependent on utilizing expensive channel-sounders and tools.
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This dataset is for the paper titled: Segmentation of Cervical Cell Images based on Generative Adversarial Networks. The dataset is used to train and test the Cell-GAN, a generative adversarial network. After training, the Cell-GAN is able to generate a complete single-cell image which has the similar contour to the cell to be segmented.
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This data set is for the paper titled:
Channel Coding in 5G New Radio
Tutorial Overivew and Performance Comparison with 4G LTE
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The database contains PROCON metrics values extracted from more than 30400 source code files (with 14950 bug reports) of GitHub repository. Various Machine earning (ML) models trained using PROCON metrics outperform the ones trained using OO metrics of PROMISE repository.
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