Machine Learning
This dataset is used for the identification of video in the internet traffic. The dataset was prepared by using Wireshark. It comprises of two types of traffic data, VPN (Virtual Private Network) or encrypted traffic data and Non-VPN or unencrypted traffic. The dataset consist of the data streams (.pcap) of 43 videos. Each video is played 50 times in both VPN and Non-VPN mode. The streams were obtained by setting-up a dummy client on a PC which plays a YouTube video and Wireshark is used to capture the internet traffic.
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his repository includes all files regarding to "Analyzing Arabic Twitter-based Patient Experience Sentiments using MARBERT" graduation project.
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Ground Penetrating Radar (GPR) has a wide range of applications such as detection of buried mines, pipes and wires. GPR has been used as a near-surface remote sensing technique, and its working principle is based on electromagnetic (EM) wave theory. Here proposed data set is meant for data driven surrogate modelling based Buried Object Characterization. The considered problem of estimating geophysical parameters of a buried object is 2D. The training and testing scenarios include B-scan images (2D data), which contain 16 pairs of A-scan (concatenated forms of A-scans).
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Sales dataset
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Change address identification is one of the difficulties in bitcoin address clustering as an emerging social computing problem. Most of the current related research only applies to certain specific types of transactions and faces the problems of low recognition rate and high false positive rate. We innovatively propose a clustering method based on multi-conditional recognition of one-time change addresses and conduct experiments with on-chain bitcoin transaction data. The results show that the proposed method identifies at least 12.3\% more one-time change addresses than other heuristics.
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This research has produced datasets that can be used openly for other researchers. The dataset is compiled from images of woven fabrics originating from the East Nusa Tenggara Province of Indonesia. A total of 68 fabrics from six districts have been grouped and gone through the image embedding process to become RAW numerical data for further processing. By using Logistic Regression, the classifier accuracy rate for this dataset is only 79.4%. For that other researchers can contribute to improve this accuracy.
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This Matlab code uses Deep GRU and optimized Monarch Butterfly algorithm for MEMS accelerometer temperature drift compensation
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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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This is a dataset for DDoS attack and our dataset has over 50 milion records
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