Age, fasting and postprandial glucose and insulin levels of 3218 venezuelan women.
The data was retrieved in the Clinical Research Laboratory of the Caracas University Hospital, Venezuela, between 2009 and 2013
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This data set includes records of the student data, data descriptions, student demographic survey, class size from students to participated in the 10 program Personal Software Process course.
This version of the course was delivered between 1995 and 2006.
| The data was collected by the Software Engineering Institute (SEI) from classes taught by SEI staff and class data submitted by authorized instructors. |
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This dataset is part of our research on malware detection and classification using Deep Learning. It contains 42,797 malware API call sequences and 1,079 goodware API call sequences. Each API call sequence is composed of the first 100 non-repeated consecutive API calls associated with the parent process, extracted from the 'calls' elements of Cuckoo Sandbox reports.
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Dataset for the article: "Impacts of flow alteration on Swiss floodplains observed by remote sensing".
The present data are originating from two kinds of product:
- landsat time series of surface reflectances (product of)
- discharge statistics from the Swiss Federal Office for the Environment (extracted statistics)
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Collecting and analysing heterogeneous data sources from the Internet of Things (IoT) and Industrial IoT (IIoT) are essential for training and validating the fidelity of cybersecurity applications-based machine learning. However, the analysis of those data sources is still a big challenge for reducing high dimensional space and selecting important features and observations from different data sources. The study proposes a new testbed for an IIoT network that was utilised for creating new datasets called TON_IoT that collected Telemetry data, Operating systems data and Network data.
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One of the major research challenges in this field is the unavailability of a comprehensive network based data set which can reflect modern network traffic scenarios, vast varieties of low footprint intrusions and depth structured information about the network traffic. Evaluating network intrusion detection systems research efforts, KDD98, KDDCUP99 and NSLKDD benchmark data sets were generated a decade ago. However, numerous current studies showed that for the current network threat environment, these data sets do not inclusively reflect network traffic and modern low footprint attacks.
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The plotted graph shows the mean values of the framework evaluation data provided by 10 participants over 8 criteria.
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Boğaziçi University DDoS dataset (BOUN DDoS) is generated in Boğaziçi University via Hping3 traffic generator software by flooding TCP SYN, and UDP packets. This dataset includes attack-free user traffic as well as attack traffic and suitable for evaluating network-based DDoS detection methods. Attacks are towards one victim server connected to the backbone router of the campus. Attack packets have randomly generated spoofed source IP addresses. The data-trace was recorded on the backbone and included over 4000 active hosts.
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Typically, a paper mill comprises three main stations: Paper machine, Winder station, and Wrapping station. The Paper machine produces paper with particular grammage in gsm (gram per square meter). The typical grammage classes in our paper mill are 48 gsm, 50 gsm, 58 gsm, 60 gsm, 68 gsm, 70 gsm. The Winder station takes a paper spool that is about 6 m width as it’s input and transfers is to customized paper rolls with particular diameter and width.
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Dataset contains ten days real-world DNS traffic captured from campus network comprising of 4000 hosts in peak load hours. Dataset also contains labelled features.
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