Standards Research Data
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Dockerfile plays an important role in the Docker-based containerization process, but many Dockerfile codes are infected with smells in practice. This dataset contains a collection of 6,334 projects to help developers gain some insights into the occurrence of Dockerfile smells. Those projects belong to 10 popular programming languages, i.e., Shell, Makefile, Ruby, PHP, Python, Java, HTML, CSS, JavaScript, and Go.
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This data set contains three MATLAB codes related to the numerical examples of the article etntitled "Data Collection versus Data Estimation: A Fundamental Trade-off in Dynamic Invariant Networks with Known and Unknown Models".
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This contains three MATLAB codes of the numerical examples of the article, entitled "Data Collection versus Data Estimation: A Fundamental Trade-off in Dynamic Invariant Networks with Known and Unknown Models".
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This contains three MATLAB codes of the numerical examples of the article, entitled "Data Collection versus Data Estimation: A Fundamental Trade-off in Dynamic Invariant Networks with Known and Unknown Models".
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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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Data of our paper, Expansion Coding for Performance and Lifetime Improvement on MLC STT-RAM.
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original response data for PGC/UGC comparison
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This folder contains two csv files and one .py file. One csv file contains NIST ground PV plant data imported from https://pvdata.nist.gov/. This csv file has 902 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST ground PV plant data.
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