Other
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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Wide varieties of scripts are used in writing languages throughout the world. In a multiscript and multi-language environment, it is necessary to know the different scripts used in every part of a document to apply the appropriate document analysis algorithm. Consequently, several approaches for automatic script identification have been proposed in the literature, and can be broadly classified under two categories of techniques: those that are structure and visual appearance-based and those that are deep learning-based.
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The supplementary materials contain all the original data used in the manuscript, including lncrna-disease association, mirna-disease association and lncRNA+ mirna-disease association.
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The year 2018 was declared as "Turkey Tourism Year" in China. The purpose of this dataset, tourists prefer Turkey to be able to determine. The targeted audience was determined through TripAdvisor. Later, the travel histories of individuals were gathered in four different groups. These are the individuals’ travel histories to Europe (E), World (W) Countries and China (C) City/Province and all (EWC). Then, "One Zero Matrix (OZ)" and "Frequency Matrix (F)" were created for each group. Thus, the number of matrices belonging to four groups increased to eight.
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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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This dataset contains the simulated results of the low frequency bent antenna. The data is gererated using HFSS and ADS
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This data set consists of
1 Data set for learning noun-group patterns (from core products)
2 Data sets for the experiment assemble dependent bug reports (from Firefix product)
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A benchmark dataset is always required for any classification or recognition system. To the best of our knowledge, no benchmark dataset exists for handwritten character recognition of Manipuri Meetei-Mayek script in public domain so far. Manipuri, also referred to as Meeteilon or sometimes Meiteilon, is a Sino-Tibetan language and also one of the Eight Scheduled languages of Indian Constitution. It is the official language and lingua franca of the southeastern Himalayan state of Manipur, in northeastern India.
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Noise control is required to ensure crew habitability onboard an offshore platform. Applying noise prediction is important to identify the potential noise problem at the early stage of the offshore platform design to avoid costly retrofitting in the implementation stage. Noise data were collected. The 4 output targets are namely: spatial sound pressure level (SPL), spatial average SPL, structure-borne noise and airborne noise at different octave frequencies (e.g. 125Hz, 250Hz, 500Hz, 1000Hz, 2000Hz, 4000Hz, 8000 Hz).
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In file folder “PNML” contains Petri Net models of three different special structures: concurrent, exclusive and loop. We use “c” to stand for concurrent structure, “e” to stand for exclusive structure and “l” to stand for loop structure. We name the model as “structure abbreviation + number of branches on each special structure + count of special structures”. For example “e_4_5.pnml” is name for exclusive structure which has 5 exclusive substructures and there are 4 branches on each substructure.
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