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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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When batteries supply behind-the-meter services such as arbitrage or peak load management, an optimal controller can be designed to minimize the total electric bill. The limitations of the batteries, such as on voltage or state-of-charge, are represented in the model used to forecast the system's state dynamics. Control model inaccuracy can lead to an optimistic shortfall, where the achievable schedule will be costlier than the schedule derived using the model.

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The paper is aimed at an investigation of the features of a tubular-linear synchronous quasi-Halbach machine (T-LSM) where the radially-magnetized PMs are substituted by four equal segments with parallel magnetization. Such a substitution is done in an attempt to improve the machine cost-effectiveness which makes it a viable candidate to equip free-piston engine-based series

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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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This dataset contains sheets of handwritten Telugu characters separated in boxes. It contains vowel, consonant, vowel-consonant and consonant-consonant pairs of Telugu characters. The purpose of this dataset is to act as a benchmark for Telugu handwritting related tasks like character recognition. There are 11 sheet layouts that produce 937 unique Telugu characters. Eighty three writers participated in generating the dataset and contributed 913 sheets in all. Each sheet layout contains 90 characters except the last which contains 83 characters where the last 10 are english numerals 0-9.

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Table1 present the peak-level activation point of 8 brain regions for all 1080 subjects.

Table2 present the peak-level activation point of 8 brain regions for selected 893 subjects. 

 

Supplementary data -RotL.rar present the SPM{T}map and extracted masks calculated with 2nd-level modeling analysis from RtoL fMRI data of subjects 1 to 50.

Supplementary data -LtoR.rar present the SPM{T}map and extracted masks calculated with 2nd-level modeling analysis from LtoR fMRI data of subjects 1 to 50.

 

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In controlled source electromagnetic (CSEM) modeling with well casings, it is common to assume that the current is flowing vertically in each casing, due to the large conductivity contrast between casings and their host media. This assumption makes the integration of the tensor Green's function relating the induced fields to source currents simple, since only the z-z component of the tensor needs to be considered. However, in practice, it can be improper to neglect the horizontal current effects in the casing without a close examination.

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This dataset is related to the paper “Quantification of feature importance in automatic classification of power quality distortions” (IEEE International Conference on Harmonics and Quality of Power, March 2020). It includes the features extracted from synthetic signals with power quality distortions obtained from a public model (doi: 10.1109/ICHQP.2018.8378902).

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A paradigm dataset is constantly required for any characterization framework. As far as we could possibly know, no paradigmdataset exists for manually written characters of Telugu Aksharaalu content in open space until now. Telugu content (Telugu: తెలుగు లిపి, romanized: Telugu lipi), an abugida from the Brahmic group of contents, is utilized to compose the Telugu language, a Dravidian language spoken in the India of Andhra Pradesh and Telangana just a few other neighboring states. The Telugu content is generally utilized for composing Sanskrit writings.

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We created various types of network attacks in Internet of Things (IoT) environment for academic purpose. Two typical smart home devices -- SKT NUGU (NU 100) and EZVIZ Wi-Fi Camera (C2C Mini O Plus 1080P) -- were used. All devices, including some laptops or smart phones, were connected to the same wireless network. The dataset consists of 42 raw network packet files (pcap) at different time points.

* The packet files are captured by using monitor mode of wireless network adapter. The wireless headers are removed by Aircrack-ng.

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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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This dataset is from the paper " Improving the Effectiveness of Metamorphic Testing through Metamorphic Relation Prioritization- Submitted to Transactions in Software Engineering" by Madhusudan Srinivasan, HongChuan Wang, Prashanta Saha, and Upulee Kanewala submitted to IEEE Transactions on Software Engineering.

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This database contains the results of an experiment were healthy subjects played 5 trials of a rehabilitation-based VR game, to experience either difficulty variations or presence variations.

Colected results are demogrpahic information, emotional emotions after each trial and electrophysiological signals during all 5 trials.

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This dataset contains Cyber Threat Intelligence (CTI) data generated from public security reports and malware repositories.

The dataset is stored in a structured format (XML) and includes approximately 640,000 records from 612 security reports published from January 2008 to June 2019.

Several data types are contained in this dataset such as URL, host, IP address, e-mail account, hashes (MD5, SHA1, and SHA256), common vulnerabilities and exposures (CVE), registry, file names ending with specific extensions, and the program database (PDB) path.

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