Artificial Intelligence
Load identification have shown significant performance gains in Chinese smart grids. Most existing load identification algorithms are based on electrical characteristics of steady or transient state, which are therefore limited by feature selection and analyzing pattern.
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Presented here is a dataset used for our SCADA cybersecurity research. The dataset was built using our SCADA system testbed described in our paper below [*]. The purpose of our testbed was to emulate real-world industrial systems closely. It allowed us to carry out realistic cyber-attacks.
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The dataset comprises of image file s of size 20 x 20 pixels for various types of metals and non-metal.The data collected has been augmented, scaled and modified to represent a number a training set dataset.It can be used to detect and identify object type based on material type in the image.In this process both training data set and test data set can be generated from these image files.
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Dataset for the paper entitled "Interactive Dual Attention Network for Text Sentiment Classification"
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We introduce a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems (VCSs). In contrast to prior efforts, the proposed database contains both genuine voice commands and replayed recordings of such commands, collected in realistic VCSs usage scenarios and using modern voice assistant development kits.
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Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3 and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity.
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This dataset is a large-scale Chinese hotel review data set collected by Tan Songbo. The corpus size is 10,000 reviews. The corpus is automatically collected and organized from Trip.com.
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This dataset was created from all Landsat-8 images from South America in the year 2018. More than 31 thousand images were processed (15 TB of data), and approximately on half of them active fire pixels were found. The Landsat-8 sensor has 30 meters of spatial resolution (1 panchromatic band of 15m), 16 bits of radiometric resolution and 16 days of temporal resolution (revisit). The images in our dataset are in TIFF (geotiff) format with 10 bands (excluding the 15m panchromatic band).
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Spoken Indian Language Identification Database
(9 languages, 8 different utterance lengths)
Languages
- Assamese
- Bengali
- Gujarati
- Hindi
- Kannada
- Malayalam
- Marathi
- Tamil
- Telugu
Durations
- 30 sec
- 10 sec
- 5 sec
- 3 sec
- 1 sec
- 0.5 sec
- 0.2 sec
- 0.1 sec
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