Standards Research Data
Tenessee Eastman (TE) process simulates actual chemical processes and is widely used as a benchmark in test fault diagnosis and process control. The overall process consists of five operating units: reactor, condenser, vapor-liquid separator, recycle compressor and product stripper. It has standard training and test data sets for fault detection and diagnosis, classification, etc. Each data set is under different operating conditions。
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We conducted a semi-structured search of DBLP and MEDLINE using grouped search terms designed for maximal retrieval of relevant studies. DBLP’s search used the terms “survey” and “questionnaire data” to identify a total of 437 records from DBLP. MEDLINE’s search used three MeSH terms (“questionnaires,” “epidemiology,” and “epidemiologic methods”) with filter conditions set to exclude articles related to clinical trials and reviews as well as articles not written in English. The results were limited to articles written in English and published between 2001 and 2016.
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X-ray microscopy of a same bovine articular cartilage is enhanced by 16 hours of phosphotungstic acid (PTA) staining, showing cartilage collagen network, chondrocytes and tidemark, while the 0 hr non-stained x-ray microscopy could not resolve these features within articular cartilage.
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We introduce a benchmark of distributed algorithms execution over big data. The datasets are composed of metrics about the computational impact (resource usage) of eleven well-known machine learning techniques on a real computational cluster regarding system resource agnostic indicators: CPU consumption, memory usage, operating system processes load, net traffic, and I/O operations. The metrics were collected every five seconds for each algorithm on five different data volume scales, totaling 275 distinct datasets.
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RECOVERY-FA19 dataset is established for development and evaluation of retinal vessel detection algorithms in fluorescein angiography (FA). RECOVERY-FA19 provides 8 high-resolution ultra-widefield FA images acquired using Optos California P200DTx camera and corresponding labeled binary vessel maps.
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We proposed a new dataset, HazeRD, for benchmarking dehazing algorithms under realistic haze conditions. As opposed to prior datasets that made use of synthetically generated images or indoor images with unrealistic parameters for haze simulation, our outdoor dataset allows for more realistic simulation of haze with parameters that are physically realistic and justified by scattering theory.
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Data used on the submmitted article: "Dizang: A solution for collecting forensic evidences in cloud environments"
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"3_multi-media-of-figure5.zip" includes two short videos. Both of which shows the process of Inertial Generated Timing Sequence (IGTS) works.
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