This entry archives the SedCT MATLAB code, version 1.05, which is a MATLAB based application with graphical interface for processing of sediment core Computed Tomography (CT) data collected on a medical CT scanner. It was designed for use with products from the Oregon State University (OSU) College of Veterinary Medicine Toshiba 64 Slice medical CT scanner, but has been tested on other medical CT scanner systems. The program is documented by Reilly et al. (2017) and on the OSU Marine and Geology Repository website (www.osu-mgr.org/sedct). We also include sample CT data from a sediment core collected from Fish Lake, Utah (Reilly et al., 2018). Computed tomography (CT) of sediment cores allows for high-resolution images, three-dimensional volumes, and down core profiles. These quantitative data are generated through the attenuation of X-rays, which are sensitive to sediment density and atomic number, and are stored in pixels as relative gray scale values or Hounsfield units (HU). We present a suite of MATLAB™ tools specifically designed for routine sediment core analysis as a means to standardize and better quantify the products of CT data collected on medical CT scanners. SedCT uses a graphical interface to process Digital Imaging and Communications in Medicine (DICOM) files, stitch overlapping scanned intervals, and create down core HU profiles in a manner robust to normal coring imperfections. Utilizing a random sampling technique, SedCT reduces data size and allows for quick processing on typical laptop computers. SedCTimage uses a graphical interface to create quality tiff files of CT slices that are scaled to a user-defined HU range, preserving the quantitative nature of CT images and easily allowing for comparison between sediment cores with different HU means and variance. References Reilly, B. T., Stoner, J. S., & Wiest, J. (2017). SedCT: MATLAB™ tools for standardized and quantitative processing of sediment core computed tomography (CT) data collected using a medical CT scanner. Geochemistry, Geophysics, Geosystems, 18(8), 3231–3240. https://doi.org/10.1002/2017GC006884 Reilly, B. T., Stoner, J. S., Hatfield, R. G., Abbott, M. B., Marchetti, D. W., Larsen, D. J., et al. (2018). Regionally consistent Western North America paleomagnetic directions from 15 to 35 ka: Assessing chronology and uncertainty with paleosecular variation (PSV) stratigraphy. Quaternary Science Reviews, 201, 186–205. https://doi.org/10.1016/j.quascirev.2018.10.016

This archive includes the research data associated to the paper: Giuliano Casale. Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. ACM Meas. Anal. Comput. Syst., 1(1), 2017. The paper is accepted for presentation at ACM SIGMETRICS 2017. The research data requires MATLAB 2015a or later. Four datasets are included, each corresponding to a section of the paper: - sec5.3.1: Small and medium models without infinite server nodes (Section 5.3.1) - sec5.3.2: Large models without infinite server nodes (Section 5.3.2) - sec5.3.3: Models with infinite server nodes (Section 5.3.3) - sec5.4: Optimization programs (Section 5.4) A description of each dataset is included in the README.TXT file inside each folder.