This dataset includes scanning X-ray fluorescence (XRF) data for the core SPR0901-03KC (34.2832°N, 120.0401°W, 586 m water depth). SPR0901-03KC was collected by the research vessel R/V Sproul off Southern California in 2009.1. The research is funded by NSF OCE-0752093.
This dataset includes scanning X-ray fluorescence (XRF) data for the core MV0811-14JC (34.2818°N
120.0360°W, water depth: 582 m), which was collected by the research vessel R/V Melville off Southern California in 2008.11. The research is funded by NSF OCE-1304327.
Cotton, J.M., and Sheldon, N.D., 2013, Using stable carbon and nitrogen isotopes of hair to teach about sustainable agriculture through active learning: Journal of Geoscience Education 61, 59–67. https://doi.org/10.5408/12-309.1
This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file. and Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/ejhy-5h41
This dataset includes core physical properties (e.g., bulk density, porosity, P-wave velocity) and magnetic susceptibility data for SPR0901-04BC (34.2816°N, 120.0415°W, 588 m water depth) measured on the multisensor track (MST). SPR0901-04BC was collected by the research vessel R/V Sproul off Southern California in 2009.1. The study is supported by NSF OCE-0752093.
The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
The work on accelerating authenticated boot for embedded system resulted in designing an algorithm in python to perform the random address generation and cryptographic MAC calculation.
The Sampled Boot schemes implemented in this package allow a significant reduction of the time
needed to authenticate firmware images during startup, while still retaining a high degree of trust.
This is particularly useful for automotive applications in which startup time constraints make secure boot a time prohibitive process. and Citation for this dataset: Nasser, A., Gumise, W. (2019). Authenticated Boot Acceleration Algorithm [Code and data]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/yeh1-1x17
SPSS is required to access processed dataset in .sav format. Model output is provided as a word document, and Qualtrics survey instrument is included as PDF and .docx, where .docx version contains survey logic and question numbers.
Iyengar, R., Winkels, J., Smith, C. M., Meka, A. P., MD, Porath, J. D., MD, & Meurer, W. J., MD, MS. (2019, January 21). The Effect of Financial Incentives on Patient Decisions to Undergo Low-Value Head CT Scans. https://doi.org/10.31219/osf.io/4mdfw
This data set is a collection of word similarity benchmarks (RG65, MEN3K, Wordsim 353, simlex999, SCWS, yp130, simverb3500) in their original format and converted into a cosine similarity scale.
In addition, we have two Wikpedia Dumps from 2010 (April) and 2018 (January) in which we provide the original format (raw words), converted using the techniques described in the paper (MSSA, MSSA-D and MSSA-NR) (title in this repository), and also the word embeddings models for 300d and 1000d using a word2vec implementation. A readme.txt is provided with more details for each file.