Search Constraints
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Heath, Jeffrey
- Description:
- Images of villages in Mali in which Ben Tey (Dogon family) is the primary language. Each file name contains important information about the photos, and are structured thus: LanguageFamily_Language_IdentificationNumber_GeographicCoordinate_Description_Date_InitialsOfThePhotographer
- Keyword:
- villages, Dogon, Ben Tey, and Mali
- Citation to related publication:
- Moran, Steven & Forkel, Robert & Heath, Jeffrey (eds.) 2016. Dogon and Bangime Linguistics. Jena: Max Planck Institute for the Science of Human History. http://dogonlanguages.org
- Discipline:
- Humanities
-
- Creator:
- Reed, Matthew P., Boyle, K.
- Description:
- This is the first physical anthropomorphic test device to be based both on statistical body shape models as well as 3D printing.
- Keyword:
- Child Belt Fit Manikin
- Discipline:
- Engineering
-
- Creator:
- Heath, Jeffrey
- Description:
- Five-part documentary on making apiaries and collecting honey. Vigué ethnicity, Viemo language. location: near Karangasso-Vigué, southwestern Burkina Faso. credits at end of videos. Other documentaries from Burkina may be added later.
- Keyword:
- Burkina Faso, Vigué, Viemo, beekeeping, and apiary
- Discipline:
- Humanities
-
- Creator:
- Tye, Alexander R, Wolf, Aaron S, and Niemi, Nathan A
- Description:
- Detrital zircon age distributions provide robust insights into past sedimentary systems, but these age distributions are often complex and multi-peaked, with sample sizes too small to confidently resolve population distributions. This limited sampling hinders existing quantitative methods for comparing detrital zircon age distributions, which show systematic dependence on the sizes of compared samples. The proliferation of detrital zircon studies motivates the development of more robust quantitative methods. We present the first attempt, to our knowledge, to infer probability model ensembles (PMEs) for samples of detrital zircon ages using a Bayesian method. Our method infers the parent population age distribution from which a sample is drawn, using a Monte Carlo approach to aggregate a representative set of probability models that is consistent with the constraints that the sample data provide. Using the PMEs inferred from sample data, we develop a new estimate of correspondence between detrital zircon populations called Bayesian Population Correlation (BPC). Tests of BPC on synthetic and real detrital zircon age data show that it is nearly independent from sample size bias, unlike existing correspondence metrics. Robust BPC uncertainties can be readily estimated, enhancing interpretive value. When comparing two partially overlapping zircon age populations where the shared proportion of each population is independently varied, BPC results conform almost perfectly to expected values derived analytically from probability theory. This conformity of experimental and analytical results permits direct inference of the shared proportions of two detrital zircon age populations from BPC. We provide MATLAB scripts to facilitate the procedures we describe.
- Keyword:
- provenance, statistics, zircon, Bayesian, detrital, and density estimation
- Citation to related publication:
- A.R. Tye, A.S. Wolf, N.A. Niemi, Bayesian population correlation: A probabilistic approach to inferring and comparing population distributions for detrital zircon ages, Chemical Geology, Volume 518, 2019, Pages 67-78, ISSN 0009-2541, https://doi.org/10.1016/j.chemgeo.2019.03.039
- Discipline:
- Science
-
- Creator:
- Weng, Andrew, Mohtat, Peyman, Attia, Peter, Less, Greg, Lee, Suhak, and Stefanopoulou, Anna
- Description:
- The goal of this research is to investigate the impact of fast formation protocol on battery lifetime. The dataset has also been used to explore data-driven approaches in battery lifetime estimation (manuscript under review). Source code used to generate the results for this work has been included. The file contents contain a detailed README.md file which describes the organization of the files.
- Citation to related publication:
- Weng et al., Predicting the impact of formation protocols on battery lifetime immediately after manufacturing, Joule (2021), https://doi.org/10.1016/j.joule.2021.09.015
- Discipline:
- Engineering
-
- Creator:
- Curlis, JD, Renney, TJ, Davis Rabosky, AR, and Moore, TY
- Description:
- Efficient comparisons of biological color patterns are critical for understanding the mechanisms by which organisms evolve in ecosystems, including sexual selection, predator-prey interactions, and thermoregulation. However, elongate or spiral-shaped organisms do not conform to the standard orientation and photographic techniques required for automated analysis. Currently, large-scale color analysis of elongate animals requires time-consuming manual landmarking, which reduces their representation in coloration research despite their ecological importance. We present Batch-Mask: an automated and customizable workflow to facilitate the analysis of large photographic data sets of non-standard biological subjects. First, we present a user guide to run an open-source region-based convolutional neural network with fine-tuned weights for identifying and isolating a biological subject from a background (masking). Then, we demonstrate how to combine masking with existing manual visual analysis tools into a single streamlined, automated workflow for comparing color patterns across images. Batch-Mask was 60x faster than manual landmarking, produced masks that correctly identified 96% of all snake pixels, and produced pattern energy results that were not significantly different from the manually landmarked data set. The fine-tuned weights for the masking neural network, user guide, and automated workflow substantially decrease the amount of time and attention required to quantitatively analyze non-standard biological subjects. By using these tools, biologists will be able to compare color, pattern, and shape differences in large data sets that include significant morphological variation in elongate body forms. This advance will be especially valuable for comparative analyses of natural history collections, and through automation can greatly expand the scale of space, time, or taxonomic breadth across which color variation can be quantitatively examined.
- Keyword:
- convolutional neural network, photography, sensory ecology, color evolution, vision, and image segmentation
- Citation to related publication:
- Curlis, Renney, Davis Rabosky, Moore (submitted) Batch-Mask: An automated Mask R-CNN workflow to isolate non-standard biological specimens for color pattern analysis.
- Discipline:
- Engineering and Science
-
- Creator:
- Heath, Jeffrey
- Description:
- Images of villages in Mali in which Bankan Tey (Dogon family) is the primary language. Each file name contains important information about the photos, and are structured thus: LanguageFamily_Language_IdentificationNumber_GeographicCoordinate_Description_Date_InitialsOfThePhotographer
- Keyword:
- villages, Dogon, Bankan Tey, and Mali
- Citation to related publication:
- Moran, Steven & Forkel, Robert & Heath, Jeffrey (eds.) 2016. Dogon and Bangime Linguistics. Jena: Max Planck Institute for the Science of Human History. http://dogonlanguages.org
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey
- Description:
- images of villages in Mali in which Bangime is the primary language. Each file name contains important information about the photos, and are structured thus: LanguageFamily_Language_IdentificationNumber_GeographicCoordinate_Description_Date_InitialsOfThePhotographer
- Keyword:
- Mali, Bangime, and villages
- Citation to related publication:
- Moran, Steven & Forkel, Robert & Heath, Jeffrey (eds.) 2016. Dogon and Bangime Linguistics. Jena: Max Planck Institute for the Science of Human History. http://dogonlanguages.org
- Discipline:
- Humanities
-
Bangime language (Mali) audio files
User Collection- Creator:
- Heath, Jeffrey
- Description:
- Audio files for Bangime language (genetic isolate, eastern Mali)
5Works -
- Creator:
- Heath, Jeffrey and Dicko, Adama
- Description:
- transcriptions and translation to appear; second of two parts of this text
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey and Dicko, Adama
- Description:
- translation/translation to appear.
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey and Dicko, Adama
- Description:
- transcription/translation to appear.
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey and Dicko, Adama
- Description:
- translation/transcription to appear
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey and Dicko, Adama
- Description:
- transcription/translation to appear
- Discipline:
- Humanities
-
- Creator:
- Li, Jieming, Zhang, Leyou, Johnson-Buck, Alexander, and Walter, Nils G.
- Description:
- Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we have used deep learning to develop a rapid, automatic SMFM trace selector, termed AutoSiM, that improves the sensitivity and specificity of an assay for a DNA point mutation based on single-molecule recognition through equilibrium Poisson sampling (SiMREPS). The improved performance of AutoSiM is based on accepting both more true positives and fewer false positives than the conventional approach of hidden Markov modeling (HMM) followed by thresholding. As a second application, the selector was used for automated screening of single-molecule Förster resonance energy transfer (smFRET) data to identify high-quality traces for further analysis, and achieves ~90% concordance with manual selection while requiring less processing time. AutoSiM can be adapted readily to novel datasets, requiring only modest Transfer Learning.
- Keyword:
- deep learning, single-molecule fluorescence, total internal reflection microscopy, SiMREPS, smFRET, and Forster resonance energy transfer
- Citation to related publication:
- Li, J., Zhang, L., Johnson-Buck, A., & Walter, N. G. (2020). Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning. Nature Communications, 11(1), 5833. https://doi.org/10.1038/s41467-020-19673-1 and Hayward, S., Lund, P., Kang, Q., Johnson-Buck, A., Tewari, M., Walter, N. (2018). Single-molecule microscopy image data and analysis files for "Ultra-specific and Amplification-free Quantification of Mutant DNA by Single-molecule Kinetic Fingerprinting" [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z2CZ35DF
- Discipline:
- Science
-
- Creator:
- McCuen, Brett A.
- Description:
- The data were used to study the high-frequency geomagnetic disturbances within the magnetic field data. Included in this repository are the python scripts that perform an identification and classification of high-frequency signals within the magnetometer data that is downloaded from the databases listed in the Methodology section. All analysis and plots were created using subsequent Python libraries. The machine learning study implemented libraries from the sci-kit learn software. All of the specific methodology can be accessed in the readme.txt script.
- Keyword:
- geomagnetic field, high frequency, space weather, transient-large-amplitude, TLA, high frequency dB/dt, and dB/dt search algorithm
- Discipline:
- Science
-
- Creator:
- Nasser, Ahmad and Gumise, Wonder
- Description:
- 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
- Keyword:
- Trusted Computing, IOT security, Embedded Security, and Cyber Physical Systems
- Citation to related publication:
- Nasser, A., Gumise, W., and Ma, D., "Accelerated Secure Boot for Real-Time Embedded Safety Systems," SAE Int. J. Transp. Cyber. & Privacy 2(1) : 35-48, 2019, https://doi.org/10.4271/11-02-01-0003
- Discipline:
- Science
-
- Creator:
- Heath, Jeffrey
- Description:
- recordings made in Barato village. Referred to as "text 2021-02" and "text 2021-03." Text 2021-03 is transcribed and annotated at the end of the reference grammar (see link to Deep Blue Documents). Text 2021-02 covers a subset of the same content and has not been transcribed as of late 2022. See also "notes" file inside the work.
- Keyword:
- Bozo, Jenaama, Sorogaama
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey
- Description:
- recording in mp3 format. The reference grammar (see link to Deep Blue Documents) presents transcription and analysis as "text 2021-01."
- Keyword:
- Bozo, Jenaama, Sorogaama
- Discipline:
- Humanities
-
- Creator:
- Heath, Jeffrey
- Description:
- A subset of the Kelenga recordings are being transcribed and will serve as data for the Kelenga reference grammar which, when finished, will be included in the collection "Bozo languages of Mali (documents)" in Deep Blue Documents (see link).
- Keyword:
- Bozo and Kelenga
- Discipline:
- Humanities