We study a biodetection application as a case study to demonstrate that K-means-based unsupervised feature learning can be a simple yet effective alternative to deep learning techniques for small data sets with limited intra- as well as inter-class diversi...
bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning
This project was created to act as a final project submission for the EAPS591 course Cybertraining for FAIR Data Science offered by Purdue University for the Fall 2019-2020 semester. The aim of this project is to create a workflow for analysis and modeling...
Methane (CH4) emissions from wetland ecosystems exert large positive feedbacks to the global climate system. However, the estimation of wetland CH4 emissions at the global scale still has large uncertainties. Here we develop a predictive model of CH4 emiss...
Artificial Neural Network (ANN) Atmospheric Chemistry Modeling Biogeochemistry Earth and Atmospheric Sciences Interactive Data Language (IDL) Machine Learning Matlab Methane Dynamics Model (MDM) Methane Emission
This is the code for constructing the Thresholding After Random Projection (TARP) benchmark for a detection problem using labeled data. The benchmark is a curve in a two-dimensional plane whose x-axis is the Area Above the ROC Curve (AAC) and whose y-axis...
When developing plans for flood risk mitigation, one of the first hurdles local and state regional decision-makers must clear is gathering data on what assets actually exist on the ground in their jurisdictions. Even in areas like Louisiana—where significa...
This study proposes an empirical model to identify economic feasibility of product recycling by integrating machine learning and the Sherwood principle. A boundary that differentiates profitable and non-profitable EoL products for material recycling is qua...
The dataset consists of data from August 17, 2020, received by the ADS-B equipment installed at the Purdue University Airport (KLAF). The FAA aircraft registration database is also provided to assist in merging with the ADS-B data using the hex identificat...
RoboMal dataset is a collection of binary executables (ELF files) that are used to train and test machine learning models for malware detection in robotic software. All samples are labeled and the labels are provided in the CSV file. The RoboMal framework...
Lack of high-throughput phenotyping is a bottleneck to breeding for abiotic stress tolerance in crop plants. Efficient and non-destructive hyperspectral imaging can quantify plant physiological traits under abiotic stresses; however, prediction models gene...
Human gait analysis and detection are critical for many applications including wearable robotic devices, rehabilitation robots, reducing or tracking injury risk. We present an experimental protocol to label gait events based on gait patterns of human subje...
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