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Full-Text Articles in Engineering
Trip Based Modeling Of Fuel Consumption In Modern Heavy-Duty Vehicles Using Artificial Intelligence, Sasanka Katreddi, Arvind Thiruvengadam
Trip Based Modeling Of Fuel Consumption In Modern Heavy-Duty Vehicles Using Artificial Intelligence, Sasanka Katreddi, Arvind Thiruvengadam
Faculty & Staff Scholarship
Heavy-duty trucks contribute approximately 20% of fuel consumption in the United States of America (USA). The fuel economy of heavy-duty vehicles (HDV) is affected by several real-world parameters like road parameters, driver behavior, weather conditions, and vehicle parameters, etc. Although modern vehicles comply with emissions regulations, potential malfunction of the engine, regular wear and tear, or other factors could affect vehicle performance. Predicting fuel consumption per trip based on dynamic on-road data can help the automotive industry to reduce the cost and time for on-road testing. Data modeling can easily help to diagnose the reason behind fuel consumption with a …
An Elastic-Net Logistic Regression Approach To Generate Classifiers And Gene Signatures For Types Of Immune Cells And T Helper Cell Subsets, Arezo Torang, Paraag Gupta, David J. Klinke Ii
An Elastic-Net Logistic Regression Approach To Generate Classifiers And Gene Signatures For Types Of Immune Cells And T Helper Cell Subsets, Arezo Torang, Paraag Gupta, David J. Klinke Ii
Faculty & Staff Scholarship
Background: Host immune response is coordinated by a variety of different specialized cell types that vary in time and location. While host immune response can be studied using conventional low-dimensional approaches, advances in transcriptomics analysis may provide a less biased view. Yet, leveraging transcriptomics data to identify immune cell subtypes presents challenges for extracting informative gene signatures hidden within a high dimensional transcriptomics space characterized by low sample numbers with noisy and missing values. To address these challenges, we explore using machine learning methods to select gene subsets and estimate gene coefficients simultaneously. Results: Elastic-net logistic regression, a type of …
Application Of Machine Learning And Artificial Intelligence In Proxy Modeling For Fluid Flow In Porous Media, Shohreh Amini, Shahab Mohaghegh
Application Of Machine Learning And Artificial Intelligence In Proxy Modeling For Fluid Flow In Porous Media, Shohreh Amini, Shahab Mohaghegh
Faculty & Staff Scholarship
Reservoir simulation models are the major tools for studying fluid flow behavior in hydrocarbon reservoirs. These models are constructed based on geological models, which are developed by integrating data from geology, geophysics, and petro-physics. As the complexity of a reservoir simulation model increases, so does the computation time. Therefore, to perform any comprehensive study which involves thousands of simulation runs, a very long period of time is required. Several efforts have been made to develop proxy models that can be used as a substitute for complex reservoir simulation models. These proxy models aim at generating the outputs of the numerical …
Machine Learning In Manufacturing: Advantages, Challenges, And Applications, Thorsten Wuest, Daniel Weimer, Christopher Irgens, Klaus-Dieter Thoben
Machine Learning In Manufacturing: Advantages, Challenges, And Applications, Thorsten Wuest, Daniel Weimer, Christopher Irgens, Klaus-Dieter Thoben
Faculty & Staff Scholarship
The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means available. One area, which saw fast pace developments in terms of not only promising results but also usability, is machine learning. Promising an answer to many of the old and new challenges of manufacturing, machine learning is widely discussed by researchers and practitioners alike. However, the field is very broad and even confusing which presents a challenge and a barrier hindering …