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Context-aware quality assessment of structured and unstructured data
(2020-07)
Data analysis is a crucial process in the field of data science that extracts useful information from any form of data. The ease of access and maintenance makes structured data the most popular choice among many organizations ...
Data-driven modeling and analysis for cardiovascular disease risk prediction and reduction
(2021-05)
In recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD could be preventable by modifying lifestyle behaviors, the objective of this ...
Model-data fusion in digital twins of large scale dynamical systems
(2022-07)
Digital twins (DTs) are virtual entities that serve as the real-time digital counterparts of actual physical systems across their life-cycle. In a typical application of DTs, the physical system provides sensor measurements ...
Deep Autoencoders for Cross-Modal Retrieval
(2019-05-01)
Increased accuracy and affordability of depth sensors such as Kinect has created a great depth-data source for 3D processing. Specifically, 3D model retrieval is attracting attention in the field of computer vision and ...
New stochastic pore-scale simulation and machine learning approach to predicting permeability and tortuosity of heterogeneous porous media
(2023-05)
A new 3D stochastic pore-scale simulation approach was introduced in this study to investigate how stochastic pore connectivity impacts the permeability and hydraulic tortuosity of heterogeneous porous media. Multiple ...
Data-driven sub-grid model development for large eddy simulations of turbulence
(2019-05)
Turbulence modeling remains an active area of research due to its significant impact on a diverse set of challenges such as those pertaining to the aerospace and geophysical communities. Researchers continue to search for ...
Mechanical characterization of heterogeneous hyperelastic membrane using inverse methods
(2021-12)
Many soft biological tissues are heterogeneous, having different properties at different locations. Characterizing these tissues is very important for virtually testing potential medical technologies or protocols. Some ...
Machine learning and personality traits: A disturbing contribution from the algorithmic culture to behavioral science
(2018-12)
The time has come for behavioral scholars to benefit from the superior prediction accuracy of modern data mining practices over traditional data modeling. The current investigative study uses machine learning techniques ...
Digital Transformation: How to Beat the High Failure Rate
(2019-05-01)
Firms every year spend $1.3 trillion on digital transformation programs to improve efficiency because digital leaders outperform their peers in nearly every industry. However, digital transformations that are intended to ...
Quadcopter Trajectory Prediction and Wind Estimation Using Machine Learning
(2019-07)
Small unmanned aerial systems are heavily impacted by wind disturbances. Wind causes deviations from desired trajectories, potentially leading to crashes. In this thesis, we consider two inherently related problems: ...