Over the last two decades, satisfiability and satisfiability-modulo theory (SAT/SMT) solvers have grown powerful enough to be general purpose reasoning engines throughout software engineering and computer science. However, most practical use cases of SAT/SMT solvers require not just solving a single SAT/SMT problem, but solving sets of related SAT/SMT problems....
Hydrogen is an increasingly attractive low-carbon energy carrier for a variety of stationary and mobile applications. Currently, the vast majority of hydrogen in the United States is produced via the energy intensive steam reforming of natural gas. The cost and carbon emissions associated with hydrogen production can be reduced by...
The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power...
This thesis outlines the development of new elastomeric materials and manufacturing processes for soft robotics. Specifically, this work describes the development of custom material formulations for use in additive manufacturing, additive manufacturing processing techniques for silicone elastomers, and multi-component additive manufacturing techniques. Material synthesis and processing is a gap in...
Variability is an important and widely studied topic across domains such as version control, software product lines, and metaprogramming. This dissertation presents an investigation into the process of systematically adding variability to data structures and programs, leading to guidelines for variational data structures and implications for programs that create, manipulate,...
In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
Cell signaling is often mediated by protein-protein interactions, which must be specific, tunable, and transient to allow agile responsiveness to cellular messages. Due to their unique properties, multivalent, intrinsically disordered proteins make ideal candidates to accomplish these vital tasks. A single protein with multiple binding sites may bind numerous partners,...
Polycyclic aromatic hydrocarbons (PAHs) are a group of environmental contaminants consisting of fused benzene rings. Parent-PAHs, methylated-PAHs (MPAHs), and PAHs with molecular weight of 302 a.m.u (MW302-PAHs) are considered as unsubstituted-PAHs. These unsubstituted-PAHs undergo transformation reactions resulting in the formation of PAH-transformation products (PAH-TPs), or substituted-PAHs, including nitrated-, oxygenated-, and...
The scarcity of wireless spectrum resources and the overwhelming demand for wireless broadband resources have prompted industry, government agencies and academia within the wireless communities to develop and come up with effective solutions that can make additional spectrum available for broadband data. As part of these ongoing efforts, cognitive radio...
Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications.
Time-series analysis involves a variety of tasks.
To predict future...