Pseudomonas aeruginosa is an important gram-negative opportunistic pathogen whose large genome allows it to thrive in diverse environments. There is a wide range of phenotypic variation within the species, which can be attributed both to variation in sequences present in most isolates (the core genome) or the presence or absence...
Deep learning is a new area of machine learning research that allows deep neural networks composed of multiple processing layers to learn representations of data with multiple levels of abstraction. Deep learning has helped in achieving the objective of pushing machine learning closer to one of its original goals of...
Polymer nanocomposites have attracted great interest in recent years because of their potential as tailored materials with enhanced properties. Recent experiments have shown that polymer nanocomposites are able to achieve significant improvement in dielectrical, thermal, mechanical and other physical properties compared with their parent polymer systems. More importantly, these outstanding...
Platelets are circulating anucleate discs derived from megakaryocytes, and play major roles in hemostasis, inflammation, thrombosis, and vascular biology. Multi-phase culture systems for inducing in vitro platelet production from mature megakaryocytes have been explored to allow progenitor expansion, megakaryocyte maturation, and promotion of platelet formation and shedding. In this thesis,...
Cells are complex, autonomous machines that integrate many environmental cues to execute a desired response. Though this property makes cells versatile, it presents significant design challenges when, to treat diseases, we must alter cellular responses. To understand changes to the complex regulatory pathways that cause diseases, studies often investigate the...
The ability of a machine to synthesize textual output in a form of human language is a long-standing goal in a field of artificial intelligence and has wide-range of applications such as spell correction, speech recognition, machine translation, abstractive summarization, etc. The statistical approach to enable such ability mainly involves...
In this dissertation, we start with the dictionary learning (DL) based single-frame super-resolution (SR) problem, where low resolution (LR) input frames are super-resolved to high resolution (HR) output frames. We propose to extend the previous single-frame SR methods to multiple-frames, i.e., estimating single HR output frame by multiple LR input...
The goal of this thesis is to design practical algorithms for nonlinear optimization in the case when the objective function is stochastic or nonsmooth. The thesis is divided into three chapters. Chapter 1 describes an active-set method for the minimization of an objective function that is structurally nonsmooth, viz., it...
Thermal overheating is a serious concern in modern supercomputing systems. Elevated temperature levels reduce the reliability and the lifetime of the underlying hardware and increase their power consumption. Previous studies on mitigating thermal hotspots at the hardware and run-time system levels have typically used approaches that trade off performance for...