The ongoing climate change has impacted the lives and livelihoods of people. A climate-related disaster acts as an exogenous shock to the economy that can have lingering effects over a larger region even if all the locations are not directly affected. Climate-related disasters do not follow the administrative boundaries. So,...
This thesis presents a novel design for a rheometer style viscometer by implementing high temperature and inert atmospheric requirements on the device. The goals of this device are to measure the viscosity of high temperature molten salts, which are corrosive and extremely hydroscopic. It also aims to be able to...
Automatic event extraction from natural text is an important and challenging task for natural language understanding. Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But such efforts, like tradition methods, have so far only focused on...
In this dissertation, we investigate three numerical methods for inverting the Laplace transform. These methods are all based on the trapezoidal-type approximations to the Bromwich integral. The first method is the direct integration method: It is a straightforward application of the trapezoidal rule to the Bromwich integral, followed by convergence...
Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language.
In this dissertation, we will first introduce several deep models...
The vast majority of U.S. farm bill spending goes to nutrition assistance, on the one hand, and farm safety net programs, on the other. Although these programs are a major part of federal government expenditures, controversial and governed by a common bill, they have rarely been quantitatively analyzed together. To...