RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures based on base-pairing probabilities. Two typical examples of the latter group are the popular maximum expected accuracy (MEA) method...
Most database users do not know formal query languages, such as SQL, and prefer to express their information needs using usable query languages, such as keyword queries. Keyword queries, however, are inherently ambiguous and challenging for the database systems to understand and answer effectively. We propose a novel approach to...
Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
A series of laboratory experiments were conducted to study the wave field in the inner lagoon excited by ‘long’ incident waves. Three cases were considered: Cases A, B and C presenting incident waves of wavelength with factors of 1, 2 and 2.5 times the width of the reef respectively. The...
Changes in the global climate and forest management practices have given rise to increasing numbers and severity of wildfires. More than five million acres burned in the United States in 2017, while in Canada 7.4 million acres burned. In particular, an increasing amount of dead woody biomass is a key...
The Rust programming language is a systems programming language with a strong static type system. A central feature of Rust’s type system is its unique concept of “ownership”, which enables Rust to give a user safe, low-level control over resources without the overhead of garbage collection. In Haskell, most data...
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 Intense Pulsed Light (IPL) sintering, pulsed large-area visible light from a xenon lamp is absorbed by nanoparticle films or patterns and converted to heat, resulting in rapid sintering of the nanoparticles. This work experimentally characterizes IPL sintering of silver nanoparticle films. A newly observed turning point in the evolution...
Appropriate representations of variational software simplify the analysis of their properties.This thesis proposes tailored representations of two kinds variational softwares: difference files of merge commits in Git and feature models. For the former, we use the Choice Edit Model, which is based on the choice calculus, to represent changes introduced...
Software testing is the process of evaluating the accuracy and performance of software, and automated software testing allows programmers to develop software more efficiently by decreasing testing costs. We compared two advanced random test generators, a Feedback-Directed Random Test Generator (FDR) and a Feedback-Controlled Random Test Generator (FCR), for an...
Mutation testing is one of the effective approaches measuring test adequacy of test suites. It is widely used in both academia and industry. Unfortunately, the adoption and practical use of mutation testing for Python 2.x programs face three obstacles. First, limited useful mutation operators. Existing mutation testing tools support very...
With the development of technologies in genome sequencing and variant detection, a huge number of variants are detected. To further analyze the variants, it requires an efficient tool to annotate the functional effect of variants. This project managed to develop an efficient program to annotate the functional effect of variants...
Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
We model the popular board game of Clue as an MDP and evaluate Monte-Carlo policy rollout in a simulated environment pitting different agents and policies against each other. We describe the choices we made in the representation, along with some of the problems we encountered along the way. We find...
The Open Modeling Environment (OME) is a tool developed to address some known shortcomings in ecological System Dynamics (SD) modeling research. OME provides a common set of methods for interacting directly with spatial information, reducing the need for modelers to create their own methods for doing so. The environment is...
Direct red Solid Oxide Fuel Cell (SOFC) Turbine hybrid plants have the potential to dramatically increase power plant efficiency, decrease emissions, and provide fast response to transient loads. The US Department of Energy's (DOE) Hybrid Performance Project is an experimental hybrid SOFC plant, built at the National
Energy Technology Laboratory...
Monte-Carlo Tree Search (MCTS) is an online-planning algorithm for decision-theoretic planning in domains with stochastic and combinatorial structure. The general applicability of MCTS makes it an ideal first choice to investigate when developing planners for complex applications requiring automated control and planning. The first contribution of this thesis is to...
Automatic analysis of American football videos can help teams develop strategies and extract patterns with less human effort. In this work, we focus on the problem of automatically determining which team is on offense/defense, which is an important subproblem for higher-level analysis. While seemingly mundane, this problem is quite challenging...
We investigate the data collection problem in sensor networks. The network consists of a number of stationary sensors deployed at different sites for sensing and storing data locally. A mobile element moves from sites to sites to collect data from the sensors periodically. There are different costs associated with the...
Constructing a panorama from a set of videos is a long-standing problem in computer vision. A panorama represents an enhanced still-image representation of an entire scene captured in a set of videos, where each video shows only a part of the scene. Importantly, a panorama shows only the scene background,...
Pedestrian distraction at roadway crossings has been correlated with a higher risk of pedestrian-vehicle collisions due to the pedestrian's cognitive, visual, and motor attention being drawn to a wide variety of secondary tasks.
This study is different from previous field studies of pedestrian midblock crossings in that the geometric layout...
The purpose of this article is to explore student reasoning with regard to problems in logic, particularly those related to the Principle of Mathematical Induction (PMI). The five case studies presented build off of work done by other researchers, most notably Dubinsky and Harel, who both looked at how students'...
Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
Auctions are used to solve resource allocation problem between many agents and many items in real-world settings. Unfortunately, in most cases, it is possible for selfish agents to manipulate the system for their own interest at the expense of the social welfare. Such manipulation can be prevented using the Vickrey-Clarke-Groves...
Novelty detection plays an important role in machine learning and signal processing. This
project studies novelty detection in a new setting where the data object is represented as
a bag of instances and associated with multiple class labels, referred to as multi-instance
multi-label (MIML) learning. Contrary to the common assumption...
Physical activity recognition using accelerometer data is a rapidly emerging field with many real-world applications. Much of the previous work in this area has assumed that the accelerometer data has already been segmented into pure activities, and the activity recognition task has been to classify these segments. In reality, activity...
Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
Air traffic flow management over the U.S. airpsace is a difficult problem. Current management approaches lead to hundreds of thousands of hours of delay, costing billions of dollars annually. Weather and airport conditions may instigate this delay, but routing decisions balancing delay with congestion contribute significantly to the propagation of...
Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
We consider the problem of strategic adversarial planning in a Real-Time Strategy (RTS) game. Strategic adversarial planning is the generation of a network of high-level tasks to satisfy goals while anticipating an adversary's actions. In this thesis we describe an abstract state and action space used for planning in an...
The first edition of the Highway Safety Manual (HSM) provides a quantitative
approach to predict the safety of transportation facilities based on the recently
developed scientific methods. This approach, known as the predictive method, was
developed for several states in the United States. Due to differences in driver
population, weather...
Since free riders in P2P network reduce the system's performance, how to maintain and encourage the nodes' cooperation is an important aspect of P2P related research. In this thesis, a P2P system is modeled based on two games: stag hunt game and snowdrift game. To relate the model to the...
A thesis presented on the determination of factors related to deposition, clearance, and dosimetry of the ICRP 30 lung model as related to smoking. Variations in calculations used to determine radiation doses leave a need to determine a standard method to determine absorbed dose from smoking. Standard parameters are used...
Customer requirements and engineering specifications will influence the direction of the design in any product, so it is crucial to make the requirements as stable as possible so quality designs can be produced on time within a budget. It would be optimal for requirements and specifications to remain constant but...
Monte-Carlo planning algorithms such as UCT make decisions at each step by
intelligently expanding a single search tree given the available time and then
selecting the best root action. Recent work has provided evidence that it can be
advantageous to instead construct an ensemble of search trees and make a...