Index Catalog // ScholarsArchive@OSU

Numerical modeling and experiments on wood-strand composites

Creator:: Le, Edward A.
Abstract:: In wood-based composites, the glue-line (interface) between wood-strands affects the stress transfer from one member to the next. The glue-line properties determine the rate of load transfer between phases and these properties depend on wood species, surface preparation, glue properties, glue penetration into wood cells, and moisture content of the...
Resource Type:: Dissertation

Learning ranking functions for efficient search

Creator:: Xu, Yuehua
Abstract:: This dissertation explores algorithms for learning ranking functions to efficiently solve search problems, with application to automated planning. Specifically, we consider the frameworks of beam search, greedy search, and randomized search, which all aim to maintain tractability at the cost of not guaranteeing completeness nor optimality. Our learning objective for...
Resource Type:: Dissertation

Nanoparticle-assisted diffusion brazing of metal microchannel arrays : nanoparticle synthesis, deposition, and characterization

Creator:: Eluri, Ravindranadh T.
Abstract:: Microchannel process technology (MPT) offers several advantages to the field of nanomanufacturing: 1) improved process control over very short time intervals owing to shorter diffusional distances; and 2) reduced reactor size due to high surface area to volume ratios and enhanced heat and mass transfer. The objective of this thesis...
Resource Type:: Dissertation

Toward computer vision for understanding American football in video

Creator:: Hess, Robin W.
Abstract:: In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
Resource Type:: Dissertation

Bayesian optimization with empirical constraints

Creator:: Azimi, Javad
Abstract:: Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
Resource Type:: Dissertation

Microstructure of radiation damage in the uranium film and its backing materials irradiated with 136 MeV 136Xe+26, Microstructure of radiation damage in the uranium film and its backing materials irradiated with 136 MeV ¹³⁶Xe⁺²⁶

Creator:: Sadi, Supriyadi
Abstract:: Microstructure changes in uranium and uranium/metal alloys due to radiation damage are of great interest in nuclear science and engineering. Titanium has attracted attention because of its similarity to Zr. It has been proposed for use in the second generation of fusion reactors due to its resistance to radiation-induced swelling....
Resource Type:: Dissertation

Machine learning for improving the quality of citizen science data

Creator:: Yu, Jun
Abstract:: Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
Resource Type:: Dissertation

New learning modes for sequential decision making

Creator:: Judah, Kshitij
Abstract:: This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy learning algorithms o er teachers little flexibility in how policies are taught. In particular, one of two learning modes is typically considered: 1)...
Resource Type:: Dissertation

Multiagent learning for locomotion and coordination in tensegrity robotics

Creator:: Iscen, Atil
Abstract:: Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...
Resource Type:: Dissertation

The density signature

Creator:: Migler-VonDollen, Theresa
Abstract:: In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
Resource Type:: Dissertation

Incorporating and Learning Behavior Constraints for Sequential Decision Making

Creator:: Pinto, Jervis
Abstract:: Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
Resource Type:: Dissertation

Variational Typing and Its Applications

Creator:: Chen, Sheng
Abstract:: The study of variational typing originated from the problem of type inference for variational programs, which encode numerous different but related plain programs. In this dissertation, I present a sound and complete type inference algorithm for inferring types of all plain programs encoded in variational programs. The proposed algorithm runs...
Resource Type:: Dissertation

Predicting Aerodynamic Loads on Highly Flexible Membrane Wings

Creator:: Carpenter, Trenton James
Abstract:: Through passive adaptation to incidental flow, flexible aerodynamic surfaces exploit effects of increased lift, delayed stall and disturbance rejection. Wings of birds, bats, and insects exhibit these passive effects, and at the same time through the use of structural state feedback sensed from the loads on the wing, active control...
Resource Type:: Dissertation

Improving automated email tagging with implicit feedback

Creator:: Sorower, Mohammad Shahed
Abstract:: Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
Resource Type:: Dissertation

Nonuniform Sampling Of Band-limited Functions

Creator:: Al-Hammali, Hussain Y.
Abstract:: In this thesis, we will study certain generalizations of the classical Shannon Sampling Theorem, which allows for the reconstruction of a pi-band-limited, square-integrable function from its samples on the integers. J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which includes nonuniform and...
Resource Type:: Dissertation

Parsing with Recurrent Neural Networks

Creator:: Cross, James Henry, III
Abstract:: Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
Resource Type:: Dissertation

Object Tracking-by-Segmentation in Videos

Creator:: Chen, Sheng
Abstract:: This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
Resource Type:: Dissertation

Monte Carlo Tree Search with Fixed and Adaptive Abstractions

Creator:: Hostetler, Jesse A.
Abstract:: Monte Carlo tree search (MCTS) is a class of online planning algorithms for Markov decision processes (MDPs) and related models that has found success in challenging applications. In the online planning approach, the agent makes a decision in the current state by performing a limited forward search over possible futures...
Resource Type:: Dissertation

Structured learning with latent variables : theory and algorithms

Creator:: Zhao, Kai
Abstract:: Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
Resource Type:: Dissertation

Learning with Partial Supervision for Clustering and Classification

Creator:: Pei, Yuanli
Abstract:: 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...
Resource Type:: Dissertation

Weakly Supervised Learning for Activity Recognition from Time Series Data

Creator:: Guan, Xinze
Abstract:: The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...
Resource Type:: Dissertation

Simulator-Defined MDP Planning with Applications in Natural Resource Management

Creator:: Alkaee Taleghan, Majid
Abstract:: This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
Resource Type:: Dissertation

Reaction Pathways of Oxo-Hydroxo Group 5 Clusters to Metal Oxide Thin Films

Creator:: Mansergh, Ryan H.
Abstract:: Oxo-hydroxo Group 5 metal clusters are an untapped resource to study and advance aqueous solution processing of metal oxide thin films. The tetramethylammonium (TMA) hexatantalate salt (TMA6[H2Ta6O19]) yields dense Ta2O5 films (~95% of the bulk ß-Ta2O5 density) with atomically smooth surfaces (<4 Å root mean square surface roughness). This same...
Resource Type:: Dissertation

Adaptive Multiagent Traffic Management for Autonomous Robotic Systems

Creator:: Rebhuhn, Carrie
Abstract:: There is growing commercial interest in the use of unmanned aerial vehicles (UAVs) in urban environments, specifically for package delivery applications. However, the size, complexity and sheer numbers of expected UAVs makes conventional air traffic management that relies on human air traffic controllers infeasible. To enable UAVs to safely and...
Resource Type:: Dissertation

Machine learning methods for public policy : simulation, optimization, and visualization

Creator:: McGregor, Sean
Abstract:: Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
Resource Type:: Dissertation

Incorporating User Feedback into Machine Learning Systems

Creator:: Das, Shubhomoy
Abstract:: Although machine learning systems are often effective in real-world applications, there are situations in which they can be even better when provided with some degree of end user feedback. This is especially true when the machine learning system needs to customize itself to the end user's preferences, such as in...
Resource Type:: Dissertation

Automated decomposition of complex parts for manufacturing with advanced joining processes

Creator:: Massoni, Brandon R.
Abstract:: Recent advancements in joining operations and additive manufacturing now allow complex metal parts to be built up from raw materials, as opposed to being machined down from solid blocks. This not only opens up the design space, but also allows for much more efficient manufacturing. By decomposing a complex part...
Resource Type:: Dissertation

Approximation Schemes in Planar Graphs

Creator:: Zheng, Baigong
Abstract:: There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
Resource Type:: Dissertation

Anomaly Detection: Theory, Explanation and User Feedback

Creator:: Siddiqui, Md Amran
Abstract:: Anomaly detection has been used in variety of applications in practice, including cyber-security, fraud detection and detecting faults in safety critical systems, etc. Anomaly detectors produce a ranked list of statistical anomalies, which are typically examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, most...
Resource Type:: Dissertation

Representationally Robust and Scalable Learning over Relational Databases

Creator:: Picado Leiva, Jose Manuel
Abstract:: Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
Resource Type:: Dissertation

Learning with Limited Labeled Data in Natural Language Processing

Creator:: Obeidat, Rasha
Abstract:: 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...
Resource Type:: Dissertation

Conceptual Representations within the Social and Material Contexts of an Engineering Workplace and Academic Environments

Creator:: Barner, Matthew S.
Abstract:: Situated cognition theory emphasizes the role that social and material contexts have on learning and knowledge application. Several studies of engineering workplace environments have noted differences between the social and material contexts of the workplace and those of undergraduate engineering education. No existing research has studied the social and material...
Resource Type:: Dissertation

Computing Resource Usage as a Factor of Student Success

Creator:: Moissinac, Béatrice
Abstract:: Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
Resource Type:: Dissertation

Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

Creator:: Deng, Dezhong
Abstract:: Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
Resource Type:: Dissertation

Interpretable Machine Learning: Applications in Biology and Genomics

Creator:: Danaee, Padideh
Abstract:: Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
Resource Type:: Dissertation

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