Interfacing Agents with Natural Language

Technology is leading us to a world where computers are everywhere. A new breed of machines capable of sensing and reacting to stimuli in the real world is under development. Unfortunately, these new, powerful devices can oftentimes be difficult for the average person to understand. It is imperative that an easy to use interface be implemented to usher in this new world. Natural language (speech) would be an ideal solution. However, it has proven implausible on a large scale. A Menu-Based Natural Language Interface (MBNLI) could retain the intuitiveness of speech, while eliminating the obstacles impeding implementation. This research paper describes the development and applications of a MBNLI

Doctor of Philosophy

dissertationSystematic differences in functional connectivity magnetic resonance imaging metrics have been consistently observed in autism. I attempted to predict group membership using data provided by the Autism Brain Imaging Data Exchange, including resting state functional magnetic resonance imaging data obtained from 964 subjects and 16 separate international sites. For each of 964 subjects, I obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter and attempted to classify the subjects using a leave-one-out classifier with the 26.4 million connections as features. Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification. Classification accuracy was significantly higher for sites with longer blood oxygen-level dependent imaging times. Attempts to use multisite classifiers will likely require improved classification algorithms, longer blood oxygen-level dependent imaging times, and standardized acquisition parameters for possible future clinical utility. Lateralization of brain structure and function occurs in typical development and subserves functions such as language and visuospatial processing. Abnormal lateralization is present in various neuropsychiatric disorders. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such iv phenotypic differences in the strength of left-dominant or right-dominant networks exist. I evaluated whether strongly lateralized connections covaried within the same typically developing individuals (n = 1011). I also compared lateralization of functional connections in typical development and in autism. In typical development, left- and rightlateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "rightbrained" network strength across individuals. The autism group lacked left lateralization in three connections involving language regions and regions from the default mode network. Abnormal language lateralization in autism may be due to abnormal language development rather than a deficit in hemispheric specialization of the entire brain

STRUCTURAL MICROMETEOROID AND RADIATION SHIELDING FOR INTERPLANETARY SPACECRAFT

This paper focused on two significant space forces that can affect the success of a spacecraft: the radiation and micrometeoroid environments. Both are looked at in the context of the region of space between Earth and Mars. The goal was create reference environments, to provide context to results of environmental modeling, and to provide recommendations to assist in early design decisions of interplanetary spacecraft. The radiation section of this report used NASA\u27s OLTARIS program to generate data for analysis. The area of focus was on the radiation effects for crewed missions, therefore effective dose equivalent was the metric used to compare different models of radiation and shielding. Test spheres with one, two, or three different materials layers were compared, along with modifiers such as alloys or weight vs. thickness emphasis. Results were compared to limits set by the European and Russian Space Agencies to provide context. The results hinged heavily on the intensity of the Solar Particle Events (SPEs), with testing using additional temporary radiation shielding proving to be a requirement for feasible shielding masses. Differences in shield material effectiveness were found to be negligible for thin Galactic Cosmic Rays (GCRs) and thick SPEs. Thick shields were found to perform better when the more efficient shield was on the outside of the test sphere. The micrometeoroid section used equations and programs from multiple sources to generate state vectors, flux, and finally impact models for four different case studies. Impacts v were generated with mass, velocity, and impact angle/location statistics. The mass and velocity results were run through statistical software to generate information such as mean and standard deviation with confidence intervals. Also looked at were higher mass impacts, limited to above 10-3 grams as opposed to above 10-6 for the regular case. The results of this show that very thin monolithic shields (0.1 cm-0.25 cm) could protect against the average 10-6 impact. The Ram, Nadir, and Anti-sun faces received the highest quantity of impacts and Wake received the least. When looking at the worst cases average mass and velocity for the high mass impacts significantly higher shielding was required to prevent penetration (up to 5 cm for some cases). However, the test cases had probabilities of no high mass impacts greater than 46% of the time, with shorter mission having greater chances of no high mass impacts

Determining South Mississippi forest susceptibility to windthrow and shear damage in a hurricane environment through data mining of meteorological, physiographical, pedological, and tree level data

An estimated 39 million m3 of timber was damaged across the Southeast Forest District of Mississippi due to Hurricane Katrina. Aggregated forest plot-level biometrics was coupled with wind, topographical, and soil attributes using a GIS. Data mining through Regression Tree Analysis (RTA) was used to determine factors contributing to shear damage of pines and wind-throw damage of hardwoods. Results depict Lorey’s Mean Height (LMH) and Quadratic Mean Diameter (QMD) are important variables in determining the percentage of trees and basal area damaged for both forest classes with sustained wind speed important for wind-throw and peak wind gusts for shear. Logistic regression based on stand damage classification compared to RTA revealed LMH, stand height to diameter ratio, and sustained wind variable concurrence. Reclassification of MIFI plot damage calls based on percentage of trees damaged increased predictability of wind-throw and shear classification. This research can potentially aid emergency and forest managers for better mitigation and recovery decisions following a hurricane

Student Perceptions of Institutional Crisis Management, Preparedness, and Response: The Case of the Active Shooter

Institutional crisis management is becoming more relevant with every passing tragedy and crisis event. This study utilized a modified existing survey to collect quantitative data from students attending a large four-year public research institution located in the Southeastern region of the United States. A stratified random sample of commuter students and non-commuter students was analyzed to compare statistical similarities and differences between the groups. The largest group of student respondents were full-time, freshmen, female, involved, and currently live on campus. Students perceived their institutions to be moderately prepared to respond to both general crises and active shooting situations, although a majority of students did not know if written institutional plans were in place. Students perceived active shooter protocol communication as less effective than communication of general crisis management protocol. Students are generally satisfied with the text messages and emails used to notify students during a crisis situation, but there are other communication mediums they also believed would be effective. Analyzing data on students’ perceptions of their respective institutional crisis management, preparedness, and response helps establish sound practices for extending protection to the campus community from immediate threats during a campus crisis. While there are numerous campus crises and forms of preparedness, this study focused on active shootings as the crisis and emergency notification systems (ENS) as the response

Studies of Reaction Processes for Voloxidation Methods

Various facets of the voloxidation process and processes that have been derived from the voloxidation process have been investigated since its development over four decades ago. Despite the numerous studies performed, gaps remain in understanding of particular fundamental aspects of the reaction processes. In this work, several of these specific aspects of the oxidation processes for standard voloxidation and NO2 [nitrogen dioxide] voloxidation are studied experimentally and modeled. In the case of standard voloxidation, the oxidation rates of simulant UO­2 [uranium dioxide] pressurized water reactor pellets in oxygen-rich environments were studied with an emphasis on the controlling phenomena for the reaction and the influence of cladding on these phenomena. Parametric isolation experiments for the oxidation of UO2 pellets using thermogravimetric analysis were employed in which oxidant concentration, temperature, gas flow rate, and effect of cladding were studied. To supplement the thermogravimetric experiments, the reaction interface was characterized using neutron diffraction to validate assumptions for model development. From these experiments, a model approach is derived for the oxidation of clad UO2 pellets during voloxidation. This work provides needed insight into the influence of various parameters on oxidation rate and reveals the potential controlling phenomena and their parameter dependencies to allow for improved process design. Advanced NO2 voloxidation, unlike standard voloxidation, is a novel process only recently proposed and thus there is much to investigate. The NO2 voloxidation experiments and reaction models presented focus on the oxidation process of U3O8 [triuranium octoxide] to UO3 [uranium trioxide]. A structure for the ε [epsilon]-UO3 polymorph is proposed and employed for in situ X-ray diffraction studies for quantitative analysis to determine reaction rates and reaction mechanism. The data collected were modeled using a phenomena-based approach to propose the controlling mechanism for reaction. From the findings of the research presented, a better understanding of the oxidation process of U3O8 to UO3 by NO2 was achieved

Comparison of DC and SRF Photoemission Guns For High Brightness High Average Current Beam Production

A comparison of the two most prominent electron sources of high average current high brightness electron beams, DC and superconducting RF photoemission guns, is carried out using a large-scale multivariate genetic optimizer interfaced with space charge simulation codes. The gun geometry for each case is varied concurrently with laser pulse shape and parameters of the downstream beamline elements of the photoinjector to obtain minimum emittance as a function of bunch charge. Realistic constraints are imposed on maximum field values for the two gun types. The SRF and DC gun emittances and beam envelopes are compared for various values of photocathode thermal emittance. The performance of the two systems is found to be largely comparable provided low intrinsic emittance photocathodes can be employed

Effect of distillers dried grains with solubles and a feed additive containing essential oils on performance of wean-to-finish pigs

Two studies were conducted to evaluate the effect of distillers dried grains with solubles (DDGS) and a feed additive containing essential oils on growth performance of wean-to-finish and nursery pigs. Feed disappearance and BW were recorded to calculate ADG, ADFI, and G:F ratio. One study was performed to test the effect of high levels of DDGS and high levels of DDGS plus essential oils on wean-to-finish pigs growth performance. High DDGS levels significantly decrease G:F ratio when compared to control overall. Pigs fed high DDGS + essential oils had a tendency to improve BW at d 42 of the study and G:F from d 0-42 compared to control. The same group of pigs fed high DDGS + essential oils had a significant improvement in overall G:F compared to those fed high DDGS. Upon completion of the study carcass data was collected from the pigs utilized in the study. There were no differences observed among dietary treatments live weight, HCW, percent yield and BF. However, there was a tendency for LD and percent lean to decrease in pigs fed high DDGS dietary treatment compared to those fed control. Additionally, pigs fed high DDGS + essential oils compared to pigs fed high DDGS tended to increase LD. Another study was conducted to evaluate the effect of essential oils on nursery pigs growth performance. There was no effect on nursery pigs growth performance from d 0-41. Similarly, no effect on growth performance was observed from d 14-41 when essential oils were added to nursery pigs diets in this study. In summary, high DDGS alone in wean-to-finish diets significantly decreased G:F, while there was tendency to decrease both LD and percent lean compared to control. The addition of essential oils to high DDGS containing diets significantly improved G:F and tended to improve loin depth in wean-to-finish pigs compared to high DDGS. High DDGS + essential oils tended to improve d 42 average weight and d 0-42 G:F vs control. However, in the study conducted looking at the effect of essential oils in standard nursery diets, no effects were observed

Examining Communication and Patient Recall in a Family Medicine Residency

Background. Understanding key aspects of effective physician-patient communication could benefit residency education and improve patient comprehension of health information. Discrepancies between what physicians say and what patients understand can reduce quality of care (e.g., patient adherence and satisfaction), making it imperative to know when gaps in patient understanding exist. The objective of this study was to identify residents’ efforts to assess patient understanding and the degree to which patients recalled information and instructions provided in the medical encounter. Methods. Residents and patients were observed in routine medical encounters in a Midwestern family medicine residency center. Patients were surveyed immediately following the encounter for recall of information and recommendations from the encounter, satisfaction with physician communication, and health literacy. Results. A total of 21 physician-patient encounters were observed. An inverse relationship was noted (Spearman’s rho = -0.43, N = 21, p = 0.05) between number of topics discussed during the encounter and the percentage of information recalled. Conclusions. Patient recall was related inversely to the number of topics covered by resident physicians. These results challenge physicians and medical educators to study and employ further those elements of physician-patient communication that enhance patient recall and understanding

Inferring gene regulatory networks from asynchronous microarray data with AIRnet

Background Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time series microarray data to infer gene signaling networks given a large number of accurate time series samples. Microarray data available for many biological experiments is limited to a small number of arrays with little or no time series guarantees. When several samples are averaged to examine differences in mean value between a diseased and normal state, information from individual samples that could indicate a gene relationship can be lost. Results Asynchronous Inference of Regulatory Networks (AIRnet) provides gene signaling network inference using more practical assumptions about the microarray data. By learning correlation patterns for the changes in microarray values from all pairs of samples, accurate network reconstructions can be performed with data that is normally available in microarray experiments. Conclusions By focussing on the changes between microarray samples, instead of absolute values, increased information can be gleaned from expression data