Master of Science

thesisTechnological innovations have increased the ability to collect and store information. However, these innovations potentially create a psychological problem because the increasing amounts of information must be managed within the still limited human cognitive processing capacity. One common data visualization approach to improve information search is the concept of increased bottom-up stimulus-driven saliency to guide the user. But is increasing the salience of an item enough to produce a sufficient, efficient search with high decision accuracy? How does increasing the salience of an item without regard to its relevance affect the search for information? Is there a difference between lists and tag clouds and what role does the system context; play? To answer these questions we adapted the concepts of the Wason selection task (WST) and considered the propositional logic values of P, Q, not P and not Q, to analyze search sufficiency, efficiency, decision accuracy and search patterns. We found that the incongruence or congruence of salience and relevance can impede or support the search for information. However, increasing the salience of relevant items is not enough to insure a sufficient or efficient search with an accurate decision. The search for information is affected by interactions between the display format, the system context; and the congruence conditions

Doctor of Philosophy

dissertationThe present study explored data presentation and human cognition with the objective of improving electronic Decision Support Systems (DSS). Computers have been used as tools for decision support for over 60 years, with the intent to supplement or replace human cognition. However, electronic computing has failed to reliably replace human cognition in complex domains. The suboptimal properties of the data and complexities of the domain often require human interpretation and intervention. Human interpretation relies on experience, values, intuition, insight and learning; which can lead to shortcuts or heuristics. Heuristics in the correct context can be economical and effective in solving many problems. When heuristics fail the results are labeled as cognitive biases or errors. Biases all share the elements of structuring incorrect or inappropriate models or hypotheses and/or insufficient consideration of the data. Most biases can be linked to confirmation bias - which is manifested by searches for and consideration of only confirming data. De-biasing techniques share the concept of shifting cognitive processing from an automatic associative mode to a more deliberate, conscious rule-based mode. This study used a modified Wason 2-4-6 task that combined methods of, 1) increased salience through data visualization with 2) appealing to the rule-based system through task instructions. The results indicate that neither increased salience nor instructions ensure increased search sufficiency, efficiency or decision accuracy. However, this study provides insight into the perceived value of evidence and iv four potential limitations related to self-directed searches: 1) The selection of necessary disconfirming evidence cannot be assumed, regardless of the perceived value of disconfirming evidence. 2) The selection of sufficient evidence does not ensure accuracy; however, 3) insufficient selection of disconfirming evidence results in lower accuracy. 4) Ambiguous evidence is considered more valuable than potentially disconfirming evidence. Implications for the design of decision support systems are presented along with limitations and directions for future research

Does the shoe fit? Applying lessons learned in aviation to healthcare

pre-printAviation's successful use of Decision Support Systems (DSS) has not been replicated in the healthcare subset of DSS referenced as Clinical Decision Support (CDS). Here the domains of healthcare and aviation are compared and contrasted providing an overview of the adaptation of lessons learned in aviation to healthcare. We propose there are differences in characteristics inherent to the contexts of aviation and healthcare that affect the data necessary for efficient, effective CDS systems. Specifically, ten context characteristics are discussed that jointly and separately affect the availability, quantity, quality and temporal relevance of the data. By providing remedies for overcoming deficiencies and supporting accurate representation of the data perhaps then CDS systems will meet their potential for improved adoption, user satisfaction and patient outcomes

COMPARISON BETWEEN GROUND REACTION FORCE PATTERNS AND ANGULAR, APPROACH, AND BALL VELOCITIES FOR IN-STEP KICKING

The purpose of this study was to determine if patterns in vertical ground reaction forces resulted in differences in hip, knee and trunk angular velocity and efficiency of the open kinetic chain. 20 subjects performed a maximal in-step kick while ground reaction forces of the plant leg, as well as angular, approach and ball velocities were recorded. Although approach and ball velocity did not change between groups, the decreasing vertical force group had significantly higher initial peak vertical ground reaction forces and angular hip velocities than subjects with a double vertical peak pattern. There was a significant relationship between approach velocity and ball velocity, as well as a negative relationship between posterior lean on contact and leg angular velocity. It seems that the pattern of vertical force with the plant leg is not a key factor in ball velocity

Measuring the Effect of E-Learning on Job Performance

E-learning is becoming a leading delivery method in workplace-learning settings across organizations of various sectors and of varying sizes. The ultimate goal is to drive business results. Managers need to provide evidence of a positive impact on corporate strategy and investment objectives. If the business goal cannot be identified, there should be a query on why it is there in the first place. Transfer of the knowledge learned in the training session to the work situation is not built into most skills training delivery, especially those provided through e-learning. The outcomes and the effects of training on job performance are not measured because no method currently exists for credible evaluation. This problem exists across the Information Technology (IT) industry. Constant IT innovation makes technical competencies a fundamental requirement and continuous IT skills training a necessity. The trainee may have acquired the appropriate new skill, but the work environment to which the employee returns may make practicing what was learned counterproductive. The goal of the dissertation was to produce a valid and reliable instrument to measure the alignment of IT e-learning with corporate and departmental strategies. The instrument will be valuable to industries with IT departments. The methodology for this study followed the Kirkpatrick Model, specifically Level 3, an evaluation that measures behavioral change on the job. The evaluation included specific application of the special knowledge or skills learned in the training. IT employees were surveyed after the completion of an online training class. The results indicated the frequency and effectiveness of the on-the-job application. In addition, open-ended questions provided feedback on the survey instrument and the training. Utilized by corporations, the balanced scorecard approach was followed to track the argument of online training with organizational goals. This approach includes a method to develop a measure such as strategy maps that depict overall organization strategic themes to improve the link between training and corporate strategy

Bio-optical discrimination of diatoms from other phytoplankton in the surface ocean: Evaluation and refinement of a model for the Northwest Atlantic

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing of Environment 217 (2018): 126-143, doi:10.1016/j.rse.2018.08.010.Diatoms dominate global silica production and export production in the ocean; they form the base of productive food webs and fisheries. Thus, a remote sensing algorithm to identify diatoms has great potential to describe ecological and biogeochemical trends and fluctuations in the surface ocean. Despite the importance of detecting diatoms from remote sensing and the demand for reliable methods of diatom identification, there has not been a systematic evaluation of algorithms that are being applied to this end. The efficacy of these models remains difficult to constrain in part due to limited datasets for validation. In this study, we test a bio-optical algorithm developed by Sathyendranath et al. (2004) to identify diatom dominance from the relationship between ratios of remote sensing reflectance and chlorophyll concentration. We evaluate and refine the original model with data collected at the Martha's Vineyard Coastal Observatory (MVCO), a near-shore location on the New England shelf. We then validated the refined model with data collected in Harpswell Sound, Maine, a site with greater optical complexity than MVCO. At both sites, despite relatively large changes in diatom fraction (0.8–82% of chlorophyll concentration), the magnitude of variability in optical properties due to the dominance or non-dominance of diatoms is less than the variability induced by other absorbing and scattering constituents of the water. While the original model performance was improved through successive re-parameterizations and re-formulations of the absorption and backscattering coefficients, we show that even a model originally parameterized for the Northwest Atlantic and re-parameterized for sites such as MVCO and Harpswell Sound performs poorly in discriminating diatom-dominance from optical properties.This work was supported by: a Woods Hole Oceanographic Institution Summer Student Fellowship (NSF REU award #1156952) and a Bowdoin College Grua/O'Connell Research Award to SJK; grants to HMS from NASA (Ocean Biology and Biogeochemistry program and Biodiversity and Ecological Forecasting program), NSF (Ocean Sciences), the Gordon and Betty Moore Foundation, the Simons Foundation, and NOAA through the Cooperative Institute for the North Atlantic Region (CINAR) under Cooperative Agreement NA14OAR4320158; and grants to CSR from NASA (Ocean Biology and Biogeochemistry program)

Fast and accurate prediction of positive and negative urine cultures by flow cytometry

Background: Urinary tract infection (UTI) is a widespread infectious disease in humans. Urine culture, a huge workload in the microbiology laboratory, is still the standard diagnostic test for UTI, but most of the cultures are negative. A reliable screening method could reduce unnecessary cultures and quicken reporting of negative results. Methods: We evaluated the usefulness of a flow cytometry (FC) screening method in the prediction of positive urine culture to reduce the number of urine cultures. The urine specimens sent to the laboratory for culture were tested with the flow cytometer Accuri C6. FC bacterial counts were compared to standard urine culture results to assess the best cut-off values. Results: Two hundred nine urine samples were included, of which 79 (37.8 %) were culture positive. On comparing the culture and the FC data in the ROC curve, the FC bacterial counts of >= 10(6) bacteria/mL provided a reliable screening for bacteriuria with a sensitivity and specificity of 99 and 58 %, respectively. All negative FC results (<106 bacteria/mL) showed a negative predictive value of 99 % with a negative likelihood ratio of 0.02. The FC bacterial counts of >= 10(8)/mL showed a positive predictive value of 99 % with a positive likelihood ratio of 60.9. Conclusions: Counting bacteria in human urine samples by the FC is a fast, accurate and cost-effective screening method for bacteriuria. Our results showed that FC is able to rule out UTI, which can lead to a substantial reduction (36 %) of urine cultures. It also demonstrated that this method predicts positive cultures accurately

Ecologic Factors Associated with West Nile Virus Transmission, Northeastern United States

Risk for disease was 4 times greater in the least forested counties

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time

Variation in Vector Competence for Dengue Viruses Does Not Depend on Mosquito Midgut Binding Affinity

Several factors, such as mosquito and virus genetics and environmental variables, determine the ability of mosquitoes to transmit dengue viruses. In this report, we describe new and important information that in some ways contradicts what is in the literature. Midgut infection barriers have been described as important determinants of virus transmission in mosquitoes but we found that virus binding to these midgut cells does not vary. When we compared binding of 8 different, low passage dengue viruses to mosquito midguts that were dissected out of Aedes aegypti mosquitoes (the main vectors of dengue) from Mexico and Texas, we found that there were no differences. Previously, we (and others) had shown that these same viruses differed significantly in replication and dissemination throughout the rest of the mosquito body, including the salivary glands, and therefore they differed greatly in their potential to be transmitted to humans. Thus, the data presented here are important considerations for future studies of vector competence and in determining strategies for control of dengue viruses in the vector