The field of radio broadcast requires the cohesion of several different skill sets in order to be a success. KHEA Radio has used a traditional form of teaching, which means taking a one-on-one approach. Taking this approach has worked for years in the past and has been the only option for teaching. The down side to this method of teaching is that it requires one seasoned employee to stop their work and take the time to train a new employee. Because of the significant void in the area of instructional content for radio sound engineering, my co-worker and I had to troubleshoot this console and basically teach ourselves its functions. I saw the need for better instructional content on the Internet and in print based on my own experiences. The skills used to create the following instructional content were gained from course work at Arizona State University. The graduate department of Technical Communication makes every effort to equip students with varied skills that can be applied to different fields within the overall scheme of technical communication. This guide serves as a tool for radio broadcast novices to learn the basics of sound board operation.

YourBrandPartner.com exists to provide content to those seeking specific advice and information on purchasing custom promotional items. For this investigation, I conducted a usability test with a select user group to identify user experience issues. The primary goal of this research was to conduct general usability testing through large group survey and a small in-person usability testing group. I designed surveys and tests to investigate if users experienced difficulties in finding the information they were looking for on the website. Based on the results of this study, I recommend reviewing the visual design of the website, increasing site speed, creating a better experience between the blog and e- commerce interactions, and creating an environment that is more accommodating of where the user is in the buying process. This full report includes expanded participant feedback, methodology behind the study, and full recommendations for improvement.

The purpose of this applied project was to research and recommend to Phoenix Children’s Hospital (PCH) improvements to their website in order to provide parents whose child has been newly diagnosed with cancer the most clear and appropriate health information. I conducted a study in order to analyze and evaluate the health information content currently provided to parents at PCH. This was done by through qualitative coding methods on both printed documents provided by The Emily Center Library, as well as interviews conducted with three Hematology/Oncology nurses at PCH. Additionally, I researched the current literature surrounding this topic in order to provide a background of information. Based on the results, I recommended that PCH offer parents a comprehensive cancer database in which all provided information would be searchable via their website. This database would also allow them to expand on their two topic focuses: home care and emotional support. Additionally, I recommended that parents are provided information on how to identify credible and non- credible sources on the Internet so that they can find information that is truly medically valuable when searching for information on their own. Lastly, I offered future recommendations that will require continued research so that PCH’s provided health information can continue to grow and improve.

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does not speak to how animals make<br/>decisions that tend to be adaptive. Using simulation studies, prior work has shown empirically<br/>that a simple decision-making heuristic tends to produce prey-choice behaviors that, on <br/>average, match the predicted behaviors of optimal foraging theory. That heuristic chooses<br/>to spend time processing an encountered prey item if that prey item's marginal rate of<br/>caloric gain (in calories per unit of processing time) is greater than the forager's<br/>current long-term rate of accumulated caloric gain (in calories per unit of total searching<br/>and processing time). Although this heuristic may seem intuitive, a rigorous mathematical<br/>argument for why it tends to produce the theorized optimal foraging theory behavior has<br/>not been developed. In this thesis, an analytical argument is given for why this<br/>simple decision-making heuristic is expected to realize the optimal performance<br/>predicted by optimal foraging theory. This theoretical guarantee not only provides support<br/>for why such a heuristic might be favored by natural selection, but it also provides<br/>support for why such a heuristic might a reliable tool for decision-making in autonomous<br/>engineered agents moving through theatres of uncertain rewards. Ultimately, this simple<br/>decision-making heuristic may provide a recipe for reinforcement learning in small robots<br/>with little computational capabilities.

Robots are often used in long-duration scenarios, such as on the surface of Mars,where they may need to adapt to environmental changes. Typically, robots have been built specifically for single tasks, such as moving boxes in a warehouse or surveying construction sites. However, there is a modern trend away from human hand-engineering and toward robot learning. To this end, the ideal robot is not engineered,but automatically designed for a specific task. This thesis focuses on robots which learn path-planning algorithms for specific environments. Learning is accomplished via genetic programming. Path-planners are represented as Python code, which is optimized via Pareto evolution. These planners are encouraged to explore curiously and efficiently. This research asks the questions: “How can robots exhibit life-long learning where they adapt to changing environments in a robust way?”, and “How can robots learn to be curious?”.

Enantiomers are pairs of non-superimposable mirror-image molecules. One molecule in the pair is the clockwise version (+) while the other is the counterclockwise version (-). Some pairs have divergent odor qualities, e.g. L-carvone (“spearmint”) vs. D-carvone (“caraway”), while other pairs do not. Existing theory about the origin of such differences is largely qualitative (Friedman and Miller, 1971; Bentley, 2006; Brookes et al., 2008). While quantitative models based on intrinsic molecular features predict some structure–odor relationships (Keller et al., 2017), they cannot identify, e.g. the more intense enantiomer in a pair; the mathematical operations underlying such features are invariant under symmetry (Shadmany et al., 2018). Only the olfactory receptor (OR) can break this symmetry because each molecule within an enantiomeric pair will have a different binding configuration with a receptor. However, features that predict odor divergence within a pair may be identifiable; for example, six-membered ring flexibility has been offered as a candidate (Brookes et al., 2008). To address this problem, we collected detection threshold data for >400 molecules (organized into enantiomeric pairs) from a variety of public data sources and academic literature. From each pair, we computed the within-pair divergence in odor detection threshold, as well as Mordred descriptors (molecular features derived from the structure of a molecule) and Morgan fingerprints (mathematical representations of molecule structure). While these molecular features are identical within-pair (due to symmetry), they remain distinct across pairs. The resulting structure+perception dataset was used to build a predictive model of odor detection threshold divergence. It predicted a modest fraction of variance in odor detection threshold divergence (r 2 ~ 0.3 in cross-validation). We speculate that most of the remaining variance could be explained by a better understanding of the ligand-receptor binding process.