Computational Approaches to Exploring Persian-Accented English

Methods involving phonetic speech recognition are discussed for detecting Persian-accented English. These methods offer promise for both the identification and mitigation of L2 pronunciation errors. Pronunciation errors, both segmental and suprasegmental, particular to Persian speakers of English are discussed

Leading Digit Laws on Linear Lie Groups

We determine the leading digit laws for the matrix components of a linear Lie group $G$. These laws generalize the observations that the normalized Haar measure of the Lie group $\mathbb{R}^+$ is $dx/x$ and that the scale invariance of $dx/x$ implies the distribution of the digits follow Benford's law, which is the probability of observing a significand base $B$ of at most $s$ is $\log_B(s)$; thus the first digit is $d$ with probability $\log_B(1 + 1/d)$). Viewing this scale invariance as left invariance of Haar measure, we determine the power laws in significands from one matrix component of various such $G$. We also determine the leading digit distribution of a fixed number of components of a unit sphere, and find periodic behavior when the dimension of the sphere tends to infinity in a certain progression.Comment: Version 1.0, 17 pages, 1 figur

An International Comparison of the Effects of Government Agricultural Support on Food Budget Shares

This study evaluates econometrically the effect of government support to agriculture on a measure of the affordability of food in 10 Organization for Economic Cooperation and Development (OECD) countries. The panel model we construct specifically utilizes two values calculated by the OECD: Producer Support Estimates as a percentage of gross farm receipts and the Consumer Nominal Protection Coefficient. These two variables represent transfers from taxpayers to agricultural producers through government programs and transfers from consumers to government through protectionist measures, respectively. By using dummy variables, we find implications for groups of countries on the basis of their relative levels of support and protection.agricultural policy, obesity, Agribusiness, Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety, I18, Q18,

Incentives Matter: Assessing Biofuel Policies in the South

As a result of the increase in the real cost of fossil fuel-based energy in recent years, federal and state governments have taken a more active role in energy policy by creating incentives to develop alternative sources of energy, including biofuels. However, policymakers often become focused on the specific type of energy and not the energy services consumers ultimately value. The lack of recognition of energy as a commodity results in policies that ignore the characteristics of the associated markets: easy entry and exit, no barriers to entry, and sensitivity to changes in supply and demand. Consequently, energy industries may fail to arise because entrepreneurs must be able to account for all costs and earn—at a minimum—a competitive return on the investment. This article evaluates the options available to policymakers related to biofuels, which are of particular concern to the South, and includes an assessment of the knowledge base on which policy decisions are made.alternative energy, biofuels, energy policy, Resource /Energy Economics and Policy, Q41, Q42, Q48,

INVESTIGATING CHILD FEEDING IN A VIRTUAL REALITY BUFFET

Master of Public HealthPublic Health Interdepartmental ProgramTandalayo KiddIn partial fulfillment of the Masters of Public Health (MPH) degree, I completed my field experience in the Social and Behavioral Research Branch (SBRB) at the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in Bethesda, Maryland from June 5th 2017 through August 11th 2017. The NIH is a federal government agency which serves as the nation’s primary resource for biomedical and public health research that improves health and save lives. NHGRI is one of twenty-seven institutes at the NIH. NHGRI’s mission is to encompass a broad range of studies aimed at understanding the structure and function of the human genome and its role in health and disease. The branch I specifically worked in was SBRB, which conducts a broad array of research in applying new genomic discovery to improve health and clinical care. During my time at NHGRI, I was able to use my skills attained from the Masters of Public Health program at Kansas State University to advance the progress of ongoing projects as well as increase my knowledge and skills in areas outside of obesity research, such as diabetes related-stigma and virtual reality child feeding measures. For my experience, I worked with Dr. Susan J. Persky; a senior investigator in SBRB. Throughout my time at SBRB, I was tasked to work on a variety of ongoing projects which will assist with future research. Tasks included implementing coding systems to transform observed dietary behavior into quantitative variables, data coding, creating future study materials and presenting research findings at NIH poster day

The Cultural Adaptation of Internet Dating: Attitudes towards Online Relationship Formation

This study explores the social approval of internet dating through the ranking of vignette scenarios. The scenarios are manipulated by the conditions of face-to-face interaction, presence of mutual acquaintance, and use of internet technology. Measures of legitimacy, predicted longevity, and social perception test for changes in attitudes of the varied ways in which a hypothetical couple meets. One of seven randomly distributed scenarios was ranked by a total of 346 undergraduates to disentangle the above conditions and test for an effect on social approval. Situated in the framework of cultural adaptation, script theory and the saturated self, support is found for low cultural approval of internet dating. Conditions of face-to-face interaction, issues of trust, and affinity to the internet demonstrate clear effects on the approval of relationships formed through internet dating

Intelligent Feature Selection Techniques for Pattern Classification of Time-Domain Signals

Time-domain signals form the basis of analysis for a variety of applications, including those involving variable conditions or physical changes that result in degraded signal quality. Typical approaches to signal analysis fail under these conditions, as these types of changes often lie outside the scope of the domain\u27s basic analytic theory and are too complex for modeling. Sophisticated signal processing techniques are required as a result. In this work, we develop a robust signal analysis technique that is suitable for a wide variety of time-domain signal analysis applications. Statistical pattern classification routines are applied to problems of interest involving a physical change in the domain of the problem that translate into changes in the signal characteristics. The basis of this technique involves a signal transformation known as the Dynamic Wavelet Fingerprint, used to generate a feature space in addition to features related to the physical domain of the individual application. Feature selection techniques are explored that incorporate the context of the problem into the feature space reduction in an attempt to identify optimal representations of these data sets