University of Memphis

About: University of Memphis is a education organization based out in Memphis, Tennessee, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 7710 authors who have published 20082 publications receiving 611618 citations. The organization is also known as: U of M.

Automatic detection of learner's affect from conversational cues

Abstract: We explored the reliability of detecting a learner's affect from conversational features extracted from interactions with AutoTutor, an intelligent tutoring system (ITS) that helps students learn by holding a conversation in natural language. Training data were collected in a learning session with AutoTutor, after which the affective states of the learner were rated by the learner, a peer, and two trained judges. Inter-rater reliability scores indicated that the classifications of the trained judges were more reliable than the novice judges. Seven data sets that temporally integrated the affective judgments with the dialogue features of each learner were constructed. The first four datasets corresponded to the judgments of the learner, a peer, and two trained judges, while the remaining three data sets combined judgments of two or more raters. Multiple regression analyses confirmed the hypothesis that dialogue features could significantly predict the affective states of boredom, confusion, flow, and frustration. Machine learning experiments indicated that standard classifiers were moderately successful in discriminating the affective states of boredom, confusion, flow, frustration, and neutral, yielding a peak accuracy of 42% with neutral (chance = 20%) and 54% without neutral (chance = 25%). Individual detections of boredom, confusion, flow, and frustration, when contrasted with neutral affect, had maximum accuracies of 69, 68, 71, and 78%, respectively (chance = 50%). The classifiers that operated on the emotion judgments of the trained judges and combined models outperformed those based on judgments of the novices (i.e., the self and peer). Follow-up classification analyses that assessed the degree to which machine-generated affect labels correlated with affect judgments provided by humans revealed that human-machine agreement was on par with novice judges (self and peer) but quantitatively lower than trained judges. We discuss the prospects of extending AutoTutor into an affect-sensing ITS.

Resolving inconsistencies in trends in old-age disability: Report from a technical working group

Abstract: In September 2002, a technical working group met to resolve previously published inconsistencies across national surveys in trends in activity limitations among the older population. The 12-person panel prepared estimates from five national data sets and investigated methodological sources of the inconsistencies among the population aged 70 and older from the early 1980s to 2001. Although the evidence was mixed for the 1980s and it is difficult to pinpoint when in the 1990s the decline began, during the mid- and late 1990s, the panel found consistent declines on the order of 1%-2.5% per year for two commonly used measures in the disability literature: difficulty with daily activities and help with daily activities. Mixed evidence was found for a third measure: the use of help or equipment with daily activities. The panel also found agreement across surveys that the proportion of older persons who receive help with bathing has declined at the same time as the proportion who use only equipment (but not personal care) to bathe has increased. In comparing findings across surveys, the panel found that the period, definition of disability, treatment of the institutionalized population, and age standardizing of results were important to consider. The implications of the findings for policy, national survey efforts, and further research are discussed.

The impact of religious fasting on human health

Abstract: The past two decades have seen a rise in the number of investigations examining the health-related effects of religiously motivated fasts. Islamic Ramadan is a 28 - 30 day fast in which food and drink are prohibited during the daylight hours. The majority of health-specific findings related to Ramadan fasting are mixed. The likely causes for these heterogeneous findings are the differences between studies in the following: 1) the amount of daily fasting time; 2) the percentage of subjects who smoke, take oral medications, and/or receive intravenous fluids; and 3) the subjects' typical food choices and eating habits. Greek Orthodox Christians fast for a total of 180 - 200 days each year, and their main fasting periods are the Nativity Fast (40 days prior to Christmas), Lent (48 days prior to Easter), and the Assumption (15 days in August). The fasting periods are more similar than dissimilar, and they can each be described as a variant of vegetarianism. Some of the more favorable effects of these fasts include the lowering of body mass, total cholesterol, LDL-C, and the LDL-C/HDL-C ratio. The Biblical-based Daniel Fast prohibits the consumption of animal products, refined carbohydrates, food additives, preservatives, sweeteners, flavorings, caffeine, and alcohol. It is most commonly partaken for 21 days, although fasts of 10 and 40 days have been observed. Our initial investigation of the Daniel Fast noted favorable effects on several health-related outcomes, including: blood pressure, blood lipids, insulin sensitivity, and biomarkers of oxidative stress. This review summarizes the health-specific effects of these fasts and provides suggestions for future research.