Highly mobile computing devices promise to improve quality of life, productivity, and performance. Increased situation awareness and reduced mental workload are two potential means by which this can be accomplished. However, it is difficult to measure these concepts in the ‘wild’. We employed an ultra-portable battery operated and wireless functional near infrared spectroscopy (fNIRS) to non-invasively measure hemodynamic changes in the brain’s prefrontal cortex. Measurements were taken during navigation of a college campus with either a hand-held display, or an augmented (...) reality wearable display. Hemodynamic measures were also paired with secondary tasks of visual perception and auditory working memory to provide behavioral assessment of situation awareness and mental workload. Navigating with an augmented reality wearable display produced the least workload during both secondary tasks. The hemodynamics associated with errors were also different between the two devices. Errors with an augmented reality wearable display were associated with increased prefrontal activity and the opposite was observed for the hand-held display. This suggests that the cognitive mechanisms underlying errors between the two devices differ. These findings show fNIRS is a valuable tool for assessing new technology in ecologically valid settings and that head-mounted displays offer benefits with regards to mental workload while navigating, and potentially superior situation awareness with improved display design. (shrink)

There are a number of key data-centric questions that must be answered when developing classifiers for operator functional states. “Should a supervised or unsupervised learning approach be used? What degree of labeling and transformation must be performed on the data? What are the trade-offs between algorithm flexibility and model interpretability, as generally these features are at odds?” Here, we focus exclusively on the labeling of cognitive load data for supervised learning. We explored three methods of labeling cognitive states for three-state (...) classification. The first method labels states derived from a tertiary split of trial difficulty during a spatial memory task. The second method was more adaptive; it employed a mixed-effects stress–strain curve and estimated an individual’s performance asymptotes with respect to the same spatial memory task. The final method was similar to the second approach; however, it employed a mixed-effects Rasch model to estimate individual capacity limits within the context of item response theory for the spatial memory task. To assess the strength of each of these labeling approaches, we compared the area under the curve (AUC) for receiver operating curves (ROCs) from elastic net and random forest classifiers. We chose these classifiers based on a combination of interpretability, flexibility, and past modeling success. We tested these techniques across two groups of individuals and two tasks to test the effects of different labeling techniques on cross-person and cross-task transfer. Overall, we observed that the Rasch model labeling paired with a random forest classifier led to the best model fits and showed evidence of both cross-person and cross-task transfer. (shrink)

This paper discusses a deterministic model of the spread of an infectious disease in a closed population that was proposed byKermack &McKendrick . The mathematical assumptions on which the model is based are listed and criticized. The ‘threshold theorem’ according to which an epidemic develops if, and only if, the initial population density exceeds a certain value determined by the parameters of the model, is discussed. It is shown that the theorem is not true. A weaker result is stated (...) and proved.A new simplified version of the model is discussed. In this model it is assumed that an infected individual becomes infectious after a constant time and that it will removed after a constant time. Numerical simulations of this model show that the form of the fluctuations in the number of diseased individuals depends on the values of the parameters. The number of infectious individuals may oscillate up and down under certain circumstances. Necessary conditions for the number of infectious individuals to rise above previous levels are stated and proved. (shrink)

This article traces the history of the Susceptible, Infected, Recovered (SIR) model in early 20th-century epidemiology (1904–27). The aim is to test the hypothesis that the active stance taken by Ross, Hudson, McKendrick, and Kermack represents a turn in the history of modern epidemiology, shifting the classical method of statistical epidemiology from a data-based model to a theory-based model. The article shows that epidemiological modeling is based on a mathematical simplification of epidemics at the time of the microbiological complexification (...) of epidemiology. What were the implications of the mathematical theory of epidemics for the development of modern epidemiology? How can epidemic dynamics be expressed mathematically without compromising the biological representation? This is exactly what is at stake here: from the work of Ross to the standardization of the SIR model by McKendrick and Kermack, modeling has been confronted with the problem of relating its equations to the facts. (shrink)

The classical models of epidemics dynamics by Ross and McKendrick have to be revisited in order to incorporate elements coming from the demography (fecundity, mortality and migration) both of host and vector populations and from the diffusion and mutation of infectious agents. The classical approach is indeed dealing with populations supposed to be constant during the epidemic wave, but the presently observed pandemics show duration of their spread during years imposing to take into account the host and vector population (...) changes as well as the transient or permanent migration and diffusion of hosts (susceptible or infected), as well as vectors and infectious agents. Two examples are presented, one concerning the malaria in Mali and the other the plague at the middle-age. (shrink)

Kendall's (1956) approach to the general epidemic is generalized by dropping the assumptions of constant infectivity and random recovery or death of ill individuals. A great deal of attention is paid to the biological background and the heuristics of the model formulation. Some new results are: (l) the derivation of Kermack's and McKendrick's integral equation from what seems to be the most general set of assumptions in section 2.2, (2) the use of Kermack's and McKendrick's final value equation (...) to arrive at a finite time version of the threshold theorem for the general case, comparable to that for the case of only one Markovian state of illness in section 2.5, (3) the analysis of the behaviour of the solutions of the integral equation when the starting infection approaches zero in section 2.7, (4) the derivation of the probability structure of a general branching process, after conditioning on extinction in section 3.6, (5) the statement of the generalized versions of Kendall's ideas in the form of precise limit conjectures in section 4, (6) the derivation of a closed expression for the limit epidemic resulting from (3) in appendix 4. (shrink)