Familiarization through Ambient Images Alone

The term “ambient images” has begun to show up in much of the current literature on facial recognition. Ambient images refer to naturally occurring views of a face that captures the idiosyncratic ways in which a target face may vary (Ritchie & Burton, 2017). Much of the literature on ambient images have concluded that exposing people to ambient images of a target face can lead to improved facial recognition for that target face. Some studies have even suggested that familiarity is the result of increased exposure to ambient images of a target face (Burton, Kramer, Ritchie, & Jenkins, 2016). The current study extended the literature on ambient images. Using the face sorting paradigm from Jenkins, White, Van Montfort, and Burton (2011), the current study served three purposes. First, this study captured whether there was an incremental benefit in showing ambient images. Particularly, we observed whether performance improved as participants were shown a low, medium, or high number of ambient images. Next, this study attempted to provide a strong enough manipulation that participant would be able to perform the face sorting task perfectly, after being exposed to a high number (45 total) of ambient images. Lastly, this study introduced time data as a measure of face familiarity. The results found support for one aim of this study and partial support for another aim of this study. Time data were found to be an effective quantitative measure of familiarity. Also, there was some evidence of an incremental benefit of ambient images, but that benefit disappeared after viewing around 15 unique exemplar presentations of a novel identity’s face. Lastly, exposing participants to 45 ambient images alone did not cause them to reach perfect performance. The paper concludes with a discussion on the need to extend past ambient images to understand how to best mimic natural familiarity in a lab setting

Heat Transfer by Numerical Solution for a Class of Radiating Fins

It has long been known that the heat transfer from a solid body to an ambient fluid can be increased by increasing the surface area of the solid body. Extended surfaces, or fins, are indispensable for compact heat exchangers. Geometrically, fins may be classified as straight fins, annular fins, and rod fins or spines. In most applications of fins, a fluid is circulating inside the fin-supporting pipe while the outside is exposed to another ambient fluid. The purpose of fin analysis is to find the temperature distribution in the fin and the heat transfer from the fin to the ambient fluid, i.e., the fin efficiency, which is the basis of comparing various fin designs. Conduction is the heat transfer mechanism in the fin and convection and radiation occur at the surface. The amount of radiation heat transfer, in accordance with Stefan-Boltzmann\u27s law, is proportional to the difference between the fourth power of the temperature of the fin and the ambient fluid. The fourth-power term makes the fin equation non-linear and difficult to solve analytically. Earlier researchers linearized the radiation term by replacing the fourth power law by an equivalent convection coefficient times the difference of the temperature in order to obtain an analytical solution. (See more in text

Comparison of different methods in analyzing short-term air pollution effects in a cohort study of susceptible individuals

BACKGROUND: Short-term fluctuations of ambient air pollution have been associated with exacerbation of cardiovascular disease. A multi-city study was designed to assess the probability of recurrent hospitalization in a cohort of incident myocardial infarction survivors in five European cities. The objective of this paper is to discuss the methods for analyzing short-term health effects in a cohort study based on a case-series. METHODS: Three methods were considered for the analyses of the cohort data: Poisson regression approach, case-crossover analyses and extended Cox regression analyses. The major challenge of these analyses is to appropriately consider changes within the cohort over time due to changes in the underlying risk following a myocardial infarction, slow time trends in risk factors within the population, dynamic cohort size and seasonal variation. RESULTS: Poisson regression analyses, case-crossover analyses and Extended Cox regression analyses gave similar results. Application of smoothing methods showed the capability to adequately model the complex time trends. CONCLUSION: From a practical point of view, Poisson regression analyses are less time-consuming, and therefore might be used for confounder selection and most of the analyses. However, replication of the results with Cox models is desirable to assure that the results are independent of the analytical approach used. In addition, extended Cox regression analyses would allow a joint estimation of long-term and short-term health effects of time-varying exposures

Mean curvature flow in an extended Ricci flow background

In this paper, we consider functionals related to mean curvature flow in an ambient space which evolves by an extended Ricci flow from the perspective introduced by Lott when studying a mean curvature flow in a Ricci flow background. One of them is a weighted extended version of the Gibbons-Hawking-York action on Riemannian metrics in compact manifolds with boundary. We compute its variational properties from which naturally arise boundary conditions to the analysis of its time-derivative under Perelman's modified extended Ricci flow. For instance, the boundary integrand term provides an extension of Hamilton's differential Harnack expression for mean curvature flows in Euclidean space. We also derive the evolution equations for both the second fundamental form and the mean curvature under mean curvature flow in an extended Ricci flow background. In the special case of gradient solitons to the extended Ricci flow, we discuss mean curvature solitons and establish a Huisken's monotonicity-type formula. We show how to construct a family of mean curvature solitons and establish a characterization of such a family. Also, we show how for constructing examples of mean curvature solitons in an extended Ricci flow background.Comment: 24 pages. Suggestions and comments are welcom

A 3D simulation environment with real dynamics: a tool for benchmarking mobile robot performance in long-term deployments

This paper describes a method to compare and evaluate mobile robot algorithms for long-term deployment in changing environments. Typically, the long-term performance of state estimation algorithms for mobile robots is evaluated using pre-recorded sensory datasets. However such datasets are not suitable for evaluating decision-making and control algorithms where the behaviour of the robot will be different in every trial. Simulation allows to overcome this issue and while it ensures repeatability of experiments, the development of 3D simulations for an extended period of time is a costly exercise. In our approach long-term datasets comprising high-level tracks of dynamic entities such as people and furniture are recorded by ambient sensors placed in a real environment. The high-level tracks are then used to parameterise a 3D simulation containing its own geometric models of the dynamic entities and the background scene. This simulation, which is based on actual human activities, can then be used to benchmark and validate algorithms for long-term operation of mobile robots