PhotoGeo: a photo digital library with spatial-temporal support and self-annotation

The recent popularity of digital cameras has posed a new problem: how to efficiently store and retrieve the very large number of digital photos captured and chaotically stored in multiple locations without any annotation. This paper proposes an infrastructure, called PhotoGeo, which aims at helping users with the people photo annotation, event photo annotation, storage and retrieval of personal digital photos. To achieve the desired objective, PhotoGeo uses new algorithms that make it possible to annotate photos with the key metadata to facilitate their retrieval, such as: the people who were shown in the photo (who); where it was captured (where); the date and time of capture (when); and the event that was captured. The paper concludes with a detailed evaluation of these algorithms.     

The Building Blocks of a PaaS

Traditional cloud computing providers enable developers to program and deploy applications in the cloud by using platform as a service (PaaS) providers. Despite the benefits of such an approach, this service model usually comes with a high level of the lock in effect into the service provider. The lock in effect occurs when a software developer needs to change its cloud provider. When this happens, it usually means a major application rewrite, specific for the new PaaS. This paper details the initial results of a project whose goal is to build a PaaS where vendor lock in does not occur. With this PaaS, developers wishing to deploy their applications into the cloud may continue to program using their usual development environments. There are no necessary changes required to make the application PaaS compatible. As a proof of concept, we developed an open source PaaS management application as a regular web application and then deployed it on the cloud.     

Wearable cognitive assistants in a factory setting: a critical review of a promising way of enhancing cognitive performance and well-being

Cognition, Technology & Work - Rapid technological innovations are constantly influencing the complexification and automatization of the work lines pushing human operators to use diverse...     

Team cognition in a cyber defense context: focus on social support behaviors

In the face of increasingly prominent cyber security issues, the organization of cyber team analysts has become crucial to thwart cyber threats. Few studies have examined the functioning of the team and the interaction between individuals in a cyber defense context and how the context influences team adaptation. The present study investigates team cognition in a cyber defense context and in particular the nature of task- or team-centered communication among analysts during a cyber defense simulation exercise. Results indicate that markers of situation assessment and shared mental models are both strategically present and linked. Nevertheless, the frequency of these markers varies depending on the quantity and quality of problems encountered; in particular, variations in social support behaviors are observed. Decreasing social support behaviors during high level activities suggests the adaptation of social behaviors depending on the threats and attacks on the system. Theoretical and practical implications are discussed in terms of theories and potential consequences for strategic adaptation and team resilience.

     

Predicting teamwork results from social network analysis

Modelling students' behaviours has reached a status that can only be overcome by improving the ability of predicting the results on teamwork. Indeed, teamwork is an important piece on the learning process, but understanding their mechanisms and predicting the results achieved is far from being solved by traditional classifiers. In this paper, we address the problem of predicting teamwork results, and propose a recommender system that suggests new teams, in the context of a given curricular unit. Any student, who is looking for a team, may use the system; in particular, he may ask for the best team to join, either considering all available colleagues or just the set of his previous teammates. Our system makes use of social network analysis and classification methods as the algorithmic core of the decision‐making process. System evaluation is presented through a set of experimental results, which report the performance of social network analysis and classification algorithms over real datasets.     

Dynamic Model Adaptation for Multiscale Simulation of Hyperbolic Systems with Relaxation

In numerous industrial CFD applications, it is usual to use two (or more) different codes to solve a physical phenomenon: where the flow is a priori assumed to have a simple behavior, a code based on a coarse model is applied, while a code based on a fine model is used elsewhere. This leads to a complex coupling problem with fixed interfaces. The aim of the present work is to provide a numerical indicator to optimize to position of these coupling interfaces. In other words, thanks to this numerical indicator, one could verify if the use of the coarser model and of the resulting coupling does not introduce spurious effects. In order to validate this indicator, we use it in a dynamical multiscale method with moving coupling interfaces. The principle of this method is to use as much as possible a coarse model instead of the fine model in the computational domain, in order to obtain an accuracy which is comparable with the one provided by the fine model. We focus here on general hyperbolic systems with stiff relaxation source terms together with the corresponding hyperbolic equilibrium systems. Using a numerical Chapman–Enskog expansion and the distance to the equilibrium manifold, we construct the numerical indicator. Based on several works on the coupling of different hyperbolic models, an original numerical method of dynamic model adaptation is proposed. We prove that this multiscale method preserves invariant domains and that the entropy of the numerical solution decreases with respect to time. The reliability of the adaptation procedure is assessed on various 1D and 2D test cases coming from two-phase flow modeling.     

Angular displacement fiber-optic sensor: theoretical and experimental study

An optical-fiber sensor based on twist-induced optical activity has been developed for measuring angular displacements at low temperature. The sensing part is composed of a fiber coil rotated between two points, which induces a twist of two sections of fiber. A theoretical study of the evolution of a general input state of polarization in the sensor gave us its main characteristics. Then experimental investigations permitted the construction of a sensor to take angular measurements over a 100-deg range with an accuracy of 0.2 deg. The thermal sensitivity of this kind of sensor is also briefly reported.     

Microwave-Assisted Fabrication of Superamphiphobic Surfaces on Aluminum Substrates

The field of superamphiphobic surface fabrication has evolved rapidly in the last decade; however, research on important issues such as sustainability and green chemistry procedures is still scarce. Herein, a simple method of microwave irradiation (MW) to minimize energy consumption during the preparation of superamphiphobic aluminum (Al) surfaces is reported. Al substrates are first etched in diluted HCl solutions to generate a microstructure and then irradiated in a commercial microwave unit for several time intervals, temperatures, and pressures. The surfaces are then coated with different compounds, and the wettability is tested with high and very-low surface tension liquids. Optical profilometry and scanning electron microscopy images show that the density of hierarchical micro-nanostructures increases with MW time, temperature, and pressure. At 170 °C and 7.9 bar, the surfaces present a high density of structures and re-entrant topographies. The obtained coatings display excellent repellence to liquids with surface tensions as low as 27.5 mN m⁻¹. X-ray photoelectron spectroscopy data show the importance of efficient surface functionalization for the production of superamphiphobicity in Al substrates. The results show that MW irradiation of Al substrates can be a green and efficient method for fabricating superamphiphobic surfaces.     

BirdVis: visualizing and understanding bird populations

Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records. These observations, together with local-scale environmental covariates such as climate, habitat, and vegetation phenology have been a valuable resource for a global community of educators, land managers, ornithologists, and conservation biologists. By associating environmental inputs with observed patterns of bird occurrence, predictive models have been developed that provide a statistical framework to harness available data for predicting species distributions and making inferences about species-habitat associations. Understanding these models, however, is challenging because they require scientists to quantify and compare multiscale spatialtemporal patterns. A large series of coordinated or sequential plots must be generated, individually programmed, and manually composed for analysis. This hampers the exploration and is a barrier to making the cross-species comparisons that are essential for coordinating conservation and extracting important ecological information. To address these limitations, as part of a collaboration among computer scientists, statisticians, biologists and ornithologists, we have developed BirdVis, an interactive visualization system that supports the analysis of spatio-temporal bird distribution models. BirdVis leverages visualization techniques and uses them in a novel way to better assist users in the exploration of interdependencies among model parameters. Furthermore, the system allows for comparative visualization through coordinated views, providing an intuitive interface to identify relevant correlations and patterns. We justify our design decisions and present case studies that show how BirdVis has helped scientists obtain new evidence for existing hypotheses, as well as formulate new hypotheses in their domain.     

PedVis: a structured, space-efficient technique for pedigree visualization

Public genealogical databases are becoming increasingly populated with historical data and records of the current population's ancestors. As this increasing amount of available information is used to link individuals to their ancestors, the resulting trees become deeper and more dense, which justifies the need for using organized, space-efficient layouts to display the data. Existing layouts are often only able to show a small subset of the data at a time. As a result, it is easy to become lost when navigating through the data or to lose sight of the overall tree structure. On the contrary, leaving space for unknown ancestors allows one to better understand the tree's structure, but leaving this space becomes expensive and allows fewer generations to be displayed at a time. In this work, we propose that the H-tree based layout be used in genealogical software to display ancestral trees. We will show that this layout presents an increase in the number of displayable generations, provides a nicely arranged, symmetrical, intuitive and organized fractal structure, increases the user's ability to understand and navigate through the data, and accounts for the visualization requirements necessary for displaying such trees. Finally, user-study results indicate potential for user acceptance of the new layout.