An ambient intelligence approach for learning in smart robotic environments

Smart robotic environments combine traditional (ambient) sensing devices and mobile robots. This combination extends the type of applications that can be considered, reduces their complexity, and enhances the individual values of the devices involved by enabling new services that cannot be performed by a single device. To reduce the amount of preparation and preprogramming required for their deployment in real‐world applications, it is important to make these systems self‐adapting. The solution presented in this paper is based upon a type of compositional adaptation where (possibly multiple) plans of actions are created through planning and involve the activation of pre‐existing capabilities. All the devices in the smart environment participate in a pervasive learning infrastructure, which is exploited to recognize which plans of actions are most suited to the current situation. The system is evaluated in experiments run in a real domestic environment, showing its ability to proactively and smoothly adapt to subtle changes in the environment and in the habits and preferences of their user(s), in presence of appropriately defined performance measuring functions.     

Field-Aligned Interpolation for Semi-Lagrangian Gyrokinetic Simulations

This work is devoted to the study of field-aligned interpolation in semi-Lagrangian codes. In the context of numerical simulations of magnetic fusion devices, this approach is motivated by the observation that gradients of the solution along the magnetic field lines are typically much smaller than along a perpendicular direction. In toroidal geometry, field-aligned interpolation consists of a 1D interpolation along the field line, combined with 2D interpolations on the poloidal planes (at the intersections with the field line). A theoretical justification of the method is provided in the simplified context of constant advection on a 2D periodic domain: unconditional stability is proven, and error estimates are given which highlight the advantages of field-aligned interpolation. The same methodology is successfully applied to the solution of the gyrokinetic Vlasov equation, for which we present the ion temperature gradient (ITG) instability as a classical test-case: first we solve this in cylindrical geometry (screw-pinch), and next in toroidal geometry (circular Tokamak). In the first case, the algorithm is implemented in Selalib (semi-Lagrangian library), and the numerical simulations provide linear growth rates that are in accordance with the linear dispersion analysis. In the second case, the algorithm is implemented in the Gysela code, and the numerical simulations are benchmarked with those employing the standard (not aligned) scheme. Numerical experiments show that field-aligned interpolation leads to considerable memory savings for the same level of accuracy; substantial savings are also expected in reactor-scale simulations.     

DOST: a distributed object segmentation tool

This paper presents a novel distributed object segmentation framework that allows one to extract potentially large coherent objects from digital images. The proposed approach requires minimum user supervision and permits to segment the objects accurately. It works in three steps starting with the user input in form of few mouse clicks on the target object. First, based on user input, the statistical characteristics of the target distributed object are modeled with Gaussian mixture model. This model serves as the primary segmentation of the object. In the second step, the segmentation result is refined by performing connected component analysis to reduce false positives. In the final step the resulting segmentation map is dilated to select the neighboring pixels that are potentially incorrectly classified; this allows us to recast the segmentation as a graph partitioning problem that can be solved using the well-known graph cut technique. Extensive experiments have been carried out on heterogeneous images to test the accuracy of the proposed method for the segmentation of various types of distributed objects. Examples of application of proposed technique in remote sensing to segment roads and rivers from aerial images are also presented. The visual and objective evaluation and comparison with the existing techniques show that the proposed tool can deliver optimal performance when applied to tough object segmentation tasks.

     

Multimodal workflow for the creation of interactive presentations of 360 spin images of historical violins

Multimedia Tools and Applications - The adoption of multimedia and multimodal applications inside museums and exhibitions is becoming a common practice. These installations proved to be...     

CrisMap: a Big Data Crisis Mapping System Based on Damage Detection and Geoparsing

Natural disasters, as well as human-made disasters, can have a deep impact on wide geographic areas, and emergency responders can benefit from the early estimation of emergency consequences. This work presents CrisMap, a Big Data crisis mapping system capable of quickly collecting and analyzing social media data. CrisMap extracts potential crisis-related actionable information from tweets by adopting a classification technique based on word embeddings and by exploiting a combination of readily-available semantic annotators to geoparse tweets. The enriched tweets are then visualized in customizable, Web-based dashboards, also leveraging ad-hoc quantitative visualizations like choropleth maps. The maps produced by our system help to estimate the impact of the emergency in its early phases, to identify areas that have been severely struck, and to acquire a greater situational awareness. We extensively benchmark the performance of our system on two Italian natural disasters by validating our maps against authoritative data. Finally, we perform a qualitative case-study on a recent devastating earthquake occurred in Central Italy.     

Why Tyrosol Derivatives Have to Be Quantified in the Calculation of “Olive Oil Polyphenols” Content to Support the Health Claim Provisioned in the EC Reg. 432/2012

The viewpoint is the outcome of the scientific expertise of the scientists that sign it and work collaboratively in the frame of the OLEUM project. The project aims to better guarantee olive oil quality and authenticity by empowering detection and fostering prevention of olive oil fraud and by an effort of harmonization, correct interpretation, and use of official and supporting analytical methods. Practical Applications: The consensus among scientists, the European food authorities, IOC, and the olive industry on which compounds should be determined to support the health claim on olive oil polyphenols (EC Reg. 432/2012) is of utmost importance and can be supported by the evidence provided in this viewpoint article. The exact interpretation of this health claim involves the clarification of the compounds that should be summed up to give the amount of at least 5 mg phenols per 20 g of oil.     

Characterization of community based-P2P systems and implications for traffic localization

In this paper, we present one of the first and most extensive characterizations of closed community-based P2P systems. Such systems are organic groups of peer-to-peer (P2P) clients, which can be joined only by users belonging to a certain network (e.g., connected to a given Internet Service Provider (ISP)). A number of factors motivate the growth of these communities, such as quality of content, anonymity of transfers, and the potential for better performance that enhances user experience. Our study is conducted in two contrasting environments—a campus network and a national ISP—located in different continents. In both cases, large-scale closed communities have been found to be the predominant P2P systems in use. We shed light both on the factors motivating the growth of such communities, and present results characterizing the extensiveness of their usage, the performance achievable by the systems, and the implications of such communities for network providers. While our findings are interesting in their own right, they also offer important lessons for ongoing research that seeks to localize traffic within ISP boundaries. In particular, our results suggest that (i) in ISPs with heterogeneous access technologies, the performance benefits to users on localizing P2P traffic is largely dependent on the degree of seed-like behavior of peers behind high-bandwidth access technologies; and (ii) while localization can reduce the traffic on Internet peering links, it has the potential to cause a significant increase in traffic on internal links of providers, potentially requiring upgrades of network links.     

Poly(butylene succinate)/layered double hydroxide bionanocomposites: Relationships between chemical structure of LDH anion,delamination strategy,and final properties

A series of poly(butylene succinate) (PBS) containing organo‐modified layered double hydroxide (LDH) are prepared by melt compounding and by in situ polymerization of succinic ester and 1,4‐butanediol. Various LDHs intercalated with renewable organic anions are used. More specifically, lauryl sulfate, stearate, succinate, adipate, sebacate, citrate, and ricinoleate ions are used as LDHs organo‐modifiers. The thermal, rheological, and dynamic mechanical properties of the samples are investigated. The results reveal a general mechanical reinforcement imparted by the clays. Significant changes are observed for the in situ polymerized nanocomposites, especially for LDH stearate which improves the properties of PBS nanostructure, whereas very few differences are observed for the other samples. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 1931–1940, 2013