Abstract

Abstract
Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels. © 2014 AIP Publishing LLC.

Abstract

Abstract
In the last decade, SAR interferometry techniques, especially those that use time series analysis experienced a strong development in both, methodologies and applications, becoming an operational tool for deformation monitoring. The emergence of a growing number of SAR dedicated missions combined with the increasing interest from academics, but also private research groups, reflected in the number of available software packages developed with interferometric analysis purposes, were the major responsible for the InSAR/MTI achievements occurred over the past few years. Many free-of-charge (freeware or open-source) and commercial software packages exist. Due to its proven reliability and freeware distribution among the scientific community, Stanford Method for Persistent Scatterers/Multi-Temporal Interferometry (StaMPS/MTI) implementation, is widely used for ground deformation monitoring. This paper presents viStaMPS v1.2, a collaborative scientific project that appeared with three major purposes: (1) facilitate the usage by users nonfamiliar with the specificities of the programming language that supports StaMPS; (2) implement several visualization tasks not available in the StaMPS standard approach requiring that each user to develop its own code for visualization and interpretation purposes and (3) create a collaborative research project, continually under development counting on the dynamism of its users to improve and/or add new features. (C) 2014 Published by Elsevier Ltd.

Abstract
In agent mediated electronic commerce the diversity of the involved actors can lead to diff erent conceptualizations of their needs and capabilities giving rise to semantic incompatibilities that might hamper negotiations and the fulfilling of satisfactory transactions. In order to provide help in the conversation among diff erent agents, these systems should provide ontology services, more specifically, ontology matching services. However, given the natural ambiguity of the ontology matching process, raising the possibility of multiple alignments between the same pair of ontologies, it is necessary to choose the one that best meets the interests of both agents. On the other hand, agents may possess diff erent interests, therefore the ontology alignment may also become the object of further negotiation. In this context, the application and exploitation of relationships captured in social networks can result in the establishment of more accurate adequacy relations of ontology alignments to agents, as well as the improvement of the negotiations' efficiency and, consequently, the users' satisfaction with the electronic commerce system. In this paper we present the AEMOS system which follows an ontology-based information integration approach, exploiting the ontology matching paradigm, improved by the application and exploitation of the relationships captured in the social networks. Copyright © 2014, Australian Computer Society Inc.

Abstract
This paper presents a survey on multi-robot search inspired by swarm intelligence by further classifying and discussing the theoretical advantages and disadvantages of the existing studies. Subsequently, the most attractive techniques are evaluated and compared by highlighting their most relevant features. This is motivated by the gradual growth of swarm robotics solutions in situations where conventional search cannot find a satisfactory solution. For instance, exhaustive multi-robot search techniques, such as sweeping the environment, allow for a better avoidance of local solutions but require too much time to find the optimal one. Moreover, such techniques tend to fail in finding targets within dynamic and unstructured environments. This paper presents experiments conducted to benchmark five state-of-the-art algorithms for cooperative exploration tasks. The simulated experimental results show the superiority of the previously presented Robotic Darwinian Particle Swarm Optimization (RDPSO), evidencing that sociobiological inspiration is useful to meet the challenges of robotic applications that can be described as optimization problems (e.g., search and rescue). Moreover, the RDPSO is further compared with the best performing algorithms within a population of 14 e-pucks. It is observed that the RDPSO algorithm converges to the optimal solution faster and more accurately than the other approaches without significantly increasing the computational demand, memory and communication complexity.