Model-driven engineering for mobile robotic systems: a systematic mapping study

Software and Systems Modeling - Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of...     

Ontological reasoning for improving the treatment of emotions in text

With the advent of affective computing, the task of adequately identifying, representing and processing the emotional connotations of text has acquired importance. Two problems facing this task are addressed in this paper: the composition of sentence emotion from word emotion, and a representation of emotion that allows easy conversion between existing computational representations. The emotion of a sentence of text should be derived by composition of the emotions of the words in the sentence, but no method has been proposed so far to model this compositionality. Of the various existing approaches for representing emotions, some are better suited for some problems and some for others, but there is no easy way of converting from one to another. This paper presents a system that addresses these two problems by reasoning with two ontologies implemented with Semantic Web technologies: one designed to represent word dependency relations within a sentence, and one designed to represent emotions. The ontology of word dependency relies on roles to represent the way emotional contributions project over word dependencies. By applying automated classification of mark-up results in terms of the emotion ontology the system can interpret unrestricted input in terms of a restricted set of concepts for which particular rules are provided. The rules applied at the end of the process provide configuration parameters for a system for emotional voice synthesis.     

Nogood-FC for solving partitionable constraint satisfaction problems

Many real problems can be naturally modelled as constraint satisfaction problems (CSPs). However, some of these problems are of a distributed nature, which requires problems of this kind to be modelled as distributed constraint satisfaction problems (DCSPs). In this work, we present a distributed model for solving CSPs. Our technique carries out a partition over the constraint network using a graph partitioning software; after partitioning, each sub-CSP is arranged into a DFS-tree CSP structure that is used as a hierarchy of communication by our distributed algorithm. We show that our distributed algorithm outperforms well-known centralized algorithms solving partitionable CSPs.     

Geometric Methods for Shape Recovery from Line Drawings of Polyhedra

Using structural geometric arguments, Whiteley showed that a line drawing is a correct projection of a spherical polyhedron if and only if it has a cross-section compatible with it. We here enlarge the class of drawings to which this test applies, including those of polyhedral disks, possibly with perforations. This extension is helpful, as it makes the test applicable to verify and reconstruct drawings from usual scenes with opaque objects.The presented results rely on geometric constructions, thus offering an alternativeapproach to line drawing interpretation, complementary to the algebraic-combinatorial treatment given in the classic work by Sugihara.Lluís Ros was born inVilafranca del Penedès (Catalonia), on June 30, 1968. He is currently a research scientist at the Institut de Robótica i Informàtica Industrial of the Spanish High Council for Scientific Research, where he holds a Ramón y Cajal position since February 2003. He received a M.Sc. degree in mechanical engineering in 1992, and a Ph.D. degree (with honors) in advanced robotics in 2000, both from the Polytechnic University of Catalonia. His research interests are in geometry, with applications to machine vision, robot kinematics and computer graphics.Federico Thomas was born in Barcelona, on October 5, 1961. He received the B.S. degree in telecommunications engineering in 1984, and the Ph.D. degree (with honors) in computer science in 1988, both from the Polytechnic University of Catalonia. Since March 1990, he has been a research scientist in the Institut de Robòtica i Informàtica Industrial of the Spanish High Council for Scientific Research. His research interests are in geometry and kinematics, with applications to robotics, computer graphics and machine vision.     

Genomic Analysis Made It Possible to Identify Gene-Driver Alterations Covering the Time Window between Diagnosis of Neuroblastoma 4S and the Progression to Stage 4

Neuroblastoma (NB) is a tumor of the developing sympathetic nervous system. Despite recent advances in understanding the complexity of NB, the mechanisms that determine its regression or progression are still largely unknown. Stage 4S NB is characterized by a favorable course of disease and often by spontaneous regression, while progression to true stage 4 is a very rare event. Here, we focused on genomic analysis of an NB case that progressed from stage 4S to stage 4 with a very poor outcome. Array-comparative genomic hybridization (a-CGH) on tumor-tissue DNA, and whole-exome sequencing (WES) on exosomes DNA derived from plasma collected at the onset and at the tumor progression, pointed out relevant genetic changes that can explain this clinical worsening. The combination of a-CGH and WES data allowed for the identification iof somatic copy number aberrations and single-nucleotide variants in genes known to be responsible for aggressive NB. KLRB1, MAPK3 and FANCA genes, which were lost at the time of progression, were studied for their possible role in this event by analyzing in silico the impact of their expression on the outcome of 786 NB patients.     

Programmed Cell Death in the Small Intestine: Implications for the Pathogenesis of Celiac Disease

The small intestine has a high rate of cell turnover under homeostatic conditions, and this increases further in response to infection or damage. Epithelial cells mostly die by apoptosis, but recent studies indicate that this may also involve pro-inflammatory pathways of programmed cell death, such as pyroptosis and necroptosis. Celiac disease (CD), the most prevalent immune-based enteropathy, is caused by loss of oral tolerance to peptides derived from wheat, rye, and barley in genetically predisposed individuals. Although cytotoxic cells and gluten-specific CD4⁺ Th1 cells are the central players in the pathology, inflammatory pathways induced by cell death may participate in driving and sustaining the disease through the release of alarmins. In this review, we summarize the recent literature addressing the role of programmed cell death pathways in the small intestine, describing how these mechanisms may contribute to CD and discussing their potential implications.     

Development and characterisation of a Y2Ti2O7-based glass-ceramic as a potential oxidation protective coating for titanium suboxide (TiOx)

A silica-based glass-ceramic, with Y₂Ti₂O₇ as the major crystalline phase, is designed, characterised and tested as an oxidation-protective coating for a titanium suboxide (TiO_x) thermoelectric material at temperatures of up to 600 °C. The optimised sinter-crystallisation treatment temperatures are found to be 1300 °C and 855 °C for a duration of 30 min, and this treatment leads to a glass-ceramic with cubic Y₂Ti₂O₇ and CaAl₂Si₂O₈ as crystalline phases. An increase of ~270 °C in the dilatometric softening temperature is observed after devitrification of the parent glass, thus further extending its working temperature range.Excellent adhesion of the glass-ceramic coating to the thermoelectric material is maintained after exposure to a temperature of 600 °C for 120 h under oxidising conditions, thus confirming the effectiveness of the T1 glass-ceramic in protecting the TiO_x material.     

Thermo-physical properties of as deposited and aged thermal barrier coatings (TBC) for gas turbines: State-of-the art and advanced TBCs

In the perspective of fuelling the future generations of gas turbines by hydrogen rich syngas, the evaluation of the effect of a higher water vapour content into the flue gases on the TBC used, or potentially usable, is a need. For this purpose YPSZ APS TBC with two different microstructures have been exposed for 500?h at different temperatures in the range 1000?°C–1250?°C either in air and air +20% vol. H₂O. The comparison between the different testing conditions has been performed in terms of sintering kinetics and phase stability, as evaluated by thermal diffusivity measurements and Synchrotron X-Rays diffraction, respectively. Furthermore the characterisation of thermal properties of two innovative TBCs (GZO-YPSZ and YAG) potentially able to withstand the CMAS attack and erosive environments, respectively, has been carried out.No clear evidence of a different behaviour of TBC has been observed, at least in the considered aging time and temperature range.     

A backoff strategy for model‐based experiment design under parametric uncertainty

Model‐based experiment design techniques are an effective tool for the rapid development and assessment of dynamic deterministic models, yielding the most informative process data to be used for the estimation of the process model parameters. A particular advantage of the model‐based approach is that it permits the definition of a set of constraints on the experiment design variables and on the predicted responses. However, uncertainty in the model parameters can lead the constrained design procedure to predict experiments that turn out to be, in practice, suboptimal, thus decreasing the effectiveness of the experiment design session. Additionally, in the presence of parametric mismatch, the feasibility constraints may well turn out to be violated when that optimally designed experiment is performed, leading in the best case to less informative data sets or, in the worst case, to an infeasible or unsafe experiment. In this article, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure both feasibility and optimality of the planned experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session to keep the system within a feasible region with specified probability. This approach is particularly useful when designing optimal experiments starting from limited preliminary knowledge of the parameter set, with great improvement in terms of design efficiency and flexibility of the overall iterative model development scheme. The effectiveness of the proposed methodology is demonstrated and discussed by simulation through two illustrative case studies concerning the parameter identification of physiological models related to diabetes and cancer care. © 2009 American Institute of Chemical Engineers AIChE J, 2010