A semantic repository approach to improve the government to business relationship

A major objective in business interactions consists in enhancing the business perspective over service provision by developing strategies and tools to provide support in the selection of services according to the value they have for businesses. This means providing a way to determine the value of services according to specific business criteria, and conceive technologies that support the sharing of knowledge involved in service provision. In this paper we present an approach based on semantic repositories. The repository enables a business perspective over service provision, based on the association between services and business processes, and is related to the problem of supporting businesses in the value-driven service selection. This perspective is addressed in the paper by exploiting expressive semantic representations and reasoning. An ontology for representing relevant semantic properties of services and processes is provided, and an algorithm for value-based service selection is presented. Two real life case studies show the effectiveness of the approach.     

Time–temperature dependence of the electrical resistivity of high‐density polyethylene/carbon black composites

Several carbon blacks with surface areas from 105 to 1353 m²/g were used to produce composites through melt compounding with a high‐density polyethylene matrix. The electrical behavior of the obtained composites was investigated by the measurement of their resistivity as a function of the carbon black content and type at various temperatures and times during isothermal annealing treatments. The percolation threshold markedly decreased as the carbon black surface area increased, reaching a minimum value of 1.8 vol % for the carbon black with a surface area of 1353 m²/g. The resistivity passed through a maximum as the test temperature increased. Moreover, the analysis of the experimental data evidenced that the host high‐density polyethylene matrix and the conductive carbon black network rearranged during the isothermal thermal treatments, causing a resistivity decrease. This rearrangement became less and less important as the carbon black surface area increased. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Detecting siblings in image pairs

In everyday life, face similarity is an important kinship clue. Computer algorithms able to infer kinship from pairs of face images could be applied in forensics, image retrieval and annotation, and historical studies. So far, little work in this area has been presented, and only one study, using a small set of low quality images, tackles the problem of identifying siblings pairs. The purpose of our paper is to present a comprehensive investigation on this subject, aimed at understanding which are, on the average, the most relevant facial features, how effective can be computer algorithms for detecting siblings pairs, and if they can outperform human evaluation. To avoid problems due to low quality pictures and uncontrolled imaging conditions, as for the heterogeneous datasets collected for previous researches, we prepared a database of high quality pictures of sibling pairs, shot in controlled conditions and including frontal, profile, expressionless, and smiling faces. Then we constructed various classifiers of image pairs using different types of facial data, based on various geometric, textural, and holistic features. The classifiers were first tested separately, and then the most significant facial data, selected with a two stage feature selection algorithm were combined into a unique classifier. The discriminating ability of the automatic classifier combining features of different nature has been found to outperform that of a panel of human raters. We also show the good generalization capabilities of the algorithm by applying the classifier, in a cross-database experiment, to a low quality database of images collected from the Internet.     

Microwave Regenerated Catalytic Foam: A More Effective Way for PM Reduction

In this work the effect of microwave irradiation on the regeneration of soot-loaded uncatalytic and catalytic ceramic foam filters was studied for two different catalytic filter formulations. Combining dielectric permittivity and catalytic activity of the foam filter components with microwave absorbing properties of soot allowed a more effective filter regeneration. Moreover, iron based catalysts, typically not active towards soot oxidation in case of electrical heating, showed a significant activity in the presence of microwave.     

Memory functions in polymer modified asphalts

The viscoelastic nonlinear behavior of several base and polymer modified asphalts (PMA) has been studied in step‐strain experiments. The polymers were poly(styrene‐b‐butadiene‐b‐styrene), poly(styrene‐b‐ethylene‐co‐butylene‐b‐styrene), poly(ethylene‐r‐vinylacetate) copolymers, and a linear low density poly(ethylene), which were chosen as representatives of the main categories of asphalt modifiers. Because of the complexity of the morphological structure of these materials, the relaxation modulus has only partial and qualitative similarities with that of melt or high concentrated solutions of entangled polymeric liquids. No time strain separability can be applied, and the relaxation experiments are conveniently described by means of the memory functions. These have been calculated both via a parametric fitting procedure and by interpolation algorithms. Results are presented, and a correlation between the PMA structure and the corresponding memory function is proposed for the investigated materials. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 2330–2340, 2007     

A temperature programmed desorption study of the interaction of acetic anhydride with zeolite beta (BEA)

The interaction of acetic anhydride with the Na- and H-forms of zeolite BETA, as well as with materials where copper or iron has been introduced into BEA by ion exchange, has been studied by temperature programmed desorption (TPD). In all cases acetic acid is a main desorption product in the temperature range 370–570 K. Ketene desorption is also significant, although it is argued that much of it is retained in the zeolite pores, where it undergoes further decomposition into carbon monoxide, hydrogen and water. There is an inverse correlation between the quantity of ketene desorbed and the activity of the catalysts in the catalytic acylation of anisole by acetic anhydride to yield p-methoxyacetophenone. The significance of this observation is discussed and an acylation mechanism involving ketene is proposed.     

Identification and Rejuvenation of NBTI-Critical Logic Paths in Nanoscale Circuits

The Negative Bias Temperature Instability (NBTI) phenomenon is agreed to be one of the main reliability concerns in nanoscale circuits. It increases the threshold voltage of pMOS transistors, thus, slows down signal propagation along logic paths between flip-flops. NBTI may cause intermittent faults and, ultimately, the circuit’s permanent functional failures. In this paper, we propose an innovative NBTI mitigation approach by rejuvenating the nanoscale logic along NBTI-critical paths. The method is based on hierarchical identification of NBTI-critical paths and the generation of rejuvenation stimuli using an Evolutionary Algorithm. A new, fast, yet accurate model for computation of NBTI-induced delays at gate-level is developed. This model is based on intensive SPICE simulations of individual gates. The generated rejuvenation stimuli are used to drive those pMOS transistors to the recovery phase, which are the most critical for the NBTI-induced path delay. It is intended to apply the rejuvenation procedure to the circuit, as an execution overhead, periodically. Experimental results performed on a set of designs demonstrate reduction of NBTI-induced delays by up to two times with an execution overhead of 0.1 % or less. The proposed approach is aimed at extending the reliable lifetime of nanoelectronics.     

Improving robotic machining accuracy through experimental error investigation and modular compensation

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis.     

Bioinspired Nanocomposites: Ordered 2D Materials Within a 3D Lattice

Composites, materials composed of two or more materials—metallic, organic, or inorganic—usually exhibit the combined physical properties of their component materials. The result is a material that is superior to conventional monolithic materials. Advanced composites are used in a variety of industrial applications and therefore attract much scientific interest. Here the formation of novel carbon‐based nanocomposites is described via incorporation of graphene oxide (GO) into the crystal lattice of single crystals of calcite. Incorporation of a 2D organic material into single‐crystal lattices has never before been reported. To characterize the resulting nanocomposites, high‐resolution synchrotron powder X‐ray diffraction, electron microscopy, transmission electron microscopy, fluorescence microscopy and nanoindentation tests are employed. A detailed analysis reveals a layered distribution of GO sheets incorporated within the calcite host. Moreover, the optical and mechanical properties of the calcite host are altered when a carbon‐based nanomaterial is introduced into its lattice. Compared to pure calcite, the composite GO/calcite crystals exhibits lower elastic modulus and higher hardness. The results of this study show that the incorporation of a 2D material within a 3D crystal lattice is not only feasible but also can lead to the formation of hybrid crystals exhibiting new properties.