A super-peer model for resource discovery services in large-scale Grids

As deployed Grids increase from tens to thousands of nodes, peer-to-peer (P2P) techniques and protocols can be used to implement scalable services and applications. The super-peer model is a novel approach that helps the convergence of P2P models and Grid environments and can be used to deploy a P2P information service in Grids. A super-peer serves a single physical organization in a Grid, and manages metadata associated to the resources provided by the nodes of that organization. Super-peers connect to each other to form a peer network at a higher level. This paper examines how the super-peer model can handle membership management and resource discovery services in a multi-organizational Grid. A simulation analysis evaluates the performance of a resource discovery protocol; simulation results can be used to tune protocol parameters in order to increase search efficiency.     

Convolution profiles for right inversion of multivariable non-minimum phase discrete-time systems

The problem of the non-causal inversion of linear multivariable discrete-time systems is analyzed in the geometric approach framework and is solved through the computation of convolution profiles which guarantee perfect tracking under the assumption of infinite-length preaction and postaction time intervals. It is shown how the shape of the convolution profiles is related to both the relative degree and the invariant zeros of the plant. A computational setting for the convolution profiles is derived by means of the standard geometric approach tools. Feasibility constraints are also taken into account. A possible implementation scheme, based on a finite impulse response system acting on a stabilized control loop, is provided.     

Structural modifications induced by recycling of polypropylene

The effect of numerous reprocessing cycles on transport properties of isotactic polypropylene (iPP) films was studied and related to the change of molecular weight and molecular weight distribution occurring during the recycling. Sorption curves of dichloromethane vapor in different samples of iPP were analyzed at 25°C to investigate the effect of structure modifications on the sorption mode. Moreover, gas permeability measurements were performed to evaluate the influence of reprocessing on the gas transport properties. The results obtained were attributed to modifications in the molecular structure of the polymer, evidenced from gel permeation chromatography (GPC), and to a different morphology of the films, as results from X-ray diffractograms and dynamic-mechanical thermal analysis (DMTA).     

Adsorption Behavior of Halogenated Anesthetic and Water Vapor on Cr‐Based MOF (MIL‐101) Adsorbent. Part I. Equilibrium and Breakthrough Characterizations

A synthesized chromium‐based metal organic framework (Cr‐MOF) was used for the adsorption of halogenated anesthetics, i.e., sevoflurane (SF). Adsorption isotherm and breakthrough experiments involving SF (reference sorbate) and water vapor were measured at 298 K and atmospheric pressure on both Cr‐MOF and a commercially used reference adsorbent. The Cr‐MOF MIL‐101 showed a significantly higher SF adsorption capacity and much higher selectivity relative to water vapor compared to the reference adsorbent. Binary‐mixture breakthrough tests demonstrated a “roll‐up effect” for SF on the reference adsorbent while no such effect was observed on MIL‐101.     

A query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy

In this paper we propose a query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy, storing and classifying the tags used to label a set of available resources. Our approach builds and maintains a profile for each user. When he submits a query (consisting of a set of tags) on this folksonomy to retrieve a set of resources of his interest, it automatically finds further “authoritative” tags to enrich his query and proposes them to him. All “authoritative” tags considered interesting by the user are exploited to refine his query and, along with those tags directly specified by him, are stored in his profile in such a way to enrich it. The expansion of user queries and the enrichment of user profiles allow any content-based recommender system operating on the folksonomy to retrieve and suggest a high number of resources matching with user needs and desires. Moreover, enriched user profiles can guide any collaborative filtering recommender system to proactively discover and suggest to a user many resources relevant to him, even if he has not explicitly searched for them.     

A control oriented model for manual-pick warehouses

Nowadays the low cost of wireless communications allows the real time monitoring of the state of manual-pick warehouse systems making possible the real time control of these systems. At this aim, an approach based on a two-level model is presented in this paper. At the lower level, Petri nets are used to build online a model representing the active missions state and to detect conflicts among resources. At the upper level, logical expressions are used to add constraints for a single mission or item. The model is proved to be effective for online monitoring, scheduling and rescheduling of warehouse activities.     

Process simulation of a hybrid SOFC/mGT and enriched air/steam fluidized bed gasifier power plant

The aim of this work is to experimentally and numerically analyze the performance of a integrated power plant composed by a steam oxygen fluidized bed biomass gasifier fed by woods, a Solid Oxide Fuel Cell (SOFC) and a micro Gas Turbine (mGT). The numerical analysis is carried out by using ChemCAD software. In particular, SOFC and gasifier were modeled using proper developed Fortran subroutines interfaced to the basic software. The adopted SOFC model was already validated by the authors in previous works, while the gasifier model was here developed and validated by means of experimental activities carried out by using a bench scale gasifier. Different compounds (Benzene, Toluene, Naphthalene, Phenols) were chosen to analyze the tar evolution in the gaseous stream during the gasification process. Hot gas cleaning (based on catalytic ceramic filter candles inserted in the freeboard of the gasifier – UNIQUE concept) was adopted to remove tar and particulates from the fuel hot gas stream. Different moisture contents in the range between 10 and 30% (i.e. in a deviation of 10% around the usual wood moisture content of 20%) were numerically simulated as well as the degree of purity of the oxygen utilized in the power plant (between 25% and 95%, the rest being N₂). The power requirement for pure oxygen production leads to a reduction of the electrical efficiency of the whole power plant. For this reason, a sensitivity analysis was conducted to find the optimal operation conditions in order to maximise the syngas (H₂, CO) content in the produced gas, while maintaining a high overall electrical efficiency.     

Reliability as Tool for Hydraulic Network Planning

This paper presents a methodology to evaluate the reliability of water distribution systems that can be used in the design phase and for identifying repair works to be carried out on existing systems. The methodology is based on the statistical analysis of dimensionless performance indices (hydraulic performance indices) derived from a large number of simulations of various water system demand scenarios and∕or operating conditions. The hydraulic reliability index is assumed as the probability that, under a given operating condition, the hydraulic performance index will be above a certain threshold. Finally, the system's overall reliability (mechanical + hydraulic) is estimated using the overall reliability index, which is defined by the weighted mean of the hydraulic performance indices obtained for the various operating conditions. A case study using this methodology shows the concrete possibilities of applying this approach to a wide spectrum of cases, and the small influence on overall system reliability normally exerted by such events as the failure of links, pipes, and valves.     

Accurate neural model identification of measurement devices

A neural approach to modeling measurement devices is presented. This approach allows the usual components of a measurement apparatus (transducers, filters, amplifiers, analog-to-digital converters, etc.) to be easily modeled by means of suitably trained artificial neural networks. Two applications regarding analog and mixed analog/digital devices are reported, highlighting the peculiarity of this approach and the accuracy that can be obtained.