Variation of internal structure and performance of polyethylene- and polypropylene-modified bitumen during blending process

Linear-viscoelastic characteristics and performance are evaluated throughout the blending process of polyethylene and polypropylene with bitumen. Results indicate that type, form and percentage of polyolefin play a significant role in the time evolution of the composite's mechanical response. Toluene extraction of modified bitumen revealed, for the first time, the formation of a sponge-like polymer network. Visual inspection and Fourier transform infrared analysis of the polyolefins recovered after extraction indicates higher affinity of the polyethylene with bitumen in agreement with the rheological test results. The use of polypropylene is discouraged if rutting performance is a concern, and polyethylene in both pellets and powder form at 4%, and after 210 min of blending produces a modified bitumen with acceptable performance.     

Anonymity preserving sequential pattern mining

The increasing availability of personal data of a sequential nature, such as time-stamped transaction or location data, enables increasingly sophisticated sequential pattern mining techniques. However, privacy is at risk if it is possible to reconstruct the identity of individuals from sequential data. Therefore, it is important to develop privacy-preserving techniques that support publishing of really anonymous data, without altering the analysis results significantly. In this paper we propose to apply the Privacy-by-design paradigm for designing a technological framework to counter the threats of undesirable, unlawful effects of privacy violation on sequence data, without obstructing the knowledge discovery opportunities of data mining technologies. First, we introduce a k-anonymity framework for sequence data, by defining the sequence linking attack model and its associated countermeasure, a k-anonymity notion for sequence datasets, which provides a formal protection against the attack. Second, we instantiate this framework and provide a specific method for constructing the k-anonymous version of a sequence dataset, which preserves the results of sequential pattern mining, together with several basic statistics and other analytical properties of the original data, including the clustering structure. A comprehensive experimental study on realistic datasets of process-logs, web-logs and GPS tracks is carried out, which empirically shows how, in our proposed method, the protection of privacy meets analytical utility.     

Recommending multimedia visiting paths in cultural heritage applications

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users—i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user’s satisfaction and system accuracy.     

Distributed estimation via iterative projections with application to power network monitoring

This work presents a distributed method for control centers to monitor the operating condition of a power network, i.e., to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements.     

3D floor plan recovery from overlapping spherical images

Computational Visual Media - We present a novel approach to automatically recover, from a small set of partially overlapping spherical images, an indoor structure representation in terms of a 3D...     

Thermal evolution of Fe62.5Co6Ni7.5Zr6Nb2Cu1B15 metallic glass

Thermal evolution of Fe_62.5Co₆Ni_7.5Zr₆Nb₂Cu₁B₁₅ amorphous alloy prepared by one-roll melt-spinning technique was studied by XRD and DTA. The crystallisation process, occurring in several steps, can be summarised as follows: a a + -Fe a + -Fe + -Fe -Fe + -Fe + ZrB₁₂, where a and a are amorphous phases, and a can be indexed as a -Fe (fcc) structure, with a crystalline order on an average distance of 8 Å. The metallic glass demixed on quenching, but component phases tended to mix by exchanging Fe atoms in a temperature range overlapped with the first crystallisation, which yields -Fe nanocrystals (27 Å). Higher temperature exo-peaks correspond mainly to a recrystallisation of the phases formed at lower temperature. It was found that this alloy has nanocrystalline structure also after heating at a well higher temperature than first crystallization. Even after the last exo-peak, the average crystallite size (D) was considerably smaller than that found in the literature for analogous metallic glasses; D values for our alloy were comparable to those of nanocrystalline phases of other systems heat treated below the temperature of exothermal DTA peaks. Extensive oxidation above 600°C, even at a low oxygen content (c _{o 2} 2 ppm), led to a marked modification of the surface layer: two zirconia polymorphs were identified on the surface of the ribbons, and the ratio of -Fe to -Fe content increased with respect to the bulk. Differences in thermal evolution between outer layer and bulk are attributed to a different phase composition and non-uniform distribution since the as-quenched stage.     

Parametric probabilistic transition systems for system design and analysis

We develop a model of parametric probabilistic transition Systems (PPTSs), where probabilities associated with transitions may be parameters. We show how to find instances of the parameters that satisfy a given property and instances that either maximize or minimize the probability of reaching a certain state. As an application, we model a probabilistic non-repudiation protocol with a PPTS. The theory we develop allows us to find instances that maximize the probability that the protocol ends in a fair state (no participant has an advantage over the others). A preliminary version of this paper was presented at SEFM’04 [LMT04]. 05 April 2006