Hierarchical mapping of Northern Eurasian land cover using MODIS data

The Northern Eurasian land mass encompasses a diverse array of land cover types including tundra, boreal forest, wetlands, semi-arid steppe, and agricultural land use. Despite the well-established importance of Northern Eurasia in the global carbon and climate system, the distribution and properties of land cover in this region are not well characterized. To address this knowledge and data gap, a hierarchical mapping approach was developed that encompasses the study area for the Northern Eurasia Earth System Partnership Initiative (NEESPI). The Northern Eurasia Land Cover (NELC) database developed in this study follows the FAO-Land Cover Classification System and provides nested groupings of land cover characteristics, with separate layers for land use, wetlands, and tundra. The database implementation is substantially different from other large-scale land cover datasets that provide maps based on a single set of discrete classes. By providing a database consisting of nested maps and complementary layers, the NELC database provides a flexible framework that allows users to tailor maps to suit their needs. The methods used to create the database combine empirically derived climate–vegetation relationships with results from supervised classifications based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. The hierarchical approach provides an effective framework for integrating climate–vegetation relationships with remote sensing-based classifications, and also allows sources of error to be characterized and attributed to specific levels in the hierarchy. The cross-validated accuracy was 73% for the land cover map and 73% and 91% for the agriculture and wetland classifications, respectively. These results support the use of hierarchical classification and climate–vegetation relationships for mapping land cover at continental scales.     

Adaptive course generation through learning styles representation

This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focused on the construction of an adaptive e-learning platform. The aim of the platform is the automatic generation and personalization of courses, taking into account pedagogical knowledge on the didactic domain as well as statistic information on both the student’s knowledge degree and learning preferences. Pedagogical information is described by means of an innovative methodology suitable for effective and efficient course generation and personalization. Moreover, statistic information can be collected and exploited by the system in order to better describe the student’s preferences and learning performances. Learning material is chosen by the system matching the student’s learning preferences with the learning material type, following a pedagogical approach suggested by Felder and Silverman. The paper discusses how automatic learning material personalization makes it possible to facilitate distance learning access to both able-bodied and disabled people. Results from the Diogene and Intraserv evaluation are reported and discussed.     

Experimental setup for lensless imaging via soft x-ray resonant scattering

We have developed a setup for measuring holographically formed interference patterns using an integrated sample-mask design. The direct space image of the sample is obtained via a two-dimensional Fourier transform of the X-ray diffraction pattern. We present the details of our setup, commenting on the influence of geometrical parameters on the imaging capabilities. As an example, we present and discuss the results of test experiments on a patterned Co film.     

Polyamides incorporating furan moieties. 5. Synthesis and characterisation of furan-aromatic homologues

2,2′-Bis (5-chloroformyl 2-furyl) propane and various aromatic diamines were used as monomers in the study of their interfacial polycondensation and the properties of the ensuing furanic-aromatic polyamides. The effects of such variables as the nature of the organic phase, the temperature, the reaction time, and the type and concentration of the catalyst were investigated as well as the properties of the polyamides in terms of structure, average chain length, T_g, T_m and thermal stability.     

Capacitive micromachined ultrasonic transducer (CMUT) arrays for medical imaging

Capacitive micromachined ultrasonic transducers (CMUTs) bring the fabrication technology of standard integrated circuits into the field of ultrasound medical imaging. This unique property, combined with the inherent advantages of CMUTs in terms of increased bandwidth and suitability for new imaging modalities and high frequency applications, have indicated these devices as new generation arrays for acoustic imaging. The advances in microfabrication have made possible to fabricate, in few years, silicon-based electrostatic transducers competing in performance with the piezoelectric transducers. This paper summarizes the fabrication, design, modeling, and characterization of 1D CMUT linear arrays for medical imaging, established in our laboratories during the past 3 years. Although the viability of our CMUT technology for applications in diagnostic echographic imaging is demonstrated, the whole process from silicon die to final probe is not fully mature yet for successful practical applications.     

Modelling and Validating a multiple-configuration railway signalling system using SDL

This paper discusses some issues about the usage of SDL and related commercial SDL support tools for the validation of a railway signalling system: in particular, the issue of the multiple configurations presented by this system is addressed, discussing the possible strategies to validate the system regardless to the actual configuration.     

On the ill-conditioning of subspace identification with inputs

There is experimental evidence that the performance of standard subspace algorithms from the literature (e.g. the N4SID method) may be surprisingly poor in certain experimental conditions. This happens typically when the past signals (past inputs and outputs) and future input spaces are nearly parallel. In this paper we argue that the poor behavior may be attributed to a form of ill-conditioning of the underlying multiple regression problem, which may occur for nearly parallel regressors. An elementary error analysis of the subspace identification problem, shows that there are two main possible causes of ill-conditioning. The first has to do with near collinearity of the state and future input subspaces. The second has to do with the dynamical structure of the input signal and may roughly be attributed to “lack of excitation”. Stochastic realization theory constitutes a natural setting for analyzing subspace identification methods. In this setting, we undertake a comparative study of three widely used subspace methods (N4SID, Robust N4SID and PO-MOESP). The last two methods are proven to be essentially equivalent and the relative accuracy, regarding the estimation of the (A,C) parameters, is shown to be the same.     

The Tetragonal to Orthorhombic Structural Phase Transition in Multiband FeAs-based Superconductors

We report the temperature-dependent x-ray powder diffraction of the FeAs-based superconductors in the range between 300 and 95 K. In the case of NdOFeAs we have detected the structural phase transition from the tetragonal phase, with P4/nmm space group, to the orthorhombic phase, with Cmma space group, over a broad temperature range from 150 to 120 K, centered at T ₀∼137 K. This transition is reduced, by about ∼30 K, by the internal chemical pressure going from LaOFeAs to NdOFeAs. On the contrary, the superconducting critical temperature increases from 27 to 51 K going from LaOFeAs to NdOFeAs doped samples. The FeAs layers in all undoped “1111” and “122” systems suffer a tensile misfit strain. The tensile misfit strain is reduced in “1111” and in “122” samples and at optimum doping the misfit strain is close to zero. This result shows that the normal striped orthorhombic Cmma phase competes with the superconducting tetragonal phase. In the orthorhombic clusters the charges can move only along the stripes in the b direction and are localized by the magnetic interaction.