81 result(s)
Page Size: 10, 20, 50
Export: bibtex, xml, json, csv
Order by:

CNR Author operator: and / or
more
Typology operator: and / or
Language operator: and / or
Date operator: and / or
more
Rights operator: and / or
2010 Article Unknown

Climate change assessment for Mediterranean agricultural areas by statistical downscaling
Palatella L., Miglietta M. M., Paradisi P., Lionello P.
In this paper we produce projections of seasonal precipitation for four Mediterranean areas: Apulia region (Italy), Ebro river basin (Spain), Po valley (Italy) and An- talya province (Turkey). We performed the statistical down- scaling using Canonical Correlation Analysis (CCA) in two versions: in one case Principal Component Analysis (PCA) filter is applied only to predictor and in the other to both pre- dictor and predictand. After performing a validation test, CCA after PCA filter on both predictor and predictand has been chosen. Sea level pressure (SLP) is used as predictor. Downscaling has been carried out for the scenarios A2 and B2 on the basis of three GCM's: the CCCma-GCM2, the Csiro-MK2 and HadCM3. Three consecutive 30-year pe- riods have been considered. For Summer precipitation in Apulia region we also use the 500 hPa temperature (T500) as predictor, obtaining comparable results. Results show dif- ferent climate change signals in the four areas and confirm the need of an analysis that is capable of resolving internal differences within the Mediterranean region. The most ro- bust signal is the reduction of Summer precipitation in the Ebro river basin. Other significative results are the increase of precipitation over Apulia in Summer, the reduction over the Po-valley in Spring and Autumn and the increase over the Antalya province in Summer and Autumn.Source: Natural hazards and earth system sciences (Print) 10 (2010): 1647–1661.

See at: CNR People


2010 Article Unknown

Complex intermittency blurred by noise: theory and application to neural dynamics
Allegrini P., Menicucci D., Bedini R., Gemignani A., Paradisi P.
We propose a model for the passage between metastable states of mind dynamics. As changing points we use the rapid transition processes simultaneously detectable in EEG signals related to different cortical areas. Our model consists of a non-Poissonian intermittent process, which signals that the brain is in a condition of complexity, upon which a Poisson process is superimposed. We provide an analytical solution for the waiting- time distribution for the model, which is well obeyed by physiological data. Although the role of the Poisson process remains unexplained, the model is able to reproduce many behaviors reported in literature, although they seem contradictory.Source: Physical review. E, Statistical, nonlinear and soft matter physics (Online) 82 (2010): 015103-1–015103-4. doi:10.1103/PhysRevE.82.015103
DOI: 10.1103/PhysRevE.82.015103

See at: DOI Resolver | pre.aps.org | CNR People


2010 Article Unknown

Detection limit of biomarkers using the near-infrared band-gap fluorescence of single-walled carbon nanotubes
D' Acunto M., Colantonio S., Moroni D., Salvetti O.
Progress is being made in the development of microanalytical systems for biosensing. Because the sensor signal-to-noise ratio increases with decreasing size for many devices, considerable effort to fabricate small sensors is going to be addressed. Due to their hollow cylindrical structure, carbon nanotubes (CNTs) are considered very promising for many potential nano-device applications. Fluorescence microscopy in the near-infrared (NIR) between 950 and 1600nm has been developed as a novel method to image and study single-walled carbon nanotubes (SWNTs) in a variety of environments. Recently, hybridisation of DNA using NIR band-gap fluorescence has been experimentally demonstrated. We describe a numerical simulation, where the fluorescence shift energy is connected to exciton density variation when the molecular recognition is located on the SWNT immersed in a physiological solution.Source: Journal of modern optics (Print) 57 (2010): 1695–1699. doi:10.1080/09500341003658170
DOI: 10.1080/09500341003658170

See at: DOI Resolver | CNR People | www.informaworld.com


2010 Book Unknown

Advanced Infrared Technology and Applications
Abbozzo Ronchi L., Carlomagno G. M., Corsi C., Grinzato E., Pippi I., Salvetti O.
This special issue of the Journal of Modern Optics contains extended versions of selected papers accepted and presented at the 10th International Workshop on Advanced Infrared Technology and Applications held on 8-11 September 2009 at the Astronomy and Space Science Department of the University of Florence, Italy. The workshop - an event in a biennial series of meetings that started in 1991, and organised by Fondazione 'Giorgio Ronchi' (Florence), the Institutes of Information Science and Technologies 'Alessandro Faedo' (Pisa), Construction Technologies (Padova), Applied Physics 'Nello Carrara' (Florence) of the Italian National Research Council and the CREO Consortium, L'Aquila - constitutes a forum for bringing together academic and industrial researchers to exchange knowledge, ideas and experiences in the field of infrared (IR) science and technology. The main topics of the workshop included, in particular, advanced technology and materials, smart and fibre-optic sensors, aerospace and industrial applications, astronomy and earth monitoring, nondestructive tests and evaluation, systems for cultural heritage, near-, mid-, and long-wavelength systems, and image processing and data analysis. This special issue includes 17 papers that discuss scientific and technological aspects related to a few of these areas.Source: Boca Raton: Taylor & Francis, 2010
DOI: 10.1080/09500340.2010.527708

See at: DOI Resolver | CNR People


2010 Article Unknown

Surface growth processes induced by AFM debris production. A continuum picture
D' Acunto M.
Recent ultra-high vacuum (UHV) scratching atomic force microscopy (AFM) experiments showed the formation of small clusters, larger aggregates or regular patterns on the surface being scanned. In this paper, we suggest a theory that should capture the basic mechanisms that produce the formation of such structures. Such cluster structures, generally self-organized in regular structures, are mainly produced by the flux of adatoms generated by the AFM tip stripping off adatoms during the continuous passage of the probe tip on the surface being analysed. We assume that surface diffusion is the dominant transport mechanism of mass and a nonequilibrium thermodynamics framework for the self-organized growth process is developed. The accurate knowledge of such growth structures is important for two main reasons: it is possible to have an indirect measurement of the incidence of the wear basic mechanisms involved during the AFM scratching test while analysing the structures generated and the patterned structures produced could be used as a base (precursor factor) for mature surface growth processes. Despite granular structure of atom-by-atom nature of the debris, our theory uses a continuum approach for the description of the surface growth induced during the wearing passage of the probe tip.Source: Physica. B, Condensed matter (Print) 405 (2010): 793–801. doi:10.1016/j.physb.2009.10.003
DOI: 10.1016/j.physb.2009.10.003

See at: DOI Resolver | CNR People | www.sciencedirect.com


2010 Conference object Unknown

Dependent component analysis for cosmology: a case study
Kuruoglu E. E.
In this paper, we discuss various dependent component analysis approaches available in the literature and study their performances on the problem of separation of dependent cosmological sources from multichannel microwave radiation maps of the sky. Realisticaly simulated cosmological radiation maps are utilised in the simulations which demonstrate the superior performance obtained by tree-dependent component analysis and correlated component analysis methods when compared to classical ICA.Source: LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference, pp. 538–545, St. Malo, France, 27-30 September 2010
DOI: 10.1007/978-3-642-15995-4_67

See at: DOI Resolver | CNR People | www.springerlink.com


2010 Article Unknown

Modelling with mixture of symmetric stable distributions using Gibbs sampling
Salas-gonzalez D., Kuruoglu E. E., Ruiz D. P.
The stable distribution is a very useful tool to model impulsive data. In this work, a fully Bayesian mixture of symmetric stable distribution model is presented. Despite the non-existence of closed form for alpha-stable distributions, the use of the product property makes it possible to infer on parameters using a straight forward Gibbs sampling. This model is compared to the mixture of Gaussians model. Our proposed methodology is proved to be more robust to outliers than the mixture of Gaussians. Therefore, it is suitable to model mixture of impulsive data. Moreover, as Gaussian is a particular case of the alpha-stable distribution, the proposed model is a generalization of mixture of Gaussians. Mixture of symmetric alpha-stable is intensively tested on both simulated and real data.Source: Signal processing (Print) 90 (2010): 774–783. doi:10.1016/j.sigpro.2009.07.003
DOI: 10.1016/j.sigpro.2009.07.003

See at: DOI Resolver | CNR People


2010 Article Unknown

Modeling non-Gaussian time-varying vector autoregressive processes by particle filtering
Gencaga D., Kuruoglu E. E., Ertuzun A.
We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical processes, mobile communication channels and biomedical signals. In the literature, most work utilize multivariate Gaussian models for the mentioned applications, mainly due to the lack of efficient analytical tools for modeling with non-Gaussian distributions. In this paper, we propose a particle filtering approach which can model non-Gaussian autoregressive processes having cross-correlations among them. Moreover, time-varying parameters of the process can be modeled as the most general case by using this sequential Bayesian estimation method. Simulation results justify the performance of the proposed technique, which potentially can model also Gaussian processes as a sub-case.Source: Multidimensional systems and signal processing 21 (2010): 73–85. doi:10.1007/s11045-009-0081-8
DOI: 10.1007/s11045-009-0081-8

See at: DOI Resolver | CNR People | www.springerlink.com


2010 Article Unknown

Preliminary description of a self-similarity phenomenon in the connection patterns of dreams
Barcaro U., Rizzi P.
The objective of the research was to recognize and describe a phenomenon of self-similarity in dreams, specifically in the connection patterns of dreams: These patterns were obtained by means of a linguistic analysis of data including dream reports and associations provided by the dreamer. Dreams of four patients in therapy, three for each patient, were considered. It was found that a well-defined pattern (Basic Pattern) existed at three levels: links among dream sources of a dream, connections among source clusters of a dream, and connections among different dreams of a same patient. This self-similarity pattern was meaningfully interpretable at all the three levels. Considering the small number of patients, the description and interpretation of the results should be viewed as only preliminary. However, a minimum value for the occurrence frequency of the observed phenomenon can be given with good statistical significance.Source: Dreaming (N.Y.N.Y.) 20 (2010): 136–148. doi:10.1037/a0019241
DOI: 10.1037/a0019241

See at: DOI Resolver | psycnet.apa.org | CNR People


2010 Article Unknown

Bayesian source separation for cosmology [Estimating cosmological components]
Kuruoglu E. E.
Recent satellite missions have provided and continue to provide us with vast amounts of data on radiation measurements that generally present themselves as superpositions of various cosmological sources, most importantly cosmic microwave background (CMB) radiation and other galactic and extragalactic sources. We would like to obtain the estimates of these sources separately since they carry vital information of cosmological significance about our Universe. Although initial attempts to obtain sources have utilized blind estimation techniques, the presence of important astrophysical prior information and the demanding nature of the problem makes the use of informed techniques possible and indispensable. In this article, our objective is to present a formulation of the problem in Bayesian framework for the signal processing community and to provide a panorama of Bayesian source separation techniques for the estimation of cosmological components from the observation mixtures.Source: IEEE signal processing magazine (Print) 27 (2010): 43–54. doi:10.1109/MSP.2009.934718
DOI: 10.1109/MSP.2009.934718

See at: DOI Resolver | ieeexplore.ieee.org | CNR People


2010 Article Unknown

Decision support in heart failure through processing of electro- and echocardiograms
Chiarugi F., Colantonio S., Emmanouilidou D., Martinelli M., Moroni D., Salvetti O.
Objective: Signal and imaging investigations are currently key components in the diagnosis, prognosis and follow up of heart diseases. Nowadays, the need for more efficient, cost-effective and personalised care has led to a renaissance of clinical decision support systems (CDSSs). The purpose of this paper is to present an effective way of achieving a high-level integration of signal and image processing methods in the general process of care, by means of a clinical decision support system, and to discuss the advantages of such an approach. From the wide range of heart diseases, heart failure, whose complexity best highlights the benefits of this integration, has been selected. Methods: After an analysis of users' needs and expectations, significant and suitably designed image and signal processing algorithms are introduced to objectively and reliably evaluate important features involved in decisional problems in the heart failure domain. Then, a CDSS is conceived so as to combine the domain knowledge with advanced analytical tools for data processing. In particular, the relevant and significant medical knowledge and experts' knowhow are formalised according to an ontological formalism, suitably augmented with a base of rules for inferential reasoning. Results: The proposed methods were tested and evaluated in the daily practice of the physicians operating at the Department of Cardiology, University Magna Graecia, Catanzaro, Italy, on a population of 79 patients. Different scenarios, involving decisional problems based on the analysis of biomedical signals and images, were considered. In these scenarios, after some training and 3 months of use, the CDSS was able to provide important and useful suggestions in routine workflows, by integrating the clinical parameters computed through the developed methods for echocardiographic image segmentation and the algorithms for electrocardiography processing. Conclusions: The CDSS allows the integration of signal and image procSource: Artificial intelligence in medicine (Print) 50 (2010): 95–104. doi:10.1016/j.artmed.2010.05.001
DOI: 10.1016/j.artmed.2010.05.001

See at: DOI Resolver | CNR People | www.sciencedirect.com


2010 Book Unknown

Astronomy and cosmology
Leshem A., Kamalabadi F., Kuruoglu E. E., Van Der Veen A.
Special issue on Astronomy and cosmologySource: New York: IEEE, 2010
DOI: 10.1109/MSP.2009.934928

See at: DOI Resolver | ieeexplore.ieee.org | CNR People


2010 Article Unknown

Fractal complexity in spontaneous EEG metastable-state transitions: new vistas on integrated neural dynamics
Allegrini P., Paradisi P., Menicucci D., Gemignani A.
Resting-state EEG signals undergo Rapid Transition Processes (RTPs) that glue otherwise stationary epochs. We study the fractal properties of RTPs in space and time, supporting the hypothesis that the brain works at a critical state. We discuss how the global intermittent dynamics of collective excitations is linked to mentation, namely non-constrained non-task-oriented mental activity.Source: Frontiers in physiology 1 (2010): 128–129. doi:10.3389/fphys.2010.00128
DOI: 10.3389/fphys.2010.00128

See at: DOI Resolver | CNR People | www.frontiersin.org


2010 Article Unknown

Scientific computing for astrophysical map analysis
Salerno E.
A research team at the Signal and Image Processing Lab of ISTI-CNR has been involved in studying data analysis algorithms for the European Space Agency's Planck Surveyor Satellite since 1999. The huge amount of data on the cosmic microwave background radiation provided by the Planck sensors requires very efficient analysis algorithms and high-performance computing facilities. The CNR group has proposed some of the source separation procedures that are now operational at the Planck data processing centre in Trieste, Italy.Source: ERCIM news 81 (2010): 20–21.

See at: ercim-news.ercim.eu | CNR People


2010 Article Unknown

A knowledge-based infrastructure for the management of diagnostic imaging procedures in the heart failure domain
Martinelli M., Moroni D., Salvetti O., Tampucci M.
Within the European HEARTFAID Project, an integrated platform of services has been developed to assist chronic heart failure stakeholders in their routine workflow and to provide an optimal management of heart failure patients, by exploiting the most advanced technologies, innovative methods for diagnostic data processing, and significant and up-to-date knowledge, suitably formalized. Since signal and imaging investigations are currently a basic step of the diagnostic, prognostic and follow-up processes of heart diseases, the platform has been designed so as to include an advanced system for the management, storage and deployment of the related heterogeneous information, ranging from the raw data - consisting in 1D signals, 2D/3D images and image sequences - to the extracted quantitative parameters and, finally, to their interpretation. The purpose of this paper is to describe an effective way to obtain an integrated management of all the data and transactions across the distributed repositories necessary to deal with such workflows. Intelligent knowledge-based services are also provided for assisting - in a holistic approach - all the decision making processes related to those data. In particular, among the several functionalities provided by HEARTFAID platform, the paper focuses on the integration of echocardiography workflows. To this end, a suitably developed standard-compliant IT infrastructure called EchoCardio Lab is introduced and architectural details of its components are given.Source: TRANSACTIONS ON MASS-DATA ANALYSIS OF IMAGES AND SIGNALS 2 (2010): 3–18.

See at: CNR People


2010 Article Unknown

Color space transformations for analysis and enhancement of ancient degraded manuscripts
Tonazzini A.
In this paper we focus on ancient manuscripts, acquired in the RGB modality, which are degraded by the presence of complex background textures that interfere with the text of interest. Removing these artifacts is not trivial, especially with ancient originals, where they are usually very strong. Rather than applying techniques to just cancel out the interferences, we adopt the point of view of separating, extracting and classifying the various patterns superimposed in the document. We show that representing RGB images in different color spaces can be effective for this goal. In fact, even if the RGB color representation is the most frequently used color space in image processing, it does not maximize the information contents of the image. Thus, in the literature, several color spaces have been developed for analysis tasks, such as object segmentation and edge detection. Some color spaces seem to be particularly suitable to the analysis of degraded documents, allowing for the enhancement of the contents, the improvement of the text readability, the extraction of partially hidden features, and a better performance of thresholding techniques for text binarization. We present and discuss several examples of the successful application of both fixed color spaces and self-adaptive color spaces, based on the decorrelation of the original RGB channels. We also show that even simpler arithmetic operations among the channels can be effective for removing bleed-through, refocusing and improving the contrast of the foreground text, and to recover the original RGB appearance of the enhanced document.Source: Pattern recognition and image analysis 20 (2010): 404–417. doi:10.1134/S105466181003017X
DOI: 10.1134/S105466181003017X

See at: DOI Resolver | CNR People | www.springerlink.com


2010 Article Unknown

La struttura temporale dell'operare in un modello dell'attività mentale
Beltrame R.
In analogia a quanto accade in musica dove una figura ritmica può venir suonata o descritta come struttura temporale, si prospettano impieghi diversi in un modello dell'attività mentale del modo di svolgersi nel tempo di tale attività e della cosapevolezza di questo come struttura temporale.Source: Methodologia online WP239 (2010): 1–6.

See at: CNR People


2010 Conference object Unknown

Source separation for multi-spectral image data with Gaussian mixture priors, with application to the cosmic microwave background
Wilson S. P., Kuruoglu E. E., Yoon J., Quir´os Carretero A.
Source separation is a common task in signal processing and is often analogous to factor analysis. In this work we look at a factor analysis model for source separation of multi-spectral image data where prior information about the sources is quantified as a Gaussian mixture model with an unknown number of factors. Markov chain Monte Carlo techniques for model parameter estimation are used. The development of this methodology is motivated by the need to bring an efficient solution to the separation of components in the microwave radiation maps to be obtained by the satellite mission Planck which has the objective of uncovering cosmic microwave background radiation. The proposed algorithm successfully incorporates a rich variety of prior information available to us in this problem in contrast to most of the previous work that assumes completely blind separation of the sources. Results on realistic simulations of Planck maps and on WMAP 5th year results are shown. The technique suggested is easily applicable to other source separation applications by modifying some of the priors. The computational challenges of this application are large. Multivariate prior mixture models, that incorporate spatial smoothness of sources and dependencies between them, considerably complicate implementation. In addition, Planck data consist of 9 images of order 107 pixels each. We explore various functional approximation approaches to computing marginal posterior distributions, and compare performance with the best MCMC algorithms that we have been able to implement.Source: Ninth Valencia International Meeting on Bayesian Statistics, pp. 299–300, Valencia, Spagna, 3-8 June 2010

See at: CNR People


2010 Conference object Unknown

A deterministic algorithm for optical flow estimation
Gerace I., Martinelli F.
Motion computation is a fundamental and difficult problem of Computer Vision which regards either the computation of 3-D motion in the image space or the computation of 2-D motion in the image plane. In this paper, we deal with the latter problem, which is also called optical flow. We propose a new deterministic algorithm for determining optical flow through regular- ization techniques so that the solution of the problem is defined as the minimum of an appropriate energy function. We also assume that the displacements are piecewise continu- ous and that the discontinuities are variable to be estimated. More precisely, we introduce a hierarchical three-step optimization strategy to minimize the constructed energy function, which is not convex. In the first step we find a suitable initial guess of the displacements field by a gradient-based GNC algorithm. In the second step we define the local energy of a displacement field as the energy function obtained by fixing all the field with the exception of a row or of a column. Then, through an application of the shortest path technique we minimize iteratively each local energy function restricted to a row or to a column until we arrive at a fixed point. In the last step we use again a GNC algorithm to recover a sub-pixel accuracy. The experimental results confirm the goodness of this technique.Source: SIMAI 10th Congress, pp. 54–54, Cagliari, 21-25 June 2010

See at: CNR People


2010 Book Unknown

The interwoven sources of dreams
Barcaro U.
The subject of this book is the study of dreaming from a specific point of view, which provides useful and enlightening results: the analysis of the complex patterns of links among the memory sources of dreams. The significance of these patterns is logical and emotional at the same time. This approach is interdisciplinary: it directly involves the fields of psychology, psychotherapy, linguistics, computer science, mathematics (graph theory, neural networks), history of psychology, literature, and motion pictures.Source: London: Karnac Books, 2010

See at: CNR People