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2008 Article Open Access OPEN

Component separation methods for the PLANCK mission
Leach S. M., Cardoso J., Baccigalupi C., Barreiro R. B., Betoule M., Bobin J., Bonaldi A., Delabrouille J., De Zotti G., Dickinson C., Eriksen H. K., Gonzalez-nuevo J., Hansen F. K., Herranz D., Le Jeune M., Lopez-caniego M., Martinez-gonzalez E., Massardi M., Melin J., Miville-dechêne M., Patanchon G., Prunet S., Ricciardi S., Salerno E., Sanz J. L., Stark J., Stivoli F., Stolyarov V., Stompor R., Vielva P.
Context. The planck satellite will map the full sky at nine frequencies from 30 to 857 GHz. The CMB intensity and polarization that are its prime targets are contaminated by foreground emission. Aims. The goal of this paper is to compare proposed methods for separating CMB from foregrounds based on their di?erent spectral and spatial characteristics, and to separate the foregrounds into "components" with di?erent physical origins (Galactic synchrotron, free-free and dust emissions; extra-galactic and far-IR point sources; Sunyaev-Zeldovich e?ect, etc.). Methods. A component separation challenge has been organised, based on a set of realistically complex simulations of sky emission. Several methods including those based on internal template subtraction, maximum entropy method, parametric method, spatial and harmonic cross correlation methods, and independent component analysis have been tested. Results. Di?erent methods proved to be e?ective in cleaning the CMB maps of foreground contamination, in reconstructing maps of di?use Galactic emissions, and in detecting point sources and thermal Sunyaev-Zeldovich signals. The power spectrum of the residuals is, on the largest scales, four orders of magnitude lower than the input Galaxy power spectrum at the foreground minimum. The CMB power spectrum was accurately recovered up to the sixth acoustic peak. The point source detection limit reaches 100 mJy, and about 2300 clusters are detected via the thermal SZ e?ect on two thirds of the sky.We have found that no single method performs best for all scientific objectives. Conclusions. We foresee that the final component separation pipeline for planck will involve a combination of methods and iterations between processing steps targeted at di?erent objectives such as di?use component separation, spectral estimation, and compact source extraction.Source: Astronomy & astrophysics (Print) 491 (2008): 597–615. doi:10.1051/0004-6361:200810116
DOI: 10.1051/0004-6361:200810116

See at: arXiv.org e-Print Archive Open Access | Caltech Authors Open Access | Hal-Diderot Open Access | SISSA Digital Library Open Access | DOI Resolver | www.aanda.org | CNR People


2008 Article Unknown

Detection of signs of brain dysfunction in epileptic children by recognition of transient changes in the correlation of seizure-free EEG
Righi M., Barcaro U., Starita A., Karakonstantaki E., Micheloyannis S.
Seizure-free EEG signals recorded from epileptic children were compared with EEG signals recorded from normal children. The comparison was based on the detection of transient events characterized by decrease in the correlation between different traces. For this purpose, a conceptually and mathematically simple method was applied. Two clear and remarkable phenomena, able to quantitatively discriminate between the two groups of subjects, were evidenced, with high statistical significance. In fact, it was observed that: (a) The number of events for the epileptic group was larger; (b) Applying restrictive criteria for event definition, the number of subjects in the epileptic group presenting events was larger. The results support the hypothesis of a decrease in brain correlation in children with epilepsy under treatment. This confirms the efficacy of the EEG signal in evaluating cortical functional differences not visible by visual inspection, independently of the cause (epilepsy or drugs), and demonstrate the specific effectiveness of the analysis method applied.Source: Brain topography 21 (2008): 43–51. doi:10.1007/s10548-008-0057-2
DOI: 10.1007/s10548-008-0057-2

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2008 Article Unknown

Estimation of time-varying AR SaS processes using Gibbs sampling
Gencaga D., Kuruoglu E. E., Ertuzun A., Yildirim S.
In this work, we present a novel method for modeling time-varying autoregressive impulsive signals driven by symmetric alpha stable distributions. The proposed method can be interpreted as a two-stage Gibbs sampler composed of a particle filter, which is capable of estimating the unknown time-varying autoregressive coefficients, and a hybrid Monte Carlo method for estimating the unknown but constant distribution parameters of a symmetric alpha stable process. This method is an alternative to a recently published technique in which both the autoregressive coefficients and the distribution parameters are estimated jointly within a single sequential Monte Carlo framework-the single particle filter technique. The proposed method achieves lower error variances in estimating the distribution parameters compared with the single sequential Monte Carlo technique, and thus, successfully models symmetric impulsive signals.Source: Signal processing (Print) 88 (2008): 2564–2572. doi:10.1016/j.sigpro.2008.03.021
DOI: 10.1016/j.sigpro.2008.03.021

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2008 Conference object Open Access OPEN

Evaluation of feature subset selection, feature weighting, and prototype selection for biomedical applications
Little S., Salvetti O., Perner P.
Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease appears more rarely than the normal case. In such a situation classifiers that generalize over the data such as decision trees and Naïve Bayesian are not the proper choice as classification methods. Case-based classifiers that can work on the samples seen so far are more appropriate for such a task. We propose to calculate the contingency table and class specific evaluation measures despite the overall accuracy for evaluation purposes of classifiers for these specific data characteristics. We evaluate the different options of our case-based classifier and compare the performance to decision trees and Naïve Bayesian. Finally, we give an outlook for further work.Source: ECCBR 2008 - Advances in Case-Based Reasoning, 9th European Conference, pp. 312–324, Trier, Germany, 1-4 September 2008
DOI: 10.1007/978-3-540-85502-6

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2008 Article Unknown

Modeling of non-stationary autoregressive alpha-stable processes by particle filters
Gencaga D., Ertuzun A., Kuruoglu E. E.
In the literature, impulsive signals are mostly modeled by symmetric alpha-stable processes. To represent their temporal dependencies, usually autoregressive models with time-invariant coefficients are utilized. We propose a general sequential Bayesian odeling methodology where both unknown autoregressive coefficients and distribution parameters can be estimated successfully, even when they are time-varying. In contrast to most work in the literature on signal processing with alpha-stable distributions, our work is general and models also skewed alpha-stable processes. Successful performance of our method is demonstrated by computer simulations. We support our empirical results by providing posterior Cramer-Rao lower bounds. The proposed method is also tested on a practical application where seismic data events are modeled.Source: Digital signal processing (Print) 18 (2008): 465–478. doi:10.1016/j.dsp.2007.04.01
DOI: 10.1016/j.dsp.2007.04.01

See at: DOI Resolver | scienceserver.cilea.it | CNR People


2008 Article Unknown

Usefulness of the analysis of links among dream sources in therapy
Barcaro U., Rizzi P.
A study of the links among the memory sources of dreams can be carried out by means of an automatic analysis of text files including dream reports and associations. Heuristic criteria can provide plausible explanations for the existence of these links, which generally present a logical and at the same time emotional significance. The aim of this paper is to support the idea that the study of the link patterns among dream sources, in addition to being interesting from the cognitive viewpoint can be also useful for the therapeutic process. An interaction schema is described including four operators: the dreamer (patient), the therapist, the detector of possible links, and the proposer of plausible explanations. Two examples are given of application of this schema. (PsycINFO Database Record (c) 2012 APA, all rights reserved)Source: Dreaming (N.Y.N.Y.) 18 (2008): 139–157. doi:10.1037/a0012899
DOI: 10.1037/a0012899

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


2008 Book Unknown

Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry
Perner P., Salvetti O.
The automatic analysis of signals and images together with the characterization and elaboration of their representation features is still a challenging activity in many relevant scientific and hi-tech fields such as medicine, biotechnology, and chemistry. Multidimensional and multisource signal processing can generate a number of information patterns which can be useful to increase the knowledge of several domains for solving complex problems. Furthermore, advanced signal and image manipulation allows relating specific application problems into pattern recognition problems, often implying also the development of KDD and other computational intelligence procedures. Nevertheless, the amount of data produced by sensors and equipments used in biomedicine, biotechnology and chemistry is usually quite huge and structured, thus strongly pushing the need of investigating advanced models and efficient computational algorithms for automating mass analysis procedures. Accordingly, signal and image understanding approaches able to generate automatically expected outputs become more and more essential, including novel conceptual approaches and system architectures. The purpose of this third edition of the International Conference on Mass Data Analysis of Signals and Images in Medicine, Biotechnology, Chemistry and Food Industry (MDA 2008; www.mda-signals.de) was to present the broad and growing scientific evidence linking mass data analysis with challenging problems in medicine, biotechnology and chemistry. Scientific and engineering experts convened at the workshop to present the current understanding of image and signal processing and interpretation methods useful for facing various medical and biological problems and exploring the applicability and effectiveness of advanced techniques as solutions. The primary goal of the conference was to disseminate this knowledge to a multidisciplinary community and encourage cooperative proactive collaboration in all the interested fields. We were pleased to see that the idea of the conference was taken up by a growing number of researchers and that we could start to bundle the activities in this area. We appreciate the help and understanding of the editorial staff at Springer, and in particular Alfred Hofmann, who supported the publication of these proceedings in the LNAI series. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference. The next International Conferences on Mass Data Analysis of Signals and Images (www.mda-signals.de) will be held in July 2009. We are looking forward to your submissions.

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2008 Book Open Access OPEN

Human-Activity Analysis in Multimedia Data
Salvetti O., Cetin E. A., Pauwels E.
Many important applications in multimedia revolve around the detection of humans and the interpretation of their behavior. These include surveillance and intrusion detection, video conferencing applications, assisted living applications, and automatic analysis of sports videos, broadcasts, and movies, to name just a few. Success in these tasks often requires the integration of various sensor or data modalities such as video, audio, motion, and accompanying text, and typically hinges on a host of machine-learning methodologies to handle the inherent variability and complexity of the ensuing features. The computational efficiency of the resulting algorithms is critical since the amount of data to be processed in multimedia applications is typically large, and in real-time systems, speed is of the essence. There have been several recent special issues dealing with the dection of humans and the analysis of their activity relying solely on video footage. In this special issue, we have tried to provide a platform to contributions that make use of a broader spectrum of multimedia information, complementing video with audio or text information as well as other types of sensor signals, whenever available. The first group of papers in the special issue addresses the joint use of audio and video data. The paperDOI: 10.1155/2008/293453

See at: EURASIP Journal on Advances in Signal Processing Open Access | SpringerOpen Open Access | Bilkent University Institutional Repository Open Access | Repository CWI Amsterdam Open Access | DOI Resolver | link.springer.com | CNR People


2008 Book Unknown

Introduction to the issue on Signal Processing for Space Research and Astronomy
Leshem A., Christou J., Jeffs B. D., Kuruoglu E. E., Van Der Veen A.
SPACE research in general, and astronomy in particular, are some of the most challenging application areas for signal processing. Digital signal and image processing techniques have been widely used for optical astronomy and radio astronomy as well as in deep-space communication. Several new instruments are being designed for radio, optical, and other frequencies. These instruments will push our understanding of the universe even further and ambitious design goals for these instruments will rely on advanced signal processing techniques. Traditionally, radio telescope design was in the forefront of electrical engineering technology. Technological advances in the last decade have created possibilities for large distributed interferometric radio and optical telescopes with very large receiving areas, extremely large aperture, and a sensitivity which is one to two orders of magnitude better than the current generation. Increased sensitivity implies receiving more interfering signals; therefore, RFI detection and removal is now an important topic in radio astronomy. Fortunately, massive digital phased-array technology has also greatly advanced during this period and can provide increased flexibility to filter out interference as well as the possibility of directing multiple beams simultaneously. Several major, international research groups are working on next generations of phased-array instruments. The most ambitious one falls under the framework of the Square Kilometer Array programm (SKA), with a target commissioning date of 2020. A second instrument, which is a distributed phasedarray radio telescope is the Low Frequency Array (LOFAR) currently under construction in The Netherlands, and slated for 2009. The LOFAR design calls for an instrument consisting of about 13 000Source: New York: IEEE, 2008
DOI: 10.1109/JSTSP.2008.2006397

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2008 Article Unknown

Descriptive approach to medical image mining. An algorithmic scheme for analysis of cytological specimens
Gurevich I. B., Yashina V., Koryabkina I., Niemann H., Salvetti O.
The present paper is devoted the development and formal representation of a descriptive model for an information technology to automate the morphological analysis of cytologic preparations (a tumor of the lymphatic system). The theoretical basis of the model is a descriptive approach to image analysis and understanding and its main mathematical tools. Practical application of the algebraic tools of the descriptive approach is demonstrated, and the algorithmic scheme of the technology is described in the language of descriptive image algebras.Source: Pattern recognition and image analysis 18 (2008): 542–562. doi:10.1134/S1054661808040032
DOI: 10.1134/S1054661808040032

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2008 Article Unknown

Real-time tracking of sound parameters in a multimedia system
Bertini G., Magrini M., Lunardi S., Lucia G.
Modern multimedia performances and presentations offer innovative methods for user interaction, in order to be more appealing to the audience. Following this trend and in collaboration with VIS S.r.l. (an SME in Rome), the Institute of Information Sciences and Technology (ISTI-CNR) has developed a system called Pandora, which controls real-time video effects applied to filmed or synthesized scenes by means of parameters extracted from sound signals. The system can be used both for artistic interactive multimedia performances and also for other non-artistic applications.Source: ERCIM news 73 (2008): 46–47.
Project(s): EPOCH via OpenAIRE

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


2008 Conference object Unknown

A decision support resource as a kernel of a semantic Web based platform oriented to heart failure
Colantonio S., Martinelli M., Moroni D., Salvetti O., Candelieri A., Conforti D., Perticone F., Sciacqua A., Biniaris C., Marsh A.
Chronic heart failure (CHF) is a complex cardiovascular syndrome whose management requires a complex clinical program involving, at different levels, several care stakeholders and the integration and interpretation of a number of diagnostic data and information. Within the EU FP6 project HEARTFAID (www.heartfaid.org), an integrated platform of services is being developed to assist CHF stakeholders in their routine workflow and to provide an optimal management of CHF patients, by exploiting the most advanced technologies, compliant to medical standards, advanced instruments for diagnostic data processing, and significant and up-to-date knowledge, suitably formalized. The platform consists in a distributed and heterogeneous infrastructure developed by integrating different and functionally independent components according to the up-to-date service oriented technologies. A Knowledge-based Clinical Decision Support System (CDSS) constitutes the kernel of the platform and is aimed at aiding the decisional processes of CHF care givers. So far, the main functionalities of the platform and of the CDSS have been developed according to an accurate analysis of realistic clinical scenarios. Semantic web technologies are being used as the most advanced tools for formalizing, re-using and sharing medical knowledge, and reasoning on it; while a service oriented approach is being adopted for the integration and easy access to a number of users' applications. Main results are detailed and discussed in this paper.Source: The 2008 International Conference on Semantic Web and Web Service, pp. 111–117, Las Vegas, Nevada, US, 14-17, July 2008

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2008 Conference object Unknown

Alpha-stable statistical modeling and application of marginal price in electricity market
Chen Q., Chenchi L., Kuruoglu E. E., Yan Z.
In the electricity market, modeling marginal price facilitates to solve many problems in it. To model the probability density function (PDF) of system marginal price (SMP) in the spot market, positivism analysis on SMP PDF is presented in this paper. In contract to the weakness of some traditional probabilistic distribution model, an ? -stable distribution model that proposed in this paper, has a better adaptation of skewness and heavy tail effect manifested by electricity prices with the theoretical support of Generalized Central Limit Theorem (GCLT). Based on this new model, an equal probability bidding strategy for generation companies is proposed in this paper. Finally, a numerical example applying the actual data from PJM electricity market, proves our deduction that ? -stable distribution is more attractive, and the new bidding strategy not only increases the profit in selling electricity, but also decreases the risk in it.Source: China International Conference on Electricity Distribution, pp. 1–7, Guangzhou, China, 10-13 December 2008

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2008 Conference object Unknown

An intelligent and integrated platform for supporting the management of chronic heart failure patients
Colantonio S., Conforti D., Martinelli M., Moroni D., Perticone F., Salvetti O., Sciacqua A.
Within the EUFP6 project HEARTFAID, an integrated platform of services is being 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, compliant to medical standards, advanced instruments for diagnostic data processing, and significant and up-to-date knowledge, suitably formalized. The core of the platform intelligence is represented by a Knowledge based Clinical Decision Support System, which is aimed at making more effective and efficient all the processes related to chronic heart failure patients' management. In this paper, the current results of the platform development are reported and discussed.Source: Computers in Cardiology 2008, pp. 897–900, Bologna, Italy, 14-17 Settembre 2008

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2008 Conference object Unknown

CD and DVD preservation issues
Righi M.
This paper provides basic advice for CD/DVD archives maintenance.Source: AXMEDIS 2008, pp. 46, Florence, Italy, 17-19 novembre 2008

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2008 Conference object Unknown

Decision support and image & signal analysis in heart failure. A comprehensive use case
Colantonio S., Martinelli M., Moroni D., Salvetti O., Perticone F., Sciacqua A., Chiarugi F., Conforti D., Gualtieri A., Lagani V.
The European STREP project HEARTFAID aims at defining an innovative platform of services able to intelligently support clinical operators in the daily management of heart failure patients. The core of the platform intelligence is a Clinical Decision Support System, developed by integrating innovative knowledge representation techniques and hybrid reasoning methods, and including advanced tools for the analysis of diagnostic data, i.e. signals and images. Aiming at showing how all these issues are combined in the HEARTFAID platform, we present a comprehensive use case, centred on echocardiography workflow and covering the clinical course leading from visit scheduling to therapeutic choices, highlighting the intervention and the value added by the Clinical Decision Support System.Source: First International Conference on Health Informatics. HEALTHINF 2008, pp. 288, Funchal, Madeira, Portugal, 28-31 January 2008

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2008 Conference object Unknown

Descriptive Approach to Medical Image Analysis - Substantiation and Interpretation
Salvetti O., Gurevich I., Yashina V., Niemann H.
The paper is devoted to the development and formal representation of the descriptive model of information technology for automating morphologic analysis of cytological specimens (lymphatic system tumors). The main contributions are detailed description of algebraic constructions used for creating of mathematical model of information technology and its specification in the form of algorithmic scheme based on Descriptive Image Algebras. It is specified the descriptive model of an image recognition task and the stage of an image reduction to a recognizable from. The theoretical base of the model is the Descriptive Approach to Image Analysis and its main mathematical tools. It is demonstrated practical application of algebraic tools of the Descriptive Approach to Image Analysis and presented an algorithmic scheme of a technology implementing the apparatus of Descriptive Image Algebras.Source: First International Workshop on Image Mining: Theory and Applications (IMTA 2008), pp. 26–36, Funchal, Madeira, Portugal, 22-23 January 2008

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2008 Conference object Unknown

Evaluating a case-based classifier for biomedical applications
Little S., Salvetti O., Perner P.
Many medical diagnosis applications are characterized by datasets that contain under-represented classes due to the fact that the disease appears more rarely than the normal case. In such a situation classifiers that generalize over the data such as decision trees and Naïve Bayesian are not the proper choice as classification methods. Case-based classifiers that can work on the samples seen so far are more appropriate for such a task. We propose to calculate the contingency table and class specific evaluation measures despite the overall accuracy for evaluation purposes of classifiers for these specific data characteristics. We evaluate the different options of our case-based classifier and compare the performance to decision trees and Naïve Bayesian. Finally, we give an outlook for further work.Source: 21st IEEE International Symposium on Computer-Based Medical Systems, 2008, pp. 284–286, Jyväskylä, Finland, 17-19 June 2008
DOI: 10.1109/CBMS.2008.87

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


2008 Conference object Open Access OPEN

Framework for online superimposed event detection by sequential Monte Carlo methods
Urfalioglu O., Kuruoglu E. E., Cetin E.
In this paper, we consider online seperation and detection of superimposed events by applying particle filtering. We concentrate on a model where a background process, represented by a 1D-signal, is superimposed by an Auto-Regressive (AR) 'event signal', but the proposed approach is applicable in a more general setting. The activation and deactivation times of the event-signal are assumed to be unknown. We solve the online detection problem of this superpositional event by extending the state space dimension by one. The additional parameter of the state represents the AR-signal, which is zero when deactivated. Numerical experiments demonstrate the effectiveness of our approach.Source: IEEE International Conference on Acoustics, Speech and Signal Processing, 2008. ICASSP, pp. 2125–2128, Las Vegas, USA, March 31 - April 4 2008
DOI: 10.1109/ICASSP.2008.4518062

See at: Bilkent University Institutional Repository Open Access | DOI Resolver | ieeexplore.ieee.org | CNR People


2008 Conference object Unknown

Levy walk evolution for global optimization
Urfalioglu O., Cetin E., Kuruoglu E. E.
A novel evolutionary global optimization approach based on adaptive covariance estimation is proposed. The proposed method samples from a multivariate Levy Skew Alpha-Stable distribution with the estimated covariance matrix to realize a random walk and so to generate new solution candidates in the mutation step. The proposed method is compared to the popular Di erential Evolution method, which is one of the best general evolutionary global optimizers available. Experimental results indicate that the proposed approach yields a general improvement in the required number of function evaluations to solve global optimization problems. Especially, as shown in experiments, the underlying heavy tailed alpha-stable distribution enables a considerably more e ective global search in more complex problems.Source: Genetic and evolutionary computation conference, pp. 537–538, Atlanta, Georgia, USA, 12-16 Luglio 2008

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