2003
Journal article
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A simulation model for analyzing brain structures deformations
Di Bona S, Lutzemberger L, Salvetti O
Recent developments of medical software applications,from the simulation to the planning of surgical operations,have revealed the need for modelling human tissues and organs, not only from a geometric point of viewbut also from a physical one, i.e. soft tissues, rigid body, viscoelasticity, etc. This has given rise to the term 'deformable objects', which refers to objects with a morphology, a physical and a mechanical behaviour of their own and that reflects their natural properties. In this paper, we propose a model, based upon physical laws, suitable for the realistic manipulation of geometric reconstructions of volumetric data taken from MR and CT scans. In particular, a physically based model of the brain is presented that is able to simulate the evolution of different nature pathological intra-cranial phenomena such as haemorrhages, neoplasm, haematoma, etc and to describe the consequences that are caused by their volume expansions and the influences they have on the anatomical and neuro-functional structures of the brain.Source: PHYSICS IN MEDICINE AND BIOLOGY, vol. 48, pp. 4001-4002
Di Bona S, Lutzemberger L, Salvetti O
Recent developments of medical software applications,from the simulation to the planning of surgical operations,have revealed the need for modelling human tissues and organs, not only from a geometric point of viewbut also from a physical one, i.e. soft tissues, rigid body, viscoelasticity, etc. This has given rise to the term 'deformable objects', which refers to objects with a morphology, a physical and a mechanical behaviour of their own and that reflects their natural properties. In this paper, we propose a model, based upon physical laws, suitable for the realistic manipulation of geometric reconstructions of volumetric data taken from MR and CT scans. In particular, a physically based model of the brain is presented that is able to simulate the evolution of different nature pathological intra-cranial phenomena such as haemorrhages, neoplasm, haematoma, etc and to describe the consequences that are caused by their volume expansions and the influences they have on the anatomical and neuro-functional structures of the brain.Source: PHYSICS IN MEDICINE AND BIOLOGY, vol. 48, pp. 4001-4002
2003
Journal article
Open Access
Brain volumes characterization using hierarchical neural networks
Di Bona S, Niemann H, Pieri G, Salvetti O
Objective knowledge of tissue density distribution in CT/MRI brain datasets can be related to anatomical or neuro-functional regions for assessing pathologic conditions characterised by slight differences. The process of monitoring illness and its treatment could be then improved by a suitable detection of these variations. In this paper, we present an approach for three-dimensional (3D) classification of brain tissue densities based on a hierarchical artificial neural network (ANN) able to classify the single voxels of the examined datasets. The method developed was tested on case studies selected by an expert neuro-radiologist and consisting of both normal and pathological conditions. The results obtained were submitted for validation to a group of physicians and they judged thesystem to be really effective in practical applications.Source: ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 28 (issue 3), pp. 307-322
DOI: 10.1016/s0933-3657(03)00061-7
Metrics:
Di Bona S, Niemann H, Pieri G, Salvetti O
Objective knowledge of tissue density distribution in CT/MRI brain datasets can be related to anatomical or neuro-functional regions for assessing pathologic conditions characterised by slight differences. The process of monitoring illness and its treatment could be then improved by a suitable detection of these variations. In this paper, we present an approach for three-dimensional (3D) classification of brain tissue densities based on a hierarchical artificial neural network (ANN) able to classify the single voxels of the examined datasets. The method developed was tested on case studies selected by an expert neuro-radiologist and consisting of both normal and pathological conditions. The results obtained were submitted for validation to a group of physicians and they judged thesystem to be really effective in practical applications.Source: ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 28 (issue 3), pp. 307-322
DOI: 10.1016/s0933-3657(03)00061-7
Metrics:
See at:
ISTI Repository 
| Artificial Intelligence in Medicine 
| CNR IRIS | CNR IRIS | www.sciencedirect.com
2003
Journal article
Restricted
Monte Carlo Markov chain techniques for unsupervised MRF-based image denoising
Tonazzini A, Bedini L
This paper deals with discontinuity-adaptive smoothing for recovering degraded images,when Markov random ?eld models with explicit lines are used,but no a priori information about the free parameters of the related Gibbs distributions is available. The adopted approach is based on the maximization of the posterior distribution with respect to the line ?eld and the Gibbs parameters,while the intensity ?eld is assumed to be clamped to the maximizer of the posterior itself,conditioned on the lines and the parameters. This enables the application of a mixed-annealing algorithm for the maximum a posteriori (MAP) estimation of the image ?eld,and of Markov chain Monte Carlo techniques, over binary variables only, for the simultaneous maximum likelihood estimation of the parameters. A practical procedure is then derived which is nearly as fast as a MAP image reconstruction by mixed-annealing with known Gibbs parameters. We derive the method for the general case of a linear degradation process plus superposition of additive noise,and experimentally validate it for the sub-case of image denoising.Source: PATTERN RECOGNITION LETTERS, vol. 24, pp. 55-64
DOI: 10.1016/s0167-8655(02)00188-5
Metrics:
Tonazzini A, Bedini L
This paper deals with discontinuity-adaptive smoothing for recovering degraded images,when Markov random ?eld models with explicit lines are used,but no a priori information about the free parameters of the related Gibbs distributions is available. The adopted approach is based on the maximization of the posterior distribution with respect to the line ?eld and the Gibbs parameters,while the intensity ?eld is assumed to be clamped to the maximizer of the posterior itself,conditioned on the lines and the parameters. This enables the application of a mixed-annealing algorithm for the maximum a posteriori (MAP) estimation of the image ?eld,and of Markov chain Monte Carlo techniques, over binary variables only, for the simultaneous maximum likelihood estimation of the parameters. A practical procedure is then derived which is nearly as fast as a MAP image reconstruction by mixed-annealing with known Gibbs parameters. We derive the method for the general case of a linear degradation process plus superposition of additive noise,and experimentally validate it for the sub-case of image denoising.Source: PATTERN RECOGNITION LETTERS, vol. 24, pp. 55-64
DOI: 10.1016/s0167-8655(02)00188-5
Metrics:
See at:
Pattern Recognition Letters | CNR IRIS | CNR IRIS | www.sciencedirect.com
2003
Journal article
Unknown
Preliminary results on the foraging ecology of Balearic shearwaters (Puffinus mauretanicus) from bird-borne data loggers
Aguilar J. S., Benvenuti S., Dall'Antonia L., Mcminn-Grivè M., Mayol-Serra J.
A data logger devised and manufactured by our research team in order to study the homing routes of carrier pigeons was subsequently modified to study the homing and foraging strategies of breeding marine birds. Recent versions of the data logger, equipped with a flight sensor and depth meter or saltwater switch, were used in a study of the foraging strategies of chick-rearing Balearic shearwaters (Puffinus mauretanicus) in the framework of the project LIFE-Puffinus financed by the Balearic Government amd the EU. Due to low recapture rates (only 3 out of 6 tagged birds were recovered), only preliminary data from a small sample are available. Data loggers have recorded data on the pattern of nest attendance (including departure time to foraging trips and return time) and the diurnal pattern of flight and dive activity (including depth and duration of dives). Despite the small sample size, the results show that our data loggers can successfully be applied to the study of the breeding biology and foraging ecology - including the diving pattern-of Balearic shearwaters and similar speciesSource: Scientia marina 67 (2003): 129–134.
Aguilar J. S., Benvenuti S., Dall'Antonia L., Mcminn-Grivè M., Mayol-Serra J.
A data logger devised and manufactured by our research team in order to study the homing routes of carrier pigeons was subsequently modified to study the homing and foraging strategies of breeding marine birds. Recent versions of the data logger, equipped with a flight sensor and depth meter or saltwater switch, were used in a study of the foraging strategies of chick-rearing Balearic shearwaters (Puffinus mauretanicus) in the framework of the project LIFE-Puffinus financed by the Balearic Government amd the EU. Due to low recapture rates (only 3 out of 6 tagged birds were recovered), only preliminary data from a small sample are available. Data loggers have recorded data on the pattern of nest attendance (including departure time to foraging trips and return time) and the diurnal pattern of flight and dive activity (including depth and duration of dives). Despite the small sample size, the results show that our data loggers can successfully be applied to the study of the breeding biology and foraging ecology - including the diving pattern-of Balearic shearwaters and similar speciesSource: Scientia marina 67 (2003): 129–134.
See at: CNR ExploRA
2003
Journal article
Restricted
Skewed alpha-stable distributions for modelling textures
Kuruoglu Ee, Zerubia J
In this letter, we introduce a novel family of texture models which provide alternatives to texture models which are based on Gaussian distributions. In particular, we introduce linear textures generated with a member of the alpha-stable distribution family which is a generalisation of the Gaussian distribution. The new family of texture models is capable of representing both impulsive and unsymmetric (skewed) image data which cannot be accommodated by the Gaussian model. We present new techniques for texture model estimation and we demonstrate the success of the techniques on synthetic data.Source: PATTERN RECOGNITION LETTERS, vol. 24, pp. 339-348
Kuruoglu Ee, Zerubia J
In this letter, we introduce a novel family of texture models which provide alternatives to texture models which are based on Gaussian distributions. In particular, we introduce linear textures generated with a member of the alpha-stable distribution family which is a generalisation of the Gaussian distribution. The new family of texture models is capable of representing both impulsive and unsymmetric (skewed) image data which cannot be accommodated by the Gaussian model. We present new techniques for texture model estimation and we demonstrate the success of the techniques on synthetic data.Source: PATTERN RECOGNITION LETTERS, vol. 24, pp. 339-348
2003
Journal article
Unknown
SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling
Achim A., Tsakalides P., Bezerianos A.
Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. This paper proposes a novel Bayesian-based algorithm within the framework of wavelet analysis, which reduces speckle in SAR images while preserving the structural features and textural information of the scene. First, we show that the subband decompositions of logarithmically transformed SAR images are accurately modeled by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we exploit this a priori information by designing a maximum a posteriori (MAP) estimator. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to current state-of-the-art soft thresholding techniques applied on real SAR imagery and we quantify the achieved performance improvement.Source: IEEE transactions on geoscience and remote sensing 41 (2003): 1773–1784.
Achim A., Tsakalides P., Bezerianos A.
Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. This paper proposes a novel Bayesian-based algorithm within the framework of wavelet analysis, which reduces speckle in SAR images while preserving the structural features and textural information of the scene. First, we show that the subband decompositions of logarithmically transformed SAR images are accurately modeled by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we exploit this a priori information by designing a maximum a posteriori (MAP) estimator. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to current state-of-the-art soft thresholding techniques applied on real SAR imagery and we quantify the achieved performance improvement.Source: IEEE transactions on geoscience and remote sensing 41 (2003): 1773–1784.
See at: CNR ExploRA
2003
Journal article
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Source separation in astrophysical maps using independent factor analysis
Kuruoglu Ee, Bedini L, Paratore Mt, Salerno E, Tonazzini A
A microwave sky map results from a combination of signals from various astrophysical sources, such as cosmic microwave background radiation, synchrotron radiation and galactic dust radiation. To derive information about these sources, one needs to separate them from the measured maps on different frequency channels. Our insufficient knowledge of the weights to be given to the individual signals at different frequencies makes this a difficult task. Recent work on the problem led to only limited success due to ignoring the noise and to the lack of a suitable statistical model for the sources. In this paper, we derive the statistical distribution of some source realizations, and check the appropriateness of a Gaussian mixture model for them. A source separation technique, namely, independent factor analysis, has been suggested recently in the literature for Gaussian mixture sources in the presence of noise. This technique employs a three layered neural network architecture which allows a simple, hierarchical treatment of the problem. We modify the algorithm proposed in the literature to accommodate for space-varying noise and test its performance on simulated astrophysical maps. We also compare the performances of an expectation-maximization and a simulated annealing learning algorithm in estimating the mixture matrix and the source model parameters. The problem with expectation-maximization is that it does not ensure global optimization, and thus the choice of the starting point is a critical task. Indeed, we did not succeed to reach good solutions for random initializations of the algorithm. Conversely, our experiments with simulated annealing yielded initialization-independent results. The mixing matrix and the means and coefficients in the source model were estimated with a good accuracy while some of the variances of the components in the mixture model were not estimated satisfactorily.Source: NEURAL NETWORKS, vol. 16, pp. 479-491
Kuruoglu Ee, Bedini L, Paratore Mt, Salerno E, Tonazzini A
A microwave sky map results from a combination of signals from various astrophysical sources, such as cosmic microwave background radiation, synchrotron radiation and galactic dust radiation. To derive information about these sources, one needs to separate them from the measured maps on different frequency channels. Our insufficient knowledge of the weights to be given to the individual signals at different frequencies makes this a difficult task. Recent work on the problem led to only limited success due to ignoring the noise and to the lack of a suitable statistical model for the sources. In this paper, we derive the statistical distribution of some source realizations, and check the appropriateness of a Gaussian mixture model for them. A source separation technique, namely, independent factor analysis, has been suggested recently in the literature for Gaussian mixture sources in the presence of noise. This technique employs a three layered neural network architecture which allows a simple, hierarchical treatment of the problem. We modify the algorithm proposed in the literature to accommodate for space-varying noise and test its performance on simulated astrophysical maps. We also compare the performances of an expectation-maximization and a simulated annealing learning algorithm in estimating the mixture matrix and the source model parameters. The problem with expectation-maximization is that it does not ensure global optimization, and thus the choice of the starting point is a critical task. Indeed, we did not succeed to reach good solutions for random initializations of the algorithm. Conversely, our experiments with simulated annealing yielded initialization-independent results. The mixing matrix and the means and coefficients in the source model were estimated with a good accuracy while some of the variances of the components in the mixture model were not estimated satisfactorily.Source: NEURAL NETWORKS, vol. 16, pp. 479-491
2003
Conference article
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About the role of mapping in gesture-controlled live computer music
Tarabella L, Bertini G
Interactive computer music proposes a number of considerations about what the audience experiences in relationship of what-is-going-on-on-stage and the overall musical result. While a traditional music instrument is a compact tool and 'to play an instrument' has a precise meaning for everybody, the new electro-acoustic instrument is a system consisting of a number of spread out components: sensors and controllers, computer and electronic sound generators, amplifiers and loudspeakers. How to link information between the various parts of this exploded instrument is deeply correlated to new modalities of composing and performing in relationship with how the audience perceives and accepts these new paradigm. We here report our point of view and considerations about the role of 'mapping' derived from our experience both in developing original controllers and in the realization of interactive electro-acoustic performances.DOI: 10.1007/978-3-540-39900-1_19
Metrics:
Tarabella L, Bertini G
Interactive computer music proposes a number of considerations about what the audience experiences in relationship of what-is-going-on-on-stage and the overall musical result. While a traditional music instrument is a compact tool and 'to play an instrument' has a precise meaning for everybody, the new electro-acoustic instrument is a system consisting of a number of spread out components: sensors and controllers, computer and electronic sound generators, amplifiers and loudspeakers. How to link information between the various parts of this exploded instrument is deeply correlated to new modalities of composing and performing in relationship with how the audience perceives and accepts these new paradigm. We here report our point of view and considerations about the role of 'mapping' derived from our experience both in developing original controllers and in the realization of interactive electro-acoustic performances.DOI: 10.1007/978-3-540-39900-1_19
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com
2003
Journal article
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Reversal of visual impairment in patients with retinis pigmentosa after administration of glutathione peroxidase enzyme
Ammannati P, Giordani R, Chimenti M
The glutathione peroxidase enzyme (GPX) administration effects have been studied in patients with retinitis pigmentosa (RP). RP at present is defined as a degenerative, progressive and irreversible one. It was found that in RP patients there was a decrease of GPX level in respect to normal subjects. Moreover in rabbits it was shown that retrobulbar administration of GPX prevents the abolition of the electroretinogram due to previous administration of an oxidant agent as AgNO. On the basis of the results obtained, it was hypothesized that a deficit of reducing enzyme of the pentose phosphate pathway may binder the regeneration of the pigment modified by the oxidation process due to light that hits the retina. This process can bring to a pathological increase of the epithelial pigmentation. It was decided to investigate the potential effect of the replacement therapy with GPX administration. The number of patients is 7636 and their cumulative data are reported. The treatment was administration of one I.U. of GPX in retrobulbar fat, for three consecutive days each month, for three consecutive months, in each eye. We measured the visual acuity, the peripheral retinal fields and ERG before and after therapy. After completion of therapy over the 90% of the patients showed a significant clinical improvement, confirmed by the measured parameters. The amelioration for visual acuity ranged from 1/10 (R.E.) to no variation (L.E.) to 68% in both eyes. ERG, extinct in about 98% the patients, presented an improvement from a normal morphology with a very reduced voltage to a normal voltage and morphology. These results have been stable for the 6 years of follow-up. The results support the hypothesis that a deficit of GPX may play an important role in the pathophysiology of RP. These results conduct to consider that the pentose phosphate pathway is essential for the retina correct metabolism and function.
Ammannati P, Giordani R, Chimenti M
The glutathione peroxidase enzyme (GPX) administration effects have been studied in patients with retinitis pigmentosa (RP). RP at present is defined as a degenerative, progressive and irreversible one. It was found that in RP patients there was a decrease of GPX level in respect to normal subjects. Moreover in rabbits it was shown that retrobulbar administration of GPX prevents the abolition of the electroretinogram due to previous administration of an oxidant agent as AgNO. On the basis of the results obtained, it was hypothesized that a deficit of reducing enzyme of the pentose phosphate pathway may binder the regeneration of the pigment modified by the oxidation process due to light that hits the retina. This process can bring to a pathological increase of the epithelial pigmentation. It was decided to investigate the potential effect of the replacement therapy with GPX administration. The number of patients is 7636 and their cumulative data are reported. The treatment was administration of one I.U. of GPX in retrobulbar fat, for three consecutive days each month, for three consecutive months, in each eye. We measured the visual acuity, the peripheral retinal fields and ERG before and after therapy. After completion of therapy over the 90% of the patients showed a significant clinical improvement, confirmed by the measured parameters. The amelioration for visual acuity ranged from 1/10 (R.E.) to no variation (L.E.) to 68% in both eyes. ERG, extinct in about 98% the patients, presented an improvement from a normal morphology with a very reduced voltage to a normal voltage and morphology. These results have been stable for the 6 years of follow-up. The results support the hypothesis that a deficit of GPX may play an important role in the pathophysiology of RP. These results conduct to consider that the pentose phosphate pathway is essential for the retina correct metabolism and function.
See at:
CNR IRIS | CNR IRIS | www.acm.org
2003
Journal article
Open Access
A machine vision system controlling the cutting of animal hide
Fantini E, Ganovelli F, Pingi P
Based on the integration of image acquisition techniques and real-time systems, an innovative system for cutting raw hides has been developed at ISTI-CNR. The aim is to partly automate the cutting process, so that minimal human intervention is needed. The current procedure for cutting animal hide is completely manual. The hide is spread out on a bench and expert operators decide the best cutting lines on the basis of the location of specific features. The hide is then manually cut using ad hoc knives and the parts are removed from the bench. The work of cutting the hide is the most time consuming step, and requires three or four workers.Source: ERCIM NEWS, vol. 55, pp. 32-33
Fantini E, Ganovelli F, Pingi P
Based on the integration of image acquisition techniques and real-time systems, an innovative system for cutting raw hides has been developed at ISTI-CNR. The aim is to partly automate the cutting process, so that minimal human intervention is needed. The current procedure for cutting animal hide is completely manual. The hide is spread out on a bench and expert operators decide the best cutting lines on the basis of the location of specific features. The hide is then manually cut using ad hoc knives and the parts are removed from the bench. The work of cutting the hide is the most time consuming step, and requires three or four workers.Source: ERCIM NEWS, vol. 55, pp. 32-33
2003
Journal article
Open Access
Una Stella nel Battistero di Pisa
Tarabella L
A computer analysis on the reverberation characteristics of Pisa Baptistery and the studies about the symmetries of the Monuments of the whole Piazza dei Miracoli in Pisa by the american mathematician David Speiser, led to the discovery of a suggestive reference frame used for designing and building the Baptistery: everthing here is based on the golden number, the regular pentagon and, finally, a star.
Tarabella L
A computer analysis on the reverberation characteristics of Pisa Baptistery and the studies about the symmetries of the Monuments of the whole Piazza dei Miracoli in Pisa by the american mathematician David Speiser, led to the discovery of a suggestive reference frame used for designing and building the Baptistery: everthing here is based on the golden number, the regular pentagon and, finally, a star.
2003
Journal article
Open Access
Scene understanding using hierarchical neural networks
Pieri G, Salvetti O
Scientists at ISTI-CNR are using Hierarchical Neural Networks in order to develop a methodology for the automatic identification of characteristic patterns ) - representative of particular phenomena - in a given scene. This approach can be adopted in a wide range of applications.Source: ERCIM NEWS, vol. 52, p. 52
Pieri G, Salvetti O
Scientists at ISTI-CNR are using Hierarchical Neural Networks in order to develop a methodology for the automatic identification of characteristic patterns ) - representative of particular phenomena - in a given scene. This approach can be adopted in a wide range of applications.Source: ERCIM NEWS, vol. 52, p. 52
2003
Journal article
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Real-time detection and clinical categorisation of ultrasound high intensity transient signal
Barcaro U, Di Bona S, Fontanelli R, La Manna S, Orlandi G, Salvetti O, Sartucci F
In this paper we address the problem of interpreting ultrasound images obtained from doppler devices in order to classify, and hence to distinguish, the dangerous cerebral microemboli from the innocuous ones. In order to obtain an automatic categorisation of the cerebral high intensity transient signal, a multilevel neural network based on a hierarchical architecture has been implemented for image processing and classification. The images, obtained by measuring the blood flow velocities in brain arteries and veins,have been acquired using the 'Multi Dop X4' ultrasound device by DWL. The approach proposed, applied to real clinical cases selected by expert neurologists for their peculiar characteristics, has shown to be a valid real-time support for the diagnosis of cerebral vascular diseasesSource: WSEAS TRANSACTIONS ON SYSTEMS, vol. 2, pp. 921-926
Barcaro U, Di Bona S, Fontanelli R, La Manna S, Orlandi G, Salvetti O, Sartucci F
In this paper we address the problem of interpreting ultrasound images obtained from doppler devices in order to classify, and hence to distinguish, the dangerous cerebral microemboli from the innocuous ones. In order to obtain an automatic categorisation of the cerebral high intensity transient signal, a multilevel neural network based on a hierarchical architecture has been implemented for image processing and classification. The images, obtained by measuring the blood flow velocities in brain arteries and veins,have been acquired using the 'Multi Dop X4' ultrasound device by DWL. The approach proposed, applied to real clinical cases selected by expert neurologists for their peculiar characteristics, has shown to be a valid real-time support for the diagnosis of cerebral vascular diseasesSource: WSEAS TRANSACTIONS ON SYSTEMS, vol. 2, pp. 921-926
2003
Journal article
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A multilevel neural approach to dynamic scene analysis
Di Bona S, Salvetti O
A neural network architecture is presented for monitoring events coded in image time sequences. The image sequence defines the sampling of high frequency phenomena where only morphological aspects of the scene are taken into account. In particular a model for implementing a hierarchical neural network architecture is proposed. Preliminary results are shown in the study of the oscillation states in the flame front of the power plant gas combustors.Source: PATTERN RECOGNITION AND IMAGE ANALYSIS, vol. 13, pp. 86-89
Di Bona S, Salvetti O
A neural network architecture is presented for monitoring events coded in image time sequences. The image sequence defines the sampling of high frequency phenomena where only morphological aspects of the scene are taken into account. In particular a model for implementing a hierarchical neural network architecture is proposed. Preliminary results are shown in the study of the oscillation states in the flame front of the power plant gas combustors.Source: PATTERN RECOGNITION AND IMAGE ANALYSIS, vol. 13, pp. 86-89
2003
Journal article
Open Access
Quando l'astrofisica chiede aiuto all'informatica. L'analisi dei dati astrofisici ha bisogno della ricerca informatica più avanzata
Salerno E
L'elaborazione statistica dei segnali sia avvia ad assumere un ruolo chiave nello studio del nostro Universo. Molti problemi dell'astrofisica sono infatti legati alla possibilità di discriminare tra teorie in competizione nell'affascinante impresa di comprenderne la nascita, l'evoluzione e il destino, e un loro aspetto comune è che l'informazione utile si deve estrarre da insiemi di dati di dimensione enorme e affetti da notevoli errori. Dal punto di vista informatico si tratta di 'data mining', ossia di ricerca di informazione nascosta. Un caso in cui oggi si deve ricorrere a tecniche di data mining è rappresentato dallo studio della radiazione cosmica di fondo.
Salerno E
L'elaborazione statistica dei segnali sia avvia ad assumere un ruolo chiave nello studio del nostro Universo. Molti problemi dell'astrofisica sono infatti legati alla possibilità di discriminare tra teorie in competizione nell'affascinante impresa di comprenderne la nascita, l'evoluzione e il destino, e un loro aspetto comune è che l'informazione utile si deve estrarre da insiemi di dati di dimensione enorme e affetti da notevoli errori. Dal punto di vista informatico si tratta di 'data mining', ossia di ricerca di informazione nascosta. Un caso in cui oggi si deve ricorrere a tecniche di data mining è rappresentato dallo studio della radiazione cosmica di fondo.
2003
Journal article
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Automatic monitoring of states evolution in dinamic scene supervision
Di Bona S, Salvetti O
A neural network model is presented for monitoring events coded in image sequences. The image sequences define the sampling of high frequency space/time changeable phenomena where both the morphological and densitometric aspects of the scene are taken into account. In this frame, a model for implementing a multilevel neural network architecture is proposed. This model is tested in the field of power production for monitoring the combustion instability degree in power plant gas combustors. The main goal of this study is both to provide a support for preventing the oscillation states in the combustor's flame front and to characterise the instability itself. The work has been developed within a collaboration with ENEL Production and Research S.p.A. (Italian National Department for Electric Power), that supplied the study cases and the technical support for conducting the experiments. The preliminary results obtained show the effectiveness of the approach proposed.Source: PATTERN RECOGNITION AND IMAGE ANALYSIS, vol. 13, pp. 495-504
Di Bona S, Salvetti O
A neural network model is presented for monitoring events coded in image sequences. The image sequences define the sampling of high frequency space/time changeable phenomena where both the morphological and densitometric aspects of the scene are taken into account. In this frame, a model for implementing a multilevel neural network architecture is proposed. This model is tested in the field of power production for monitoring the combustion instability degree in power plant gas combustors. The main goal of this study is both to provide a support for preventing the oscillation states in the combustor's flame front and to characterise the instability itself. The work has been developed within a collaboration with ENEL Production and Research S.p.A. (Italian National Department for Electric Power), that supplied the study cases and the technical support for conducting the experiments. The preliminary results obtained show the effectiveness of the approach proposed.Source: PATTERN RECOGNITION AND IMAGE ANALYSIS, vol. 13, pp. 495-504
2003
Conference article
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Performing SPICE assessments: yet another tool
Fabbrini F, Fantini E, Fusani M, Lami G
In this paper we first discuss the requirements that a SPICE assessment must satisfy to fulfill the needs of different stakeholders, then the requirements an automatic tools has to satisfy in order to be able to provide a real support in the different phases an assessment is composed of. We present also a new tool we developed at the I.S.T.I. that has been designed by following an innovative approach. This tool is able to provide support also in some phases of a SPICE assessment not affected by the existing tools. Finally, we show the strengths of the tool and we discuss its weaknesses and usage risks.
Fabbrini F, Fantini E, Fusani M, Lami G
In this paper we first discuss the requirements that a SPICE assessment must satisfy to fulfill the needs of different stakeholders, then the requirements an automatic tools has to satisfy in order to be able to provide a real support in the different phases an assessment is composed of. We present also a new tool we developed at the I.S.T.I. that has been designed by following an innovative approach. This tool is able to provide support also in some phases of a SPICE assessment not affected by the existing tools. Finally, we show the strengths of the tool and we discuss its weaknesses and usage risks.
2003
Conference article
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Pozitif alfa-kararli olasilik yogunluk fonksiyonu icin analitik bir yaklastirma
Kuruoglu Ee
Bu makelede, genelde analitik bir ifadeye sahip olmayan pozitif alpha-kararli olasilik yogunluk fonksiyonu icin analitik bir yaklastirma 'oneriyoruz. 'Onerdigimiz yaklastirma, pozitif alpha-kararli rastsal degiskenlerin Pearson ve diger bir pozitif alpha-kararli dagilima c'oz'umlenmesine dayanmakta. Bu c'oz'umleme herhangi bir pozitif alpha-kararli dagilimin birer Pearson karisimi seklinde ifade edilebilmesini saglamakta.
Kuruoglu Ee
Bu makelede, genelde analitik bir ifadeye sahip olmayan pozitif alpha-kararli olasilik yogunluk fonksiyonu icin analitik bir yaklastirma 'oneriyoruz. 'Onerdigimiz yaklastirma, pozitif alpha-kararli rastsal degiskenlerin Pearson ve diger bir pozitif alpha-kararli dagilima c'oz'umlenmesine dayanmakta. Bu c'oz'umleme herhangi bir pozitif alpha-kararli dagilimin birer Pearson karisimi seklinde ifade edilebilmesini saglamakta.
See at:
CNR IRIS | CNR IRIS | siu2003.eng.ku.edu.tr
2003
Conference article
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The OBJECT-ORIENTED pureCMusic FRAMEWORK
Tarabella L
The Object-Oriented pureCMusic (OO-pCM) framework gives the possibility to write a piece of music in terms of an algorithmic-composition-based program (also controlled by data streaming from external controllers) and of synthesis algorithms. Everything is written following the C language syntax and compiled into machine code that runs at CPU speed. The framework provides a number of functions for sound processing, for generating complex events and for managing external data coming from standard Midi controllers and/or other special gesture interfaces.
Tarabella L
The Object-Oriented pureCMusic (OO-pCM) framework gives the possibility to write a piece of music in terms of an algorithmic-composition-based program (also controlled by data streaming from external controllers) and of synthesis algorithms. Everything is written following the C language syntax and compiled into machine code that runs at CPU speed. The framework provides a number of functions for sound processing, for generating complex events and for managing external data coming from standard Midi controllers and/or other special gesture interfaces.
2003
Conference article
Restricted
The pCM framework for realtime sound and music generation
Tarabella L
This programming framework gives the possibility to write a piece of music in terms of synthesis algorithms, score and management of data streaming from external interfaces. The pCM framework falls into the category of the 'embedded music language' and has been implemented under the Metrowerks' Code Warrior C-compiler. I started to write a very basic library of functions for sound processing and for driving the gesture interfaces realized at cART project of CNR, Pisa. In the long run the library became a very efficient, stable and powerful framework based on pure C programming, that is 'pure-C-Music', or pCM.
Tarabella L
This programming framework gives the possibility to write a piece of music in terms of synthesis algorithms, score and management of data streaming from external interfaces. The pCM framework falls into the category of the 'embedded music language' and has been implemented under the Metrowerks' Code Warrior C-compiler. I started to write a very basic library of functions for sound processing and for driving the gesture interfaces realized at cART project of CNR, Pisa. In the long run the library became a very efficient, stable and powerful framework based on pure C programming, that is 'pure-C-Music', or pCM.