1,721,082 research outputs found
Il ruolo della struttura semantica e della composizione morfologica nell'accuratezza di decodifica:dislessici evolutivi e normolettori a confronto.
No full textNello specifico, il nostro lavoro di ricerca si propone di valutare l’influenza
degli indizi contestuali sull’accuratezza di decodifica (corretto posizionamento
dell’accento) del dislessico evolutivo e del normolettore confrontando due principali condizioni: assenza e presenza di disponibilità
contestuale. In aggiunta, nell’ottica di effettuare una specifica indagine
linguistica, l’intento è anche quello di analizzare l’influenza della composizione
sillabico-accentuale, sull’accuratezza di decodifica (corretto posizionamento
dell’accento) dei due gruppi di soggetti (Mulatti e Job, 2003; Marcolini
e Burani, 2003; Burani, Barca e Ellis, 2006; Marcolini, Donato, Stella
e Burani, 2006; Barca, Ellis e Burani, 2007). A tal proposito, sappiamo che,
nella maggior parte delle parole italiane, l’accento è collocato sulla vocale
della penultima sillaba (accentazione regolare: ballàre); più rara è invece
la condizione che vede l’accento collocato sulla vocale della terzultima sillaba
(accentazione irregolare: cèlebre)
Special issue on signal processing and machine learning for biomedical data
Full text linkThis Special Issue is focused on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems. Biomedical data play a fundamental role in many fields of research and clinical practice. Very often the complexity of these data and their large volume makes it necessary to develop advanced analysis techniques and systems. Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging, requires new signal processing and machine learning methods. The recent progress in machine learning techniques, and in particular deep learning, revolutionized various fields of artificial vision, significantly pushing the state of the art of artificial vision systems into a wide range of high-level tasks. Such progress can help address problems in the analysis of biomedical data.This Special Issue placed particular emphasis on contributions dealing with practical, applications-led research, on the use of methods and devices in clinical diagnosis. The works that make up this special issue show a remarkable variety of applications for the detection and classification of medical imaging problems. In particular, the aforementioned works can be divided on the basis of types of techniques used, into three categories—signal processing (SP) methods, traditional machine learning (ML) methods, and deep learning (DL) methods
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
La sensibilità agli indizi semantici e alla struttura morfologica della parola: un confronto tra dislessici evolutivi e normolettori
No full textAppropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A Microcalcification Detection System in Mammograms based on ANN Clustering
No full textBreast cancer is one of the leading causes to women mortality in the world. Clustered microcalcifications (MCs) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. In this work, we present a novel method for the detection of MCs in mammograms which consists of regions of Interest (ROIs) segmentation, based on a spatial filter that allows the detection of small and large microcalcifications, clustering and classification of MCs by Artificial Neural Network. The system has been tested on a public dataset of digital images and compared with previous approaches. The results demonstrate that the proposed approach could achieve significantly higher FROC curves: our CAD system achieve a cluster-based sensitivity of 70, 80, and 90 % at 0.31, 0.69, and 1.6 FPs/image, respectively
OPERATIONAL CHARACTERISTICS OF A LIM ORIENTED FOR METROPOLITAN OR SUBURBAN TRANSPORTATION
No full textHEp-2 intensity classification based on deep fine-tuning
No full textThe classification of HEp-2 images, conducted through Indirect ImmunoFluorescence (IIF) gold standard method, in the positive / negative classes, is the first step in the diagnosis of autoimmune diseases. Since the test is often difficult to interpret, the research world has been looking for technological features for this problem. In recent years the methods of deep learning have overcome the other machine learning techniques in their effectiveness and robustness, and now they prevail in artificial intelligence studies. In this context, CNNs have played a significant role especially in the biomedical field. In this work we analysed the capabilities of CNN for fluorescence classification of HEp-2 images. To this end, the GoogLeNet pre-trained network was used. The method was developed and tested using the public database A.I.D.A. For the analysis of pre-trained network, the two strategies were used: as features extractors (coupled with SVM classifiers) and after fine-tuning. Performance analysis was conducted in terms of ROC (Receiver Operating Characteristic) curve. The best result obtained with the fine-tuning method showed an excellent ability to discriminate between classes, with an area under the ROC curve (AUC) of 98.4% and an accuracy of 93%. The classification result using the CNN as features extractor obtained 97.3% of AUC, showing a difference in performance between the two strategies of little significance
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