1,721,410 research outputs found
Using keyword spotting systems as tools for the transcription of historical handwritten documents: Models and procedures for performance evaluation
No full textThe paper proposes a performance model for estimating the improvement of the time needed to transcribe small collections of handwritten documents by using a keyword spotting system (KWS) with respect to the time for manually achieving the transcription. The proposed model assumes that no other information than those obtained from the samples and the KWS system performance on the training set are available, and, depending on them, establishes analytically the condition the performance measures must satisfy to make it profitable to use the system, and, in the affirmative case, estimates the gain and the accuracy of such estimation. The model is complemented by a step-by-step procedure for building the training set, running the KWS on it, estimating the performance parameters on the data set, and eventually estimating the overall improvement and the accuracy of this estimate
Infrared synchrotron radiation spectroscopy and microspectroscopy: new tools for interdisciplinary applications
No full textOptical performances of SINBAD, the Synchrotron INfrared Beamline At DANE. 22, J) CESTELLI GUIDI, M., PICCININI, M., MARCELLI, A., NUCARA, A., CALVANI, P., BURATTINI. E.,
No full textSINBAD (Synchrotron Infrared Beamline At DANE) is the first Italian synchrotron radiation beamline operating in the infrared range. It collects the radiation emitted by DANE, an electron-positron collider designed to work at 0.51 GeV with a beam current I > 1 A. Here, the actual performances of the beamline, in terms of brilliance gain with respect to black bodies and polarization properties, are presented and discussed. Finally, the stability of the SINBAD source, a critical issue for Fourier transform infrared spectroscopy, is discussed
High performance liquid chromatography electrospray ionisation and atmospheric pressure chemical ionisation mass spectrometry for the analysis of butylated amino resins
No full textEtherified amino resins are used in conjunction with alkyds, polyesters, epoxy or acrylic resins in coating formulation. They are formed from the reaction between formaldehyde and compounds containing NH2 groups, for example, amide, amine or imide groups. Control of this reaction is important in order to obtain the appropriate mixture targeted for the intended use and, as a consequence, the development of analytical procedures able to describe the different species present in the final resin mixtures is necessary. The use of high-performance liquid chromatography, coupled with electrospray ionisation or atmospheric pressure chemical ionisation mass spectrometry, proved to be efficient in the characterisation of n-butylated melamine-formaldehyde resins. The same analytical approach was also applied to describe the first steps in the synthesis of i-butylated urea-formaldehyde resins
The onset of motor learning impairments in Parkinson’s disease: a computational investigation
No full text: The basal ganglia (BG) is part of a basic feedback circuit regulating cortical function, such as voluntary movements control, via their influence on thalamocortical projections. BG disorders, namely Parkinson's disease (PD), characterized by the loss of neurons in the substantia nigra, involve the progressive loss of motor functions. At the present, PD is incurable. Converging evidences suggest the onset of PD-specific pathology prior to the appearance of classical motor signs. This latent phase of neurodegeneration in PD is of particular relevance in developing more effective therapies by intervening at the earliest stages of the disease. Therefore, a key challenge in PD research is to identify and validate markers for the preclinical and prodromal stages of the illness. We propose a mechanistic neurocomputational model of the BG at a mesoscopic scale to investigate the behavior of the simulated neural system after several degrees of lesion of the substantia nigra, with the aim of possibly evaluating which is the smallest lesion compromising motor learning. In other words, we developed a working framework for the analysis of theoretical early-stage PD. While simulations in healthy conditions confirm the key role of dopamine in learning, in pathological conditions the network predicts that there may exist abnormalities of the motor learning process, for physiological alterations in the BG, that do not yet involve the presence of symptoms typical of the clinical diagnosis
Design-based estimation of mark variograms in forest ecosystem surveys
No full textMark variograms are widely adopted in forest ecosystem studies for analyzing spatial interaction among trees. Inference on mark variograms can be performed under a model-dependent perspective (ergodic variograms) or under a deterministic perspective (non-ergodic variograms). A simple and workable definition of non-ergodic mark variogram is introduced based on distances between pairs of trees distinguished by distance classes. Design-based estimators of mark variogram values are proposed as the ratio of two Horvitz-Thompson estimators using replicated plots randomly located on the study area and making use of the inclusion probabilities of the pairs of trees. Jackknife estimators of their variances are considered. A simulation study is performed on a real forest stand to check the statistical performance of the proposed strategy. (c) 2019 Elsevier B.V. All rights reserved
End-to-End Transcript Alignment of 17th Century Manuscripts: The Case of Moccia Code
No full textThe growth of digital libraries has yielded a large number of handwritten historical documents in the form of images, often accompanied by a digital transcription of the content. The ability to track the position of the words of the digital transcription in the images can be important both for the study of the document by humanities scholars and for further automatic processing. We propose a learning-free method for automatically aligning the transcription to the document image. The method receives as input the digital image of the document and the transcription of its content and aims at linking the transcription to the corresponding images within the page at the word level. The method comprises two main original contributions: a line-level segmentation algorithm capable of detecting text lines with curved baseline, and a text-to-image alignment algorithm capable of dealing with under- and over-segmentation errors at the word level. Experiments on pages from a 17th-century Italian manuscript have demonstrated that the line segmentation method allows one to segment 92% of the text line correctly. They also demonstrated that it achieves a correct alignment accuracy greater than 68%. Moreover, the performance achieved on widely used data sets compare favourably with the state of the art
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