Multigranular scale speech recognition: tehnological and cognitive view

We propose a Multigranular Automatic Speech Recognizer. The hypothesis is that speech signal contains information distributed on more different time scales. Many works from various scientific fields ranging from neurobiology to speech technologies, seem to concord on this assumption. In a broad sense, it seems that speech recognition in human is optimal because of a partial parallelization process according to which the left-to-right stream of speech is captured in a multilevel grid in which several linguistic analyses take place contemporarily. Our investigation aims, in this view, to apply these new ideas to the project of more robust and efficient recognizers

Représentations du mineur, de ses droits et du risque psychosocial

Cette étude porte sur les représentations des droits et du risque psychosocial des mineurs dans une population de jeunes et d'adultes. L'enquête, effectuée grâce à une méthodologie de type quanti-qualitatif, montre que l'on peut mieux interpréter les représentations des droits des mineurs si l'on tient compte de la diversification des profils typiques du mineur, caractérisés, chez les plus jeunes, par une vision mythique de l'enfance et par une anticipation du mal-être de l'adolescence et du risque évolutif, surtout chez les adultes ayant des fonctions éducatives. Les articulations représentationnelles semblent dépendre des principes organisateurs comme la responsabilité et l'idée de justice, l'implication personnelle des sujets dans leurs relations quotidiennes avec les mineurs, en fonction de leur phase évolutive et leurs propres interprétations de rôle. Summary We present a study about the representations of the rights and of the psychosocial risk of minors in a population composed of both young people and adults. The investigation, carried out with a quantitative and qualitative methodology, illustrates how social representations of minors' rights become understandable taking account, among other elements, of the diversification of minor's typical outlines. It emerges that this representational system is characterized by a mythical view of infancy from younger people and by an anticipation of adolescence discomfort and developmental risk especially in adults who have an educational task. Representational articulations seem to depend not only on organizing principles as responsibility and the sense of justice, but even on personal involvement that subjects experience in their daily relationships with minors, in relation to their developmental stage and to their own role interpretations

Pathway to a Compact SASE FEL Device

Newly developed high peak power lasers have opened the possibilities of driving coherent light sources operating with laser plasma accelerated beams and wave undulators. We speculate on the combination of these two concepts and show that the merging of the underlying technologies could lead to new and interesting possibilities to achieve truly compact, coherent radiator devices

Estimating the generation interval from the incidence rate, the optimal quarantine duration and the efficiency of fast switching periodic protocols for COVID‑19

The transmissibility of an infectious disease is usually quantified in terms of the reproduction number Rt representing, at a given time, the average number of secondary cases caused by an infected individual. Recent studies have enlightened the central role played by w(z), the distribution of generation times z, namely the time between successive infections in a transmission chain. In standard approaches this quantity is usually substituted by the distribution of serial intervals, which is obtained by contact tracing after measuring the time between onset of symptoms in successive cases. Unfortunately, this substitution can cause important biases in the estimate of Rt . Here we present a novel method which allows us to simultaneously obtain the optimal functional form of w(z) together with the daily evolution of Rt , over the course of an epidemic. The method uses, as unique information, the daily series of incidence rate and thus overcomes biases present in standard approaches. We apply our method to one year of data from COVID-19 officially reported cases in the 21 Italian regions, since the first confirmed case on February 2020. We find that w(z) has mean value z ≃ 6 days with a standard deviation a ≃ 1 day, for all Italian regions, and these values are stable even if one considers only the first 10 days of data recording. This indicates that an estimate of the most relevant transmission parameters can be already available in the early stage of a pandemic. We use this information to obtain the optimal quarantine duration and to demonstrate that, in the case of COVID-19, post-lockdown mitigation policies, such as fast periodic switching and/or alternating quarantine, can be very efficient

Deep Saturated Free Electron Laser Oscillators and Frozen Spikes

We analyze the behavior of Free Electron Laser (FEL) oscillators operating in the deep saturated regime and point out the formation of sub-peaks of the optical pulse. They are very stable configurations, having a width corresponding to a coherence length. We speculate on the physical mechanisms underlying their growth and attempt an identification with FEL mode locked structures associated with Super Modes. Their impact on the intra-cavity nonlinear harmonic generation is also discussed along with the possibility of exploiting them as cavity out-coupler.Comment: 28 page

Apparent superluminal advancement of a single photon far beyond its coherence length

We present experimental results relative to superluminal propagation based on a single photon traversing an optical system, called 4f-system, which acts singularly on the photon's spectral component phases. A single photon is created by a CW laser light down{conversion process. The introduction of a linear spectral phase function will lead to the shift of the photon peak far beyond the coherence length of the photon itself (an apparent superluminal propagation of the photon). Superluminal group velocity detection is done by interferometric measurement of the temporal shifted photon with its correlated untouched reference. The observed superluminal photon propagation complies with causality. The operation of the optical system allows to enlighten the origin of the apparent superluminal photon velocity. The experiment foresees a superluminal effect with single photon wavepackets.Comment: 11 pages, 2 figure

Testing Convolutional Neural Networks for finding strong gravitational lenses in KiDS

Convolutional Neural Networks (ConvNets) are one of the most promising methods for identifying strong gravitational lens candidates in survey data. We present two ConvNet lens-finders which we have trained with a dataset composed of real galaxies from the Kilo Degree Survey (KiDS) and simulated lensed sources. One ConvNet is trained with single \textit{r}-band galaxy images, hence basing the classification mostly on the morphology. While the other ConvNet is trained on \textit{g-r-i} composite images, relying mostly on colours and morphology. We have tested the ConvNet lens-finders on a sample of 21789 Luminous Red Galaxies (LRGs) selected from KiDS and we have analyzed and compared the results with our previous ConvNet lens-finder on the same sample. The new lens-finders achieve a higher accuracy and completeness in identifying gravitational lens candidates, especially the single-band ConvNet. Our analysis indicates that this is mainly due to improved simulations of the lensed sources. In particular, the single-band ConvNet can select a sample of lens candidates with $\sim40\%$ purity, retrieving 3 out of 4 of the confirmed gravitational lenses in the LRG sample. With this particular setup and limited human intervention, it will be possible to retrieve, in future surveys such as Euclid, a sample of lenses exceeding in size the total number of currently known gravitational lenses.Comment: 16 pages, 10 figures. Accepted for publication in MNRA

Finding Strong Gravitational Lenses in the Kilo Degree Survey with Convolutional Neural Networks

The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources. Indeed, this is the case for the search for strong gravitational lenses, where the population of the detectable lensed sources is only a very small fraction of the full source population. We apply for the first time a morphological classification method based on a Convolutional Neural Network (CNN) for recognizing strong gravitational lenses in $255$ square degrees of the Kilo Degree Survey (KiDS), one of the current-generation optical wide surveys. The CNN is currently optimized to recognize lenses with Einstein radii $\gtrsim 1.4$ arcsec, about twice the $r$-band seeing in KiDS. In a sample of $21789$ colour-magnitude selected Luminous Red Galaxies (LRG), of which three are known lenses, the CNN retrieves 761 strong-lens candidates and correctly classifies two out of three of the known lenses. The misclassified lens has an Einstein radius below the range on which the algorithm is trained. We down-select the most reliable 56 candidates by a joint visual inspection. This final sample is presented and discussed. A conservative estimate based on our results shows that with our proposed method it should be possible to find $\sim100$ massive LRG-galaxy lenses at z\lsim 0.4 in KiDS when completed. In the most optimistic scenario this number can grow considerably (to maximally $\sim$2400 lenses), when widening the colour-magnitude selection and training the CNN to recognize smaller image-separation lens systems.Comment: 24 pages, 17 figures. Published in MNRA