Target-Aware Neural Architecture Search and Deployment for Keyword Spotting

Keyword spotting (KWS) utilities have become increasingly popular on a wide range of mobile and home devices, representing a prolific application field for Convolutional Neural Networks (CNNs), which are commonly exploited to perform keyword classification. Addressing the challenges of targeting such resource-constrained platforms, requires a careful definition of the CNN architecture and the overall system implementation. These reasons have led to a growing need for design and optimization flows, able to intrinsically take into account the system's performance when ported on the target platform. In this work, we present a design methodology based on Neural Architecture Search, exploited to combine the exploration of the optimal network topology, the audio pre-processing scheme, and the data quantization policy. The proposed design flow includes target-awareness in the exploration loop, comparing the different design alternatives according to a model-based pre-evaluation of metrics like execution latency, memory footprint, and energy consumption, evaluated considering the application's execution on the target processing platform. We have tested our design flow to obtain target-specific CNNs for a resource-constrained commercial platform, the ST SensorTile. Considering two different application scenarios, enabling the comparison with the state-of-the-art of efficient CNN-based models for KWS, we have obtained up to a 1.8% accuracy improvement and a 40% footprint reduction in the most favorable case

Bathymetric and longitudinal distribution analyysis of the rockfish Helicolenus Dactylopterus (Delaroche, 1809) in the southern Tyrrhenian Sea (central Mediterranean)

This study provides information on bathymetric and longitudinal distribution heterogeneity of the rockfish Helicolenus dactylopterus in the southern Tyrrhenian Sea. Data were drawn from experimental bottom trawl (1996-2002) plus bottom trap (2001-02) surveys. The frequency of occurrence and mean relative density (N/km2) and biomass (kg/km2) indexes were calculated for two survey seasons (spring and autumn), four geographic sectors and three depth strata. MANOVA was used to test fish abundance among years, sectors and strata. Analysis of the length-frequency distributions was carried out by two-way (gears and depths) ANOVA, post hoc multiple comparisons for testing differences among depths and Student’s t test for testing differences between gears. Length-weight relationship was also estimated and the allometric coefficient was tested with the Student’s t test. The results showed a significant positive bathymetric gradient of sizes both for trawl and trap surveys; at same depths, fish caught by traps were significantly longer than those caught by trawl. In spring surveys, significant differences were found among strata for both abundance indexes; in autumn surveys, significant differences between depth strata were found only for density indices. The distribution and abundance patterns of H. dactylopterus along the southern Tyrrhenian Sea was homogeneous among sectors. Length-weight relationship showed a significant positive allometric growth

MEDITS-based information on the deep water red shrimps Aristaeomorpha foliacea and Aristeus antennatus (Crustacea: Decapoda: Aristeidae)

Special Volume: Mediterranean marine demersal resources: the Medits international trawl survey (1994-1999)The application of statistical models on a time series of data arising from the MEDITS International Trawl Survey, an experimental demersal resources survey carried out during six years (1994-1999) in the same season of the year (late spring - early summer) using the same fishing gear in a large part of the Mediterranean, has allowed for a study to compare, for the first time, the space-time distribution, abundance, and size structure of the two Aristeids Aristaeomorpha foliacea and Aristeus antennatus throughout most of the Mediterranean Sea. This research has shown a large variability among the six reference areas, that were arbitrarily defined within the basin. In particular the two shrimps do not seem to present any correlation or yield continuity in the years. The same lack of homogeneity was also observed in the time trend of the abundances and frequencies of each of the two species. These data seem to confirm the intrinsic variability of the species, the cause of which is still unknown and undocumented. Nevertheless, a longitudinal gradient of catches has been observed where A. antennatus is more abundant in the west and A. foliacea in the east of the basinVersión del editor1,006

Low-grade gliomas in patients with Noonan syndrome: case-based review of the literature

Noonan syndrome (NS) is a congenital autosomic dominant condition characterized by a variable spectrum from a clinical and genetical point of view. Germline mutations in more than ten genes involved in RAS–MAPK signal pathway have been demonstrated to cause the disease. An higher risk for leukemia and solid malignancies, including brain tumors, is related to NS. A review of the published literature concerning low grade gliomas (LGGs) in NS is presented. We described also a 13-year-old girl with NS associated with a recurrent mutation in PTPN11, who developed three different types of brain tumors, i.e., an optic pathway glioma, a glioneuronal neoplasm of the left temporal lobe and a cerebellar pilocytic astrocytoma. Molecular characterization of the glioneuronal tumor allowed to detect high levels of phosphorylated MTOR (pMTOR); therefore, a therapeutic approach based on an mTOR inhibitor (everolimus) was elected. The treatment was well tolerated and proved to be effective, leading to a stabilization of the tumor, which was surgical removed. The positive outcome of the present case suggests considering this approach for patients with RASopathies and brain tumors with hyperactivated MTOR signaling

AN ANN MODEL TO STUDY DRIVER BEHAVIOUR IN URBAN ENVIRONMENT

10th AIEN

Multimodal transport Axis Design. Forecast model for crossover solutions in road network reconnection

none3A. Capra; S. Rinelli; G. SpinazzolaA., Capra; Rinelli, Savino; G., Spinazzol