Ricerc@Sapienza

Palmprint verification is one of the most significant and popular approaches for personal authentication due to its high accuracy and efficiency. Using deep region of interest (ROI) and feature extraction models for palmprint verification, a novel approach is proposed where convolutional neural networks (CNNs) along with transfer learning are exploited. The extracted palmprint ROIs are fed to the final verification system, which is composed of two modules. These modules are (i) a pre-trained CNN architecture as a feature extractor and (ii) a machine learning classifier.

The goal of this special issue is to understand how and to what extent novel computational intelligence techniques based on the emerging end-to-end learning paradigm can be efficiently employed in Digital Audio, in the light of all aforementioned aspects.

The sounds of work activities and equipment operations at a construction site provide critical information regarding construction progress, task performance, and safety issues. The construction industry, however, has not investigated the value of sound data and their applications, which would offer an advanced approach to unmanned management and remote monitoring of construction processes and activities.

In this paper, a Machine Learning (ML), and more specifically, a Deep Learning (DL) approach, is applied to the resolution of a typical electromagnetic problem such as the analysis and classification of Ground Penetrating Radar (GPR) radargrams. In particular, the study employs a DL architecture, known as DenseNet, to classify a set of radargrams, generated through the gprMax simulation software, and representing the scattering from perfect electric conductor (PEC) cylinders of infinite length, buried in various media, at different depths, and with different radius amplitudes.

The aim of this work is to exploit Machine Learning (ML) for the analysis of Ground Penetrating Radar images.
In particular, the objective is to apply a scaled-down version of DenseNet [1] architecture with a multiporse
approach to extract from b-scan images of buried cylinders: the cylinder radius, the cylinder length, the depth
with respect to the ground, and the relative permittivity of the cylinder and of the medium in which the cylinder
is immersed. The cylinders have an infinite length or have a length much greater than the diameter. The main

Pseudomonas aeruginosa

Biofilm resistance to antimicrobials is a complex phenomenon, driven not only by genetic mutation induced resistance, but also by means of increased microbial cell density that supports horizontal gene transfer across cells. The prevention of biofilm formation and the treatment of existing biofilms is currently a difficult challenge; therefore, the discovery of new multi-targeted or combinatorial therapies is growing.

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among the prominent studies essential oils are investigated as antibacterial agents alone or in combination with known drugs. Minor studies involved essential oil inspection as potential anticancer and antiviral natural remedies. In line with the authors previous reports the investigation of an in-house library of extracted essential oils as a potential blocker of HSV-1 infection is reported herein.

Recurrent and chronic respiratory tract infections in cystic fibrosis (CF) patients result in progressive lung damage and represent the primary cause of morbidity and mortality. Staphylococcus aureus (S. aureus) is one of the earliest bacteria in CF infants and children. Starting from early adolescence, patients become chronically infected with Gram-negative non-fermenting bacteria, and Pseudomonas aeruginosa (P. aeruginosa) is the most relevant and recurring.

Fruits of Lycium barbarum L., have been used in Chinese traditional medicine for centuries. In the last decade, there has been much interest in the potential health benefits of many biologically constituents of these fruits. The high level of carotenoids offers protection against development of cardiovascular diseases, diabetes and related comorbidities.