Exploiting n-gram location for intrusion detection

Signature-based and protocol-based intrusion detection systems (IDS) are employed as means to reveal content-based network attacks. Such systems have proven to be effective in identifying known intrusion attempts and exploits but they fail to recognize new types of attacks or carefully crafted variants of well known ones. This paper presents the design and the development of an anomaly-based IDS technique which is able to detect content-based attacks carried out over application level protocols, like HTTP and FTP. In order to identify anomalous packets, the payload is split up in chunks of equal length and the n-gram technique is used to learn which byte sequences usually appear in each chunk. The devised technique builds a different model for each pair and uses them to classify the incoming traffic. Models are build by means of a semi-supervised approach. Experimental results witness that the technique achieves an excellent accuracy with a very low false positive rate

Solving biclustering with a GRASP-like metaheuristic: two case-study on gene expression analysis

The explosion of "omics" data over the past few decades has generated an increasing need of efficiently analyzing high-dimensional gene expression data in several different and heterogenous contexts, such as for example in information retrieval, knowledge discovery, and data mining. For this reason, biclustering, or simultaneous clustering of both genes and conditions has generated considerable interest over the past few decades. Unfortunately, the problem of locating the most significant bicluster has been shown to be NP-complete. We have designed and implemented a GRASP-like heuristic algorithm to efficiently find good solutions in reasonable running times, and to overcome the inner intractability of the problem from a computational point of view. Experimental results on two datasets of expression data are promising indicating that this algorithm is able to find significant biclusters, especially from a biological point of view

A logic-based approach for the verification of UML timed models

This article presents a novel technique to formally verify models of real-time systems captured through a set of heterogeneous UML diagrams. The technique is based on the following key elements: (i) a subset of Unified Modeling Language (UML) diagrams, called Coretto UML (C-UML), which allows designers to describe the components of the system and their behavior through several kinds of diagrams (e.g., state machine diagrams, sequence diagrams, activity diagrams, interaction overview diagrams), and stereotypes taken from the UML Profile for Modeling and Analysis of Real-Time and Embedded Systems; (ii) a formal semantics of C-UML diagrams, defined through formulae of the metric temporal logic Tempo Reale ImplicitO (TRIO); and (iii) a tool, called Corretto, which implements the aforementioned semantics and allows users to carry out formal verification tasks on modeled systems. We validate the feasibility of our approach through a set of different case studies, taken from both the academic and the industrial domain

Autonomic Faulty Node Replacement in UAV-Assisted Wireless Sensor Networks: a Test-bed

Several use-cases of the Internet of Things (IoT) rely on the development of large-scale Wireless Sensor Networks (WSNs) in harsh environments characterized by limited Internet connectivity and battery-powered operations. In such scenarios, the failure of a single node due to energy depletion or hardware issues may cause network partitions and disrupt partially or completely the system operations until the intervention of a human operator. In this paper, we investigate the usage of Unmanned Aerial Networks (UAVs) to enable sensory data collection and support resilient communications in presence of faulty sensor nodes. More specifically, we study the possibility of replacing the ground devices with UAVs which are able to temporarily restore the multi-hop communication towards the WSN sink. To this aim, we extended the Uhura framework, a platform for robotic networking, with novel features for automatic network partition detection and UAV-sink coordination. Then, we created a small test-bed composed of a Bluetooth Mesh WSN and one drone, and characterized the performance of the UAV-assisted WSN system in terms of packet delivery ratio of the end-to-end data flows

Apps for oral hygiene in children 4 to 7 years : fun and effectiveness

Nowadays apps in preschool age are largely used in learning improvement. The aim of this work was to test effectiveness of apps in improving oral hygiene in children patients aged from 4 to 7 years and evaluating correlation between parents educational attainment and children oral hygiene. 100 patients aged from 4 to 7 years were randomly assigned by an external office in the study group (SG: 32 females, 18 males) and in the control group (CG: 28 females and 22 males). Plaque index (PI) and carious lesions localisation were detected. At baseline all patients and one of the parents were instructed at chair-side about the proper oral hygiene techniques. SG patients were also given app as an aid in oral hygiene practice. Follow-up was 12 months. Measurements were made every three months at chair-side visits. Information about children compliance in oral hygiene and educational level of parents were obtained by questionnaires at t0 and after 12 months. SG patients showed stronger oral hygiene and PI lower than those in CG. Questionnaire showed higher compliance of SG patients and parents educational level seemed to affect children oral hygiene. Apps in children allowed achieving encouraging results with improvement of oral hygiene and health

Laser scanning technology for the hypogean survey: the case of Santa Barbara karst system (Sardinia, Italy)

The morphological knowledge of the territory, bothin its surface and subterranean aspects, is the main premise to all decision-making procedures as well as all planning and management activities. Knowledge takes shape into reliable precise and complete thematic cartography and databases, whichare necessary for anybody dealing withunderground contexts: speleologists, scientists, public administrations, managing authorities etc. Surveys in caves are normally carried out withtraditional techniques and instruments, whichare essential for a first representation but not enoughfor a pragmatic effective topographic approach. Laser scanning technique can be an alternative to the traditional systems. Laser scanning quickly acquires the shape of cavities as “point clouds” (x, y, z coordinates and colour values) and produces a highprecision database of the surveyed object. Laser scanning technology is therefore a feasible way to document caves in a precise exhaustive way, limiting risks relating to lack and/or inadequacy of data. The present paper explains the laser scanning survey carried out in San Giovanni mine near Iglesias (Sardinia, Italy), particularly in Santa Barbara and Santa Barbara 2 caves, the data post-processing and three-dimensional modelling of “point clouds” (operations performed witha dedicated software), and the use of the obtained digital model. Moreover, the paper describes the advantages of laser scanning for the hypogean survey in comparison to traditional methods and the future potentialities of a broad application of laser scanning instruments in caves.

Classification of glomerular hypercellularity using convolutional features and support vector machine

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention. An example of lesion is the glomerular hypercellularity, which is characterized by an increase in the number of cell nuclei in different areas of the glomeruli. Glomerular hypercellularity is a frequent lesion present in different kidney diseases. Automatic detection of glomerular hypercellularity would accelerate the screening of scanned histological slides for the lesion, enhancing clinical diagnosis. Having this in mind, we propose a new approach for classification of hypercellularity in human kidney images. Our proposed method introduces a novel architecture of a convolutional neural network (CNN) along with a support vector machine, achieving near perfect average results with the FIOCRUZ data set in a binary classification (lesion or normal). Our deep-based classifier outperformed the state-of-the-art results on the same data set. Additionally, classification of hypercellularity sub-lesions was also performed, considering mesangial, endocapilar and both lesions; in this multi-classification task, our proposed method just failed in 4\% of the cases. To the best of our knowledge, this is the first study on deep learning over a data set of glomerular hypercellularity images of human kidney.Comment: 26 page

Long-term monitoring and microbiological control programs against lepidopteran defoliators in Sardinian cork oak forests (Italy)

The gypsy moth, Lymantria dispar (L.), and the tent caterpillar, Malacosoma neustrium (L.), are the main cork oak, Quercus suber L., pests in the Mediterranean area and cause complete defoliation in large forest districts. In order to control infestations, large scale aerial applications of insecticides based on Bacillus thuringiensis subsp. kurstaki (Btk) have been carried out in Sardinia (Italy) since 2001. This paper evaluated the frequency of outbreaks in forest districts with varying homogeneity of land use, forest areas annually exposed to defoliation and the effectiveness of control programs based on Btk insecticide applications.The volume of areas annually exposed to defoliation depends on forest homogeneity, as infestations are more frequent in cork oak areas with a lower than 25% canopy cover rate. The microbiological control programme efficiently protected cork oaks from lepidopteran defoliators and caused an overall annual mean mortality of over 60%, with maximum rates of 89.9 and 98.0% for L. dispar and M. neustrium, respectively. To date, approximately 180,000 hectares of cork oak forests have been protected by spraying Btk-based insecticides

Imprenditori si diventa. Cento nuove imprese nel Piemonte degli anni '90: i protagonisti

Preprint dell'edizione Rosenberg & Sellier ; Collana Piemonte ; 25- Indice #4- Presentazione #8- Il fattore imprenditoriale in aree di grandi imprese: il caso del Piemonte #9- Nuove imprese e nuovi imprenditori tra teoria e ricerca empirica #18- Una ricerca empirica sui nuovi imprenditori in Piemonte #33- I nuovi imprenditori #55- Le imprese create dai neo-imprenditori #73- La creazione delle imprese: occasioni, risorse, fattori, rapporti #79- Dinamica delle imprese e caratteristiche degli imprenditori #103- Gli imprenditori in azienda #123- Problemi, giudizi e prospettive dei neo-imprenditori #130- Nuovi imprenditori e sistema pubblico: rapporti, giudizi, attese #162- Riferimenti bibliografici #177- Appendice. ‘Ritratti personali' di alcuni neo-imprenditori #18