Intrusion Detection System based on time related features and Machine Learning

The analysis of the behavior of network communications over time allows the extraction of statistical features capable of characterizing the network traffic flows. These features can be used to create an Intrusion Detection System (IDS) that can automatically classify network traffic. But introducing an IDS into a network changes the latency of its communications. From a different viewpoint it is possible to analyze the latencies of a network to try to identifying the presence or absence of the IDS. The proposed method can be used to extract a set of phisical or time related features that characterize the communication behavior of an Internet of Things (IoT) infrastructure. For example the number of packets sent every 5 minutes. Then these features can help identify anomalies or cyber attacks. For example a jamming of the radio channel. This method does not necessarily take into account the content of the network packet and therefore can also be used on encrypted connections where is impossible to carry out a Deep Packet Inspection (DPI) analysis

SAT-Based Decision Procedures for Automated Reasoning: a Unifying Perspective

Propositional reasoning (SAT) is an essential part of many reasoning tasks. Many problems in computer science can be compiled to SAT and then effectively decided using state-of-the-art solvers. Alternatively, if reduction to SAT is not feasible, the ideas and technology of state-of-the-art SAT solvers can be useful in deciding the propositional component of the reasoning task being considered. This last approach has been used in different contexts by different authors, many times by authors of this paper. Because of the essential role played by the SAT solver, these decision procedures have been called "SAT-based". SAT-based decision procedures have been proposed for various logics, but also in other areas such as planning. In this paper we present a unifying perspective on the various SAT-based approaches to these different reasoning tasks

Design and Simulation of THz Quantum Cascade Lasers

Strategies and concepts for the design of THz emitters based on the quantum cascade scheme are analyzed and modeled in terms of a fully three-dimensional Monte Carlo approach; this allows for a proper inclusion of both carrier-carrier and carrier-phonon scattering mechanisms. Starting from the simulation of previously published far-infrared emitters, where no population inversion is achieved, two innovative designs are proposed. The first one follows the well-established chirped-superlattice scheme whereas the second one employs a double-quantum well superlattice to allow energy relaxation through optical phonon emission. For both cases a significant population inversion is predicted at temperatures up to 80 K.Comment: 4 pages, 2 figures, 2 table

Infinite Dimensional Control Problems with Positivity State Constraints: a Banach Lattice Approach

This paper is devoted to studying a family of deterministic optimal control problems in an infinite dimension. The difficult feature of such problems is the presence of positivity state constraints, which arise very often in economic applications (our main motivation). To deal with such constraints we set up the problem in a Banach space with a Riesz space structure (i.e., a Banach lattice) and not necessarily reflexive, like $\mathcal{C}^0$. In this setting, which seems to be new in this context, we are able, using a type of infinite-dimensional Perron-Frobenius Theorem, to find explicit solutions of the HJB equation associated to a suitable auxiliary problem and to use such results to get information about the optimal paths of the starting problem. This was not possible to perform in the previously used infinite-dimensional setting where the state space was an $\mathrm{L}^2$ space

Updated management of malignant biliary tract tumors: an illustrative review

The management of malignant biliary tumors (MBTs) is complex and requires a multidisciplinary approach. Guidelines and methods of staging for biliary tumors have recently been released by main international societies, altering the clinical and radiologic approach to this pathologic condition. The aim of the present review is to detail the updated role of imaging in preoperative staging and follow-up and to illustrate clinical/therapeutic pathways. In addition, future perspectives on imaging and targeted/embolization therapies are outlined

Changes in biological properties and antioxidant capacity of an agricultural soil amended with sewage sludge

The effects of applying sewage sludge (SS) to agricultural soil (at low rate of 22.5, LRS, and at high rate of 45 t ha−1 dry basis, HRS) were monitored over a 120-d experimental period. Total organic carbon (TOC), water- soluble organic carbon (WSOC), alkali-soluble phenols, basal respiration, 10 specific enzyme activity, dehydrogenase activity (DH-ase), metabolic potential (MP) and FDA-hydrolytic activity (FDA) were strongly increased by both rates of SS applications. In the SS amended soil, about 70% of the organic C added with the material remained at the end of the experiment. Basal respiration increased with increasing SS doses. The 15 specific enzyme activity and the MP indicate an increase in the enzyme activity in soil. AQ10 The addition of SS led to higher values than the control of all the tested parameters up to the end of the experimental period. The anti- oxidant capacity (trolox equivalent antioxidant capacity, TEAC) was influ- 20 enced by SS addition only when applied at HRS. After 120 days only HRS value of TEAC (5.13 mM g−1) was higher than control (4.09 mM g−1). The pattern of TEAC did not enable any link to be established between antioxidant capacity and both alkali-soluble phenols and basal respira- tion in soil

Characterization and origin of organic and inorganic pollution in urban soils in Pisa (Tuscany, Italy).

We assessed the quality of 31 urban soils in Pisa by analyzing total petroleum hydrocarbons (TPH), Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn and the platinum group (PGEs). The risk was evaluated by the geological accumulation index (Igeo) and the enrichment factor (EF). Results were compared with those obtained from a non-urban site and with the quantitative limits fixed by Italian legislation. In nearly all the monitored sites, the legal limit for TPH of 60 mg/kg in residential areas was exceeded, indicating widespread and intense pollution throughout the entire city area. The Igeo indicated no Cd, Cu, Mn, Ni and Zn pollution and minimal Pb and Cr pollution, due to anthropogenic enrichment. Legal Hg and Zn limits of 1 and 150 mg/kg respectively were exceeded in about 20% of sites, Cd (2 mg/kg), Cr (150 mg/kg) and Cu (120 mg/kg) in only one site, the Ni legal limit of 120 mg/kg was never exceeded. Some urban soils showed a higher Hg level than the more restrictive legal limit of 5 mg/kg concerning areas for industrial use. Based on the soluble, exchangeable and carbonate-bound fractions, Mn and Zn showed the highest mobility, suggesting a more potential risk of soil contamination than the other metals. The TPH and both Cr and Hg amounts were not correlated with any of the other monitored metals. The total contents of Cd, Pb, Zn and Cu in soils were positively correlated with each other, suggesting a common origin from vehicular traffic. The PGE values (Pt and Pd) were below the detection limits in 75% - 90% of the monitored areas, suggesting that their accumulation is at an early stage

Neural Network Modeling of Arbitrary Hysteresis Processes: Application to GO Ferromagnetic Steel

A computationally efficient hysteresis model, based on a standalone deep neural network, with the capability of reproducing the evolution of the magnetization under arbitrary excitations, is here presented and applied in the simulation of a commercial grain-oriented electrical steel sheet. The main novelty of the proposed approach is to embed the past history dependence, typical of hysteretic materials, in the neural net, and to illustrate an optimized training procedure. Firstly, an experimental investigation was carried out on a sample of commercial GO steel by means of an Epstein equipment, in agreement with the international standard. Then, the traditional Preisach model, identified only using three measured symmetric hysteresis loops, was exploited to generate the training set. Once the network was trained, it was validated with the reproduction of the other measured hysteresis loops and further hysteresis processes obtained by the Preisach simulations. The model implementation at a low level of abstraction shows a very high computational speed and minimal memory allocation, allowing a possible coupling with finite-element analysis (FEA)

Structural Identification from Operational Modal Analysis: The Case of Steel Structures

In the case of old existing structures where the cultural value is very high, structural health analyses and investigations would be better performed without damages or service interruptions. Thus, modal analysis aimed at identifying eigenfrequencies and eigenmodes represents a very effective strategy to identify structural characteristics. In this paper, an innovative strategy to identify structural parameters exploiting the modal information obtained from operational modal analysis is proposed. The importance of the structural modeling in the problem formulation is highlighted. In the case of a simply supported beam, it was possible to assess the beam steel elastic modulus, while in the case of a cantilever beam, some constraint characteristics have been evaluated as well. In the steel frame case, the focus was on the constraint conditions of the structure determining the flexural stiffness of the springs representing the column base constraints. The method performances are promising for applications in larger structures such as bridges and buildings