Future scenarios of parallel computing: Distributed sensor networks

Over the past few years, motivated by the accelerating technological convergence of sensing, computing and communications, there has been a growing interest in potential and technological challenges of Wireless Sensor Network. This paper will introduce a wide range of current basic research lines dealing with ad hoc networks of spatially distributed systems, data rate requirements and constraints, real-time fusion and registration of data from distributed sensors, cooperative control, hypothesis generation, and network consensus filtering. This technical domain has matured to the point where a number of industrial products and systems have appeared. The presentation will also describe the state of the art regarding current and soon-to-appear applications

Numerical prediction of the non-linear behaviour of perforated metal shear panels

Steel plate shear walls (SPSWs) are innovative systems able to confer to either new or existing structures a significant capacity to resist earthquake and wind loads. Many tests have shown that these devices may exhibit high strength, initial stiffness and ductility, as well as an excellent ability to dissipate energy. When full SPSWs are used as bracing devices of buildings, they may induce excessive stresses in the surrounding main structure where they are inserted, so to require the adoption of large cross section profiles. For this reason, perforated steel panels, which are weakened by holes aiming at limiting the actions transmitted to the surrounding frame members, represent a valid alternative to full panels. In this work, aiming at showing the advantages of such devices, a FEM model of perforated panels has been calibrated on the basis of recent experimental tests. Subsequently, a parametric FEM analysis on different series of perforated panels, by changing the number and diameter of the holes, the plate thickness and the metal material, has been carried out. Finally, the achieved numerical results have been used to set up design charts to correctly estimate the strength and stiffness of perforated metal shear panels

Fire design in safety engineering: likely fire curve for people’s safety

The present study analyses fire design settings according to Fire Safety Engineering (FSE) for the simulation of fire in civil activities and compares these simulations developed using natural and analytic fire curves. The simulated Heat Rate Release (HRR) curve, appropriately linearized, allows for the estimation of a Likely Fire Curve (LFC). The analytic curves have been introduced for the purpose of evaluating the strength and integrity of the structure, and the adoption of these curves in the fire safety engineering was made following the assumption that the phenomena of major intensity ensure the safe approach of fire design. This argument describes the method adopted for determining a likely fire model that guarantees a greater adherence of the virtualized phenomenon with respect to the potential event. The study showed that the analytic curve, adopted in order to verify the structural strength, in the beginning phases of fire produces fields of temperature and toxic concentrations lower than those obtained by simulation of the Likely Fire Curve. The assumption of the Likely Fire Curve model safeguards exposed people during self-rescue and emergency procedure. The programs used since 2011 for the simulation are FDS (Fire Dynamic Simulator v. 5.4.3) and Smokeview (5.4.8). Comparative analysis was developed using thermo-fluid dynamic parameters (temperature and heat release rate) relevant to the safety of the exposed persons; the case study focuses on children and employees of the nursery. The main result shows that the safety criterion, implicitly included in the analytical fire curves - normally used for fire resistance - doesn’t have the same applicability of a performance based approach on safety evaluation involving people. This paper shows that the Likely Fire Curve assumption involves a thermo-chemical stress more relevant to assessing the safety of exposed people

Anomaly Detection using Autoencoders in High Performance Computing Systems

Anomaly detection in supercomputers is a very difficult problem due to the big scale of the systems and the high number of components. The current state of the art for automated anomaly detection employs Machine Learning methods or statistical regression models in a supervised fashion, meaning that the detection tool is trained to distinguish among a fixed set of behaviour classes (healthy and unhealthy states). We propose a novel approach for anomaly detection in High Performance Computing systems based on a Machine (Deep) Learning technique, namely a type of neural network called autoencoder. The key idea is to train a set of autoencoders to learn the normal (healthy) behaviour of the supercomputer nodes and, after training, use them to identify abnormal conditions. This is different from previous approaches which where based on learning the abnormal condition, for which there are much smaller datasets (since it is very hard to identify them to begin with). We test our approach on a real supercomputer equipped with a fine-grained, scalable monitoring infrastructure that can provide large amount of data to characterize the system behaviour. The results are extremely promising: after the training phase to learn the normal system behaviour, our method is capable of detecting anomalies that have never been seen before with a very good accuracy (values ranging between 88% and 96%).Comment: 9 pages, 3 figure

Polarization of a quasi two-dimensional repulsive Fermi gas with Rashba spin-orbit coupling: a variational study

Motivated by the remarkable experimental control of synthetic gauge fields in ultracold atomic systems, we investigate the effect of an artificial Rashba spin-orbit coupling on the spin polarization of a two-dimensional repulsive Fermi gas. By using a variational many-body wavefunction, based on a suitable spinorial structure, we find that the polarization properties of the system are indeed controlled by the interplay between spin-orbit coupling and repulsive interaction. In particular, two main effects are found: 1) The Rashba coupling determines a gradual increase of the degree of polarization beyond the critical repulsive interaction strength, at variance with conventional 2D Stoner instability. 2) The critical interaction strength, above which finite polarization is developed, shows a dependence on the Rashba coupling, i.e. it is enhanced in case the Rashba coupling exceeds a critical value. A simple analytic expression for the critical interaction strength is further derived in the context of our variational formulation, which allows for a straightforward and insightful analysis of the present problem.Comment: 7 pages, 3 figure

Italian hybrid fire prevention code

Fire safety of residential buildings and activities subjected to fire inspection is a difficult task, especially when the safety targets have to be adopted in built buildings or in activities that are going to be modified into more complex ones. Generally, these circumstances show more constraints and it could be difficult to achieve an acceptable level of fire residual risk by prescriptive based fireregulations. Therefore, the Italian National Fire Rescue and Service in charge for fire safety, in August 2015 issued a new Fire Prevention Code whose design methodology is more oriented to fire performance based design rather than prescriptive fire codes. The flexibility of this new fire design methodology offers a very complex tool to experts in order to design fire safety measures and strategies of buildings and activities subjected to fire inspection. The present paper aims tohighlig hts the contents and the fire safety strategy design methodology of the new Italian Fire Prevention Code

How knowledge collecting fosters organizational creativity

3noStructured Abstract: Purpose Based on the interactionist perspective proposed by Woodman, Sawyer, and Griffin (1993), this paper conceives organizational creativity as a complex concept whose investigation requires the understanding of the process, the product, the person, and the situation. Accordingly, this work attempts to enrich the understanding of how organizational creativity can be fostered by offering a framework which combines (inter-)individual-level learning (collecting knowledge from others), information sharing (through ICT infrastructures), and contextual factors (perceived top management support). Design/Methodology/Approach The empirical analysis draws on a sample of 362 employees from five subsidiaries of multinational corporations. The analysis is based on multivariate regression models considering Organizational Creativity as dependent variable. Findings The paper shows that individuals’ orientation toward learning from others significantly enhance organizational creativity. However, heavy ICT use negatively moderates the relationship between knowledge collecting and organizational creativity, while top management support does not show a significant moderating effect on the association between knowledge collecting and organizational creativity. Research limitations/implications Although based on a geographically-bounded perimeter, the analysis allows some generalizations. Originality/Value Based on these results, the paper contributes to the literature on organizational creativity by confirming the importance of providing a holistic view of the phenomenon, consistent with its inherent complexity. In so doing, it suggests organizations and their managers should simultaneously pay attention to individual and contextual factors when planning2015 Impact Factor: 1.429 * - 5 year Impact Factor (2015) - 1.868 - * 2015 Journal Citation Reports® (Thomson Reuters, 2016) - See more at: http://emeraldgrouppublishing.com/products/journals/journals.htm?id=md - ABS 2015 - level 2partially_openopenGiustiniano, Luca; Lombardi, Sara; Cavaliere, VincenzoGiustiniano, Luca; Lombardi, Sara; Cavaliere, Vincenz