Using the Meteorological Information for the Regional Rainfall Frequency Analysis: An Application to Sicily

Regional frequency analysis is a useful tool for accurate estimation of precipitation quantiles than at-site frequency analysis, especially in the case of regions with a short rainfall time series. The use of meteorological information, combined with rainfall data analysis, could improve the selection of homogeneous regions. Starting from 1958, 198 meteorological configurations, related to extreme events, have been identified throughout the national territory of Italy. The reanalyzed meteorological data of the 40 Year Re-analysis Archive (ERA-40) of the European Centre for Medium-Range Weather Forecast (ECMWF) have been analyzed to identify homogeneous regions with respect to the Convective Available Potential Energy (CAPE), the Q vector Divergence (QD) and the Vertically Integrated Moisture Flux (VIMF). The latter index appears to be the better candidate for finding regional homogeneity inside areas where high frequency values of CAPE or QD are present. The paper presents an application based on the delimitation of homogeneous regions using climatic indexes for the island of Sicily. By applying the proposed methodology, seven homogeneous areas over Sicily were found. The consistency of the final results has been validated by using a coupled approach based on the Valuation of Floods in Italy procedure (VAPI) and on the heterogeneity test of Hosking and Wallis (Water Resour Res 29:271–281, 1993, 1997).     

Distributed pursuit-evasion without mapping or global localization via local frontiers

This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.     

A Low‐Memory,Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain

In this work we present a new algorithm for accelerating the colour bilateral filter based on a subsampling strategy working in the spatial domain. The base idea is to use a suitable subset of samples of the entire kernel in order to obtain a good estimation of the exact filter values. The main advantages of the proposed approach are that it has an excellent trade‐off between visual quality and speed‐up, a very low memory overhead is required and it is straightforward to implement on the GPU allowing real‐time filtering. We show different applications of the proposed filter, in particular efficient cross‐bilateral filtering, real‐time edge‐aware image editing and fast video denoising. We compare our method against the state of the art in terms of image quality, time performance and memory usage.     

Parallel option pricing on GPU: barrier options and realized variance options

This paper shows two examples of how the analysis of option pricing problems can lead to computational methods efficiently implemented in parallel. These computational methods outperform ??general purpose?? methods (i.e., for example, Monte Carlo, finite differences methods). The GPU implementation of two numerical algorithms to price two specific derivatives (continuous barrier options and realized variance options) is presented. These algorithms are implemented in CUDA subroutines ready to run on Graphics Processing Units (GPUs) and their performance is studied. The realization of these subroutines is motivated by the extensive use of the derivatives considered in the financial markets to hedge or to take risk and by the interest of financial institutions in the use of state of the art hardware and software to speed up the decision process. The performance of these algorithms is measured using the (CPU/GPU) speed up factor, that is using the ratio between the (wall clock) times required to execute the code on a CPU and on a GPU. The choice of the reference CPU and GPU used to evaluate the speed up factors presented is stated. The outstanding performance of the algorithms developed is due to the mathematical properties of the pricing formulae used and to the ad hoc software implementation. In the case of realized variance options when the computation is done in single precision the comparisons between CPU and GPU execution times gives speed up factors of the order of a few hundreds. For barrier options, the corresponding speed up factors are of about fifteen, twenty. The CUDA subroutines to price barrier options and realized variance options can be downloaded from the website http://www.econ.univpm.it/recchioni/finance/w13. A?more general reference to the work in mathematical finance of some of the authors and of their coauthors is the website http://www.econ.univpm.it/recchioni/finance/.     

Distributed estimation via iterative projections with application to power network monitoring

This work presents a distributed method for control centers to monitor the operating condition of a power network, i.e., to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements.     

Open Innovation in an Enterprise 3.0 framework: Three case studies

Nowadays, especially after the recent financial downturn, companies are looking for much more efficient and creative business processes. They need to place better solutions in the market in a less time with less cost. There is a general intuition that communication and collaboration, especially mixed with Web 2.0 approach within companies and ecosystems, can boost the innovation process with positive impacts on business indicators. Open Innovation within an Enterprise 2.0 context is a one of the most chosen paradigm for improving the innovation processes of enterprises, based on the collaborative creation and development of ideas and products. The key feature of this new paradigm is that the knowledge is exploited in a collaborative way flowing not only among internal sources, i.e. R&D departments, but also among external ones as other employees, customers, partners, etc. In this paper we show how an ontology-based analysis of plain text can provide a semantic contextualization of content support tasks, such as finding semantic distance between contents, and can help in creating relations between people with shared knowledge and interests. Along this paper we will present the results obtained by the adoption of this technology in a large corporate environment like Bankinter, a financial institution, Telefonica I+D, an international telecommunication firm and Repsol, a major oil company in Spain.     

A control oriented model for manual-pick warehouses

Nowadays the low cost of wireless communications allows the real time monitoring of the state of manual-pick warehouse systems making possible the real time control of these systems. At this aim, an approach based on a two-level model is presented in this paper. At the lower level, Petri nets are used to build online a model representing the active missions state and to detect conflicts among resources. At the upper level, logical expressions are used to add constraints for a single mission or item. The model is proved to be effective for online monitoring, scheduling and rescheduling of warehouse activities.     

A hybrid model for real time simulation of urban traffic

In this paper a hybrid model is presented to predict the behavior of traffic in urban area. Intersections and on/off-ramps are modeled by Colored Timed Petri Nets while road links are modeled by a stochastic discrete time model. It is assumed that vehicle routings at each intersection are stochastic. A Particle Filter algorithm based on the hybrid model is developed to estimate the system state. The validation of the model by using real data is discussed. The limited computational effort required makes the model suitable to be used in simulation-based control schemes for urban traffic.     

A Traffic Generator for Testing Communication Systems: Presentation,Implementation and Performance

This paper presents a multi-application traffic generator (MTG), aimed at the generation of packets over a LAN. The generated traffic simulates the one produced by a number of both isochronous and anisochronous applications, thus allowing the measurement of a number of parameters relevant to the communication network. From a test point of view, data generated by the MTG system is equivalent to data generated by real applications spread over a LAN. The MTG system is presented, its implementation is described, some figures relevant to the MTG performance are shown, and the statistical analysis which can be performed on the recorded data is briefly introduced. The user manual of the MTG system is referenced in (Celandroni, Ferro, and Potorti 1995).     

Effects of secondary electron emission from a floating surface on the plasma sheath

The paper describes the region between a Maxwellian plasma source and a floating surface by a 1D-3 V fully kinetic, electrostatic particle simulation. The electric field is self-consistently computed from the Poisson equation. The secondary electron emission is modelled by considering an expression for the secondary emission coefficient dependent on the primary electron energy and surface materials and a realistic secondary electron distribution function is introduced at the collector surface. The model is able to simulate the space-charge-limited conditions as well as the positively charged wall cases.