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 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.     

Psychological and Social Predictors of Changes in Fruit and Vegetable Consumption Over 12 Months Following Behavioral and Nutrition Education Counseling.

This study assessed psychological and social factors predicting 12-month changes in fruit and vegetable consumption achieved by 271 men and women from a low-income population randomized to brief behavioral and nutrition education counseling. Greater increases in fruit and vegetable intake were achieved in the behavioral than in the nutrition education condition (1.49 vs. 0.87 portions per day, p=.021). Increases were predicted by baseline social support for dietary change but not by baseline psychological measures. However, short-term (8-week) changes in dietary self-efficacy, encouragement, anticipated regret, perceived benefits, and knowledge of recommended intake predicted 12-month changes in fruit and vegetable consumption independently of gender, age, ethnicity, income, and baseline intake. These factors accounted for 51% of the superiority of behavioral counseling over nutrition education. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Experimental and Numerical Analysis of Soil–Pipe Interaction

Cases of pipeline damage caused by landslides are common in coastal or mountainous regions, where a continuous monitoring/repair activity is planned in order to maintain their serviceability. The analysis of the soil–structure interaction phenomenon can be invoked to improve the planning and design of buried pipelines, to guide monitoring, and to reduce the risk of damage or failure. Two different approaches are considered in this paper: small scale laboratory tests and numerical simulations using the distinct element method (DEM). The experimental setup consists of a box filled with sand and water. Several experiments were performed, in which the diameter and the depth of the tube varied. The numerical simulations are divided in two separate series: in the first, the numerical model is calibrated and its reliability in reproducing the experimental tests is checked; in the second series, the direction of the relative displacement between the tube and the surrounding “numerical soil” varies over the range ±90° with respect to the horizontal. In the latter, both vertical and horizontal components of the drag force are measured and the corresponding interaction diagrams are constructed. The DEM simulations provide useful information about the shape of the failure mechanisms and the force transfer within the soil.     

Languages generated by P systems with active membranes

We propose an alternative approach to generate languages by means of P systems: building up an appropriate representation for a string by means of a corresponding membrane structure and then generating the string by visiting the membrane structure according to a well-specified strategy. To this aim, we consider P systems with active membranes, allowing membrane creation or division or duplication and dissolution, where the output of a computation may be obtained either by visiting the tree associated with the membrane structure, or by following the traces of a specific object, called traveller, or sending out the objects. For each of these approaches, we provide characterizations of recursively enumerable languages based on P systems that use different sets of operations for modifying the membrane structure. Francesco Bernardini: He started his Ph.D. at the University of Sheffield in December 2002 after having previously got a master degree in Computer Science from the University of Pisa in Italy. His research is dedicated to the study of theoretical aspects of membrane computing (P systems) and discrete models of biological systems based on P systems. Marian Gheorghe, Ph.D.: His main research interests are in computational models and their applications to software modelling and testing, formal specifications of agent based systems, software engineering. He was investigating computational power of various generative devices (regular, context-free, fully initial; grammar systems; L-systems and variants). He is currently interested in natural computing (membrane calculus) and biological modelling.