Quasi-elastic light scattering for intermittent dynamics

Dynamic light-scattering techniques provide noninvasive probes of diverse media such as colloidal suspensions, granular materials, and foams. Traditional analysis relies on the Gaussian properties of the scattering process found in most experimental situations and uses second-order intensity-correlation functions. This approach fails in the presence of, among other things, the collective intermittent dynamics found in systems such as granular materials. By extending the existing formalism and introducing higher-order intensity-correlation functions, we show how to detect and quantify the intrinsic dynamics and switching statistics of intermittent processes. We then explore two systems: (1) an auger-driven granular column for which the granular dynamics are controlled and the formalism is tested and (2) a granular heap whose dynamics are a priori unknown but may, now, be characterized.     

Learning independent components on the orthogonal group of matrices by retractions

Neural independent component learning algorithms based on optimization on manifolds have attracted interest in the neural network community. In the past years, we have developed learning algorithms specialized for the orthogonal group of matrices as parameters manifold. Here, we sketch a view of these algorithms by the help of ‘retractions’ on manifolds.     

First data from the EGLE experiment onboard the ISS

EGLE is a wide frequency band search- coil magnetometer designed and built at the Roma Tre University. It has been installed onboard the ISS by the Italian astronaut Roberto Vittori on April 25, 2005 within the LAZIO- EGLE experiment carried out during the ENEIDE Soyuz mission. The scope of the experiment is to test EGLE in space and to investigate geomagnetic field variations. The main applications of EGLE are the study of electromagnetic environment inside the ISS, the correlation of magnetic field data with particle fluxes detected by LAZIO particle detector, and the monitoring of ionospheric perturbations possibly caused by Earth seismic activity. Since continuous electromagnetic field measurements on board the ISS are important for diverse space applications, a magnetometer with a suitable design is requested. Appropriate solutions for these applications, which have been adopted by EGLE, are in particular the use of 1- Wire technology and the possibility to detect by means of a search- coil magnetometer a large portion of the ULF frequency band, usually measured by flux- gate probes. To investigate the topside ionosphere electromagnetic environment and stability of Van Allen radiation belts in relation with seismic and anthropogenic electromagnetic emissions, a specific satellite mission (the ESPERIA project) has been designed for the Italian Space Agency (ASI), and up to now a few instruments of its payload have been built and tested in space. One of them is exactly the EGLE search- coil magnetometer. The first magnetic observations performed by this instrument reveal to be promising and demand for a further and deeper analysis based on a longer time series of data.     

With a little help from my friends

In this paper, we propose a content-based method the for semi-automatic organization of photo albums based on the analysis of how different users organize their own pictures. The goal is to help the user in dividing his pictures into groups characterized by a similar semantic content. The method is semi-automatic: the user starts to assign labels to the pictures and unlabeled pictures are tagged with proposed labels. The user can accept the recommendation or made a correction. To formulate the suggestions is exploited the knowledge encoded in how other users have partitioned their images. The method is conceptually articulated in two parts. First, we use a suitable feature representation of the images to model the different classes that the users have collected, second, we look for correspondences between the criteria used by the different users. Boosting is used to integrate the information provided by the analysis of multiple users. A quantitative evaluation of the proposed approach is obtained by simulating the amount of user interaction needed to annotate the albums of a set of members of the flickr^® photo-sharing community.     

Experimental study on performance and emissions of a high speed diesel engine fuelled with n-butanol diesel blends under premixed low temperature combustion

In the present paper, results of an experimental investigation carried out in a modern diesel engine running at different operative conditions and fuelled with blends of diesel and n-butanol, are reported. The exploration strategy was focused on the management of the timing and injection pressure to achieve a condition in which the whole amount of fuel was delivered before ignition. The aim of the paper was to evaluate the potential to employ fuel blends having low cetane number and high resistance to auto-ignition to reduce engine out emissions of NOx and smoke without significant penalty on engine performance. Fuel blends were mixed by the baseline diesel (BU00) with 20% and 40% of n-butanol by volume. The n-butanol was taken by commercial production that is largely produced through petrochemical pathways although the molecule is substantially unchanged for butanol produced through biological mechanisms.The experimental activity was performed on a turbocharged, water cooled, DI diesel engine, equipped with a common rail injection system. The engine equipment includes an exhaust gas recirculation system controlled by an external driver, a piezo-quartz pressure transducer to detect the in-cylinder pressure signal and a current probe to acquire the energizing current to the injectors. Engine tests were carried out at 2500 rpm and 0.8 MPa of BMEP exploring the effect of start of injection, O₂ concentration at intake and injection pressure on combustion behavior and engine out emissions. The in-cylinder pressure and rate of heat release were investigated for the neat diesel and the two blends to evaluate engine performance and exhaust emissions both for the conventional diesel and the advanced premixed combustion processes.The management of injection pressure, O₂ concentration at intake and injection timing allowed to realize a partial premixed combustion by extending the ignition delay, particularly for blends. The main results of the investigation made reach smoke and NOx emissions due to the longer ignition delay and a better mixing control before combustion. The joint effect of higher resistance to auto ignition and higher volatility of n-butanol blends improved emissions compared to the neat diesel fuel with a low penalty on fuel consumption.     

Fluidization of fine powders with air in the particulate and the bubbling regions

Several fractions of a silica—alumina catalyst and an impregnated catalyst were fluidized with air to check published bubble point correlations and to determine the expansion of the dense phase in the bubbling region. The minimum bubbling velocities were fairly close to those reported by Geldart and others, but U_mb varied with only the 0.6 power of the particle size. The dense phase expansion was significant even at velocities much above U_mb and corresponded to relative velocities up to 2 – 3 times U_mf.     

Engineering order‐preserving pattern matching with SIMD parallelism

The order‐preserving pattern matching problem has gained attention in recent years. It consists in finding all substrings in the text, which have the same length and relative order as the input pattern. Typically, the text and the pattern consist of numbers. Since recent times, there has been a tendency to utilize the ability of the word RAM model to increase the efficiency of string matching algorithms. This model works on computer words, reading and processing blocks of characters at once, so that usual arithmetic and logic operations on words can be performed in one unit of time. In this paper, we present a fast order‐preserving pattern matching algorithm, which uses specialized word‐size packed string matching instructions, grounded on the single instruction multiple data instruction set architecture. We show with experimental results that the new proposed algorithm is more efficient than the previous solutions. ©2016 The Authors. Software: Practice and Experience Published by John Wiley & Sons Ltd.     

Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

The behavioral origins of the stylized facts of financial returns have been addressed in a growing body of agent-based models of financial markets. While the traditional efficient market viewpoint explains all statistical properties of returns by similar features of the news arrival process, the more recent behavioral finance models explain them as imprints of universal patterns of interaction in these markets. In this paper we contribute to this literature by introducing a very simple agent-based model in which the ubiquitous stylized facts (fat tails, volatility clustering) are emergent properties of the interaction among traders. The simplicity of the model allows us to estimate the underlying parameters, since it is possible to derive a closed form solution for the distribution of returns. We show that the tail shape characterizing the fatness of the unconditional distribution of returns can be directly derived from some structural variables that govern the traders’ interactions, namely the herding propensity and the autonomous switching tendency.JEL classifications: G12; C61Earlier versions of this paper have been presented at the 11th Symposium of the Society of Nonlinear Dynamics and Econometrics, Florence, March 2003, the 8th Spring Meeting of Young Economists, Leuven, April 2003, the 8th Workshop on Economics with Heterogeneous Interacting Agents, Kiel, May 2003, the 27th congress of Associazione per la Matematica Applicata alle Scienze Economiche e Sociali, Cagliari, September 2003; research seminars at the Department of Econometrics, University of Geneva, March 2003, and at the Department of Physics, University of Cagliari, May 2003, and have gained considerably from comments by many participants in these events.