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Search Results: 1 - 10 of 2913 matches for " Enrico Ser-Giacomi "
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Information Recovery In Behavioral Networks
Tiziano Squartini,Enrico Ser-Giacomi,Diego Garlaschelli,George Judge
Physics , 2015, DOI: 10.1371/journal.pone.0125077
Abstract: In the context of agent based modeling and network theory, we focus on the problem of recovering behavior-related choice information from origin-destination type data, a topic also known under the name of network tomography. As a basis for predicting agents' choices we emphasize the connection between adaptive intelligent behavior, causal entropy maximization and self-organized behavior in an open dynamic system. We cast this problem in the form of binary and weighted networks and suggest information theoretic entropy-driven methods to recover estimates of the unknown behavioral flow parameters. Our objective is to recover the unknown behavioral values across the ensemble analytically, without explicitly sampling the configuration space. In order to do so, we consider the Cressie-Read family of entropic functionals, enlarging the set of estimators commonly employed to make optimal use of the available information. More specifically, we explicitly work out two cases of particular interest: Shannon functional and the likelihood functional. We then employ them for the analysis of both univariate and bivariate data sets, comparing their accuracy in reproducing the observed trends.
Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves
Vincent Rossi,Enrico Ser-Giacomi,Cristóbal López,Emilio Hernández-García
Physics , 2014, DOI: 10.1002/2014GL059540
Abstract: Oceanic dispersal and connectivity have been identified as crucial factors for structuring marine populations and designing Marine Protected Areas (MPAs). Focusing on larval dispersal by ocean currents, we propose an approach coupling Lagrangian transport and new tools from Network Theory to characterize marine connectivity in the Mediterranean basin. Larvae of different pelagic durations and seasons are modeled as passive tracers advected in a simulated oceanic surface flow from which a network of connected areas is constructed. Hydrodynamical provinces extracted from this network are delimited by frontiers which match multi-scale oceanographic features. By examining the repeated occurrence of such boundaries, we identify the spatial scales and geographic structures that would control larval dispersal across the entire seascape. Based on these hydrodynamical units, we study novel connectivity metrics for existing reserves. Our results are discussed in the context of ocean biogeography and MPAs design, having ecological and managerial implications.
Flow networks: A characterization of geophysical fluid transport
Enrico Ser-Giacomi,Vincent Rossi,Cristobal Lopez,Emilio Hernandez-Garcia
Physics , 2014, DOI: 10.1063/1.4908231
Abstract: We represent transport between different regions of a fluid domain by flow networks, constructed from the discrete representation of the Perron-Frobenius or transfer operator associated to the fluid advection dynamics. The procedure is useful to analyze fluid dynamics in geophysical contexts, as illustrated by the construction of a flow network associated to the surface circulation in the Mediterranean sea. We use network-theory tools to analyze the flow network and gain insights into transport processes. In particular we quantitatively relate dispersion and mixing characteristics, classically quantified by Lyapunov exponents, to the degree of the network nodes. A family of network entropies is defined from the network adjacency matrix, and related to the statistics of stretching in the fluid, in particular to the Lyapunov exponent field. Finally we use a network community detection algorithm, Infomap, to partition the Mediterranean network into coherent regions, i.e. areas internally well mixed, but with little fluid interchange between them.
Most probable paths in temporal weighted networks: An application to ocean transport
Enrico Ser-Giacomi,Ruggero Vasile,Emilio Hernandez-Garcia,Cristobal Lopez
Physics , 2014, DOI: 10.1103/PhysRevE.92.012818
Abstract: We consider paths in weighted and directed temporal networks, introducing tools to compute sets of paths of high probability. We quantify the relative importance of the most probable path between two nodes with respect to the whole set of paths, and to a subset of highly probable paths which incorporate most of the connection probability. These concepts are used to provide alternative definitions of betweenness centrality. We apply our formalism to a transport network describing surface flow in the Mediterranean sea. Despite the full transport dynamics is described by a very large number of paths we find that, for realistic time scales, only a very small subset of high probability paths (or even a single most probable one) is enough to characterize global connectivity properties of the network.
Dominant transport pathways in an atmospheric blocking event
Enrico Ser-Giacomi,Ruggero Vasile,Irene Recuerda,Emilio Hernández-García,Cristóbal López
Physics , 2015, DOI: 10.1063/1.4928704
Abstract: A Lagrangian flow network is constructed for the atmospheric blocking of eastern Europe and western Russia in summer 2010. We compute the most probable paths followed by fluid particles which reveal the {\it Omega}-block skeleton of the event. A hierarchy of sets of highly probable paths is introduced to describe transport pathways when the most probable path alone is not representative enough. These sets of paths have the shape of narrow coherent tubes flowing close to the most probable one. Thus, even when the most probable path is not very significant in terms of its probability, it still identifies the geometry of the transport pathways.
Geostatistical Modeling of Uncertainty for the Risk Analysis of a Contaminated Site  [PDF]
Enrico Guastaldi
Journal of Water Resource and Protection (JWARP) , 2011, DOI: 10.4236/jwarp.2011.38066
Abstract: This work is a study of multivariate simulations of pollutants to assess the sampling uncertainty for the risk analysis of a contaminated site. The study started from data collected for a remediation project of a steel- works in northern Italy. The soil samples were taken from boreholes excavated a few years ago and analyzed by a chemical laboratory. The data set comprises concentrations of several pollutants, from which a subset of ten organic and inorganic compounds were selected. The first part of study is a univariate and bivariate sta- tistical analysis of the data. All data were spatially analyzed and transformed to the Gaussian space so as to reduce the effects of extreme high values due to contaminant hot spots and the requirements of Gaussian simulation procedures. The variography analysis quantified spatial correlation and cross-correlations, which led to a hypothesized linear model of coregionalization for all variables. Geostatistical simulation methods were applied to assess the uncertainty. Two types of simulations were performed: correlation correction of univariate sequential Gaussian simulations (SGS), and sequential Gaussian co-simulations (SGCOS). The outputs from the correlation correction simulations and SGCOS were analyzed and grade-tonnage curves were produced to assess basic environmental risk.
Perturbation of Hydrogen Degenerate Levels and SO(4)  [PDF]
Enrico Onofri
Journal of Modern Physics (JMP) , 2014, DOI: 10.4236/jmp.2014.512106

We present a short note about the perturbative correction to Rydberg energies under a perturbation cosθ/rμ and discuss the role of SO(4) symmetry.

Evaluation of the Multiple Imputation Method Regarding the Quantitative Characters with Missing Observations and Covariance Structures
SER Gazel
Journal of Animal and Veterinary Advances , 2012, DOI: 10.3923/javaa.2011.3269.3273
Abstract: The study aims to apply the Multiple Imputation (MI) method in case of missing observation in the quantitative data and to determine the covariance structure between the repeated measures. In estimating the missing observations, missing observations were assumed to be Missing at Random (MAR) and MCMC (Markov Chain Monte Carlo) technique and multiple imputation method were applied. To that end, live-weight data with missing observation and quantitative structure was used. Time factor was included as a continuous variable into the model that was formed to evaluate the live-weight data and random intercept and slope model were created. Compound Symetry (CS), Heterogenous Compound Symetry (CSH), Unstructured (UN), First order Autoregressive (AR (1)), Heterogenous first order Autoregressive (ARH (1)), Toeplitz (TOEP) and Heterogenous Toeplitz (TOEPH) structures were used to determine the covariance structure between repeated measurements in the data sets that have missing observations and missing observations which were estimated. Consequently, CS, AR (1) and TOEP structures were assumed to be the best model according to the AIC and BIC cohesion goodness of fit in modeling covariance matrix structure regarding the variable in the model established on the repeated measure data handled in both cases. UN, CSH, TOEPH and ARH (1) were found to be the worst model with heterogeneous covariance structure.
The Analysis of Computer Education and Instructional Technologies Prospective Teachers’ Mind Maps Relating to Their Profession (The Case of Gazi University)
Ser?in KARATA?
Journal of Kirsehir Education Faculty , 2010,
Abstract: The purpose of this study is to analyze the professional perspectives of Computer Education and Instructional Technologies (CEIT) department prospective teachers. Predetermining prospective teachers’ potential problems will handle to the solution ways of these problems after graduation. In this manner, necessary measures could be taken focusing on different variables. So, this study thereby is believed to contribute to the literature. The data were collected during the 2007-2008 academic year at Gazi UniversityDepartment of CEIT with 28 fourth year students who are asked to create a mind map about the concept “CEIT teacher” served as the data collection instrument. The mind maps, examined by content analysis, were categorized under 8 headings; teaching characteristics, personality characteristics, interests/jobs; technology, computer, perspectives about the department, health and about future concerns. As for teaching characteristics, prospective teachers mentioned the need to have good communicationskills for the CEIT teacher, and for personality characteristics to have positive statements. The favorite job of prospective teachers’ interest is web/graphic designer. Some CEIT prospective teachers worry about their future and some of them are anxious about their health.
Performance Analysis of a Novel Dual-Frequency Multiple Access Relay Transmission Scheme  [PDF]
Javier DEL SER, Babak H. KHALAJ
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2009, DOI: 10.4236/ijcns.2009.27066
Abstract: In this paper we present the performance analysis of a novel channel assignment scheme where two non-cooperative independent users simultaneously communicate with their destination through a single relay by using only two frequency channels. The analytic derivation of the probability of symbol error for two main relay techniques will be provided, namely Amplify-and-Forward (AF) and Decode-and-Forward (DF). As shown by the obtained results, our switched-frequency approach results in a model that can achieve full- diversity by means of maximum-likelihood decoding at the receiver. Our results are especially important in the DF case, since in traditional techniques (such as half-duplex two-time slot approaches) two sources si-multaneously transmit on the same channel through the first time slot, which necessitates some sort of su-perposition coding. However, since in our scheme both users transmit over orthogonal channels, such a coding scheme is not required. In addition, it is shown that the DF approach based on our novel channel assign-ment scheme outperforms the AF scheme, especially in scenarios where the relay is closer to the receiver.
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