854 resultados para Probabilistic functions
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We calculate the equilibrium thermodynamic properties, percolation threshold, and cluster distribution functions for a model of associating colloids, which consists of hard spherical particles having on their surfaces three short-ranged attractive sites (sticky spots) of two different types, A and B. The thermodynamic properties are calculated using Wertheim's perturbation theory of associating fluids. This also allows us to find the onset of self-assembly, which can be quantified by the maxima of the specific heat at constant volume. The percolation threshold is derived, under the no-loop assumption, for the correlated bond model: In all cases it is two percolated phases that become identical at a critical point, when one exists. Finally, the cluster size distributions are calculated by mapping the model onto an effective model, characterized by a-state-dependent-functionality (f) over bar and unique bonding probability (p) over bar. The mapping is based on the asymptotic limit of the cluster distributions functions of the generic model and the effective parameters are defined through the requirement that the equilibrium cluster distributions of the true and effective models have the same number-averaged and weight-averaged sizes at all densities and temperatures. We also study the model numerically in the case where BB interactions are missing. In this limit, AB bonds either provide branching between A-chains (Y-junctions) if epsilon(AB)/epsilon(AA) is small, or drive the formation of a hyperbranched polymer if epsilon(AB)/epsilon(AA) is large. We find that the theoretical predictions describe quite accurately the numerical data, especially in the region where Y-junctions are present. There is fairly good agreement between theoretical and numerical results both for the thermodynamic (number of bonds and phase coexistence) and the connectivity properties of the model (cluster size distributions and percolation locus).
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We derive a set of differential inequalities for positive definite functions based on previous results derived for positive definite kernels by purely algebraic methods. Our main results show that the global behavior of a smooth positive definite function is, to a large extent, determined solely by the sequence of even-order derivatives at the origin: if a single one of these vanishes then the function is constant; if they are all non-zero and satisfy a natural growth condition, the function is real-analytic and consequently extends holomorphically to a maximal horizontal strip of the complex plane.
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Seismic recordings of IRIS/IDA/GSN station CMLA and of several temporary stations in the Azores archipelago are processed with P and S receiver function (PRF and SRF) techniques. Contrary to regional seismic tomography these methods provide estimates of the absolute velocities and of the Vp/Vs ratio up to a depth of similar to 300 km. Joint inversion of PRFs and SRFs for a few data sets consistently reveals a division of the subsurface medium into four zones with a distinctly different Vp/Vs ratio: the crust similar to 20 km thick with a ratio of similar to 1.9 in the lower crust, the high-Vs mantle lid with a strongly reduced VpNs velocity ratio relative to the standard 1.8, the low-velocity zone (LVZ) with a velocity ratio of similar to 2.0, and the underlying upper-mantle layer with a standard velocity ratio. Our estimates of crustal thickness greatly exceed previous estimates (similar to 10 km). The base of the high-Vs lid (the Gutenberg discontinuity) is at a depth of-SO km. The LVZ with a reduction of S velocity of similar to 15% relative to the standard (IASP91) model is terminated at a depth of similar to 200 km. The average thickness of the mantle transition zone (TZ) is evaluated from the time difference between the S410p and SKS660p, seismic phases that are robustly detected in the S and SKS receiver functions. This thickness is practically similar to the standard IASP91 value of 250 km. and is characteristic of a large region of the North Atlantic outside the Azores plateau. Our data are indicative of a reduction of the S-wave velocity of several percent relative to the standard velocity in a depth interval from 460 to 500 km. This reduction is found in the nearest vicinities of the Azores, in the region sampled by the PRFs, but, as evidenced by SRFs, it is missing at a distance of a few hundred kilometers from the islands. We speculate that this anomaly may correspond to the source of a plume which generated the Azores hotspot. Previously, a low S velocity in this depth range was found with SRF techniques beneath a few other hotspots.
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OBJECTIVE: To evaluate the potential advantages and limitations of the use of the Brazilian hospital admission authorization forms database and the probabilistic record linkage methodology for the validation of reported utilization of hospital care services in household surveys. METHODS: A total of 2,288 households interviews were conducted in the county of Duque de Caxias, Brazil. Information on the occurrence of at least one hospital admission in the year preceding the interview was obtained from a total of 10,733 household members. The 130 records of household members who reported at least one hospital admission in a public hospital were linked to a hospital database with 801,587 records, using an automatic probabilistic approach combined with an extensive clerical review. RESULTS: Seventy-four (57%) of the 130 household members were identified in the hospital database. Yet only 60 subjects (46%) showed a record of hospitalization in the hospital database in the study period. Hospital admissions due to a surgery procedure were significantly more likely to have been identified in the hospital database. The low level of concordance seen in the study can be explained by the following factors: errors in the linkage process; a telescoping effect; and an incomplete record in the hospital database. CONCLUSIONS: The use of hospital administrative databases and probabilistic linkage methodology may represent a methodological alternative for the validation of reported utilization of health care services, but some strategies should be employed in order to minimize the problems related to the use of this methodology in non-ideal conditions. Ideally, a single identifier, such as a personal health insurance number, and the universal coverage of the database would be desirable.
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This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.
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This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.
Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems
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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.
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Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.
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This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
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WDM multilayered SiC/Si devices based on a-Si:H and a-SiC:H filter design are approached from a reconfigurable point of view. Results show that the devices, under appropriated optical bias, act as reconfigurable active filters that allow optical switching and optoelectronic logic functions development. Under front violet irradiation the magnitude of the red and green channels are amplified and the blue and violet reduced. Violet back irradiation cuts the red channel, slightly influences the magnitude of the green and blue ones and strongly amplifies de violet channel. This nonlinearity provides the possibility for selective removal of useless wavelengths. Particular attention is given to the amplification coefficient weights, which allow taking into account the wavelength background effects when a band needs to be filtered from a wider range of mixed signals, or when optical active filter gates are used to select and filter input signals to specific output ports in WDM communication systems. A truth table of an encoder that performs 8-to-1 multiplexer (MUX) function is presented.
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In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.
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3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon, Portugal.
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This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.
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We present the supersymmetric standard model three-loop beta-functions for gauge and Yukawa couplings and consider the effect of three-loop corrections on the standard running coupling analyses.