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Search Results: 1 - 10 of 233141 matches for " R.Rui "
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Musical Instrument Classification Based on Nonlinear Recurrence Analysis and Supervised Learning
Radioengineering , 2013,
Abstract: In this paper, the phase space reconstruction of time series produced by different instruments is discussed based on the nonlinear dynamic theory. The dense ratio, a novel quantitative recurrence parameter, is proposed to describe the difference of wind instruments, stringed instruments and keyboard instruments in the phase space by analyzing the recursive property of every instrument. Furthermore, a novel supervised learning algorithm for automatic classification of individual musical instrument signals is addressed deriving from the idea of supervised non-negative matrix factorization (NMF) algorithm. In our approach, the orthogonal basis matrix could be obtained without updating the matrix iteratively, which NMF is unable to do. The experimental results indicate that the accuracy of the proposed method is improved by 3% comparing with the conventional features in the individual instrument classification.
A Study on Communication Media Selection: Comparing the Effectiveness of the Media Richness, Social Influence, and Media Fitness  [PDF]
Rui Gu, Kunihiko Higa, Douglas R. Moodie
Journal of Service Science and Management (JSSM) , 2011, DOI: 10.4236/jssm.2011.43035
Abstract: Media selection has become a more complex problem because of the fast development of Information and Communication Technology. However, there is little quantified work on the tools for media selection decisions. The three main tools available are Media Richness Theory (MRT) [1], Social Influence Perspectives (SIP) [2], and Media Fitness Framework (MFF) [3,4]. MFF is a combination of the factors from MRT and SIP with additional factors for environmental and resource limitations. In this research, we tested the effectiveness of media selection prediction of these three tools on 72 communication tasks from 18 companies. We then compared the results to real data. This comparison showed MFF to be more effective than either MRT or SIP, particularly in multiple-media situations. MFF also had a faster convergence of media selection prediction.
512 anos de história conjunta... e muitos anos ainda por vir Five hundred twelve years of history together... and many more years to come
Flavia R Machado,Rui Moreno
Revista Brasileira de Terapia Intensiva , 2012, DOI: 10.1590/s0103-507x2012000200001
Further details on inference under right censoring for transformation models with a change-point based on a covariate threshold
Michael R. Kosorok,Rui Song
Mathematics , 2006,
Abstract: We consider linear transformation models applied to right censored survival data with a change-point based on a covariate threshold. We establish consistency and weak convergence of the nonparametric maximum lieklihood estimators. The change-point parameter is shown to be $n$-consistent, while the remaining parameters are shown to have the expected root-$n$ consistency. We show that the procedure is adaptive in the sense that the non-threshold parameters are estimable with the same precision as if the true threshold value were known. We also develop Monte-Carlo methods of inference for model parameters and score tests for the existence of a change-point. A key difficulty here is that some of the model parameters are not identifiable under the null hypothesis of no change-point. Simulation students establish the validity of the proposed score tests for finite sample sizes.
Learning ambiguous functions by neural networks
Rui Ligeiro,R. Vilela Mendes
Computer Science , 2013,
Abstract: It is not, in general, possible to have access to all variables that determine the behavior of a system. Having identified a number of variables whose values can be accessed, there may still be hidden variables which influence the dynamics of the system. The result is model ambiguity in the sense that, for the same (or very similar) input values, different objective outputs should have been obtained. In addition, the degree of ambiguity may vary widely across the whole range of input values. Thus, to evaluate the accuracy of a model it is of utmost importance to create a method to obtain the degree of reliability of each output result. In this paper we present such a scheme composed of two coupled artificial neural networks: the first one being responsible for outputting the predicted value, whereas the other evaluates the reliability of the output, which is learned from the error values of the first one. As an illustration, the scheme is applied to a model for tracking slopes in a straw chamber and to a credit scoring model.
Elementary signaling modes predict the essentiality of signal transduction network components
Rui-Sheng Wang, Réka Albert
BMC Systems Biology , 2011, DOI: 10.1186/1752-0509-5-44
Abstract: In this work, we present an integrative computational method for evaluating the essentiality of components in signaling networks. This approach expands an existing signaling network to a richer representation that incorporates the positive or negative nature of interactions and the synergistic behaviors among multiple components. Our method simulates both knockout and constitutive activation of components as node disruptions, and takes into account the possible cascading effects of a node's disruption. We introduce the concept of elementary signaling mode (ESM), as the minimal set of nodes that can perform signal transduction independently. Our method ranks the importance of signaling components by the effects of their perturbation on the ESMs of the network. Validation on several signaling networks describing the immune response of mammals to bacteria, guard cell abscisic acid signaling in plants, and T cell receptor signaling shows that this method can effectively uncover the essentiality of components mediating a signal transduction process and results in strong agreement with the results of Boolean (logical) dynamic models and experimental observations.This integrative method is an efficient procedure for exploratory analysis of large signaling and regulatory networks where dynamic modeling or experimental tests are impractical. Its results serve as testable predictions, provide insights into signal transduction and regulatory mechanisms and can guide targeted computational or experimental follow-up studies. The source codes for the algorithms developed in this study can be found at http://www.phys.psu.edu/~ralbert/ESM webcite.The normal functioning of biological organisms relies on the coordinated action of a multitude of components. The interactions between genes, proteins, metabolites and small molecules form networks that govern gene regulation, determine metabolic rates, and transduce signals [1,2]. Inter-cellular interaction networks such as neuronal netwo
Comparative Effects of Nitrogen Fertigation and Granular Fertilizer Application on Growth and Availability of Soil Nitrogen during Establishment of Highbush Blueberry
David R. Bryla,Rui M. A. Machado
Frontiers in Plant Science , 2011, DOI: 10.3389/fpls.2011.00046
Abstract: A 2-year study was done to compare the effects of nitrogen (N) fertigation and granular fertilizer application on growth and availability of soil N during establishment of highbush blueberry (Vaccinium corymbosum L. “Bluecrop”). Treatments included four methods of N application (weekly fertigation, split fertigation, and two non-fertigated controls) and four levels of N fertilizer (0, 50, 100, and 150 kg·ha?1 N). Fertigation treatments were irrigated by drip and injected with a liquid urea solution; weekly fertigation was applied once a week from leaf emergence to 60 d prior to the end of the season while split fertigation was applied as a triple-split from April to June. Non-fertigated controls were fertilized with granular ammonium sulfate, also applied as a triple-split, and irrigated by drip or microsprinklers. Weekly fertigation produced the smallest plants among the four fertilizer application methods at 50 kg·ha?1 N during the first year after planting but the largest plants at 150 kg·ha?1 N in both the first and second year. The other application methods required less N to maximize growth but were less responsive than weekly fertigation to additional N fertilizer applications. In fact, 44–50% of the plants died when granular fertilizer was applied at 150 kg·ha?1 N. By comparison, none of the plants died with weekly fertigation. Plant death with granular fertilizer was associated with high ammonium ion concentrations (up to 650 mg·L?1) and electrical conductivity (>3 dS·m?1) in the soil solution. Early results indicate that fertigation may be less efficient (i.e., less plant growth per unit of N applied) at lower N rates than granular fertilizer application but is also safer (i.e., less plant death) and promotes more growth when high amounts of N fertilizer is applied.
Feigenbaum networks
Rui Carvalho,R. Vilela Mendes,Joao Seixas
Physics , 1997,
Abstract: We study dynamical systems composed of a set of linearly coupled quadratic maps which, if uncoupled, would be on the Feigenbaum accumulation point. For two units we prove the existence of an infinite number of sinks for an open set of coupling parameters. In the limit of many units a mean field analysis also implies the stabilization in periodic orbits of, at least, a subset of the coupled units. Possible applications in the fields of control of chaos, signal processing through complex dynamics and as models of self-organization, are discussed.
From synchronization to multistability in two coupled quadratic maps
Rui Carvalho,Bastien Fernandez,R. Vilela Mendes
Physics , 2000, DOI: 10.1016/S0375-9601(01)00370-X
Abstract: The phenomenology of a system of two coupled quadratic maps is studied both analytically and numerically. Conditions for synchronization are given and the bifurcations of periodic orbits from this regime are identified. In addition, we show that an arbitrarily large number of distinct stable periodic orbits may be obtained when the maps parameter is at the Feigenbaum period-doubling accumulation point. An estimate is given for the coupling strength needed to obtain any given number of stable orbits.
Multiuser Charging Control in Wireless Power Transfer via Magnetic Resonant Coupling
Mohammad R. Vedady Moghadam,Rui Zhang
Computer Science , 2015,
Abstract: Magnetic resonant coupling (MRC) is a practically appealing method for realizing the near-field wireless power transfer (WPT). The MRC-WPT system with a single pair of transmitter and receiver has been extensively studied in the literature, while there is limited work on the general setup with multiple transmitters and/or receivers. In this paper, we consider a point-to-multipoint MRC-WPT system with one transmitter sending power wirelessly to a set of distributed receivers simultaneously. We derive the power delivered to the load of each receiver in closed-form expression, and reveal a "near-far" fairness issue in multiuser power transmission due to users' distance-dependent mutual inductances with the transmitter. We also show that by designing the receivers' load resistances, the near-far issue can be optimally solved. Specifically, we propose a centralized algorithm to jointly optimize the load resistances to minimize the power drawn from the energy source at the transmitter under given power requirements for the loads. We also devise a distributed algorithm for the receivers to adjust their load resistances iteratively, for ease of practical implementation.
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