Search results for " partial"
showing 10 items of 356 documents
Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares
2013
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from Hindawi: http://dx.doi.org/10.1155/2013/162938 Missing values are prevalent in microarray data, they course negative influence on downstream microarray analyses, and thus they should be estimated from known values. We propose a BPCA-iLLS method, which is an integration of two commonly used missing value estimation methods-Bayesian principal component analysis (BPCA) and local least squares (LLS). The inferior row-average procedure in LLS is replaced with BPCA, and the least squares method is put into an iterative framework. Comparative result shows that the proposed method has obtaine…
Simple algorithms for calculation of the axial‐symmetric heat transport problem in a cylinder
2001
The approximation of axial‐symmetric heat transport problem in a cylinder is based on the finite volume method. In the classical formulation of the finite volume method it is assumed that the flux terms in the control volume are approximated with the finite difference expressions. Then in the 1‐D case the corresponding finite difference scheme for the given source function is not exact. There we propose the exact difference scheme. In 2‐D case the corresponding integrals are approximated using different quadrature formulae. This procedure allows one to reduce the heat transport problem described by a partial differential equation to an initial‐value problem for a system of two ordinary diff…
A fully adaptive wavelet algorithm for parabolic partial differential equations
2001
We present a fully adaptive numerical scheme for the resolution of parabolic equations. It is based on wavelet approximations of functions and operators. Following the numerical analysis in the case of linear equations, we derive a numerical algorithm essentially based on convolution operators that can be efficiently implemented as soon as a natural condition on the space of approximation is satisfied. The algorithm is extended to semi-linear equations with time dependent (adapted) spaces of approximation. Numerical experiments deal with the heat equation as well as the Burgers equation.
A Survey on Proxy Mobile IPv6 Handover
2016
[EN] As wireless technologies have been improving in recent years, a mobility management mechanism is required to provide seamless and ubiquitous mobility for end users who are roaming among points of attachment in wireless networks. Thus, Mobile IPv6 was developed by the Internet Engineering Task Force (IETF) to support the mobility service. However, Mobile IPv6 is unable to fulfill the requirements of real-time applications, such as video streaming service and voice over IP service, due to its high handover (HO) latency. To address this problem, Proxy Mobile IPv6 (PMIPv6) has been introduced by the IETF. In PMIPv6, which is a network-based approach, the serving network controls mobility m…
Nonlinear psi-quasi-contractions of Ciric-type in partial metric spaces
2012
In this paper we obtain results of fixed and common fixed points for self-mappings satisfying a nonlinear contractive condition of Ciric-type in the framework of partial metric spaces. We also prove results of fixed point for self-mappings satisfying an ordered nonlinear contractive condition in the setting of ordered partial metric spaces.
Prediction and Surveillance Sampling Assessment in Plant Nurseries and Fields
2022
In this paper, we propose a structured additive regression (STAR) model for modeling the occurrence of a disease in fields or nurseries. The methodological approach involves a Gaussian field (GF) affected by a spatial process represented by an approximation to a Gaussian Markov random field (GMRF). This modeling allows the building of maps with prediction probabilities regarding the presence of a disease in plants using Bayesian kriging. The advantage of this modeling is its computational benefit when compared with known spatial hierarchical models and with the Bayesian inference based on Markov chain Monte Carlo (MCMC) methods. Inference through the use of the integrated nested Laplace app…
Two theorems of N. Wiener for solutions of quasilinear elliptic equations
1985
Relatively little is known about boundary behavior of solutions of quasilinear elliptic partial differential equations as compared to that of harmonic functions. In this paper two results, which in the harmonic case are due to N. Wiener, are generalized to a nonlinear situation. Suppose that G is a bounded domain in R n. We consider functions u: G--~R which are free extremals of the variational integral
Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions
2022
This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step. Hidden Markov models are analyzed for this purpose. Several prediction methods have been previously evaluated and the prediction by partial matching, which was the most efficient, is considered in this work as a component of a hybrid model together with an optimally configured hidden Markov model. The experimental results show that the hidden Markov model is a viable choice to predict the next assembly step, whereas the hybrid predictor is even better, outperforming in so…
A framework for assessing frequency domain causality in physiological time series with instantaneous effects.
2013
We present an approach for the quantification of directional relations in multiple time series exhibiting significant zero-lag interactions. To overcome the limitations of the traditional multivariate autoregressive (MVAR) modelling of multiple series, we introduce an extended MVAR (eMVAR) framework allowing either exclusive consideration of time-lagged effects according to the classic notion of Granger causality, or consideration of combined instantaneous and lagged effects according to an extended causality definition. The spectral representation of the eMVAR model is exploited to derive novel frequency domain causality measures that generalize to the case of instantaneous effects the kno…
Growth rates of F0 and F1 larval and juvenile European seabass Dicentrarchus labrax in resonse to ocean acidification and warming
2022
Ongoing climate change is leading to warmer and more acidic oceans. The future distribution of fish within the oceans depends on their capacity to adapt to these new environments. Only few studies have examined the effects of ocean acidification (OA) and warming (OW) on the metabolism of long-lived fish over successive generations. We therefore aimed to investigate the effect of OA on larval and juvenile growth and metabolism on two successive generations of European sea bass (Dicentrarchus labrax L.) as well as the effect of OAW on larval and juvenile growth and metabolism of the second generation. European sea bass is a large economically important fish species with a long generation time…