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Mathematical modelling of translation of mRNA in eucaryotes; steady states, time-dependent processes and application to reticulocytest

Journal of Theoretical Biology, 1980
Abstract Based on a kinetic model for the translation of mRNA the following conclusions are derived: 1. (1) Under normal conditions in a cell, initiation and elongation determine the rate of protein synthesis. The latter process turns out to be potentially even more important than the former.
R, Heinrich, T A, Rapoport
openaire   +2 more sources

An application of time-dependent ARMA models to reliability-decay processes

Microelectronics Reliability, 1993
Abstract This paper describes a somewhat different approach to the analysis of failure data of systems that operate under varying operational and/or environmental conditions. Surprisingly enough, it was found during the course of investigations that if the failure times of a system follow either Rayleigh, Weibull or exponential distributions and if ...
openaire   +1 more source

Strategies for Model Simplification and Data Reduction in Holographic Virtual Prototyping and Product Visualization Through Application Dependent Model Pre-Processing

Volume 2: 29th Computers and Information in Engineering Conference, Parts A and B, 2009
Three-dimensional (3D) displays are increasingly becoming common output devices for design support systems. They are widely used in applications such as virtual prototyping e.g. for visualization of product data and for concepts demonstration. Holographic displays are among the visualization devices that are capable of generating suitable 3D virtual ...
Eliab Z. Opiyo   +2 more
openaire   +1 more source

Slepian models for X 2-processes with dependent components with application to envelope upcrossings

Journal of Applied Probability, 1989
A Slepian model for the local behaviour near the level upcrossings of a x 2-process with dependent Gaussian components is presented. In case of independent components, this model is shown to take on a rather simple form, thereby simplifying earlier results by Aronowich and Adler.
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Soft Sensor Modeling Based on Multi-State-Dependent Parameter Models and Application for Quality Monitoring in Industrial Sulfur Recovery Process

IEEE Sensors Journal, 2018
Soft sensors have gained wide popularity in the industrial processes for online quality prediction in the recent years. In the case of online deployment, it is important to incorporate fewer input variables to improve the performance of the soft sensor.
Bahareh Bidar   +3 more
openaire   +1 more source

Application of EC, ECE, and ECE-ECE Models with Potential Dependent Transfer Coefficient to Selected Electrode Processes

Journal of The Electrochemical Society, 2007
The electrochemical-chemical (EC), electrochemical, chemical, electrochemical (ECE), and electrochemical, chemical, electrochemical-electrochemical, chemical, electrochemical (ECE-ECE) models with and without an included α variability were applied to the reduction of 2-methyl-2-nitropropane, benzenesulfonyl fluoride, and p-toluenesulfonyl fluoride. The
Przemysław T. Sanecki, Piotr M. Skitał
openaire   +1 more source

An Approach to Development of an Application Dependent SPICE Conformant Process Capability Model

2013
The Process capability modeling elaborated by the world-wide software engineering community during the last 25 years became a tool for systematization and codifying knowledge and experience of process oriented activities. This tool is designed to improve the predictability of activity results, i.e. process capability.
Michael Boronowsky   +3 more
openaire   +1 more source

Time dependent neural network models for detecting changes of state in complex processes: Applications in earth sciences and astronomy

Neural Networks, 2006
A computational intelligence approach is used to explore the problem of detecting internal state changes in time dependent processes; described by heterogeneous, multivariate time series with imprecise data and missing values. Such processes are approximated by collections of time dependent non-linear autoregressive models represented by a special kind
Valdés, Julio J., Bonham-Carter, Graeme
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Sequential Dependence Modeling Using Bayesian Theory and D-Vine Copula and Its Application on Chemical Process Risk Prediction

Industrial & Engineering Chemistry Research, 2014
An emerging kind of prediction model for sequential data with multiple time series is proposed. Because D-vine copula provides more flexibility in dependence modeling, accounting for conditional dependence, asymmetries, and tail dependence, it is employed to describe sequential dependence between variables in the sample data.
Xiang Ren   +3 more
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Nonlinear models with strongly dependent processes and applications to forward premia and real exchange rates [PDF]

open access: possible, 2006
This paper considers estimation and inference in some general non linear time series models which are embedded in a strongly dependent, long memory process. Some new results are provided on the properties of a time domain MLE for these models. The paper also includes a detailed simulation study which compares the time domain MLE with a two step ...
Richard T. Baillie, George Kapetanios
openaire   +1 more source

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