In proteomics 2-dimensional SDS-polyacrylamide gel electrophoresis (2D-PAGE) is the most widely used method for analyzing protein mixtures qualitatively. There are, however, a lot of noise and measurement biases which...
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ISBN:
(纸本)9789604742813
In proteomics 2-dimensional SDS-polyacrylamide gel electrophoresis (2D-PAGE) is the most widely used method for analyzing protein mixtures qualitatively. There are, however, a lot of noise and measurement biases which needs to be accounted for both in the localization of spots as well as in the quantitative measurement of protein expression. Previous techniques for denoising 2D gels are based on thresholding, smoothing and spot recognition. Wavelet transformations have also been applied to denoise 2D gels, however these techniques are typically in the frequency domain and they tend to shift spots slightly. In this paper, we improve the protein spot detection process by wavelet de-noising based on genetic algorithm.
Input variables selection plays a critical role in data-driven modelling, especially for complex systems with high dimensionality between the input/output space. In this paper, a new artificial neural network based fo...
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Input variables selection plays a critical role in data-driven modelling, especially for complex systems with high dimensionality between the input/output space. In this paper, a new artificial neural network based forward input selection scheme is proposed. The objective of the proposed scheme is to select the smallest number of important variables as model inputs, which will then be used for neural-fuzzy data modelling. The proposed input selection scheme is applied to a case study of Charpy impact energy prediction, with data extracted from an industrial database. Model performance has been compared with previous results where a much larger input set was used. Simulation results show that the number of inputs for the Charpy data model can be significantly reduced with little performance degradation. Also, the performance of the proposed scheme outperforms both the standard correlation analysis and fuzzy clustering based input selection schemes.
This paper deals with design of a synchronous frame control strategy for single-phase inverter-based islanded distributed generation (DG) systems. Although, implementation of these regulators requires a minimum of two...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of ...
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An algorithmic framework is developed for automatic deployment of car-like robots based on Linear Temporal Logic (LTL) formulae over a set of regions of interest in the environment. The environment and the regions of interest are a priori known, and the robot has non-negligible size and restricted steering capabilities. The approach relies on constructing a probabilistic finite-state abstraction of the car-like robot and on finding a trajectory (run) in this abstraction such that the probability of satisfying the LTL formula is maximized. The feasibility of our approach is supported by simulations under Matlab environment.
In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous networks. Namely, we propose a distributed version of the well known simplex algorithm. We prove its convergen...
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The article presents thermal analysis of three-phase induction motor using coupled circuit models. The MATLAB/SIMULINK environment and PLECS toolbox were used to create mathematical model of the examined motor. Coeffi...
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The article presents thermal analysis of three-phase induction motor using coupled circuit models. The MATLAB/SIMULINK environment and PLECS toolbox were used to create mathematical model of the examined motor. Coefficient of heat transfer through the winding was set experimentally. Results of calculations presented are verified by the measurements on the physical motor.
Motivated by the distributed control of fleets of identical linear subsystems, we consider the stability of block upper-triangular switched linear systems with switching delay, when switching between stable modes. Pro...
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Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robu...
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Abstract This paper introduces a method for synthesizing reduced-order nonlinear model-based predictive controllers that have support in an arbitrary open subset, for semilinear parabolic equations. The predictive con...
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Abstract This paper introduces a method for synthesizing reduced-order nonlinear model-based predictive controllers that have support in an arbitrary open subset, for semilinear parabolic equations. The predictive control law is computed based on reduced-order, nonlinear multi-step-ahead finite-element predictors, identified directly from experimental input-output data. An advantage of this approach is that it does not require knowledge of the partial differential equation (PDE) model of the process. The proposed approach is computationally efficient and suitable for real-time implementation as it does not involve solving a complex nonlinear programming problem. The design method can deal effectively with load disturbances and noise in a similar manner to that adopted in the classical Generalized Predictive control framework. The method is used to design and evaluate numerically a nonlinear predictive controller for a one-dimensional nonlinear parabolic equation.
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoi...
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In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows to measure the relative position between the robot and some known objects (goals and beacons), and to use them to obtain the robot's absolute position, by means of a triangulation method. Finally, the results obtained in Webots and in the real platform are presented.
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