M. Haddadi

Variable selection for image quality assessment using a Neural Network based approach

Compressed image quality assessment is of increasing importance in image coding systems where the schemes optimization is based on the distortion measure. There exist many distortion measures in the literature which are often validated by comparing them to the human appreciation of the image quality, in particular the Mean Opinion Score (MOS).

Customising cost function for optimising image quality measures performances

This article proposes two reduced reference variance/covariance-based image quality metrics using a neural network approach. The main contribution is that the proposed metrics are computationally simple and do not require the entire reference images to be calculated while still giving higher performance ranges than 18 other full-reference image quality metrics available in the literature. The first metric called error-based cost function is more accurate than most of the others, while the second metric called correlation-based cost function outperforms the others in terms of correlation and monotonicity. A comparative study has been conducted over three image quality databases including the LIVE (second release), TID2008 and CSIQ.

A complete statistical evaluation of state-of-the-art image quality measures

A quantitative predictive performance evaluation of seventeen full-reference image quality assessment metrics has been conducted in the present work. The process has been made over six publicly available subjectively rated image quality databases for four degradation types namely JPEG and JPEG2000 compression, Gaussian blur and Gaussian noise. Results show that there is no significant impact of the choice of image quality databases on the evaluation of the different full reference image quality metrics. These latter are found to fall into the same range of performance in terms of their correlation to the subjective human ratings, accuracy and monotonicity.

Design of an Adaptive Cathodic Protection Device Powered by Four Photovoltaic Solar Panels

Among a large number of photovoltaic applications, we are interested in the cathodic protection. It is one of the solutions used for the structures subjected to corrosion, mainly in oil and gas industries. In this work, optimum design sizing and system description are presented. Based on the design of a solar photovoltaic powered minicathodic protection system, a standard configuration of the photovoltaic system using a combination of four panels (two in series and two in parallel), has been derived. This standard size option must be matched at any cases of the cathodic protection station. For this purpose, an adaptive circuit, which is a voltage regulator with variable output, has been developed. Usually, cathodic protection systems work with constant current output, which is the necessary condition to procure immunity voltage of the structures against corrosion. The major difficulty to achieve this goal is the variations in the surrounding medium resistivity. To overcome this difficulty, several systems of control and regulation intended for cathodic protection system powered by photovoltaic energy have been designed and discussed. In our case, we propose an adaptive adjustment of the buck-boost converter output voltage by means of the microcontroller pulse width modulation output. In this paper, a complete design of the adaptive cathodic protection system using photovoltaic energy is carried out.

MIMO-descriptor systems model reduction

Abstract In this paper we present a new algorithm to construct different types of lower degree approximates of a high-degree linear singular system based onto singular value decomposition (SVD) approach that had the main advantage to preserve the key properties of the original system, such as stability, and give a quantization of approximation error. By the use of Schur method, model reduction is performed either on the proper and improper parts of a high-degree original system. A numerical example is provided to illustrate the behavior of approximates vis-a-vis original system.

Design of a Quadratic Boost Converter for a Standalone PV System Based on INC MPPT Algorithm

At now days, many researches to design and to improve the efficiency of PV systems using DC/DC converters are made. In this paper, the design of a quadratic boost for PV application based on Incremental conductance (INC) maximum power point tracking (MPPT) algorithm is presented. This kind of boost is an enhanced topology which can provide a high conversion voltage ratio for small duty cycle values. It presents the combination of two boosts connected in cascade using the same active switch. The proposed topology is commanded by hard switching signal based on PWM with a variable duty cycle given by the MPPT algorithm. Furthermore, in order to verify its performance, several simulations have been carried out under Matlab/Simulink environment. Also, the practical verification is held, the INC algorithm was implemented on to Xilinx Virtex-5 (XC5VLX50-1FFG676) Field Programmable Gate Array (FPGA). The quadratic boost is verified in real time with a real PV module SM-55. Experimental results confirm the convenience of the proposed topology in PV applications.

Correlation of hourly diffuse fraction of global horizontal solar radiation in Tamanrasset, Algeria

In order to evaluate the energy production of a solar system, the tilted global radiation is needed. Generally, only the global horizontal radiation data are available. To calculate a tilted global radiation, it is necessary to estimate the diffuse or the direct component of the horizontal solar radiation. In this article, a statistical procedure has been employed to develop correlations between the hourly measured of global radiation on horizontal surface and its diffuse component. In this context, the present work compares nine models for estimating diffuse fraction, using a 10 years data archive (1996–2005) of hourly global and diffuse solar radiation obtained at Tamanrasset meteorological station. After a first comparison of these nine models, three better performing models were selected for a more detailed analysis. The accuracy of the candidate correlations are performed in terms of the two widely used statistical indicators, MBE, RMSE and t-stat was also introduced. Thereby, new correlation coefficients are established taking into account the local data. The results suggest that some models can improve more accurately, by calibration procedure, the performance of the predictive models.

An overview of solar cells parameters extraction methods

This article presents a review of several methods used for parameters extraction of solar cells. These methods are found in the literature since the 60s. At least thirty distinct methods are mentioned and categorized. Three of each category are discussed in details. The best one is chosen based on some criteria cited below. This paper could serve as a convenient reference for future work in solar research and development on photovoltaic devices.