Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u

This research is marked by " lighting and processors formalism for spaces of shops selling mobile phones ," aims to " reveal about the relationship between lighting treatments formal designs spaces own internal selling mobile phone in addition to the recognition criteria Altsamama to lighting techniques and processes formality spaces shops competent to sell mobile phone " and lies the importance of this research in the " active role of the lighting in the building processors formalities and processes to prepare designs and show the final form integrated functionally and aesthetically so as to be ready for implementation , taking into consideration the role expressionist in the recipient and to make these spaces more than meet the require

In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

Acne scars are one of the most common problems following acne vulgaris. Despite the extensive list of available treatment modalities, their effectiveness depends upon the nature of the scar. Ablative lasers had been used to treat acne scars; one of them is the fractional CO2 laser. The aim of this study is to evaluate the outcome of fractional CO2 laser in the treatment of acne scars. Methods: Since January 2010 to June 2013, using 10600 nm fractional CO2 laser beams, the acne scar of 400 patients, 188 males and 212 females, mean age of 34 years, have been treated and classified according to severity into four grades following Goodman and Baron classification. Each patient underwent 3-5 sessions once monthly. The mean laser exposure time

In this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback