This paper presents an intelligent control strategy that uses a feedforward artificial neural network in order to improve the performance of the MPPT (Maximum Power Point Tracker) MPPT photovoltaic (PV) power system based on a modified Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk converter has some advantages compared to other type of converters. However the nonlinearity characteristic of the Cuk converter due to the switching technique is difficult to be handled by conventional controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. The NNC designed tracked the converter voltage output and improve the dynamic performance regardless load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyze and verified using MATLAB-Simulink. Simulation results confirm the excellent performance of the proposed NNC technique for the studied PV system. 

The multilevel multi-string inverter has gained much attention in recent years due to its advantages in lower switching loss, better electromagnetic compatibility, higher voltage capability, and lower harmonic distortion. Solar Energy is one of the favorable renewable energy resources and the multilevel inverter has been proven to be one of the important enabling technologies in photovoltaic (PV) utilization. As the number of levels increases, it is important to control more switches in parallel with their concurrent processing capability. This paper proposes an IGBT clamped three phase nine levels photovoltaic inverter topology with a multicarrier dual reference pulse-width modulated (PWM) control scheme. Four carrier waves of the fundamental frequency and different amplitudes are compared with two references (a sine wave and its opposite) for generating the control signals of the switches. Some DC/DC boost converters are used to amplify the voltage produced by the photovoltaic generators. Each of these converters is controlled by an MPPT algorithm in order to track the maximum power point of the GPV. Results of simulation in Matlab environment are given and discussed.

 In this study, single crystal Ge layers have been deposited by molecular beam epitaxy on PSi substrate, with different thicknesses (40 nm and 80 nm) at the growth temperature of 400°C. Raman and Atomic force microscopy (AFM) have been applied for investigation of photoluminescence, structural and morphological properties of the Ge on PSi layers. The results show a stronger Raman intensity of PSi due to change of its optical constant. Similarly the Si/Ge/PSi sample shows a peak at 399 cm-1 but with lower intensity compared with that of PSi probably due to the Si emission partially covered by the Ge inside the pores. Besides that a sharp Raman peak at 298 cm-1 is observed which reflects Raman active transverse optical mode of the introduced Ge which indicates the growth of Ge with good crystallinity. AFM characterization shows the rough silicon surface which can be regarded as a condensation point for small skeleton clusters to form, with different size of pores. These changes are highly responsible for its photoluminescence in the red wavelength range. This study explores the applicability of prepared Ge/PSi layers for its various applications in advanced optoelectronics field and silicon-on-insulator applications.

In this study, single crystal Ge layers have been deposited by molecular beam epitaxy on PSi substrate, with different thicknesses (40 nm and 80 nm) at the growth temperature of 400°C. Raman and Atomic force microscopy (AFM) have been applied for investigation of photoluminescence, structural and morphological properties of the Ge on PSi layers. The results show a stronger Raman intensity of PSi due to change of its optical constant. Similarly the Si/Ge/PSi sample shows a peak at 399 cm-1 but with lower intensity compared with that of PSi probably due to the Si emission partially covered by the Ge inside the pores. Besides that a sharp Raman peak at 298 cm-1 is observed which reflects Raman active transverse optical mode of the introduced Ge which indicates the growth of Ge with good crystallinity. AFM characterization shows the rough silicon surface which can be regarded as a condensation point for small skeleton clusters to form, with different size of pores. These changes are highly responsible for its photoluminescence in the red wavelength range. This study explores the applicability of prepared Ge/PSi layers for its various applications in advanced optoelectronics field and silicon-on-insulator applications.

In this study, single crystal Ge layers have been deposited by molecular beam epitaxy on PSi substrate, with different thicknesses (40 nm and 80 nm) at the growth temperature of 400°C. Raman and Atomic force microscopy (AFM) have been applied for investigation of structural and morphological properties in order to explain the photoluminescence properties of the Ge on PSi layers. The results show a stronger Raman intensity of PSi due to change of its optical constant. Similarly, the Si/Ge/PSi sample shows a peak at 399 cm-1 but with lower intensity compared with that of PSi probably due to the Si emission partially covered by the Ge inside the porous. Besides that, a sharp Raman peak at 298 cm-1 is observed which reflects Raman active transverse optical mode of the introduced Ge which indicate the growth of Ge with good crystallinity. AFM characterization shows the rough silicon surface which can be regarded as a condensation point for small skeleton clusters to form, with different size of pores. These changes are highly responsible for its photoluminescence in the red wavelength range. This study explores the applicability of prepared Ge/PSi layers for its various applications in advanced optoelectronics field and silicon-on-insulator applications.

Nowadays, communications networks becomes an essential tool for exchange information. This fact allows having robust systems that ensures secure transfers against arbitrary intrusion. In literature, we encounter various encryption schemes that meet this requirement. In this paper, we interest to the chaos cipher map that achieved image encryption and its resistance against attacks based on genetic algorithm, an efficiency bio-inspired heuristic that used as powerful tool for resolution of complex combinatory problems. The skill of the approach is the use of such heuristic, and for a first time, in attack of image encryption schemes. We show its effectiveness by reporting results of some preliminary experiments, including a comparison with brute force attack.