The current study aims to show the importance of plant products as mosquitocides against Culex quinquefasciatus. Castor oil Nanoemulsions were subedit in various ratios including castor oil, ethanol, tween 80, and deionized water by using ultrasonication. Thermodynamic, centrifugation, PH, assay which improved that the formula  of 10 ml  of castor  oil, ethanol  5ml, tween 80 (14 ml) and deionized water 71ml was more stable than other formulas. The stable formula of castor oil nanoemulsion was characterized by transmission electron microscopy (TEM) and dynamic light scattering (DLS). Nanoemulsion droplets were spherical in shape and were found to have a Z-average diameter of 87.4nm. A concentration of ca

In this research, we investigate and evaluate the efficiency of a hetero junction N749-  device based on a simple donor-acceptor model for electron transfer. Electron transfer from a photo-excited N749 sensitized into a wide-band gap  is the basic charge separation in dye-sensitized solar cells, or "DSSCs". Due to the understanding of the current of the DSSCs functioning mechanism, the energy levels of the hetero junction N749-  device surrounded by DCM solvent as polar media must be continuum levels. The current-voltage (J-V) characteristics of the N749- device are calculated in two concentrations at room temperature (T=300 k) and 100   irradiation. The fill factor and efficiency of the device are found to be 0.134 and 6.990 for con

    As part of our research on efficiency improvement of PERC (Passivated Emitter Rear Solar Cell), achieving very low reflectivity values of solar cell surface is a must. One of the most advance technologies to do so is the use of advanced texturing for the front surface of the cells. This texture, also known as Black Silicon, consists of peaks and valleys of nano metric dimensions and capable of dramatically reducing the reflectance of the front surface. A reflectance around 5%  was reached ,using simulation, when using a Black-Silicon texturing with height of 50nm with peak rounding of 5nm. Even though this texturing may affect other parameters such as series resistance or surface recombination, as a starting point

Solar cells thin films were prepared using polyvinyl alcohol (PVA) as a thin film, with extract of natural pigment from local flower. A concentration of 0.1g/ml of polyvinyl alcohol solution in water was prepared for four samples, with various concentrations of plant pigment (0, 15, 25 and 50) % added to each of the four solutions separately for preparing (PVA with low concentrated dye , PVA with medium concentrated dye and PVA with high concentrated dye ) thin films respectively . Ultraviolet absorption regions were obtained by computerized UV-Visible (CECIL 2700). Optical properties including (absorbance, reflectance, absorption coefficient, energy gap and dielectric constant) via UV- Vis were tested, too.  Fourier transform infra

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In