This work aimed PVA nanofibers in a range of concentrations were successfully manufactured via electrospinning. PVA NFs/Si was effectively prepared using the electrospinning process. The structural, morphological, optical and electrical properties of the prepared PVA were studied using XRD, FE-SEM, UV-Vis spectrophotometer and I-V characteristics, respectively. The amorphous structure of PVA nanofibers was observed. The optical energy gap from ultraviolet to visible was between (2.75 and 2.41) eV, making this compound highly sensitive to visible orange light at 610 nm, with a photosensitivity of 66%. The optical energy gap of PVA/Si heterojunction was utilized to modify this film from the UV to the visible spectrum. As show in the results,

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

Autonomous systems are these systems which power themselves from the available ambient energies in addition to their duties. In the next few years, autonomous systems will pervade society and they will find their ways into different applications related to health, security, comfort and entertainment. Piezoelectric harvesters are possible energy converters which can be used to convert the available ambient vibration energy into electrical energy. In this contribution, an energy harvesting cantilever array with magnetic tuning including three piezoelectric bimorphs is investigated theoretically and experimentally. Other than harvester designs proposed before, this array is easy to manufacture and insensitive to manufacturi

Thin films of vanadium oxide nanoparticles doped with different concentrations of europium oxide (2, 4, 6, and 8) wt % are deposited on glass and Si substrates with orientation (111) utilizing by pulsed laser deposition technique using Nd:YAG laser that has a wavelength of 1064 nm, average frequency of 6 Hz and pulse duration of 10 ns. The films were annealed in air at 300 °C for two hours, then the structural, morphological and optical properties are characterized using x-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM) and UV-Vis spectroscopy respectively. The X-ray diffraction results of V2O5:Eu2O3 exhibit that the film has apolycrystalline monoclinic V2O5 and triclinic V4O7 phases. The FESEM image shows a h

We studied at the morphology, structural setup, and optical characteristics of thin cadmium (CdSe) films a thickness of 250 nm that were created by thermal evaporation over glass, The films exhibited a hexagonal shape were crystalline, and tended to form grains in the (111) crystallographic direction, according to the X-ray diffraction examinations. These characteristics were established using the investigation's findings. Through the use of thin films of CdSe doped with Ag at a concentration of 1.5%, the crystal structure orientations for pure CdSe (25.32, 41.84) and CdSe:Ag (25.39, 41.01) that were both pure as well as those that were doped with silver were both determined. The band gap of the optical spectrum decreased by 1.93–

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

Abstract

Paraffin wax is utilized for the heat storage applications taking advantage from the high stored latent heat during the phase change (from solid to fluid) period. What isn't right with this procedure is that the wax has a little heat transfer rate because of its low thermal conductivity. The thermal conductivity improvement of the paraffin wax has been examined utilizing nano-material with high thermal conductivity. In the recent study, (Al₂O₃) nanoparticles with weights of 1, 2, and 3% of the paraffin wax were added to the paraffin wax. The Iraqi paraffin wax accessible at the local markets was utilized as a phase change material (PCM).

Many properties of the

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