The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers

The Turkish Kurdistan Workers Party (PKK) is one of the most influential elements in the Iraqi national security since 2014. It has a new and effective role in the Iraqi political arena, as a result of participating in combat operations against ISIS in Nineveh Governorate, which prompted several minorities within the province to sympathize with its presence and its role in particular in Sinjar  after ISIS committed the most brutal crimes against the Aizidi minority, Turkey took advantage of the security conditions that Iraq went through after the entry of ISIS into the country to expand its influence in the north, using the pretext of the PKK and the previous agreement between the two countries on border protection. Also, the continued

Magnesium-doped Zinc oxide (ZnO: Mg) nanorods (NRs) films and pure Zinc oxide deposited on the p-silicon substrates were prepared by hydrothermal method. The doping level of the Mg concentration (atoms ratio of Mg to Zn was chosen to be 0.75% and 1.5%. X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDX) were performed to characterize the prepared films. X-ray diffraction analysis showed a decrease in the lattice parameters of the Mg-doped ZnO NRs. Under 10V applied bias voltage, the responsivity of p-n junction UV photodiode based on pure ZnO and Mg: ZnO with doping ratio (0.75% and 1.5%) was 0.06 A/W and (0.15A/W and 0.27A/W) at UV illumination of wavelength 365 nm respectively, 0.071 A/W and (0.084A/W and 0.11A/W) fo

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

    In this paper a method  to determine whether an image is forged (spliced) or not is presented. The proposed method is based on  a classification model to determine the authenticity of a tested image. Image splicing causes many sharp edges (high frequencies) and discontinuities to appear in the spliced image. Capturing these high frequencies in the wavelet domain rather than in the spatial domain is investigated in this paper. Correlation between high-frequency sub-bands coefficients of Discrete Wavelet Transform (DWT) is also described using co-occurrence matrix. This matrix was an input feature vector to a classifier. The best accuracy of 92.79% and 94.56% on Casia v1.0 and Casia v2.0 datasets respectively was achieved. This pe

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to