Providing stress of poetry on the syllable-, the foot-, and the phonological word- levels is one of the essential objectives of Metrical Phonology Theory. The subsumed number and types of syllables, feet, and meters are steady in poetry compared to other literary texts that is why its analysis demonstrates one of the most outstanding and debatable metrical issues. The roots of Metrical Phonology Theory are derived from prosody which studies poetic meters and versification. In Arabic, the starting point of metrical analysis is prosodic analysis which can be attributed to يديهارفلا in the second half of the eighth century (A.D.). This study aims at pinpointing the values of two metrical parameters in modern Arabic poetry. To

     Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd  level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

      This study shows the effects of copper material electrode, applied voltage, and different pressure values on electrical discharge plasma. The purpose of the work is the application of the spectral analysis method to obtain accurate results of nitrogen plasma parameters. By using the optical emission spectroscopy (OES), many N₂ molecular spectra peaks appeared in the range from 300 to 480 nm. Also, some additional peaks were recorded, corresponding to atomic and ionic lines for nitrogen, target material, and hydrogen, in all samples. The electron density (n_e) was calculated from the measurement of Stark broadening effect, which was found to decrease with increasing pressure from 0.1 mba

        The adsorption of Congo red (CR) dye on modified synthetic zeolite 5A  , the general name of which is Linde Type A (LTA)which is modified by amino mercepto thiadiazole (AMT)  and have been characterized  by using fourier transform infrared (FT-IR) , x-ray diffraction (XRD) spectroscopies, atomic force microscopy (AFM) and scanning electron microscope (SEM) analysis.In this work Modified zeolite was utilized as adsorbent to remove (CR) dye from aqueous solution by adsorption. Batch experiments were conducted to study the effects contact time , initial concentration of adsorbate and temperature on dye adsorption. The equilibrium adsorption data were analyzed by using several isotherm models ( Freu

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

In this paper, a national grid-connected photovoltaic (PV) system is proposed. It extracts the maximum power point (MPP) using three-incremental-steps perturb and observe (TISP&O) maximum power point tracking (MPPT) method. It improves the classic P&O by using three incremental duty ratio (ΔD) instead of a single one in the conventional P and O MPPT method. Therefore, the system's performance is improved to a higher speed and less power fluctuation around the MPP. The Boost converter controls the MPPT and then is connected to a three-phase voltage source inverter (VSI). This type of inverter needs a high and constant input voltage. A second-order low pass (LC) filter is connected to the output of VSI to reduce t

This paper deals with the estimation of the stress strength reliability for a component which has a strength that is independent on opposite lower and upper bound stresses, when the stresses and strength follow Inverse Kumaraswamy Distribution. D estimation approaches were applied, namely the maximum likelihood, moment, and shrinkage methods. Monte Carlo simulation experiments were performed to compare the estimation methods based on the mean squared error criteria.

The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each