Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

Schizophrenic patients who are at great risk of relapse are characterized by non-compliance,
denial of illness and need for treatment and no contact with family. So, the prevention of relapse
and readmission to hospital are crucial in mental health practice.
The present study is a descriptive-analytical study that was carried out from November 2nd
2006 through the end of 20 of April 2008.
Objectives: To assess the associated factors with the risk of relapse in schizophrenic patients at
psychiatric hospitals in Baghdad city.
Methodology: A purposive "non-probability" sample of (50) schizophrenic patient who hasd
relapsed was involved in the present study. Data were collected through the use of the constructed
qu

The effect of ethanol and methanol solvent, and their mixture has been studied on the absorption and fluorescence spectra of laser dye Rhodamine B at concentration of (10-4) Molar at room temperature. The molar absorption coefficient has been determined for mixture which was (3.223) at wave number (18181.8 cm-1), Also the Quantum Efficiency of the two solvents (ethanol and methanol) and their mixture have been calculated ,which was for mixture spectrum (38.94%) and it was larger comparing with other and solvents. The characteristics of spectrum has been determined by calculating (??) of absorption spectrum for the solvents and its mixture at maximum wave number ( ) cm-1 depending on solvent polarity and the transitions between molecular ene

Gas adsorption phenomenon on solid surface has been used as a mean in separation and purification of gas mixture depending on the difference in tendencies of each component in the gas mixture to be adsorbed on the solid surface according to its behaviour. This work concerns to study the possibilities to separate the gas mixture using adsorption-desorption phenomenon on activated carbon. The experimental results exhibit good separation factor at temperature of -40 .

Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m