The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability fun

اهمية البحث والحاجة اليه :

ان القياس ضروري في دراسة كل فعالية يقوم بها الكائن الحي ، فلغة العلم ، هي رموز ومصطلحات وتعبيرات احصائية ( العيسى ، 1973 : 3 ) .

والقياس بشكل عام مهم في كل العلوم ، فهي على اختلاف انواعها تقوم بتوجيه اهتمامها نحو دراسة العلاقة بين المتغيرات ( Variables ) ، في الميادين التي تبحثها لذلك يجب ان تكون هذه المتغيرات قابلة للقياس بشكل دقيق لنتمكن من در

In this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.

The aim of this paper is to present the numerical method for solving linear system of Fredholm integral equations, based on the Haar wavelet approach. Many test problems, for which the exact solution is known, are considered. Compare the results of suggested method with the results of another method (Trapezoidal method). Algorithm and program is written by Matlab vergion 7.

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Dell Hymesin 1964coined The Ethnography of Communication in an attempt to explain the ways in which people use the language to interact. It hypothesizes that ethnography is less applicable among participants who have the same sociocultural background. It was proven that all the basic speech components occur whenever there is an interactional situation. The elements of (SPEAKING) schema are closely connected. However, the findings establish the fact that these elements take place effectively among participants who have the same sociocultural background.One of the most outstanding conclusions is the capability of the (SPEAKING) model to analyze not only an interaction between two or more participants, but also any event which consists of a mo