Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

Doppler broadening of the 511 keV positron annihilation ??? ? was used to estimate the concentration of defects ?? different deformation levels of pure alnminum samples. These samples were compressed at room temperature to 15, 22, 28, 38,40, and 75 % thickness reduction. The two-state ^sitron-trapping model has been employed. 'I he s and w lineshape parameters were measured using high-resolution gamma spectrometer with high pure germanium detector of 2.1 keV resolution at 1.33 MeV of 60Co. The change of defects concentration (Co) with the deformation level (e) is found to obey an empirical formula of the form Cd - A £ B where A and ? are positive constants that depend mainly on the deformation procedure and the temperature at which the def

There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim

Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use

Learning programming is among the top challenges in computer science education. A part of that, program visualization (PV) is used as a tool to overcome the high failure and drop-out rates in an introductory programming course. Nevertheless, there are rising concerns about the effectiveness of the existing PV tools following the mixed results derived from various studies. Student engagement is also considered a vital factor in building a successful PV, while it is also an important part of the learning process in general. Several techniques have been introduced to enhance PV engagement; however, student engagement with PV is still challenging. This paper employed three theories—constructivism, social constructivism and cognitive load t

The steady consumption of fish led many researchers to study it preferences over other foods, especially for radioactivity content. The specific activity concentration (S.A) of natural occurring radioactive materials (NORM) have been measured for Cyprinus carpio fishes collected from several industrial fishes' lakes located in Baghdad governorate using gamma spectroscopy doped with high purity germanium coaxial detector (HPGe). Thirteen fishes' samples were collected from industrial lakes, three samples were collected from cages, and two samples were collected from Trigger River. The last two types of samples were collected in order to compare the results with it. The measured overall averages of S.A for Ra-226, Th-232, and K-40 were 58.

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

Pure SnSe thin film and doped with S at different percentage (0,3,5,7)% were deposited from alloy by thermal evaporation technique on glass substrate at room temperature with 400±20nm thickness .The influences of S dopant ratio on characterization of SnSe thin film Nano crystalline was investigated by using Atomic force microscopy(AFM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Hall Effect measurement, UV-Vis absorption spectroscopy to study morphological, structural, electrical and optical properties respectively .The XRD showed that all the films have polycrystalline in nature with orthorhombic structure, with preferred orientation along (111)plane .These films was manufactured of very fine crystalline size in the ra