Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

An efficient combination of Adomian Decomposition iterative technique coupled Elzaki transformation (ETADM) for solving Telegraph equation and Riccati non-linear differential equation (RNDE) is introduced in a novel way to get an accurate analytical solution. An elegant combination of the Elzaki transform, the series expansion method, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has

This study Ajert to modify the chemical composition of milk fat cows and make it similar to the installation of milk fat mother through the addition of protein and soybean oil to be given Alkhltatnsp sensory protein that the best plan is the ratio of 1:1

Cox regression model have been used to estimate proportion hazard model for patients with hepatitis disease recorded in Gastrointestinal and Hepatic diseases Hospital in Iraq for (2002 -2005). Data consists of (age, gender, survival time terminal stat). A Kaplan-Meier method has been applied to estimate survival function and hazerd function.

The study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical test

Resource estimation is an essential part of reservoir evaluation and development planning which highly affects the decision-making process. The available conventional logs for 30 wells in Nasiriyah oilfield were used in this study to model the petrophysical properties of the reservoir and produce a 3D static geological reservoir model that mimics petrophysical properties distribution to estimate the stock tank oil originally in place (STOOIP) for Mishrif reservoir by volumetric method. Computer processed porosity and water saturation and a structural 2D map were utilized to construct the model which was discretized by 537840 grid blocks. These properties were distributed in 3D Space using sequential Gaussian simulation and the variation in