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

The prospective study has been designed to determine some biomarkers in Iraqi female patients with
breast cancer. The current study contained 30 patients whose tissue samples have been collected from
hospitals in Medical City in Baghdad after consent patients themselves and used immunohistochemical
technique to determine these markers. The results showed a significant correlation between ER and PR tissue
markers (Sig = 0.000) and a significant correlation between cyclin E phenotype and cyclin E intensity (Sig =
0.001).

Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

Buckling analysis of a laminated composite thin plate with different boundary conditions subjected to in-plane uniform load are studied depending on classical laminated plate theory; analytically using (Rayleigh-Ritz method). Equation of motion of the plates was derived using the principle of virtual work and solved using modified Fourier displacement function that satisfies general edge conditions. The eigenvalue problem generated by using Ritz method, the set of linear algebraic equations can be solved using MATLAB for symmetric and anti-symmetric, cross and angle-ply laminated plate considering some design parameters such as aspect ratios, number of layers, lamination type and orthotropic ratio. The results obtained g

A series of new imides compounds[1-4] were synthesized from reaction of tetrachlorophthalic anhydride or nitro phthalic anhydride or malic anhydride or Succinic anhydride with 4-amino benzene thiol under fusion conditions. Chloroacetic acid has been added after compounds [1-4] reacted with distilled H2O and Na2CO3, producing compounds [5-8]. In benzene, compounds [5-8] also interacted with the thionyl chloride to produce [9-12]. Poly (vinyl alcohol) was chemically modified by reacting PVA with compounds [9-12] and dimethyl formamide to produce compounds [13-16]. Iron oxide nanoparticles (IONPs) are mixed with modified PVA [13-16] to create nanocomposites [17-20]. Spectral and analytical data from synthesized compounds, such as 1H-NMR, FTI

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c

Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. T

In this work semi–empirical method (PM3) calculations are carried out by (MOPAC) computational packages have been employed to calculate the molecular orbital's energies for some organic pollutants. The long– chain quaternary ammonium cations called Iraqi Clays (Bentonite – modified) are used to remove these organic pollutants from water, by adding a small cationic surfactant so as to result in floes which are agglomerates of organobentonite to remove organic pollutants. This calculation which suggests the best surface active material, can be used to modify the adsorption efficiency of aniline , phenol, phenol deriviatives, Tri methyl glycine, ester and pecticides , on Iraqi Clay (bentonite) by comparing the theoretical results w