Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extraction of features like mass lesions in mammograms for early detection of breast cancer. The proposed technique is based on a four-step procedure: (a) the preprocessing of the image is done, (b) regions of interest (ROI) specification, (c) supervised segmentation method includes two stages performed using the minimum distance (MD) criterion, and (d) feature extraction based on Gray level Co-occurrence matrices GLCM for the identification of mass lesions. The method suggested for the detection of mass lesions from mammogram image segmentation and analysis was tested over several images taken from Al-Ilwiya Hospital in Baghdad, Iraq. The proposed technique shows better results
Lasmiditan (LAS) is a recently developed antimigraine drug and was approved in October, 2019 for the treatment of acute migraines; however, it suffers from low oral bioavailability, which is around 40%.
This study aimed to improve the LAS bioavailability via formulation as nanoemulsionbased in situ gel (NEIG) given intranasally and then compare the traditional aqueous-LASsuspension (AQS) with the two successful intranasal prepared formulations (NEIG 2 and NEIG 5) in order to determine its relative bioavailability (F-relative) via using rabbits.
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
The lead has adverse effects in contamination the aquatic environment, for this reason, a laboratory simulation was conducted using kaolinite collected from the Ga’ara Formation at western Iraq to be considered as a natural sorbent material that can be addressed Pb2+ from the aqueous environments. The Energy-Dispersive X-ray Spectroscopy and atomic absorption spectroscopy clarifying very fine grains and pure phase with a very little quantity of quartz and has a number of active sites for adsorption. The sorption of kaolinite for the Pb2+ has been carefully tested by several designed laboratory experiments. Five lead solutions of different concentrations (25, 50, 75, 100 and 125 ppm) were tested under different values of pH (1.3-9)
... Show MoreCopper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc
... Show MoreThis paper highlights the main features of conjunctive adverbials and their occurrence in English academic prose. It accounts for the semantic roles of conjunctive adverbials, forms in which they are used, their positions within a sentence, and their frequency of occurrence in different registers with special reference to academic prose. It also tries to investigate possible differences in men's and women's use of conjunctive adverbials.
Keyword: conjunctive adverbials, linking adverbials, stance adverbials, circumstance adverbials, academic prose
Forty different samples (water and soil) were collected from different places in Iraq and Syria. Only (6) isolates showed the ability to grow and utilize agar as a sole source of carbon and energy. Morphological, cultural characterization and biochemical tests confirmed that These isolates belonging to genus Pseudomonas (HK1-HK6) .Plasmid profiles results showed that these isolates were harbored (2 -3) small Plasmids . HK1 isolate was selected because of its efficiency and ability to grow in high density on agar media for transformation and curing experiments, these were checked by transformation experiments after their expression in E. coli MM294. The genes responsible for agar utilization were located on thes
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