In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

This study's objective is to assess how well UV spectrophotometry can be used in conjunction with multivariate calibration based on partial least squares (PLS) regression for concurrent quantitative analysis of antibacterial mixture (Levofloxacin (LIV), Metronidazole (MET), Rifampicin (RIF) and Sulfamethoxazole (SUL)) in their artificial mixtures and pharmaceutical formulations. The experimental calibration and validation matrixes were created using 42 and 39 samples, respectively. The concentration range taken into account was 0-17 μg/mL for all components. The calibration standards' absorbance measurements were made between 210 and 350 nm, with intervals of 0.2 nm. The associated parameters were examined in order to develop the optimal c

People with diabetes can develop different foot problems. In the blood stream glucose reacts with hemoglobin to make a glycosylated hemoglobin molecule called hemoglobin A1c or HbA1c, the more glucose in the blood the more hemoglobin A1c will be present in the blood. The HbAlc test is currently one of the best ways to check diabetes to be under control.  The aim of study is to compare between the blood investigations which includes the fasting blood sugar and HbAlC (glycosylated hemoglobin), and to evaluate the benefit of  HbAlc (measurement for diabetic patients with foot ulcer,  to be a good indicator for controlling blood glucose). Sixty patients with type2 diabetes mellitus from the outpatient clinic of Baghdad Teachin

Objectives: The study aimed to determine the effect of chemotherapy on the life style of patients who
receive chemotherapy.
Methodology: A descriptive study was conducted in Specialty Surgery Teaching Hospital, Al-yamok
Teaching Hospital, and Radiation and Nuclear Medicine Hospital in Baghdad for the period from May
2007 to October 2008. A purposive "non-probability" sample of (loo) patients with bladder cancer
who receive chemotherapy where concerned in this study.
A questionnaire fom was constnicted for the purpose of the study and it was comprised of
two parts. The questiormaire consists of (125) items. They include (1) demographic information (2)
assessment of lifestyle dimension. The content validity of the q

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The Zubair reservoir in the Abu-Amood field is considered a shaly sand reservoir in the south of Iraq. The geological model is created for identifying the facies, distributing the petrophysical properties and estimating the volume of hydrocarbon in place. When the data processing by Interactive Petrophysics (IP) software is completed and estimated the permeability reservoir by using the hydraulic unit method then, three main steps are applied to build the geological model, begins with creating a structural, facies and property models. five zones the reservoirs were divided (three reservoir units and two cap rocks) depending on the variation of petrophysical properties (porosity and permeability) that results from IP software interpr

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and