Radiotherapy is medical use of ionizing radiation, and commonly applied to the
cancerous tumor because of its ability to control cell growth.
The amount of radiation used in photon radiation therapy called dose (measured
in grey unit), which depend on the type and stage of cancer being treated.
In our work, we studied the dose distribution given to the tumor at different
depths (zero-20 cm) treated with different field size (4×4- 23×23 cm).
Results show that the deeper treated area has less dose rate at the same beam
quality and quantity. Also it has been noted increasing in the field increasing in the
depth dose at the same depth even if the radiation energy is constant. Increasing in
radiation dose attributed to the scattered radiation, which is expected,
proportionately with increase in the beam size. The aim of work studies the
relationship between the depth dose and the radiation source beam size
This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics
... Show MorePulsed laser deposition (PLD) technique was applied to prepared Chromium oxide (Cr2O3) nanostructure doped with Titanium oxide (TiO2) thin films at different concentration ratios 3,5,7 and 9 wt % of TiO2. The effect of TiO2 dopant on the average size of crystallite of the synthesized nanostructures was examined by X-ray diffraction. The morphological properties were discussed using atomic force microscopy(AFM). Observed optical band gap value ranged from 2.68 eV to 2.55 eV by ultraviolet visible(UV-Vis.) absorption spectroscopy with longer wave length shifted in comparison with that of the bulk Cr2O3 ~3eV. This indicated that the synthesized samples a
... Show MoreThe identification and sequencing of Amyloid Precursor Protien (APP) and presenilin (PS) opened the door for the engineering of transgenic mouse models to study pathogenic mechanisms of Alzheimer Disease (AD). The first successful mouse models over-expressed human APP with an Familiar AD (FAD) linked mutation in the brain. These mice exhibit Aß plaques, neuron loss, dystrophic neurites, inflammatory responses, learning impairments and deficits in synaptic transmission and/or long-term potentiation. The genotypes of all offspring of APP/PS1 mutant mice are analysed by Polymerise Chain Reactions. Generally there are two possibilities to analyse the DNA. The First, primers for APP or PS1 was used separately assuming that both genes are int
... Show MoreIn this study, pure Co3O4 nano structure and doping with 4 %, and
6 % of Yttrium is successfully synthesized by hydrothermal method.
The XRD examination, optical, electrical and photo sensing
properties have been studied for pure and doped Co3O4 thin films.
The X-ray diffraction (XRD) analysis shows that all films are
polycrystalline in nature, having cubic structure.
The optical properties indication that the optical energy gap follows
allowed direct electronic transition calculated using Tauc equation
and it increases for doped Co3O4. The photo sensing properties of
thin films are studied as a function of time at different wavelengths to
find the sensitivity for these lights.
High photo sensitivity dope
Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
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