In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

 A simple,  sensitive, accurate and low cost effective spectrophotometric method has been developed for the determination of Tetracycline and Doxycycline in pure and pharmaceutical formulations. The method is based on the reaction of methyldopa with 4-aminoantipyren (4-AAP) in presence of potassium ferriecyanide (PFC) in an alkaline medium. Two optimization methods were applied to determine the optimum conditions of oxidizing coupling reaction variables; univariate and design of experiment (DOE) method. The conditions effecting the  reaction; pH, buffer Volume,   reagent concentration, oxidant concentration, type of buffer, order of addition, time of reaction and stability were optimized . Under univariate and design

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Backgrround:: Cholera is gastroenteritis caused by enterotoxin producing Vibrio cholera. Cholera is predominantly a waterborne disease especially in countries with inadequate sanitation. Several rapid methods have been developed and used to detect V. cholerae serotypes directly from stools.
Objjecttiives:: to evaluate a rapid and accurate method for the diagnosis of cholera caused by V. cholerae O1 and O139 serogroups d to find the incidence of sporadic cases of cholera in Baghdad.
Metthods:: Sixty four stool samples were collected from four hospitals in Baghdad. The age of patients ranging from two months to 12 years, 26 were females and 38 males. Immunochromatographic visual test for qualitative detection of O1 and /or O139 serog

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu