A concept of indoor solar illumination is described and simulated. The solar illumination system is composed of a tracking primary reflector, a selective secondary reflector, a visible light guide and a scattering solid glass tube fixture. Each part of the solar illumination system is optically suited and compatible with other parts to realize high efficiency. The simulation is conducted for Baghdad city for a library hall. Two major days over a year are chosen to investigate the illumination system for acceptable visible light level for reading hall. The two days are: summer solstice day and winter solstice day at 8:00 AM and 12:00 PM for each. Research results showed that the design of the solar system is achieved on the base of minimu

The performance of a solar assisted desiccant cooling system for a meeting-hall located in the College of Engineering/University of Baghdad was evaluated theoretically. The system was composed of four components; a solar air heater, a desiccant dehumidifier, a heat exchanger and an evaporative cooler. A computer simulation was developed by using MATLAB to assess the effect of various design and operating conditions on the performance of the system and its components. The actual weather data on recommended days were used to assess the load variation and the system performance during those days. The radiant time series method (RTS) was used to evaluate the hourly variation of the cooling load. Four operation modes were employed for perform

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: C-reactive protein (CRP) is an acute phase protein that its plasma levels increase after trauma or surgery so it is used as an indicator for the level of inflammation after surgery. The objective of this study is to investigate pre- and post-operative levels of CRP in three types of oral surgical interventions (Apicoectomy, Impaction, and Impacted teeth exposure). Materials and Methods: A total number of (48) healthy individuals aged (20-60) years who needed oral surgical intervention for either (removal of impacted third molars, exposure of an impacted canine, or Apicoectomy). A 4ml venous blood was obtained from each patient at two occasions (pre-operatively at the day of operation and post-operatively after 48 hours), then ce

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

The characters of facades' form of the Iraqi building after 2003 have been changed, it has been described by many names. The problem of the research is that what are the features of the characters of the form in the façades of the buildings in Baghdad city after 2003? Are the façade of the individual houses or the commercial buildings is the heaviest in the visual weight? The research aims to answer those questions by choosing the vernacular architecture as a measurement tool. It is the informal image of the architecture, which is built by people informally and spontaneously, without official control and legislation to be organized. This is smellier to what has happened in Baghdad, after 2003 according to previous stud