In this paper, an experimental study of the thermal performance for hybrid solar air conditioning system was carried out, to investigate system suitability for the hot climate in Iraq. The system consists of vapor compression unit combined with evacuated tube solar collector and liquid storage tank. A three-way valve was installed after the compressor to control the direction flow of the refrigerant, either to the storage tank or directly to the condenser. The performance parameters were collected by data logger to display and record in the computer by using LabVIEW software. The results show that the average coefficient of performance of hybrid solar air conditioning system (R=1) was about 2.42 to 2.77 and the average p

Due to the deterioration of water quality within the last few years because of the increase of water consumption and the waste water production and disposal into the river The water quality in both surface and ground water resources was negatively affected .The concept of water quality index is used as a tool for water quality classification in Tigris River within Baghdad City .Twenty two parameters of pollution were selected to measure the water quality indices of Tigris river within Baghdad city .Those parameters were measured during (2000-2004)as average monthly values ,three water treatment plants were selected out of the eight water treatment plants that exist along the river.Al Kharkh water treatment plant to reflect the water quality

OpenStreetMap (OSM) is the world’s biggest publicly licensed geographic data collection. Because OSM is rapidly being used in a wide range of applications, researchers have focused their efforts on determining its quality. The OSM buildings data quality is still ambiguous, due to the limitations, and a few researchers have evaluated the OSM buildings data quality through difficulties where the authoritative data are not obtainable. The focus of this research is to analyze and assess the accuracy of OSM buildings including completeness, and positional accuracy methods. Two different study areas in Baghdad city-Iraq have been investigated: Al-Rasheed and Al-Karrada. The process of the (OSM) data evaluation involved identifying the correspon

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

Three cohesionless free flowing materials of different density were mixed in an air fluidized bed to study the mixing process by calculating performance of mixing index according to Rose equation (1959) and to study the effect of four variables (air velocity, mixing time, particle size of trace component and concentration of trace component) on the mixing index and as well as on mixing performance. It was found that mixing index increases with increasing the air velocity, mixing time and concentration of trace component until the optimum value. Mixing index depends on the magnitude of difference in particle size The first set of experiments (salt then sand then cast iron) give higher mixing index and better performance of mixing than the

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include