This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calculate the classification accuracy. Statistical analysis for the result of the classification of each scene is presented for each class .The study showed that the ICA transform makes the satellite image significantly increases the classification accuracy, as well as that the Gaussian kernel gives the highest classification accuracy than other kernels.
Length of plasma generated by dc gas discharge under different vacuum pressures was studied experimentally. The cylindrical discharge tube of length 2m was evacuated under vacuum pressure range (0.1-0.5) mbar at constant external working dc voltage 1500V. It was found that the plasma length (L) increased exponentially with increasing of background vacuum air pressure. Empirical equation has been obtained between plasma length and gas pressure by using Logistic model of curve fitting. As vacuum pressure increases the plasma length increases due to collisions, ionizations, and diffusions of electrons and ions.
The assessment of a river water’ quality is an essential procedure of monitor programs and isused to collect basic environmental data. The management of integrated water resources in asustainable method is also necessary to allow future generations to meet their water needs. Themain objective of this research is to assess the effect of the Diyala River on Tigris River waterquality using Geographic Information System (GIS) technique. Water samples have beencollected monthly from November 2017 to April 2018 from four selected locations in Tigris andDiyala Rivers using the grab sampling method. Fourteen parameters were studied which areTurbidity, pH, Dissolved Oxygen, Biological Oxygen Demand, Electrical Conductivity, TotalDissolved Solids,
... Show MoreThe assessment of a river water’ quality is an essential procedure of monitor programs and is used to collect basic environmental data. The management of integrated water resources in a sustainable method is also necessary to allow future generations to meet their water needs. The main objective of this research is to assess the effect of the Diyala River on Tigris River water quality using Geographic Information System (GIS) technique. Water samples have been collected monthly from November 2017 to April 2018 from four selected locations in Tigris and Diyala Rivers using the grab sampling method. Fourteen parameters were studied which are Turbidity, pH, Dissolved Oxygen, Biological Oxygen Demand, Electrical Conductivi
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The purpose of this research is to improve the organizational performance of the Oil Projects Company by adopting an approach to strategic change، and finding appropriate solutions to the problems facing the company. The researcher adopted in designing his research by conducting a survey of previous literature that dealt with approaches to strategic change، as the results of the survey showed that most researchers agree on the approach of renewal and modernization، Which formed a starting point for the researcher to identify the extent of the company's management interest in renewal and modernization to improve its level of performance، and the quality of the procedures followed on the ground that is related to
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreThe civil engineering field currently focus on sustainable development. It is important to develop new sustainable and economic generations of concrete, using eco-friendly materials in the construction industry with a fair amount of costs and minimizing the impact upon the environment by reducing CO2 emissions from the cement industry as a whole while still obtaining high cement quality and strength. The main objective of this research is to clarify the mechanical behavior and ability to use Portland limestone cement in producing self compacted concrete, due to the beneficious effec of the limestone cement economically and enviromently. The research investigates the effect of using steel and polymer meshs as reinforcement, where the results
... Show MoreSlurry-infiltrated fibrous concrete (SIFCON) is a special type of concrete that has great strength, as well as high ductility. However, the unit weight is high, which exceeds the unit weight of fiber-reinforced concrete, because of the high fiber content. This research aims to verify the compressive and flexural strength, as well as the density of SIFCON when using two different fibers (steel and polyolefin). Sometimes mono type of fiber steel or polyolefin, sometimes by hybridizing two types of fiber steel + polyplefin. Volume fraction (6% for all species) was used. Hook-end steel fiber and polyolefin fiber are used. With hybridization, a total volume fraction of 6% was used, which
World statistics proved that the most of work dangerous accidents, which causes death, are occurred in the construction works. These accidents related to many causes such as loss of workers experience and ignoring rules of safety requirements, especially young workers. Due to the risk of accidents that may occur in the site of work, the idea of this study crystallized to show the relationship between the age of worker and number of injuries and accidents, to identify the causes of these injuries, and to put the appropriate solutions to avoid or reduce the risk of work injuries. Also, the research shows the main principles of safety requirements to forming a clear picture about the subject of the study. A questioner form was prepared to c
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