The selection of proper field survey parameters of electrical resistivity can significantly provide efficient results within a reasonable time and cost. Four electrode arrays of 2D Electric Resistivity Imaging (ERI) surveys were applied to characterize and detect subsurface archaeological bodies and to determine the appropriate array type that should be applied in the field survey. This research is to identify the subsurface features of the Borsippa archaeological site, Babylon Governorate, Middle Iraq. Synthetic modeling studies were conducted to determine the proper array and parameters for imaging the shallow subsurface features or targets. The efficiency of many array types has been tested for the detection the buried archaeological artifacts by enhancing the data coverage and sensitivity with minimizing ambiguity, from the observations. The applied arrays are Wenner, Wenner-Schlumberger, Pole-Dipole, and Dipole-Dipole. The simulated synthetic model consists of five shallow artifacts or walls embedded in the proposed silt clayey soil deposits. The models were constructed using the RES2DMOD program, and the Inversion approach was conducted using the RES2DINV program. Data of subsurface resistivity variation were inverted using the robust (i.e., L1-norm) inversion algorithm. The results reflect that the Dipole-Dipole array is recommended for shallow depths investigations, while for greater depths, the Wenner-Schlumberger array is proper to apply. The concluded results were applied in real case studies, to effectively image archaeological bodies, and successfully detecting low resistivity zones at superficial and greater depths. The relatively high resistivity features have been imaged which is probably related to the archaeological features. The results of the investigation provide archaeologists with proper insights for assessing and excavating properly the surveyed part of the Borsippa and any archaeological sites in future work.
This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.
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
... Show MoreImage 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
... Show MoreThe study addressed the water ecosystems of the marshes of Maysan Governorate as one of the important areas in Iraq in terms of the environmental, economic and tourism aspects. This area was exposed to great environmental changes due to natural and human factors which greatly affected the water ecosystem and made the area susceptible to many problems that affected the biological life of living organisms. The marshes of Maysan Governorate was affected by vital factors and non-vital factors. The marshes of Maysan Governorate was characterized by the UN Organization as one of the most important centers of biodiversity in the world because of the abundance of different and rare living organisms such as birds, fish, and reptiles as well as the e
... Show MoreAbstract Background: Coccidiosis in birds, including ostriches, is a major concern for animal health and productivity worldwide. There is limited data on Eimeria infections in farmed ostriches (Struthio camelus). Therefore, this research aims to investigate the species of Eimeria in ostriches using molecular methods. It is considered the first detailed molecular study of Eimeria species in Iraqi ostrich farms. Methods: A total of 150 ostrich feces samples from farms in three regions of Iraq using both microscopy and molecular methods. Statistical analysis of the positive samples was performed using the chi-square test, with the significance level set at a p-value < 0.05. Results: Initial testing showed a high prevalence rate of 51.33%. Five
... Show MoreBackground: Dental caries is the most common oral problem, although dental caries is not life threating, it has aharmful effect on quality of life. Socioeconomic factors were found to be strong predictors of the prevalence of oral diseases in children, likes family income, occupational prestige, and education. The aim of this study is to assess the effect of socioeconomic factors on occurrence dental caries in their children. Materials and methods: The sample consists of 550 kindergartens children aged between (4-5) years were selected randomly, girls and boys. The kindergartens selection was randomly from different geographical areas in Al-Najaf governorate. Information was taken from children's parents using questionnaire with the help o
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