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Electrical Resistivity Synthetic Modeling and Field Survey for Subsurface Features Investigation of the Borsippa Archaeological Site, Babylon Governorate, Middle Iraq
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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.

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Natural Sciences
Geology and Structure Analysis of Shaqlawa – Merawa Area, Northern Iraq Using Remote Sensing, GIS and Field Observations
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This study appears GIS techniqueand remote sensing data are matching with the field observation to identify the structural features such as fault segments in the urban area such as the Merawa and Shaqlawa Cities. The use of different types of data such as fault systems, drainage patterns (previously mapped), lineament, and lithological contacts with spatial resolution of 30m was combined through a process of integration and index overlay modeling technique for producing the susceptibility map of fault segments in the study area. GIS spatial overlay technique was used to determine the spatial relationships of all the criteria (factors) and subcriteria (classes) within layers (maps) to classify and map the potential ar

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Design and implementation of silicon single-photon avalanche photodiode modeling tool for QKD systems
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Single-photon detection concept is the most crucial factor that determines the performance of quantum key distribution (QKD) systems. In this paper, a simulator with time domain visualizers and configurable parameters using continuous time simulation approach is presented for modeling and investigating the performance of single-photon detectors operating in Gieger mode at the wavelength of 830 nm. The widely used C30921S silicon avalanche photodiode was modeled in terms of avalanche pulse, the effect of experiment conditions such as excess voltage, temperature and average photon number on the photon detection efficiency, dark count rate and afterpulse probability. This work shows a general repeatable modeling process for significant perform

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Publication Date
Mon Jan 01 2024
Journal Name
Malaysian Journal Of Nursing
Experiences of Nurses in Providing Care for Patients on the Cancer Journey: A Cross-Sectional Survey
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Publication Date
Mon Oct 01 2012
Journal Name
Iraqi Journal Of Physics
Synthesis and study the electrical properties of carbon nanotubes- polyvinylchloride composites
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The aim of this paper, study the effect of carbon nanotubes on the electrical properties of polyvinylchloride. Samples of polyvinylchloride carbon nanotubes composite prepared by using hot press technique. The weight percentages of carbon nanotubes are 0,5,10 and 20wt.%. Results showed that the D.C electrical conductivity increases with increasing of the weight percentages of carbon nanotubes. Also, the D.C electrical conductivity changed with increase temperature for different concentrations of carbon nanotubes. The activation energy of D.C electrical conductivity is decreased with increasing of carbon nanotubes concentration.

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Publication Date
Sat Jul 01 2023
Journal Name
Chalcogenide Letters
Investigating the optical and electrical characteristics of As60Cu40-xSex thin films
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In this work, As60Cu40-xSex thin films were synthesized, and the pulsed laser deposition method was used to study the effected partial replacement of copper with selenium. The electrical characteristics and optical characteristics, as indicated by the absorbance and transmittance as a function of wavelength were calculated. Additionally, the energy gap was computed. The electrical conductivity of the DC in the various conduction zones was calculated by measuring the current and voltage as a function of temperature. Additionally, the mathematical equations are used to compute the energy constants, electron hopping distance, tail width, pre-exponential factor, and density of the energy states in variation zones (densities of the energ

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Synthesis and some of the electrical properties of the polymer Mosul poly Berrol
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Thin films were prepared from poly Berrol way Ketrrukemaaih pole of platinum concentrations both Albaarol and salt in the electrolytic Alastontrel using positive effort of 7 volts on the pole and the electrical wiring of the membrane record

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Body mass index and shortened telomere length in middle-aged female and male RUNNING HEAD: Middle-aged and shortened telomere length
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Obesity is a risk factor associated with age-related disorders that accelerate aging, and it increases the risk of metabolic diseases. Therefore, this study was conducted to investigate the association of leukocyte telomere length (LTL) with the presence of higher body weight in middle-aged females and males. The study subjects comprised 160 (80 control and 80 higher body mass index BMI groups) with ranging ages of 30-50 years included and stratified for BMI. The physio-biochemical analysis was measured using enzymatic determination. Mean telomere length was determined by using the southern blotting technique. The association analysis revealed a significant variance (P < 0.01) in biochemical parameters between higher BMI grou

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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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