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joe-1600
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regression models, respectively. This work is an effort to practice the advantages of machine learning techniques to build a robust and cost-effective model for Cc estimation by designers, decision makers, and stakeholders.

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Use of lower squares and restricted boxes In the estimation of the first-order self-regression parameter AR (1) (simulation study)
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Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Isolation and Identification of Local Bactria Produced from Soil-Borne Urease
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Abstract<p>The hydrolysis of urea by the enzyme urease is significant for increasing the irroles in human pathogenicity, biocementation, soil fertilizer, and subsequently in soil improvement. This study devoted to the isolation of urease from urea-rich soil samples collected from seven different locations. Isolation of the various bacterial species was conducted using nutrient agar. The identity of isolated urease was based on morphological characteristics and standard microbiological and biochemical procedures. The urease producing strains of bacteria were obtained using the urease hydrolysis test. The bacterial isolates produced from soil samples collected from different environments and treat</p> ... Show More
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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Geological Journal
Advanced Geostatistical Techniques for Building 3D Geological Modeling: A Case Study from Cretaceous Reservoir in Bai Hassan Oil Field
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A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulnen

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
The Accumulation Risk of Heavy Metals in Vegetables which Grown in Contaminated Soil
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The present study has been carried out to estimate heavy metals mobility, bioconcentration and transfer from polluted soil to roots tissues and from roots tissues to aerial parts using bioconcentration factor and translocation factor. Soil samples and the biomass of the eight vegetable species have been collected during summer season, 2019 from four different sites in Wadi Al-Arg, Taif Governorate, KSA. In general, heavy metals content of soil samples in site III and IV have recorded elevated values compared with those of site I and II. The soil from site IV has shown the highest concentration of Mn, Ni, Cr, Pb, Cu, and Cd amounted 31.63, 14.05, 13.56, 22.79, 31.02 and 2.98 mg/kg dry soil respectively, while the soil from site III has sh

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Assessing of Some Toxic Heavy Metals Levels and Using Geo Accumulation Index in Sediment of Shatt Al-Arab and the Iraqi Marine Region
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Mercury, arsenic, cadmium and lead, were measured in sediment samples of river and marine environmental of Basra governorate in southern of Iraq. Sixteen sites of sediment were selected and distributed along Shatt Al-Arab River and the Iraqi marine environment. The samples were distributed among one station on Euphrates River before its confluence with Tigris River and Shatt Al-Arab formation, seven stations along Shatt Al-Arab River and eight stations were selected from the Iraqi marine region. All samples were collected from surface sediment in low tide time. ICP technique was used for the determination of mercury and arsenic for all samples, while cadmium and lead were measured for the same samples by using Atomic Absorption Spectrosc

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Publication Date
Wed Dec 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of Cytotoxicity and Biocompatibility of Ti2AlC in Rabbits
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Background: The Titanium and its alloys are suitable for dental implant and medical applications. Biocompatibility of the materials is a major factor in determining the success of the implant and has a great impact on their rate of osseointegration. The aim of this study was to evaluate the biocompatibility and cytotoxicity of Ti2AlC in comparison to CPTi & Ti6Al7Nb in rabbits. Materials and Methods: 10 male New Zealand White rabbits, weighing (2-2.5 kg), aged (10-12 months) were used in this study. Cylindrical implants were prepared from the study materials (CPTi, Ti6Al7Nb and Ti2AlC) with (8mm) height and (3mm) diameter for the evaluation of tissue response and disc specimens were prepared with (6 mm) diameter and (2 mm) thickness for ev

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Experimental Study on Using Cement Kiln Dust and Plastic Bottle Waste to Improve the Geotechnical Characteristics of Expansive Soils in Sulaimani City, Northern Iraq
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In this study, stabilization of expansive soils using waste materials namely; Cement Kiln Dust (CKD), and waste plastic bottles (WPB) was experimentally investigated. Using CKD and WPB are exponentially increasing day by day, due to their capability to solve both environmental and geotechnical problems successfully. Expansive soils were collected from locations with a wide range of plasticity index (PI) (15 - 27) and liquid limit (LL) (35% - 64%). Stabilizer percentages were varied from 0% to 20%, and curing durations for CKD cases were 7 and 28 days. Results showed the best percentages of CKD and WPB are 12% of each one respectively. LL, plastic limit (PL), and swelling percent (SP) loss were observed, which are 46%, 55%, and 96% respec

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Synthesis and evaluation of chalcone derivatives for antimicrobial and antioxidant activities using microwave-assisted methodology
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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Monitoring of south Iraq marshes using classification and change detection techniques
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Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

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