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Dynamic Behavior of Machine Foundations on layered sandy soil under Seismic Loadings
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In this paper, a dynamic investigation is done for strip, rectangular and square machine foundation at the top surface of two-layer dry sand with various states (i.e., loose on medium sand and dense on medium sand). The dynamic investigation is performed numerically using finite element programming, PLAXIS 3D. The soil is expected as a versatile totally plastic material that complies with the Mohr-Coulomb yield criterion. A harmonic load is applied at the base with an amplitude of 6 kPa at a frequency of (2 and 6) Hz, and seismic is applied with acceleration – time input of earthquake hit Halabjah city north of Iraq. A parametric study is done to evaluate the influence of changing L/B ratio (Length=12,6,3 m and width=3 m), type of sand, and frequency of the machine for soil with two layers (dense and medium sand) and (loose and medium sand). It was noticed that the displacement decreases when the foundation is strip, and has the highest values when the foundation is square. At the same time, the maximum vertical stress of the foundation (L/B = 4 and L/B = 1) appears to be (1262) kPa and (1255) kPa, respectively, due to increasing the foundation mass as a result of increasing its dimensions. Then again, the displacement increases by 20% for vertical displacement when decreasing the relative density. In addition, it has been noticed that there is a decrease in displacement when the frequency value changes from (2 to 6) Hz.

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Publication Date
Wed Aug 02 2017
Journal Name
International Journal Of Materials Chemistry And Physics
Assessing the Sustainability of Asphalt Stabilized Subgrade Soil for Embankment Construction
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Gypseous soil is considered as a problematic soil for embankment construction, however, implementation of emulsified asphalt as a stabilization agent could be a proper solution for enhancing its properties as a subgrade soil. In this work, the sustainability of asphalt stabilized soil has been assessed in terms of its resistance to cyclic (freezing-thawing) and (heating-cooling) processes. Specimens have been prepared at optimum fluid content (moisture and emulsion) and tested under direct shear stresses while subjected to 30 cycles of (freezing-thawing) and (heating-cooling). Both of dry and soaked testing conditions have been implemented. Data have been observed after each 10 cycles, and compared with that of reference mix. It was conclud

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Mineralogy of Sand Fraction in Selective Soil Sections in Baghdad City
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Abstract<p>This study has been undertaken to investigate the mineralogical properties and morphological features of sand fraction in some soils of Baghdad / Iraq.The morphological features of sand fractions were studied by Polarized optical microscope. Results have shown that the grains of these minerals from samples of sands have different colors, those from the surface horizons have dark brownish spots, due to staining by organic matter, and have a yellowish– to yellowish brown spots due to accumulation of Iron oxides.Results of light minerals indicated that quartz is dominant due to effect of parent material of these soils. Two types of opaque minerals (black and brown) are found, whereas t</p> ... Show More
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Improvement of Soil by Using Polymer Fiber Materials Underneath Square Footing
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The change in project cost, or cost growth, occurs from many factors, some of which are related to soil problem conditions that may occurs during construction and/or during site investigation period. This paper described a new soil improvement method with a minimum cost solution by using polymer fiber materials having a length of (3 cm) in both directions and (2.5 mm) in thickness, distributed in uniform medium dense .
sandy soil at different depths (B, 1.5B and 2B) below the footings. Three square footings has been used (5,7.5 and 10 cm) to carry the above investigation by using lever arm loading system design for such purposes.
These fibers were distributed from depth of (0.1B) below the footing base down to the investigated dep

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Publication Date
Tue Oct 14 2025
Journal Name
Cab Reviews: Perspectives In Agriculture, Veterinary Science, Nutrition And Natural Resources
The role of modern agricultural practices in enhancing soil erosion resistance
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This review focuses on conservation agriculture (CA) and its effects on increasing the soil’s resistance to erosion. CA involves minimum soil disturbance (minimum tillage/ no-till), diversified crop rotation, and maintenance of the soil cover to increase soil fertility and reduce erosion. CA reduces soil loss by up to 90% and water erosion by approximately 50 to 70% from runoff as it increases the health of the soil, yield of crops, and water-retention capacity of the soil by incorporating soil organic matter and promoting biodiversity. Crop rotation prevents the replenishment and depletion of soil nutrients by atmospheric fixation of nitrogen/biological nitrogen fixation. Controlled traffic farming (CTF) is a new strategy in which travel

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Sliding mode control based on high-order extended state observer for flexible joint robot under time-varying disturbance
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Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

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Publication Date
Thu Sep 14 2023
Journal Name
Al-khwarizmi Engineering Journal
Applying Scikit-learn of Machine Learning to Predict Consumed Energy in Al-Khwarizmi College of Engineering, Baghdad, Iraq
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Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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