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Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites in Baghdad city were used. 70% of these results were used to train the prediction ANN models and the rest were equally divided to test and validate the ANN models. The performance of the developed models was examined using the correlation coefficient R. The final models have demonstrated that the ANN has capability for acceptable prediction of compression index and compression ratio. Two equations were proposed to estimate compression index using the connecting weights algorithm, and good agreements with test results were achieved.

 

 

 

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Outdoor Testing of a Zig-Zag Solar Air heater with and without Artificial Roughness on Absorber Plate
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In this paper, thermal performance of a zig-zig solar air heater (ZZSAH) with and without using steel wire mesh on the absorber plate of the collector is experimentally investigated. The experimental work includes four inclination angles of the collector 20o, 30o, 45o, and 60o and four air mass flow rates of 0.03, 0.04, 0.06, and 0.08 kg/s under varieties of operating conditions of a geographic location of  Baghdad. New correlation equations of Nusselt number are obtained from experimental results for both types of collectors where the effect of varying of the inclination angle of collector taken into consideration in the experiment. The correlations show good agreement wi

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Publication Date
Thu May 25 2023
Journal Name
Polycyclic Aromatic Compounds
Effect of Modified Nano-Graphene Oxide and Silicon Carbide Nanoparticles on the Mechanical Properties and Durability of Artificial Stone Composites from Waste
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Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Geological Journal
Assessment of Groundwater Quality for Drinking Purposes Using Water Quality Index, and Identifying the Affecting Mechanism in Rashdiya, Central Iraq
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Groundwater is an important resource that can be used for various purposes. Various factors can change the chemistry of the GW, such as the chemical composition of an aquifer as well as the leaching of human waste into groundwater. The study area is a barren land covered by some sabkhas, in addition to some agricultural fields. The study aims to assess groundwater quality for drinking purposes using the Water Quality Index. The groundwater is chemically heterogeneous and has a wide quality range from very poor to excellent. Evaporation appears to be the controlling factor among the other shallow waters, while relatively deep water is related to rock-soil dominance. Rocks, land use and land cover have helped control the groundwater q

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Publication Date
Tue Jan 02 2024
Journal Name
Turkish Archives Of Pediatrics
Evaluation of Decayed, Missing Due to Caries, and Filled Teeth Index in Children with Phenylketonuria in Comparison to Normal Population
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem
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Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Enhancing Smart Cities with IoT and Cloud Computing: A Study on Integrating Wireless Ad Hoc Networks for Efficient Communication
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Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Fri May 21 2021
Journal Name
International Journal Of Pavement Research And Technology
Developing Resilient Modulus Prediction Models Based on Experimental Results of Crushed Hornfels Mixes with Different Gradations and Plasticity
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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Advanced Joining Processes
Coupled Eulerian–Lagrangian prediction of thermal and residual stress environments in dissimilar friction stir welding of aluminum alloys
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The evaluation of residual stresses (RS) induced by the friction stir welding (FSW) process is crucial in anticipating the performance of the welded structure. The existence of such residual stresses within a friction stir welded structure may lead to excessive distortion and weakness to afford the applied external loads. To assess quantitatively the effect of these residual stresses generated by FSW process, the current paper implements a Coupled Eulerian–Lagrangian (CEL) finite element simulation to analyze both thermal and subsequent resulted remaining stress environments in dissimilar friction stir welding of AA6061-T6 and AA2024-T3 alloys. The thermal analysis step was conducted first and followed by a mechanical analysis step in whi

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