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Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steering angle of a self-driving vehicle that is suitable to be applied to embedded automotive technologies with limited performance. Three well-known pre-trained models were compared in this study: AlexNet, ResNet18, and DenseNet121.

Transfer learning was utilized by modifying the final layer of pre-trained models in order to predict the steering angle of the vehicle. Experiments were conducted on the dataset collected from two different tracks. According to the study's findings, ResNet18 and DenseNet121 have the lowest error percentage for steering angle values. Furthermore, the performance of the modified models was evaluated on predetermined tracks. ResNet18 outperformed DenseNet121 in terms of accuracy, with less deviation from the center of the track, while DenseNet121 demonstrated greater adaptability across multiple tracks, resulting in better performance consistency.

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Parametric Study of Mixed Convective Radiative Heat Transfer in an Inclined Annulus
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The steady state laminar mixed convection and radiation through inclined rectangular duct with an interior circular tube is investigated numerically for a thermally and hydrodynamicaly fully developed flow. The two heat transfer mechanisms of convection and radiation are treated independently and simultaneously. The governing equations which used are continuity, momentum and energy equations. These equations are normalized and solved using the Vorticity-Stream function and the Body Fitted Coordinates (B.F.C) methods. The finite difference approach with the Line Successive Over-Relaxation (LSOR) method is used to obtain all the computational results. The (B.F.C) method is used to generate the grid of the problem. A computer program (Fortr

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Numerical Study of Heat Transfer Enhancement in Heat Exchanger Using AL2O3 Nanofluids
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In this study, the flow and heat transfer characteristics of Al2O3-water nanofluids for a range of the Reynolds number of 3000, 4500, 6000 and 7500 with a range of volume concentration of 1%, 2%, 3% and 4% are studied numerically. The test rig consists of cold liquid loop, hot liquid loop and the test section which is counter flow double pipe heat exchanger with 1m length. The inner tube is made of smooth copper with diameter of 15mm. The outer tube is made of smooth copper with diameter of 50mm. The hot liquid flows through the outer tube and the cold liquid (or nanofluid) flow through the inner tube. The boundary condition of this study is thermally insulated the outer wall with uniform velocity a

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
Theoretical study of electronic transfer current rate at dye-sensitized solar cells
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Parametric Study of Mixed Convective Radiative Heat Transfer in an Inclined Annulus
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The steady state laminar mixed convection and radiation through inclined rectangular duct with an interior circular tube is investigated numerically for a thermally and hydrodynamicaly fully developed flow. The two heat transfer mechanisms of convection and radiation are treated independently and simultaneously. The governing equations which used are continuity, momentum and energy equations. These equations are normalized and solved using the Vorticity-Stream function and the Body Fitted Coordinates (B.F.C) methods. The finite difference approach with the Line Successive Over-Relaxation (LSOR) method is used to obtain all the computational results. The (B.F.C) method is used to generate the grid of the problem. A computer program (Fortran

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Publication Date
Wed Oct 08 2025
Journal Name
Iraqi Journal Of Applied Physics
Fluorescence Energy Transfer Characteristics in Binary Acriflavine-Red Nut Lasing Dye Mixtures
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Publication Date
Sun Nov 01 2015
Journal Name
Energy Conversion And Management
Laminar convective heat transfer of hexylamine-treated MWCNTs-based turbine oil nanofluid
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Multi-walled carbon nanotubes (MWCNTs) were functionalized by hexylamine (HA) in a promising, cost-effective, rapid and microwave-assisted approach. In order to decrease defects and remove acid-treatment stage, functionalization of MWCNTs with HA was carried out in the presence of diazonium reaction. Surface functionality groups and morphology of chemically-functionalized MWCNTS were characterized by FTIR, Raman spectroscopy, thermogravimetric analysis (DTG), and transmission electron microscopy (TEM). To reach a promising dispersibility in oil media, MWCNTs were functionalized with HA. While the cylindrical structures of MWCNTs were remained reasonably intact, characterization results consistently confirmed the sidewall-functionalization o

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Publication Date
Sun Dec 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Heat Transfer and Hydrodynamic in Internal Jacket Airlift Bioreactor with Microbubble Technology
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   Integration of laminar bubbling flow with heat transfer equations in a novel internal jacket airlift bioreactor using microbubbles technology was examined in the present study. The investigation was accomplished via Multiphysics modelling to calculate the gas holdup, velocity of liquid recirculation, mixing time and volume dead zone for hydrodynamic aspect. The temperature and internal energy were determined for heat transfer aspect.

   The results showed that the concentration of microbubbles in the unsparged area is greater than the chance of large bubbles with no dead zones being observed in the proposed design.  In addition the pressure, due to the recirculation velocity of liquid around the draft

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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Heat Transfer and Thermal Expansion of Coefficient EP -(MWCNT/x-TiO2)Nanocomposites
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The thermal properties (thermal transfer and thermal expansion coefficient) of the enhanced epoxy resin (MWCNT / x-TiO2) were studied by weight ratios with the values (0%, 3%, 5%, 7% and 10%) and a constant ratio of 3% of MWCNT. The ultrasonic technology was used to prepare the neat and composites which were then poured into Teflon molds according to standard conditions. Thermo-analyzer sensor technology was used to measure thermal transfer (thermal conductivity, thermal flow, thermal diffusion, thermal energy and heat resistance). The thermal conductivity, flow, and thermal conductivity values were increased sequentially by increasing the weight ratio of the filler while the results of stored energy values an

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Effect of Air Bubbles on Heat Transfer Coefficient in Turbulent Convection Flow
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Experimental and numerical studies have been conducted for the effect of injected air bubbles on the heat transfer coefficient through the water flow in a vertical pipe under the influence of uniform heat flux. The investigated parameters were water flow rate of (10, 14 and 18) lit/min, air flow rate of (1.5, 3 and 4) lit/min for subjected heat fluxes of (27264, 36316 and 45398) W/m2. The energy, momentum and continuity equations were solved numerically to describe the motion of flow. Turbulence models k-ε was implemented. The mathematical model is using a CFD code Fluent (Ansys15). The water was used as continuous phase while the air was represented as dispersed. phase. The experimental work includes design, build and instrument a test

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