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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
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Principles of Learning Organizations and It`s Role to achieve Group Working: A Viewed Study in Public Company for Webbing Industries in Hilla
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     Organizations must interact with the environment around them, so the environment must be suitable for that interaction. These companies are now trying to become Learning Organizations because it try to face that challenges may rise from its environments. The Learning Organization is a concept that is becoming an increasingly widespread philosophy in modern companies, from the largest multinationals to the smallest ventures. What is achieved by this philosophy depends considerably on one's interpretation of it and commitment to it. This study gives a definition that we felt was the true ideology behind the Learning Organization and Group Working. A Learning Organization is one in which people at all levels

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Effect of car painting vapours on pulmonary and liver function of Automobile painting worker within Baghdad governorate area
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Background: Automobile spray painting is considered an occupation with a high risk of respiratory impairment and asthma. Exposure to organic solvents used for spraying might be of high risk for development of dysfunction in other organs.
Objective: The study was designed to evaluate the pulmonary and hepatic toxicity due to exposure of automobile painters to organic solvents in work places within the Baghdad governorate area.
Methods: Thirty cross sectional selected male workers employed in automobile body paint shops in two industrial areas within Baghdad city (Al-Sheikh Omar and Al-Rasheed camp regions) were recruited to the study during the period from March to May 2012. Thirty non-exposed students and employees in the college o

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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Publication Date
Sun Jun 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
The vision of Hebrew writers and critics of the future of the Jews in their writings at the end of the 19th century and the beginning of the twentieth c: דעותיהם של הסופרים והמבקרים העבריים על עתידם של היהודים לפי כתבותיהם בשלהי המאה ה-19 ובתחילת המאה ה-20
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It is very known  how great is the  role of the Jewish writers in the system of the Zionist movement. The movement relied on writers and writers to carry out their programs, especially those pertaining to the creation of a "national homeland" for Jews. Most Jewish writers sang of  Palestine even though they were not born there.

    On such a  basis, we have followed closely the writings of writers, critics and others by the end of the nineteenth century and the beginning of the twentieth century. We found that these writings are based on one common question: What is the fate of the Jewish people?

    Most of these writings were accompanied by Theodor Herzl's proj

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the statistical methods used to Forecast the size of the Iraqi GDP for the two sectors (public and private) for the period (2025-2016)
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Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Physical Education
Motivation and Self – Confidence and their relation to Routine Performance on Parallel Bars in Men’s Artistic Performance
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Publication Date
Mon Jun 28 2021
Journal Name
Journal Of Physical Education
Motivation and Self – Confidence and their relation to Routine Performance on Parallel Bars in Men’s Artistic Performance
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The research aimed at identifying the relationship between motivation and self–confidence on the performing routines in the parallel bar. The researchers used the descriptive method on (480) thirds year college of physical education and sport sciences/ university of Baghdad students. The data was collected and treated using proper statistical operations to conclude that there is a high correlation relationship between motivation and self-confidence with routine performance on parallel bars. In addition to that, the researchers concluded that third-year students have high motivation and self – confidence and there is a positive relationship between motivation, self-confidence, and routine performance on parallel bars.

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Physical Education
The Effect of Special Exercises Using with Assisting Aids According to Differentiated Learning (Visual Learners) in Learning Crescent Kick in Fighters of Specialized Taekwondo schools
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Publication Date
Sat Aug 06 2022
Journal Name
Ijci. International Journal Of Computers And Information
Techniques for DDoS Attack in SDN: A Comparative Study
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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

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Publication Date
Sun Jun 01 2014
Journal Name
University Of Baghdad
New Analytical Methods for Drugs Analysis A Comparative Study
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Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo

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