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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 Jun 06 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
A comparative study of the mechanical and electrical activities of the heart according to the energy systems of advanced players
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The study aims to identify the mechanical and electrical activities of the heart according to the energy systems of advanced players and to detect the differences between the energy systems in terms of the mechanical and electrical activities of the heart for advanced players. It was clear from the results of the significance of the differences between the three groups according to the energy systems of the advanced players in all research variables that (the non-oxygenic system "Lactic"), which represents the advanced players in the arches (800 m, 1500 m) was the first in most tests of mechanical and electrical activities of the heart, which is (Margaria-Kalamen, Wingate, systolic muscle strength of the heart FC, Stroke Volume SV

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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
A comparative study between conventional methods and Vidas UP Salmonella (SPT) to investigate salmonella species from local and imported meat
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The study was preformed for investigating of Salmonella from meat, and compared Vidas UP Salmonella (SPT) with the traditional methods of isolation for Salmonella , were examined 42 meat samples (Beef and Chicken) from the Local and Imported From local markets in the city of Baghdad from period December 2013 -February 2014 the samples were cultured on enrichment and differential media and examined samples Vidas, and confirmed of isolates by cultivation chromgenic agar, biochemical tests ,Api20 E systeme , In addition serological tests , and the serotypes determinate in the Central Public Health Laboratory / National Institute of Salmonella The results showed the contamination in imported meat was more than in the local meat 11.9% and 2

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Numerical Simulation of 3D- Flow Structure and Heat Transfer for Longitudinal Riblet Upstream of Leading Edge Endwall Junction of Nozzle Guide Vane
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The simulation have been made for  3D flow structure and heat  transfer with and without

longitudinal riblet upstream of leading edge vane endwall junction of first stage nozzle guide vane .The research explores concept of weakening the secondary flows and reducing their harmful effects.Numerical investigation involved examination of the secondary flows ,velocity and heat transfer rates by solving the governing equations (continuity, Navier -stokes and energy equations ) using the known package FLUENT version (12.1).The governing equations were solved for three dimentional, turbulent flowe, incompressible with an appropriate turbulent model (k-ω,SST) .The numerical solution was carried out for 25 mode

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Ridge regression method with some classical methods to estimate the parameters of Lomax distribution by simulation
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Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition
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Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Comparison of Protein Concentration in Red and White Muscles in Two Species of Bony Fish
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The current study deals with estimating the protein concentration and the effect of fish weight on protein concentration values in red and white muscles in two different regions ( R1 : Anterior region lies 2 cm behind the head and R2: posterior region lies 2cm from caudal fin  (in  two types of bony fish, namely common carp (Cyprinus carpio) and Nile tilapia (Oreochromis niloticus). Samples were collected from Karmat Ali river- north of Basrah between October 2019 and February 2020. The protein was extracted using protein extraction buffer, the current study show that the average of  protein concentration in red muscles of Nile tilapia ranged between  7.74-7.4 mg / ml  and ( 6.8-8.85 mg / ml) in R1 and R2 region re

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Biomechanical Aspects of Shoulder and Hip Articulations: A Comparison of Two Ball and Socket Joints
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The shoulder and hip joints though essentially both are ball and socket joints, show structural variability to serve functional needs.

This study aims at revealing some of the structural and functional properties of each of the two joints regarding the factors that contribute to the stability of any joint in the body, namely: bone, ligament, and muscle.

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Publication Date
Sun Jan 01 2017
Journal Name
المجلة القانونية العلمية المحكمة
المشاكل الاقتصادية المالية للقروض الخارجية من منظور القانون المالي الدولي (دراسة مقارنة)
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Publication Date
Sun Oct 01 2017
Journal Name
العلوم التربوية والنفسية
فاعلية استراتيجية التعلم بالتخيل الموجه في التحصيل الرياضي
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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