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joe-2033
Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network
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The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types of Asphalt Concrete distress including (bleeding of Asphalt, patching, block cracking, edge cracking, longitudinal and transverse cracking, rutting, pot holes, longitudinal and transverse deformation) with their various severity and intensity conditions have been included in the system as data base. The surface of the pavement was divided into sections, and the pavement condition is visually evaluated by the raters using specially designed forms, each type of defect was measured, classified, and rated according to type, severity, and extent. Data will be fed to the system using the computer, various types of intensity and severity of distress were analyzed by the system, the present condition rating (PCR) of the pavement section is determined, and the system suggests the required maintenance action. The developed system which is assigned (PMMS-09) was verified in evaluating the pavement surface condition at AL-Jaderiah campus roadway network. The results indicated that the system is sound in evaluation of the pavement condition and in suggestion of the proper maintenance to reserve the pavement condition.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Sun Dec 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Solving the Inverse Kinematic Equations of Elastic Robot Arm Utilizing Neural Network
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The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use projection pursuit regression and neural network to overcome curse of dimensionality
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Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Performance Analysis on Multiple Device Connections of Small Office Home Office Network
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Malaysia has been supported by one of the high-speed fiber internet connections called TM UniFi. TM UniFi is very familiar to be used as a medium to apply Small Office Home Office (SOHO) concept due to the COVID-19 pandemic. Most of the communication vendors offer varieties of network services to fulfill customers' needs and satisfaction during the pandemic. Quality of Services is queried by most users by the fact of increased on users from time to time. Therefore, it is crucial to know the network performance contrary to the number of devices connected to the TM UniFi network. The main objective of this research is to analyze TM UniFi performance with the impact of multiple device connections or users' services. The study was conducted

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Sun Dec 01 2024
Journal Name
Al-kindy College Medical Journal
A Revolutionary Road Map for Obesity Management and Beyond: Tirzepatide as a Dual-Acting Insulinotropic Polypeptide Receptor Agonist
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Tirzepatide is a revolutionary and promising medication with a high impact in the treatment of Obesity and T2DM with their complications. Its efficacy was proven through different trials in achieving favorable weight loss and a significant reduction in glycemic index. It also treated a large diversity of related co-morbidities, including fatty liver, cardiovascular disease, dyslipidemia, and more. Tirzepatide is well tolerated, has a good safety profile, and is highly reliable and suitable for use in a population.

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Scopus
Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Educational And Psychological Researches
the university education and human development
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We notice that the issue of development is one of the most important issues in ourepoch especially in our country which classify within back ward countries.

When we talk here about the development we don’t mean only the development of capitals or the development of products.but the most important thing is the development of mind .if we notice the experience of  developits economy and it didn’t reach to the wanted aim.because these sides .  The highness of the meutal rate of the nation is the standard of of the nation is the standard of the sentific and cultural advance for this nation .And that is what we have noticed in human societies ingenerall .

We noticed that

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Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
The role of environmental taxation and environmental incentives to reduce environmental pollution manifestations in the urban environment
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        The aim of studying the role of environmental taxation is to reduce or mitigate the problem of environmental pollution and obtain a clean environment. And the importance of research lies in the fact that environmental taxation is one of the basic tools to achieve environmental balance. As it is considered one of the sustainable economic tools that focuses on the concept of environmental taxes and fees. Therefore, the incentives stimulated institutions to invest in clean energy and use environmentally friendly machines. Through it, the rules of the competition are updated in favor of organizations that respect the environment so that they can obtain a green competitive advantage. And that the mai

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