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Street Networks and Urban Sustainability by Quantifying Connectivity, Accessibility, and Walkability for Resilient Cities
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Street networks are crucial in shaping the quality of urban life. Through their impact on mobility and social interaction, they play a critical role in shaping how people move around the city and determine the connectivity, accessibility, safety, and convenience of different areas. Thus, it is essential to develop a systematic understanding of street networks to create livable, sustainable, accessible, and equitable cities. The aim of this study is to analyze and develop the role of street networks in shaping urban mobility, connectivity, and accessibility, and thereby enhance sustainable urban living by creating people-centric cities. Quantitative techniques and measures are employed to examine urban structure metrics to understand both physical and spatial characteristics at micro and macro scales. Three primary parameters for the configuration of street patterns - grid pattern ratio (GPR), pedestrian route directness factor (PRD/PRF), and ped-shed (PS) and effective walking area (EWA) - are selected to compute the formational attributes of selected streets in Baghdad, Iraq. The evaluation employs different arithmetic methods linked with a Geographical Information System (GIS) to quantify and compare two examined areas, and the results reveal a contradiction in the spatial configuration of the sample street patterns. From these findings, the paper offers specific recommendations and urban design guidelines to improve the quality of similar urban areas. The paper concludes that in-depth knowledge of a street’s role in its urban context helps to optimize spatial configuration processes in the built environment.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

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Publication Date
Fri Dec 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Laminar Free Convection in Three Dimensional Inclined Porous Annulus with Fins on the Inner Cylinder
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An experimental and numerical study was carried out to investigate the heat transfer by natural convection in a three dimensional annulus enclosure filled with porous media (silica sand) between two inclined concentric cylinders with (and without) annular fins attached to the inner cylinder under steady state condition. The experiments were carried out for a range of modified Rayleigh number (0.2 ≤Ra*≤ 11) and extended to Ra*=500 for numerical study and for annulus inclination angle of (δ = 0˚, 30˚, 60˚ and 90˚). The numerical study was to give the governing equation under assumptions that used Darcy law and Boussinesq’s approximation and then it was solved numerically using finite difference approximation. It was found that t

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Thu Jun 20 2024
Journal Name
Fizjoterapia Polska
Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The relationship of empowering workers with organizational performanceField research of the views of the scientific leaders of a number of colleges at the University of Baghdad
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The Strategy of employees' empowerment, organizational performance and total quality management represent three informative which were and still the hub of many studies and researches including the current study. The higher education is considered one of the most important services sectors and the main development as well as the civil progress in the society. It is the main source that provides the organizations with the human resources having scientific or practical professions. So Higher Education has been chosen especially Baghdad University as a sample of the study. The study problem is concentrated to find answers of the following   questions: What the level of the powers mandate in the organization concerning the

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Fri Mar 01 2019
Journal Name
Applied Acoustics
Theoretical model of absorption coefficient of an inhomogeneous MPP absorber with multi-cavity depths
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
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