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The Impact of Unregulated Urban Sprawl on Public Services and Quality of Life in Baghdad: A Case Study of Al-Dora District Using Spatial Analysis
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The rapid and uncontrolled expansion of urban sprawl in Baghdad, particularly after 2003, has significantly transformed the city's landscape. This expansion stems from socio-political instability, a lack of affordable housing, and inadequate urban planning frameworks. As informal settlements encroach on agricultural lands, the city's infrastructure—including water, sanitation, and transportation systems—faces mounting pressure. This situation presents critical challenges to the sustainability of Baghdad’s public services and the quality of life for its residents. This study aims to evaluate the impact of unregulated urban sprawl on Baghdad’s public services and infrastructure, focusing on how informal growth has undermined the city's capacity to deliver essential services. Through the analysis of household and stakeholder survey data, the study highlights critical shortcomings in service delivery and infrastructure within the Al-Dora district. Moreover, the research proposes actionable recommendations to enhance urban planning and governance, addressing the socio-environmental consequences of unregulated growth. The findings emphasize the severe strain urban sprawl has exerted on Baghdad’s public services, with critical deficiencies observed in water supply, electricity access, healthcare services, and transportation networks, particularly in informal settlements. Stakeholders identified institutional barriers, such as poor coordination and insufficient policies, as major obstacles to managing this growth. The study underscores the urgent need for urban planning reforms, strengthened governance, and the integration of modern technologies like GIS to monitor and control urban sprawl. These recommendations aim to foster a sustainable urban future for Baghdad, ultimately improving the quality of life for its residents. Copyright: ©2024 The authors.

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Publication Date
Wed Aug 29 2018
Journal Name
Journal Of Engineering
Zeta Potential, Effective Membrane Charge and Donnan Potential for TiO2 NF Ceramic Membrane
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Nanofiltration (NF) ceramic membrane have found increasing applications particularly in wastewater and water treatment. In order to estimate and optimize the performance of NF membranes, the membrane should be characterized correctly in terms of their basic parameters such as effective pore radius (rp) and equivalent effective thickness as well as effective surface charge ( ), the effective charge density ( ) and Donnan potential ( ). The impact of electrokinetic (zeta) potential on the membrane surface charge density, effective membrane charge density and Donnan potential at two different concentrations of the reference solutions 0.001, 0.01 M sodium chloride at various pH values from 3 to 9, and effective po

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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Publication Date
Mon Feb 07 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Mathematical connection skills and their relationship with productive thinking among secondary school students
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Nanostructures
Association Between Silver Nanoparticle Dose and Brain or Renal NF-κB Gene Expression
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Several studies have claimed that AgNPs’ safety is not completely verified. The current work studied the CNS and renal genetic abnormalities (as manifested by modifications in NF-κB transcription) in mice treated with diverse AgNP concentrations. The findings revealed that as the amount of AgNPs was elevated, NF-κB production increased considerably.

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Tue May 04 2021
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Tactical thinking and its relationship with solving mathematical problems among mathematics department students
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This research aims to know the essence of the correlative relationship between tactical thinking and solving mathematical problems. The researchers followed the descriptive research method to analyze relations, as all students from the mathematics department in the morning study were part of the research group. The research sample of (100) male and female students has been chosen based on the arbitrators' views. The tools for studying the sample of research composed of (12) items of the multiple-choice test in its final form to measure tactical thinking and require establish-ing a test of (6) test-type paragraphs to solve mathematical problems. The findings showed that sample students' tactical thinking and their capacity to overcome mathem

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Publication Date
Wed Jul 02 2025
Journal Name
Advances In Nonlinear Variational Inequalities
Suggesting Approximation and Exact Algorithms to Solve New Tri-Criteria Machine Scheduling Problems
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This study presents the multi criteria single-machine model. The machine scheduling problem (MSP) for ntasks on a single machine involves minimizing a function of three criteria: total completion time (C_j),maximum earliest (E_max), and tardiness (〖ΣT〗_j), This is an NP-hard issue. Within this work's theoretical section, we present the mathematical formulation of The presented topic thenhighlights the usefulness of the dominance rule (DR), which may be used to develop effective solutions. Whilein the practical part, one of the important exact methods; The proposed MSP tricriteria are solved by applyingthe Branch and Bound (BAB) method, which finds a set of efficient solutions for 1//F(ΣC_j ,ΣT_j ,E_max) upto n=100 jobs. The BAB appro

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Publication Date
Mon Nov 24 2025
Journal Name
2025 13th International Conference On Control, Mechatronics And Automation (iccma)
Modeling Twisting and Coiling Actuators with Regression-Based Learning: Application to Neck Rehabilitation
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Twisting and coiling actuators (TCAs) are lightweight artificial muscles that can produce large linear contractions while lifting heavy loads with low power. A TCA consists of two or more strings connected to a rotational motor and a load. When activated, the strings twist and coil, causing contraction. This study presents a data-driven framework for modeling TCA behavior using experimental data. Polynomial regression, Support Vector Regression (SVR), and symbolic regression were applied using the motor angle and payload weight as inputs. The models were evaluated under various loads and implemented in a neck-rehabilitation prototype. SVR showed the highest accuracy (RMSE: 6.17 mm upward, 4.98 mm downward); however, it lacks a closed-form e

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Publication Date
Mon Jan 01 2018
Journal Name
Rsc Advances
Capacitive performance of vertically aligned reduced titania nanotubes coated with Mn<sub>2</sub>O<sub>3</sub> by reverse pulse electrodeposition
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Mn2O3 was coated onto reduced titania nanotubes by reverse pulse electrodeposition, showing smooth and homogenous deposits without covering the opening of the nanotubes.

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