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Prediction of Urban Spatial Changes Pattern Using Markov Chain
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Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to analyze time series based on current values to predict the series values in the future without relying on the past or historical values of the studied series. The research questions in this study are formulated thus: What are the trends in the patterns of urban land use functions in Al-Najaf, Iraq, between 2005 to 2015? How can the values of the changes be predicted for the year 2025? The hypothesis is based on the increasing spatial functional change of land use patterns in the city during the study period due to various economic and social factors. Making accurate predictions of the size of spatial changes motivates this study as a guide to urban management towards developing possible solutions to address the effects of this change, as well as the need to understand its causes and future upward trends. The contribution of this article is the presented outlook for spatial functions for the next 10 years. The computations using the Markov chain model will enable management to understand future relations and develop appropriate policies to reduce the hazards of unplanned changes in the city. Results show that residential posts, slums, and commercial activities are getting worse, while change values for industrial functions and other things are going down. 

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Publication Date
Thu Jul 05 2018
Journal Name
Eurasip Journal On Wireless Communications And Networking
Positioning and guiding educational robots by using fingerprints of WiFi and RFID array
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Publication Date
Thu Feb 01 2024
Journal Name
Heliyon
Removal of amoxicillin from contaminated water using modified bentonite as a reactive material
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This study concerns the removal of a trihydrate antibiotic (Amoxicillin) from synthetically contaminated water by adsorption on modified bentonite. The bentonite was modified using hexadecyl trimethyl ammonium bromide (HTAB), which turned it from a hydrophilic to a hydrophobic material. The effects of different parameters were studied in batch experiments. These parameters were contact time, solution pH, agitation speed, initial concentration (C0) of the contaminant, and adsorbent dosage. Maximum removal of amoxicillin (93 %) was achieved at contact time = 240 min, pH = 10, agitation speed = 200 rpm, initial concentration = 30 ppm, and adsorbent dosage = 3 g bentonite per 1L of pollutant solution. The characterization of the adsorbent, modi

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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Engineering
Heat Dissipation Performance of High-Power CPUs using Finned Copper Foam Heat Sinks
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Thermal management has become a major issue in the latest high performance computing machines because high CPU temperatures result in inefficient performance and decreased hardware life span. In this work, the cooling performance of a finned metal foam heat sink (FMFHS) was examined. The pore density values of tested copper metal foam (CMF) samples with different values of PPI 5, 10 and 20, with a constant porosity of 90%. For reference, these samples were measured by a conventional Aluminum plate-fin heat sink (CHS). The work was performed under experimental conditions in which air directed over the heat sink surface at air velocities (2.5, 3.0 and 3.5 m/s). The environmental temperature was fixed at 27 °C. Findings

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Adsorption of heavy metal ions using activated carbon derived from Eichhornia (water hyacinth)
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Abstract<p>Removal of heavy metal ions such as, cadmium ion (Cd <sup>2+</sup>) and lead ion (Pb <sup>2+</sup>) from aqueous solution onto Eichhornia (water hyacinth) activated carbon (EAC) by physiochemical activation with potassium hydroxide (KOH) and carbon dioxide (CO<sub>2</sub>) as the activating agents were investigated. The Eichhornia activated carbon was characterized by Brunauer Emmett Teller (BET), Fourier Transform Infrared spectroscopy (FTIR), and Scanning Electron Microscopy (SEM) techniques. Whereas, the effect of adsorbent dosage, contact time of pH, and metal ion concentration on the adsorption process have been investigated using the batch process t</p> ... Show More
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Publication Date
Sun Jan 01 2017
Journal Name
Green Chemistry
Dissolution of pyrite and other Fe–S–As minerals using deep eutectic solvents
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Processing sulfur containing minerals is one of the biggest sources of acute anthropogenic pollution particularly in the form of acid mine drainage.

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Attitude and Altitude Control of Quadrotor Carrying a Suspended Payload using Genetic Algorithm
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The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Green synthesis of gold NPs by using dragon fruit: Toxicity and wound healing
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Abstract<p>In this work, the study of <italic>Hylocereus undatus</italic> properties was done by studying quantitative phytochemical compounds and seeking for total phenolic compounds, synthesis of gold nanoparticles was created via reduction of aqueous gold ions with the aqueous fruit extract of The <italic>Hylocereus undatus</italic> (dragon). The synthesized AuNPs were asserted by using (Uv-Vis) spectrophotometer; Fourier transforms infrared (FI-IR) spectroscopy, Atomic force microscope (AFM), Scanning Electron Microscopy (SEM) Zitasizer. The absorbance for SPR is noticed in 546 nm by using Uv-Visible spectroscopy The SEM and AFM analysis evidenced the particle size betwee</p> ... Show More
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Publication Date
Mon Nov 09 2020
Journal Name
Heat Transfer
Experimental performance of cooling photovoltaic panels using geothermal energy in an arid climate
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Publication Date
Thu Oct 21 2021
Journal Name
Iraqi Journal Of Agricultural Sciences
SYNTHESIS, CHARACTERIZATION AND CYCLAZATION OF PYRAN USING Ag2O NANOPARTICLE FROM NATURAL SOURCE “GINGER”
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This study was aimed to synthesis Ag2O nanoparticles (N.P.s) utilizing the Ginger plant (Zingiber officinale) extract. As catalysts for pyran derivatives formation employing a three-component coupling reaction among aromatic and aliphatic aldehydes, malononitrile, and dimedone. The nanoparticles exhibit robust catalytic activity with high productivity. Results revealed that Ag2O NPs improved various vital features, like higher yields, reaction time, simple chemical separation, catalytic economic efficiency, and quick process. This study aimed to cyclize heterocyclic compounds to provide new hetero compounds applying nano-oxides obtained from natural (unmanufactured) sources and used in several medical, pharmaceutical, and industrial

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

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