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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 that region. The results show that the neural network has good performance compared with two other analytical methods which are average positioning method and optimal positioning method.

Publication Date
Mon Sep 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Impact of Design Parameters in Thermal Solar Water Storage Tank Systems: (A Review)
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This work provides a historical overview of water storage tanks used for solar energy collection, with a focus on the impact of different geometric configurations on thermal performance and energy storage efficiency. The designs of cylindrical, spherical, rectangular and triangular tanks were reviewed to analyse their effects on thermal gradients, heat retention and energy storage capacity. Within the scope of nominal processes, the study primarily aimed to identify the factors influencing the choice of tank shape in terms of size, capacity and aspect ratio. Another key objective was to assess what enhances heat storage in the tank to improve thermal efficiency. Comparing cylindrical shapes to other shapes, such as spherical, rectan

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Publication Date
Tue Apr 24 2018
Journal Name
Journal Of The American Geriatrics Society
A Systems Approach to Identify Factors Influencing Adverse Drug Events in Nursing Homes
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The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

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Publication Date
Wed Aug 15 2018
Journal Name
Al-khwarizmi Engineering Journal
Study the Dissociation Enthalpies for R134a Clathrate Hydrate in Binary and Ternary Systems
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In the present work the clathrate hydrate dissociation enthalpies of refrigerant R134a+ water system, and R134a + water + salt system were determined. The heat of dissociation of three types of aqueous salts solutions of NaCl, KBr and NaF at three concentrations (0.09, 0.17and 0.26) mol·kg−1 for each salt type, were enthalpy measured. The Clapeyron equation was used tocalculate heat of dissociation of experimental data for binary and ternary system.In order to find the effect of compressibility factor on heat dissociation enthalpy, the study was conducted by using equation of state proposed by Peng and Robinson Stryjek-Vera (PRSV). The obtained results of dissociation enthalpy for binary system were (143.8) kJ.mol-1

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Publication Date
Fri Apr 24 2026
Journal Name
F1000research
Machine Learning Assisted Hybrid Cuckoo Search for Predictive Optimization in Renewable Energy Systems
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Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

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Publication Date
Sun May 17 2026
Journal Name
Micro And Nanostructures
Tunable broadband selective absorber for active thermal management in solar energy harvesting systems
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Excess heat significantly reduces the efficiency and lifespan of electrical and optoelectronic devices. While passive radiative cooling is becoming more common, achieving active thermal control without physical reconfiguration remains challenging. Unlike conventional static absorbers, we propose a broadband plasmonic solar absorber designed to regulate energy absorption in the near-infrared (NIR) region without modifying the geometrical parameters. The design utilizes a coaxial cylindrical metal-insulator-metal (MIM) configuration, combining refractory copper (Cu), silicon dioxide (SiO2), and a trilayer graphene (Gr) that allows electrical tuning in a broadband solar absorber. Simulation results show a maximum broadband absorption efficienc

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Fri Nov 28 2025
Journal Name
Arabian Journal For Science And Engineering
Role of Artificial Intelligence in Enhancing Efficiency and Sustainability in Middle Eastern Oil and Gas: A Review
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This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.

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Publication Date
Wed Apr 12 2017
Journal Name
Int'l Journal Of Computing, Communications & Instrumentation Engg.(ijccie)
Variant Parameters effect on OFDM Estimation Power Consumption
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Publication Date
Wed Sep 09 2009
Journal Name
University Of Baghdad
Estimation of Reservoir Rock Properties from Well Measurements
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Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil

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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Estimation of Surface Runoff to Bahr AL-Najaf
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The estimation of the amounts of Surface runoff resulting from rainfall in the water basins is of great importance in water resources management. The study area (Bahr Al-Najaf) is located on the western edge of the plateau and the southwestern part of the city center of Najaf, with an area of 2729.4 (km2). The soil and water assessment tool (SWAT) with ArcGIS software was used to simulate the runoff coming from the three main valleys (Kharr (A and B)), Shoaib Al-Rahimawi, and Maleh), that contribute the flow to the study area. The results of the model showed that the SWAT software was successfully simulating the flow conditions based on the coefficient of determination (R2), the Nash coefficient (NS

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