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Improving the Accuracy of Handheld GPS Receivers Based on NMEA File Generating and Least Squares Adjustment
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This study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enhance its accuracy. Moreover, one hundred reference control points were established using geodetic GPS receiver (GR5 receiver), and fixing them in a specified sites of the University of Baghdad, Al Jadriya campus, which selected as a study area, to evaluate positioning accuracy of handheld GPS before and after adjustment. The study findings showed significant decrease in root mean square error (RMSE) in both horizontal and vertical directions from 9.4 m to 3.2 m and 6.8 m to 2.4 m respectively.

 

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
Hartha Formation divisions Based on Well Logs Analysis in Majnoon Oil Field, Southern Iraq
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This study aims to evaluate reservoir characteristics of Hartha Formation in Majnoon oil field based on well logs data for three wells (Mj-1, Mj-3 and Mj-11). Log interpretation was carried out by using a full set of logs to calculate main petrophysical properties such as effective porosity and water saturation, as well as to find the volume of shale. The evaluation of the formation included computer processes interpretation (CPI) using Interactive Petrophysics (IP) software.  Based on the results of CPI, Hartha Formation is divided into five reservoir units (A1, A2, A3, B1, B2), deposited in a ramp setting. Facies associations is added to well logs interpretation of Hartha Formation, and was inferred by a microfacies analysis of th

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
High Transaction Rates Performance Evaluation for Secure E-government Based on Private Blockchain Scheme
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Refractive Index Sensor Based on Micro- Structured Optical Fibers with Using Finite Element Method
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In this paper a refractive index sensor based on micro-structured optical fiber has been proposed using Finite Element Method (FEM). The designed fiber has a hexagonal cladding structure with six air holes rings running around its solid core.  The air holes of fiber has been infiltrated  with different liquids such as water , ethanol, methanol, and toluene then sensor characteristics like ; effective refractive index , confinement loss, beam profile of the fundamental mode, and sensor resolution are investigated by employing the FEM. This designed sensor characterized by its low confinement loss and high resolution so a small change in the analyte refractive index could be detect which is could be useful to detect the change of

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Publication Date
Sat Sep 21 2013
Journal Name
Nonlinear Dynamics
BER performance enhancement for secure wireless optical communication systems based on chaotic MIMO techniques
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

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Publication Date
Thu Jun 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Innovations in t-way test creation based on a hybrid hill climbing-greedy algorithm
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Analysis for Hybrid Massive MIMO FSO/RF Links Based on Efficient Channel Codes
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