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Accuracy Assessment of Stonex X-300 Laser Scanner Cameras
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Assessment the actual accuracy of laboratory devices prior to first use is very important to know the capabilities of such devices and employ them in multiple domains. As the manual of the device provides information and values in laboratory conditions for the accuracy of these devices, thus the actual evaluation process is necessary.

In this paper, the accuracy of laser scanner (stonex X-300) cameras were evaluated, so that those cameras attached to the device and lead supporting role in it. This is particularly because the device manual did not contain sufficient information about those cameras.

To know the accuracy when using these cameras in close range photogrammetry, laser scanning (stonex X-300) device is used to obtain photos of a board including (23) ground control points on it, those observed from two stations and adjusted by using equations of the 3D adjusted triangulation networks by lengths and angles (hybrid routine). (10) GCPs and (13) checkpoints were used to compare the Root Mean Square Error (RMSE) of checkpoints that result from using laser scan cameras with (RMSE) of the same checkpoints that result from using digital photos (Nikon 5200D).

The result of (RMSE) comparison was ) in the X direction, ) in the Y direction and ) in the Z direction.

 

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
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In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
CO2 Laser Treatment of Cervical Ectropion
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Cervical ectropion is considered to be a physiologic condition caused by columnar epithelium migration from the cervical canal into the vaginal portion of the cervix and usually there is no treatement for clinically asymptomatic cervical ectropion . Treatment can be achieved by thermal cauterization (Electrocautery), Cryosurgery or laser vaporization. Aim of the study: To study the effectiveness of CO2 laser (10600nm) in treatment of symptomatic cervical ectropion . Setting: The study was carried out at Laser Medicine Research Clinic at the Institute of Laser for Postgraduate Studies, University of Baghdad between the first of August 2013 to the end of October 2013. Patients and Methods: Ten female Patients with age range between 25-48 y

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Publication Date
Thu Oct 01 2015
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Quantitative identification of phosphate using X-ray diffraction and Fourier transform infrared (FTIR) spectroscopy
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Inthisstudy,FourierTransformInfraredSpectrophotometry(FTIR),XRay Diffraction(XRD)andlossonignition(LOI),comparativelyemployedtoprovideaquick,relativelyinexpensiveandefficientmethodforidentifyingandquantifyingcalcitecontentofphosphateoresamplestakenfromAkashatsiteinIraq.Acomprehensivespectroscopicstudyofphosphate-calcitesystemwasreportedfirstintheMid-IRspectra(4004000cm-1)usingShimadzuIRAffinity-1,fordifferentcutsofphosphatefieldgradeswithsamplesbeneficiatedusingcalcinationandleachingwithorganicacidatdifferenttemperatures.Thenusingtheresultedspectratocreateacalibrationcurverelatesmaterialconcentrationstotheintensity(peaks)ofFTIRabsorbanceandappliesthiscalibrationtospecifyphosphate-calcitecontentinIraqicalcareousphosphateore.Theirpeakswereass

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Publication Date
Sun Mar 01 2009
Journal Name
Baghdad Science Journal
A Study of structural and electrical properties ofCuIn (Sex Te1-x) 2 thin films
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structural and electrical of CuIn (Sex Te1-x)2

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Publication Date
Tue Dec 25 2018
Journal Name
Journal Of Engineering Science And Technology
RIETVELD TEXTURE REFINEMENT ANALYSIS OF LINDE TYPE A ZEOLITE FROM X-RAY DIFFRACTION DATA
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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Thu Dec 15 2011
Journal Name
Iraqi Journal Of Laser
Laser Hole Drilling of Stainless Steel 321H and Steel 33 Using 3D CO2 Laser CNC Machine
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In present work an investigation for precise hole drilling via continuous wave (CW) CO2 laser at 150 W maximum output power and wavelength 10.6 μm was achieved with the assistance of computerized numerical controlled (CNC) machine and assist gases. The drilling process was done for thin sheets (0.1 – 0.3 mm) of two types of metals; stainless steel (sst) 321H, steel 33 (st). Changing light and process parameters such as laser power, exposure time and gas pressure was important for getting the optimum results. The obtained results were supported with computational results using the COMSOL 3.5a software code.

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Publication Date
Thu Dec 25 2025
Journal Name
Retos
The effect of neurofeedback on free throw accuracy in female basketball players of Baghdad University
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Background: Female basketball players often face difficulties in maintaining free throw accuracy, particularly under psychological and neural pressure. Traditional training emphasizes physical skills, often neglecting cognitive and neurophysiological factors essential for precision performance. Objective: This study examined the effect of neurofeedback training on free throw accuracy in female basketball players at the University of Baghdad, comparing outcomes between an experimental group and a control group, and assessing associated neural changes. Methods: A quasi-experimental design involved two groups: an experimental group receiving neurofeedback to regulate brainwave activity, and a control group undergoing traditional traini

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Publication Date
Sun Mar 27 2022
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Effect of resistance training on the biomechanics and accuracy of serve receiving skills in volleyball
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This study aimed to identify the effect of resistance training on the biomechanics and accuracy of serve receiving skills in volleyball. The research community was composed of 26 young volleyball players of Baghdad volleyball clubs. A total of 4 players were selected for the preliminary experiment, while 14 participants were recruited as the main sample for the study. In the present study, a set of resistance exercises were designed by the researchers for the volleyball players of the sample. Exercises were performed by the sample participants during the course of study. The biomechanical variables considered in the present study were: Preparation moment (shoulder joint angle, hip angle, knee joint angle), moment of pr

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Publication Date
Wed Jun 04 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. T

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