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Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining
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Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- sectional study.Methods: Data taken from 114 patients with DVT were analyzed by association rules mining.Immobility was the most important risk factor. Results: Smoking add more risk to immobile, post operative patient. Age per se has no effect.100% of patients with long bone fracture, were immobile. Fever occurred in one third of post operative patients who develop DVT. Conclusions: Association rules mining allow better and faster analysis of more data with an interactive powerful system, which saves time and effort, and discovers the relations among many factors to one or more than one factors. So, we use this method for analysis in this study, and we get the above mentioned relations, which are important for the future management of DVT.

 
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Publication Date
Fri Mar 27 2020
Journal Name
Solid State Technology
Seepage and Slope Stability Analysis for Hemrin Earth Dam in Iraq Using Geo-Studio Software
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Publication Date
Sat May 08 2021
Journal Name
Iraqi Journal Of Science
EEG Signals Analysis for Epileptic Seizure Detection Using DWT Method with SVM and KNN Classifiers
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Epilepsy is a critical neurological disorder with critical influences on the way of living of its victims and prominent features such as persistent convulsion periods followed by unconsciousness. Electroencephalogram (EEG) is one of the commonly used devices for seizure recognition and epilepsy detection. Recognition of convulsions using EEG waves takes a relatively long time because it is conducted physically by epileptologists. The EEG signals are analyzed and categorized, after being captured, into two types, which are normal or abnormal (indicating an epileptic seizure).  This study relies on EEG signals which are provided by Arrhythmia Database. Thus, this work is a step beyond the traditional database mission of delivering use

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Publication Date
Sun Jun 05 2011
Journal Name
Baghdad Science Journal
Quantitative Analysis of Some Insecticides and Their Mixture in Agriculture by Using UV-Vis Spectrophotometer
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We studied in this research how to find a method of estimating the quantity (Kinetically) of three kinds of Insecticide and their mixture, which are used in agriculture. The extracted insecticide from the polluted samples with these insect from air, soil, and the leaves of trees, have be used into the reaction with H2O2 and benzedine. The kinetic study of this reaction was formed in basic medium,( pH= 8.6), using UV. Spectra at (?= 420nm). The study showed that the reaction is the first order, and the speed of the reaction was used to estimate the concentration of insecticide in solution and mixture. The experiments of this study indicated that this method has the speed and efficiency for quantitatively estimating these

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Publication Date
Mon Sep 01 2008
Journal Name
Al-khwarizmi Engineering Journal
Correcting Working Postures in Water Pump Assembly Tasks using the OVAKO Work Analysis System (OWAS)
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Ovako Working Postures Analyzing System (OWAS) is a widely used method for studying awkward working postures in workplaces. This study with OWAS, analyzed working postures for manual material handling of laminations at stacking workstation for water pump assembly line in Electrical Industrial Company (EICO) / Baghdad. A computer program, WinOWAS, was used for the study. In real life workstation was found that more than 26% of the working postures observed were classified as either AC2 (slightly harmful), AC3 (distinctly harmful). Postures that needed to be corrected soon (AC3) and corresponding tasks, were identified. The most stressful tasks observed were grasping, handling, and positioning of the laminations from workers. The construct

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Publication Date
Tue Oct 26 2021
Journal Name
Series On Biomechanics
Monitoring and analysis of plantar pressure map and foot motions using a wearable sensing system
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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Split and Merge Regions of Satellite Images using the Non-Hierarchical Algorithm of Cluster Analysis
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يعد التقطيع الصوري من الاهداف الرئيسة والضرورية في المعالجات الصورية للصور الرقمية، فهو يسعى الى تجزئة الصور المدروسة الى مناطق متعددة اكثر نفعاً تلخص فيها المناطق ذات الافادة لصور الاقمار الصناعية، وهي صور متعددة الاطياف ومجهزة من الاقمار الصناعية باستخدام مبدأ الاستشعار عن بعد والذي اصبح من المفاهيم المهمة التي تُعتمد تطبيقاته في اغلب ضروريات الحياة اليومية، وخاصة بعد التطورات المتسارعة التي شهد

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Publication Date
Thu Dec 23 2021
Journal Name
Iraqi Journal Of Science
Spatial Analysis of the CO Emission from Nineveh Governorate Using Remote Sensing Techniques and GIS
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     Carbon Monoxide (CO) has a significant indirect effect on greenhouse gasses due to its ozone and carbon dioxide precursor, and its mechanism of degradation involving the hydroxyl radical (OH) which control the oxidizing ability of the tropospheric. To understand the effect of human activities on atmospheric composition, accurate estimates of the sources of atmospheric carbon monoxide (CO) are necessary. MOPITT (Measurements of Pollution in the Troposphere) is a NASA Terra satellite instrument designed to allow both Thermal-Infra-Red (TIR) and Near-Infra-Red (NIR) observations to be used to collect vertical CO profiles in the Troposphere via the concept of correlation spectroscopy. The objective of the current stu

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Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Dec 05 2021
Journal Name
Iraqi Journal Of Science
The Deep Faults in Kut-Hai and Surrounding Area Inferred From Gravity and Magnetic Data
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Gravity and magnetic data are used to study the tectonic situation of Al-Kut- Al-
Hai and surrounding areas in central Iraq. The study included application of many
processing and interpretation programs. The window method with different spacing
was used to separate the residual from regional anomalies for gravity and magnetic
data. The Total Horizontal Derivative (THDR) techniques used to identify the fault
trends in the basement and sedimentary cover rocks depending upon gravity and
magnetic data. The identified faults in the study area show (NW-SE), (NE-SW) (NS)
and (E-W) trends. It is believed that these faults extending from the basement to
the upper most layer of the sedimentary cover rocks.

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