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IMPROVEMENT THE MECHANICAL WEAR RESISTANCE OF METAL KNIFE USED IN HARVESTER MACHINE
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SKF Dr. Abbas S. Alwan, Dhurgham I. Khudher, INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2015

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Publication Date
Sun Jan 12 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Distribution of tooth wear among institutionalized residents (50-89 years old) in Baghdad city\ Iraq (Cross-sectional study)
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Background: Tooth wear is one of the most common problems in the older dentate population which results from the interaction of three processes (attrition, abrasion and erosion) and it affects all societies, different age groups, and all cultures. This study was achieved to evaluate the prevalence and distribution of tooth wear among institutionalized residents in Baghdad city\ Iraq. Subjects and Methods: This survey was accomplished on four private and one governmental institution in Baghdad city. One-hundred twenty three (61 males, 62 females) aged 50-89 years were participated in this study. The diagnosis and recording of tooth wear were according to criteria of Smith and Knight. Results: The prevalence of tooth wear was 100% with a mean

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Evaluation of the level of Some Heavy Metals in Tobacco of Domestic and Imported Cigarette Brands Used in Iraq
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Smoking-related diseases can be attributed to the inhalation of many different toxins, including heavy metals, which have a host of harmful health effects. The primary objective of this study was to determine whether local and imported cigarette brands used in Iraq , have they elevated levels of metals or not .Three metals Lead (Pb) , Cadmium (Cd) and Chromium(Cr) were determined in tobacco of seventeen brands of imported cigarettes commonly available in Iraq and three Iraqi domestic cigarettes , which were randomly taken from retail market in Baghdad by using flame atomic absorption spectrometry. The produced data of imported and local cigarette brands were discussed and compared together and with studies from elsewhere .The result

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Improvement of the Rheological and Filtration Properties of Drilling Mud Using the Syrian Clay
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Drilling fluid properties and formulation play a fundamental role in drilling operations. The Classical water-based muds prepared from only the Syrian clay and water without any additives((Organic and industrial polymers) are generally poor in performance. Moreover, The high quantity of Syrian clay (120 gr / l) used in preparing drilling fluids. It leads to a decrease in the drilling speed and thus an increase in the time required to complete the drilling of the well. As a result, the total cost of drilling the well increased, as a result of an increase in the concentration of the solid part in the drilling fluid. In this context, our study focuses on the investigation of the improvement in drilling mud   Prepa

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Materials And Environmental Science
Study the effect of some chemicals used locally in agricultural processes in Iraq on the DNAof some non-targeted organisms
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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
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning
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     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
A Study of Wear Rate Epoxy Resin filled with SiO2 particle and Glass fibers
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This research is devoted to study the effect of different in weight percentage of Sio2 particles and glass fibers (5, 10, 15, 20) wt. % on the wear rate epoxy resin. The results show that the value of hardness increase with the increase for the weight percentage of reinforcing particles and fibers, while the wear rate decrease with the increase the load level of the reinforcing particles and fibers . The largest value of the hardness, and the lowest value of the wear rate for epoxy reinforced with 20% of SiO2, the wear rate increase in general with increasing the applied load.

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Publication Date
Tue May 04 2021
Journal Name
Journal Of Tribology
Hardened Edges Effects on Wear Characteristics of Cultivator Sweeps Using Circular Soil Bin Test
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Abstract<p>Tillage tools are subject to friction and low-stress abrasive wear processes with the potential deterioration of the desired soil quality, loss of mechanical weed efficacy, and downtime for replacing worn tools. Limited experimental methods exist to quantify investigate the effect of wear-resistant coatings on shape parameters of soil-engaging tools. ASTM standard sand/rubber wheel abrasion and pin-on-disk tests are not able to simulate wear characteristics of the complex shape of the tillage tools. Even though the tribology of tillage tools can be realistic from field tests, tillage wear tests under field conditions are expensive and often challenging to generate repeatable engineeri</p> ... Show More
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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