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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
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Publication Date
Wed Dec 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Evaluation of Mechanical Properties of Particulate Composites
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A series of experiments have been taken out to test the validity of the effect of Aluminum hydrate on its interaction with Aluminum during sintering of aluminum metal matrix. The approach has been shown to be valid and several compositions have been fabricated. The alumina hydrate particle size and the amount of alumina hydrate in the composites are also shown to have an influence on the extent of densification.

The densities for all sintered specimens were measured. It was found that density increases as compaction pressure increases, the density decreases as particles size increases. At 400 MPa there is an optimum particles size which is (90-125) µm to reach maximum density and the density decreases as volume fraction increase

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Publication Date
Mon Jul 12 2021
Journal Name
Egyptian Journal Of Chemistry
GC-FID estimation of BTEX compounds in liquid oil resulting from catalytic pyrolysis of used tires
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Thermal decomposition of used tires was studied under atmospheric pressure and thermal heating program up to 350 °C for 110-120 min in a glass reactor. The effects of using MgO or SiO2 as catalyst in the thermal pyrolysis of tires waste on the yield ratio, reaction time, initial degree of decomposition also the contents of BTEX compounds in resulting pyrolytic oil was estimated via GC-FID. The results showed that the MgO catalyst gave a gas output in proportion of 17.063%, a liquid in a proportion of 38.245% and a solid product in proportion of 44.733%, while the SiO2 catalyst gave proportions of 14.308%, 40.161% and 45.448% for gas, liquid and solid products respectively. The results revealed that the thermal pyrolysis produced minor cont

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Bacteremia in Ibn Al-Baladi hospital in Baghdad; Incidence etiology and antibiotic resistance of pathogens
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60 cases of Bacteremia were documented at Ibn Al-Baladi hospital during 6 months (1-1-2002 to 1-7-2002), with an incidence of 5.2 were gram-negative organisms and most common one was Salmonella and Klebsiella. Incidence was significantly higher in male than female .Antimicrobial sensitivity tests revealed that isolated bacteria are with multiple drug resistance to commonly used antimicrobial agents. Salmonella showed high resistance to cephaloxin, co-trimoxazole and amoxicillin and also Klebsiella showed resistance to cephaloxin and amoxicillin.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Development of resistance of some klebsiella species isolated locally
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200 samples collected Adrar of patients with urinary tract infection were investigating the types of bacteria most local isolates showed high resistance to antibiotics penicillin c ??????? Amoxicillin Beracelin

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Sat Oct 31 2020
Journal Name
Eastern-european Journal Of Enterprise Technologies
Design and development of high-accuracy machine for wire bending
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
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Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Engineering
Stability Improvement of The Iraqi Super Grid (400kV) using High Voltage Direct Current (HVDC) Transmission
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This research analyzes the level of the short circuit effect of the Iraqi super network and decides the suitable location for the High Voltage Direct Current (HVDC) connections in order to obtain the best short circuit reduction of the total currents of the buses in the network. The proposed method depends on choosing the transmission lines for Alternating current (AC) system that suffers from high Short Circuit Levels (SCLs) in order to reduce its impact on the transmission system and on the lines adjacent to it and this after replacing the alternating current (AC) line by direct current (DC) line. In this paper, Power System Simulator for Engineering (PSS/E) is used to model two types of HVDC lines in an effective regi

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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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