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Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust at high speed mobility.

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Chemical Sensor Based on a Hollow-Core Photonic Crystal Fiber
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In this work a chemical sensor was built by using Plane Wave Expansion (PWE) modeling technique by filling the core of 1550 hollow core photonic crystal fiber with chloroform that has different concentrations after being diluted with distilled water. The minimum photonic bandgap width is.0003 and .0005 rad/sec with 19 and 7 cells respectively and a concentration of chloroform that filled these two fibers is 75%.

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The impact of not applying justice career empowerment in Jordanian government institutions on the performance of working women
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The study aimed to identify the reality of the application of the organizational equity empowerment at the Jordanian government institutions from the viewpoint of women employees in terms of each of the (delegation equity, training equity, appraisal equity, join in committees equity, participation in decision-making equity), and the impact of non-application of equity empowerment on performance.

Population of the study amounted (986) women employee, while the researcher distributed (340) questionnaire through a randomly sample method.

The study used the questionnaire as a tool to collect the data. And to ensure the reliability of the questionnaire has been calculated Cronbach's co

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Publication Date
Fri Jan 01 2021
Journal Name
2nd International Conference On Engineering & Science
Comparative on-grid solar systems winter performance analyses of different PV technologies in Baghdad weather
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Publication Date
Sun Jun 01 2014
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci.
Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Dimensions of performance to provide nursing services: a comparative analytical research in Baghdad of Rusafa Health Organization
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     This research aims to study the performance of operations to provide nursing services, which included dimensions (quality, timeliness, leadership skills, behavioral manifestations, relationships with others, problem-solving and decision-making, job performance) and its effects in nursing performance. The research to prove the value of the performance of service delivery processes dimensions by nursing staffs working in Iraqi hospitals, nursing and measuring performance. To find out the nature of nursing services, and a comparison between hospitals to measure the extent of the application dimensional among themselves, and that by relying on the dimensions of a global study, which was measu

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Publication Date
Fri Jan 01 2016
Journal Name
Proceedings Of The Eleventh International Network Conference (inc 2016)
A review on power consumption reduction techniques on OFDM
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Scopus (2)
Scopus
Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation
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In this work, microbubble dispersed air flotation technique was applied for cadmium ions removal from wastewater aqueous solution. Experiments parameters such as pH (3, 4, 5, and 6), initial Cd(II) ions concentration (40, 80, and 120 mg/l)  contact time( 2, 5, 10 , 15, and 20min), and surfactant (10, 20and 40mg/l) were studied in order to optimize the best conditions .The experimental results indicate that microbubbles were quite effective in removing cadmium ions and the anionic surfactant SDS was found to be more efficient than cationic CTAB in flotation process. 92.3% maximum removal efficiency achieved through 15min at pH 5, SDS surfactant concentration 20mg/l, flow rate250 cm3/min and at 40mg/l Cd(II) ions initial co

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Publication Date
Wed Oct 01 2014
Journal Name
Engineering And Technology Journal
Investigating Forward kinematic Analysis of a 5-axes Robotic Manipulator using Denavit-Hartenberg Method and Artificial Neural Network
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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The predictive Ability of Admission Criteria and Student Performance Level in Master Programs in College of Education at Sultan Qaboos University
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Abstract

Most universities in the world are largely committed to creating credible and transparent admission standards that provide justice in admission and have the ability to predict students' performance in their chosen programs. Hence, this study aimed to reveal the predictive ability of the acceptance criteria for the level of performance of master's students in the College of Education at Sultan Qaboos University. Quantitative data were collected from (115) students' admission documents for those accepted in the postgraduate programs for the academic year 2019-2020, and GPA data was collected from students’ transcripts for the fall semester of 2019. Qualitative data were also collected from the interviews

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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