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Theoretical Simulation Of Stress-Strain Relations For Some Iraqiclays Using The Endochronic Model
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Publication Date
Sun Dec 27 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Banking Market & Its Effect To Fulfill Competitive Advantage For Banks
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As harmony with modernized environmental developments which were appeared within economical , banking areas with what accompanied of chances or challenges , the matter is required to face those modernizations , adaptation with them , as considering them strength points not weak points , and these developments banking marketing as it should be on the Iraqi public banks and private and hybrid to take advantage of this process to increase excellence and the expansion of the banking business opportunities, , enlarge in the banking businesses especially the banking transaction are distinguished by serious competition & strong between banks , and the final result is to serve Iraqi banking system & customers that the national economy ta

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Publication Date
Fri Jan 01 2010
Journal Name
2010 Second International Conference On Computer Research And Development
Per-Priority Flow Control (PPFC) for Enhancing Metro Ethernet QoS
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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Sun Jun 03 2018
Journal Name
Baghdad Science Journal
Diamine Derivatives as Photostabilizers for Thermoplasticized Poly(Vinyl Chloride) [I]
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The photostabilization? of poly vinyl chloride (PVC) ? films has been investigated by using diamine derivatives. The? (PVC) films were? contained 0.5% weight? of diamine derivatives which prepared by the method of casting. The photostabilizations? ?of these compounds were determined by monitoring the carbonyl index value with irradiation time. Also, the effect ?of concentrations of additives (range 0.1-0.5wt) on the rate of photostabilization? process was studied. Therefore we found? that a increased photostabilization rates was increase with increasing? concentrations of compound. Besides, the influence? on film thickness? of photostabilization process was also studied; ?and the results? showed that? the increasing of film thickness incr

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Optimized Kalman filters for sensorless vector control induction motor drives
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<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq
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The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstraction and examin

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Publication Date
Wed Feb 07 2018
Journal Name
Proceedings Of The 2018 4th International Conference On Mechatronics And Robotics Engineering
Secure Transition for Robotic Surgery With Elliptic Curve Diffie Hellman
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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Sat Jan 01 2011
Journal Name
International Journal Of Computer Theory And Engineering
MIPOG - An Efficient t-Way Minimization Strategy for Combinatorial Testing
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