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Improving accuracy of CADx system by hybrid PCA and backpropagation
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—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when combined principal component analysis and feed forward back propagation neural network. This work has investigated the ability to improve the CAD system in order to use in detection abnormality even with low cost diagnosis methods (such as mammogram images or X-ray). The results show that the reduction of correlated details within the training data by using the PCA method can enhance the recognition performance. The performance of the neural network diagnostic to discriminate the normal cases from cancerous cases, evaluated by using recognition analysis show a high accuracy in detection. The proposed approach can be considered as a potential tool for diagnosis breast cancer from x-ray and mammography images and prediction for nonexperts and clinicians.

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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Fri Jan 17 2025
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Optimal Hybrid Fuzzy PID for Pitch Angle Controller in Horizontal Axis Wind Turbines
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Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal

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Publication Date
Thu Apr 03 2025
Journal Name
Isa Transactions
Optimal hybrid type-3 fuzzy controller for horizontal axis wind turbines: Comparative study
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The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Engineering
Hydraulic Analysis of the Samarra-Al Tharthar System
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Low incoming discharge upstream of Samarra-Al Tharthar System leads to sediment accumulation and forming islands, especially an island upstream of Al Tharthar Regulator. This island and the sedimentation threaten the stability of the structure and reduce the efficiency of the system. This study aims to hydraulically identify the sedimentation problem mentioned above, to find solutions of how to control the sediment problems, and to develop the capacity of
the system for 500 years return period flood of 15060 m3/s. Surface Water Modeling System (SMS10.1) with two dimensional depth average models (RMA-2) software were used to simulate and analyze the system. The results of analysis showed that the maximum permissible discharge through t

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Application of Groebner Bases to Study a Communication System
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This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.

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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Using Smart Control System to Enhancement the Split Air Conditioning System Performance
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In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 500C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Simulation and Experimental Investigation of Performance and Flow Behavior for Steam Ejector Refrigeration System
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The ejector refrigeration system is a desirable choice to reduce energy consumption. A Computational Fluid Dynamics CFD simulation using the ANSYS package was performed to investigate the flow inside the ejector and determine the performance of a small-scale steam ejector. The experimental results showed that at the nozzle throat diameter of 2.6 mm and the evaporator temperature of 10oC, increasing boiler temperature from 110oC to 140oC decreases the entrainment ratio by 66.25%. At the boiler temperature of 120oC, increasing the evaporator temperature from 7.5 to 15 oC increases the entrainment ratio by 65.57%. While at the boiler temperature of 120oC and

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