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A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.

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Publication Date
Sun Jan 01 2023
Journal Name
Studies In Systems, Decision And Control
Gap Analysis by Readiness Review Including Online Learning During COVID-19 Pandemic Period for Engineering Programs at the College of Engineering—University of Baghdad
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Publication Date
Fri May 09 2025
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Sun Nov 19 2017
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques
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Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An exploratory study of history-based test case prioritization techniques on different datasets
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In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Estimation the blast wave pressure effecters by apply Remote Sensing (RS) and Geographic Information System (GIS) techniques
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After the year 2003 terrorist attacks knock Baghdad city capital of Iraq using bomb explosion various, shook the nation, and made public resident of Baghdad aware of the need for better ways to protect occupants, assets, and buildings cause the terrorist gangs adopt style burst of blast to injury vulnerability a wider range form, and many structures will suffer damage from air blast when the overpressure concomitant the blast wave, (i.e., the excess over the atmospheric pressure 14.7 pounds per square inch at standard sea level conditions are about one-half pound per square inch or more(
to attainment injury. Then, the distance to which this overpressure level will extend depends primarily on the energy yield (§1.20) of the burst of

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Suggested Model For Using Customer's Data Management Information System/ A Case Study In Al-Rasheed Bank/General Agent Office/ Nothren Reigon
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This study aim to  identify the concept of  web based information systems since its one of the important topics that is  usually omitted by our organizations, in addition to,  designing a web based information system in order to manage the customers data of Al- Rasheed bank, as a unified information system that is specialized to the banking deals of the customers with the bank, and providing a suggested model to apply the virtual private network as a tool that is to protect the transmitted data through the web based information system.

This study is considered important because it deals with one of the vital topics nowadays, namely: how to make it possible to use a distributed informat

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Novel Approximate Solutions for Nonlinear Initial and Boundary Value Problems
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This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Building a Reliable Steganography System Using Random Key in a spatial Domain of Image
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With time progress importance of hiding information become more and more and all steganography applications is like computer games between hiding and extracting data, or like thieves and police men always thieve hides from police men in different ways to keep him out of prison. The sender always hides information in new way in order not to be understood by the attackers and only the authorized receiver can open the hiding message. This paper explores our proposed random method in detail, how chooses locations of pixel in randomly , how to choose a random bit to hide information in the chosen pixel, how it different from other approaches, how applying information hiding criteria on the proposed project, and attempts to test out in code, and

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
An Evolutionary Algorithm With Heuristic Operator for Detecting Protein Complexes in Protein Interaction Networks With Negative Controls
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