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Machine Learning Approach for Facial Image Detection System

     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s result indicates that the J48 classifier with LDA achieves the highest performance with 96.0001% accuracy.

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Publication Date
Wed Sep 12 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Comparison between Multi-Layer Perceptron and Radial Basis Function Networks in Detecting Humans Based on Object Shape

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Segmenting the Dermatological Diseases Images by Developing the Range Operator

Medical image segmentation is a frequent processing step in image medical understanding and computer aided diagnosis. In this paper, development of range operator in image segmentation is proposed depending on dermatology infection. Three different block sizes have been utilized on the range operator and the developed ones to enhance the behavior of the segmentation process of medical images. To exploit the concept of range filtering, the extraction of the texture content of medical image is proposed. Experiment is conducted on different medical images and textures to prove the efficacy of our proposed filter was good results.

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Effect of Successive Convolution Layers to Detect Gender

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Epidemiological Complex Networks: A Survey

     In this review paper, several research studies were surveyed to assist future researchers to identify available techniques in the field of infectious disease modeling across complex networks. Infectious disease modelling is becoming increasingly important because of the microbes and viruses that threaten people’s lives and societies in all respects. It has long been a focus of research in many domains, including mathematical biology, physics, computer science, engineering, economics, and the social sciences, to properly represent and analyze spreading processes. This survey first presents a brief overview of previous literature and some graphs and equations to clarify the modeling in complex networks, the detection of societie

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Formation of Compressive Residual Stress by Face Milling Steel AISI 1045

Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Performance Enhancement of Face Recognition under High-Density Noise Using PCA and De-Noising Technique

       There are many techniques for face recognition which compare the desired face image with a set of faces images stored in a database. Most of these techniques fail if faces images are exposed to high-density noise. Therefore, it is necessary to find a robust method to recognize the corrupted face image with a high density noise. In this work, face recognition algorithm was suggested by using the combination of de-noising filter and PCA. Many studies have shown that PCA has ability to solve the problem of noisy images and dimensionality reduction. However, in cases where faces images are exposed to high noise, the work of PCA in removing noise is useless, therefore adding a strong filter will help to im

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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Molecular diagnosis of bcr-abl fusion gene in CML patients using Monoplex-Two Steps- Reveres Transcriptase–Polymerase Chain

Background: Chronic myeloid leukemia (CML) is a stem cell disorder associated with an acquired chromosomal abnormality, Philadelphia chromosome (Ph), which arises from the reciprocal translocation of part of long arm of chromosome 9, in which proto-oncogene ablson gene (abl) is located, to long arm of chromosome 22, in which break point cluster region gene (bcr) is located. The bcr-abl fusion gene can be detected using several molecular methods. For its simplicity, rapidity, and sensitivity, Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) is one of the most common techniques used for analyzing whether a target gene is being expressed or not.
Patients and methods: Venous blood (VB) sample from hem

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Using Normalized Difference Vegetation Index (Ndvi) To Assessment The Changes Of Vegetations Cover In Surrounding Area Of Himreen Lake

The study area lies in the eastern part of Iraq, within Diyala and small parts of Salah Al-Din and Sulamanyah Governorates. The eastern boundary of the map represents Iraqi-Iranian International borders; it covers about 7001 Km2.The present study depends on two scenes of Thematic Mapper (TM5) data of Landsat and one scene of Multi-Spectral Scanner (MSS) data of Landsat, these data are subset and corrected within the ERDAS 9.2 software using UTM N38 projection. Normalized Difference Vegetation Index (NDVI) was adopted as practical tool for monitoring the surrounding area of Himreen Lake. The obtained result shows the distributions of NDVI for period 1976-1992 were positive pattern of (High vegetation density and Moderate vegetation densit

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Publication Date
Tue Jan 11 2022
Journal Name
Iraqi Journal Of Science
Methods and Simulations used to Detect Photons from Exoplanets of a Parent Star

The extrasolar planets in the vicinity of stars are expected to be bright enough
and are very difficult to be observed by direct detection. The problem is attributed to
the side loops of the star that created due to the telescope diffraction processing.
Several methods have been suggested in the literatures are being capable to detect
exoplanet at a separation angle of 4λ/D and at a contrast ratio of 10-10. These
methods are more than one parameter function and imposing limitations on the inner
working distance. New simple method based on a circular aperture combined with a
third power Gaussian function is suggested. The parameters of this function are then
optimized based on obtaining a minimum inner working dis

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary-Based Mutation With Functional Annotation to Identify Protein Complexes Within PPI Networks

     The research deals with an evolutionary-based mutation with functional annotation to identify protein complexes within PPI networks. An important field of research in computational biology is the difficult and fundamental challenge of revealing complexes in protein interaction networks. The complex detection models that have been developed to tackle challenges are mostly dependent on topological properties and rarely use the biological  properties of PPI networks. This research aims to push the evolutionary algorithm to its maximum by employing gene ontology (GO) to communicate across proteins based on biological information similarity for direct genes. The outcomes show that the suggested method can be utilized to improve the

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