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Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

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Publication Date
Sat Nov 26 2022
Journal Name
Sensors
3D Object Recognition Using Fast Overlapped Block Processing Technique
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Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun Jan 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Proposed Algorithm for Gumbel Distribution Estimation
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Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The efficiency of cluster analysis to analyzing medical image of Covid-19 patient by using K-means algorithm
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Applying Ensemble Classifier, K-Nearest Neighbor and Decision Tree for Predicting Oral Reading Rate Levels
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For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Tax Exemptions and their impact in reducing the phenomenon of tax evasion: A field study
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The research aims to verifying the tax exemptions granted in accordance with the Iraqi tax legislations, showing their suitability for basic tax rules, and identifying their role to reduce the tax evasion phenomenon and the negative effects resulting therefrom, which arerepresented by a decrease in the proceeds of tax revenue and therefore leadings to a reduction of public revenues of the state. Also, the research tries to identify the ways to reduce cases of tax evasion due to their reflection positively on the public budgetof the state. The data of the research was collected through two models of questionnaires distributed to a sample of taxpayers from some professions and a sample of the tax administration staff. The research has reac

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Publication Date
Sun Apr 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Role the media to limit from get games children instigator on the violence
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Violence is a very serious phenomenon affecting the upbringing and culture kids, are playing the most violent forms of development of these Phenomenon, the research aims to determine the role of the media in reducing violence, and conducted a field study on parents Children by 200 form, the results revealed the importance of the media in raising awareness of the risks of violence on the child  Especially television, which hugely increased Show features, as well as the role of parents in guiding the child to buy Useful because the game to play negative impact of violence on children's health, and the media play an important role in raising awareness of these Risks through educational programs and television commercials, and o

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of educational institutions and regulatory bodies to reduce the financial and administrative corruption
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This research seeks to clarify the regulatory and educational role of the regulatory and educational institutions in reducing the phenomenon of financial and administrative corruption as a dangerous phenomenon of the communities, as it touched search kinds of financial and administrative corruption and the causes and effects, as well as to the role of educational institutions in reducing this phenomenon, and finally between experiments some SAIs and accounting Arab and foreign countries on how to reduce the phenomenon of financial and administrative corruption.The research aims to several targets which shed light on the role of educational and supervisory institutions in reducing corruption, a statement origins and evolution of and justi

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Publication Date
Sun Mar 28 2021
Journal Name
Journal Of The College Of Education For Women
The Role of Social Work in Reducing the Phenomenon of Fanaticism: حسن فاضل جواد
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The present study is concerned with the concept of ethics academically. It aims to investigate the major problems that contemporary Iraqi society suffers from; on top of which is the problem of sectarian and religious intolerance. Such a problem has a major role in the emergence of extremism and terrorism. It further destabilizes the security and stability of the country, exposing, as a result, the lives of citizens to the danger of genocide, disintegrating the social structure, stopping the wheel of development, rampant corruption, and deteriorating the political, social, moral and economic situation. Here comes the role of social work as governmental institutions and civil society organizations in curbing this reprehensible phenomenon

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