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A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift algorithm is used for segmenting the affected areas of skin cancer images. Finally, these segmented images are given to a deep learning classifier called Deep forest for prediction of skin cancer. The experiments are carried out on two publicly available datasets called ISIC-2019 and HAM10000 datasets for the analysis of segmentation and classification. From the outcomes, it is clearly verified that the projected model achieved better performance than the existing deep learning techniques.

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Role of a University Professor in the Development of Democracy with the Contents of a University Student in the Light of a Democratic Society
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The current research aims to answer the following questions: what is the substance of democracy? What is the content of a democratic society? What is the role of university professor in the democratic development of the student university in light of the new Iraqi society? In order to achieve the goals of the research, the researcher developed an a questionnaire based on literature, Iraq's draft constitution in 2005, and his experience of the field of teaching human rights and public freedoms and the teaching of democracy. It was applied to a sample of faculty members in Department of Education and Psychology / College of Education / University Baghdad for the year 20014 were obtained their answers were then processed statistically. Henc

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Advanced Pharmaceutical Technology & Research
Hesperetin effect on MLH1 and MSH2 expression on breast cancer cells BT-549
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Publication Date
Mon Jul 06 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Obesity and Breast Cancer: Circulating Adipokines and Their Potential Diagnostic as Risk Biomarkers
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Obesity and cancer are two major epidemics of this century. Obesity is related to a higher risk of many types of cancer. Studies have accessed circulating adipokines, as key-mediators in obesity and breast cancer. The study is aimed to examine the circulating levels of insulin-like growth factor-1, leptin, adiponectin, and resistin in premenopausal Iraqi women with breast cancer. The current study was performed during the period from June 2019 to December 2019 at Oncology unit/ Medical City Hospital-Baghdad. A total of 90 premenopausal women with BC/ stage II and III after 2nd dose of chemotherapy were contributed in this study as patients group. Their ages ranged from (35- 50) years in addition to 90 premenopausal healthy women wer

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Surfactant Cloud Point Extraction as a Procedure of Preconcentrating for Metoclopramide Determination Using Spectro Analytical Technique
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In current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection the level of YKL-40 biochemical marker and vitamin D level in sera of Iraqi Uterine cancer females' patients
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Objective: Detection the level of YKL-40 biochemical marker and vitamin D level in sera of Iraqi uterine cancer
females' patients.
Methodology: This study included 90 female volunteers, 30 of them were healthy volunteers who were
considered as a control group, while sixty serum samples were collected from women patients suffering from
uterine tumors (30 malignant and 30 fibroid benign tumors), benign cases were considered as a disease
control group for malignant tumors. The average age of those females was 30-75 years, which matched the
control group. All the samples were collected from Azady hospital in Kirkuk and the gynecologic department at
Medical City in Baghdad during October /2012 to May /2013. All the serum

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods of Estimating the Parameters and Survival Function of a Log-logistic Distribution with a Practical Application
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The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

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Publication Date
Fri Jul 12 2013
Journal Name
Journal Of Biosciences
A functional connection of Dictyostelium paracaspase with the contractile vacuole and a possible partner of the vacuolar proton ATPase
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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Design of an Efficient Face Recognition Algorithm based on Hybrid Method of Eigen Faces and Gabor Filter
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Face recognition is one of the most applications interesting in computer vision and pattern recognition fields. This is for many reasons; the most important of them are the availability and easy access by sensors. Face recognition system can be a sub-system of many applications. In this paper, an efficient face recognition algorithm is proposed based on the accuracy of Gabor filter for feature extraction and computing the Eigen faces. In this work, efficient compressed feature vector approach is proposed. This compression for feature vector gives a good recognition rate reaches to 100% and reduced the complexity of computing Eigen faces. Faces94 data base was used to test method.

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