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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
Sun Dec 05 2021
Journal Name
Iraqi Journal Of Science
The Deep Faults in Kut-Hai and Surrounding Area Inferred From Gravity and Magnetic Data
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Gravity and magnetic data are used to study the tectonic situation of Al-Kut- Al-
Hai and surrounding areas in central Iraq. The study included application of many
processing and interpretation programs. The window method with different spacing
was used to separate the residual from regional anomalies for gravity and magnetic
data. The Total Horizontal Derivative (THDR) techniques used to identify the fault
trends in the basement and sedimentary cover rocks depending upon gravity and
magnetic data. The identified faults in the study area show (NW-SE), (NE-SW) (NS)
and (E-W) trends. It is believed that these faults extending from the basement to
the upper most layer of the sedimentary cover rocks.

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Evaluation of Plasma-microRNA320 level among Colorectal Cancer Iraqi Patients
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Colorectal cancer (CRC) Patients showed different expression patterns of miRNAs which are involved in carcinogenesis in comparison to healthy controls individuals, miRNAs are involved in tumor progression and development of metastases. We investigate the expression profile of microRNA 320 and to quantify the expression level abundance among colorectal cancer patients in comparison to the healthy control group. The A total number of 60 plasma samples was collected from CRC patients along with 40 plasma samples from healthy controls and subjected to relative quantification using qPCR assay with a specified set of primers designed using s

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Publication Date
Sat Jun 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction and Correlations of Residual Entropy of Superheated Vapor for Pure Compounds
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Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one

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Publication Date
Sun Dec 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of The Chemical Composition and Physical properties of Aged Asphalt Cement
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In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

loge(DI)=a1+0.0123(2loge T

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Semi-Analytical Prediction of Flank Tool Wear in Orthogonal Cutting of Aluminum
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This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Optimizing Blockchain Consensus: Incorporating Trust Value in the Practical Byzantine Fault Tolerance Algorithm with Boneh-Lynn-Shacham Aggregate Signature
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The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

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Publication Date
Thu May 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Statistical Mean Studying for Detected Intensities by Enet Web Camera for the White Test Image Under Different Fluorescent Lightness
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    The aim of this work, is to study color filming by using different intensities of fluorescent light, where we evaluate the capture image qualities for the RGB bands and component of L. And we study the relation between the means of RGBL values of the images as a function of the power of fluorescent light circuit . From the results, we show that the mean μ increases rapidly at low power values, then it will reach the stability at high power values.  

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Publication Date
Tue Apr 16 2024
Journal Name
Ecancermedicalscience
Prostate cancer across four countries in the Middle East: a multi-centre, observational, retrospective and prognostic study
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Publication Date
Wed Dec 15 2010
Journal Name
Iraqi Journal Of Laser
Evaluation the Effect of 805 nm Wavelength Diode Laser on Repair of Mandibular Bone Repair and Skin Incisions in Rabbits
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The long healing time of bone after tooth extraction in order to construct artificial teeth is uncomfortable to the patient because of aesthetic or masticatory problems in addition to the daily visit to dental clinic. The objective of this study was to evaluate the effect of 805 nm diode laser with long time intervals on repair of bone and skin incisions in rabbits through biochemical, radiological and histological findings. Eighteen New-Zealand rabbits were undergone surgical operations to make a cavity in the bone of the lower jaw, the rabbits were divided into two groups:- Group A (control group) containing nine rabbits. Group B (lased group) containing nine rabbits in which two cavities were done, one on the right side and the other

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