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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 Jan 27 2019
Journal Name
Civil Engineering Journal
Effect of Size and Location of Square Web Openings on the Entire Behavior of Reinforced Concrete Deep Beams
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This paper presents an experimental and numerical study which was carried out to examine the influence of the size and the layout of the web openings on the load carrying capacity and the serviceability of reinforced concrete deep beams. Five full-scale simply supported reinforced concrete deep beams with two large web openings created in shear regions were tested up to failure. The shear span to overall depth ratio was (1.1). Square openings were located symmetrically relative to the midspan section either at the midpoint or at the interior boundaries of the shear span. Two different side dimensions for the square openings were considered, mainly, (200) mm and (230) mm. The strength results proved that the shear capacity of the dee

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Publication Date
Thu Jun 30 2011
Journal Name
Al-kindy College Medical Journal
The Expression of Epstein-Barr virus in Breast cancer in relation to age
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Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Identification of Genomic Markers By RAPD-PCR Primers in Iraq Breast Cancer Patients
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Random Amplification of Polymorphic DNA (RAPD) analysis was used in this study to direct the attention toward increasing the efficiency of early diagnosis of breast cancer in clinical laboratories at Iraq using recent PCR-dependent protocols and investigate DNA polymorphisms in addition to the detection of genomic markers. Blood samples were collected from 12 diagnosed females with breast cancer (malignant) patients, 12 females with breast benign tumor and 12 controls (normal females). DNA was extracted and RAPD-PCR was performed. The results showed unique profiles of amplified DNA fragments produced in genomic DNA of breast tumors by an arbitrary primers of A8, A11, A12, A13, A15 and A18. Out of the 6 primers used, 1 primer produced mon

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Publication Date
Sat Nov 22 2014
Journal Name
Indian Journal Of Physics
Comparison between shell model and self-consistent mean field calculations for ground charge density distributions and elastic form factors of 12C and 16O nuclei
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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Swab – Surge Pressure Investigation, and the Influence Factors, Prediction and Calculation (Review)
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Surge pressure is supplemental pressure because of the movement of the pipes downward and the swab pressure is the pressure reduction as a result of the drill string's upward movement. Bottom hole pressure is reduced because of swabbing influence. An Investigation showed that the surge pressure has great importance for the circulation loss problem produced by unstable processes in the management pressure drilling (MPD) actions. Through Trip Margin there is an increase in the hydrostatic pressure of mud that compensates for the reduction of bottom pressure due to stop pumping and/or swabbing effect while pulling the pipe out of the hole. This overview shows suggested mathematical/numerical models for simulating surge pressure problems ins

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
A Study of a Certain Family of Multivalent Functions Associated with Subordination
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The aim of this paper is to introduce a certain family of new classes of multivalent functions associated with subordination. The various results obtained here for each of these classes include coefficient estimates radius of convexity, distortion and growth theorem.  

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Publication Date
Tue Dec 01 2015
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Expression Analysis of Salivary Microrna-31 in Oral Cancer Patients
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Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Characterization of Topical Letrozole Nanoemulsion for Breast Cancer
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Letrozole (LZL) is a non-steroidal competitive aromatase enzyme system inhibitor. The aim of this study is to improve the permeation of LZL through the skin by preparing as nanoemulsion using various numbers of oils, surfactants and co-surfactant with deionized water. Based on solubility studies, mixtures of oleic acid oil and tween 80/ transcutol p as surfactant/co-surfactant (Smix) in different percentages were used to prepare nanoemulsions (NS). Therefore, 9 formulae of (o/w) LZL NS were formulated, then pseudo-ternary phase diagram was used as a useful tool to evaluate the NS domain at Smix ratios: 1:1, 2:1 and 3:1.

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