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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 Apr 29 2018
Journal Name
Iraqi Journal Of Science
Solving Flexible Job Shop Scheduling Problem Using Meerkat Clan Algorithm
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Meerkat Clan Algorithm (MCA) that is a swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. Meerkat has some behaviour. Sentry, foraging, and baby-sitter are the behaviour used to build this algorithm through dividing the solution sets into two sets, all the operations are performed on the foraging set. The sentry presents the best solution. The Flexible Job Shop Scheduling Problem (FJSSP) is vital in the two fields of generation administration and combinatorial advancement. In any case, it is very hard to accomplish an ideal answer for this problem with customary streamlining approaches attributable to the high computational unpredictability. Most

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction of Un-Cored Intervals Using FZI Method and Matrix Density Grouping Method: A Case Study of Abughirab Field/Asmari FM., Iraq
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Knowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea

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Publication Date
Sun Jan 24 2016
Journal Name
Al-academy
Shift formal regulations on Mesopotamian pottery (Pottery Samarra model): محمد جاسم محمد العبيدي
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Operated Alandziahih "drift theory" as a science talk in most of the cash and technical studies in the early twentieth century, making him and the sciences, arts and culture both fields of experiences, in an attempt to explore the institutions that theory, a number of laws which took control in the internal structures of those acts, resulting in for those institutions to be actively contribute their ideas to guide the pace on the right track. And thus lay the foundations of this theory, which was a big affair in the early twentieth century and still vigorous pace to this day, particularly their applications in various fields of the arts.Although each type of Arts, both in the composition or the theater or means of communication, took joi

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Efficient method to Recognition of Anemia Images based on Moment Invariants and Decision tree classifier
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Anemia is one of the common types of blood diseases, it lead to lack of number of RBCs (Red Blood Cell) and amount hemoglobin level in the blood is lower than normal.
In this paper a new algorithm is presented to recognize Anemia in digital images based on moment variant. The algorithm is accomplished using the following phases: preprocessing, segmentation, feature extraction and classification (using Decision Tree), the extracted features that are used for classification are Moment Invariant and Geometric Feature.
The Best obtained classification rates was 84% is obtained when using Moment Invariants features and 74 % is obtained when using Geometric Feature. Results indicate that the proposed algorithm is very effective in detect

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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessment of Some Hematological parameters in Iraqi Women with Different Breast Cancer Stages
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Breast cancer (BC) is the most commonly diagnosed cancer in women. The metabolism of iron is closely regulated by hepcidin which exerts its action by interacting with a ferroportin.

 The aim of the present study was to assess the alterations in the levels of some serum biomarkers that have a role in iron homeostasis (hepcidin and ferroportin) in addition to hematological parameters (hemoglobin, leukocyte and platelets count) in different stages of BC.

This study included 66 women with BC. The patients were categorized as follows : group 1 includes :22 patients with stage I disease ,group 2 includes: 22 patients with stage II disease ,and group 3 include: 22 patients with stage III disease .Group 4 includes :22 appare

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Publication Date
Wed May 10 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate The Mean of Normal Distribution Via Preliminary Test Shrinkage Technique
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 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
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Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

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Publication Date
Mon Jan 12 2009
Journal Name
Department Of Horticulture And Landscape Gardening Design
ESTIMATION OF GENE ACTION AND GENETIC PARAMETERS FOR SOME CHARACTERS OF IN SUMMER SQUASH (Cucrbita pepo L.) BY USING MEAN GENERATION ANALYSIS
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An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of vegetative , flowery growth , yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1= cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses)

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