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Best Way to Detect Breast Cancer by UsingMachine Learning Algorithms
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Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with missing value and without
missing value, where the missing value is one attribute is missing from one sample
for data set. The test result is show SMO is the best algorithm, especiallywhen the
research removes the samples that contained the missing value.

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Publication Date
Thu Jun 17 2021
Journal Name
Revista Iberoamericana De PsicologÍa Del Ejercicio Y El Deporte
THE EFFECT OF USING THE ELECTRONIC PARTICIPATORY LEARNING STRATEGY ACCORDING TO THE WEB PROGRAMS IN LEARNING SOME BASIC SKILLS OF BASKETBALL FOR FIRST-GRADE INTERMEDIATE SCHOOL STUDENTS ACCORDING TO THE CURRICULAR COURSE
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The research aims to identify the impact of using the electronic participatory learning strategy according to internet programs in learning some basic basketball skills for middle first graders according to the curricular course, and the sample of research was selected in the deliberate way of students The first stage of intermediate school.As for the problem of research, the researchers said that there is a weakness in the levels of school students in terms of teaching basketball skills, which prompted the researchers to create appropriate solutions by using a participatory learning strategy.The researchers imposed statistically significant differences between pre and post-test tests, in favor of the post tests individually and in favor of

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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimation Hazard of Lung Cancer Due to Radiate Radon Gas in Diyala Governorate Schools
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In this research, the concentration of radon gas has been calculated in the classrooms of schools in Diyala Governorate by using the nuclear track detector (CR-39), which was one of the organic solid-state nuclear detectors (SSNTDs). After calculating the radon gas concentration, the lung cancer cases were calculated. The results showed that the lowest value was found in (Alshumue) school (4.753) people. In contrast, the highest value was found in (Habhib) school (20.421). The average values of lung cancer cases in Diyala governorate were equal to (9.319) per person. The results showed that the number of lung cancer cases per year per million persons in Diyala Governorate schools was below the allowed limit from (ICRP) agency (170-230) p

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Publication Date
Sat Feb 26 2022
Journal Name
Iraqi Journal Of Science
Evaluation of PARP-1 by immunohistochemistry in a sample of Iraqi patients with gastric cancer
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     PARP-1 is a protein enzyme with a major role in DNA repair that is overexpressed in many malignancies. It is correlated with susceptibility and metastasis to lymph nodes in gastric cancer (GC). The objective of the present investigation is to estimate PARP1 expression in patients with gastric cancer and detected if it could be used as a predictive marker. Furthermore, we aimed to find the correlation between PARP1 expression and clinicopathological parameters, such as gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade, and stages of GC. This is a retrospective study from the period 2018-2020. Fifty randomly selected subjects (10 normal and 40 GC) were examined for formalin-fixe

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Proposed Approach for Analysing General Hygiene Information Using Various Data Mining Algorithms
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General medical fields and computer science usually conjugate together to produce impressive results in both fields using applications, programs and algorithms provided by Data mining field. The present research's title contains the term hygiene which may be described as the principle of maintaining cleanliness of the external body. Whilst the environmental hygienic hazards can present themselves in various media shapes e.g. air, water, soil…etc. The influence they can exert on our health is very complex and may be modulated by our genetic makeup, psychological factors and by our perceptions of the risks that they present. Our main concern in this research is not to improve general health, rather than to propose a data mining approach

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Designing Cassegrain Telescope System with Best Obscuration Ratio of Secondary Mirror
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     A computer simulation was conducted using Optics Software for Layout and Optimization (OSLO) to design a Cassegrain telescope system for on-axis rays. In order to establish such a telescope, the two mirrors of the optical system were designed as spherical surfaces: a concave mirror and a convex mirror. The obscuration ratios of the Cassegrain telescope's secondary mirror were examined using different values, which ranged between 0.1 and 0.3, to determine the best obscuration ratio. This work adopted three criteria to decide which obscuration ratio is the best for the Cassegrain telescope. The first criterion was the number of rays that reached the final image. The second criterion was calculating the modulation transfer function

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Publication Date
Mon May 31 2021
Journal Name
Iraqi Journal Of Science
Multi-criteria Decision Making on the Best Drug for Rheumatoid Arthritis
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The theory of Multi-Criteria Decision Making (MCDM) was introduced in the second half of the twentieth century and aids the decision maker to resolve problems when interacting criteria are involved and need to be evaluated.  In this paper, we apply MCDM on the problem of the best drug for rheumatoid arthritis disease. Then, we solve the MCDM problem via -Sugeno measure and the Choquet integral to provide realistic values in the process of selecting the most appropriate drug. The approach confirms the proper interpretation of multi-criteria decision making in the drug ranking for rheumatoid arthritis.

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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Some Results in Grűnwald-Letnikov Fractional Derivative and its Best Approximation
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Abstract<p>In This paper, we have been approximated Grűnwald-Letnikov Derivative of a function having m continuous derivatives by Bernstein Chlodowsky polynomials with proving its best approximation. As well as we have been solved Bagley-Torvik equation and Fokker–Planck equation where the derivative is in Grűnwald-Letnikov sense.</p>
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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Determining the Best Rainwater Harvesting System in Al-Muthanna Governorate, Iraq
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     Rainwater harvesting is one of the available solutions to overcome water scarcity in arid and semi-arid regions with highly variable rainfall and unexpected periods of drought or floods. This study aims to identify the best rainwater harvesting system in Al-Muthanna governorate using Remote Sensing (RS) and Geographic Information System (GIS) techniques. Landsat 8 images were used to produce the land use map which shows five different classes: water (0.2%), bare soil (82.11%), built-up (15.71%), forest (0.27%), and farmland and grass (1.71%). The results revealed that the rainwater harvesting system can be applied only in the north and north-eastern parts of the study area which consists of residential and agricultural areas and

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Publication Date
Thu Apr 11 2019
Journal Name
Scientific Reports
Small-Molecule Ferroptotic Agents with Potential to Selectively Target Cancer Stem Cells
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Abstract<p>Effective management of advanced cancer requires systemic treatment including small molecules that target unique features of aggressive tumor cells. At the same time, tumors are heterogeneous and current evidence suggests that a subpopulation of tumor cells, called tumor initiating or cancer stem cells, are responsible for metastatic dissemination, tumor relapse and possibly drug resistance. Classical apoptotic drugs are less effective against this critical subpopulation. In the course of generating a library of open-chain epothilones, we discovered a new class of small molecule anticancer agents that has no effect on tubulin but instead kills selected cancer cell lines by harnessing reactive oxygen </p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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