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Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, which is used to cluster genes. FCM allows an object to belong to two or more clusters with a membership grade between zero and one and the sum of belonging to all clusters of each gene is equal to one. This paradigm is useful when dealing with microarray data. The total time required to implement the first model is 22.2589 s. The second model combines FCM and particle swarm optimization (PSO) to obtain better results. The hybrid algorithm, i.e., FCM–PSO, uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–PSO method is effective. The total time of implementation of this model is 89.6087 s. The third model combines FCM with a genetic algorithm (GA) to obtain better results. This hybrid algorithm also uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–GA method is effective. Its total time of implementation is 50.8021 s. In addition, this study uses cluster validity indexes to determine the best partitioning for the underlying data. Internal validity indexes include the Jaccard, Davies Bouldin, Dunn, Xie–Beni, and silhouette. Meanwhile, external validity indexes include Minkowski, adjusted Rand, and percentage of correctly categorized pairings. Experiments conducted on brain tumor gene expression data demonstrate that the techniques used in this study outperform traditional models in terms of stability and biological significance.

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Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Numerical solution to inverse coefficient problem for hyperbolic equation under overspecified condition of general integral type
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Wed Jul 17 2019
Journal Name
Aip Conference Proceedings
The correction of the line profiles for x-ray diffraction peaks by using three analysis methods
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In this study used three methods such as Williamson-hall, size-strain Plot, and Halder-Wagner to analysis x-ray diffraction lines to determine the crystallite size and the lattice strain of the nickel oxide nanoparticles and then compare the results of these methods with two other methods. The results were calculated for each of these methods to the crystallite size are (0.42554) nm, (1.04462) nm, and (3.60880) nm, and lattice strain are (0.56603), (1.11978), and (0.64606) respectively were compared with the result of Scherrer method (0.29598) nm,(0.34245),and the Modified Scherrer (0.97497). The difference in calculated results Observed for each of these methods in this study.

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
The Efficacy of Poppy, Papaver nudicaule extract as an Anesthetic for the Common Carp, Cyprinus carpio
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Aqueous extract of poppy plant) Papaver nudicaule) with five concentrations (50, 100, 150, 200 and 250) mg/l were used to anesthetize fingerlings of the common carp Cyprinus carpio (Mean total length 8.91 ± 0.31 cm and mean total weight 7.72 ± 1.19 gm) instead of the traditional use of MS-222. Results showed that extracted solution of poppy have partial and overall anesthesia effect on these fishes with inverse relationship between the concentrations used and the time needed to reach partial and overall anesthesia, and also direct relationship between concentrations used and time needed for fish recovery. Best results were obtained by using a concentration of 250 mg/l, where time for partial anesthesia was 8 ± 1.52 m

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Clinical and Refractive Outcomes of Toric Phakic Implantable Collamer lens Implantat for correction of myopic astigmatism
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Background: Currently there are four general approaches to correct refractive errors: refractive corneal surgery, crystalline lens surgery and implantation of an intraocular lens in anterior or posterior chamber.

Objective: To evaluate the predictability, safety and stability of toric phakic implantable collamer lens implantation to correct moderate to high myopic astigmatism. in  Eye Specialty Private Hospital, Baghdad, Iraq.

Type of the Study: a prospective non randomize intervention study.

Methods: 60 eyes of 40 patients underwent implantation of a toric implantable collamer lens (V4c design).Mean spherical refraction was ₋11.32 diopter

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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Synthesis of chitosan-iron keplerate composite as an adsorbent for removal of toxic ions from water
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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Operating Conditions for Adsorption of Heavy Metals from an Aqueous Solution by an Agriculture Waste
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   The aim of this work is to detect the best operating conditions that effect on the removal of Cu2+, Zn2+, and Ni2+ ions from aqueous solution using date pits in the batch adsorption experiments. The results have shown that the Al-zahdi Iraqi date pits demonstrated more efficient at certain values of operating conditions of adsorbent doses of 0.12 g/ml of aqueous solution, adsorption time 72 h, pH solution 5.5 ±0.2, shaking speed  300 rpm, and smallest adsorbent particle size needed for removal of metals.  At the same time the particle size of date pits has a little effect on the adsorption at low initial concentration of heavy metals. The adsorption of metals increases with increas

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Publication Date
Wed Jan 04 2006
Journal Name
The Iraqi Postgraduate Medical Journal
Elucidation of a Role for the Aqueous Extract of Borage in Mammary Gland Growth and Development
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Gaussian Integer Solutions of the Diophantine Equation x^4+y^4=z^3 for x≠ y
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The investigation of determining solutions for the Diophantine equation  over the Gaussian integer ring for the specific case of  is discussed. The discussion includes various preliminary results later used to build the resolvent theory of the Diophantine equation studied. Our findings show the existence of infinitely many solutions. Since the analytical method used here is based on simple algebraic properties, it can be easily generalized to study the behavior and the conditions for the existence of solutions to other Diophantine equations, allowing a deeper understanding, even when no general solution is known.

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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