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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Quality of Life of Patients with Type II Diabetes Mellitus in Al- Hilla City-Iraq
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Diabetes mellitus is a global problem nowadays due to increase the disease cases all over the world, in both the developed and developing countries which may affect the quality of life (QOL ) of diabetic patients. This study was conducted to assess the quality of life of patients with type 2 diabetes mellitus (DM) and to determine some selected clinical and sociodemographic factors that affect the quality of life of these patients in Al Hila city-Iraq. This was a cross sectional study in which 100 patients with type 2 diabetes mellitus attending diabetic outpatient clinics of Merjan Teaching Hospital-Al Hila. To assess the quality of life of those diabetic patients, the World Health Organizations Quality of Life Assessment (WHOQOL) was a

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Classification of Fetus Gender Based on Fuzzy C-Mean Using a Hybrid Filter
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Abstract<p>This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap</p> ... Show More
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
The Kinetic responses and foraging behavior of Drosophila melanogaster larvae
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Adaptive responses in larval behavior may be of two kinds: Taxis: This involves a change in direction relative to source of a stimulus. Kinesis: Kinesis has no directional component, but involves change in the rate of performance in response to a stimulus. Drosophila larvae exhibited flexible behavioral responses associated with food acquisition and selection for different environmental conditions. In this investigation, we are concerned explosively with kinetic responses to food viability. Third instar larvae were subjected to test for thirty minutes in each of the following conditions i) in distilled water, ii) in Ringer's solution, iii) in glucose solution and on live yeast suspension. In each case the larva was in a thin layer of solu

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Study the nonlinear behavior of MWCNTs and ZnO/Se/MWCNTs
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MWCNTs and hybrid nanocomposite ZnO/Se/MWCNTs have been prepared via Solvothermal technique using Parr reactor at the temperature 180°C and SeCl2 as a catalyst. The obtained MWCNTs and ZnO/Se/MWCNTs are investigated using the FE-SEM, XRD, UV-VIS Spectroscopy and Z-Scan. The novelty of this research is studying the nonlinear optical properties for these prepared materials and the results exhibit that the thickness of the deposited film for hybrid nanocomposite ZnO/Se/MWCNTs is increased, which in turn, increase the nonlinear phase shift of the laser beam compared with the MWCNTs.

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Publication Date
Sun Jan 01 2023
Journal Name
: Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, , Vol. 17, Nº. 5, 2022, Págs. 319-322
THE ASSERTIVE BEHAVIOR OF DISABLED TENNIS AND TABLE TENNIS PLAYERS
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
EXPERIMENTAL OBSERVATIONS ON THE BEHAVIOR OF A PILED RAFT FOUNDATION
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The piled raft is a geotechnical composite construction consisting of three elements: piles, raft and soil.
In the design of piled rafts, the load shared between the piles and the raft, and the piles are used up to a
load level that can be of the same order of magnitude as the bearing capacity of a comparable single
pile or even greater. Therefore, the piled raft foundation allows reduction of settlements in a very
economic way as compared to traditional foundation concepts.
This paper presents experimental study to investigate the behavior of piled raft system in sandy
soil. A small scale “prototype” model was tested in a sand box with load applied to the system through
a compression machine. The settlement was

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Publication Date
Tue Jul 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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