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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
Thu May 04 2023
Journal Name
Journal Of Indian Association Of Biomedical Scientists
“Relationship between Cathepsin K and Total oxidative state in diabetes mellitus Iraqi Women patients with osteoporosis
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Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them. Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 normal healthy f

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Rutting Prediction of Asphalt Mixtures Containing Treated and Untreated Recycled Concrete Aggregate
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Rutting is a crucial element of the mechanical performance characteristics of asphalt mixtures, which was the primary target of this study. The task involved substituting various portions of virgin coarse aggregate with recycled concrete aggregate materials that had been treated or left untreated at rates ranging from 25 to 100%, with a constant increase of 25%. The treatment process of recycled concrete aggregate involved soaking in acetic acid, followed by a mechanical process for a short time inside a Los Angeles machine without the balls. This research utilized two primary tests: the standard Marshall test to identify the optimal asphalt contents and the volumetric characteristics of asphalt mixtures. The other one w

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Study the Impact Behavior of the Prosthetic Lower Limb Lamination Materials Due to Low Velocity Impactor
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This work involves three parts ,  first part  is manufacturing different types of laminated below knee prosthetic socket materials with different classical laminated materials used in Baghdad center for prosthetic and orthotic (4perlon layers+2carbon fiber layer+4 perlon layers) , two suggested laminated materials(3perlon layers+2carbon fiber layer+3 perlon layers) and (3perlon layers+1carbon fiber layer+3 perlon layers) ) in order to choose perfect laminated socket . The second part tests (Impact test) the laminated materials specimens used in socket manufacturing in order to get the impact properties for each socket materials groups using an experimental rig designed especially for this purpose. The interface pressure between

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Publication Date
Mon Jan 15 2018
Journal Name
Pollution Research
STUDY THE EFFECT OF THE WAVES EMITTED FROM TOWERS COMMUNICATION IN SOME BIOLOGICAL STANDERDS FROM DIFFERENT REGIONS IN BAGHDAD
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The mobile phone has become one of the most important in our days. The effects of waves from mobile base station may cause health effects on human. The aim of this work was to study the effect of radiofrequency (RF) emitted from mobile base station on the hemoglobin (Hb), packed cell (PCV), white blood cells (WBC) and liver enzymes activity including glutamic oxaloacetic transaminase (GOT), glutamic pyruvie transaminase (GPT) and Alkaline phosphatase (ALP). In this study the people divided into control group who living away from mobile base station and experimental group who living near to the mobile base station. The present result found there is no significant differences (P<0.05) in the Hb and PCV, but there was a significant increases (

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
A Study of the Nutritional Behavior and Body Mass Indexes for Students of Age (17-25) Years In Baghdad, Iraq.
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The aim of this study was to assess the nutritional status for samples at the age of 17-15 years. These samples were taken from secondary schools and universities in Baghdad area, 123 of them were male and 261 were female. Data on weight, height and body mass index (BMI) were determined in each individual. Smaller sample of 215 individuals (male and female) from the original sample was taken in order to record their nutritional behavior and daily food intake during the 24 hours prior to the visit through personal meeting using special questionnaire. The results showed that the weight and the height were within the range of the people of neighboring Arab countries, who are in the same age. Beside 44.4- 55.95% of these samples were within t

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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