<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>
The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du
... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreReservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
... Show MoreObjective: The objectives of the present study were to evaluate the effectiveness of the instructional intervention
about medical and health knowledge of patients with diabetes mellitus type II.
Methodology: A Quasi- experimental study was carried out in National Center for Diabetes Mellitus/ Almustansria
University, started from 4th January 2012, to 1st April 2012. Non-probability (purposive sample) of (50) diabetes
mellitus type II, who visit National Center for Diabetes Mellitus/ Almustansria University. The study sample is
divided equally into (25) study and (25) control groups. The study group received the instructional intervention.
While the control not exposed to the instructional intervention. The data are coll
Coronary artery disease (CAD) is a major health concern and leading of death in individuals with type 2 diabetes mellitus (T2DM). Glutathione S – Transferase(GST) are known for their broad range of detoxification and in the metabolism of xenobiotics . The role of functional variants of these genes in the development of various disorder is proven. We investigated the possible role of these variants in the development of CAD in T2DM patients. In this case – control study a total of 60 patients (T2DM = 30 ; T2DM – CAD = 30) and 30 controls were included. Serum lipid profiles were measured and DNA was extracted from the blood samples. Multiplex PCR for GSTT1/M1 (present / null) polymorphism, were performed for genotyping of study pa
... Show MoreThis research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give
The massive growth of the automotive industry and the development of vehicles use lead to produce a huge amount of waste tire rubber. Rubber tires are non-biodegradable, resulting in environmental problems such as fire risks. In this search, the flexural behavior of steel fiber reinforced self-compacting concrete (SFRSCC) beams containing different percentages and sizes of waste tire rubbers were studied and compared them with the flexural behavior of SCC and SFRSCC. Micro steel fiber (straight type) with aspect ratio 65 was used in mixes. The replacement of coarse and fine aggregate was 20% and 10% with chip and crumb rubber. Also, the replacement of limestone dust and silica fume was 50%, 25%, and 12% with ground rubbe
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