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COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduced forecasting procedures into Artificial Neural Network models compared with regression model. Data collected from Al –Kindy Teaching Hospital from the period of 28/5/2019 to 28/7/2019 show an energetic part in forecasting. Forecasting of a disease can be done founded on several parameters such as the age, gender, number of daily infections, number of patient with other disease and number of death . Though, forecasting procedures arise with their private data of tests. This study chats these tests and also offers a set of commendations for the persons who are presently hostile the global COVID-19 disease.

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Health Sciences
Molecular assessment of some cardiovascular genetic risk factors among Iraqi patients with ischemic heart diseases
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Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Risk-Based Inspection Due to Corrosion Consequences for Oil and Gas Flowline: A Review
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   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli

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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Comparison of Sizes of Zinc Oxide Nanoparticles Extracted from Staphylococcus lugdunensis and Berberis vulgaris Plant Extract Against Some Types of Bacteria and Yeast
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Staphylococcus lugdunensis, isolation between 12.5 to 1.8% routine works may be a possible peroral route of infective endocarditis and found in the oral cavity by examined using saliva. Similar supragingival plaque isolation was observed. The increased bacteria resistance to antibiotics multiple have led to novel methods for resistance bacteria; antimicrobial agents are well known (ZnO NPs) by biological method and are lower toxicity and biology safety ZnNOPs activity by plant extraction and less toxicity as well as bio-safe. The nanoparticle was synthesized by biological method (Green) by barberry (Berberis vulgaris) extract. In this study using (WAD) method using different concentrations between (128, 64, 32, and 16) mg/mL of ZnO NPs, The

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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Comparison of Sizes of Zinc Oxide Nanoparticles Extracted from Staphylococcus lugdunensis and Berberis vulgaris Plant Extract Against Some Types of Bacteria and Yeast
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Staphylococcus lugdunensis, isolation between 12.5 to 1.8% routine works may be a possible peroral route of infective endocarditis and found in the oral cavity by examined using saliva. Similar supragingival plaque isolation was observed. The increased bacteria resistance to antibiotics multiple have led to novel methods for resistance bacteria; antimicrobial agents are well known (ZnO NPs) by biological method and are lower toxicity and biology safety ZnNOPs activity by plant extraction and less toxicity as well as bio-safe. The nanoparticle was synthesized by biological method (Green) by barberry (Berberis vulgaris) extract. In this study using (WAD) method using different concentrations between (128, 64, 32, and 16) mg/mL of ZnO

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Diabetes Mellitus as a Risk Factor for Pulmonary Tuberculosis
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Background: In the past, an association between Tuberculosis (TB) and Diabetes Mellitus (DM) was widely accepted, today the potential public health and clinical importance of this relationship seems to be largely ignored. The national clinical and policy guidance in the UK on the central of TB, for example, does not consider the relationship with DM.Objectives: To determine the risk of association between diabetes mellitus and pulmonary TB.Methods: A retrospective study conducted in Ibn Zuhr hospital for chest diseases from Jan 2008 – sep 2010 , included in the study 402 patients with TB divided into diabetic & non diabetic, 96 (23.8%) were diabetic while other 306 were TB not diabetic.Results: Risk of TB among DM patients were cle

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Publication Date
Thu Mar 01 2018
Journal Name
2018 Tenth International Conference On Advanced Computational Intelligence (icaci)
On high-level control of power-augmentation lower extremity exoskeletons: Human walking intention
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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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