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The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.</p>
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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Disorder Activity of Some Enzymes Plays an Important Role in Pathological Mechanism of Rheumatoid Arthritis Disease
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The aim of this research to show the role of some enzymes in pathological mechanism of rheumatoid arthritis (RA) disease. Sixty patients with RA and matched number of apparently healthy volunteers were included in the study. Spectrophotometric methods were used to determine Peroxy nitrite (ONOO), Nitric oxide (NO), Nitric oxide synthase activity (NOS) cycloxygenase-2 activity (COX-2), glutathione peroxidase (GPX) activity and superoxide dismutase (SOD) activity in serum of both groups. Colorimetric assay kits were used to determine Iron. Rheumatoid factor (RF) was determined using Imuno-Latex kit. ONOO, NO levels, and NOS activity were significantly higher in the patients compared to the control group. Conversely, Iron level, SOD

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
Detecting and Monitoring the Vegetal Cover of Karbala Province (Iraq) Using Change Detection Methods
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Karbala province was one of the most important areas in Iraq and considered an
economic resource of vegetation such as trees of fruits, sieve and other vegetation.
This research aimed to utilize change detection for investigating the current
vegetation cover at last three decay. The main objectives of this research are collect
a group of studied area (Karbala province) satellite images in sequence time for
the same area, these image captured by Landsat (TM 1995, ETM+ 2005 and
Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such as atmosphere
correction and rectification has been done. Mosaic model between the parts of
studied area was performing. Gap filling consider being very important step has
be

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Publication Date
Wed Nov 01 2023
Journal Name
Clinical Epidemiology And Global Health
The association of interleukin-10 single nucleotide polymorphisms (rs1800871) and serum levels in Iraqi patients with celiac disease: A case-control study
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Publication Date
Mon Apr 01 2019
Journal Name
Iraqi Journal Of Biotechnology
The Promising Anti-Tumor Impact of Newcastle Disease Virus Expressing IL-2 and P53 Genes in Many Cancer Cell Lines In vitro
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Abstract: Recombinant Newcastle disease virus (rNDV) has shown an anticancer effect in preclinical studies, but has never been tested in a lung cancer models. In this study we explored the anticancer activity of genetically modified NDV expressing IL-2-P53 (rClone30–IL-2-P53) in lung cancer model. We have cloned IL-2 and P53 genes and inserted them in the viral genome of New Castle Disease Virus to create a genetically modified rNDV- IL-2-P53 virus and tested the anti-tumor activity of the new virus in vitro on different types of cancer cell lines by MTT assay. TheIL-2 and P53 gene were successfully cloned and inserted into the viral genome by using a Mlu I and Sfi I endonucleases, viral vector was constructed correctly and successf

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Hybrid CNN-SMOTE-BGMM Deep Learning Framework for Network Intrusion Detection using Unbalanced Dataset
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This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Preliminary Assessment of the Soil Foundation Characteristics Utilizing the 2D Resistivity Imaging and Down-Hole Seismic Refraction Techniques: A Case Study in Tenth of Ramadan City, Egypt
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      Two-dimensional electrical resistivity imaging and seismic refraction, in the form of down-hole survey, were applied to delineate the subsurface section and elastic moduli and identify geotechnical characteristics of subsurface materials in the 10th of Ramadan industrial area, Cairo, Egypt. The results of four 2-D profiles of electrical resistivity, in the form of dipole–dipole and Wenner configurations, revealed that the subsurface section contains two main geo-electrical layers; the first is made of sand, some silt, and gravels, reflecting low resistivity values ranging from 25 to 65.5 ohm m. This layer is overlying a high resistivity layer (65.5 to135 ohm m), corresponding to medium to coars

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Two Domain Flow Method for Leachate Prediction Through Municipal Solid Waste Layers in Al–Amari Landfill Site
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Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

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Publication Date
Tue Feb 11 2025
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
BER performance enhancement for secure wireless communication systems based on chaotic-MIMO techniques
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The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi

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Publication Date
Sat Dec 01 2012
Journal Name
2012 International Conference On Radar, Communication And Computing (icrcc)
BER performance improvement for secure wireless communication systems based on CSK- STBC techniques
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There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

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