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A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
The importance of improved forests in Iraq and their impact on the economic and social future
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عانت الغابات في العراق قصوراً واضحاً في مجال إشباع حاجة السكان لمنتجاتها الرئيسية المتمثلة بالأخشاب ومنتجاتها الثانوية المتمثلة بالأغصان والأوراق والنباتات الطبيعية والحيوانات البرية ونواتجها الأخرى، مما يتطلب التفكير بمحاولة إيجاد سبل جديدة لحل هذه المشكلة الاقتصادية المرتبطة بعنصريها الحاجة للأخشاب والأموال المخصصة لتطويرها عموماً.

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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
Influence of design anode and cathode channel on (PEMFC) fuel cell performance
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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
The Energy Spectra and Heat Capacity of GaAs Gaussian Quantum Dot in an External Magnetic Field
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In this paper, a theoretical study of the energy spectra and the heat capacity of one electron quantum dot with Gaussian Confinement in an external magnetic field are presented. Using the exact diagonalization technique, the Hamiltonian of the Gaussian Quantum Dot (GQD) including the electron spin is solved. All the elements in the energy matrix are found in closed form. The eigenenergies of the electron were displayed as a function of magnetic field, Gaussian confinement potential depth and quantum dot size. Explanations to the behavior of the quantum dot heat capacity curve, as a function of external applied magnetic field and temperature, are presented.

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Publication Date
Wed Jul 15 2026
Journal Name
Wasit Journal Of Sports Sciences
The impact of the Needham model on learning the skills of dribbling and handling in football for students
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
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Abstract<p>In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.</p>
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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
  Positional Accuracy Assessment for Updating Authoritative Geospatial Datasets Based on Open Source Data and Remotely Sensed Images
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OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtain

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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Reflection of mergers and acquisitions in the stock returns and financial performance - An Empirical Study of major international companies to the pharmaceutical industry-
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Research aims to identify the immediate impact of the announcement of mergers in the stockholders and the feasibility of gain abnormal return and benefiting from  asymmetric information during the announcement that unite 30 days before the announcement of the merger, and announcement day, and 30 days after the announcement of the merger. It was the largest and most important mergers and acquisitions pick that occurred during the global financial crisis, specifically in health care/pharmaceutical industry, Pfizer and Wyeth merger with Novartis acquisition on Alcon. search has adopted three hypotheses: the first hypothesis that ((achieves the target company's shareholders positive abnormal return (or negative) during and befor

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Publication Date
Fri Oct 19 2018
Journal Name
Journal Of Economics And Administrative Sciences
THE IMPACT OF TRAINING BASED UPON MERITS IN IMPROVING THE EMPLOYEES PERFORMANCE AT THE JORDANIAN UNIVERSITY HOSPITALS Abstract
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The study aims to identify the impact of competency-based training in its dimensions (skills, cognitive abilities, attitudes, and attitudes) in improving the performance of employees (achievement, strategic thinking and problem solving) in Jordanian university hospitals.

The study based on analytical descriptive method. The study population consisted of the Jordanian University Hospitals, the University Hospital of Jordan and the King Abdullah Hospital, as applied study case. The sample of the study consists of all upper and middle administrative employees of these hospitals; questionnaire distributed all of them and the number of valid questionnaires for analysis were 182 questionnaire.

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