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Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.

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Publication Date
Wed Jan 26 2022
Journal Name
Bmc Public Health
Investigating the current environmental situation in the Middle East and North Africa (MENA) region during the third wave of COVID-19 pandemic: urban vs. rural context
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Abstract<sec> <title>Background

Coronavirus 2019 (COVID-19) pandemic led to a massive global socio-economic tragedy that has impacted the ecosystem. This paper aims to contextualize urban and rural environmental situations during the COVID-19 pandemic in the Middle East and North Africa (MENA) Region.

Results

An online survey was conducted, 6770 participants were included in the final analysis, and 64% were females. The majority of the participants were urban citizens (74%). Over 50% of the urban residents significantly (p

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Publication Date
Sat Oct 01 2016
Journal Name
I-manager’s Journal On Communication Engineering And Systems
SOLVING NETWORK CONGESTION PROBLEM BY QUALITY OF SERVICE ANALYSIS USING OPNET
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Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Sun May 15 2022
Journal Name
Al-kindy College Medical Journal
A serology conundrum – HIV infection in acute babesiosis infection could merely be a false positive result
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Babesiosis is a tick-borne disease caused by Babesia microti. We present a case of false positive HIV in the setting of confirmed babesiosis infection. An understanding that patients with babesiosis can have a false positive HIV test result is important in management decisions.

 

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Publication Date
Wed Jun 22 2005
Journal Name
مجلة الحقوق
جريمة الاتجار بالبشر كأحدى صور المستحدثة
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المستخلص جريمة الإتجار بالبشر تُعد من الجرائم المستحدثة التي نشأت نتيجة لعدد من التغيرات الاجتماعية والاقتصادية والتكنولوجية في عالمنا، هذه الجريمة تتسم بطبيعتها الخطيرة والمعقدة، حيث تستغل الإنسان كسلعة تُباع وتُشترى من اجل تحقيق مكاسب مالية غير مشروعة. تعد الجريمة الوجه الجديد للرق والعبودية الذي كان السمه المميزة للعصور الغابره، على الرغم من أن البشرية قد تمكنت من القضاء على العبودية إلا أنها عادت بش

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Publication Date
Fri Aug 28 2015
Journal Name
Al-khwarizmi Engineering Journal
wavelength division multiplexing passive optical network modelling using optical system simulator
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Wavelength Division Multiplexing Passive Optical Network modeling Using Optical System Simulator
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Abstract

Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The sim

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Publication Date
Tue Dec 31 2024
Journal Name
Indian Journal Of Clinical Biochemistry
Farnesoid X Receptor-Mediated Bile Acids Regulation in Cholestasis
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The main process, for the elimination of cholesterol from the human body, involves the alteration of cholesterol into bile acid (BA), by the liver. The farnesoid X receptor (FXR), a member of the nuclear receptor superfamily, is essential for the regulation of BA, glucose, and lipid metabolism. It is largely found in the liver, intestines, kidney, and adrenal glands, and to a smaller degree in the heart and adipose tissue. The binding locations, of the FXR, are in close proximity to formerly undisclosed target genes, with distinctive activities associated with transcriptional regulators, autophagy, apoptosis, hypoxia, inflammation, RNA processing, and a number of cellular signaling pathways. The preservation of BA homeostasis, by the FXR, e

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