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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 results comparing with others. Computer simulation has been performed to study and verify the above mechanisms in the performance enhancement using the OPNET simulator.

Publication Date
Wed Sep 11 2024
Journal Name
Lecture Notes In Civil Engineering
An Image Processing Algorithm to Address the Problem of Stains Merge on Water Sensitive Papers and Its Impact on the Evaluation of Spray Quality Indicators
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There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-m

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
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 introduce

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Publication Date
Sat Mar 01 2014
Journal Name
Eeng. &tech.journal
Preparation and Characterization of High Quality SnO2 Films Grown by (HPCVD)
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ABSTRACT: In this research SnO2 thin films have been prepared by using hot plate atmospheric pressure chemical vapor deposition (HPCVD) on glass and Si (n-type) substrates at various temperatures. Optical properties have been measured by UV-VIS spectrophotometer, maximum transmittance about (94%) at 400 0C. Structure properties have been studied by using X-ray diffraction (XRD) , its shows that all films have a crystalline structure in nature and by increasing growth temperature from(350-500) 0C diffraction peaks becomes sharper and grain size has been change. Atomic force microscopy (AFM) uses to analyze the morphology of the Tine Oxides surface structure. Roughness & Root mean square for different temperature have been investigated. The r

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Future trends of the insurance sector in the integration of public insurance companies in Iraq And its impact on the quality of insurance service: Applied Study in the Iraqi General Insurance Company and the National Insurance Company
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     This study research to Showing The impact of the integration process on the quality of Insurance service and analyze the impact financially to determine whether there is any impact on the quality of the insurance service, in addition to identifying the obstacles that impede the merger between the insurance companies, insurance and the appropriate proposals for its' application and benefit from the benefits achieved.

The importance of The study lies in the fact that it is an important and vital spotlight that is becoming increasingly important in the world to confront the various difficulties and crises that have occurred  recently in light of the liberalization of international trade, globalization a

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Sat Jan 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
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AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

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Publication Date
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The efficiency of cluster analysis to analyzing medical image of Covid-19 patient by using K-means algorithm
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