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Network Traffic Prediction Based on Time Series Modeling
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    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and (MAPE). The results showed the possibility of modeling the network traffic time series and that the performance of the linear regression model is the best compared to the rest of the models for both series.

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Analytical Modeling of Stresses in the Wall 0f the Human Heart
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The mechanical function of the heart is governed by the contractile properties of the cells, the mechanical stiffness of the muscle and connective tissue, and pressure and volume loading conditions on the organ. Although ventricular pressures and volumes are available for assessing the global pumping performance of the heart, the distribution of stress and strain that characterize regional ventricular function and change in cell biology must be known. The mechanics of the equatorial region of the left, ventricle was modeled by a thick-walled cylinder. The tangential (circumferential) stress, radial stress and longitudinal stress in the wall of the heart have been calculated. There are also significant torsional shear in the wall during b

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Publication Date
Wed Oct 20 2010
Journal Name
The International Journal Of Advanced Manufacturing Technology
Finite element modeling and simulation of proposed design magneto-rheological valve
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Magneto-rheological (MR) valve is one of the devices generally used to control the speed of Hydraulic actuator of MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. A mathematical model for the MR valve is developed and the simulation is carried out to evaluate the newly developed MR valve. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMMR). The model dimensions of MR valve, material properties are taken into account. The results of analysis are presented in terms of magnetic strength H and magnetic flux density B. The simulation results based on the proposed model indicate that the ef

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion
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Publication Date
Mon Apr 03 2023
Journal Name
Karbala International Journal Of Modern Science
Performance Estimation and System Modeling for Refractive Index Structure Constant Cn2
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Groundwater flow modeling and hydraulic assessment of Al-Ruhbah region, Iraq
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Abstract<p>Al-Ruhbah region is located in the southwest of Najaf Governorate. A numerical model was created to simulate groundwater flow and analyze the water quality of the groundwater, by developing a conceptual model within the groundwater modeling system software. Nineteen wells were used, 15 for pumping and four for observation. A three-dimensional model was built based on the cross-sections indicating the geologic layers of the study area, which were composed of five layers. When a distance of 1,000 m between the wells was adopted, 135 wells can be operated simultaneously. These wells were hypothetically operated at 6, 12, and 18 h intervals, with a discharge of 200, 430, and 650 m<j></j></p> ... Show More
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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Heterogeneously Catalyzed Esterification Reaction: Experimental and Modeling Using Langmuir- Hinshelwood Approach
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The esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Modeling of Monocrystalline PV Cell Considering Ambient Conditions in Baghdad City
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Abstract

 

The environmental conditions are important factors, because they affect both the efficiency of a photovoltaic module and the energy load. This research was carried out experimentally and modeling was done in MATLAB –Simulink by monitoring the variation in power output of the system with environmental conditions such as solar radiation, ambient temperature, wind speed, and humidity of Baghdad city. From the results, the ambient temperatures are inversely proportional to humidity and the output power performance of the system, while the wind speed is directly proportional with the output power performance of the system.  

 

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Modeling Of Digital Media In The Management Of Educational Performance In Morocco School’s
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Faced with the increasing opening of the education and training sector on the digital world, the actors of this sector are called to develop alongside the disciplinary and pedagogical skills other strategic and technological skills that allow to offer the adequate conditions to manage their establishments.
Today, the pedagogical director is called to master an important set of technical and technological tools and this for two complementary reasons, the first is the knowledge of educational and pedagogical and the second is innovation in managerial practices
Our intervention is part of a comparative approach in which we will verify the degree of use of technological tools by our population of directors (123) private and public
T

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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Exact and Near Pareto Optimal Solutions for Total Completion Time and Total Late Work Problem
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     In this paper, the bi-criteria machine scheduling problems (BMSP) are solved, where the discussed problem is represented by the sum of completion and the sum of late work times  simultaneously. In order to solve the suggested BMSP, some metaheurisitc methods are suggested which produce good results. The suggested local search methods are simulated annulling and bees algorithm. The results of the new metaheurisitc methods are compared with the complete enumeration method, which is considered an exact method, then compared results of the heuristics with each other to obtain the most efficient method.

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