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Numerical Modeling of a Pile Group Subjected to Seismic Loading Using the Hypoplasticity Model
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Various simple and complicated models have been utilized to simulate the stress-strain behavior of the soil. These models are used in Finite Element Modeling (FEM) for geotechnical engineering applications and analysis of dynamic soil-structure interaction problems. These models either can't adequately describe some features, such as the strain-softening of dense sand, or they require several parameters that are difficult to gather by conventional laboratory testing. Furthermore, soils are not completely linearly elastic and perfectly plastic for the whole range of loads. Soil behavior is quite difficult to comprehend and exhibits a variety of behaviors under various circumstances. As a result, a more realistic constitutive model is needed, one that can represent the key aspects of soil behavior using simple parameters. In this regard, the powerful hypoplasticity model is suggested in this paper. It is classified as a non-linear model in which the stress increment is stated in a tonsorial form as a function of strain increment, actual stress, and void ratio. Eight material characteristics are needed for the hypoplastic model. The hypoplastic model has a unique way to keep the state variables and material parameters separated. Because of this property, the model can implement the behavior of soil under a variety of stresses and densities while using the same set of material properties.

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

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Publication Date
Thu Dec 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The design of a proposed model for the application of the insurance policy for medical errors
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The aim of this study is to design a proposed model for a document to insure the mistakes of the medical profession in estimating the compensation for medical errors. The medical profession is an honest profession aimed primarily at serving human and human beings. In this case, the doctor may be subject to error and error , And the research has adopted the descriptive approach and the research reached several conclusions, the most prominent of which is no one to bear the responsibility of medical error, although the responsibility shared and the doctor contributes to them, doctors do not deal with patients according to their educational level and cultural and there are some doctors do not inform patients The absence of a document to insu

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Numerical Simulation for Cylindrical Electrostatic Precipitator: Effect of the Applied Voltage
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Coaxial (wire-cylinder) electrodes arrangements are widely used for electrostatic deposition of dust particles in flue gases, when a high voltage is applied to electrodes immersed in air and provide a strongly non-uniform electric field. The efficiency of electrostatic filters mainly depends on the value of the applied voltage and the distribution of the electric field. In this work, a two-dimensional computer simulation was constructed to study the effect of different applied voltages (20, 22, 25, 26, 28, 30 kV) on the inner electrode and their effect on the efficiency of the electrostatic precipitator. Finite Element Method (FEM) and COMSOL Multiphysics software were used to simulate the cross section of a wire cylinder. The results sh

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Publication Date
Tue Jul 21 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Numerical Study of the Heat Transfer Behavior in Helical Microcoil Tube
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Publication Date
Mon Apr 18 2022
The modeling techniques of the second‐order correlation function <i>g</i> <sup>(2)</sup> ( <i>τ</i> ) for a quantum emitter
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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Epidemiological, Clinical, and immunological characteristics of Mycoplasma pneumonia infections among a group of hospitalized children in Suleimani city/Iraq
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Background: Mycoplasma pneumoniae (M. pneumoniae) is an important respiratory bacterial pathogen, especially among children. It causes acute upper and lower respiratory infections.Objective: This study was aimed to measure anti- M. pneumoniae antibodies among hospitalized children who were admitted to hospital diagnosed with acute respiratory tract infections.Method: Automated ELISA technique was performed to detect anti- M. pneumoniae antibodies (IgM and IgG antibodies) in serum from 108 children less than 5 years old. The children were admitted to the Pediatric Teaching Hospital in Suleimani city/Kurdistan Region/Iraq because of acute respiratory tract infections. A questionnaire was designed to collect demographic and clinical data fr

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Scopus (14)
Scopus
Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Scopus (14)
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