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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
Sat Apr 11 2009
Journal Name
Journal Of Kerbala University
Evaluation The Behaviour of Reinforced Loose Sand under Inclined Loading
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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Factors associated with Exacerbation of Myasthenia Gravis in a Group of Iraqi Patients
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Background: Myasthenia gravis is an autoimmune disease of the neuromuscular junction that results in fluctuating muscle weakness as well as significant fatigue. Disease exacerbation is a critical condition, and the predisposing factors for it need to be identified to improve preventive measures.

Objectives:  Our study aims to determine the predisposing factors for myasthenia gravis exacerbations in a group of Iraqi patients.

Subjects and Methods: A total number of 30 myasthenia gravis patients were admitted to the hospital with an exacerbation of their symptoms, determined as the development of functional disability, dysphagia, or respiratory fai

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
A Modified Fama-MacBeth Model based on the Single-Index Model
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The aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth.  Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment.  Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence in Analyzing Historical Documents: The Egyptian Libyan Border as a Model (1911–1951)
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
The Simulation Technique to Estimate the Parameters of Generalized Exponential Rayleigh Model
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     The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM),  and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used

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Publication Date
Wed Jul 22 2026
Journal Name
Journal Of Economics And Administrative Sciences
The effect of creating knowledge according to the model (Nonaka & Takeuchi, 1995) on organizational ambidexterity: A study on a sample of Iraqi private banks
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Purpose - This study relies on the descriptive and analytical approach through collecting and analyzing the necessary data, as this approach focuses on polling the opinions of the research sample and its directions, and aims to develop a model that studies the relationship between knowledge creation and organizational ambidexterity in Iraqi private banks and verifying its validity experimentally. Design / Methodology / Introduction - A survey was conducted through a questionnaire form to collect data from a sample of (113) managers in private commercial banks. In addition, this study used the AMOS program and the ready-to-use statistical program package (SPSS V.25) to test the proposed hypotheses of the theoretical model experimentally. Res

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Publication Date
Mon Oct 01 2018
Journal Name
Conference: First International Conference On Water Resources
Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

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Publication Date
Fri Sep 30 2016
Journal Name
Al-khwarizmi Engineering Journal
Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Parameters Affecting the Strength and Behavior of RC Dapped-End Beams: A Numerical Study
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The finite element method has been used in this paper to investigate the behavior of precast reinforced concrete dapped-ends beams (DEBs) numerically. A parametric investigation was performed on an experimental specimen tested by a previous researcher to show the effect of numerous parameters on the strength and behavior of RC dapped-end beams. Reinforcement details and steel arrangement, the influence of concrete compressive strength, the effect of inclined load, and the effect of support settlement on the strength of dapped-ends beams are examples of such parameters. The results revealed that the dapped-end reinforcement arrangement greatly affects the behavior of dapped end beam. The failure load decreases by 25% when

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Publication Date
Tue Oct 19 2021
Journal Name
Biochem
A Neuro-Fuzzy Technique for the Modeling of β-Glucosidase Activity from Agaricus bisporus
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This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

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