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bsj-973
ON NAIVE TAYLOR MODEL INTEGRATION METHOD
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Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an effective tool for reducing both the dependency problem and the wrapping effect. By construction, Taylor model methods appear particularly suitable for integrating nonlinear ODEs. In this paper, we analyze Taylor model based integration of ODEs and compare Taylor model with traditional enclosure methods for IVPs for ODEs. More advanced Taylor model integration methods are discussed in the algorithm (1). For clarity, we summarize the major steps of the naive Taylor model method as algorithm 1.

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Publication Date
Tue Jan 01 2019
Journal Name
Opcion, Año
The effect of the -Zahorik- model on acquiring grammatical concepts among students of the College of Administration and Economics/University of Baghdad
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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Xi'an University Of Architecture & Technology
The Effect of (Landa) Model on Acquiring Grammatical Concepts Upon His Request to the College of Administration and Economics University of Bagdad
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The current research aims to identify the impact of the (Landa) model on acquiring grammatical concepts among students of the College of Administration and Economics, University of Baghdad, and to achieve the research goal, the researcher has set the following hypotheses: There are no statistically significant differences at the level of significance (0.05) between the average degrees Students of the experimental group who studied the Arabic language according to the (Landa) model and the marks of the students of the control group who studied the same subject in the usual way in the post test, there are no statistically significant differences at the level of significance (0.05) in the average differences between the test scores before and

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Publication Date
Tue Jul 01 2025
Journal Name
Journal Of Studies In Humanities And Educational Sciences
The Effect of the Needham Constructivist Model on the Achievement of Third Year Biology Department Students in the Subject of Teaching Methods
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The current research aims to know the effect of Needham's constructivist model on the achievement of third-year students in the Life Sciences Department in the teaching methods subject. To achieve the research objectives, the experimental method was followed for the experimental and control groups with dimensional measurement of the achievement variable of the teaching methods subject. The research sample included (62) students in the third year of the Life Sciences Department, distributed into two equal groups in the variables (self-assessment of learning methods - chronological age in years - intelligence level - previous information). To measure the level of students' achievement, an achievement test was constructed consisting of (40) te

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Publication Date
Fri Sep 01 2017
Journal Name
Global Journal Of Pure And Applied Mathematics
Solution of Modified Kuznetsov Model with Mixed Therapy
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In this paper two modifications on Kuznetsov model namely on growth rate law and fractional cell kill term are given. Laplace Adomian decomposition method is used to get the solution (volume of the tumor) as a function of time .Stability analysis is applied. For lung cancer the tumor will continue in growing in spite of the treatment.

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Geological Journal
Geological Model for Mauddud Reservoir Khabaz Oil Field
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Mon Jun 22 2015
Journal Name
International Journal Of Industrial Management
Regression Factors of Small Businesses Performance: Conceptual Model
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This study represents an attempt to develop a model that demonstrates the relationship between HRM Practices, Governmental Support and Organizational performance of small businesses. Furthermore, this study assay to unfold the socalled “Black Box” to clarify the ambiguous relationship between HRM practices and organizational performance by considering the pathway of logical sequence influence. The model of this study consists two parts, the first part devoted to examining the causal relationships among HRM practices, employees’ outcomes, and organizational performance. The second part assesses the direct relationship between the governmental support and organizational performance. It is hypothesized that HRM practices positively influ

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Engineering Geology And Hydrogeology
Assessing Pullout Resistance of Earth Reinforced Embankment Model
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- The sandy soil with high gypsum content (usually referred to as gypseous soil) covers vast area in south, east, middle and west regions of Iraq, such soil possess a type of cohesive forces when attached with optimum amount of water, then compacted and allowed to cure, but losses its strength when flooded with water again. Much work on earth reinforcement was published which concentrate on the gain in bearing capacity in the reinforced layer using different types of cohesive or cohesion less soil and various types of reinforcement such as plastic, metal, grids, and synthetic textile. Little attention was paid to there enforce gypseous soil. The objective of this work is to study the interaction between such soil and reinforcement strips

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