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Intellectual and Religious Characteristics Andalusion Societ Image Beni Al-Ahmar Era Poetry as a model
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The intellectual and religious characteristics were an influential presence in the same Andalusian poet, especially among the poets of Beni El-Ahmar because they are part of the heritage of poets, and that is to push them towards the glory of this heritage and to take care of it and benefit from its inclusion, inspiration and similarity.

That this inflection on the poetic heritage is justified by the poets of the sons of the Red were inclined to preserve the inherited values, especially as it was related to their poetry, especially that the Andalusian poet did not find embarrassment in the inspiration of heritage and emerged when he mentioned the homes and the ruins and the camel and the journey, although the community Andalusian society is also urban and the religious aspect has a strong correlation in the language of the Koran, which made the Andalusian poet revolves in the orbit of holiness because of his religious culture has led stories and stories played a prominent role in lighting the text of poetry and clarify to the recipient, was a quote from the Quranic texts, Many all that took place in and around the text based on those images portrayed by the poet and he drew from the cultural and religious covenantal. With reference recently to the sources and references that included everything related to the research and its course.

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Agile manufacturing assessment model using multi-grade evaluation
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In unpredicted industrial environment, being able to adapt quickly and effectively to the changing is key in gaining a competitive advantage in the global market. Agile manufacturing evolves new ways of running factories to react quickly and effectively to changing markets, driven by customized requirement. Agility in manufacturing can be successfully achieved via integration of information system, people, technologies, and business processes. This article presents the conceptual model of agility in three dimensions named: driving factor, enabling technologies and evaluation of agility in manufacturing system. The conceptual model was developed based on a review of the literature. Then, the paper demonstrates the agility

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Euro Dinar Trading Analysis Using WARIMA Hybrid Model
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The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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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 Jan 31 2020
Journal Name
Iraqi Geological Journal
GEOLOGICAL MODEL OF MAUDDUD FORMATION IN BADRA OILFIELD
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A 2D geological model for Mauddud Formation in the Badra oil field is built using Rockworks 16 software. Mauddud Formation produces oil from limestone units; it represents the main reservoir in the Badra oil field. Six wells (BD-1, BD-2, BD-4, BD-5, P-15, and P-19) are selected to build facies and petrophysical (Porosity and Water saturation) models. Wells data are taken from the core and cutting samples and studied through the microscopic. The petrophysical data (effective porosity and water saturation) are derived from computer processes interpretation results that are calculated by using Interactive Petrophysics software. The 2D models are built to illustrate the vertical and horizontal distribution of petrophysical properties between we

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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
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
Wed Jan 01 2020
Journal Name
Proceedings Of The 2020 2nd International Conference On Sustainable Manufacturing, Materials And Technologies
The food web prey-predator model with toxin
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