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Philosophy of Precognitive Dream in the American Film (Minority Report - a Model)
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When we talk about the foresight in films, it is necessary to talk about dreams because foresight represents one of its distinct types. The Precognitive vision has become a possible material in dealing with as subjects in the film industry that adopt these ideas with their philosophical and scientific orientations, because they represent the imagination that predictors are specialized with. It can be invested through the introduction of a vision of another kind to achieve its goals and ambitions in the film industry and in particular the huge institutions of production as in Hollywood. The cinema works in the light of those concepts of production which found the prognostic dream (the foresight) as a distinctive genre in its films,
The research included the problem of research which was that the philosophy of foresight has distinctive characteristics worthy of attention and tracking from the precognitive vision in activating the elements of cinematic language and narrative to show the contents rooted from those ideas, hence the importance of the research came to confirm the intellectual necessities of the precognitive vision in the cinematic films reaching the objective of the research which is the disclosure of the content of foresight in the American film.
The theoretical framework included two sections the first of which dealt with the philosophical idea of insight, and the second dealt with the philosophy of insight in the American film in addition to the theoretical framework indicators.
The research procedures used the theoretical framework indicators as a tool for analysis through a film model that dealt with the issue of foresight in the film (Minority Report).
The results revealed that the film in showing the foresight is subject to what the human natural laws are subject to with the same dream vision. As far as the conclusions are concerned, the most important of which is that the level of foresight in seeing the details that are not possible in the reality made the predictor able to manage the events and with absolute freedom as a manufacturer, controller and participant in details difficult for others to control as it is a subjective authority. In the light of the results, the researcher recommends studying books on dreams in the literary field for the purpose of coming up with ideas for filmmaking.

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Publication Date
Sun Oct 06 2013
Journal Name
Journal Of Educational And Psychological Researches
Following model educational offenders in collection and Alasbaka of fifth grade students preparatory in history
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Following model educational offenders in collection and Alasbaka of fifth grade students preparatory in history A. M. Dr Prepared by: Dr. Bashaer Mawloud Tawfeeq, The Center of Educational and Psychological Studies Baghdad University - There is no difference statistically significant at the 0.05 level of significance between the average scores of the following students studying using model and offenders and who are studying in the usual manner (traditional) in the collection - There is no difference statistically significant at the 0.05 level of significance between the mean scores for the following students studying using model and offenders and who are studying in the usual manner (traditional) in retention Find limits: Current search

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Publication Date
Sun Mar 21 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of the reliability system in model of stress- strength according to distribution of inverse Rayleigh
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using system dynamics model and the statistical indicators for Road Map of "Green government departments" project In Iraq
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Abstract                                                         

The issue of the protection of the environment is a shared responsibility between several destinations and sectors, and constitutes a main subject in which they can achieve sustainable development. In the sectors of government programs can be set up towards the establishment of the government sector to the green environment, so to be the implementati

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Publication Date
Tue Oct 22 2024
Journal Name
Iraqi Statisticians Journal
Inferential Methods for the Dagum Regression Model
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The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

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Publication Date
Sat Dec 17 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Use of the Definite article in the Ottoman Turkish Language in the Fourteenth and Seventeenth Centuries: Qaboos Namah and Mazaki Collection as a Model: '' Kabusnâme ve Mezâkî Divanı Örneğinde ''14. ve 17. Yüzyılarda Osmanlı Türkçesinde Harf-i Ta'rifin Kullanması Üzerine Bir İnceleme
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The Turks used the Ottoman Turkish language from the thirteenth century to the twentieth century.  During this period and under the influence of Islamic civilization, a large number of words and structures were used from the Arabic and Persian languages, Therefore, many Arabic grammatical structures were used in the Ottoman Turkish language, such as the definite article simply because it was widely used.

The paper is concerned with the use of the Arabic definite article in the Ottoman Turkish language, and the aim of this contrastive study is to find out the similarities and differences between the two languages ​​in terms of meaning and structure. Since linguistic studies depend on the practical side or applied approach, two

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating the Scheff'e Model of the Mixture
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Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Mon Jul 10 2023
Journal Name
Journal Of Engineering
Bearing Capacity of a Strip Model Footing on Loose Sand Reinforced With Pomegranate Sticks Mat
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A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

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