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jeasiq-2182
Solving Resource Allocation Model by Using Dynamic Optimization Technique for Al-Raji Group Companies for Soft Drinks and Juices
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In this paper, the problem of resource allocation at Al-Raji Company for soft drinks and juices was studied. The company produces several types of tasks to produce juices and soft drinks, which need machines to accomplish these tasks, as it has 6 machines that want to allocate to 4 different tasks to accomplish these tasks. The machines assigned to each task are subject to failure, as these machines are repaired to participate again in the production process. From past records of the company, the probability of failure machines at each task was calculated depending on company data information. Also, the time required for each machine to complete each task was recorded. The aim of this paper is to determine the minimum expected time for the completion of all the machines assigned to perform their tasks in the company by using the dynamic optimization technique over finite and infinite horizons. By comparing the results, it was found that the first and second tasks were better than the third and the fourth tasks because the first task and the second one had completed their tasks in a shorter period than the others, they took 1379.2 hours and 1379.3 respectively during  of horizons (stages), while the third task took 1379.4 hours and the fourth task 1379.5 hours. A careful analysis of the situation revealed that the time it takes for each machine to complete its tasks has been reduced, from appropriate planning and quick and effective maintenance can enhance the capacity of the machines and thus reduce time and effort, which contributes to reducing the company's costs and thus maximizing the production capability to increase the company's profits

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Publication Date
Tue Sep 15 2020
Journal Name
Al-academy
Forbidden Montage and the transition Technique in one-snapshot Movies 1917 Film- A model: محمد عبد الجبار كاظم-عذراء محمد حسن
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  Starting from the term (forbidden montage) initiated by the French critic (Andre Bazin) as a method of processing the movies that depend on (mise en scene) achieved by the action of the camera and its ability to photograph and employ the depth of the field, in addition to the possibility of free movement without interruption in the filming environment in order to avoid montage as much as possible (the montage that distorts focus and distracts attention and moves away from realism, which is the most important theoretical pillar of Bazin in photography). The pursuit was behind a cinema that depicts its topics in one integrated snapshot with all its details thus approximating reality without any interference of montage. Our study sta

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Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
Estimation of urban land price within holly cities by using integrated GIS-regression models: case study Al-Kufa city- Iraq
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        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
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In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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Publication Date
Sun Aug 23 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Development Accounting Rule disclosure by accounting policies in the light of Islamic and electronic banking Activities: Proposal pattern
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the bank sect for any country  is very important  because  its represent a major  nerve   to feed a verity economic and finance activities .development any state measure by development  banking  sets and its represent  important  factor to investors attract . and because  important  of this subject ,teen accounting rule is a specialized for it .its related by  Disclosures in the Financial Statements Of Banks and The Similar Institutions, its accredit  by auditing and accounting standard  consul in republic of Iraq.in date 10/28/1998.                      &

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating Quality of Control Policies and Procedures for Banking Transactions Using the Non-application Gap Model to Enhance Financial Reporting Requirements Applied Study in an Iraqi Private Bank
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The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatements. The researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is

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Publication Date
Tue Sep 01 2026
Journal Name
Sustainable Engineering And Innovation
Material cost reduction using cutting optimization Pro5 and enhanced N-BEATS deep learning forecasting: a case study
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Manufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Comparing the Sequential Nonlinear least squared Method and Sequential robust M method to estimate the parameters of Two Dimensional sinusoidal signal model:
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Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

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Publication Date
Mon Jun 21 2021
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
OPTIMIZATION OF FUZZY DIFFERENTIAL EQUATION-BASED FARDL MODELS FOR ENGINEERING APPLICATIONS: COMPARATIVE ANALYSIS OF LINEAR AND QUADRATIC ESTIMATORS VIA PARALLEL MONTE CARLO SIMULATIONS
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Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Electronics,computer Networking And Applied Mathematics
Comparison of Some Estimator Methods of Regression Mixed Model for the Multilinearity Problem and High – Dimensional Data
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In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

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