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Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was checked by comparing it's results with the results of six forecasting models developed for the same data by Al-Suhili and khanbilvardi, 2014.The check of the performance of the new developed model was made for three forecasted series for each variable, using the Akaike test which indicates that the developed model is more successful, since it gave the minimum (AIC) values for (91.67 %) of the forecasted series. This indicates that the developed model had improved the forecasting performance. For the rest of cases (8.33%), other models gave the lowest AIC value, however it is slightly lower than that given by the developed model. Moreover the t-test for monthly means comparison between the models indicates that the developed model has the highest percent of succeed (100%).

 

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Thermo-Rheological Investigation and Modeling of the Shear Viscosity of Polypropylene above the Melting Temperature
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The increasing use of polymeric materials in the daily life, leads to challenges in the processing industry to deliver high performance materials with affordable terms. However, new processing techniques lead to high costs. In order to reduce processing costs it is necessary to understand the non-Newtonian behavior of the polymers in their molten state to be able to simulate the processes before the construction of the plants starts. Here the shear thinning behavior of the viscosity of polymeric melts is essential. Thus, this paper deals with the experimental investigation of the thermo-rheological behavior of the viscosity of one of the most used polymers (Polypropylene) over a wide range of temperatures and shear rates.  Furthermo

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment
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Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Analysis Based on Well Logging Data for Tight Carbonate Reservoir: The SADI Formation Case in Halfaya Oil Field
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Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

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Publication Date
Mon Jan 01 2018
Journal Name
2018 Detroit, Michigan July 29 - August 1, 2018
Design and validation of an electronic data logging systems (CAN Bus) for monitoring machinery performance and management- Planting application
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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Sun Mar 15 2020
Journal Name
Al-academy
Formal Data of Bauhaus School and their Implications for Fabrics and Costumes Design: نور منصور خميس-وسن خليل ابراهيم
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The current research discusses the topic of the formal data within the methodological framework through defining the research problem, limits and objectives and defining the most important terms mentioned in this research. The theoretical framework in the first section addressed (the concept of the Bauhaus school, the philosophy of the Bauhaus school and the logical bases of this school). The second section dealt with (the most important elements and structural bases of the Bauhaus school) which are considered the most important formal data of this school and their implications on the fabrics and costumes design. The research came up with the most important indicators resulting from the theoretical framework.
Chapter three defined the

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Building discriminant function for repeated measurements data under compound symmetry (CS) covariance structure and applied in the health field
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Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

 

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Publication Date
Sun Sep 01 2013
Journal Name
2013 Ieee International Conference On Circuits And Systems (iccas)
Improved undetected error probability model for JTEC and JTEC-SQED coding schemes
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The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

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Publication Date
Fri May 18 2018
Journal Name
Thesis
The Arabian killifish (Aphanius dispar) as a novel model for mycophysiological studies.
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Abstract Candida albicans is a commensal fungal pathogen that grows in yeast and hyphal forms in the human gut. C. albicans causes mucosal and cutaneous diseases that can result in significant mortality following systematic infections and it also exhibits drug resistance. Zebrafish have been an excellent model to investigate C. albicans infections because of their transparency and the availability of many transgenic lines. However, there is a limitation in using zebrafish as a model because the fish embryos cannot survive at 37°C therefore it is not suitable for studying Candida infections at physiological relevant human body temperature. In this thesis, the normal embryonic development of Arabian killifish (A. dispar) is investigated, rev

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