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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
Wed Aug 25 2021
Journal Name
2021 7th International Conference On Contemporary Information Technology And Mathematics (iccitm)
Anomaly Detection in Flight Data Using the Naïve Bayes Classifier
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Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Combining Several Substitution Cipher Algorithms using Circular Queue Data Structure
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With the revolutionized expansion of the Internet, worldwide information increases the application of communication technology, and the rapid growth of significant data volume boosts the requirement to accomplish secure, robust, and confident techniques using various effective algorithms. Lots of algorithms and techniques are available for data security.  This paper presents a cryptosystem that combines several Substitution Cipher Algorithms along with the Circular queue data structure. The two different substitution techniques are; Homophonic Substitution Cipher and Polyalphabetic Substitution Cipher in which they merged in a single circular queue with four different keys for each of them, which produces eight different outputs for

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Scopus (13)
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Publication Date
Sun Oct 07 2012
Journal Name
Journal Of Educational And Psychological Researches
Core Thinking skills for the kindergarten children, according to some variables
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The study aimed at the following:

    Identify the differences in average scores core  thinking skills kindergarten children by variable sex (male - female), and by variable age (5.6 - 5.11).

To achieve this researcher adopted a standardized test of core thinking skills for the kindergarten children, which was built and standardization by the researcher Meyada Asaad Mussa 2012 . applied test on a sample of (814) ) boys and girls who were randomly chosen form,  from directorates of Baghdad Education Adoption of the proportional distribution.

    

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Aesthetic Levels in Shape Variables in Spectacular Films the Indian Film (Main Tera Hero) a Model: غسان محسن حمد
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The spectacular film is a type of feature films which has specific elements that contribute in increasing the aesthetics of the shape in its structure. The researcher started studying this type of films by researching the spectacular film concept, the history of its development, who are its most important stars and then tackling the Indian cinema represented by Bollywood, which is considered a school for this type of film. The researcher addressed the most important influential elements that entre in its production as well as studying these elements that contribute to building the shape including the configuration, movements of cameras, lenses, the lighting, colors, costumes etc. and what influence they have in forming a special aestheti

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Publication Date
Fri Oct 03 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced TEA Algorithm Performance using Affine Transformation and Chaotic Arnold Map
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In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Computer And Communications
Pathfinding in Strategy Games and Maze Solving Using A* Search Algorithm
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Publication Date
Fri May 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI images using region growing algorithm
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LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Engineering And Applied Sciences
Enhancing LSB algorithm against brute-force attack using ASCII mapping technique
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
CTJ: Input-Output Based Relation Combinatorial Testing Strategy Using Jaya Algorithm
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Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing

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