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Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
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Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Borderline-SMOTE + Imbalanced Ratio(IR), Adaptive Synthetic Sampling (ADASYN) +IR) Algorithm, where the work these techniques are generate the synthetic samples for the minority class to achieve balance between minority and majority classes and then calculate the IR between classes of minority and majority. Experimental results show ImprovedSMOTE algorithm outperform the Borderline-SMOTE + IR and ADASYN + IR algorithms because it achieves a high balance between minority and majority classes.

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Publication Date
Thu May 28 2020
Journal Name
Iraqi Journal Of Science
Human Action Recognition Based on Bag-of-Words
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Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of featur

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Optimum Median Filter Based on Crow Optimization Algorithm
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          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Image Encryption Based on Intelligent Session Mask Keys
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The revolution of multimedia has been a driving force behind fast and secured data transmission techniques. The security of image information from unapproved access is imperative. Encryptions technique is used to transfer data, where each kind of data has its own special elements; thus various methods should to be used to conserve distributing the image. This paper produces image encryption improvements based on proposed an approach to generate efficient intelligent session (mask keys) based on investigates from the combination between robust feature for ECC algebra and construction level in Greedy Randomized Adaptive Search Procedure (GRASP) to produce durable symmetric session mask keys consist of ECC points. Symmetric behavior for ECC

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Short Answers Assessment Approach based on Semantic Network
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      Finding similarities in texts is important in many areas such as information retrieval, automated article scoring, and short answer categorization. Evaluating short answers is not an easy task due to differences in natural language. Methods for calculating the similarity between texts depend on semantic or grammatical aspects. This paper discusses a method for evaluating short answers using semantic networks to represent the typical (correct) answer and students' answers. The semantic network of nodes and relationships represents the text (answers). Moreover, grammatical aspects are found  by measuring the similarity of parts of speech between the answers. In addition, finding hierarchical relationships between nodes in netwo

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Identifying Digital Forensic Frameworks Based on Processes Models
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Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Ebonite linings Based on Natural and Synthetic Rubber
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 The corrosion of metals is of great economic importance. Estimates show that the quarter of the iron and the steel produced is destroyed in this way. Rubber lining has been used for severe corrosion protection because NR and certain synthetic rubbers have a basic resistance to the very corrosive chemicals particularly acids. The present work includes producing ebonite from both natural and synthetic rubbers ; therefore, the following materials were chosen to produce ebonite rubber: a) Natural rubber (NR). b) Styrene butadiene rubber (SBR). c) Nitrile rubber (NBR). d) Neoprene rubber (CR) [WRT]. The best ebonite vulcanizates are obtained in the presence of 30 Pphr sulfur, and carbon black as reinforcing filler. The relation between

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Telecom Churn Prediction based on Deep Learning Approach
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      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Association between Emotional Intelligence and Academic Adaptation among a Sample of Gifted Students in the Intermediate and Secondary Schools in Jeddah
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This study aims to examine the relationship between emotional intelligence and academic adaptation among a sample of gifted students in intermediate and high schools in Jeddah, Saudi Arabia. The study also seeks to examine the differences between group means in emotional intelligence and academic adaptation due to demographic variables (gender and school level). In addition, the study aims to examine the role of emotional intelligence in predicting the level of academic adaptation. The researcher performed the descriptive, correlational, predictive, and comparative approaches to collect the data from a sample comprised of (309) gifted students using the emotional intelligence scale developed by Bar-on (2000), whi

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
The Representaion of Algebraic Integers as Sum of Units over the Real Quadratic Fields: REPRESENTAION OF ALGEBRAIC INTEGERS AS SUM OF UNITS OVER THE REAL QUADRATIC FIELDS
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In this paper we generalize Jacobsons results by proving that any integer  in   is a square-free integer), belong to . All units of  are generated by the fundamental unit  having the forms

Our generalization build on using the conditions

This leads us to classify the real quadratic fields  into the sets  Jacobsons results shows that  and Sliwa confirm that  and  are the only real quadratic fields in .

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