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A Decision Tree-Aware Genetic Algorithm for Botnet Detection
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     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from the whole features set. Thus, it obtains efficient botnet detection results in terms of F-score, precision, detection rate, and  number of relevant features, when compared with DT alone.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
3-D Packing in Container using Teaching Learning Based Optimization Algorithm
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

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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 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 Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Image encryption algorithm based on the density and 6D logistic map
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One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are genera

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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Publication Date
Mon May 01 2017
Journal Name
2017 5th International Conference On Information And Communication Technology (icoic7)
Analysis of the number of ants in ant colony system algorithm
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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
The Value of Diffusion Weighted MRI in the Detection and Localization of Prostate Cancer among a Sample of Iraqi Patients
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Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

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Publication Date
Fri Feb 09 2024
Journal Name
Eximia
The reality of the moral climate and its relationship to the decision-making of boxing referees from the standpoint of coaches
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The purpose of this paper is to identifying the relationship between the moral climate and the decision-making of boxing referees from the standpoint of the coaches, and the research problem lies through the work of the researchers in training and managing the teams. It was noted that the role of the referees is one of the most important roles played by the workers to achieve the objectives of the federation, and that the moral climate that prevails among the administrative body the union and the referees on the one hand and between the referees and coaches on the other hand are among the factors of the success of everyone’s work and the survival and strengthening of confidence in their work and thus the continuity of success and

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Publication Date
Sat Aug 01 2026
Journal Name
Aip Conference Proceedings
Effects of an augmented motor reality–based training program on spatial awareness and skill-based decision making in youth basketball players
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New sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventi

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Effects of an augmented motor reality–based training program on spatial awareness and skill-based decision making in youth basketball players
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ew sports technologies have highlighted the importance of perceptual – cognitive training in order to optimize performance in sports e.g., dynamic team sport such as basketball. Augmented motor reality AMR is a new training model based on realistic movement combined with interactive virtual cues that may be useful to enhance spatial orientation and decision making. The purpose of this study was to investigate the effects of an AMR-based training program on spatial awareness and skill-based decision making in youth basketball players. Twenty-four male young basketball players aged 15.2±0.8 years were randomized to the experimental group n=12, receiving AMR training, and control group n=12, performing conventional practice. The interventio

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