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BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation) using C#, followed by selecting the best N features used as input into four classifier algorithms evaluated using machine learning (WEKA); multilayerperceptron, JRip, IBK, and random forest. In BotDetectorFW, the thoughtful and diligent cleaning of the dataset within the preprocessing stage beside the normalization, binary clustering of its features, followed by the adapting of feature selection based on suitable feature distance techniques, and finalized by testing of selected classification algorithms. All together contributed in satisfying the high-performance metrics using fewer features number (8 features as a minimum) compared to and outperforms other methods found in the literature that adopted (10 features or higher) using the same dataset. Furthermore, the results and performance evaluation of BotDetectorFM shows a competitive impact in terms of classification accuracy (ACC), precision (Pr), recall (Rc), and f-measure (F1) metrics.</span></p>

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Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Mon Sep 30 2024
Journal Name
Modern Sport
Manufacturing an Innovative Device to Adjust the Distance between Female Fencing Players' Feet
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تم التطرق في هذا البحث الى دور الذكاء الاصطناعي والتكنولوجيا الحديثة في العملية التدريبية بما يخدم أهدافه والاستفادة منه من خلال المخرجات الجيدة، حيث ان توظيف التكنولوجيا في تدريب رياضة المبارزة يسهل العملية التدريبية على المدرب واللاعب ويساهم في تقليل الجهد المبذول والوقت المستغرق ، وهدفت الدراسة الى التعرف على تأثير الجهاز المصنع في ضبط المسافة بين القدمين لدى عينة البحث  ،استخدم المنهج التجريبي بت

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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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Publication Date
Sun Jun 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
Artistic Features Of Re-Writing The Novel "On The Eve, on The Eve" By YevgueniBobov: As an Example: Жанровые Особенности Ремейка (На Материале Романа Е. Попова «Накануне Накануне»)
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 The paper tackles two topics. The first is about the term "Ремейк" which is very common in contemporary Russian literature; it has counterparts such as " Обработка" and " Переделка", where these two may indicate any of the following meanings (remake, reformulate, rewrite, treatment, modification, change). It has been shown that this term does not have a stable definition. Also, the role of this term in literary studies has been mentioned along with how it has come to its peak of use in post-modern literature.

The second is that I have taken a sample of well-known works in Russian literature " On the Eve, On the Eve " by the contemporary Russian writer YevgueniBobov, and shown the effort of the writer

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Publication Date
Sat Jan 01 2022
Journal Name
Food Science And Technology
Study on herbicide residues in soybean processing based on UPLC-MS/MS detection
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Publication Date
Sat Nov 02 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators
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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Mathematics &amp; Computer Science
The Use of Gradient Based Features for Woven Fabric Images Classification
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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique
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Abstract<p>Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essent</p> ... Show More
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