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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 Jan 01 2017
Journal Name
Journal Of Engineering
Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Electrochemical harvesting of Chlorella sp.: Electrolyte concentration and interelectrode distance
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Two modes of electrochemical harvesting for microalgae were investigated in the current work. A sacrificial anode (aluminum) was used to study the electrocoagulation-flotation process, and a nonsacrificial anode (graphite) was used to investigate the electroflotation process. The study inspected the effect of chloride ions concentration and the interelectrode distance on the performance of the electrochemical harvesting processes. The results demonstrated that both electrodes achieved maximum harvesting efficiency with a 2 g/L NaCl concentration. Interestingly, by increasing the NaCl concentration to 5 g/L, the harvesting efficiency reduced dramatically to its lowest value. Generally, the energy consumption decreased with increasing

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
A Characterization of Maximal Outerplanar-Open Distance Pattern Uniform Graphs
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Let A ⊆ V(H) of any graph H, every node w of H be labeled using a set of numbers; , where d(w,v) denotes the distance between node w and the node v in H, known as its open A-distance pattern. A graph H is known as the open distance-pattern uniform (odpu)-graph, if there is a nonempty subset A ⊆V(H) together with  is the same for all . Here  is known as the open distance pattern uniform (odpu-) labeling of the graph H and A is known as an odpu-set of H. The minimum cardinality of vertices in any odpu-set of H, if it exists, will be known as the odpu-number of the graph H. This article gives a characterization of maximal outerplanar-odpu graphs. Also, it establishes that the possible odpu-number of an odpu-maximal outerplanar graph i

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Teaching techniques due to the Brain-based learning theory among math teachers
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The purpose of the study is to identify the teaching techniques that mathematics' teachers use due to the Brain-based learning theory. The sample is composed of (90) teacher: (50) male, (40) female. The results have shown no significant differences between male and female responses' mean. Additionally, through the observation of author, he found a lack of using Brain-based learning techniques. Thus, the researcher recommend that it is necessary to involve teachers in remedial courses to enhance their ability to create a classroom that raise up brain-based learning skills.  

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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering &amp; Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Applied Engineering Research
A Proposed Method for Generating a Private Key Using Digital Color Image Features
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In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

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Publication Date
Thu Dec 30 2021
Journal Name
Al-kindy College Medical Journal
Palestinian Experience in Stage Four Pressure Ulcer
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Pressure ulcer (now called Pressure injury) happens when the bony prominence like the sacrum exposes to pressure for a long period and also can cause soft tissue injury. In order to prevent and cure pressure-induced wounds, continuous and attentive repositioning is necessary. Wound management begins with the identification and aggressive management of the modifiable factors, such as positioning, incontinence, spasticity, diet, devices, and medical comorbidity, which contribute to pressure injury formation. Initial interventions include washing, cleaning, and maintaining the surfaces of the wound. In certain cases, it may be sufficient to debride the non-viable or contaminated tissue; however, operational care in more severe cases

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Publication Date
Mon Mar 09 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
Sentiment Analysis of Twitter Users Using Deep Learning Models
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of International Dental And Medical Research
The effects of progesterone administration in mice during pregnancy on ovarian development and anogenital distance of the offspring
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Progesterone is highly used in pregnant women as therapeutic agent to maintain and support pregnancy. To explore the effects of progesterone usage allover gestation till 7days postnatally on mice offspring ovaries development and anogenital distance. Ten pregnant mice were equally divide into control group that was injected with sesame oil which is used as a solvent for progesterone and treated group that is daily intraperitoneally injected with progesterone (dissolved in sesame oil 1: 10) at dose 10.2 mg/kg (the equivalent human dose) all through gestation till7day postnatal then sacrificed and measuring the anogenital distance (the distance between anus and genital papilla). Histological slides were prepared, and Diameters of the ovary, p

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