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A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines Grey Wolf Optimization (GWO) with Borderline-SMOTE. Particle Swarm Optimization (PSO) was used to select the most important features that provide the greatest amount of information for training the first layer, which was built using deep learning techniques, and linking them in a hybrid manner that combines a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) and the Attention mechanism. The proposed model was evaluated using two different types of datasets: the CICIOT2023 dataset, which is characterized by its large size and significant variation in the number of attacks, and the UNSW-NB15 dataset, which is characterized by its simplicity and less imbalance compared to the first dataset, to prepare and generalize the system across multiple environments. The proposed class showed binary classification results with an accuracy of 0.94, an Area Under the Curve (AUC) of 0.93, an optimized F1-score of 0.338, and a Matthews Correlation Coefficient (MCC) of 0.324 at the best threshold on the CICIoT2023 dataset. It also achieved an accuracy of approximately 0.96, an AUC of 0.985, and an MCC of over 0.82 on the UNSW-NB15 dataset. These results confirmed the construction of a strong and resilient layer, preparing the foundation for a robust hierarchical offside detection system.

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Engineering
Design and Implementation of a Generalized N-Digit Binary-To-Decimal Converter on an FPGA Seven-Segment Display Using Verilog Hdl Design and Implementation of a Generalized N-Digit Binary-To-Decimal Converter on an FPGA Seven-Segment Display Using Verilog Hdl
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It is often needed to have circuits that can display the decimal representation of a binary number and specifically in this paper on a 7-segment display. In this paper a circuit that can display the decimal equivalent of an n-bit binary number is designed and it’s behavior is described using Verilog Hardware Descriptive Language (HDL). This HDL program is then used to configure an FPGA to implement the designed circuit.

Publication Date
Sun Aug 01 2021
Journal Name
Sensors And Actuators B: Chemical
Sensitive and simple colorimetric methods for visual detection and quantitative determination of semicarbazide in flour products using colorimetric reagents
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After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

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Publication Date
Mon Jan 01 2024
Journal Name
Jordanian Journal Of Computers And Information Technology
BEYOND WORDS: HARNESSING SPEECH SOUND FOR SPEAKER AGE AND GENDER DETECTION USING 1D CNN ARCHITECTURE WITH SELF-ATTENTION MECHANISM
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Applied Engineering Science
Design and implementation of a smart home automation system based on global system for mobile communications
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Recently, there has been an increasing advancement in the communications technology, and due to the increment in using the cellphone applications in the diverse aspects of life, it became possible to automate home appliances, which is the desired goal from residences worldwide, since that provides lots of comfort by knowing that their appliances are working in their highest effi ciency whenever it is required without their knowledge, and it also allows them to control the devices when they are away from home, including turning them on or off whenever required. The design and implementation of this system is carried out by using the Global System of Mobile communications (GSM) technique to control the home appliances – In this work, an ele

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Genetic Algorithm Based PID Controller Design for a Precise Tracking of Two-Axis Piezoelectric Micropositioning Stage
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 In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Fri Sep 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
. Medical Image Compression using Hybrid Technique of Wavelet Transformation and Seed Selective Predictive Method
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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Scopus
Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
An Experimental Research on Design and Development Diversified Controllers for Tri-copter Stability Comparison
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Abstract<p>The drones have become the focus of researchers’ attention because they enter into many details of life. The Tri-copter was chosen because it combines the advantages of the quadcopter in stability and manoeuvrability quickly. In this paper, the nonlinear Tri-copter model is entirely derived and applied three controllers; Proportional-Integral-Derivative (PID), Fractional Order PID (FOPID), and Nonlinear PID (NLPID). The tuning process for the controllers’ parameters had been tuned by using the Grey Wolf Optimization (GWO) algorithm. Then the results obtained had been compared. Where the improvement rate for the Tri-copter model of the nonlinear controller (NLPID) if compared with </p> ... Show More
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Publication Date
Mon Mar 25 2019
Journal Name
Al-academy
Educational -Learning Design in the Achievement and Motivation of Students in the High School towards Art Education: كنعان غضبان حبيب
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  The present study aimed at ((building an educational -learning design based on the theory of Merrill in (CDT) and measuring the effectiveness of this design in the motivation and achievement of the high school fifth grade students to art education in the subject of the history of modern art)). The research community is made of fifth grade preparatory students in the secondary school of Umm Ayman in the Directorate of Education of Baghdad / Ar-Rusafa in a simple random way. The study sample (58 students) was chosen from section (e) to study according to Merrill theory (CDT) and section (d) to study according to the traditional way.
The pilot design of the control and experimental equivalent groups that have partial control in t

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