Robust Speed Control of a Three Phase Induction Motor Using Support Vector Regression

The Three Phase Induction Motor (TIM) is one of the most widely used motors due to its low price, robustness, low maintenance cost, and high efficiency. In this paper, a Support Vector Regression (SVR) based controller for TIM speed control using Indirect Vector Control (IVC) is presented. The IVC method is more frequently used because it enables better speed control of the TIM with higher dynamic performance. Artificial Neural Network (ANN) controllers have been widely used for TIM speed control for several reasons such as their ability to successfully train without prior knowledge of the mathematical model, their learning ability, and their fast implementation speed. The SVR-based controller overcomes the drawbacks of the ANN-based controller, i.e. its low accuracy, overfitting, and poor generalization ability. The speed response under the proposed controller is faster in terms of rising and settling time. The dynamic speed response of the proposed controller is also superior to that of the ANN-PI controller. The performance of the proposed controller was compared for TIM speed control with an ANN-PI controller via simulations in SIMULINK.

Anti-Phishing Awareness Delivery Methods

Phishing attacks are increasingly exploited by cybercriminals, they become more sophisticated and evade detection even by advanced technical countermeasures. With cybercriminals resorting to more sophisticated phishing techniques, strategies, and different channels such as social networks, phishing is becoming a hard problem to solve. Therefore, the main objective for any anti-phishing solution is to minimize phishing success and its consequences through complementary means to advanced technical countermeasures. Specifically, phishing threats cannot be controlled by technical controls alone, thus it is imperative to complement cybersecurity programs with cybersecurity awareness programs to successfully fight against phishing attacks. This paper provides a review of the delivery methods of cybersecurity training programs used to enhance personnel security awareness and behavior in terms of phishing threats. Although there are a wide variety of educational intervention methods against phishing, the differences between the cybersecurity awareness delivery methods are not always clear. To this end, we present a review of the most common methods of workforce cybersecurity training methods in order for them to be able to protect themselves from phishing threats.

Evaluating the Performance Parameters of Cryptographic Algorithms for IOT-based Devices

Nowadays, terabytes of digital data are generated and sent online every second. However, securing this extent of information has always been a challenging task. Cryptography is a fundamental method for securing data, as it makes data unintelligible for attackers, offering privacy to authorized clients. Different cryptographic algorithms have different speeds and costs that make them suitable for different applications. For instance, banking applications need outrageous security amenities, as they utilize superior algorithms having greater requirements, while gaming applications focus more on speed and cost reduction. Consequently, cryptographic algorithms are chosen based on a client's prerequisites. This study compared DES, AES, Blowfish, and RSA, examining their speed, cost, and performance, and discussed their adequacy for use in wireless sensor networks and peer-to-peer communication.

Numerical Investigation of Oil Gas Separation with the Use of VOF CFD

In this research paper, a numerical study regarding gas-oil separation is presented. Employing the geometry of a classic separator used by the NRDI for Gas Turbines COMOTI and a Computer-Aided Design (CAD) software, the computational domain was defined. To perform the Computational Fluid Dynamics (CFD) investigation, the mesh was created with the ANSYS Meshing tool, and the ANSYS CFX was employed as a solver. The computational domain was split into 5 subdomains, 3 were fluid and 2 were defined as porous media. The volume porosity, loss model, and permeability were set up. In terms of turbulence flow, the standard k–ε model was adopted. The results of the numerical calculations in terms of oil volume fraction and streamline profiles were used to analyze the separator configuration. The results show that the numerical investigation with the VOF (Volume of Fluid Method) - CFD model is capable of analyzing the performance of a two-phase separator equipped with two demisters-porous media.

Design and Analysis of a Dual Rotor Multiphase Brushless DC Motor for its Application in Electric Vehicles

The main objective of this paper is to study the effect of phase numbers in the dual rotor Brushless DC (BLDC) motor for its application in Electric Vehicles (EVs). The performance of two novel 5-, and 7-phase dual rotor BLDC motors is compared against the standard 3-phase dual rotor BLDC motor. The proposed motors combine the positive characteristics of multiphase BLDC motor and the dual rotor BLDC motor thus achieving better fault tolerance capability, high power density, and less per phase stator current. Finite Element Method (FEM) was used to design the 3-, 5-, and 7-phase dual-rotor BLDC motors. The design parameters and operating conditions are kept the same for a fair comparison. The stator current and torque performance of the proposed motors were obtained with FEM simulation and were compared with the standard 3-phase dual rotor BLDC motor. It is possible to use low power rating power electronics switches for the proposed motor. The simulation results also validate low torque ripples and high-power density in the proposed motors. Finally, the fault analysis of the designed motors shows that the fault tolerance capability increases as the phase number increases.

Chaos Control and Stabilization of a PID Controlled Buck Converter Using the Spotted Hyena Optimizer

The voltage controlled buck converter by constant-frequency pulse-width modulation in continuous conduction mode gives rise to a variety of nonlinear behaviors depending on the circuit parameters values, which complicate their analysis and control. In this paper, a description of the DC/DC buck converter and an overview of some of its chaotic dynamics is presented. A solution based on the optimized PID controller is suggested to eliminate the observed nonlinear phenomena and to enhance the dynamics of the converter. The parameters of the controller are optimized with the Spotted Hyena Optimizer (SHO) which uses the sum of the error between the reference voltage and the output voltage as well as the error between the values of the inductor current in every switch opening instant to determine the fitness of each solution. The simulations results in MATLAB proved the efficiency of the proposed solution.

Efficiency Assessment of a Signalized Roundabout and a Traffic Intersection in Baghdad City

In Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundabout is better than the signalized intersection but experiences high delay, and low LOS. Therefore, alternatives are proposed to improve the performance for current and future traffic volumes with low-medium delays.

Investigation of a Digital Hydraulic Valve Operated by Servo Motors

This paper describes a new type of digital hydraulic valve run by two servo motors. Digital hydraulics is a cutting-edge technology, which saves more exhausted energy than conventional hydraulic valves. It includes conventional valves, but its working principle is different. Similar or different size valves constitute a digital hydraulic valve assembly. When the assigned valves are opened, a certain amount of flow is obtained from the output of the valve assembly. To control a digital hydraulic valve, Pulse Number Modulation (PNM) Control technique is used for equal valve flow rates, while Pulse Code Modulation (PCM) is used for different valve flow rates. Valves are exerted by independently launched electric coils. Previous studies used controller board and external power booster circuits for coils. In this study, a new type of digital hydraulic valve is designed, manufactured, and tested with the PNM method. The studied valve body has two different valve groups. Every group includes 16 equal valves and 1 camshaft rotated by 1 servo motor. The servo motors are controlled by a PLC. The calculated performance index is found to be 5.1ms which is similar to the results of previous studies. The experimental results showed that the cam and servo motor controlled digital hydraulics is applicable to variable speed control hydraulic systems.

Removal of Multiplicative Gamma Noise from Images via SRAD Model Amelioration

In this paper, an improved Speckle Reducing Anisotropic Diffusion (SRAD), destined to remove multiplicative gamma noise applied to different images is proposed. The basic idea is to divide the image into several riddled areas and then calculate the Equivalent Number of Look (ENL) of each region. The largest value of the ENL is the best optimal homogeneous region of the image. This optimal choice allows us to solve the major problem of the SRAD algorithm articulated around a visual choice of the homogeneous region which is not satisfactory and causes non-uniformity in this area. To give more validity to the proposed method, several experimentations were conducted using different kinds of images and were approved by some quantitative metrics like PSNR, SNR, VSNR, and SSIM. The computer simulation results confirm the efficiency of the proposed method which outperformances the classical SRAD method.

A Survey of the Application of Artifical Intellegence on COVID-19 Diagnosis and Prediction

The importance of classification algorithms has increased in recent years. Classification is a branch of supervised learning with the goal of predicting class labels categorical of new cases. Additionally, with Coronavirus (COVID-19) propagation since 2019, the world still faces a great challenge in defeating COVID-19 even with modern methods and technologies. This paper gives an overview of classification algorithms to provide the readers with an understanding of the concept of the state-of-the-art classification algorithms and their applications used in the COVID-19 diagnosis and detection. It also describes some of the research published on classification algorithms, the existing gaps in the research, and future research directions. This article encourages both academics and machine learning learners to further strengthen the basis of classification methods.