The optimal solution for unit commitment problem using binary hybrid grey wolf optimizer

The aim of this work is to solve the unit commitment (UC) problem in power systems by calculating minimum production cost for the power generation and finding the best distribution of the generation among the units (units scheduling) using binary grey wolf optimizer based on particle swarm optimization (BGWOPSO) algorithm. The minimum production cost calculating is based on using the quadratic programming method and represents the global solution that must be arriving by the BGWOPSO algorithm then appearing units status (on or off). The suggested method was applied on “39 bus IEEE test systems”, the simulation results show the effectiveness of the suggested method over other algorithms in terms of minimizing of production cost and suggesting excellent scheduling of units.

Median line-gram and its application in the fault diagnosis of rolling bearing

The level selection of frequency band division structure relies on previous information in most gram approaches that capture the optimal demodulation frequency band (ODFB). When an improper level is specified in these approaches, the fault characteristic information contained in the produced ODFB may be insufficient. This research proposes a unique approach termed median line-gram (MELgram) to tackle the level selection problem. To divide the frequency domain signal into a series of demodulation frequency bands, a spectrum median line segmentation model based on Akima interpolation is first created. The level and boundary of the segmentation model can be adaptively identified by this means. Second, the acquired frequency bands are quantized using the negative entropy index, and the ODFB is defined as the frequency band with the largest value. Third, the envelope spectrum is used to determine the ODFB characteristic frequency to pinpoint the bearing fault location. Finally, both simulation and experimental signal analysis are used to demonstrate the efficiency of the suggested method. Furthermore, the suggested method extracts more defect feature information from the ODFB than existing methods.

Scanning Hybrid Transaction Algorithm for Secure Financial Transactions

Identity theft is a frightening and often very serious concern to everyone. A novel risk-mitigation algorithm, the Hybrid Transaction Algorithm, is given in an effort to provide individuals with peace of mind (HTA). With the random codes, the proposed HTA aims to implement two-factor authentication. This kind of user authentication has been generally recognized, and many businesses have begun to employ it as a security feature. This may be used to identify people and provide a secure method of buying products online. The suggested method involves using mobile devices to log into card accounts using an application in order to examine the randomly generated code. This is then entered when required on an online retailer's website in order to verify the person making the transaction. This reduces the chance of an unauthorized user using someone else's details to make fraudulent transactions. Identity thieves cannot use stolen card information to make transactions unless they have a valid code. This, in turn, protects both the customer and the credit card companies, who may be financially affected. We give one case study to demonstrate the security of our methodology in order to better understand how it may safeguard someone from having a stolen credit card used. Keywords: Two-Factor Authentication; Hybrid Transaction Algorithm (HTA); AES Encryption; SHA–256.

Calculation DRM Station Coverage for Robustness Mode E

A method for calculating a DRM station coverage for the VHF bands is presented, based on the ITU-R P.1546-7 and ITU-R BS.1660-8 recommendations. It is shown that the results of covarage calculations and field measurements confirm the reliability of the suggested method.

TOWARDS WEBCAM-BASED FACE DIRECTION TRACKING TO DETECT LEARNERS' ATTENTION WITHIN ASYNCHRONOUS E-LEARNING ENVIRONMENT

Recently, as a consequence of COVID-19 pandemic, the delivery of education at most of the educational institutions depended mainly on e-learning. So, the researchers give more attention for both synchronous and asynchronous e-learning. Although from an economical perspective, asynchronous e-learning seems to be the best e-learning option for institutions, still one of the biggest challenges is how to keep learners motivated for the entire learning process. One of important motivational factors that drives the success of the learning process is the learner attention. Therefore, to retain the learners' attention during the asynchronous e-learning process, we need first to detect their loss of attention. Accordingly, more studies started to focus on detecting learners’ attention. However, those studies can't be widely used for attention detection within asynchronous e-learning environments, as the used approaches tend to be inaccurate, and complex for the design and maintain. In contrast, in this study, we explore the possibility to find a simple way that can be widely used to detect learners' attention within the asynchronous e-learning environments. Therefore, we used webcams which are available in almost every laptop, and computer vision tools to detect learners' attention by tracking their faces. Thereafter, we evaluated the accuracy of our suggested method, the result of this evaluation showed that our method is efficient.

Improved Image Analysis Method to Evaluate Tracking Property under Successive Flashover Based on Fractal Theory

Successive flashover would result in carbonized tracking on insulator surface and cause deterioration to the insulation. Thus, investigation of the tracking can be beneficial in understanding flashover characteristics during long-term operation. In this paper, DC flashover was operated on the insulator, and the image of tracking after successive discharge were captured. Improved differential box-counting method (IDBM) was applied to analyze these images based on fractal theory. Weighted item was suggested during the counting procedure for rectangle image with margin covered by cut-size box. Fractal dimension of the tracking was calculated according to the suggested method. It is claimed that the suggested method could estimate the discharge propagation property and deterioration characteristics on the insulator surface. Moreover, IDBM showed advantages in image pre-processing and deterioration property revealed compared to traditional box-counting method attributing to the consideration of color depth. This image analysis method shows universality in dealing with tracking image and could provide additional information to flashover voltage. This paper suggested a potential approach for the investigation of discharge mechanism and corresponding deterioration in future research.

The Numerical Investigation of Fractional-Order Zakharov–Kuznetsov Equations

In this article, a modified method called the Elzaki decomposition method has been applied to analyze time-fractional Zakharov–Kuznetsov equations. In this method, the Adomian decomposition technique and Elzaki transformation are combined. Two problems are investigated to show and validate the efficiency of the suggested method. It is also shown that the solutions achieved from the current producer are in good contact with the exact solutions to show with the help of graphs and table. It is observed that the suggested technique is to be reliable, efficient, and straightforward to implement for many related models of engineering and science.

Feature Extraction in Six Blocks to Detect and Recognize English Numbers

The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

Large eddy simulation of converging Richtmyer–Meshkov instability based on subgrid-scale dissipation similar method

This paper focuses on large eddy simulation of the Richtmyer–Meshkov instability (RMI) in spherical and cylindrical converging geometries with a Mach number [Formula: see text] based on subgrid-scale (SGS) dissipation similar method (SDSM). Based on the converging RMI problem, we obtain from a priori test and theoretical analysis that the suggested method can provide accurate structural correlation while ensuring the computational stability. Comparing the numerical simulation results with direct numerical simulation (DNS) and existing model in converging RMI problem, we could find that the suggested method overcomes some defects of the existing model, such as the Smagorinsky model cannot predict transition accurately and the helicity model can only predicts the quasi-two-dimensional flow precisely. It provides a beneficial tool for the research of converging RMI.