The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Abstract

   The aim of this research is to concentrate on the of knowledge management activities, initial activities: (Acquisition, Selection, Generation, Assimilation, Emission) knowledge, and support activities: (Measurement, Control, Coordination, Leadership) that is manipulate and controlling in achieving knowledge management cases in organization, that’s is leads to  knowledge chain model, then determining the level of membership for these activities to knowledge chain model in a sample of Iraqi organization pushed by knowledge (Universities). The research depends on check list for gaining the data required, theses check list designed by apparently  in diagnosing research dimensions and measurem

The meanings attributed to Female Genital Mutilation/Cutting (FGM/C) are shaped through complex negotiations within religious and socio-cultural frameworks, including those observed in Indonesia. Using a combined qualitative and quantitative (mixed methods)-ethnographic and survey approach, data from 109 students of religious tertiary institutions in East Kalimantan on their perspectives on FGM/C practices can be more comprehensively explored. The results of the study, which were analysed using the three principles of symbolic interactionism, showed that 72.5 per cent of religious college student families still practice FGM/C and 53.2 per cent stated that FGM/C practices are beneficial for women.  However, they are also willing, if

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

A prey-predator interaction model has been suggested in which the population of a predator consists of a two-stage structure. Modified Holling's disk equation is used to describe the consumption of the prey so that it involves the additional source of food for the predator. The fear function is imposed on prey. It is supposed that the prey exhibits anti-predator behavior and may kill the adult predator due to their struggle against predation. The proposed model is investigated for existence, uniqueness, and boundedness. After determining all feasible equilibrium points, the local stability analyses are performed. In addition, global stability analyses for this model using the Lyapunov method are investigated. The chance of occurrence of loc

This study aims to find out the effect of the mediator on scaffolding fourth yearstudent- teachers' teaching competencies and their self-efficacy. The present study combines scaffolding and self-efficacy by using a mediator on scaffolding students affects teaching competencies and selfefficacy and from the results of which the existence of student-teachers’ selfawareness was ensured as an effect of the same independent variable. The model affects their teaching competencies and led them to be aware of the needs of their pupils and themselves. 

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise