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

The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag

Aim: To learn more about Oral Lichen Planus Iraqi patients, including their background information, symptoms, and prognosis. Materials and Methods: From the Oral and Maxillofacial Pathology Department, College of Dentistry, Baghdad University, we retrospectively reviewed the medical records of 68 patients with a histologically confirmed clinical diagnosis of oral lichen planus and subsequently contacted the patients by phone to evaluate their prognosis. Results: Females were more likely than males to experience severe pain; the reticular form of Oral Lichen Planus was the most prevalent at 38.2%, but the erosive type was more prevalent among females. Only 53 of 68 patients responded to phone calls. More than 37% of those respondents reporte

Background: Human semen contains high concentrations of fructose, zinc (Zn) and copper (Cu) in bound and ionic forms for Zn and Cu. The presence of abnormal levels of fructose and those trace elements may affect spermatogenesis with regard to production, maturation, motility and fertilizing capacity of the spermatozoa.Objective: To evaluate the levels of fructose, Zn and Cu in seminal plasma in different groups of male infertility and to correlate their concentrations with various sperm parameters.Methods: The concentrations of fructose, Zn and Cu were measured in 114 semen samples from normozoospermic, oligozoospermic, astheno-zoospermic, and azoospermic men using the electrothermal-atomic absorption spectrometry for Zn and Cu determinatio

This study presents a linguistic analysis of how Russian and American mainstream media and official statements deployed speech acts of accusation during the 2022 Russian invasion of Ukraine. Using Speech Act Theory (Austin, 1962; Searle, 1976) as the framework. The study analyzes 50 texts of English-language official statements and media headlines from both sides. In this research utterances are categorized into assertives, expressives, directives, commissives, and declarations, and analyzes their pragmatic force in shaping narratives. The analysis reveals contrasts in tone and rhetorical strategy: U.S. officials and media overwhelmingly use assertive accusations and expressive condemnations to morally indict Russia, while Russian counterpa

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

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