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

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Adolescence important and sensitive stage in social terms, being a stage where learns teenager bear social responsibilities and composition of their ideas about family life, as well as it is the stage where the teenager looking to himself for an important place in the community to become independent socially people, so it highlights the role of Social Work to do better effort and I believe him in order to prepare for the adolescent stage of adolescence and help him overcome the problems so that makes it adapts to the society in which he lives

The Department of Art Education in the College of Fine Arts is one of the educational institutions that aims to prepare teachers specialized in teaching art education in secondary schools and other educational institutions, which forces those in charge of preparing the curricula for this section and developing it, taking into account the rapid scientific and technological development. And the subject (Music Appreciation) is one of the subjects taught for the third grades in Art Education departments, and through the exploratory study carried out by the researcher it became clear to him that the Faculties of Fine Arts agreed to define their educational objectives and outputs in the subject (Music Appreciation) in Art Education departments

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

In this work, porous silicon gas sensor hs been fabricated on n-type crystalline silicon (c-Si) wafers of (100) orientation denoted by n-PS using electrochemical etching (ECE) process at etching time 10 min and etching current density 40 mA/cm2. Deposition of the catalyst (Cu) is done by immersing porous silicon (PS) layer in solution consists of 3ml from (Cu) chloride with 4ml (HF) and 12ml (ethanol) and 1 ml (H2O2). The structural, morphological and gas sensing behavior of porous silicon has been studied. The formation of nanostructured silicon is confirmed by using X-ray diffraction (XRD) measurement as well as it shows the formation of an oxide silicon layer due to chemical reaction. Atomic force microscope for PS illustrates that the p