The purpose of this paper is to preparing exercises for using the (Blazepod) device for advanced basketball players, and then identifying the effect of using the (Blazepod) device in developing some of the player's defensive movement for advanced basketball players. 12 players from the Adhamiya Sports Club, the category of applicants for the 2022/2023 sports year, where they were chosen in a deliberate manner from the community of origin represented by clubs, and the researchers used the defender player's movement test, and the results of the study showed that the special exercises prepared by the researcher using the (Blazepod) device affected the development Defensive skills (the movement of the defending player) greatly increased among a

Abstract The surface of kaolin was diagnosed by an AFM and the results were shown The height of the highest peak reached by a quantity of Kaolin ‎surface is 2.5 µm, the granules, and their diameter with an average diameter of 666.1nm. Using Kaolin's adsorption properties, erythrosine was removed of its aqueous solution. It was determined that the maximal dye adsorption ranged 36.53–40.61%. ‎‎‎‎The results of using the Freundlich, Langmuir, and Temkin adsorption isotherms revealed that at temperatures of (298,308,318) K, the Freundlich model was followed, the Langmuir model did not match, and the Temkin model could only be partially applied. There is also physical adsorption. One of the three kinetic models of the

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

In this paper investigate the influences of dissolved CO₂/H₂S gases, crude oil velocity and temperature on the rate of corrosion of crude oil transmission pipelines of Maysan oil fields southern Iraq. The Potentiostatic corrosion test technique was conducted into two types of carbon steel pipeline (materials API 5L X60 and API 5L X80). The computer software ECE electronic corrosion engineer was used to predict the influences of CO₂ partial pressure, the composition of crude oil, flow velocity of crude oil and percentage of material elements of carbon steel on the rate of corrosion. As a result, the carbon steel API 5L X80 indicates good and appropriate resistance to corrosion compared to carbon steel API

Autorías: Hadeer Idan Ghanim, Ishraq Mahmood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2021. Artículo de Revista en Dialnet.