Autorías: Muhammad Hamza Shihab, Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2022. Artículo de Revista en Dialnet.

The current research aims to identify the level of both psychological comfort and job performance among a sample of high school teachers for the academic year (2019-2020). The researcher has built two tools to measure psychological comfort, and one to measure job performance. The researcher applied the two scales to a random stratified sample of (100) male and female teachers. The results showed a low level of feeling with psychological comfort among secondary school teachers and a good level of sense of job performance. There is no statistically significant difference in the level of psychological comfort according to gender. There is a significant difference in psychological comfort according to the variable of the length of service in

University libraries seek to evaluate their performance in order to correct their path and adjust it in the right direction. Therefore, they use (performance indicators), which are a tool used by institutions to evaluate the weaknesses and strengths in their work and the reasons for failure to achieve some goals sometimes. They convert (goals, procedures and actions) into a formula that can be measured mathematically, which contributes to the library determining the gap between its current performance and what those libraries are supposed to be on, clarifying the path that the library is following, controlling the risks that may befall it, and thus enhancing the process of continuous improvement to avoid areas of failure and weakness becaus

Taguchi experimental design (TED) is applied to find the optimum effectiveness of aqueous Red Pomegranate Peel (RPP) extract as a green inhibitor for the corrosion of mild steel in 2M H₃PO₄ solution. The Taguchi methodology has been used to study the effects of changing, temperature, RPP concentration and contact period, at three levels. Weight-loss measurements were designed by construction a L₉ orthogonal arrangement of experiments.   Results of the efficiencies of inhibition were embraced for the signal to noise proportion & investigation of variance (ANOVA).  The results were further processed with a MINITAB-17 software package to find the optimal condition

An experimental program was conducted to determine the residual of composite Steel Beams-Reinforced Concrete (SB-RC) deck floors fabricated from a rolled steel beam topped with a reinforced concrete slab, exposed to high temperatures (fire flame) of 300, 500, and 700ºC for 1 hour, and then allowed to cool down by leaving them in the lab condition to return to the ambient temperature. The burning results showed that, by exposing them to a fire flame of up to 300ºC, no serious permanent deflection occurred. It was also noticed that the specimen recovered 93% of 19.2 mm of the deflection caused by burning. The recovered deflection of burned composite SB-RC deck floor at 500ºC was 40% of 77.9 mm of the deflection caused by burning with a res

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables