Autoría: Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.

He research specifies subjects which may contribute in improve productivity of the General Company for vegetable oil product/ Al-Farab factory and aims to release the relationship between system Quick Response Manufacturing (QRM) and scheduling operations.

The Implementation was in the general company for vegetable oil product (Al-Farab factory), Universe Factory It suffers from a failure to follow Scheduling in its operations And not taking into account the lead times And delays in product delivery dates, Here are drawing the attention of the administration in the factory to use Quick Response Manufacturing (QRM) to control the energy and inventory, machin

The study aims to achieve several objectives, including follow-up scientific developments and transformations in the modern concepts of the Holistic Manufacturing System for the purpose of identifying the methods of switching to the entrances of artificial intelligence, and clarifying the mechanism of operation of the genetic algorithm under the Holonic Manufacturing System, to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines Using the Holistic Manufacturing System method and the Genetic algorithm, which allows for optimal maintenance time and minimizing the total cost, which in turn enables the workers of these machines to control the vacations in th

The current study aims to examine the level of problems faced by university students in distance learning, in addition to identify the differences in these problems in terms of the availability of internet services, gender, college, GPA, interactions, academic cohort, and family economic status. The study sample consisted of (3172) students (57.3% females). The researchers developed a questionnaire with (32) items to measure distance learning problems in four areas: Psychological (9 items), academic (10 items), technological (7 items), and study environment (6 items). The responses are scored on a (5) point Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree). Means, standard deviations, and Multivariate Analysis of Vari

Using zooplankton as bioindicators, this study evaluates the ecological condition of the Euphrates River in Iraq's Babylon Province. Site 1 (North Hillah, next to the old Babylon ruins), Site 2 (Hillah city center), Site 3 (South Hillah, close to Al-Mahaweel), and Site 4 (near Al-Kifl town) were the four monitoring locations chosen along the river. The highest and lowest averages of the measured physical and chemical factors indicate temperature (25.1°-29.4°), pH (7.2-7.9), electrical conductivity (EC) (940 µS/cm-1241µS/cm), total dissolved solids TDS (591 mg/L-789mg/L), dissolved oxygen (DO) (5.6 mg/ l-7.1 mg/L), biological oxygen demand (BOD5) (2.4mg/L-4.2 mg/L), nitrate (1.3 mg/L–3.2 mg/L), nitrite (0.04 mg/L–0.13 mg/L),

Semiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K