This study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo

Is the chemical industries of great importance for the economy of any country, through what is borne by these industries is an important part of the changes contained in the industrial output of transfer and, moreover, that these industries are overlaps and intricacies of sector-wide with the rest of the manufacturing sectors, with agriculture and services , through the offering of these industries produce Production requirements intervention such as chemical fertilizer used in the production of agricultural crops, in addition to the various areas for the use of phosphorus in the food industry, to the extent that it is difficult to find material Food preparation is not included i

Lean Six Sigma methodologies and Ergonomics principles are the main pillars of this work given their importance in the implementation of continuous improvement in assembly workstations design. When looking at the introduction of the Ergonomics that has been affected by the integration of the Lean and Six Sigma for improvements, it is necessary to understand why these methodologies belong to each other and how they can be handled in the industrial field. The aim of the work seeks towards the impact of analyzing the integration of the basics tools of Lean and Six Sigma that enhanced Ergonomics highlighted the importance of using the priority matrix in the selection of the priority criteria. Two models of a system based on

In many oil-recovery systems, relative permeabilities (kr) are essential flow factors that affect fluid dispersion and output from petroleum resources. Traditionally, taking rock samples from the reservoir and performing suitable laboratory studies is required to get these crucial reservoir properties. Despite the fact that kr is a function of fluid saturation, it is now well established that pore shape and distribution, absolute permeability, wettability, interfacial tension (IFT), and saturation history all influence kr values. These rock/fluid characteristics vary greatly from one reservoir region to the next, and it would be impossible to make kr measurements in all of them. The unsteady-state approach was used to calculate the relat

Electric vehicles are emerging as a sustainable alternative to conventional transportation. However, route planning in Internet of Vehicles environments remains challenging because conventional routing algorithms based on travel distance or time do not adequately consider electric vehicle-specific constraints. Existing routing strategies often overlook the combined effects of battery energy, traffic congestion, and charging requirements, resulting in inefficient routing decisions. This paper proposes an adaptive Energy, Congestion, and Charging-Aware Routing (ECCAR) protocol that uses energy-feasibility verification, cost-based charging-station selection, and route re-optimization for electric vehicles in Internet of Vehicles enviro