The role of government in controlling currency in the market has been a topic of discussion for many year. The currency market is an essential aspects of international trade, as it provides a medium for exchange between different countries. The exchanges rates of different currencies fluctuate based on various factors such as economic stability, geopolitical events, and market demand. Governments play a vital role in controlling currency in the market through various measures such as monetary policies, foreign exchange controls, and interventions. This reports aims to examine the different ways in which government scan controls currency in the markets and the effectiveness of these methods. Additionally, we will compare the role of the government in controlling currency in the market in present times with that in ancient India and analyzes the role of governments in controlling currency in the market, including its impact on the global economy and the effectiveness of different measures used.

This research study aims to explore the views of educational leaders in relation to the educational policies developed in the educational community and their effectiveness. The sample of this study constitutes of 105 educational leaders of primary, secondary and post-secondary education from all geographical areas of Greece. From the statistical analyzes of the findings it emerged that educational leaders encourage the development and implementation of educational policies within the educational organization and more specifically they focus on the school policy for creating the school learning environment and to a lesser extent on school policy for teaching, which they evaluate as particularly effective for improving the development of the educational community.

Today and in the future, overhead cranes are and will continue to be an extremely important component in various industrial operations, especially in the context of Ukraine's reconstruction and integration into the European Economic Area. Currently, the approach to hoisting cranes as secondary machines designed to perform only auxiliary handling operations has changed. Modern cranes, especially special cranes, are increasingly being used to perform basic technological operations. An area that has long been a subject of interest is machines that can independently manage all crane operations and thus operate autonomously using end-to-end digitalisation.

The feed-forward neural network and the back propagation algorithm have been used to analyze the three process phases by detecting and classifying the fault. The artificial neural network (ANN) was trained and evaluated on multiple sets of field data from simulating faults at different fault scenarios (fault kinds and fault resistance) of 11 kV, 100 km in length. Empirical findings validate the effectiveness of this approach in precisely classifying faults on the transmission line. This method can be used to attain high fault classification accuracy.

The process of implementing Lean Management in organizations should be done as effectively as possible, using the adequate resources, and taking into account critical success factors. Additionally, the prior assessment of these factors by using some techniques could lead not only to better Lean Management (LM) implementations but also to soundly prioritize LM alternatives that the organization might have. Then, this research presents a methodology that will help decision-makers to choose the most adequate Multi Criteria Decision Aid (MCDA) technique to weight important critical success factors and ranking the possible LM implementation alternatives such as LM toolsets, LM thinking or LM transformations.