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This research paper aims to develop a comprehensive tourism satellite account‐human resource module (TSA‐HRM) which can complement and enhance the analytical capacity provided by the TSA, allowing for a broader insight into tourism's role in the economy, especially that of Egypt.

The objectives have been achieved through reviewing the literature in the fields of tourism satellite account (TSA) and its handling of tourism employment. To answer the research questions, one strategy and one method associated with the qualitative approach are used. The strategy refers to the case study, while the method refers to participant observation. An in‐depth analysis of the TSA project in Egypt was performed using the Data Quality Assessment Framework (DQAF) introduced by the International Monetary Fund.

The results indicate that statistics on tourism‐related employment in Egypt are usually fragmented, difficult to compare and often lack quality, credibility and reliability. Thus Egypt is in need of a way to improve tourism labor market statistics. However, the process of assessment of the TSA project in Egypt shows that Egypt has good experience in implementing the TSA system. The application of the TSA in Egypt at this high level will create a new horizon for improving the quality of tourism employment statistics.

At the time of the research Egypt was in the process of constructing its first TSA, and this of course is considered one of the limitations. Since the introduction of TSA to the Egyptian tourism industry in 2009, the statistical system of tourism has made a considerable contribution to improve the quality of data, based on evaluating some of the DQAF criteria, but there are no results so far. The present situation caused the study to fall within the theoretical framework, without producing any statistics on tourism employment in Egypt according to the proposed TSA‐HRM.

The model proposed will provide detailed data about employment, labor or human resource issues related to tourism in the Egyptian economy, which provides a useful resource for planning policy and decision making.

Considering the research findings, the study developed a comprehensive quantitative (monetary and non‐monetary) and qualitative tourism human resources module of tourism satellite account to extend the analytical capacity of the TSA as well as trace most issues relevant to the tourism labor market in Egypt.

The aim of this paper is to evaluate the effect of surface treatment on slurry erosion behavior of AISI 5,117 steel using artificial neural network (ANN) technique.

The slurry erosion wear behavior of electroless nickel-phosphorus (Ni-P) coated, carburized and untreated AISI 5,117 alloy steel was investigated experimentally and theoretically using ANN technique based on error back propagation learning algorithm.

From the obtained results, it can be concluded that the proposed AAN model can be successfully used for evaluating slurry erosion behavior of the Ni-P coated, carburized and untreated AISI 5,117 steel for wide range of operating conditions and Ni-P coating and carburizing improve the slurry erosion resistance of AISI 5,117 steel; however, the coating is more efficient.

Slurry erosion is a serious problem for the performance, reliability and service life of engineering components used in many industrial applications. To improve the performance of these components, engineering surface technologies have been attracting a great deal of attention. The extent of slurry erosion is dependent on a wide range of variables. To account all variables that effect on erosion behavior, prediction of erosion behavior by soft computational technique is one of the most important requirements. ANN has the ability to tackle the problem of complex relationships among variables that cannot be accomplished by traditional analytical methods.