The protection, safety and security (PSS) of complex objectives have become managerial subjects for aspects such as guarantee, growth and development. These aspects are marked by intrinsic and extrinsic factors. The present paper approaches the analysis of the current state in the PSS field through a case study with reference to the situation of small modular reactor (SMR) investments, which officially entered the application agenda for the first time in Romania and in the European Union (EU). The main object of the research aims at the perception scale of integrated PSS, using the method of interviewing decision-makers and researching the factorial structure of the centrality items of PSS activities in SMRs. The central view of this article is to conceptually delimit integrated PSS, their operationalization to complex objectives, and, respectively, their management in the context of research on the analysis and development directions registered nationally and internationally in the field. Derived from this approach, we defined secondary objectives as follows: to highlight the achievements in the field that contribute to ensuring the functioning of complex industrial objectives; to characterize energy demands in the context of the increasing phenomenon of globalization, technological transfer and knowledge; and to establish the framework for evaluating integrated PSS that have a preventive, safe and feasible contribution in the new economy.

In a world undergoing continuous and accelerated digital transformation, Machine Learning (ML) is one of the most important technologies in the field of Artificial Intelligence that shapes the modern economy. ML plays a crucial role in economics, marketing, and beyond, transforming the way companies make decisions and optimize their processes. In economics, ML helps analyze large volumes of data to predict market trends, identify growth opportunities, and manage financial risks. In marketing, ML-based technologies allow for the personalization of consumer experiences through automated recommendations and targeted advertising, improving campaign efficiency and maximizing ROI (Return on Investment). Also, by analyzing customer behavior, companies can anticipate their needs and adjust strategies in real time. Thus, ML becomes an essential tool for adaptability and success in a dynamic economic environment. ML has also the ability to provide the most competitive solutions in many areas. This article presents the concept of ML, how ML can contribute to providing solutions in marketing, as well as an example of how to use ML in marketing using two specific classification algorithms and also a specific ML software. The paper contains six sections, namely Introduction, Literature review, ML and Marketing, Methodology, Results and discussions and finally a Conclusions section.