This paper aims to summarize recent trends in the field of intelligent education and build on the research findings to propose a conceptual model of an intelligent educational environment (IEE) along with possible applications. A bibliometric analysis explores the recent trends to obtain insights into the current research directions. The concept of an IEE is introduced and correlated to other popular concepts in the educational field. Relevant user requirements for the IEE are defined and discussed. They serve as the basis for creating the conceptual model as a UML class diagram. The proposed model gives an overall picture of the relationships among the essential elements of the IEE and provides insights into its future development. Two possible applications are outlined: personalized teaching and learning and the assessment process. Any particular application of the model to build an IEE must consider all specific user requirements and add relevant details. The proposed conceptual model can be used to enhance the teaching–learning process and improve learners’ performance.

EU countries face two major challenges in the energy sector – the control of carbon emissions and the high dependence on imported primary energy sources. Both European Commission and national governments actively develop, update and upgrade strategies and plans for the energy sector. They aim to ensure the gradual reaching of consecutive targets for increasing the weight of Renewable Energies (RE) in the European primary energy mix. The selection of Renewable Energy investment projects in these sectors involves different groups of experts who have to consider the specifics of different countries, regions, and technologies. The Decision-making process becomes more complicated, as in addition to political goals it has to ensure the efficiency and competitiveness of European economies. Several conflicting objectives have to be balanced with complex social, economic, technological, and environmental factors. Our study explores the application of combined methods and evaluation techniques for improving the assessment and selection of prospective RE projects. We implement an innovative integration of the Analytical Hierarchy Process (AHP) for block criteria systematization combined with objective Shannon Entropy in the MOORA evaluation.

This paper presents a combined approach based on the Analytical Hierarchy Process(AHP) with criteria structured in blocks and objective weighting of criteria with Entropy for improving the methodology of Multi-Criteria Decision Making (MCDM) for selecting laptop computers. A structured approach allows optimizing the combination of professional experts ' opinions and objectivity of data-driven entropy methods. The hybrid method is applied on a real dataset of 11 evaluation criteria and 12 alternatives from 4 major manufacturers of personal computers (PC) with a simulation reflecting the needs of individual users and small education organizations under conditions of COVID-19.

The continuous progress of computing technologies increases the need for improved methods and tools for assessing the performance of information systems in terms of reliability, conformance, and quality of service. This paper presents an extension of Information Theory by introducing a novel hierarchy concept as a complement to the traditional entropy approach. The methodology adjustments are applied to a simulative numerical example for assessing the reliability of systems with different complexity and performance behavior.