Using a regional evolutionary perspective and a cross-regional data panel for 278 European Union regions, this study investigates the relationship between regional digital development and labour market resilience. To address a fundamental concern of regional studies, it proposes an analytical framework that assesses digital disparities in the spatial context and provides a nuanced understanding of digital dimensions impacting labour market resilience. The primary labour market outcome, the employment rate, was evaluated to investigate the regional resilience in the Great Recession. A gradient boosting method was used to identify the digital predictors in different resilience stages and to articulate policy-relevant conclusions.

Although in 2012 the European Union (EU) has promoted energy efficiency in order to ensure a gradual 20% reduction of energy consumption by 2020, its targets related to energy efficiency have increased and extended to new time horizons. Therefore, in 2016, a new proposal for 2030 of energy efficiency target of 30% has been agreed. However, during the last years, even if the electricity consumption by households decreased in the EU-28, the largest expansion was recorded in Romania. Taking into account that the projected consumption peak is increasing and energy consumption management for residential activities is an important measure for energy efficiency improvement since its ratio from total consumption can be around 25–30%, in this paper, we propose an informatics solution that assists both electricity suppliers/grid operators and consumers. It includes three models for electricity consumption optimization, profiles, clustering and forecast. By this solution, the daily operation of appliances can be optimized and scheduled to minimize the consumption peak and reduce the stress on the grid. For optimization purpose, we propose three algorithms for shifting the operation of the programmable appliances from peak to off-peak hours. This approach enables the supplier to apply attractive time-of-use tariffs due to the fact that by flattening the consumption peak, it becomes more predictable, and thus improves the strategies on the electricity markets. According to the results of the optimization process, we compare the proposed algorithms emphasizing the benefits. For building consumption profiles, we develop a clustering algorithm based on self-organizing maps. By running the algorithm for three scenarios, well-delimited profiles are obtained. As for the consumption forecast, highly accurate feedforward artificial neural networks algorithm with backpropagation is implemented. Finally, we test these algorithms using several datasets showing their performance and integrate them into a web-service informatics solution as a prototype.

Sustainable energy consumption is a research area of a large interest in last years. New energy-efficient lighting technologies exist, which can significantly reduce household electricity consumption, but their adoption has been slow. A considerable number of international studies show that sustainable development scenarios will be realistic if they involve the human behavior. The paper provides a solution to integrate consumer behavior with techno-economic energy issues, inside a complex energy model. This approach aims to reduce the error, from the demand side of the energy model. Consumer behavior in energy consumption is described by using specific attributes of energy technologies, namely virtual technologies. The GAMS/TIMES/VEDA energy modelling software tool has been used to integrate the techno-economic energy specific data and consumer behavior, in order to achieve the research purposes. A sociological survey about Romanians’ behavior in energy consumption has been conducted and its results have been integrated in the energy based model, in form of virtual technologies. This approach, known as “Social MARKAL”, allows the analyst to evaluate the possible contribution of information campaigns in changing lighting consumers’ behavior and effect of technology switch. The model is developed for the period 2010-2026, and is implemented by using GAMS/TIMES/VEDA software platform. The results presented this paper focuses on the household lighting technologies

The goal of the paper is to present an architecture designed for mobile multimedia content adaptation, applied to the newest solutions for instruction and learning, generically named mobile learning or m-learning. The field of research is situated at the intersection of mobile tools and e-learning and the research has as a goal to provide the opportunity to access computer resources from any location and to adapt the multimedia content to the specific features of mobile devices, communication environment, userspsila preferences and userspsila knowledge. The systems developed based on the architecture proposed in this paper will be able to provide powerful facilities for searching and support for instruction effectiveness, for performances evaluation, are time and location independent. The technical solutions proposed follow to use the potential of mobile devices to become important tools in education field.