In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, we analyze the effect of unemployment on two of the main aspects of social life: social exclusion and life satisfaction. First, we predict unemployment rates using the Auto Regressive Integrated Moving Average (ARIMA) model and the results are further used in a linear regression model alongside social exclusion and life satisfaction data, thus obtaining the hybrid model. With the help of the point prediction method, we use the hybrid model to predict new values for the two aspects of social life for the upcoming three years and we analyze the results obtained in order to better understand their interconnection. The results suggest that unemployment has particularly adverse effects on the subjective perception of life satisfaction, furthermore increasing the social exclusion percentage.

The rapid proliferation of social media platforms has led to a remarkable increase of fake news dissemination, creating a significant challenge for the integrity of online information. To analyze this issue, this study aims to investigate the relationship between user characteristics and behaviors on social media platforms as a prequel for the development of effective fake news detection strategies. For that purpose, we examined open access datasets available for Romanian internet users and selected several internet usage activities which we analyzed in relation to key demographic characteristics that lead to establishing user profiles prone to manipulations. By understanding the underlying factors that contribute to the spread of fake news, we can design targeted interventions to mitigate its impact and promote a more informed and responsible online environment.

This paper aims to analyze the influence that certain social factors (education and area of residence) have on the most likely scenarios people encounter in their online activities. Among the possible scenarios of using the internet, based on everyday individuals’ activities, we selected seeking information about health, goods, and services, taking online courses, internet banking, and participating in social networks. Using data acquired from international databases over the 2002–2020 period, we proposed five hypotheses and applied a multilinear regression model to the data collected for four European countries, namely, Bulgaria, Greece, Romania, and Slovenia. We have analyzed the degree of confirmation for all five hypotheses. The results provided a better understanding of the influence of the above-mentioned factors on the considered scenarios, allowing stakeholders to define and propose specific development policies.

The rapid technological advancement has led to an increased amount of content and information which needs to be reliably analyzed and correlated in order to make accurate inferences. Data quality is a stringent issue when considering gaps or missing information and various imputation methods, algorithms or statistical techniques have been created to correct missing data. To this purpose we propose an imputation method using the Sliding Window Technique to help infer missing data from datasets, a method that is efficient in terms of accuracy and complexity. In order to illustrate the method, we present a case study that simulates a scenario in which a half-yearly dataset must be analyzed in relation to annual datasets. The obtained results are passed to a statistical descriptive analysis and the conclusions derived from the performed analysis suggest that the estimations are homogeneous enough.

The purpose of this article is to better understand the behavior of the residual stresses in aluminium alloy plates by using mathematical modelling. Quenching of aluminium alloy plates causes an uneven temperature variation in aluminum alloy plates, and elastic and elasto-plastic deformations occur inside the material. The latter causing the formation of deformations and residual stresses. The non-linear thermo-mechanical direct coupled analysis of the quenching process for a 6061 aluminium alloy plate was achieved by using ANSYS finite element software. The residual stresses due to solid thermal effects were determined by calculation of the Third principal stresses, the most negative or compressive. The developed mathematical model offers a support in the understanding the behavior of the residual stresses in aluminium alloy plates and a better control of them.