The role of new technologies in tourism is changing rapidly, leading to the development of customer relationships through the use of virtual reality in the marketing of tourist destinations. In addition to focusing on the influence of travel intentions that has prevailed in practice so far, the use of VR is expected to have an impact on the travel experience on the spot. This exploratory research study was conducted with 824 respondents to identify the role of virtual reality in choosing a tourist destination, as well as the expectations of potential customers that could rekindle the tourism industry for a post-pandemic world. The results pointed out that highly used virtual reality applications for destination marketing aim to create a certain image for a tourist destination and to communicate this to the outside world in a consistent and coordinated manner. The findings also reinforce the importance of developing future scenarios for virtual reality as a decisive factor for strategic planning in the tourism sector.

Today, industrial robots are used in dangerous environments in all sectors, including the sustainable energy sector. Sensors and processors collect and transmit information and data from users as a result of the application of robot control systems and sensory feedback. This paper proposes that the estimation of a collaborative robot system’s performance can be achieved by evaluating the mobility of robots. Scenarios have been determined in which an autonomous system has been used for intervention in crisis situations due to fire. The experimental model consists of three autonomous vehicles, two of which are ground vehicles and the other is an aerial vehicle. The conclusion of the research described in this paper highlights the fact that the integration of robotic systems made up of autonomous vehicles working in unstructured environments is difficult and at present there is no unitary analytical model.

Today, terrestrial robots are used in a multitude of fields and for performing multiple missions. This paper introduces the novel development of a family of crawling terrestrial robots capable of changing very quickly depending on the missions they have to perform. The principle of novelty is the use of a load-bearing platform consisting of two independent propulsion systems. The operational platform, which handles the actual mission, is attached (plug and play) between the two crawler propulsion systems. The source of inspiration is the fact that there are a multitude of intervention robots in emergency situations, each independent of the other. In addition to these costs, there are also problems with the specialization of a very large number of staff. The present study focused on the realization of a simplified, modular model of the kinematics and dynamics of the crawler robot, so that it can be easily integrated, by adding or removing the calculation modules, into the software used. The designed model was integrated on a company controller, which allowed us to compare the results obtained by simulation with those obtained experimentally. We appreciate that the analyzed Explosive Ordnance Disposal (EOD) robot solution represents a premise for the development of a family of EOD robots that use the same carrier platform and to which a multitude of operational platforms should be attached, depending on the missions to be performed.

Digital marketing has given new life to healthcare services by enhancing their visibility in the online space. People choose online healthcare services because they can receive instant answers and communicate with specialists in their comfortable environment at the right time. The purpose of this study was to understand the impact of virtual communities on the intention to use telemedicine. The model is based on a combination of consumer desire (psychological objective) and loyalty through promotional formats (economic objective), as well as data collected from 442 respondents analyzed using structural equation modeling. The research results show that by analyzing target groups in social networks, content can be individualized, and an accurate measurement of e-patient satisfaction must be conducted in order to improve the experience of future consumers of telemedicine services. The results of this study explain what makes people want to use digital healthcare services and can serve as a guide for people who run virtual communities and help digital healthcare service providers figure out how to market their services.

This paper presents mathematical models to estimate the kinematics and dynamics of wheeled and tracked robots. The models account for the physical–mechanical characteristics of the ground, the influence of the center of gravity displacement on the cornering moment of resistance, and the influence of the interaction of the crawler with the roadway. The results of the models are characterized by defining computational relationships for a robot’s equations of motion, longitudinal forces, transverse forces, and resistive turning moments generated via longitudinal forces and transverse forces.

Researchers from different fields have studied the effects of the COVID-19 pandemic and published their results in peer-reviewed journals indexed in international databases such as Web of Science (WoS), Scopus, PubMed. Focusing on efficient methods for navigating the extensive literature on COVID-19 pandemic research, our study conducts a content analysis of the top 1000 cited papers in WoS that delve into the subject by using elements of natural language processing (NLP). Knowing that in WoS, a scientific paper is described by the group Paper = {Abstract, Keyword, Title}; we obtained via NLP methods the word dictionaries with their frequencies of use and the word cloud for the 100 most used words, and we investigated if there is a degree of similarity between the titles of the papers and their abstracts, respectively. Using the Python packages NLTK, TextBlob, VADER, we computed sentiment scores for paper titles and abstracts, analyzed the results, and then, using Azure Machine Learning-Sentiment analysis, extended the range of comparison of sentiment scores. Our proposed analysis method can be applied to any research topic or theme from papers, articles, or projects in various fields of specialization to create a minimal dictionary of terms based on frequency of use, with visual representation by word cloud. Complementing the content analysis in our research with sentiment and similarity analysis highlights the different or similar treatment of the topics addressed in the research, as well as the opinions and feelings conveyed by the authors in relation to the researched issue.