This study deals with a methodology for increasing the efficiency of dynamic process calculations in elastic elements of complex engineering constructions. We studied the complex dynamic processes in a simple engineering construction, a mechanical system of an elastic body–continuous flow of homogeneous medium. The developed methodology is based on the use of a priori information on some of the vibrations forms, the construction of a “simplified” mathematical model of system dynamics, and the obtaining of an analytical relationship that describe the overall range of factors on the elastic vibrations of system. The methodology is used for cases of complex vibrations of elastic bodies, and the obtained results can serve as a basis for choosing the main technological and operational parameters of elastic elements of mechanisms and machines that perform complex vibrations. The results obtained in this work are the basis for calculating the blast effect on the elements of protective structures in order to increase their protective capacity by improving the method of their attachment or by using additional reinforcement, buff load effects on the elements of drilling strings and dynamic processes that occur during surface strengthening by work hardening in order to avoid resonance phenomena, and technological processes of vibration displacement or vibration separation of granular media.

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Fact-checking and journalists professional standards usually are considered to be the best fail-safe against manipulations in media. However, we found that newsmakers are able to manipulate even the audience of so-called ‘high-quality media’ who practice all mentioned approaches. To prove this we have refined the concept of ‘pseudo-event’, introduced by D.J. Boorstin, by defining the term ‘fake newsworthy event’ as an event created by newsmakers, that is high-profile and attractive for media, but the only or particular aim of these actions is an agenda-setting, and this aim is not obvious from the origin of the action. Namely, the member of parliament may file some bill realizing that it cannot be adopted and trying just to shape the public opinion. Or some person may claim against a celebrity or businessman having no chance to win at trial. On the example of Ukrainian ‘high-quality media’ we showed that journalists usually do not take into account whether some topics are launched just for manipulating agenda-setting. To prove that we gathered the data about publications focused on such topics in Ukrainian ‘high-quality media’, we provided their discourse analysis, and compared the result with experts’ evaluations of ‘media quality’ and ‘artificiality rate’ of the topic. We have not found correlations between ‘artificiality’ of the topic and the number of publications. Recommendations were elaborated for the media workers if they want to avoid this type of manipulation.

Cohort analysis is a new practical method for e-commerce customers’ research, trends in their behavior, and experience during the COVID-19 crisis. The purpose of the research is to validate the efficiency of this method on the e-commerce records data set and find out the critical factors associated with customer awareness and loyalty levels. The cohort analysis features engineering, descriptive statistics, and exploratory data analysis are the main methods used to reach the study purpose. The research results showed that cohort analysis could answer various business questions and successfully solve real-world problems in e-commerce customer research. It could be extended to analyze user satisfaction with a platform’s technical performance and used for infrastructure monitoring. Obtained insights on e-commerce customers’ awareness and loyalty levels show the likeliness of a user to make a purchase or interact with the platform. Key e-business aspects from a customer point of view are analyzed and augment the user-experience understanding to strengthen customers’ relationships in e-commerce.

The Covid-19 crisis lockdown caused rapid transformation to remote working/learning modes and the need for e-commerce-, web-education-related projects development, and maintenance. However, an increase in internet traffic has a direct impact on infrastructure and software performance. We study the problem of accurate and quick web-project infrastructure issues/bottleneck/overload identification. The research aims to achieve and ensure the reliability and availability of a commerce/educational web project by providing system observability and Site Reliability Engineering (SRE) methods. In this research, we propose methods for technical condition assessment by applying the correlation of user-engagement score and Service Level Indicators (SLIs)/Service Level Objectives (SLOs)/Service Level Agreements (SLAs) measurements to identify user satisfaction types along with the infrastructure state. Our solution helps to improve content quality and, mainly, detect abnormal system behavior and poor infrastructure conditions. A straightforward interpretation of potential performance bottlenecks and vulnerabilities is achieved with the developed contingency table and correlation matrix for that purpose. We identify big data and system logs and metrics as the central sources that have performance issues during web-project usage. Throughout the analysis of an educational platform dataset, we found the main features of web-project content that have high user-engagement and provide value to services’ customers. According to our study, the usage and correlation of SLOs/SLAs with other critical metrics, such as user satisfaction or engagement improves early indication of potential system issues and avoids having users face them. These findings correspond to the concepts of SRE that focus on maintaining high service availability.