The article covers the systematic basis for the creation of new technological processes of corn harvesting machines. Modern corn-harvesting machines have reached certain thresholds according to their technological properties that most significantly affect the final production and economic indicators of planting corn for grain efficiency, still they do not meet modern requirements. The technological properties mentioned above are hardly adjusted for wide range of physical and mechanical properties of the plants and crop parameters. This situation is caused by new machine´s working parts being viewed by researchers and developers as complex technical systems not from the standpoint of general systems theory but in terms of the use of traditional knowledge of the laws of agricultural mechanics, thus not getting proper attention to their systematic coordination with working conditions. Based on this, the paper presents a structural scheme for the system “mechanized corn for grain harvesting”, key elements of which are: agricultural (А), engineering (В) and selectional (С) supply. Interconnection of the subsystem´s elements and their consistency determine the effectiveness of the whole process. Inconsistency of the links АВ and ВC is observed. The conceptual system “mechanized corn for grain harvesting” design relates to the field with clear NO-factors: incompleteness, uncertainty, inconsistency and lack of information for decision making, thus it is important to review tasks of conceptual design from the most general constructual standpoint. The method of describing systems at the conceptual level is suggested. This systematic representation of corn-harvesting machines allows to approach the task of their workflows modeling from the most general standpoint.

In this work, the level of influence of the posts published by famous people on social networks on the formation of the cryptocurrency exchange rate is investigated. Celebrities who are familiar with the financial industry, especially with the cryptocurrency market, or are somehow connected to a certain cryptocurrency, such as Elon Musk with Dogecoin, are chosen as experts whose influence through social media posts on cryptocurrency rates is examined. This research is conducted based on statistical analysis. Real cryptocurrency exchange rate forecasts for the selected time period and predicted ones for the same period, obtained using three algorithms, are utilized as a dataset. This paper uses methods such as statistical hypotheses regarding the significance of Spearman’s rank correlation coefficient and Pearson’s correlation. It is confirmed that the posts by famous people on social networks significantly affect the exchange rates of cryptocurrencies.