International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Zeolite is widely applied in agriculture due to its high cation-exchange capacity, ability to improve soil fertility, and effectiveness as a slow-release carrier of nutrients. Inaddition, its porous structure allows it to retain and purify water, thereby enhancing soilmoisture balance and reducing nutrient leaching. The present study examines the influence of varying Zeolite concentrations in soil on the germination and subsequent growth dynamics of Cucumber (Cucumis sativus L.) seedlings. Experimental data were subjected to Correlation Analysis, Analysis of Variance (ANOVA), and Statistical Hypothesis testing in order to evaluate the relationship between Zeolite content and plant growth rate. The findings indicate statistically significant effects of Zeolite percentage on both germination and vegetative development, highlighting the potential of Zeolite as a soil amendment for improving Cucumber cultivation practices.

Using the method of binary logistic regression, the dependence of dichotomous variables on one or more, quantitative or qualitative independent variables is studied. In order to solve problems with binary dependent variables, binary choice model estimation methodologies, such as logistic regression (logit) and probit regression (probit), can be implemented. The logistic model is based on the logistic distribution, while the probit model is based on the normal distribution. In this paper the binary logistic regression methodology is applied for obtaining defect-free welds by electron beam welding process, based on experimental data.

Experimental results for the quality of electron beam melting and refining of pyro-refined copper samples are analysed by an empirical model estimation approach. Investigation of the influence of the process parameters – melting power and time of refining on the removal efficiency of specific impurities, overall removal efficiency and material losses is performed.