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The work represents a successful attempt to combine a gas sensors array with instrumentation (hardware), and machine learning methods as the basis for creating numerical codes (software), together constituting an electronic nose, to correct the classification of the various stages of the wastewater treatment process. To evaluate the multidimensional measurement derived from the gas sensors array, dimensionality reduction was performed using the t-SNE method, which (unlike the commonly used PCA method) preserves the local structure of the data by minimizing the Kullback-Leibler divergence between the two distributions with respect to the location of points on the map. The k-median method was used to evaluate the discretization potential of the collected multidimensional data. It showed that observations from different stages of the wastewater treatment process have varying chemical fingerprints. In the final stage of data analysis, a supervised machine learning method, in the form of a random forest, was used to classify observations based on the measurements from the sensors array. The quality of the resulting model was assessed based on several measures commonly used in classification tasks. All the measures used confirmed that the classification model perfectly assigned classes to the observations from the test set, which also confirmed the absence of model overfitting.

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.

This study was conducted to evaluate the management of smart irrigation in grain maize production (KSC 715 cultivar) at the Seed and Plant Improvement Institute (SPII) located in Karaj, Iran, in the year 2020. Irrigation was performed based on 40% moisture discharge farm capacity and was compared with irrigation based on long-term meteorological statistics that have become common in the field (drip irrigation system, type strip, and determining the irrigation time based on the apparent reaction of the plant). The experimental results showed that under the conditions of smart irrigation management, sensitive phenological stages of the plant occur earlier, and the field is ready to be harvested approximately one month earlier; moreover, 35% of irrigation water consumption can be saved. Water consumption decreased from 8839.5 to 5675.67 m3/ha; in addition, grain yield and water productivity decreased. Although the moisture stress applied in the intelligent irrigation system completed the plant phenology period faster and due to earlier harvest, irrigation water consumption was decreased by 35%, water productivity was reduced. Finally, it seems that by adjusting the drought stress application time in more tolerant stages of maize growth in future studies and experiments, it will be possible to decrease irrigation water consumption while increasing the physical productivity of water.

The growing demand for energy is accelerating the process of consuming non-renewable energy sources, so special attention should be paid to the development of renewable energy as the energy obtained from renewable energy sources (RES) will reduce the consumption of primary raw materials and reduce emissions of harmful substances entering the atmosphere. The aim of this article is thus to investigate the attitude of Polish consumers towards renewable energy sources and to discover the relationship between the level of awareness and other factors such as age and education. The results of the research revealed that there was a correlation between the age and level of education of the respondents and their willingness to consider the issues related to renewable energy sources and implement solutions in their households that take into account the consumption of natural energy sources (p-value of the significance test for age is 0.0001227, and p-values of independence test for the level of education are 0.00013). The discovery of such correlations will allow knowing in which direction the efforts should be intensified in order to reach the largest part of society.

An original method for analyzing the influence of the meteorological, as well as physical-geographical conditions on the flooding of stormwater in small urban catchment areas is proposed. A logistical regression model is employed for the identification of the flooding events. The elaborated model enables to simulate the stormwater flooding in a single rainfall event, on the basis of the rainfall depth, duration, imperviousness of the catchment and its spatial distribution within the analyzed area, as well as the density of the stormwater network. The rainfall events are predicted considering the regional convective rainfall model for 32 rain gauges located in Poland, based on 44 years of rainfall data. In the study, empirical models are obtained to calculate the rainfall duration conditioning the flooding of stormwater in a small urban catchment area depending on the characteristics of the examined urban basins. The empirical models enabling to control the urbanization process of catchment areas, accounting for the local rainfall and meteorological characteristics are provided. The paper proposes a methodology for the identification of the areas especially sensitive to stormwater flooding in small urban catchment areas depending to the country scale. By employing the presented methodology, the regions with most sensitive urban catchments are identified. On this basis, a ranking of towns and cities is determined from the most sensitive to flooding in small urban catchment areas to the regions where the risk of flooding is lower. Using the method developed in the paper, maximum impervious catchment area are determined for the selected regions of the country, the exceedance of which determines the occurrence of stormwater flooding.

The aim of the paper is to present the idea of using ANSYS software in teaching engineering students the finite element method. ANSYS is an extremely sophisticated engineering tool used in almost every engineering company nowadays. It is introduced to almost all engineering students during their studies. Using ANSYS knowingly requires perfect understanding of the finite element method that is responsible for ANSYS work. This paper presents how this professional software can help students master FEM. The first part of the paper introduces the finite element method. It also suggests a way of using ANSYS in teaching FEM on the example of a two-dimensional restrained beam calculated in a simple computer program. The second part illustrates the effectiveness of ANSYS with sample FEM analysis of a planetary rover's chassis and presents basic fuctionalities of ANSYS Workbench Mechanical. Conducted calculations provide useful data about the model's suitability for its purpose and possibility of modifications.

We consider a natural generalization of the chromatic polynomial of a graph. Let the symbol f ( x 1 , … , x m ) ( H , λ ) denote a number of different λ -colourings of a hypergraph H = ( X , E ) , where X = { v 1 , … , v n } and E = { e 1 , … , e m } , satisfying that in an edge e i there are used at least x i different colours. In the work we show that f ( x 1 , … , x m ) ( H , λ ) can be expressed by a polynomial in λ of degree n and as a sum of graph chromatic polynomials. Moreover, we present a reduction formula for calculating f ( x 1 , … , x m ) ( H , λ ) . It generalizes the similar formulas observed by H. Whitney and R.P. Jones for standard colourings of graphs and hypergraphs respectively. We also study some coefficients of f ( x 1 , … , x m ) ( H , λ ) and their connection with the sizes of the edges of H .

We consider a natural generalization of the chromatic polynomial of a graph. Let f ( x 1 , … , x m ) ( H , λ ) denote a number of different λ-colourings of a hypergraph H = ( X , E ) , X = { v 1 , … , v n } , E = { e 1 , … e m } , satisfying that in an edge e i it is used at least x i different colours. In the paper we show that f ( x 1 , … , x m ) ( H , λ ) can be expressed by a polynomial in λ of degree n and as a sum of graph chromatic polynomials. Moreover, we present a reduction formula for calculating f ( x 1 , … , x m ) ( H , λ ) . It generalizes the similar formulas observed by H. Whitney and R.P. Jones for standard colourings of graphs and hypergraphs respectively. We also study some coefficients of f ( x 1 , … , x m ) ( H , λ ) and their connection with the sizes of the edges of H .

A subgraph of an edge-coloured graph is rainbow if all of its edges have different colours. For a given a graph H , a rainbow number is the minimum number r b ( n , H ) such that any edge-colouring of K n with at least r b ( n , H ) number of colours contains a rainbow copy of H . We determine the rainbow numbers for certain stars with one edge added and for complete graphs with one edge added.