Applied Science & Technology Source

Personality traits are indicative of consistent patterns in thoughts, emotions, and behaviours, and they consequently impact students' academic performance. Numerous scientific investigations have explored the determinants of student learning success, with some emphasizing the significance of considering both student personality traits and generational cohorts. This study seeks to examine the associations between the Big Five personality dimensions and the learning strategies employed in mathematics lectures. A random sample of first- and second-year informatics engineering science students from Vilnius Gediminas Technical University (VILNIUS TECH) was selected for this research. Data were gathered through an anonymous survey utilizing a questionnaire developed by the authors. Non-parametric statistical tests were employed to analyse the data. The findings revealed that the sample predominantly consisted of students exhibiting the personality dimensions of agreeableness and conscientiousness. Furthermore, students' selection of learning strategies was generally independent of their personality dimensions. Nonetheless, the study underscored students' preferences for diverse learning strategies, irrespective of their personality traits.

This paper introduces a self-calibratable absolute modular rotary encoder based on the equal division average method, designed to significantly enhance measurement accuracy and simplify installation. The proposed design integrates multiple optical sensors into the encoder stator Printed circuit board, enabling precise absolute position measurement through the averaging of sensors data. This multi-sensor approach compensates for alignment and installation inaccuracies, which are common issues in conventional modular encoders. To validate the design and predict encoder behaviour prior to manufacturing, a theoretical modelling of virtual optical sensors is performed. Based on experimentally collected cross-calibration data from a real optical encoder, this modelling framework enables to estimate the efficiency of self-calibration algorithm with sufficient accuracy and optimize the design and performance of the encoder. The obtained results confirm that the proposed measurement system significantly reduces error margin, improving the reliability and precision of position feedback. The initial position deviation of several hundreds of arcseconds might be reduced and kept below 8 arcseconds by using two or more additional optical sensors, even with the 0.5 mm misalignment of the encoder stator.

A majority of decision-making problems are accompanied by some kinds of predictions and uncertainties. Therefore, interval data are widely used instead of exact data. The elimination and choice expressing reality methods, referred to as ELECTRE, belong to the outranking methods. Despite their relative complexity, avoiding compensation between criteria is one of the main advantages of the ELECTRE methods. However, no version of ELECTRE methods has the capability to deal with both interval data and target-based criteria. Target-based criteria are applicable in many areas ranging from material selection to medical decision-making problems. Efficiency of the modified ELECTRE method (ELECTRE-IDAT) was examined through two challenging examples. Also, a sensitivity analysis was performed to show advantages of the ELECTRE-IDAT approach. Additionally, the concept of bounded criteria was explained and applicability of interval data as well as benefit, cost, and target criteria were described with a biomaterial selection problem.

It is essential to evaluate the fact that our living environment day by day faces with the damage caused by contaminants that are appearing within the surface runoff from airports. Even though, airports are not always being assumed as industrialized components, works, that are being carried out in everyday life in airports, including simple tasks such cleaning or washing vehicles or aircraft, procedures such repair works, fundamentally everything, that takes place on the airport area grounds, still do discharge contaminants into the environment. This sort of activities that are being carried out in everyday life, in fact create severe natural surroundings issues, pollution is not always are being controlled. Therefore, regarding these issues and in order to be able to control them, it is extremely important to observe a degree of contaminants discharged within the environment and to maintain their sorting and adequate processing. An industry as airlines manage numbers of threats and restrictions regarding the area of airline fields, taking into consideration anti-icing and de-icing processes. Regulations of the treatment processes of surface wastewater that are polluted by the drainage approaches in cold weather temperatures are essential for many airports that operate within north climate. The paper summarizes information of certain airports located in foreign countries, techniques and appropriate methods that are used in order to slow down or decrease contaminants that are being discharged within the surface runoff and backwaters. Taking into account international practice this paper introduces proposed surface runoff treatment technology at Vilnius International Airport in Lithuania.

Modified genetic algorithm with special phenotypes’ selection and crossover operators with default specified rules is proposed in this paper thus refusing the random crossover. The suggested crossover operator enables wide distribution of genes of the best phenotypes over the whole population. During selection and crossover, the best phenotypes of the newest population and additionally the genes of the best individuals of two previous populations are involved. The effectiveness of the modified algorithm is shown numerically on the real-life global optimization problem from civil engineering - the optimal pile placement problem under grillage-type foundations. This problem is a fair indicator for global optimization algorithms since the ideal solutions are known in advance but with unknown magnitudes of design parameters. Comparison of the proposed algorithm with 6 other stochastic optimization algorithms clearly reveals its advantages: at similar accuracy level the algorithm requires less time for tuning of genetic parameters and provides narrower confidence intervals on the results than other algorithms.