Tomas Bata University in Zlín
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Consumer preferences for eco-friendly products
No full textThe aspect of eco-friendliness and the promotion of domestic products is becoming an important trend in business. Knowledge of consumer attitudes towards eco-friendly products enables the public and private sectors to shape consumer behaviour and respond more appropriately in their marketing campaigns. The aim of this research paper is to identify consumer preferences for eco-friendly products in the Czech Republic. The research is based on consumer behaviour theory with a focus on eco-friendly products, environmentally responsible consumers, and the effect of their country of origin. The objective will be fulfilled through a survey of 1,523 consumers in the Czech Republic. Descriptive and inferential statistics were used to process the data. The results indicate a majority group of actively environmentally responsible consumers. The preference for eco-friendly products is significantly different in terms of gender, age, and economic status
Quality characteristics of the cv. Albion strawberry (Fragaria x ananassa Duch.) in different locations
Get PDFStrawberries are one of the most popular berries in the world due to their distinctive aroma, flavor, and known health properties. A top day-neutral strawberry variety, the Albion, with its potential for high yields of large fruit, was grown in two different locations (Dağdibi and Hamidiye) at different altitudes (1410 and 1293 m) in Pozantı, a district of the Adana province in Türkiye, for late season production. Ripe fruits were harvested during the commercial harvest period, and several important physical and biochemical parameters were examined. In addition, the fruit's (berry's) external and flesh color, fruit length and width, soluble solid content (SSC), antioxidant capacity, total phenol and anthocyanin contents, individual sugars, organic acids, and volatile compounds were determined. Among these parameters, external fruit color, fruit width and length, SSC, total anthocyanin, total phenol, and ascorbic acid values showed differences between locations. In Hamidiye, the cv. Albion had the highest values of fruit width (32.04 mm) and total phenol content (51.80 mg gallic acid equivalent/100 g). In comparison, fruit length (44.22 mm), total acidity (1.65%), anthocyanin content (33.10 mg cyanidin-3-glucoside equivalent per 100 g), and ascorbic acid (53.42 mg/100 g) were higher in Dağdibi. The results indicate that locations at different altitudes affect the fruit's physical traits and the composition of strawberries
Risk management of a SPA
No full textA SPA is one of the types of health care. The legislation states that a healthcare facility is any space that is intended for the provision of health services. Furthermore, it is noted that one of the types of health care is medical rehabilitation care. This care is provided precisely on the premises of the SPA. The purpose is to maximally restore the client's physical, speech, sensory, and psychological functions. However, in the SPA, it is also necessary to solve risk management. SPAs represent an infrastructural element and, at the same time, can be considered as a soft target. Therefore, significant attention must be paid to this issue, and the area of risk analysis for these elements be addressed. As part of the contribution, risk identification and analysis will be carried out. In the results of this paper, types of threats to SPA facilities will be published—methods such as brainstorming, What If analysis, and Ishikawa diagram will be used. Based on the performed analysis, recommendations for SPA facilities will be proposed.Tomas Bata University in Zlín, TBU; European Regional Development Fund, ERDF, (IGA/FLKR/2023/005
Rubber-based piezoresistive sensing: a new approach based on hydrodynamic flow of material deformation describing nonlinear signals in stretchable sensors
Get PDFThe nonlinearity of piezoresistive response is critical in developing strain sensors, various self-monitoring applications and wearable electronics based on filled rubbers. This parameter could change dramatically when scaling up from small-size prototypes to full-scale production. The present work focuses on the nonlinear signals in stretchable rubber-based sensors, their origin and dependence on size of samples. Thus, a set of rectangular, piezoresistive samples differing in width was prepared from natural rubber reinforced with carbon black filler. Their electric resistance was tested under planar strain/recovery conditions at 25 and 50% strain amplitudes. It was found that piezoresistance and the related nonlinear phenomena significantly depended on the size of the samples. For the first time, hydrodynamic flow of deformed material was used to explain the nonlinearities of the piezoresistive signal. The trajectory, velocity, and magnitude of this flow were accounted for by a newly developed empirical equation describing the evolution of local resistivity under the strain/recovery process.Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; National Technical Library in Prague; DKRVO, (RP/CPS/2022/006)Ministry of Education, Youth and Sports of the Czech Republic [- DKRVO (RP/CPS/2022/006)
Classification with pseudo neural networks based on evolutionary symbolic regression
No full textThis research deals with a novel approach to classification. Classical artificial neural networks, where a relation between inputs and outputs is based on the mathematical transfer functions and optimized numerical weights, was an inspiration for this work. Artificial neural networks need to optimize weights, but the structure and transfer functions are usually set up before the training. There exist some evolutionary approaches, which help to set up the structure or to optimize weights in different ways than standard artificial neural networks do. The proposed method utilizes the symbolic regression for synthesis of a whole structure, i.e. the relation between inputs and output(s). For experimentation, Differential Evolution (DE) and Self Organizing Migrating Algorithm (SOMA) for the main procedure of analytic programming (AP) and DE as an algorithm for meta-evolution were used.Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (GACR 102/09/1680); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; European Regional Development Fund, ERDF, (CZ.1.05/2.1.00/03.0089); European Regional Development Fund, ERD
Investigation of factors affecting the sound absorption behaviour of 3D printed hexagonal prism lattice polyamide structures
Get PDFThe aim of this work is to investigate the sound absorption properties of open-porous polyamide 12 (PA12) structures produced using Selective Laser Sintering (SLS) technology. The examined 3D-printed samples, fabricated with hexagonal prism lattice structures, featured varying thicknesses, cell sizes, and orientations. Additionally, some samples were produced with an outer shell to evaluate its impact on sound absorption. Experiments were conducted using the transfer function method with an acoustic impedance tube in the frequency range of 250 Hz and 6400 Hz. The results showed that the studied geometric factors significantly affected the sound absorption of the PA12 samples. In some cases, the hexagonal prism lattice structures demonstrated relatively high sound absorption properties. Thanks to their properties such as lower weight, recyclability, and resistance to moisture and chemicals, these structures become competitive with commonly used sound-insulating materials, making them promising candidates for sound absorption. Furthermore, numerical simulations using Ansys software confirmed that the sound absorption properties of the open-porous material structures generally increased with higher specific airflow resistance. The findings highlight the advantages of 3D printing technology in producing complex, highly customizable porous structures for noise reduction applications.European Commission, EC, (CZ.10.03.01/00/22_003/0000048); European Commission, ECEuropean Union [CZ.10.03.01/00/22_003/0000048]; European Union under the REFRESH - Research Excellence For REgion Sustainability and High-tech Industrie
Impact of surface modification techniques for replaceable cutting inserts on cutting forces and surface finish in machining operations
Get PDFThis study investigates the impact of surface modification techniques, specifically microblasting and Magnetorheological Finishing (MRF), on the performance of uncoated sintered carbide replaceable cutting inserts (RCIs) during machining operations. The primary focus is on the relationship between surface roughness modifications and two key performance metrics: the quality of the workpiece surface finish and the cutting forces generated during turning operations. The study involved controlled experiments using RCIs that were untreated, sandblasted, or MRF-treated. Microblasting was found to increase surface roughness, leading to higher cutting forces and poorer workpiece surface quality. Conversely, MRF treatment reduced surface roughness, resulting in lower cutting forces and improved workpiece surface finishes
Profiling clients in the language school market
Get PDFThis paper analyzes the clients of language schools and, based on this analysis, redefines the basic characteristics of the language school market, which should lead to an increase in the competitiveness of language schools. The results of this study are based on a quantitative analysis of customer preferences, expectations, and experiences. Characterization of language school clients itself focuses on the roles of the clients and their preferences regarding the place of study, type of study, study content, and form of study. This empirical study is based on quantitative research in the form of a questionnaire survey which took place during 2021. The data comes from a total of 421 completed questionnaires. Data collection and reaching out to suitable respondents were ensured through partner organizations that participated in this research project. Based on contradictions between theory and empirical findings, a total of five statistical hypotheses were established. These were supplemented by testing dependencies of selected variables in relation to the respondent’s country of origin. Based on the chi-square test of independence, Fisher’s exact test, and proportional test, it was found that the majority of language school clients (1) are not children and students, (2) are not motivated to learn by staying abroad, (3) do not prefer traditional course-based teaching, (4) prefer face-to-face teaching, and (5) do not prefer learning/teaching with specialized content. These findings have led to a better understanding of the language school market and revealed hidden opportunities for language schools to develop their competitiveness, which derives from a customer perspective.Erasmus+ project [2020-1-CZ01-KA203-078478
Beyond the hype: AI advice and investor dissonance in crypto trading
No full textThis study examines the impact of cognitive dissonance on the relationship between investors’ intentions to use AI advice and their investment behaviour in the cryptocurrency market. The study recruited 348 individuals through a non-random snow-ball sampling technique. Utilising ChatGPT for investment recommendations, the research involves a trading experiment accompanied by a two-stage survey to evaluate investor attitudes towards AI before and their cognitive dissonance levels after the experiment. Structural Equation Modelling (SEM) identifies the connection between the intent to use AI and the influence of cognitive dissonance on investment decisions. Results indicate that investors following AI advice outperformed those who did not, attributable not to AI’s predictive power but to reduced cognitive dissonance. This reduction allowed investors using AI to cut losses more effectively, in contrast to those who eschewed AI advice and tended to hold onto losing positions longer, leading to worse performance. Although focused on the cryptocurrency market, the findings suggest a potential for broader applicability in conventional financial markets. The study’s key contribution is demonstrating that AI recommendations can mitigate the disposition effect, implying that AI’s broader implementation could enhance market efficiency
Minimum description length and multi-criteria decision analysis in predictive modelling
Get PDFAccurate model selection is essential in predictive modelling across various domains, significantly impacting decision-making and resource allocation. Despite extensive research, the model selection process remains challenging. This work aims to integrate the Minimum Description Length principle with the Multi-Criteria Decision Analysis to enhance the selection of forecasting machine learning models. The proposed MDL-MCDA framework combines the MDL principle, which balances model complexity and data fit, with the MCDA, which incorporates multiple evaluation criteria to address conflicting error measurements. Four datasets from diverse domains, including software engineering (effort estimation), healthcare (glucose level prediction), finance (GDP prediction), and stock market prediction, were used to validate the framework. Various regression models and feed-forward neural networks were evaluated using criteria such as MAE, MAPE, RMSE, and Adjusted R2. We employed the Analytic Hierarchy Process (AHP) to determine the relative importance of these criteria. We conclude that the integration of MDL and MCDA significantly improved model selection across all datasets. The cubic polynomial regression model and the multi-layer perceptron models outperformed other models in terms of AHP score and MDL criterion. Specifically, the MDL-MCDA approach provided a more nuanced evaluation, ensuring the selected models effectively balanced complexity and predictive accuracy.Tomas Bata University in Zlin, Faculty of Applied Informatics [RO30246061025/2102