Tomas Bata University in Zlín
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Convexity and level sets for interval-valued fuzzy sets
Get PDFConvexity is a deeply studied concept since it is very useful in many fields of mathematics, like optimization. When we deal with imprecision, the convexity is required as well and some important applications can be found fuzzy optimization, in particular convexity of fuzzy sets. In this paper we have extended the notion of convexity for interval-valued fuzzy sets in order to be able to cover some wider area of imprecision. We show some of its interesting properties, and study the preservation under the intersection and the cutworthy property. Finally, we applied convexity to decision-making problems.Slovak grant agency VEGAVedecka grantova agentura MSVVaS SR a SAV (VEGA) [1/0150/21]; Spanish Ministry of Science and TechnologySpanish Government [TIN-201787600-P, PGC2018-098623-B-I00]; FICYT [IDI/2018/000176]Ministerio de Ciencia y Tecnología, MICYT: PGC2018-098623-B-I00, TIN-2017-87600-P; Fundación para el Fomento en Asturias de la Investigación Científica Aplicada y la Tecnología, FICYT: IDI/2018/00017
Antecedents of social media usage intensity in the financial sector of an emerging economy: a PLS-SEM algorithm
Get PDFThe purpose of this paper is to offer a critical understanding of the motivations and benefits of social media usage by small and medium financial enterprises with an empirical study from an emerging economy such as Ghana. Based on previous studies, the current study hypothesizes that customer-firm relationship, financial expectation, firm's visibility and growth, and market share expectation drive social media usage intensity in the financial industry. Quantitative data was gathered from management and staff of SMEs, specifically, financial institution outlets (having social media channels i.e., Facebook, Instagram, You Tube, Linkedln, etc.) was used to investigate the proposed conceptual framework. Using structural Equation Modelling, the research showed that customer-firm relationship, financial expectation, firm's visibility and growth, and market share expectation are positively associated with social media usage intensity within the financial sector. Moreover, it was discovered that financial firms that offer physical products only were equally employing social media networks for marketing communication purposes based on cost-effective motives. At the same time, we found that SMEs are more likely to consider 'market share expectation' as a key motivation for social media adoption by the financial industry. The findings from this study have provided some solutions to potential research issues specific to strategic management practices. Limitations and future research directions are discussed in the concluding remarks.Internal Grant Agency of FaME, Tomas Bata University in Zlin [IGA/FaME/2020/005]; Humanities and Social Sciences of Ministry of Education Planning Fund [15YJA630026]; Shandong Soft Science Foundation [2018RKB01302]; Shandong Provincial Natural Science FoundationNatural Science Foundation of Shandong Province [ZR2020MG034]; Shandong Social Science Foundation [18CLYJ20
Cooling of aluminium coils: Numerical simulation of the airflow for ventilation systems design
No full textReduction of the CO2 output during the production of aluminium, which is overall rather energy intensive (Haraldsson and Johansson, 2018), is currently one of the challenging topics for aluminium industry. The present work proposes the design of a method for energy savings during production of aluminium coils. The proposed technique is based on a forced ventilation with a pure outside air directly in the intermediate storage
Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19
Get PDFThe purpose of the paper is to create an information, fuzzy risk assessment model to support the decision-making of Municipality management for the establishment and management of measures in the safe mode (regular) of City, emergency and disaster situations, in the selected components of Smart City concept. Research on this topic was motivated by the need for support, especially in emergency situations, such as the COVID-19 pandemic. It is proposed that the evaluation be carried out at local level within the framework of the Smart City concept and selected components integrated into the entity, including the Smart Security, Smart Healthcare, and Smart Environment components supported by the Smart WebGIS subsystem. The model also assesses proposed solutions for self-government financing to ensure the acceptable risk, and economic impact of decisions on the city budget within the Smart Budget aspects of selected components. Decision-making is based on intellectual analysis, processing of fuzzy data and use of fuzzy inference. The output of the model is the assessment of the risk of the municipality subsystems, taking into account the threshold for the functioning of the municipality subsystems, the linguistic interpretation of the level of risk and the acceptability of the tolerable risk resource. The model algorithm was used to create a web application to support the Municipal management for the above-mentioned agenda, from safe time to pandemics.Agentúra na Podporu Výskumu a Vývoja, APVV: PP-COVID-20-0002; Univerzita Tomáše Bati ve Zlíně: RO/2022Internal Grant Agency of FaME Tomas Bata University in Zlin [RO/2022]; Slovak Research and Development Agency [PP-COVID-20-0002
Robotic automation of software testing from a machine learning viewpoint
Get PDFThe need to scale software test automation while managing the test automation process within a reasonable time frame remains a crucial challenge for software development teams (DevOps). Unlike hardware, the software cannot wear out but can fail to satisfy the functional requirements it is supposed to meet due to the defects observed during system operation. In this era of big data, DevOps teams can deliver better and efficient code by utilizing machine learning (ML) to scan their new codes and identify test coverage gaps. While still in its infancy, the inclusion of ML in software testing is a reality and requirement for coming industry demands. This study introduces the prospects of robot testing and machine learning to manage the test automation process to guarantee software reliability and quality within a reasonable timeframe. Although this paper does not provide any particular demonstration of ML-based technique and numerical results from MLbased algorithms, it describes the motivation, possibilities, tools, components, and examples required for understanding and implementing the robot test automation process approach. © 2021, Brno University of Technology. All rights reserved.IGA/CebiaTech/2021/00
A new approach to calibrating functional complexity weight in software development effort estimation
Get PDFFunction point analysis is a widely used metric in the software industry for development effort estimation. It was proposed in the 1970s, and then standardized by the International Function Point Users Group, as accepted by many organizations worldwide. While the software industry has grown rapidly, the weight values specified for the standard function point counting have remained the same since its inception. Another problem is that software development in different industry sectors is peculiar, but basic rules apply to all. These raise important questions about the validity of weight values in practical applications. In this study, we propose an algorithm for calibrating the standardized functional complexity weights, aiming to estimate a more accurate software size that fits specific software applications, reflects software industry trends, and improves the effort estimation of software projects. The results show that the proposed algorithms improve effort estimation accuracy against the baseline method.RVO/FAI/2021/002Faculty of Applied Informatics, Tomas Bata University in Zlin [RVO/FAI/2021/002
The influence of traditional and immobilized yeast on the amino-acid content of sparkling wine
Get PDFThis article focuses on the effect of yeast strains, vintage, and must sugar content on the amino-acid content of sparkling wines produced by the traditional method. In the experiment, the amino-acid concentrations before and after secondary fermentation, depending on the type of yeast used (basic wine without secondary fermentation, wine fermented with immobilized yeast, and wine fermented with classical Champagne yeast) and the sugar content of the must (170, 190, and 210 g per liter), and the vintage (2010 and 2011), were evaluated. Concentrations of 20 free amino acids in 18 wine variants were analyzed by ion-exchange liquid chromatography with postcolony ninhydrin derivatization and photometric detection. Results of the study show an increase in all the amino acids represented, except ornithine, after secondary fermentation. The average content of each amino acid in the basic wine, wine fermented with immobilized yeast, and wine fermented with classical Champagne yeast was higher in the variant where classical yeast was used. In this variant, the concentrations of alanine, glutamic acid, lysine, arginine, phenylalanine, valine, and glycine were almost twice as high as in the other variants. A higher proportion of most amino acids was observed in the year 2011; only for amino acids lysine, leucine, phenylalanine, tyrosine, ornithine, histidine, and methionine was a higher concentration observed in the year 2010. A higher concentration of released amino acids was also observed in wine produced from must with a higher sugar content (21 degrees NM).Research Infrastructure for Young Scientists [CZ.02.1.01/0.0/0.0/16_017/0002334]; Operational Program Research, Development, and Educatio
Competitiveness of the regions in the Czech Republic from the perspective of disaster risk financing
Get PDFMitigation of the impact of disasters and increasing resilience represent an inseparable part of the competitiveness of regions that cannot be implemented without a necessary resource framework. The paper focuses on the issue of financing individual phases of disaster management at the level of regions in the Czech conditions. The article is based on the assumption that public authorities do not systematically plan funds for dealing with crisis situations in the expenditure part of the budget, thereby not supporting the structural and functional conditions of territorial attractiveness, security and sustainability. The aim of the article is to propose a unique calculation of the minimum fund allocation for individual phases of disaster risk reduction at the regional level. The calculation concept is based on the value of the property owned by the region, the number of crisis situations predicted in the region, the number of crisis situations predicted in the Czech Republic, the administrative territory of the region and the total expenditures of the regional budget. The article presents a specific national approach to the public fund allocation to the individual disaster risk management phases, providing competitive administration and progressive and resilient development of the region. Based on the originally elaborated calculation, a comparative analysis of the expenditure part of 13 regional budgets for the 2013-2019 period was performed. The premise on the insufficient financing of disaster management was confirmed, although the Crisis Management Act imposes this obligation. The results showed that the most underfunded area was the implementation phase
Using Bert Embedding to improve memory-based collaborative filtering recommender systems
No full textThe performance of memory-based collaborative filtering recommender systems will be severely affected when the users' item preference data is sparse. In this paper, we focus on solving this issue. Our idea is to use Bert Embedding to learn a new feature set, which is denser and more semantic, for re-representing users and items. In these new features, memory-based collaborative filtering recommender systems work more efficiently. The experiments are conducted on the Movielens 100K dataset and the Yahoo Webscope R4 dataset.CNTT 2021-0
Resilience of beginning and advanced teachers in managing various changes in their profession
Get PDFThe paper is devoted to obtaining information on the resilience of kindergarten and primary school teachers. In the research, special attention was paid to beginning teachers, who we thought were more likely to be less resilient than teachers with longer experience. The research sample consisted of teachers of selected kindergartens and primary schools throughout the Czech Republic. The aim of the research was to find out whether there are differences in resilience between selected groups of teachers due to the current pandemic situation that each teacher had to deal with. Analysis of the data in the research revealed that beginning teachers have different rates of resilience compared to advanced teachers. No statistically significant differences were found in resilience between kindergarten and primary school teachers.[IGA/FHS/2019/003