<abstract><title style='display:none'>Abstract</title>
The introduction of Artificial Intelligence (AI) in educational institutions has the potential to optimize the teaching process and save teachers valuable time. Artificial Intelligence can be utilized in various areas of teaching preparation, ranging from creating teaching materials to implementing teaching strategies. This article presents six important areas where AI can be used in teaching foreign languages, highlighting the advantages and disadvantages as well as potential pitfalls.
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The Use of Artificial Intelligence in Teaching Foreign Languages

<abstract><title style='display:none'>Abstract</title>
A significant amount of the existing literature on the motives of Generation Z is rooted in the era of the COVID-19 pandemic, during which social restrictions played a crucial role in communication and interaction with friends and the world. However, since the pandemic is over now, there is a curiosity about the current motivations driving young people to use the TikTok platform. This study involved surveying over 200 participants in Germany and Kazakhstan within the specified age group to explore their motives for using the TikTok platform. The collected data underwent correlation and regression analysis to identify the primary motivators. For active usage, where participants engage in producing and uploading content, the primary motivations include expressing personal <italic>creativity</italic>, <italic>perceiving oneself as an influencer</italic>, and the need to <italic>try out new things</italic>. This research aims to provide contemporary insights into the evolving motivations of young individuals within the post-pandemic landscape.
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An In-Depth Analysis of Generation Z Selected Motives for Active Tiktok Usage

<abstract>
<title style='display:none'>Abstract</title>
Team roles, personal character, and temperament play a key role in team management. The unique approach brought by Dr. M. Belbin´s unique approach, known as the Belbin Team Roles, is widely used in education, research, and professional consultancy. However, there is a significant gap in research on team roles in family businesses, which hinders the understanding of a specific form of human economic activity: family business.
The aim of this article is to show the methodology used in the research of team roles in family businesses, with a focus on family business quality in one specific Czech company. The company was evaluated using Belbin Team Roles 360-degrees analysis and a Family Business Quality self-evaluating questionnaire. This case study provides a foundation for future research in this area.
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Team Roles in Family Businesses and Quality of Family Business – Case Study

<abstract><title style='display:none'>Abstract</title>
The purpose of this article is the theoretical treatment of organizational structuring aspect, with special emphasis on the role of pyramidal organizational structure in organizational efficiency and effectiveness. More broadly, it talks about the importance of the organizational structure for the division of tasks, roles, responsibilities, authority and so on, as well as the importance of the optimal breadth of management in the success of organizations, respectively in the correct and clear understanding of roles of each member within the organization. Likewise, it is intended that through the study carried out in 50 enterprises in Kosovo, the importance of applying an adequate organizational structure that ensures their success will be presented. The study made it clear at what level the pyramidal organizational structure is applied by these enterprises and how much efficiency and effectiveness this structure has provided to them.
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The Role of Pyramidal Organizational Structure in Organizational Efficiency and Effectiveness

<abstract>
<title style='display:none'>Abstract</title>
The use of mobile platforms can help employees automate manual processes and streamline operations to save time and perform their tasks safely and accurately. A power-assisted vehicle to move weight around the place – solution: inexpensive, easy to apply, reliable, safe. It can adjust to various tasks, operators’ gait, loads up to 500 kg. It is a relatively inexpensive, easy-to-apply, reliable, and safe solution for moving weight. The motivation of the study is to increase efficiency and reduce physical strain on the operator in material handling tasks and to promote the implementation of this smart platform. Artificial intelligence learning methods are applied to adapt to individual operator’s experience, resulting in a personalized and more comfortable interaction with the help of Q-learning algorithm with 256 learning outcomes in adjusting controller settings: damping, mass, stiffness.
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Improving Human-Robot Physical Interaction Comfort in Material Handling Tasks Using a Smart Platform

<abstract>
<title style='display:none'>Abstract</title>
This article presents the circular-economy-based biorefinery concept developed by the “Biorefinery” research group at the Zittau/Görlitz University of Applied Sciences. The biorefinery concept aims the holistic utilization of plant raw materials and residues, in orders to exploit their entire value creation potential. The material or energetic utilization of all parts of the plants or plant residues results in significant economic and ecological advantages compared to conventional recycling methods and commonly accepted utilization concepts. The biorefinery process of our research group also envisages feeding products made of or contanining natural fibers after their use to a novel recycling process using saprobionthic fungi. As a result of fungal recycling mycelium-based biocomposites are produced and provided for further applications, e.g. in the construction industry or as packaging material. In this way, carbon can be sequestered in the long term and CO2 emissions can be avoided.
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Biorefinery Concept of the Zittau/Görlitz University of Applied Sciences

<abstract>
<title style='display:none'>Abstract</title>
Research into lowering the temperature during the production and installation of hot asphalt has been going on for a long time. In addition to developing appropriate recipes, it is important to gain experience, particularly in asphalt paving technology, since in addition to the behavior of the different asphalt mixtures during their compaction, external factors such as the location of the project and weather conditions also play an important role. The testing of the low-temperature asphalt on the federal highway B 169 was carried out successfully. Due to the high pre-compaction by the paver screed, the required compaction values were achieved on the binder course with 4 rolling passes and on the surface course with 3 rolling passes. The viscosity-changing additives and the selected rolling technology had a positive influence on the results. However, precise measurement results for compaction could not be achieved using the PQI probe.
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Paving Low-Temperature Asphalt on the B 169 Highway Near Heyda

<abstract>
<title style='display:none'>Abstract</title>
The purpose of this article is to illustrate the intuitively understood links between the social and economic characteristics of an area and the waste production at a given location. These relationships have been investigated using statistical data from thirteen regions in the Czech Republic between 2019 and 2021. In order to evaluate the data, freely available tools such as Python 3.8.16 and a number of its libraries, e.g. matplotlib, plotly, sklearn, numpy and others, have been used.
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Comparison of Waste Production in Regions of the Czech Republic in 2019-2021

<abstract>
<title style='display:none'>Abstract</title>
Ensuring public safety on our roads is a top priority, and the prevalence of road accidents is a major concern. Fortunately, advances in machine learning allow us to use data to predict and prevent such incidents. Our study delves into the development and implementation of machine learning techniques for predicting road accidents, using rich datasets from Catalonia and Toronto Fatal Collision. Our comprehensive research reveals that ensemble learning methods outperform other models in most prediction tasks, while Decision Tree and K-NN exhibit poor performance. Additionally, our findings highlight the complexity involved in predicting various aspects of crashes, as the Stacking Regressor shows variability in its performance across different target variables. Overall, our study provides valuable insights that can significantly contribute to ongoing efforts to reduce accidents and their consequences by enabling more accurate predictions.
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Machine Learning Techniques for Fatal Accident Prediction

<abstract><title style='display:none'>Abstract</title>
This article looks at how artificial intelligence affects the teaching of accounting in secondary schools. The article is divided into three parts. The first part of the article is devoted to literature research on the topic of the implementation of artificial intelligence in the curriculum within the subject of accounting. In the second part of the article, the methodology for the implementation of the author’s own research is described. The third part of this article deals with the research itself, whether artificial intelligence is implemented in the curriculum of secondary schools, within the subject of accounting. The pupils are already preparing for their future profession in schools, which has already moved forward thanks to the implementation of artificial intelligence. 43 respondents participated in the research that was conducted in two secondary schools where the subject of Accounting is taught.
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The Impact of Artificial Intelligence on the Accounting Subject Curriculum

<abstract><title style='display:none'>Abstract</title>
The article investigates the impact of the COVID-19 pandemic on economic growth, specifically focusing on research and development (R&amp;D) expenditures in the Czech Republic, Germany, and Poland. The analysis spans the periods preceding, during, and following the pandemic. The central objective of the article is to examine whether the pandemic, considering the implemented restrictions and associated financial aid, influenced the economic growth trajectory and the allocation of resources to research and development in the aforementioned Central European countries. The research utilizes time series data from 2011 to 2022, sourced from Eurostat, to track the evolution of Gross Domestic Product (GDP) and Gross Expenditure on Research and Development (GERD). Key indicators under scrutiny included GDP, GERD, and R&amp;D intensity – GERD as a percentage of GDP. A chain index was constructed to facilitate not only cross-country comparisons of these indicators but also an examination of year-to-year changes and an analysis of the growth rate of the GERD indicator. The research findings reveal that that COVID-19 really affected not only the development of the monitored economies but also the R&amp;D area; however, it was not the same in all the monitored countries. The impact of the pandemic can be seen in the decline in GDP in all three countries in 2020, but GERD decreased in only two of them – the Czech Republic and Germany. Poland experienced a significant increase in research and development funding in real terms. Both indicators (GDP and GERD) immediately resumed their growth in 2021 in all analyzed countries. From that it can be concluded that the impact of the COVID-19 pandemic on the GDP and GERD of the Czech Republic, Germany and Poland was not of a long-term nature.
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The Effect of the COVID-19 Pandemic on Economic Growth and R&amp;D Spending in Czechia, Germany, and Poland

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ACC JOURNAL

The ACC JOURNAL is an international scientific journal that came into existence in 2009. The Technical University of Liberec publishes it Four universities (Technical University of Liberec,...

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The ACC JOURNAL is an international scientific journal that came into existence in 2009. The Technical University of Liberec publishes it Four universities...

ACC JOURNAL

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