University of Žilina

To test simulation models of pedestrian flows, we have performed experiments for corridors, bottleneck areas, and intersections. Our evaluations of video recordings show that the geometric boundary conditions are not only relevant for the capacity of the elements of pedestrian facilities, they also influence the time gap distribution of pedestrians, indicating the existence of self-organization phenomena. After calibration of suitable models, these findings can be used to improve design elements of pedestrian facilities and egress routes. It turns out that “obstacles” can stabilize flow patterns and make them more fluid. Moreover, intersecting flows can be optimized, utilizing the phenomenon of “stripe formation.” We also suggest increasing diameters of egress routes in stadia, theaters, and lecture halls to avoid long waiting times for people in the back, and shock waves due to impatience in cases of emergency evacuation. Moreover, zigzag-shaped geometries and columns can reduce the pressure in panicking crowds. The proposed design solutions are expected to increase the efficiency and safety of train stations, airport terminals, stadia, theaters, public buildings, and mass events in the future. As application examples we mention the evacuation of passenger ships and the simulation of pilgrim streams on the Jamarat bridge. Adaptive escape guidance systems, optimal way systems, and simulations of urban pedestrian flows are addressed as well.

The authors report the implementation of a simple one-step method for obtaining an infinite-order two-component (IOTC) relativistic Hamiltonian using matrix algebra. They apply the IOTC Hamiltonian to calculations of excitation and ionization energies as well as electric and magnetic properties of the radon atom. The results are compared to corresponding calculations using identical basis sets and based on the four-component Dirac-Coulomb Hamiltonian as well as Douglas-Kroll-Hess and zeroth-order regular approximation Hamiltonians, all implemented in the DIRAC program package, thus allowing a comprehensive comparison of relativistic Hamiltonians within the finite basis approximation.

Bloom's taxonomy of the cognitive domain and the SOLO taxonomy are being increasingly widely used in the design and assessment of courses, but there are some drawbacks to their use in computer science. This paper reviews the literature on educational taxonomies and their use in computer science education, identifies some of the problems that arise, proposes a new taxonomy and discusses how this can be used in application-oriented courses such as programming.

Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of applied issues. The core of AI is machine learning (ML)—a complex of algorithms and methods that address the problems of classification, clustering, and forecasting. The practical application of AI&ML holds promising prospects. Therefore, the researches in this area are intensive. However, the industrial applications of AI and its more intensive use in society are not widespread at the present time. The challenges of widespread AI applications need to be considered from both the AI (internal problems) and the societal (external problems) perspective. This consideration will identify the priority steps for more intensive practical application of AI technologies, their introduction, and involvement in industry and society. The article presents the identification and discussion of the challenges of the employment of AI technologies in the economy and society of resource-based countries. The systematization of AI&ML technologies is implemented based on publications in these areas. This systematization allows for the specification of the organizational, personnel, social and technological limitations. This paper outlines the directions of studies in AI and ML, which will allow us to overcome some of the limitations and achieve expansion of the scope of AI&ML applications.

The present study tested the hypothesis that increasing epoxyeicosatrienoic acids by inhibition of soluble epoxide hydrolase (sEH) would lower blood pressure and ameliorate renal damage in salt-sensitive hypertension. Rats were infused with angiotensin and fed a normal-salt diet or an 8% NaCl diet for 14 days. The sEH inhibitor, 12-(3-adamantan-1-yl-ureido)-dodecanoic acid (AUDA), was given orally to angiotensin-infused animals during the 14-day period. Plasma AUDA metabolite levels were measured, and they averaged 10+/-2 ng/mL in normal-salt angiotensin hypertension and 19+/-3 ng/mL in high-salt angiotensin hypertension on day 14 in the animals administered the sEH inhibitor. Mean arterial blood pressure averaged 161+/-4 mm Hg in normal-salt and 172+/-5 mm Hg in the high-salt angiotensin hypertension groups on day 14. EH inhibitor treatment significantly lowered blood pressure to 140+/-5 mm Hg in the normal-salt angiotensin hypertension group and to 151+/-6 mm Hg in the high-salt angiotensin hypertension group on day 14. The lower arterial blood pressures in the AUDA-treated groups were associated with increased urinary epoxide-to-diol ratios. Urinary microalbumin levels were measured, and ED-1 staining was used to determine renal damage and macrophage infiltration in the groups. Two weeks of AUDA treatment decreased urinary microalbumin excretion in the normal-salt and high-salt angiotensin hypertension groups and macrophage number in the high-salt angiotensin hypertension group. These data demonstrate that sEH inhibition lowers blood pressure and ameliorates renal damage in angiotensin-dependent, salt-sensitive hypertension.

A new approach for relativistic correlated electron structure calculations is proposed by which a transformation to a two-spinor basis is carried out after solving the four-component relativistic Hartree-Fock equations. The method is shown to be more accurate than approaches that apply an a priori transformation to a two-spinor basis. We also demonstrate how the two-component relativistic calculations with properly transformed two-electron interaction can be simulated at the four-component level by projection techniques, thus allowing an assessment of errors introduced by more approximate schemes.

We study cascading failures in networks using a dynamical flow model based on simple conservation and distribution laws. It is found that considering the flow dynamics may imply reduced network robustness compared to previous static overload failure models. This is due to the transient oscillations or overshooting in the loads, when the flow dynamics adjusts to the new (remaining) network structure. The robustness of networks showing cascading failures is generally given by a complex interplay between the network topology and flow dynamics.

The resilience of elements in a critical infrastructure system is a major factor determining the reliability of services and commodities provided by the critical infrastructure system to society. Resilience can be viewed as a quality which reduces the vulnerability of an element, absorbs the effects of disruptive events, enhances the element's ability to respond and recover, and facilitates its adaptation to disruptive events similar to those encountered in the past. In this respect, resilience assessment plays an important role in ensuring the security and reliability of not only these elements alone, but also of the system as a whole. The paper introduces the CIERA methodology designed for Critical Infrastructure Elements Resilience Assessment. The principle of this method is the statistical assessment of the level of resilience of critical infrastructure elements, involving a complex evaluation of their robustness, their ability to recover functionality after the occurrence of a disruptive event and their capacity to adapt to previous disruptive events. The complex approach thus includes both the assessment of technical and organizational resilience, as well as the identification of weak points in order to strengthen resilience. An example of the application of the CIERA method is presented in the form of a case study focused on assessing the resilience of a selected element of electrical energy infrastructure.

The aim of this study is to gain a deeper understanding of the micromorphology characteristics of thin titanium nitride (TiN) films sputtered on glass substrates by using ion beam sputtering (IBS). For that purpose, TiN samples were deposited onto glass substrates from gas mixtures with different contents of molecular nitrogen and argon atoms. Atomic force microscopy (AFM) was used to characterize the surface microtexture of obtained thin films at high magnification. The detailed analysis of AFM images using Minkowski functionals and fractal analysis reveals a significant effect of the preparation conditions on the surface features with non-monotonic dependences. Presented results suggest that non-classical spatial characteristics of the variability of the surface topography, including fractal dimension, corner frequency, roughness, and feature shape and size, can be tuned having control over the relative flow rates of the gas mixture during film deposition.

Emotions are an integral part of human interactions and are significant factors in determining user satisfaction or customer opinion. speech emotion recognition (SER) modules also play an important role in the development of human–computer interaction (HCI) applications. A tremendous number of SER systems have been developed over the last decades. Attention-based deep neural networks (DNNs) have been shown as suitable tools for mining information that is unevenly time distributed in multimedia content. The attention mechanism has been recently incorporated in DNN architectures to emphasise also emotional salient information. This paper provides a review of the recent development in SER and also examines the impact of various attention mechanisms on SER performance. Overall comparison of the system accuracies is performed on a widely used IEMOCAP benchmark database.

Nowadays, cities across the world are one after another trying to become so called Smart Cities. In this paper we propose several ideas on how to define the concept of Smart City, including our own. However, our main focus will be on the question of the safety and security in such cities in the future. Our study of the Smart City program shows the lack of importance which is being given to this topic. Because of that, we are inspired to introduce our definition of a Safe City. Along with the topics of safety and security, we also provide the reader with an insight into the importance and use of the modelling and simulations in a Safe City.

Summary Today, the Internet of Things (IoT) becomes a heterogeneous and highly distributed structure which can respond to the daily needs of people and different organizations. With the fast development of IT‐based technologies such as IoT and cloud computing, low‐cost health services and their support, efficient supervision of the centralized management, and monitoring of public health can be realized. Therefore, there has been increasing attention in the integration of IoT and health care both in academic and the business world. However, while the health care service industry fully holds the welfares of information systems for its personnel and patients, there is a need for an improved understanding of the issues and opportunities related to IoT‐based health care systems. But, as far as we know, the detailed review and deep discussion in this field are very rare. Hence, in this paper, we presented a literature review on the IoT‐based health care services from papers published until 2018. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed, and the main challenges of these mechanisms are highlighted for developing more efficient IoT techniques over health care services in the future. The results of this paper will be valuable for both practitioners and academicians, and it can provide visions into future research areas in this domain. By providing comparative information and analyzing the current developments in this area, this paper will directly support academics and working professionals for better knowing the progress in IoT mechanisms. As a general result, we found that IoT could help the governments to improve health services in society and commercial interactions.

In this work we focused on summarizing the principles of green marketing and the concepts related to it. The aim of this contribution was to prove the relationship between the implementation of green marketing principles and sustainable competitive company position on the market. In order to prove the relationship between the implementation of green marketing principles and the competitive market position of companies, we used a multiple regression method to reveal the relationship, despite many variables. This was preceded by a factor analysis that helped us to select the main factors of influence. In order to meet this goal, we have drawn from the surveys conducted by PwC (Bratislava, Slovakia), the Automobile Industry Association and the Slovak Automobile Institute to identify key factors and future expected development in the auto industry supplier segment and our marketing research, conducted from December 2015 to February 2016. Based on the results of marketing surveys, research responses and the study of available resources, we concluded that there is no comprehensive green marketing implementation model linking environmental consumer behavior with a link to the company’s marketing strategy. The contribution could help the Automotive Industry Union to present requirements to the government and help create incentives for the alternative vehicle market, and our findings could be incorporated into the creation of companies’ strategy.

Financial ratios play an important role in revealing corporate financial soundness, a role which helps to maintain the competitive position of an enterprise, with the achievement of stable development contributing to the elimination of potential financial risks. This paper aims to analyse and compare financial ratios used in the models of transition countries. The analysis focuses on the prediction of the future financial development of a particular enterprise as well as the determination of potential dependencies among the nation in consideration of financial ratios and country of origin. More than 400 prediction models of the Slovak Republic, the Czech Republic, Poland, Hungary, Romania, Lithuania, Latvia, Estonia, Croatia, Russia, Ukraine and Belarus were analysed. The crucial significance of financial ratios in divergent conditions is revealed using a cluster analysis, categorical data and a correspondence analysis. The cluster analysis identified similarities among three groups of countries: i) Belarus, Estonia, Croatia and Latvia; ii) Lithuania, Russia, Hungary and Ukraine, and iii) Czech Republic, Slovakia, Romania and Poland. The results of the correspondence analysis indicate that the individual groups of countries prefer different financial ratios in developing models of prediction of financial distress, differences which arose as a consequence of common changing political, market and economic conditions within each group of nations. In contrary to results suggested by our findings, the most frequently used financial ratios in the prediction models throughout the countries remain current ratio, total-liabilities-to-total-assets ratio, and total-sales-to-total-assets ratio.

Purpose The purpose of this paper is to provide an overview of leadership styles in the hospitality industry. It also demonstrates theories used in hospitality leadership styles research, identifies the main outcomes and highlights gaps for future research. Design/methodology/approach This paper presents a comprehensive review of the 79 articles on leadership styles in the hospitality context spanning over 13 years (2008–2020) and extends the scope in distinctive means. Findings This review has demonstrated that leadership styles research in hospitality has made progress in the past 13 years; however, there are conceptual and empirical overlaps among different leadership styles in hospitality. There is a lack of research on antecedents and integrating theories in studies. This review has revealed that several leadership styles have not been rigorously examined in hospitality research with their outcomes. Research limitations/implications The search strategy used to find articles published in Web of Science about leadership styles in hospitality was restricted to title to boost the accuracy of the subsequent literature. Practical implications By following the guidance presented in this review, the authors expect to advance and maintain hospitality leadership research to provide substantive insights into the context of hospitality leadership over the coming years. Originality/value To the best of the authors’ knowledge, this study is one of the first to undertake a comprehensive understanding of various leadership styles in the hospitality context. This study provides a comprehensive projected research agenda to demonstrate theoretical discourses and empirical research. Overall, this critical review presents a holistic idea of the focus of the prior studies and what should be highlighted in future studies.

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery.

Public social networks affect significant number of people with different professional and personal background. Presented paper deals with data analysis and in addition with safety of information managed by online social networks. We will show methods for data analysis in social networks based on its scale-free characteristics. Experimental results will be discussed for the biggest social network in Slovakia which is popular for more than 10 years. 1 , big data 2 , scale-free networks 3 , data security 4 , graph theory 5

The aim of our systematic review was to inspect the recently published literature on decentralized governance systems and integrate the insights it articulates on blockchain technology and smart contracts by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Throughout January and May 2022, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out, with search terms including “city” + “blockchain technology”, “smart contracts”, and “decentralized governance systems”. As the analyzed research studies were published between 2016 and 2022, only 371 sources satisfied the eligibility criteria. A Shiny app was harnessed for the PRISMA flow diagram to include evidence-based acquired and handled data. Analyzing the most recent and relevant sources and leveraging screening and quality assessment tools such as AMSTAR, Dedoose, Distiller SR, ROBIS, and SRDR, we integrated the core outcomes and robust correlations related to smart urban governance. As data visualization tools, for initial bibliometric mapping dimensions were harnessed, together with layout algorithms provided by VOSviewer. Future research should investigate smart contract governance of blockchain applications and infrastructure using decision-making tools and spatial cognition algorithms.

A Contributing Student Pedagogy (CSP) is a pedagogy that encourages students to contribute to the learning of others and to value the contributions of others. CSP in formal education is anticipatory of learning processes found in industry and research, in which the roles and responsibilities of 'teacher' and 'student' are fluid. Preparing students for this shift is one motivation for use of CSP. Further, CSP approaches are linked to constructivist and community theories of learning, and provide opportunities to engage students more deeply in subject material. In this paper we advance the concept of CSP and relate it to the particular needs of computer science. We present a number of characteristics of this approach, and use case studies from the available literature to illustrate these characteristics in practice. We discuss enabling technologies, provide guidance to instructors who would like to incorporate this approach in their teaching, and suggest some future directions for the study and evaluation of this technique. We conclude with an extensive bibliography of related research and case studies which exhibit elements of CSP.

layers increase the effective refractive index of the upper cladding near the facet. The index is controlled along the taper by subwavelength refractive index engineering to facilitate adiabatic mode transformation to the silicon wire waveguide while the Si-wire waveguide is inversely tapered along the coupler. The mode overlap optimization at the chip facet is carried out with a full vectorial mode solver. The mode transformation along the coupler is studied using 3D-FDTD simulations and with fully-vectorial 3D-EME calculations. The couplers are optimized for operating with transverse electric (TE) polarization and the operating wavelength is centered at 1.55 µm.