University of Novi Sad
  • Novi Sad, Province of Vojvodina, Serbia
Recent publications
Despite the passage of time, traditional music continues to hold importance as a source of creativity for new generations. It is an important component of the spiritual history of the human race. This research aims to ascertain the opinions of preschool teachers regarding the influence of traditional music on young children's social and emotional development. The sample consisted of 164 preschool teachers employed in preschool institutions in the Republic of Serbia and the Republic of Croatia. The Student's Social and Emotional Competences Scale (SSEK) (Jeremić et al. 2015) was used as an instrument, adapted for this research. The findings showed that preschool teachers concur that teaching preschoolers traditional music affects their ability to develop their social and emotional skills. Preschool teachers implement traditional music in their educational work, and those who do so more often assess the influence of traditional music on the social and emotional development of children as more prominent. This research implies a need for future research on the frequency and modalities of implementing traditional music in preschools to benefit the development of children.
In this paper our intention was to present a brief literature review focused on the latest research of the Federated Learning paradigm in order to identify current research trends, possible future directions of development, and challenges in this area. Federated learning as a new, powerful distributed intelligent paradigm can take on various forms in order to fit a diverse set of problems in a wide range of domains, economy, finance, medicine, agriculture and other industrial sectors. Based on presented research results, several key opportunities for future work can be identified and some emerging are connected to communication costs and performance of federated models trained by different algorithms.
The directed power graph \(\mathbf {{\mathcal {G}}}({\textbf{G}})\) of a group \({\textbf{G}}\) is the simple digraph with vertex set G such that \(x\rightarrow y\) if y is a power of x. The power graph \({\mathcal {G}}({\textbf{G}})\) of the group \({\textbf{G}}\) is the underlying simple graph. In this paper, we prove that Prüfer group is the only nilpotent group whose power graph does not determine the directed power graph up to isomorphism. Also, we present a group \({\textbf{G}}\) with quasicyclic torsion subgroup that is determined by its power graph up to isomorphism, i.e. such that \({\mathcal {G}}({\textbf{H}})\cong {\mathcal {G}}({\textbf{G}})\) implies \({\textbf{H}}\cong {\textbf{G}}\) for any group \({\textbf{H}}\).
Timely response to the impact of climate change is a big challenge for the whole world, especially for developing countries. Within the framework of a country's transportation system, bridges play a crucial role in maintaining an efficient and well-connected road network. Ensuring their functionality is of paramount importance. However, climate change poses serious risks to the damage of bridge structures, jeopardizing traffic safety and potentially causing complete traffic interruptions. The aim of this paper is to present the current practice in Serbia regarding vulnerability analysis of bridges and the implementation of measures to enhance resilience.
The COVID‐19 pandemic appears to be winding down. But has its psychological effect of the pandemic also faded? This next stage remains uncertain, which needs to be explored further. This article aims to understand changing consumer attitudes in post‐pandemic times. In this regard, the present study conducts a cross‐country analysis to examine and compare the COVID‐19 fear appeals of consumers in India and Spain (if they still exist) that may have an influence on the future use (FU) and recommendation of online food services (OFS). The study integrates the concept of fear appeal, the theory of planned behaviour and cultural values to observe differences between Indian and Spanish consumers, in influencing their intention to use OFS. The findings confirm the importance of hygiene risk, with very low or no significance of perceived COVID‐19 risk on OFS usage in both countries.
It has been noted that education advances at a much slower rate than modern technologies. Rapid development of modern technologies has led to the increasing need for high quality engineers, but the Universities usually do not keep the same pace. This increases the importance of lifelong learning for engineers, especially those working in quickly developing disciplines such as computer engineering and specialized software for consumer and automotive technologies. The objective of this paper is to propose a learning model suitable for application in lifelong learning setting, aimed at agile education of engineers in the computer engineering field. One example course that follows this learning model is presented in detail. The learning model was applied in courses offered to computer engineers working in consumer and automotive industries. Learning effectiveness of the proposed model was measured by summative assessment in the courses. Experiences from learners that were collected in the end-of-course surveys provide insight into positive and negative aspects of this learning model. The overall feedback received from learners was positive and this may indicate that the proposed learning model has advantages over existing models used in lifelong education.
Dietary creatine has been recently put forward as a possible intervention strategy to reduce post‐COVID‐19 fatigue syndrome yet no clinical study so far evaluated its efficacy and safety for this perplexing condition. In this parallel‐group, randomized placebo‐controlled double‐blind trial, we analyzed the effects of 6‐month creatine supplementation (4 g of creatine monohydrate per day) on various patient‐ and clinician‐reported outcomes, and tissue creatine levels in 12 patients with post‐COVID‐19 fatigue syndrome. Creatine intake induced a significant increase in tissue creatine levels in vastus medialis muscle and right parietal white matter compared to the baseline values at both 3‐month and 6‐month follow‐ups ( p < .05). Two‐way analysis of variance with repeated measures revealed a significant difference (treatment vs. time interaction) between interventions in tissue creatine levels ( p < .05), with the creatine group was superior to placebo to augment creatine levels at vastus medialis muscle, left frontal white matter, and right parietal white matter. Creatine supplementation induced a significant reduction in general fatigue after 3 months of intake compared to baseline values ( p = .04), and significantly improved scores for several post‐COVID‐19 fatigue syndrome‐related symptoms (e.g., ageusia, breathing difficulties, body aches, headache, and difficulties concentrating) at 6‐month follow‐up ( p < .05). Taking creatine for 6 months appears to improve tissue bioenergetics and attenuate clinical features of post‐COVID‐19 fatigue syndrome; additional studies are warranted to confirm our findings in various post‐COVID‐19 cohorts.
To anticipate the impact of illegal landfills, development of new models should become a part of environmental risk management strategies. One of such approaches includes applications of the artificial neural network (ANN). The main objective of this study was to elucidate the impact of illegal landfilling on the surrounding soil environment and human health, as well as to establish an artificial neural network (ANN) models for predicting the hazards of illegal landfilling as an effective tool in decision-making and environmental risk management. The identification of heavy metals source in soil was performed by principal component analysis (PCA). To assess the sensitivity of the soil ecosystem to heavy metal concentrations, Soil Quality standards and quantitative indices were used. The possible health effects were valued using the average daily doses (ADDs), hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR). ANN modeling was used for the prediction of heavy metal concentrations in the soil based on landfill size, municipality size, the number of residents, plant species, soil, and landform types. The average values of the pollution indexes for Cd were in the moderately contaminated and very high contamination categories. The \(HQ\) values were lower than the safe level. Cr and Pb posed a significant \(CR\) for adults and children, and Ni for children. The ANN models have exhibited good generalization power and accurately predicted the output parameters with a high value of the coefficient of determination. Concerning heavy metal concentrations, illegal landfills near agricultural soil have a significant impact on the soil ecosystem and people’s health. The developed ANN models can be applied generally to anticipate the heavy metal concentrations in soil, according to the before mentioned input parameters, with high accuracy.
Growth and differentiation factor-15 (GDF-15) correlates with worse outcome of many tumours and any cause mortality. Data about its role in lymphoproliferative neoplasms (LPN) are scarce. Our research aimed to reveal the correlation between GDF-15 and standard laboratory parameters of LPN activity, and to get insight into the possible value of this cytokine assessment in lymphoma patients. Prospective research included 40 patients treated for aggressive or indolent LPN, and 31 with indolent LPN on “watch and wait” regimen. Analyses were performed before and after treatment in treated patients and on two separate occasions in the “watch and wait” group. ELISA technique with R&D assays according to the manufacturer manual, from stored sera at − 70 °C was used for GDF-15 level measurement. Statistical analyses were performed by IBM SPSS Statistics 22 using descriptive and inferential statistics. As appropriate, differences between groups were assessed by two tailed t-test, Mann–Whitney or x2 test. Spearman Rank Order Correlation was done to correlate GDF-15 with standard laboratory markers of disease activity. All tests are two-tailed with significance level p < 0. 05. GDF-15 (p = 0.028) and fibrinogen (p = 0.001) concentrations increased after treatment in indolent lymphoma patients while β2 microglobulin decreased (p < 0.001). GDF-15 positively correlated with β2microglobulin before (p < 0.001) and after (p = 0.031) therapy. There were no differences in any of the aforementioned parameters in the “watch and wait” group during observation. A positive correlation between GDF-15 and β2 microglobulin in patients with indolent LPN who need treatment suggests potential value in risk assessment.
The paper refers to a new method to quantify the energy losses due to frictional effects and imperfections in contacts in the case of real industrial tribomechanical systems. Whereby energy losses represent an integral indicator of quality of the real industrial tribomechanical system, in terms of the characteristics of the contact element materials, geometric accuracy, and manufacturing and assembly errors. This paper presents a complex theoretical model based on the differential equation of motion of a real tribomechanical system down a steep plane. The outputs of the theoretical model are exact mathematical expressions that define the current values of the coefficient of friction and the friction-caused energy losses. The measuring system enables the quantification of current values of the distance traveled per unit of time. Based on a series of experimentally determined values of distance traveled per unit of time, the values of energy losses of the real industrial tribomechanical system are determined using the developed theoretical model and the appropriate software support. The obtained results indicate a high reliability, a large potential, and a wide range of possible applications of the proposed method.
A pair of thick film segmented themistors with negative temperature coefficient (NTC) were joined together (back-to-back) to form thermally coupled device (TCT). The alumina substrate enables a very high galvanic insulation of thermistors and thermal coupling at the same time. The input thermistor R <sub xmlns:mml="" xmlns:xlink="">1</sub> in the coupled pair was self-heated at constant voltages and the output thermistor R <sub xmlns:mml="" xmlns:xlink="">2</sub> was a heat receiver through the alumina substrate. Custom designed NTC thick film thermistor pastes were made out of nickel manganese and modified nickel manganese. Thermistor electrical resistances were measured in a climatic test chamber and the themistor exponential temperature factor B was determined for both pastes. The TCT device was electrically characterized at different ambient temperatures. The input power, heat transfer, resistance and temperature of both thermistors were measured as a function of input voltage and time. The input and output thermistor temperatures T <sub xmlns:mml="" xmlns:xlink="">1</sub> and T <sub xmlns:mml="" xmlns:xlink="">2</sub> were obtained using thermistor resistance and Steinhart - Hart equation.The device sensitivity and measuring inaccuracy were analyzed. The main advantage of TCT is thermal coupling / electrical decoupling. The applications of TCT device are seen in automotive electronics, home appliances and power convertors to measure output temperature vs. input power.
[BEST PAPER AWARD] To boost revenues and create a lasting competitive advantage in the present global market, an increasing number of manufacturing companies are experimenting with shifting from product-centric offerings to service solutions leveraging digital technologies according to the Industry 4.0 paradigm. This (digital) transformation, known as "Digital Servitization", aims to provide new (digital) services and/or enhance existing ones. Yet, this transformation is challenging and manufacturing companies frequently have trouble meeting their expectations. To shed light on the current state of the Digital Servitization trend in the global manufacturing sector, researchers involved in the ASAP Service Management Forum and the IFIP WG5.7 Special Interest Group on "Service Systems Design, Engineering and Management" have conducted an international survey targeting manufacturing SME managers. The main survey objectives are twofold: (i) to analyse how manufacturing companies are implementing digital technologies to support their Digital Servitization transformation from traditional business models based on product sales to models focused on service delivery, and (ii) to identify which critical issues and best practices are characterizing the Digital Servitization transformation of manufacturing companies. Survey results have demonstrated a rising trend in the global manufacturing sector towards the use of digital technologies for service delivery, but more mature servitization strategies, data management activities, coordination efforts at the ecosystem level, and supporting tools for conscious decisions in the delivery of (digital) services are still required to succeed in the new Digital Servitization arena.
A Fifth Industrial Revolution has emerged, referred to as Industry 5.0, which represents a paradigm shift towards the integration of advanced technologies and the latest innovations in manufacturing processes and systems with a new hallmark in mind characterized by three main features: human-centricity, sustainability, and resilience. In the current scientific literature, there is still a lack of efforts to systematically review the state-of-the-art of Digital Transformation towards Industry 5.0. This systematic literature review aims to address this research gap by investigating the academic progress at the crossroads of Digital Transformation and Industry 5.0. The systematic review covered the analysis of journal articles and conference papers within the Industry 5.0 domain that were published during the last five years until March 2023. An overview of Digital Transformation and Industry 5.0 research fields is firstly captured by enumerating a list of prominent journals and international conferences for publishing on Industry 5.0-related content, and secondly by illustrating the significance of Digital Transformation and Industry 5.0 based on keywords classification.
Industry 5.0 represents a new strategy for manufacturing firms in the 21 st century. Additionally, the new concepts of Industry 5.0 are developed based on Industry 4.0 and its obstacles in implementation. The existence of Digital Servitization is the result of the relationship between Industry 4.0 and Traditional Servitization. However, the relationship between Industry 5.0 concepts and Servitization is still neglected in the research. This paper has the aim of showing the relationship between Industry 5.0 concepts and Servitization. The data for this research were obtained through the Serbian dataset from the European Manufacturing Survey conducted in 2022. The results of the research show the levels of implementation of Industry 5.0 concepts (i.e., human-centricity, sustainability, and resilience). Additional results show the level of Servitization implementation (i.e., traditional and digital services). Finally, the results show the correlation analysis between Industry 5.0 and the implementation of the Servitization concepts .
The Internal Audit seeks to respond to the challenges of the modern business environment, with a special focus on working with large databases so as to provide an additional value to their organizations through intelligent testing, root cause and trend analysis, summarizing the number and value of exceptions and providing the starting point for detection of unusual trends. This article analyse different digital solutions used in the oil and gas industry, with a special focus on the comparative analysis of digital tools, advanced analytics and machine learning in different stages of internal audit activities for the purpose of performing trend analysis and testing internal controls. Proposals for further improvements of the existing internal audit practice is to reach the level of predictive analytics and data-driven decision-making. Theoretical and practical analysis of the current level of development and use of digital tools by the internal audit in the oil industry are used a basis for comparative analysis of different IT solutions in working with large databases, as well as the competencies internal auditors will require in order to recognize new risks, technologies, innovations and use their knowledge and experience to help the learning and improvement processes in the organization, encourage development of innovative business practices and processes that will help the organization reach its strategic business goals. The originality of this article lies in its focus on the use of digital solutions, advanced analytics and machine learning in different stages of internal audit activities within the oil and gas industry.
Differentially Private (DP) synthetic data generation (SDG) algorithms take as input a dataset containing private, confidential information and produce synthetic data with comparable statistical characteristics. The significance of such techniques is rising due to the growing awareness of the extent of data collection and usage in organizational contexts, as well as the implementation of new stricter data privacy regulations. Given the growing academic interest in DP SDG techniques, our study intends to perform a comparative evaluation of the statistical similarities and utility (in terms of machine learning performances) of a specific set of related algorithms in the realistic context of credit-risk and banking. The study compares PrivBayes, Copula-Shirley, and DPCopula algorithms and their variants using a proposed evaluation framework across three different datasets. The purpose of this study is to perform a thorough assessment of the score and to investigate the impact of different values of the privacy budget (\(\epsilon \)) on the quality and usability of synthetic data generated by each method. As a result, we highlight and examine the deficiencies and capabilities of each algorithm in relation to the features’ properties of the original data.
The authors of this paper start from the position that horizontal learning implies a reflective dialogue among participants in the learning process within the professional development of teachers and preschool teachers, critical examination, observation, and understanding of theory and practice from different perspectives, building common knowledge, skills, and values based on which the necessary changes in practice can be planned and implemented. The findings of several types of research indicate that horizontal learning, despite the recognized benefit by the participants of the process, is still poorly represented in practice. The research aims to examine the factors that, according to school teachers and educators, negatively affect their motivation to participate in horizontal learning and at the analysis of their proposals on how to overcome the existing problems and difficulties in the current practice of horizontal learning in the Republic of Serbia. The combined method was applied in the research. The research sample included preschool teachers, subject and classroom teachers employed in institutions from several cities in the Republic of Serbia. For the quantitative part of the research, a questionnaire was constructed (N=330), while the qualitative part of the research was carried out through a semi-structured interview (N=30). Based on the obtained research findings, we can conclude that an unfavorable social environment for learning is the dominant factor that determines the motivation of teachers and educators to participate in horizontal learning activities. In this regard, the research findings indicate that with a higher level of support for horizontal learning in the institutions where the respondents are employed, their motivation to participate in horizontal learning activities also increases. Teachers and preschool teachers recognize the director of the institution as a leader of changes and development of the institution, but also as a manager who provides conditions for the realization of horizontal learning. Research findings and concluding considerations contribute to mapping current practice and a more complete understanding of the process of horizontal learning, providing a basis for creating future policies for the professional development of employees in education.
Pollinators play a crucial role in ecosystems globally, ensuring the seed production of most flowering plants. They are threatened by global changes and knowledge of their distribution at the national and continental levels is needed to implement efficient conservation actions, but this knowledge is still fragmented and/or difficult to access. As a step forward, we provide an updated list of around 3000 European bee and hoverfly species, reflecting their current distributional status at the national level (in the form of present, absent, regionally extinct, possibly extinct or non-native). This work was attainable by incorporating both published and unpublished data, as well as knowledge from a large set of taxonomists and ecologists in both groups. After providing the first National species lists for bees and hoverflies for many countries, we examine the current distributional patterns of these species and designate the countries with highest levels of species richness. We also show that many species are recorded in a single European country, highlighting the importance of articulating European and national conservation strategies. Finally, we discuss how the data provided here can be combined with future trait and Red List data to implement research that will further advance pollinator conservation.
In this short note we confirm the deep structural correspondence between the complexity of a countable scattered chain (=\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=$$\end{document} strict linear order) and its big Ramsey combinatorics: we show that a countable scattered chain has finite big Ramsey degrees if and only if it is of finite Hausdorff rank. This also provides a complete characterization of countable chains whose big Ramsey spectra are finite. We expand the notion of big Ramsey spectrum to monomorphic structures and give a sufficient condition for a monomorphic countable structure to have finite big Ramsey spectrum.
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4,356 members
Siniša Andrašev
  • Institute of Lowland Forestry and Environment
Aleksandar Ristic
  • Department of Computing and Control Engineering
Dušanka Obradović
  • Faculty of Medicine
Dragan Ivanovic
  • Faculty of Technical Sciences
Trg Dositeja Obradovića 5, 21000, Novi Sad, Province of Vojvodina, Serbia
Head of institution
Prof. dr Dejan Jakšić
+381 21 485 2020
+381 21 450 418