Mirjana Ivanovic

University of Novi Sad · Faculty of Sciences

The aim of this paper is to explore the model of the Mountain Car Problem. We provide insight into the physics behind the model. We present some experimental results obtained by numerically simulating the model. We also propose a reinforcement learning approach for deriving an optimal control policy combining model discretization and Q-learning.Key...

There are many areas where conventional supervised machine learning does not work well, for instance, in cases with a large, or systematically increasing, number of countably infinite classes. Zero-shot learning has been proposed to address this. In generalized settings, the zero-shot learning problem represents real-world applications where test i...

In modern, constantly developing society a lot of people suffer from critical, serious diseases and need almost everyday medical assistance. Accordingly, famous health big players and respectable research institutions all over the world have been recognized necessity of development of sophisticated specific software services that will help patients...

Nowadays, more and more people suffer from serious diseases and doctors and patients need sophisticated medical and health support. Accordingly, prominent health stakeholders have recognized the importance of development of such services to make patients’ life easier. Such support requires the collection of patients’ complex data. Holistic patient’...

In the field of time series data mining, the accuracy of the simple, but very successful nearest neighbor (NN) classifier directly depends on the chosen similarity measure. To improve the efficiency of elastic measures introduced to overcome the shortcomings of Euclidean distance, the Sakoe-Chiba band is usually applied as a constraint. In this pap...

In modern dynamic constantly developing society, more and more people suffer from chronic and serious diseases and doctors and patients need special and sophisticated medical and health support. Accordingly, prominent health stakeholders have recognized the importance of development of such services to make patients life easier. Such support requir...

Estimation of effort and costs is crucial for successfully implementation of software projects. Project development time is an essential factor, both for project clients and project developers. The amount of money needed to invest in a project influences the decision whether to start a project or not or whether it will be completed successfully or...

Collective intelligence and Knowledge Exploration (CI and KE) have been adopted to solve many problems. They are particularly used by companies as a support for innovation to efficiently obtain usable results. CI is usually defined as a group ability to perform consistently well across a wide variety of tasks, and it has to be combined with KD to e...

This paper highlights the use of software agents and simulating real-world medical phenomena. We start with a brief overview of different approaches and tools for developing software agents and running simulations. One of the more recent tools was utilized in this paper to develop a model of disease spread in a population of agents and for performi...

Introduction: Breast and prostate cancer survivors can experience impaired quality of life (QoL) in several QoL domains. The current strategy to support cancer survivors with impaired QoL is suboptimal, leading to unmet patient needs. ASCAPE aims to provide personalized- and artificial intelligence (AI)-based predictions for QoL issues in breast-...

This paper presents the evaluation of the Index of Learning Styles, an assessment tool of the Felder–Silverman learning model. A few studies have previously evaluated this tool, but as far as we know, none of them considered the learners’ opinion to achieve their goals. Considering that many studies suggest continuing with the Index of Learning Sty...

Rapid and accurate assessment of software project development using artificial intelligence tools can be essential for success in the software industry. This article has two objectives: to reduce the magnitude relative error (MRE) value in estimating the effort and cost of software development using the proposed artificial neural network architectu...

In this contribution, analysis of usefulness of selected parameters of a distributed information system, for early detection of anomalies in its operation, is considered. Use of statistical analysis, or machine learning (ML), can result in high computational complexity and requirement to transfer large amount of data from the monitored system’s ele...

In modern society, with the constantly growing economy and demanding working and living conditions, a large portion of the population is facing stressful life that triggers chronic health problems like cancer, cardiovascular or neurological diseases.

Quality of life (QoL) is one of the major issues for cancer patients. With the advent of medical databases containing large amounts of relevant QoL information it becomes possible to train predictive QoL models by machine learning (ML) techniques. However, the training of predictive QoL models poses several challenges mostly due to data privacy con...

This paper proposes a new, improved COmmon Software Measurement International Consortium function point (COSMIC FP) method that uses Artificial Neural Network (ANN) architectures based on Taguchi's Orthogonal Array to estimate software development effort. The minimum magnitude relative error (MRE) to evaluate these archi-tectures considering the co...

Adequate estimation is a crucial factor for the implementation of software projects within set customer requirements. The use of Case Point Analysis (UCP) is the latest and most accurate method for estimating the effort and cost of realizing software products. This paper will present a new, improved UCP model constructed based on two different arti...

Accurate assessment of software project development using the proper artificial intelligence tools can be a significant challenge for success in the software industry. This paper aims to minimize the relative error in software estimation using the proposed model of an artificial neural network (ANN) based on Taguchi's orthogonal vector plan. By sel...

Software estimation involves meeting a huge number of different requirements, such as resource allocation, cost estimation, effort estimation, time estimation, and the changing demands of software product customers. Numerous estimation models try to solve these problems. In our experiment, a clustering method of input values to mitigate the heterog...

In the World Declaration on Higher Education, the concept of higher education is defined as “all types of studies, training or research training at the postsecondary level, provided by universities or other educational establishments that are approved as institutions of higher education by the competent state authorities” [...]

This paper contributes to the research on explainable educational recommendations by investigating explainable recommendations in the context of personalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explai...

This paper proposes a multi-agent system for modeling and simulation of epidemics spread management strategies. The core of the proposed approach is a generic spatial Susceptible-Infected-Recovered stochastic discrete system. Our model aims at evaluating the effect of prophylactic and mobility limitation measures on the impact and magnitude of the...

Context Nowadays, companies are investing in brand new software, given that fact they always need help with estimating software development, effort, costs, and the period of time needed for completing the software itself. In this paper, four different architectures of Artificial Neural Networks (ANN), as one of the most desired tools for predicting...

In this paper, two different architectures of Artificial Neural Networks (ANN) are proposed as an efficient tool for predicting and estimating software effort. Artificial Neural Networks, as a branch of machine learning, are used in estimation because they tend towards fast learning and giving better and more accurate results. The search/optimizati...

Human activities and behaviour in different domains are usually influenced by other people’s actions and opinion. Nowadays, it is evident that there is a growing research interest in sentiment analysis, evaluation and prediction. Content from web sources and social media is frequently used when people want to see others’ opinion about different thi...

Online educational technologies (ET) collect a lot of data. Analysis of that data is called learning analytics (LA) or educational data mining (EDM). In this paper we present and combine research results from development and research work with two ET systems, one in University of Novi Sad, Serbia and another in University of Turku, Finland. We comb...

This book constitutes thoroughly reviewed and selected short papers presented at the 25th East-European Conference on Advances in Databases and Information Systems, ADBIS 2021, as well as papers presented at doctoral consortium and ADBIS 2021 workshops. Due to the COVID-19 the conference and satellite events were held in hybrid mode. The 11 full p...

In this work we address the problem of optimizing collective profitability in semi-competitive intermediation networks defined as augmented directed acyclic graphs. Network participants are modeled as autonomous agents endowed with private utility functions. We introduce a mathematical optimization model for defining pricing strategies of network p...

Improvement of prediction accuracy and early detection of the Alzheimer’s disease is becoming increasingly important for managing its impact on lives of affected patients. Many machine learning approaches have been applied to support the diagnosis and prediction of this illness. In this paper we propose an approach for improving the Alzheimer’s dis...

Time-series classification has been addressed by a plethora of machine-learning techniques, including neural networks, support vector machines, Bayesian approaches, and others. It is an accepted fact, however, that the plain vanilla 1-nearest neighbor (1NN) classifier, combined with an elastic distance measure such as Dynamic Time Warping (DTW), is...

Modeling and persistence of different data structures in indoor positioning systems is a requirement for providing a large number of specialized location-based services. Collection and diversification of indoor positioning systems’ metadata are important to understand the context of the system’s operation to create a positive feedback improvement l...

Abstract Contemporary technology enhanced learning together with different innovative learning methodologies are significantly initiating progress in educational ecosystems. Educational systems and tools that invoke active participation of learners are excellent facilitators of modern education. One such system is ASQ. ASQ is an interactive present...

In this paper we report our approach and experiences concerning the introduction of Python programming language in programming-related academic curricula. Firstly we motivate our choice and approach regarding the use of Python programming language. Then we discuss the results obtained in two courses that we taught to computer science and engineerin...

Az IKT és az internet használata a tanításban nagyon fontos mind a tanárok, mind a tanulók számára. Ez befolyásolja az egész életen át tartó tanulást és a személyes fejlődést. E tanulmány célja az IKT, a multimédiás technológia és az internet használatának vizsgálata a szerbiai általános iskolákban tartott órákon. A kutatás 66 egy-, két- és háromny...

The pervasive integration of ‘things‘ in the Internet of Things together with state-of-the-art computer systems provide a stimulating environment for creativity and business opportunities, but also a large range of security challenges. Engineering the security of such systems must acknowledge the peculiar conditions under which such systems operate...

Learning analytics, as a rapidly evolving field, offers an encouraging approach with the aim of understanding, optimizing and enhancing learning process. Learners have the capabilities to interact with the learning analytics system through adequate user interface. Such systems enables various features such as learning recommendations, visualization...

We propose a Constraint Logic Programming approach for synthesizing block-structured scheduling processes with ordering constraints. The approach is experimented using ECLiPSe-CLP system.

The ubiquitous connectivity of “things” in the Internet of Things, and fog computing systems, presents a stimulating setting for innovation and business opportunity, but also an immense set of security threats and challenges. Security engineering for such systems must take into consideration the peculiar conditions under which these systems operate...

A selection of Computer Science, Informatics or similar study programs for academic studies evidently becomes an emerging choice of a vast number of students in recent years. To address some of the open questions, we performed an 25 empirical study based on a survey, with a goal to find out the main motivating fac tors directing students to select...

This book gathers research contributions on recent advances in intelligent and distributed computing. A major focus is placed on new techniques and applications for several highly demanded research directions: Internet of Things, Cloud Computing and Big Data, Data Mining and Machine Learning, Multi-agent and Service-Based Distributed Systems, Distr...

Feature selection is an important data preprocessing step in data mining and machine learning tasks, especially in the case of high dimensional data. In this paper, we propose a novel feature selection method based on feature correlation networks, i.e. complex weighted networks describing the strongest correlations among features in a dataset. The...

Blockchain as a Service for the Internet of Things is an emerging topic in the blockchain research and industrial community, especially relating to increased system consistency, security, and privacy. Blockchains represent highly distributed and autonomous decision-making systems with distributed data and process management. Internet of Things syst...

A geofence is a virtual perimeter for a real-world positioning area. Geo-fencing involves a location-aware device of a location-based service user or asset entering or exiting a virtual area. Rather than geofences being static, in indoor positioning systems they need to be dynamically updated, frequently, efficiently and on-demand. Furthermore, the...

This paper presents the results of research on female students at three different faculties of informatics: Novi Sad in Serbia, Plovdiv in Bulgaria and Tirana in Albania. The idea of this paper is to analyze and compare female students' attitudes towards studying informatics (Computer Science - CS or Information Communication Technologies -- ICT an...

Running costs of buildings represent a significant outlay for all businesses, thus finding a way to run facilities as efficiently as possible is vital. IoT-enabled Building Management Systems provide means for process and resource usage automation leading to overall efficiency improvements. Inferring spatial and temporal occupancy in all its forms...

In this paper will be presented initial experiences of delivering elective course "Business Intelligence" that first time incorporated in MSc study at Department of Mathematics and Informatics, Faculty of Sciences. The aim of this paper is to point out the necessity of timely adaptation of curricula and introduction of courses that enhance the know...

The Internet of Things (IoT) system is a concept that binds together multiple deployments of heterogenous distributed and decentralized systems. In such systems it is very hard to keep track of user data, enforce complex privacy policies, ensure safe data storage and sharing, as well as employ an efficient mechanism for process and resource managem...