Proceedings C of the 2019 e 6th Student Computer Science SR Research o Conference C tu S University of Primorska Press StuCoSReC Preface Proceedings of the 2019 6th Student Computer Science Research Conference Computer science is now among the most popular study programmes worldwide. We live in a digital age where Edited by most industries rely on data and software programmes. Iztok Fister Jr., Andrej Brodnik, Matjaž Krnc From transport infrastructure to public health systems, and Iztok Fister banking and communications, computer science is everywhere. Technology has made the world better, Reviewers and Programme Committee faster, and more connected. However, it is easy to miss Andrej Brodnik, Chair ■ University of Primorska, Slovenia Iztok Fister, Chair ■ University of Maribor, Slovenia an important component of this exciting success story. Iztok Fister Jr., Chair ■ University of Maribor, Slovenia Such development was made possible thanks to the Matjaž Krnc, Chair ■ University of Primorska, Slovenia brilliant minds of IT graduates, who took their passion Nikolaj Zimic, Chair ■ University of Ljubljana, Slovenia for technology and used it to create ground breaking ■ Amina Alić University of Maribor, Slovenia gadgets and computer programmes. Here in Slovenia, Klemen Berkovič ■ University of Maribor, Slovenia Zoran Bosnić ■ University of Ljubljana, Slovenia the three public universities share these values and Borko Bošković ■ University of Maribor, Slovenia invest heavily in their computer science students. These Janez Brest ■ University of Maribor, Slovenia efforts facilitate collaboration among our departments, Lucija Brezočnik ■ University of Maribor, Slovenia resulting in joint events such as this StuCoSRec student Patricio Bulić ■ University of Ljubljana, Slovenia conference. Mojca Ciglarič ■ University of Ljubljana, Slovenia Jani Dugonik ■ University of Maribor, Slovenia We are proud that, over the past five years, these Matjaž Gams ■ Jozef Stefan Institute, Slovenia Student Computer Science Research Conferences th Mario Gorenjak ■ University of Maribor, Slovenia have grown in several ways. In this 6 installment, we Andres Iglesias ■ Universidad de Cantabria, Spain received 24 full-paper submissions and one abstract Sašo Karakatič ■ University of Maribor, Slovenia submission. Among these, 21 papers were accepted Branko Kavšek ■ University of Primorska, Slovenia to these proceedings, and 22 talks are scheduled to Štefan Kohek ■ University of Maribor, Slovenia be presented during the conference, in three parallel Miklos Kresz ■ University of Szeged, Hungary sessions. The continued internationalization of our Niko Lukač ■ University of Maribor, Slovenia departments is also reflected with the authors of ten ■ Marjan Mernik University of Maribor, Slovenia full-paper submissions originating from outside of Uroš Mlakar ■ University of Maribor, Slovenia Eneko Osaba ■ University of Deusto, Spain Slovenia. Vili Podgorelec ■ University of Maribor, Slovenia The conference is dedicated to graduate and Jan Popič ■ University of Maribor, Slovenia undergraduate students of computer science and is Peter Rogelj ■ University of Primorska, Slovenia therefore free of charge. We gratefully acknowledge ■ Damjan Vavpotič University of Ljubljana, Slovenia the support of the Faculty of Mathematics, Natural Grega Vrbančič ■ University of Maribor, Slovenia Borut Žalik ■ University of Maribor, Slovenia Sciences and Information Technologies (University of Primorska). Published by University of Primorska Press Titov trg 4, SI-6000 Koper Matjaž Krnc Editor-in-Chief Jonatan Vinkler Managing Editor Alen Ježovnik Koper, 2019 ISBN 978-961-7055-82-5 (pdf) www.hippocampus.si/ISBN/978-961-7055-82-5.pdf ISBN 978-961-7055-83-2 (html) www.hippocampus.si/ISBN/978-961-7055-83-2/index.html DOI: https://doi.org/10.26493/978-961-7055-82-5 © University of Primorska Press Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID=302029568 ISBN 978-961-7055-82-5 (pdf) ISBN 978-961-7055-83-2 (html) Contents Preface II Papers LSTM Network for Stock Trading 5–8 ◆ Dušan Fister and Timotej Jagrič Defining computational thinking framework for introductory programming in higher education 9–12 ◆ Boštjan Bubnič Passive Floating Probe 13–17 ◆ Michele Perrone, Urban Knupleš, Mitja Žalik, Vid Keršič and Tadej Šinko Efficient Collision Detection for Path Planning for Industrial Robots 19–22 ◆ László Zahorán and András Kovács Sensitivity analysis for p-median problems 23–26 ◆ Ágnes Vida and Boglárka G.-Tóth A two-stage heuristic for the university course timetabling problem 27–30 ◆ Máté Pintér and Balázs Dávid Detection of different shapes and materials by glasses for blind and visually impaired 31–34 ◆ Urban Košale, Pia Žnidaršič and Kristjan Stopar Comparison of clustering optimization for classification with PSO algorithms 35–42 ◆ Klemen Berkovič, Uroš Mlakar, Borko Bošković, Iztok Fister and Janez Brest Hierarchical Routing Algorithm for Industrial Mobile Robots by Signal Temporal Logic Specifications 43–47 ◆ Balázs Csutak, Tamás Péni and Gábor Szederkényi Decolorization of Digital Pathology Images: A Comparative Study 49–52 ◆ Krishna Gopal Dhal, Swarnajit Ray, Arunita Das, Iztok Fister Jr. and Sanjoy Das Solving multi-depot vehicle routing problem with particle swarm optimization 53–56 ◆ Matic Pintarič and Sašo Karakatič Recognizing the subject exposure from the EEG signals with artificial neural networks 57–60 ◆ Sašo Pavlič and Sašo Karakatič Transfer Learning Tuning Utilizing Grey Wolf Optimizer for Identification of Brain Hemorrhage from Head CT Images 61–66 ◆ Grega Vrbančič, Milan Zorman and Vili Podgorelec System for remote configuration and over the air updates in restricted environments 67–70 ◆ Marko Zabreznik and Jernej Kranjec Covering problems and Influence maximization 71–74 ◆ Gyöngyvér Vass and Boglárka G.-Tóth Proceedings of the 2019 6th Student Computer Science Research Conference StuCoSReC Koper, Slovenia, 10 October III Strong deep learning baseline for single lead ECG processing 75–83 ◆ Csaba Botos, Tamás Hakkel, Márton Áron Goda, István Z. Reguly and András Horváth Primerjava osnovnega algoritma po vzoru obnašanja netopirjev in njegove hibridne različice HBA 85–90 ◆ Žan Grajfoner and Lucija Brezočnik Nadgradnja algoritma FLORS za besednovrstno označevanje slovenskih besedil 91–99 ◆ Domen Kavran, Robi Novak, Jan Banko, Rok Potočnik, Luka Pečnik and Borko Bošković Analiza igralnih strategij v iterativni zaporniški dilemi 101–106 ◆ Klemen Kac and Bor Praznik Napovedovanje nogometnega zmagovalca z rekurentno nevronsko mrežo LSTM 107–110 ◆ Nejc Planer and Mladen Borovič Izboljšanje zaznave sovražnega in zlonamernega govora s pomočjo slovarja besed 111–114 ◆ Sašo Kolac, Aljaž Soderžnik, Simon Slemenšek and Borko Bošković Investigating patterns using cellular automata 115 ◆ László Tóth Proceedings of the 2019 6th Student Computer Science Research Conference StuCoSReC Koper, Slovenia, 10 October IV Online Long Short-Term Memory Network for Stock Trading Dušan Fister Timotej Jagricˇ Univerza v Mariboru, Ekonomsko-poslovna Univerza v Mariboru, Ekonomsko-poslovna fakulteta, fakulteta, Razlagova 14, Razlagova 14, SI-2000 Maribor, Slovenia SI-2000 Maribor, Slovenia dusan.fi[email protected] [email protected] ABSTRACT sive trading strategy. LSTMs are found usable in broad ar- Economic theory teaches that it is impossible to earn higher- eas, such as sentence classification [2], trajectory prediction than-normal returns on trading stocks, and that the only of autonomous vehicles [9], flood forecasting [8] and malware chance to earn higher profits is to take higher risk. Often, detection [15]. Furthermore, LSTM are used in engineering the practice reveals that higher-than-normal stock returns for estimating remaining useful life of systems [17] and in may indeed be earned, which is a hypothesis we would like medicine for automated diagnosis of arrhythmia [11]. The to empirically test. In this way, we design so-called mechan- structure of the paper is as follows: chapter two outlines ical trading system, which focuses on the technical analysis the fundamentals of LSTM networks. Chapter three lists of past stock data, and perform daily trading for the Ger- the information about the dataset and explains methodol- man stock from period 2010-2019. Long short-term memory ogy. Chapter four shows the experiments and results, while network is taken as a basis of the mechanical trading sys- chapter five concludes the paper. tem. Obtained results show that higher-than-normal returns are easily obtainable, which polemicizes the efficiency of the 2. LONG SHORT-TERM MEMORY observed stock. Long short-term memory networks (LSTMs) are a kind of artificial neural networks, specifically designed to deal with Keywords sequential and dynamic data [6]. LSTMs are recurrent neu- ral networks (RNN) with an agile structure that attempt LSTM networks, mechanical trading system, stock trading to remember long-term dependencies and prevent both the usual RNN problems: exploding and vanishing gradients.The 1. INTRODUCTION benefit of the LSTM lies in a memory cell, i.e. central el- Efficient market hypothesis (EMH) states that asset prices ement of the network, and the three kinds of gates which fully reflect all information available [3] and that asset prices control the flow of information. Memory cell accumulates quickly incorporate any new information without delay. Con- the internal state by supplying the sequences of data. Each sequently, higher-than-normal returns cannot