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Energy efficient system for detection of elephants with Machine Learning
Marko Sagadin, 2020, master's thesis

Abstract: Human-Elephant Conflicts are a major problem in terms of elephant conservation. According to WILDLABS, an average of 400 people and 100 elephants are killed every year in India alone because of them. Early warning systems replace the role of human watchers and warn local communities of nearby, potentially life threatening, elephants, thus minimising the Human-Elephant Conflicts. In this Master's thesis we present the structure of an early warning system, which consists of several low-power embedded systems equipped with thermal cameras and a single gateway. To detect elephants from captured thermal images we used Machine Learning methods, specifically Convolutional Neural Networks. The main focus of this thesis was the design, implementation and evaluation of Machine Learning models running on microcontrollers under low-power conditions. We designed and trained several accurate image classification models, optimised them for on-device deployment and compared them against models trained with commercial software in terms of accuracy, inference speed and size. While writing firmware, we ported a part of the TensorFlow library and created our own build system, suitable for the libopencm3 platform. We also implemented reporting of inference results over the LoRaWAN network and described a possible server-size solution. We finally a constructed fully functional embedded system from various development and evaluation boards, and evaluated its performance in terms of power consumption. We show that embedded systems with Machine Learning capabilities are a viable solution to many real life problems.
Keywords: machine learning, microcontroller, on-device inference, thermal camera, low-power system
Published: 06.01.2021; Views: 164; Downloads: 43
.pdf Full text (13,35 MB)

Mards Workshop Proceedings
2020, proceedings of professional or unreviewed scientific conference contributions

Abstract: The collection contains contributions by authors who were presented at a workshop within the Erasmus + project MARDS in Maribor, at the University of Maribor.
Keywords: doctoral study, higher education, e-learning, distance learning, study evaluation
Published: 25.11.2020; Views: 133; Downloads: 16
URL Link to file

Deep Learning on Low Power Embedded Devices Using RISC-V Cores with an Extended Instruction Set
Jure Vreča, 2020, master's thesis

Abstract: This thesis explores the possibility of running neural networks on microcontrollers and how to optimize their performance using instruction set extensions. Microcontrollers are seen as too weak to run neural networks. We challenge this view and show that stripped-down neural networks can run and be useful for some applications. We used an open-source microcontroller called PULPino to run our neural network. The benefit of various instructions and optimizations for minimizing energy consumption to run deep learning algorithms was evaluated. Hardware loops, loop unrolling, and the dot-product unit were implemented and tested. We developed an FPGA-based testing system to evaluate our hardware. We also developed a deep learning library and a test neural network for our hardware. We wrote two versions of the deep learning library. One version is the reference code, and the other is the optimized code that uses the dot product unit. Using the testing system, we tested the performance of the two versions. The synthesis was run to determine the power and energy consumption. We also tried out various optimizations to see if the performance could be improved. Using instruction set extensions and algorithmic optimizations we reduced the clock cycle count by 72% for the convolutional layers and by 78% for fully-connected layers. This reduced power consumption by 73%. We compare our results with related research.
Keywords: deep learning, embedded system, instruction set, RISC-V
Published: 03.11.2020; Views: 417; Downloads: 83
.pdf Full text (2,69 MB)

Slovenian Chemistry Teachers' Understanding of Project-based Learning
Hanija Bujas, 2020, master's thesis

Abstract: Project-based learning (PBL) is a teaching method through which students gain knowledge and skills while working on a project for an extended period of time. They investigate and respond to an authentic, engaging, and complex problem. The popularity of PBL is constantly rising. However, PBL is hard to understand and therefore harder to implement in schools. In the master's thesis we wanted to understand how Slovenian chemistry teachers understand PBL, and how do they implement it in their teaching of chemistry or chemistry related subjects. We created a questionnaire on Google forms and distributed it to chemistry teachers of all Slovenian lower secondary schools and general upper secondary schools. We gathered 130 answers, out of which 95 were teachers who teach in lower secondary schools and 35 who teach in general upper secondary schools. According to the results, teachers barely understand PBL. A majority of teachers are convinced that they use PBL, when the results show that in practice they do not. Project-based learning is often confused for problem-based learning, which is the main confusion for the teachers. Our respondents believe that, because of extensive curriculum and lack of time, it is not possible to fully implement PBL in Slovenian schools.
Keywords: project-based learning, teachers, chemistry, understanding
Published: 29.10.2020; Views: 163; Downloads: 9
.pdf Full text (1,28 MB)

Exercises in Travel Writing and Literary Tourism
Laura Lupše, Maja Možic, Nuša Cesar, Žiga Zdovc, Marina Majerič, Martina Senekovič, Boštjan Koželj, Jasna Potočnik Topler, 2020

Abstract: The book entitled »Exercises in Travel Writing and Literary Tourism – A Teaching and Learning Experiment« emerged as a result of experimental project work in teaching English during the subject English in Tourism – Higher Level 1 at the Faculty of Tourism in Brežice, University of Maribor. This approach included teaching in the classroom, research in libraries and at home, and field work. The collection brings eight very different texts on Travel Writing and Literary Tourism by Master's students of Tourism, who were free in choosing the topic of the texts, their styles and the titles . The field of Travel Writing is significant, not only as its own discourse, a tourism trend and a tool of branding and embedding attractions and/or destinations, but also as a tool of teaching and learning a foreign language, which, along with upgrading specific language knowledge, encourages curiosity, research, creativity, reflection and self-development.
Keywords: travel writing, literary tourism, branding, teaching, learning, English language
Published: 29.10.2020; Views: 164; Downloads: 17
URL Link to file

Development of a Model for Predicting Brake Torque Using LSTM and TCN Models
Tomaž Roškar, 2020, master's thesis

Abstract: The main purpose of this thesis is to compare two state-of-the-art machine learning models, LSTM (Long Short-Term Memory) and TCN (Temporal Convolutional Network), on an AVL List GmbH case use, where the goal is to predict vehicle brake torque. Dataset used for model testing consists of multiple features which are preprocessed using several preprocessing methods. For model implementation Python’s libraries Keras and TensorFlow are used. Results from this thesis show that TCN is able to outperform LSTM. TCN achieves lower RMSE on the test dataset and is significantly faster in training and evaluation.
Keywords: brake torque, machine learning, neural network, LSTM, TCN, RNN, CNN
Published: 24.09.2020; Views: 167; Downloads: 0

English and Italian in the Frame of Genre-based Research and Foreign Language Learning
Ivo Fabijanić, 2020

Abstract: The publication focuses on English and Italian in the context of genre-based research in foreign language learning, with five contributions focusing on language, namely the position of abbreviations in the Italian business context, the English language in tertiary education using the LanGuide platform, the compilation of the Shakespeare's Dictionary, the attitude of young learners towards the introduction of the first foreign language and the strategies used in translating administrative texts into a minority language. In her contribution, Lenassi discusses the principle of economy in the language usage in business Italian correspondence, and focuses on the similarities and differences in the use of abbreviations. Kompara Lukančič and Fabijanić present a different approach to learning and teaching foreign languages, and they emphasise the role of language acquisition and multilingualism. Kompara Lukančič also discusses the micro- and macrostructure of the Shakespeare’s Dictionary. In his contribution, Smajla discusses the attitudes of Slovenian language learners to the introduction of the first foreign language. In the last part of the monograph Paolucci writes about his study from 2019 in which he examined source and target-oriented strategies in the translation of normative and informative administrative texts for the Italian minority in Slovenia.
Keywords: language learning, first foreign language, legal languages, business communication, lexicography.
Published: 10.09.2020; Views: 112; Downloads: 0

The Digital Pig: Automatic Systems for Behavior Detection in Weaned Pigs
Anja Žnidar, 2020, undergraduate thesis

Abstract: In this bachelor's thesis, we used machine learning techniques to detect pigs in group pens, which would help to improve the welfare and comfort of pigs. Mask-RCNN was used for object segmentation. The implementation was based on Resnet101. The goal was to achieve the highest possible precision in detection of the pig's body, head, and tail. We predicted that the accuracy will be the highest for body detection and lower for head and tail detection. We also concluded that the difference in precision and recall will be less than 10% between hand-labeled bounding boxes and the predicted bounding boxes from our model. As predicted, body detection represented the highest results, as the accuracy of head and tail detection was lower. The difference between precision and recall was 10% for body detection and higher than 10% for head and tail detection. Precision of the body detection was 96%, as the whole body is easier to detect. The head detection precision score was 66%. Tail detection precision was 77%, which is a large difference compared to the percentage of head detection. The use of machine learning in livestock farming could be a potentially useful tool for detecting welfare in pigs, as it would reduce the frequency of aggressive behaviors and the number of injuries. In the future, we want to refine our model to achieve higher precision for head and tail detection. Once the algorithm has clearly detected all the pigs in the image, we will try to refine the model to detect different forms of behavior. This technology would help us to evaluate welfare, which would be improved if necessary.
Keywords: pig, pig annotation, behavior, welfare, machine learning
Published: 08.09.2020; Views: 232; Downloads: 72
.pdf Full text (1,40 MB)

Medien im DaF-Unterricht: Analyse des Einsatzes der Busuu App
Anja Motaln, 2020, master's thesis

Abstract: Der DaF-Unterricht und Medien stehen heutzutage in einer engen Verbindung. Beim DaF-Unterricht sieht man, dass fast bei jeder Fremdsprachenunterrichtsstunde mehrere verschiedene Medien benutzt werden. Im Vordergrund dieser Magisterarbeit stehen deswegen die neuen Medien, die in den Fremdsprachenunterricht integriert werden können und mit denen man auch im Alltag umgeht. Es wird beschrieben, wie und in welcher Form man die neuen Medien im DaF-Unterricht einsetzen kann. Das Werk beschreibt die Phänomene M-Learning, E-Learning und MALL, die eine Basis für das Einfügen der Medien im Lernprozess vorstellen. Eine wichtige Unterkategorie der MALL repräsentieren die sogenannten Apps (die Kurzform für Wort Application aus dem Englischen). In dieser Arbeit beziehen sich Apps auf Programme beziehungsweise Applikationen, die auf Smartgeräten installiert sind und mit deren Hilfe man eine neue Sprache lernen kann. Der theoretische Teil der Magisterarbeit stellt die Medien im Zusammenhang mit dem DaF-Unterricht vor. Die obengenannten Begriffe werden aus theoretischer Sicht erläutert. Es existieren viele verschiedene Apps, die für das Lernen der deutschen Sprache geeignet sind. Eine Auflistung und Vorstellung solcher Apps erfolgt in diesem Werk. Weiterhin werden alle allgemein zugänglichen Informationen über die Busuu App erfasst, auf welche sich diese Magisterarbeit im folgenden praktischen Teil bezieht. Im empirischen Teil folgt die Analyse der Busuu-App in Bezug auf die Praxis. Die Busuu App ist im iOS App Store oder Android Play Store erhältlich. Dia App wird hier nach den folgenden Kriterien analysiert: Sprachniveaus, Themenbereiche, Semantisierungsverfahren, Übungstypen, Darstellung und Vermittlung von Grammatik und Weiteres von der App Angebotenes. Zudem bietet die Magisterarbeit eine Analyse der App aus der Perspektive eines Deutschlernendem, und deckt Mängel, Verbesserungsmöglichkeiten und Vorteile der App auf.
Keywords: DaF-Unterricht, Medien, neue Medien, M-Learning, Apps, Busuu App
Published: 23.07.2020; Views: 260; Downloads: 41
.pdf Full text (2,85 MB)

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