Implementation of a new reporting process in a group xSara Črešnik
, 2021, magistrsko delo
Opis: Reporting is present in every company. Whether it is small or big, it cannot be avoided. It plays a crucial role in the process and progress of business. The quality of reporting affects the development of the work environment and the company. Since business report is a document that contains business information, which supports the decisions about the future-oriented business decisions, it is very important for it to be designed in such a way that it contains the key information for the recipient and provides support for business decisions. The reporting process can take place horizontally upwards or downwards. Content and structure vary depending on the recipient of the report. We live in an age when our every step is accompanied by digitization, computerization, artificial intelligence, mass data, the Internet of Things, machine learning, and robotics. These changes have also affected the reporting process as well as its processes. The processes of data acquisition, processing and sharing have changed. Furthermore, the data quantity has increased, whereas the speed of the time in which to prepare the reports has decreased. We can have data without information, but we cannot have information without data. There is never enough time, especially nowadays when we are used to having everything at our fingertips. These are two conflicting factors – having more data and less time to prepare quality reports. The systems are developed to optimize the process, increase efficiency and quality and, what is nowadays most important, they have been created to obtain mass data in the shortest possible time. Therefore, it is important to adapt and implement software that can help achieve our daily tasks. We must know how to process huge amounts of real-time data and deliver the information they contain. It is crucial for companies to keep up with the environment and implement changes and innovations into their business process. A company is like a living organism for it must constantly evolve and grow. As soon as it stops growing and evolving, it can fail because it starts lagging and is therefore no longer competitive to others. To deliver faster feedback, companies need data of better quality. There are tools that can improve the business process, better facilitating the capacity of the human agents. The goal is to harness the employees’ full potential and knowledge for important tasks, such as analyzing, reviewing, and understanding data and acting upon them, invoking information technology to automate repetitive processes and facilitate better communication.
The focus in this master’s thesis is on the reporting process in Group X. Group X is one of the world leaders in the automotive industry, a multinational corporation based in Canada with subsidiaries around the world. The complexity of the business reporting that is implemented for the Headquarters in Canada has to address the complexity of the multinational corporation to support the decision process.
The aim of the thesis is to propose a reporting process for preparing and producing reports with a huge amount of data in a very time-efficient manner. We start by examining the existing processes and upon that, identifying the processes required for the reports to reach the final recipients. Our goal is to identify the toolset, which would increase efficiency, accuracy, credibility, and reduce errors in the fastest possible time. We investigate a short-term and a long-term solution. By a short-term solution, we mean a system, program, or a tool that can help us increase our potential by using digital resources, which are already existing in the organization. By a long-term solution, we mean a solution, which requires employment of specialized future tools in the field of reporting and in repetitive processes, which we can identify with current knowledge and expectations for development. This includes machine learning, robotic process automatization, artificial intelligence.
Ključne besede: Consolidated reporting, reporting process, robotic process automatization, business intelligence, artificial intelligence, machine learning, SharePoint, Big Data, digital transformation, electronic data interchange.
Objavljeno: 01.09.2021; Ogledov: 45; Prenosov: 3
Celotno besedilo (1,71 MB)
Energy efficient system for detection of elephants with Machine LearningMarko Sagadin
, 2020, magistrsko delo
Opis: 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.
Ključne besede: machine learning, microcontroller, on-device inference, thermal camera, low-power system
Objavljeno: 06.01.2021; Ogledov: 223; Prenosov: 52
Celotno besedilo (13,35 MB)
Deep Learning on Low Power Embedded Devices Using RISC-V Cores with an Extended Instruction SetJure Vreča
, 2020, magistrsko delo
Opis: 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.
Ključne besede: deep learning, embedded system, instruction set, RISC-V
Objavljeno: 03.11.2020; Ogledov: 480; Prenosov: 97
Celotno besedilo (2,69 MB)
Slovenian Chemistry Teachers' Understanding of Project-based LearningHanija Bujas
, 2020, magistrsko delo
Opis: 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.
Ključne besede: project-based learning, teachers, chemistry, understanding
Objavljeno: 29.10.2020; Ogledov: 201; Prenosov: 13
Celotno besedilo (1,28 MB)
Exercises in Travel Writing and Literary TourismLaura Lupše
, Maja Možic
, Nuša Cesar
, Žiga Zdovc
, Marina Majerič
, Martina Senekovič
, Boštjan Koželj
, Jasna Potočnik Topler
Opis: 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.
Ključne besede: travel writing, literary tourism, branding, teaching, learning, English language
Objavljeno: 29.10.2020; Ogledov: 227; Prenosov: 21
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Development of a Model for Predicting Brake Torque Using LSTM and TCN ModelsTomaž Roškar
, 2020, magistrsko delo
Opis: 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.
Ključne besede: brake torque, machine learning, neural network, LSTM, TCN, RNN, CNN
Objavljeno: 24.09.2020; Ogledov: 249; Prenosov: 0
English and Italian in the Frame of Genre-based Research and Foreign Language LearningIvo Fabijanić
Opis: 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.
Ključne besede: language learning, first foreign language, legal languages, business communication, lexicography.
Objavljeno: 10.09.2020; Ogledov: 162; Prenosov: 0
The Digital Pig: Automatic Systems for Behavior Detection in Weaned PigsAnja Žnidar
, 2020, diplomsko delo
Opis: 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.
Ključne besede: pig, pig annotation, behavior, welfare, machine learning
Objavljeno: 08.09.2020; Ogledov: 286; Prenosov: 87
Celotno besedilo (1,40 MB)