1. Computer science education in ChatGPT Era: experiences from an experiment in a programming course for novice programmersTomaž Kosar, Dragana Ostojić, Yu David Liu, Marjan Mernik, 2024, izvirni znanstveni članek Opis: The use of large language models with chatbots like ChatGPT has become increasingly popular among students, especially in Computer Science education. However, significant debates exist in the education community on the role of ChatGPT in learning. Therefore, it is critical to understand the potential impact of ChatGPT on the learning, engagement, and overall success of students in classrooms. In this empirical study, we report on a controlled experiment with 182 participants in a first-year undergraduate course on object-oriented programming. Our differential study divided students into two groups, one using ChatGPT and the other not using it for practical programming assignments. The study results showed that the students’ performance is not influenced by ChatGPT usage (no statistical significance between groups with a p-value of 0.730), nor are the grading results of practical assignments (p-value 0.760) and midterm exams (p-value 0.856). Our findings from the controlled experiment suggest that it is safe for novice programmers to use ChatGPT if specific measures and adjustments are adopted in the education process.
Ključne besede: large language models, ChatGPT, artificial intelligence, controlled experiment, object-oriented programming, software engineering education
Objavljeno v DKUM: 12.08.2024; Ogledov: 59; Prenosov: 4
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2. DigiPig : First developments of an automated monitoring system for body, head and tail detection in intensive pig farmingMarko Ocepek, Anja Žnidar, Miha Lavrič, Dejan Škorjanc, Inger Lise Andersen, 2022, izvirni znanstveni članek Opis: The goal of this study was to develop an automated monitoring system for the detection of pigs’ bodies, heads and tails. The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning algorithms (feature pyramid network). In the second part of the study, the goal was to improve the detection of tail posture (tail straight and curled) during activity (standing/moving around) by the use of neural network analysis (YOLOv4). Our dataset (n = 583 images, 7579 pig posture) was annotated in Labelbox from 2D video recordings of groups (n = 12–15) of weaned pigs. The model recognized each individual pig’s body with a precision of 96% related to threshold intersection over union (IoU), whilst the precision for tails was 77% and for heads this was 66%, thereby already achieving human-level precision. The precision of pig detection in groups was the highest, while head and tail detection precision were lower. As the first study was relatively time-consuming, in the second part of the study, we performed a YOLOv4 neural network analysis using 30 annotated images of our dataset for detecting straight and curled tails. With this model, we were able to recognize tail postures with a high level of precision (90%).
Ključne besede: pig, welfare, image processing, object detection, deep learning, smart farming
Objavljeno v DKUM: 11.07.2024; Ogledov: 87; Prenosov: 9
Celotno besedilo (48,11 MB)
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5. Implementation of the scheduling domain description modelAlenka Baggia, Robert Leskovar, Miroljub Kljajić, 2008, izvirni znanstveni članek Opis: This paper presents the problem of auniform scheduling domain description. It was established that the algorithm used for scheduling is general, disregarding the type of scheduling domain. On the basis of five different scheduling domains, a general description model was developed. The research is focused on the programming application of the resource scheduling model, presented as a UML class diagram. Diverse meta-languages for the model description were considered. Of these XML, an EAV model and object oriented languages have shown to be the most effective. Even though Java is not widely used as a description language, it has proved effective as a meta-language for the description of the extensible scheduling model.
Ključne besede: scheduling, domain description, description language, object oriented analysis
Objavljeno v DKUM: 30.11.2017; Ogledov: 1117; Prenosov: 405
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6. Relations between the object under consideration, dialectical system, system and model of it as a basis for the requisite holism and realism of modelling and its resultsMatjaž Mulej, Zdenka Ženko, Branka Čagran, Nastja Mulej, 2013, izvirni znanstveni članek Opis: Modelling is a crucial tool in research and development, but models simplify oneʼs perception of systems as mental pictures of reality, maybe too much. Therefore one must be aware of the addressed relations, typology of models, and apply 'USOMID - 6 Thinking Hats' method of creative cooperation to attain requisite holism of approach and requisite wholeness of outcomes.
Ključne besede: object, system, dialectical system, model, USOMID, 6 thinking hats
Objavljeno v DKUM: 10.07.2015; Ogledov: 1626; Prenosov: 403
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7. PUBLIC LIBRARY AND HANDICRAFT CENTRE IN PRIZRENFlaka Xërxa, 2013, magistrsko delo Opis: architecture, islamic architecture, library, handicraft center, prizren, kosovo
Ključne besede: This master thesis is focused on the design project for the city library of Prizren. Taking into account the development that this type of objects had and continues to have in all European cities, the general understanding is that such an object is missing in the city of Prizren, a city with ancient culture and tradition.
Aiming to achieve a design which is in accordance with the highest architectonic values and also with the specified location, in the first part of the thesis, the specifics of the existi
Objavljeno v DKUM: 12.12.2013; Ogledov: 4326; Prenosov: 688
Celotno besedilo (165,03 MB) |
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9. An efficient chain code with Huffman codingYong Kui Liu, Borut Žalik, 2005, izvirni znanstveni članek Opis: This paper presents a new chain code based on the eight-direction Freeman code. Each element in the chain is coded as a relative angle difference between it and the previous element. Statistical analysis showed that the probabilities of the Freeman codes differ importantly. Therefore, the Huffman coding was applied. The proposed chain code requires 1.97 bits/code, its chainlength is small, it allows representation of non-closed patterns and is rotationally independent.
Ključne besede: computer science, pattern recognition, chain code, Huffman code, object representations, chain code compression
Objavljeno v DKUM: 01.06.2012; Ogledov: 2051; Prenosov: 109
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