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1.
Variety of mutual-visibility problems in hypercubes
Danilo Korže, Aleksander Vesel, 2025, original scientific article

Keywords: mutual visibility, hypercube, binary code
Published in DKUM: 04.02.2025; Views: 0; Downloads: 4
.pdf Full text (571,90 KB)

2.
Efficient compressed storage and fast reconstruction of large binary images using chain codes
Damjan Strnad, Danijel Žlaus, Andrej Nerat, Borut Žalik, 2024, original scientific article

Abstract: Large binary images are used in many modern applications of image processing. For instance, they serve as inputs or target masks for training machine learning (ML) models in computer vision and image segmentation. Storing large binary images in limited memory and loading them repeatedly on demand, which is common in ML, calls for efficient image encoding and decoding mechanisms. In the paper, we propose an encoding scheme for efficient compressed storage of large binary images based on chain codes, and introduce a new single-pass algorithm for fast parallel reconstruction of raster images from the encoded representation. We use three large real-life binary masks to test the efficiency of the proposed method, which were derived from vector layers of single-class objects – a building cadaster, a woody vegetation landscape feature map, and a road network map. We show that the masks encoded by the proposed method require significantly less storage space than standard lossless compression formats. We further compared the proposed method for mask reconstruction from chain codes with a recent state-of-the-art algorithm, and achieved between and faster reconstruction on test data
Keywords: binary mask, machine learning, chain code, binary encoding, bitmap reconstruction
Published in DKUM: 29.01.2025; Views: 0; Downloads: 3
.pdf Full text (1,45 MB)

3.
Low Code Programming with APEX : How to and Practical Cases
2024

Abstract: This textbook introduces Oracle Application Express (APEX), a low-code platform for building data-driven web applications. It aims to equip readers with the skills to fully utilize APEX for real-world business challenges. Part I covers the basics of APEX in twelve chapters, including environment setup, database preparation, navigation, data exchange, application creation, report and form management, and team collaboration. Part II presents twelve business cases that provide a comprehensive understanding of application development from a business, data, and user interface perspective. Each case includes business views, problem definitions, use cases, data models, and application interfaces. The textbook is designed for approximately 75 hours of study and is suitable for both experienced developers and beginners. It includes additional material such as exported applications, scripts, data and video tutorials to enhance learning.
Keywords: low-code programming, application development, web applications, Oracle APEX, practical examples
Published in DKUM: 01.10.2024; Views: 0; Downloads: 10
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4.
An efficient multi-resolution chain coding
Andrej Nerat, Damjan Strnad, Krista Rizman Žalik, Borut Žalik, 2024, original scientific article

Keywords: chain code, progressive chain code, multi-resolution chain code
Published in DKUM: 28.08.2024; Views: 55; Downloads: 9
.pdf Full text (3,00 MB)

5.
Commit-level software change intent classification using a pre-trained transformer-based code model
Tjaša Heričko, Boštjan Šumak, Sašo Karakatič, 2024, original scientific article

Abstract: Software evolution is driven by changes made during software development and maintenance. While source control systems effectively manage these changes at the commit level, the intent behind them are often inadequately documented, making understanding their rationale challenging. Existing commit intent classification approaches, largely reliant on commit messages, only partially capture the underlying intent, predominantly due to the messages’ inadequate content and neglect of the semantic nuances in code changes. This paper presents a novel method for extracting semantic features from commits based on modifications in the source code, where each commit is represented by one or more fine-grained conjoint code changes, e.g., file-level or hunk-level changes. To address the unstructured nature of code, the method leverages a pre-trained transformer-based code model, further trained through task-adaptive pre-training and fine-tuning on the downstream task of intent classification. This fine-tuned task-adapted pre-trained code model is then utilized to embed fine-grained conjoint changes in a commit, which are aggregated into a unified commit-level vector representation. The proposed method was evaluated using two BERT-based code models, i.e., CodeBERT and GraphCodeBERT, and various aggregation techniques on data from open-source Java software projects. The results show that the proposed method can be used to effectively extract commit embeddings as features for commit intent classification and outperform current state-of-the-art methods of code commit representation for intent categorization in terms of software maintenance activities undertaken by commits.
Keywords: software maintenance, code commit, mining software repositories, adaptive pre-training, fine-tuning, semantic code embedding, CodeBERT, GraphCodeBERT, classification, code intelligence
Published in DKUM: 14.08.2024; Views: 87; Downloads: 11
.pdf Full text (1,65 MB)

6.
Evaluating the usability and functionality of intelligent source code completion assistants: a comprehensive review
Tilen Hliš, Luka Četina, Tina Beranič, Luka Pavlič, 2023, original scientific article

Abstract: As artificial intelligence advances, source code completion assistants are becoming more advanced and powerful. Existing traditional assistants are no longer up to all the developers’ challenges. Traditional assistants usually present proposals in alphabetically sorted lists, which does not make a developer’s tasks any easier (i.e., they still have to search and filter an appropriate proposal manually). As a possible solution to the presented issue, intelligent assistants that can classify suggestions according to relevance in particular contexts have emerged. Artificial intelligence methods have proven to be successful in solving such problems. Advanced intelligent assistants not only take into account the context of a particular source code but also, more importantly, examine other available projects in detail to extract possible patterns related to particular source code intentions. This is how intelligent assistants try to provide developers with relevant suggestions. By conducting a systematic literature review, we examined the current intelligent assistant landscape. Based on our review, we tested four intelligent assistants and compared them according to their functionality. GitHub Copilot, which stood out, allows suggestions in the form of complete source code sections. One would expect that intelligent assistants, with their outstanding functionalities, would be one of the most popular helpers in a developer’s toolbox. However, through a survey we conducted among practitioners, the results, surprisingly, contradicted this idea. Although intelligent assistants promise high usability, our questionnaires indicate that usability improvements are still needed. However, our research data show that experienced developers value intelligent assistants highly, highlighting their significant utility for the experienced developers group when compared to less experienced individuals. The unexpectedly low net promoter score (NPS) for intelligent code assistants in our study was quite surprising, highlighting a stark contrast between the anticipated impact of these advanced tools and their actual reception among developers.
Keywords: intelligent assistants, source code completion, source code
Published in DKUM: 21.05.2024; Views: 188; Downloads: 17
.pdf Full text (590,64 KB)
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7.
The Influence of English on the Language of Croatian Influencers on YouTube, Instagram and TikTok Social Media : master's thesis
Ena Cilar, 2023, master's thesis

Abstract: The rapid spread of the English language, which is frequently referred to as a lingua franca, has had a significant impact on other languages and the peculiar language of computer-mediated communication. What is more, the Internet, social media and digital influencers are the key agents of both language change and changes in the modern society. Due to the globally growing popularity of social media influencers, the purpose of this thesis is to explore the ways in which their language use is affected by the globality of English, with a focus on Croatian influencers. Therefore, data for this paper are drawn from altogether 270 social media posts published by the eight most successful Croatian influencers on YouTube, Instagram and TikTok. The research methods include linguistic, thematic and content analysis. The results reveal that the use of ‘ad hoc loanwords’ and intra-sentential code-switching are more common among Croatian influencers in comparison with outdated Anglicisms and inter-sentential code-switching. While the most frequently used loanwords among Croatian influencers belong to the categories of cyberculture and popular culture, the use of loanwords belonging to particular semantic fields is not strongly related to their thematic content categories. The importance and originality of this thesis are that it is the first study to provide new insights into the language use of Croatian influencers in relation with English as a global and leading online language. However, due to practical constraints, it is limited in terms of the research sample size and generalizability, which offers implications for further research.
Keywords: English as a global language, influence of English on Croatian, Croatian social media influencers, computer-mediated communication, loanwords, code-switching
Published in DKUM: 04.01.2024; Views: 544; Downloads: 70
.pdf Full text (4,75 MB)

8.
Lebensgeschichten im Grenzraum. Mehrsprachigkeit und Identität im steirisch-slowenischen Sprachraum : Magisterarbeit
Anja Brelih, 2022, master's thesis

Abstract: Sprache ist nicht nur zum Kommunizieren da, sondern sie ist auch ein Teil unserer Identität, unsere Kultur und Lebensweisen. Die Lebensgeschichten im Grenzraum haben eine lange und spannende Geschichte, die sich auch noch bis heute auswirkt. Jeder Grenzraum ist einzigartig und unterscheidet sich von anderen Grenzräumen. Wir sehen uns den Grenzraum zwischen Österreich und Slowenien an, und widmen uns besonders der Mehrsprachigkeit und Identität im steirisch-slowenischen Sprachraum. Der Grenzraum zwischen der Steiermark und Slowenien war ein sehr gemischtsprachiges Gebiet, auf beiden Seiten wurde Slowenisch und Deutsch gesprochen. Erst mit der Grenzziehung wurden die Kontakte der beiden Sprachen unterbrochen. Es wurden nicht nur sprachliche Beziehungen getrennt, sondern auch familiäre und wirtschaftliche Beziehungen. Wegen der Grenzziehung entstanden Minderheiten und zwar auf beiden Seiten. Die sprachlichen Minderheiten wurden sehr lange Zeit verschwiegen, man hörte nicht gerne die jeweils andere Sprache auf seinem Gebiet. Mit der Geschichte des Grenzraums beschäftigte man sich erst in den 1980er Jahren. Auch noch heute weiß man nicht viel über die Geschichten der Menschen, die in der Nähe von der Grenze gewohnt und mit der Grenze gelebt haben. In der Arbeit werden reale Lebensgeschichten von GrenzbewohnerInnen beschrieben, die diese Entwicklungen reflektieren. Ein sehr großes Problem war, dass die Menschen früher nicht gerne über ihre Zweisprachigkeit/Mehrsprachigkeit gesprochen haben, da diese von der Mehrheitsbevölkerung negativ bewertet wurde und sie daher ihre Zwei-/Mehrsprachigkeit verbargen. Das gilt sowohl für die slowenische Minderheit in der Steiermark als auch für die deutschsprachige Minderheit in Slowenien. Mit Hilfe von Audio- und Videointerviews bekommen wir einen praktischen Blick in die Geschichten der Mehrsprachigkeit im steirisch-slowenischen Sprachraum.
Keywords: Sprache, Grenzraum, Identität, Dialekt, Code-Switching
Published in DKUM: 02.11.2022; Views: 603; Downloads: 51
.pdf Full text (3,21 MB)

9.
Software based encoder/decoder generation for data exchange optimization in the internet of things : master's thesis
Tjaž Vračko, 2022, master's thesis

Abstract: Efficient encoding of data is an important part of projects in the Internet of Things space. Communication packets must be kept as small as possible in order to minimize the power consumption of devices. In this thesis, an automatic code generation tool, irpack, is proposed that will unify the way packets are defined across all future projects at Institute IRNAS. Using a schema, this tool generates source code of encoders and decoders in target programming languages. A schema evolution system is also defined, by which changes to packets can be compatible across multiple versions. The tool is then applied to a selection of past projects to gauge its usefulness. It is determined that irpack is able to encode the same data into a similar or smaller size packet, while also providing additional versioning information.
Keywords: encoding/decoding, schema, schema evolution, bit packing, code generation
Published in DKUM: 31.01.2022; Views: 811; Downloads: 72
.pdf Full text (2,58 MB)

10.
Design of an Embedded Position Sensor with Sub-mm Accuracy : magistrsko delo
Matej Nogić, 2019, master's thesis

Abstract: This master’s thesis presents the development of a machine-vision based localization unit developed at Robert Bosch GmbH, Corporate Sector Research and Advance Engineering in Renningen, Germany. The localization unit was developed primarily for position detection purposes with three degrees of freedom in highly versatile manufacturing systems but has an immense potential to be used anywhere where a precise, low-cost localization method on a two-dimensional surface is required. The complete product development cycle was carried out, from the components selection, schematic and optical system design, to the development of machine vision algorithms, four-layer Printed Circuit Board design and evaluation using an industrial robot. Thanks to the use of a patented two-dimensional code pattern, the localization unit can cover a surface area of 49 km2. The size and speed optimized, self-developed machine-vision algorithms running on a Cortex-M7 microcontroller allow achieving an accuracy of 100 µm and 60 Hz refresh rate.
Keywords: localization, machine-vision, code pattern, image sensor, embedded system
Published in DKUM: 14.01.2020; Views: 1340; Downloads: 57
.pdf Full text (18,20 MB)

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