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72. Exploring the Effects of Multimodal User Interfaces in Autonomous VehiclesKristina Stojmenova Pečečnik, Timotej Gruden, Grega Jakus, Sašo Tomažič, Jaka Sodnik, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This short paper presents a study design created to explore how multimodal user interfaces (UIs) influence comfort, user experience, and overall well-being in fully autonomous vehicles. The study uses a motion-based driving simulator equipped with real vehicle components to provide realistic driving conditions. Participants are asked to complete two trials: a baseline trial and one with either a simple or extended multimodal UI combining auditory, tactile, and speech-based feedback. Driving scenarios include lane changes, emergency braking, V2X and V2V communication, and road surface variations. Data collection integrates physiological measures (EGG, EDA, PPG), self-assessment questionnaires on motion sickness (MSAQ) and user experience (UEQ), and performance on a reading comprehension task simulating non-driving activities. The paper provides some initial data about the participants’ demographics and their user experience with the UI, and gives an insight into the planned nest steps in terms of analysis and results application. The findings from this study will provide an insight into the potential of multimodal HMI design to enhance safety, comfort, and user acceptance in autonomous vehicles.
Ključne besede: user interface, autonomous vehicle, multimodal interaction, non-driving related task
Objavljeno v RUP: 30.01.2026; Ogledov: 196; Prenosov: 0
 Celotno besedilo (397,64 KB) |
73. Inferring a Mobile User’s Valence and Arousal through On-Screen Text AnalysisEdita Džubur, Veljko Pejović, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: Understanding a user’s emotional state is critical for building adaptive and intelligent mobile applications. In this paper we investigate the feasibility of inferring valence and arousal from the text displayed on smartphone screens. We developed AV-Sense, a mobile application that combines the Experience Sampling Method, a technique that prompts users to report their feelings in the moment, with passive screentext logging. In a two-week study with 12 participants, we collected 787 ESM responses and over 650,000 screentext entries. Data analysis revealed meaningful temporal and individual patterns in reported affect. We then explored the use of large language models to predict valence and arousal from screentext, but results indicated limited predictive power in this setting. Our findings highlight both the potential and current challenges of screentext-based affect inference, laying the groundwork for future research on emotion-aware applications and naturalistic psychological studies.
Ključne besede: text analysis, experience sampling method, screentext sensing, valence, arousal, large language models
Objavljeno v RUP: 30.01.2026; Ogledov: 219; Prenosov: 0
Celotno besedilo (350,11 KB) |
74. Transparent Persona Generation With LLMs : An Evidence-based and Traceable Method for User-centred DesignBojan Blažica, Manca Topole, Marko Debeljak, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: Personas are a cornerstone of user-centred design, but traditional methods for developing them are difficult to validate, prone to bias and labour-intensive. Data-driven approaches have improved scalability, but often lack the narrative richness and empathy that make personas effective. We present a methodology that uses large language models (LLMs) to accelerate the creation of personas while underpinning and constraining the results with contextual and empirical data. Our approach emphasises transparency and traceability: each generated persona attribute can be linked to its source material, including project documentation, workshop transcripts, survey results or other contextual corpora. By combining the narrative strengths of LLMs with the rigour of an evidence-based foundation, the method generates personas that are both descriptive and verifiable. We present a five-step workflow methodology: (1) generation of persona candidates from contextual data using LLMs, (2) iterative refinement to ensure representativeness of personas, (3) selection of the most relevant profiles through expert evaluation, (4) design of detailed persona profiles, and (5) enrichment with empirical evidence to ensure traceability and validation. The methodology is illustrated with a case study from the field of soil health, but can also be applied to other design contexts where alignment between different stakeholders is crucial. We argue that this approach positions LLMs not as a substitute for human expertise, but as an accelerator of persona work that improves accountability, reduces bias and facilitates communication in collaborative design processes.
Ključne besede: personas, large language model, traceability, user-centered design, decision support systems
Objavljeno v RUP: 30.01.2026; Ogledov: 188; Prenosov: 2
Celotno besedilo (275,89 KB) |
75. NERVIS : An Interactive System for Graph-Based Exploration and Editing of Named EntitiesUroš Šmajdek, Ciril Bohak, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: We present an interactive visualization system for exploring named entities and their relationships across document collections. The system is designed around a graph-based representation that integrates three types of nodes: documents, entity mentions, and entities. Connections capture two key relationship types: (i) identical entities across contexts, and (ii) co-locations of mentions within documents. Multiple coordinated views enable users to examine entity occurrences, discover clusters of related mentions, and explore higher-level entity group relationships. To support flexible and iterative exploration, the interface offers fuzzy views with approximate connections, as well as tools for interactively editing the graph by adding or removing links, entities, and mentions, as well as editing entity terms. Additional interaction features include filtering, mini-map navigation, and export options to JSON or image formats for downstream analysis and reporting. This approach contributes to human-centered exploration of entity-rich text data by combining graph visualization, interactive refinement, and adaptable perspectives on relationships.
Ključne besede: Named Entity Visualization, Graph Exploration, Interactive Visualization
Objavljeno v RUP: 30.01.2026; Ogledov: 184; Prenosov: 0
Celotno besedilo (839,67 KB) |
76. Integration of Hybrid Animation in a 360-degree EnvironmentAleksandar Ilievski, Suzana Žilič Fišer, Simon Kolmanič, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This paper addresses the lack of an existing pipeline for integrating Hybrid Animation in a 360-degree environment. While works like Google Spotlight’s Pearl showcase the expressive potential of cinematic VR (Virtual Reality) animation using stylized NPR (Non-Photorealistic Rendering) techniques, they lack the integration of 2D visual elements. We propose a pipeline that leverages accessible tools, including Blender’s Grease Pencil for 2D animation, NPR shading for stylized 3D rigs, and a 360-degree render using a metadata injector. Our framework makes hybrid 360-degree animation more accessible and adaptable, enabling future developments and creative applications.
Ključne besede: Virtual Reality, Hybrid Animation, 360-degree video, Blender, Non-photorealistic Rendering
Objavljeno v RUP: 30.01.2026; Ogledov: 189; Prenosov: 1
Celotno besedilo (211,63 KB) |
77. Optimizing Product Catalogue Design : A Comparative Study of Traditional Photography and 3D ModelingSimon Kolmanič, Jan Hrašar, Štefan Horvat, Domen Mongus, 2025, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: This study examines the replacement of traditional studio photography with a 3D modelling and rendering workflow in product catalogue production. Using the case of Urnes, a manufacturer of wooden urns, we compared the two approaches in terms of time, cost, and visual fidelity. The 3D pipeline, combining Blender, Substance 3D Painter, and InDesign, reduced preparation time per variation from 179 minutes to 36 minutes—a 4.9-fold improvement. After an initial 50-hour setup, subsequent catalogue updates achieved time savings of 97.6%. An informal interview with 38 professional users confirmed that 3D renderings matched or exceeded photographs in colour and texture accuracy. Results demonstrate that 3D workflows significantly lower production costs, accelerate updates, and support product personalisation, positioning them as a sustainable alternative to photography in catalogue design.
Ključne besede: Product Catalogue Design, Computer Generated Imagery, Visual Fidelity, Cost Reduction
Objavljeno v RUP: 30.01.2026; Ogledov: 190; Prenosov: 0
Celotno besedilo (689,35 KB) |
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79. Designing the ideal political identity questionnaire using machine learning and ideology scalesAna Nikolić, Uroš Sergaš, Marko Tkalčič, 2025, objavljeni znanstveni prispevek na konferenci (vabljeno predavanje) Opis: Political ideology shapes beliefs, behavior and attitudes toward society. Many existing questionnaires for measuring ideology are lengthy, repetitive, and misaligned with self-perception. This paper investigates whether a shorter, reliable, two-dimensional political identity questionnaire can be created using machine learning and psychometric methods. Sixty participants completed four ideological instruments (MFQ, SDO, RWA and 8values). Lasso regression and Random Forest with nested cross-validation identified predictive items, while psychometric evaluation included CFA and Cronbach’s alpha. Random Forest outperformed Lasso. Internal reliability was excellent and factor loadings supported a two-factor structure despite moderate model it. Findings show that ideology can be measured efficiently with reduced items, supporting applications in research, digital platforms and political psychology.
Ključne besede: political ideology, questionnaire design, machine learning, psychometrics
Objavljeno v RUP: 30.01.2026; Ogledov: 167; Prenosov: 2
Celotno besedilo (189,01 KB) |
80. Real-time gesture transmission with a robotic hand : embodied signals for non-verbal remote communicationLea Pajnič, Matjaž Kljun, Anuradhi Maheshya W. Weerasinghe Arachchillage, Klen Čopič Pucihar, 2025, objavljeni znanstveni prispevek na konferenci Opis: This work explores how computer vision and robotics can support remote, gesture-based embodied signals for expressing presence and emotion in remote communication. We present an initial proof-of-concept in which users interact through robotic hands placed on their desks: one user’s hand gestures are captured in real time by a camera, transmitted over a network, and reproduced by a robotic hand at the remote location. The prototype uses the InMoov robotic hand and MediaPipe Hands for gesture tracking across varied lighting conditions, viewing angles, and backgrounds. Our preliminary tests demonstrate that gestures can be reliably recognised and consistently reproduced through stable network communication. While still at an early stage, this project illustrates the potential of combining affordable robotics with computer vision to create accessible alternatives to voice communication and new forms of remote communication.
Ključne besede: robotic hand, gesture transmission, embodied signals, non-verbal communication, remote communication, computer vision
Objavljeno v RUP: 30.01.2026; Ogledov: 183; Prenosov: 2
Celotno besedilo (642,14 KB) |
