IVUS 2026
Information Society and University Studies 2026

Table of Contents

• Preface
  Summary: There were 92 papers submitted for peer-review to this conference. Out of these, 28 papers were accepted for this volume.

Regular Papers

• Graphematic Analysis of Unsigned Manuscripts for Authorship Identification
  Maksim Iavich
  Maia Ninidze
  Tea Tvalavadze
  Maia Jangidze
• Rethinking Model Differencing for SysML v2: Challenges and Future Directions
  Gvidas Ambrozaitis
  Mantas Jurgelaitis
• Benchmarking DenseNet121, ViT-Base, and Swin-Tiny for Multiclass Mpox Skin Lesion Classification
  Mukhriddin Arabboev
  Shohruh Begmatov
  Sukhrob Bobojanov
  Nor Erne Nazira Bazin
  Akhram Nishanov
• Hawk-Dove Dynamics in Continuous Spaces: Escaping Local Optima via Game-Theoretic Swarm Regulation
  Jakub Dras
  Piotr Pilszczek
• Challenge-Based Learning in Cybersecurity Fundamental Studies
  Algimantas Venčkauskas
  Ignas Plauska
  Nerijus Šatkauskas
• Development of an Information Security Governance Framework in Fragmented Circumstances
  Maksim Iavich
  Vladimer Svanadze
  Ketevani Grdzelidze
• Anomaly Detection Approach for Cow Behavior Without Relying on a Predefined Gold Standard
  Arnas Nakrošis
  Jad Kaedbey
  Dmytro Klepachevskyi
  Marius Klumbys
  Vusal Aliyev
  Agnė Paulauskaitė-Tarasevičienė
• The Use of UML Use Case Diagrams and Their Specifications for Test Case Generation
  Ieva Valatkevičiūtė
  Lina Čeponienė
  Tomas Valatkevičius
• A Federated Graph Neural Network for Integrating Clinical, Imaging, and Genetic Data Across Hospital Systems
  Malika Baizakova
  Kadyralieva Nuraiym
• The Effect of Providing LSTM-Based Neural Networks Used for Time-Series Predictions with Relational Data
  Piotr Pilszczek
• Explainable AI for Fair and Transparent Resource Allocation in Smart Cities
  Zhibek Primova
  Gulzat Muktarkanova
• AI-Assisted Clinical Decision Support for Urology Oncology: Baseline Machine Learning Experiments on Noisy EHR Data
  Arnas Bosas
  Eglė Butkevičiūtė
• Updating the Professional Knowledge of Electronics Engineers in the Context of Rapidly Changing Technologies
  Deividas Urbonas
  Ramūnas Kubiliūnas
• Geo-Localization in OpenStreetMap-Derived Semantic Map Space Using Structural Embeddings
  Tomas Kanapickas
  Ugnius Lukošius
  Andrius Kriščiūnas
• Automated Test Generation for Microservices from UML Sequence Diagrams
  Tomas Vainoris
  Lina Čeponienė
• Towards Automated Evaluation of UML Models in Teaching Software Engineering
  Guoda Stulpinaitė
  Mantas Jurgelaitis
• Metadata Quality Governance in a Data Lake: A Case Study of Lithuania’s State Open Data Infrastructure
  Tomas Danikauskas
  Algirdas Šukys
  Milda Aksamitauskas
• Potentials of Neural Models for Wheat Disease Detection in Precision Agriculture
  Yuliya Averyanova
  Maxim Ivanytskyi
  Yevheniia Znakovska
  Nadiia Sauliak
  Danyil Klokta
• Can Structured Prompting Overcome Knowledge Bias in Vision-Language Models?
  Kyrylo Kolesnichenko
  Martas Ambraziunas
• An Algorithm Inspired by the Ant Colony System for Solving N × N Sliding Puzzles
  Bohdan Kostyk
• Generative Data Augmentation for Dual-Plane Monocular Depth Estimation of Non-Lambertian Surfaces
  Vilius Bankauskas
  Andrius Kriščiūnas
• A Conceptual Architecture for Confidential Feature Engineering: Integrating TEE and Blockchain for Privacy-Preserving IoT Analytics
  Artem Kipin
  Akylai Zhumabekova
  Al Khan
• Causal Ablation Analysis: Isolating Pathological Features from Spurious Correlations in Dermatoscopic Diagnosis
  Al Khan
  Ainur Mukhiyadin
• From Pixels to Graphs: Grid and Superpixel Graph Construction for Drone-Bird Image Classification Using Graph Neural Networks
  Zofia Wawrzos
• A Unified Classification Model for Quantum-Enabled Cyberattacks
  Simas Krušniauskas
  Šarūnas Grigaliūnas
  Rasa Brūzgienė
• SISSRP: A Post-Quantum Augmented PAKE Based on the Short Integer Solution Problem
  Sergei Simonovi
  Giorgi Iashvili
  Avtandil Gagnidze
  Malkhaz Bibiluri
• The 15-Puzzle: From Solvability Check to Fast Sub-Optimal Solution Search
  Bohdan Kostyk
• Mathematical Optimization of Loan Approval Neural Networks via First-Order Taylor Pruning and Affine Quantization
  Jakub Dras