http://hdl.handle.net/11089/7 2026-04-07T03:58:51Z http://hdl.handle.net/11089/57010 Various Representations of Geometric Objects in Spatial Relational and Spatial Object-Relational Databases Management Systems Stasiak, Aleksandra In this paper we look at various kinds of representations of geometric objects in spatial relational (or object-relational) database management systems. We confront it with Simple Feature Access and SQL/MM (Part: 3) standards. We also try to fnd out some other representations of geometric objects that are used not only in traditional spatial database management systems but also in some NoSQL databases. We indicate functions and methods related to geometry representations such as WKT, WKB, GML, GeoJSON, GeoHash, KML, EWKT, EWKB, TWKB, HEXEWKB used in MySQL, Oracle XE and PostGIS/PostgreSQL. We illustrate this with examples, also showing some ideas for importing/exporting geometries between these database management systems. 2025-12-17T00:00:00Z http://hdl.handle.net/11089/57009 The Dialogical Nature of Iwona Chmielewska’s Picturebooks – Aesthetic and Pedagogical Context Ludwiczak, Joanna Stanisława The issue of art for children as a subject of research has a tradition dating back to the beginnings of the aesthetic-pedagogical movement in Europe. One of the contemporary examples of art for children is the picturebook. As an artefact of visual culture, it fts in particularly well with the current issues of aesthetic education for children. The aim of the presented interpretation is to identify the attributes of Iwona Chmielewska’s work that are important in the context of a child’s encounter with art. The unique form of the phenomenon described, inherent to works of art, responds to the child’s natural characteristics and ofers them full participation in co-creating the work. 2025-12-17T00:00:00Z http://hdl.handle.net/11089/57008 A Stacked Meta Neural Network with Adaptive Nonlinear Decision Fusion for Cardiovascular Disease Prediction Liyanage, Himanshi; Lipnicka, Marta; Kaźmierczak, Szymon Cardiovascular disease (CVD) remains a leading global cause of mortality, emphasizing the need for reliable early prediction systems. This study proposes a Stacked Meta Neural Network (SMNN) that integrates multiple machine learning classifers through nonlinear decision fusion. In the frst stage, six base models generate probabilistic outputs using a k-fold out-of-fold (OOF) strategy. These are then combined by a shallow Artifcial Neural Network (ANN) meta-learner to capture hidden nonlinear interactions. Experimental evaluation on a dataset of over 66,000 records achieved strong performance, with high recall and balanced ROCAUC, demonstrating the SMNN’s efectiveness as a robust and generalizable tool for CVD risk prediction. 2025-12-17T00:00:00Z http://hdl.handle.net/11089/57007 Scalability and Stability of Ethereum Layer-2 Networks: A Comparative Analysis of Scroll, Linea, and Base Rollups Iwanicki, Arkadiusz The article presents an empirical comparison of three contemporary Layer-2 scaling solutions for the Ethereum blockchain: Scroll, Linea, and Base, representing zk-rollup and optimistic rollup architectures. The study aims to evaluate the transaction processing speed and stability of selected Layer-2 networks using real-time data collected from blockchain explorers (Blockscout, Lineascan, Basescan). The dataset comprises 45,000 transactions processed in October 2025 and aggregated at one-second resolution (1 Hz). Statistical analyses include ANOVA, Kruskal–Wallis, Levene, and Brown–Forsythe tests, as well as ADF and KPSS stationarity diagnostics, used to assess diferences in throughput and operational stability across the examined networks. The results indicate that the Base network achieves the highest mean throughput (≈ 102 TPS) and the lowest temporal volatility, whereas Linea and Scroll exhibit non-stationary, highly variable transaction dynamics driven by periodic batching. The fndings confrm the persistence of the scalability trilemma—where improvements in performance may come at the cost of higher centralization and operational dependency. This research contributes to the quantitative assessment of rollup efciency and provides a reference point for further empirical studies on blockchain scalability. 2025-12-17T00:00:00Z