Search Results (503)

Early printed books, particularly incunabula, are invaluable archives of the beginnings of modern educational systems. However, their complex layouts, antique typefaces, and page degradation caused by bleed-through and ink fading pose significant challenges for automatic transcription. In this work, we present a modular pipeline that addresses these problems by combining modern layout analysis and language modeling techniques. The pipeline begins with historical layout-aware text segmentation using Kraken, a neural network-based tool tailored for early typographic structures. Initial optical character recognition (OCR) is then performed with Kraken’s recognition engine, followed by post-correction using a fine-tuned ByT5 transformer model trained on manually aligned line-level data. By learning to map noisy OCR outputs to verified transcriptions, the model substantially improves recognition quality. The pipeline also integrates a preprocessing stage based on our previous work on bleed-through removal using robust statistical filters, including non-local means, Gaussian mixtures, biweight estimation, and Gaussian blur. This step enhances the legibility of degraded pages prior to OCR. The entire solution is open, modular, and scalable, supporting long-term preservation and improved accessibility of cultural heritage materials. Experimental results on 15th-century incunabula show a reduction in the Character Error Rate (CER) from around 38% to around 15% and an increase in the Bilingual Evaluation Understudy (BLEU) score from 22 to 44, confirming the effectiveness of our approach. This work demonstrates the potential of integrating transformer-based correction with layout-aware segmentation to enhance OCR accuracy in digital humanities applications. Full article

The Tree–Seed Algorithm (TSA) is a symmetry-driven metaheuristic algorithm that shows potential for complex optimization problems, but it suffers from local optimum entrapment and slow convergence. To address these limitations, we propose the ADTSA algorithm. First, ADTSA adopts a symmetry-driven dual-layer framework for seed generation, which promotes effective information exchange between subpopulations and accelerates convergence speed. In later iterations, ADTSA enhances the population’s exploitation ability through a population fusion mechanism, further improving the convergence speed. Moreover, we propose a historical optimal solution archiving and replacement mechanism, along with a t-distribution perturbation mechanism, to enhance the algorithm’s ability to escape local optima. ADTSA also strengthens population diversity and avoids local optima through convex lens symmetric reverse generation based on the optimal solution. With these mechanisms, ADTSA converges more effectively to the global optimum during the evolutionary process. Tests on the IEEE CEC 2014 benchmark functions showed that ADTSA outperformed several top-performing algorithms, such as LSHADE, JADE, LSHADE-RSP, and the latest TSA variants, and it also excelled in comparison with other optimization algorithms, including GWO, PSO, BOA, GA, and RSA, underscoring its robust performance across diverse testing scenarios. The proposed ADTSA’s applicability in solving complex constrained problems was also validated, with the results showing that ADTSA achieved the best solutions for these complex problems. Full article

Eutrophication has intensified in lacustrine systems across the American continent, which has been primarily driven by human activities such as intensive agriculture, wastewater discharge, and land-use change. This phenomenon adversely affects water quality, biodiversity, and ecosystem functioning. However, studies addressing the historical evolution of trophic states in lakes and reservoirs remain limited—particularly in tropical and subtropical regions. In this context, sedimentary records serve as invaluable archives for reconstructing the environmental history of water bodies. Paleolimnological approaches enable the development of robust chronologies to further analyze physical, geochemical, and biological proxies to infer long-term changes in primary productivity and trophic status. This review synthesizes the main methodologies used in paleolimnological research focused on trophic state reconstruction with particular attention to the utility of proxies such as fossil pigments, diatoms, chironomids, and elemental geochemistry. It further underscores the need to broaden spatial research coverage, fostering interdisciplinary integration and the use of emerging tools such as sedimentary DNA among others. High-resolution temporal records are critical for disentangling natural variability from anthropogenically induced changes, providing essential evidence to inform science-based lake management and restoration strategies under anthropogenic and climate pressures. Full article

This research aims to investigate the Italian architectural heritage in Brazil through the analysis of the ‘Santa Casa de Misericórdia’ hospital in São Carlos, in the state of São Paulo. As part of the KNOW.IT national project, the work aims to recover and digitally enhance Italian heritage abroad from the 19th and 20th centuries. The buildings analysed were either designed or built by Italian architects who emigrated to South America or constructed using materials and techniques typical of Italian architecture of those years. The hospital, designed by the Italian architect Samuele Malfatti in 1891, was chosen for its historical value and its role in the urban context of the city of São Carlos, which, moreover, continues to perform its function even today. The study aims to create a digital archive with 3D models and two-dimensional graphical drawings. The methodology includes historical analysis, photogrammetric survey, and digital modelling using Agisoft Metashape and 3DF Zephyr software. A total of 636 images were processed, with the maximum resolution achieved in the models being 3526 × 2097 pixels. The results highlight the influence of Italian architecture on late 19th-century São Carlos and promote its virtual accessibility and wide-ranging knowledge. Full article

Processing ancient text images presents significant challenges due to severe visual degradation, missing glyph structures, and various types of noise caused by aging. These issues are particularly prominent in Chinese historical documents and stone inscriptions, where diverse writing styles, multi-angle capturing, uneven lighting, and low contrast further hinder the performance of traditional OCR techniques. In this paper, we propose a unified neural framework, UniText, for the detection, recognition, and glyph restoration of Chinese characters in images of historical documents and inscriptions. UniText operates at the character level and processes full-page inputs, making it robust to multi-scale, multi-oriented, and noise-corrupted text. The model adopts a multi-task architecture that integrates spatial localization, semantic recognition, and visual restoration through stroke-aware supervision and multi-scale feature aggregation. Experimental results on our curated dataset of ancient Chinese texts demonstrate that UniText achieves a competitive performance in detection and recognition while producing visually faithful restorations under challenging conditions. This work provides a technically scalable and generalizable framework for image-based document analysis, with potential applications in historical document processing, digital archiving, and broader tasks in text image understanding. Full article

The digitisation of cultural heritage has transformed how GLAM (Galleries, Libraries, Archives and Museums) institutions manage and share collections. Digital catalogues are indispensable for documenting and granting public access to cultural assets. However, integrating spatial data remains challenging due to the ambiguity, uncertainty, granularity, and heterogeneity of historical data. This study addresses these issues through a case study on the Museo de América’s “Place of Provenance” data, proposing a methodology for data cleaning and evaluating geocoding accuracy using Nominatim, ArcGIS, and GeoNames APIs. We assess these APIs by quantifying geocoding errors through a “balance sheet” method, identifying instances of over-representation, under-representation, or neutral results for geographical regions. The effectiveness of each API is analysed using confusion matrices and interactive cartograms, offering insights into misallocations. Our findings reveal varying accuracy among the APIs in processing heterogeneous historical spatial data. Nominatim achieved a 40.91% neutral result in correctly geocoding countries, underscoring challenges in spatial data representation. This research provides valuable methodological experiences and insights for researchers and GLAM institutions working with cultural heritage datasets. By enhancing spatial dispersion visualisation, this work contributes to understanding cultural circulations and historical patterns. This interdisciplinary work was developed as part of the ClioViz project, integrating Data Science, data Visualisation, and art history. Full article

Every minute, vast amounts of video and image data are uploaded worldwide to the internet and social media platforms, creating a rich visual archive of human experiences—from weddings and family gatherings to significant historical events such as war crimes and humanitarian crises. When properly analyzed, this multimodal data holds immense potential for reconstructing important events and verifying information. However, challenges arise when images and videos lack complete annotations, making manual examination inefficient and time-consuming. To address this, we propose a novel event-based focal visual content text attention (EFVCTA) framework for automated past event retrieval using visual question answering (VQA) techniques. Our approach integrates a Long Short-Term Memory (LSTM) model with convolutional non-linearity and an adaptive attention mechanism to efficiently identify and retrieve relevant visual evidence alongside precise answers. The model is designed with robust weight initialization, regularization, and optimization strategies and is evaluated on the Common Objects in Context (COCO) dataset. The results demonstrate that EFVCTA achieves the highest performance across all metrics (88.7% accuracy, 86.5% F1-score, 84.9% mAP), outperforming state-of-the-art baselines. The EFVCTA framework demonstrates promising results for retrieving information about past events captured in images and videos and can be effectively applied to scenarios such as documenting training programs, workshops, conferences, and social gatherings in academic institutions Full article

Preserving cultural heritage can be efficiently supported by structured and semantic representation of historical artifacts. Bookbinding, a critical aspect of book history, provides valuable insights into past craftsmanship, material use, and conservation practices. However, existing bibliographic records often lack the depth needed to analyze bookbinding techniques, provenance, and preservation status. This paper presents a proof-of-concept system that explores how Large Language Models (LLMs) can support knowledge graph engineering within the context of 19th-century Greek bookbinding (1830–1900), and as a result, generate a domain-specific ontology and a knowledge graph. Our ontology encapsulates materials, binding techniques, artistic styles, and conservation history, integrating metadata standards like MARC and Dublin Core to ensure interoperability with existing library and archival systems. To validate its effectiveness, we construct a Neo4j knowledge graph, based on the generated ontology and utilize Cypher Queries—including LLM-generated queries—to extract insights about bookbinding practices and trends. This study also explores how semantic reasoning over the knowledge graph can identify historical binding patterns, assess book conservation needs, and infer relationships between bookbinding workshops. Unlike previous bibliographic ontologies, our approach provides a comprehensive, semantically rich representation of bookbinding history, methods and techniques, supporting scholars, conservators, and cultural heritage institutions. By demonstrating how LLMs can assist in ontology/KG creation and query generation, we introduce and evaluate a semi-automated pipeline as a methodological demonstration for studying historical bookbinding, contributing to digital humanities, book conservation, and cultural informatics. Finally, the proposed approach can be used in other domains, thus, being generally applicable in knowledge engineering. Full article

This paper outlines a methodology for creating an educational and informative communication system for non-specialised audiences in order to preserve and pass on the heritage of ideas and practices adopted in the medieval political and administrative sphere. Through the combined use of digital technologies (such as GISs, 3D modelling and virtual tours), historical sources can potentially reveal how political and administrative aspects affected different areas within the medieval city, not just the main seats of power. Bologna, a prestigious medieval university metropolis, is chosen as a case study because of the remarkable wealth of documentation in its archives from the city’s political culture in the Middle Ages. Written historical sources, including documentary and narrative texts, are among the primary tools employed in the study of European medieval urban communities in general. Documentary sources help us understand and reconstruct the complexities of civic administration, urban policies and the economy, as well as how citizens experience them daily. The involvement of citizens in the political and administrative life of late medieval cities is explored through the management and digital processing of historical documentation. Digital humanities tools can facilitate this analysis, offering a perspective that sheds light on the formation of the pre-modern state. Although digital databases and repositories have significantly contributed to preserving and digitally archiving historical sources, these are often aimed exclusively at the academic level and remain underutilised as privileged didactic and educational tools for a broad audience. Full article

In architectural heritage conservation, fragmented data practices and heterogeneous formats hinder knowledge extraction, limiting the translation of raw data into actionable conservation insights. This study proposes a knowledge-centric framework integrating smart data methodologies to bridge this gap. The framework synergizes Heritage Building Information Modeling (HBIM), semantic knowledge graphs, and knowledge bases, prioritizing three interconnected dimensions: geometric digitization through 3D laser scanning and parametric HBIM reconstruction, semantic enrichment of historical texts via NLP and rule-based entity extraction, and knowledge graph-driven discovery of spatiotemporal patterns using Neo4j and ontology mapping. Validated through dual case studies—the Historical Educational Sites in South China (humanistic narratives) and the Dong ethnic drum towers (structural logic)—the framework demonstrates its capacity to automate knowledge generation, converting 20.5 GB of multi-source data into 2652 RDF triples that interconnect 1701 nodes across HBIM models and archival records. By enabling real-time visualization of semantic relationships (e.g., educator networks, mortise-and-tenon typologies) through graph queries, the system enhances interdisciplinary collaboration. Furthermore, the proposed smart data framework facilitated the generation of domain-specific knowledge through systematic data valorization, yielding actionable insights for architectural conservation practice. This research redefines conservation as a knowledge-to-action paradigm, where smart data methodologies unify tangible and intangible heritage values, fostering data-driven stewardship across cultural, historical, and technical domains. Full article

The Shu-Sarysu Basin in central-southern Kazakhstan remains one of the underexplored gas-prone provinces, with 12 discovered gas fields including Amangeldy (884 Bcf) and Pridorozhnoye (225 Bcf). In the context of global energy transition, such basins require integrated geological assessment to constrain exploration potential. Historical studies within the region were spatially limited and prematurely discontinued, resulting in fragmented datasets and a lack of modern interpretation. This review reassesses published geological data within a petroleum systems framework, applying contemporary geodynamic and stratigraphic concepts. Analysis shows that tectonostratigraphic evolution of the basin during Devonian–Permian time (390–250 Ma) favored formation of mature, gas-prone systems within structurally compartmentalized troughs, with effective source, reservoir, and seal configurations. Building on these findings, a three-tier classification of exploration zones is proposed based on system maturity, trap integrity, and gas shows, reflecting geological success probability. This provides a basis for prioritizing future exploration despite limited seismic and drilling coverage in many areas. Recommended priorities include digitization of archival data, structural modeling, modern geochemical and diagenetic analysis, and focused evaluation of promising areas to support future exploration. Full article

This article sheds light on the historical dyeing traditions of rural inhabitants of the Eastern Baltic region. The 19th- and early 20th-century Estonian archival sources mention that rotted alder buckthorn (Frangula alnus Mill.) bark was used to dye woollen yarn red. The bark was rotted by leaving it outside for weeks or months before dyeing. Although dyeing red with alder buckthorn bark by fermenting it in wood ash lye is well known, the combination of rotting the bark and using the boiling method to dye red has not been reported. Practical experiments testing shorter and longer-term rotting of alder buckthorn bark both on and under the ground were conducted. Woollen yarns were dyed with rotted bark using the boiling method and were tested for lightfastness and alkaline pH sensitivity, and analysed using HPLC-DAD. The results show that rotting alder buckthorn bark has a strong effect on the achievable colours and that woollen yarns can be dyed different shades of red. The colours were sensitive to alkaline pH and their light fastness varied from very low to good. HPLC-DAD analysis showed that the pretreatment of the bark affected not only the colour but also the dye composition of the dyed wool. Full article

The conservation and intervention of heritage structures require a flexible, interdisciplinary environment capable of managing data throughout the building’s life cycle. Historic building information modeling (HBIM) has emerged as an effective tool for supporting these processes. Originally conceived for parametric construction modeling, BIM can also integrate historical transformations, aiding in maintenance and preservation. Historic buildings often feature complex geometries and visible material traces of time, requiring detailed analysis. This research proposes a methodology for documenting and assessing the envelope of historic buildings by locating, classifying, and recording transformations, deterioration, and structural deformations. The approach is based on semantic segmentation and classification using data from terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs), applied to the Palace of Miguel de Mañara—an iconic 17th-century building in Seville. Archival images were integrated into the HBIM model to identify previous restoration interventions and assess current deterioration. The methodology included geometric characterization, material mapping, semantic segmentation, diagnostic input, and temporal analysis. The results validated a process for detecting pathological cracks in masonry facades, providing a collaborative HBIM framework enriched with expert-validated data to support repair decisions and guide conservation efforts. Full article

In the wake of the Holocaust and the post-war reconstruction of Greece’s historic city centers, many Greek synagogues were demolished, abandoned, or appropriated, erasing centuries of Jewish architectural and communal presence. This study presents a thirty year-long research and documentation initiative aimed at preserving, recovering, and eventually digitally reconstructing these “lost” synagogues, both as individual buildings and within their urban context. Drawing on architectural surveys, archival research, oral histories, and previously unpublished materials, including the recently rediscovered Shemtov Samuel archive, the project grew through the use of technology. Beginning with in situ surveys in the early 1990s, it evolved into full-scale digitally enhanced architectural drawings that formed the basis for further digital exploration, 3D models, and virtual reality outputs. With the addition of these new tools to existing documentation, the project can restore architectural detail and cultural context with a high degree of fidelity, even in cases where only fragmentary evidence survives. These digital reconstructions have informed physical restoration efforts as well as public exhibitions, heritage education, and urban memory initiatives across Greece. By reintroducing “invisible” Jewish landmarks into contemporary consciousness, the study addresses the broader implications of post-war urban homogenization, the marginalization of minority heritage, and the ethical dimensions of digital preservation. This interdisciplinary approach, which bridges architectural history, digital humanities, urban studies, and cultural heritage, demonstrates the value of digital tools in reconstructing “lost” pasts and highlights the potential for similar projects in other regions facing comparable erasures. Full article

Ludwig Wittgenstein kept a box file titled “Nonsense Collection” that is now archived in the Research Institute Brenner-Archiv. Several items in this collection concern both science and religion (or spiritualism). Although Wittgenstein may have thought of them as jokes, these items do reflect his thoughts on the relationship between science and religion. In this paper, three items from the Nonsense Collection that touch both science and religion are presented. It will discuss first why these items are nonsensical by applying interpretation of the concept of nonsense given by McGuinness. Then it will take up different ideas of Wittgensteinian philosophy of religion proposed by Pichler, Schönbaumsfeld, Somavilla, and Sunday Grève; it shows that the items presented in this paper would also be nonsensical, according to this kind of philosophy of religion. It concludes with historical and modern cases that also show dysfunctional relationships between science and religion and that these cases may have found their way into the Nonsense Collection. Full article