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AbstractPrinting technology has evolved through the past centuries due to technological progress. Within Digital Humanities, images are playing a more prominent role in research. For mass analysis of digitized historical images, bias can be introduced in various ways. One of them is the printing technology originally used. The classification of images to their printing technology e.g. woodcut, copper engraving, or lithography requires highly skilled experts. We have developed a deep learning classification system that achieves very good results. This paper explains the challenges of digitized collections for this task. To overcome them and to achieve good performance, shallow networks and appropriate sampling strategies needed to be combined. We also show how class activation maps (CAM) can be used to analyze the results.

Viola Parente-Čapková: Digitaaliset ihmistieteet kirjallisuudentutkimuksessa

Este será um estudo transversal, observacional e comparativo de jovens atletas femininas para ajudar a desenvolver duas capacidades físicas essenciais: a força e a flexibilidade. O objetivo será caracterizar descritiva e comparativamente a força e a flexibilidade de praticantes de Ginástica e de Patinagem Artística. Além disso pretendemos perceber em que medida se observavam influências mútuas entre as variáveis avaliadas. Os participantes são 35 atletas femininas de ginástica (9.8 ± 2.05 anos) e 35 atletas femininas de patinagem artística (10,57 ± 2,66 anos). Foram avaliados níveis de força e flexibilidade através da Bateria de Testes do FitEscola. O estudo comparativo paramétrico realizado sinalizou diferenças estatisticamente significativas (p=0,02) em apenas uma prova: no teste de abdominais, o seu valor (t=-2,30) sinaliza melhores resultados no grupo das patinadoras. O estudo correlacional paramétrico (r de Pearson) sinalizou correlações estatisticamente significativas entre as variáveis de desempenho, no entanto apenas encontrámos uma associação positiva (p=0,02) entre a variável grupo e a força abdominal. Os resultados obtidos mostram que não foram observáveis diferenças significativas entre ginastas e patinadoras na maioria das qualidades físicas avaliadas. A exceção foram os resultados obtidos na avaliação da força abdominal e da flexibilidade dos membros inferiores. No entanto, as pequenas diferenças que não chegam a ser significativas devem-se ao facto de nesta idade as atletas ainda não realizarem trabalhos específicos de força, sendo o enfase dado às habilidades motoras coordenativas para que a técnica seja melhorada This will be a cross-sectional, observational and comparative study of young female athletes to help develop two essential physical abilities: strength and flexibility. The objective will be to characterize descriptively and comparatively the strength and flexibility of gymnastics and figure skating practitioners. Furthermore, we intend to understand the extent to which mutual influences were observed between the evaluated variables. Participants are 35 female gymnastics athletes (9.8 ± 2.05 years) and 35 female figure skating athletes (10.57 ± 2.66 years). Levels of strength and flexibility were assessed using the FitEscola Test Battery. The comparative parametric study performed showed statistically significant differences (p=0.02) in only one test: in the sit-up test, its value (t=-2.30) indicates better results in the group of skaters. The parametric correlational study (Pearson's r) signaled statistically significant correlations between the performance variables, however we only found a positive association (p=0.02) between the group variable and abdominal strength. The results obtained show that no significant differences were observed between gymnasts and skaters in most of the physical qualities evaluated. The exception was the results obtained in the assessment of abdominal strength and lower limb flexibility. However, the small differences that are not significant are because, at this age, the athletes still do not perform more specific strength work, with the emphasis being given to coordinating motor skills so that the technique can be improved

No abstract available.

In the domain of Galleries, Libraries, Archives and Museums (GLAM) institutions, creative and innovative tools and methodologies for content delivery and user engagement have recently gained international attention. New methods have been proposed to publish digital collections as datasets amenable to computational use. Standardised benchmarks can be useful to broaden the scope of machine-actionable collections and to promote cultural and linguistic diversity. In this article, we propose a methodology to select datasets for computationally driven research applied to Spanish text corpora. This work seeks to encourage Spanish and Latin American institutions to publish machine-actionable collections based on best practices and avoiding common mistakes. This research has been funded by the AETHER-UA (PID2020-112540RB-C43) Project from the Spanish Ministry of Science and Innovation.

Contains fulltext : 240932.pdf (Publisher’s version ) (Open Access) 20 december 2021 10 p.

AbstractIn research and policies, the identification of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management. Since at present policy analysis mostly employs qualitative research methods, the following article presents and assesses different approaches – trend analysis based on questionnaires, quantitative bibliometric surveys, the use of computer-linguistic approaches and machine learning and qualitative investigations. Against this backdrop, this article examines digital applications in cultural heritage and, in particular, built heritage via various investigative frameworks to identify topics of relevance and trendlines, mainly for European Union (EU)-based research and policies. Furthermore, this article exemplifies and assesses the specific opportunities and limitations of the different methodical approaches against the backdrop of data-driven vs. data-guided analytical frameworks. As its major findings, our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies. Since policies focus on meta-topics such as digitisation, openness or automation, the research descriptors are more granular. In general, data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends. Conversely, qualitative approaches are able to answer “why” questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge, as is the case for the term “internet”.