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Computation and the Humanities: Towards an Oral History of Digital Humanities

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Book Series: Springer Series on Cultural Computing ISSN: 2195-9056 ISBN: 9783319201696 9783319201702 Year: Pages: 285 DOI: 10.1007/978-3-319-20170-2 Language: English
Publisher: Springer Nature
Subject: Arts in general --- Computer Science
Added to DOAB on : 2017-03-02 09:53:09
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This book addresses the application of computing to cultural heritage and the discipline of Digital Humanities that formed around it. Digital Humanities research is transforming how the Human record can be transmitted, shaped, understood, questioned and imagined and it has been ongoing for more than 70 years. However, we have no comprehensive histories of its research trajectory or its disciplinary development. The authors make a first contribution towards remedying this by uncovering, documenting, and analysing a number of the social, intellectual and creative processes that helped to shape this research from the 1950s until the present day.By taking an oral history approach, this book explores questions like, among others, researchers’ earliest memories of encountering computers and the factors that subsequently prompted them to use the computer in Humanities research.Computation and the Humanities will be an essential read for cultural and computing historians, digital humanists and those interested in developments like the digitisation of cultural heritage and artefacts.

Cognitive Supervision for Robot-Assisted Minimally Invasive Laser Surgery

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Book Series: Springer Theses ISSN: 2190-5053 ISBN: 9783319303291 9783319303307 Year: Pages: 99 DOI: 10.1007/978-3-319-30330-7 Language: English
Publisher: Springer Nature
Subject: Medical technology
Added to DOAB on : 2016-12-20 12:03:50
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This thesis lays the groundwork for the automatic supervision of the laser incision process, which aims to complement surgeons’ perception of the state of tissues and enhance their control over laser incisions. The research problem is formulated as the estimation of variables that are representative of the state of tissues during laser cutting. Prior research in this area leveraged numerical computation methods that bear a high computational cost and are not straightforward to use in a surgical setting. This book proposes a novel solution to this problem, using models inspired by the ability of experienced surgeons to perform precise and clean laser cutting. It shows that these new models, which were extracted from experimental data using statistical learning techniques, are straightforward to use in a surgical setup, allowing greater precision in laser-based surgical procedures.

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