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    286 research outputs found

    The interdisciplinary analysis of the cemetery Kudachurt 14 (North Caucasian Bronze Age): Database, appendix and catalogues

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    Representing both a barrier and a corridor between the Eurasian and Asian continents, the Caucasus has constituted the setting for various socio-economic transformations throughout prehistory. The transition from the Middle to the Late Bronze Age in the Northern Caucasus is a period characterised by a shift from pastoral lifeways in the steppe to sedentary lifestyles in the high mountains, and the change from hierarchical to egalitarian societies. In this context, this data collection provides basic scientific research on social inequality, demography, oral health, and diet of humans that lived between 2200-1650 BCE in the central North Caucasian foothills. Due to the outstanding preservation of its archaeological and human remains, the cemetery Kudachurt 14 represents a hitherto missing link for a transformative period in this region

    SeedCat in ArchaeoBotLand: Kirleis, Wiebke (2019) Atlas of Neolithic Plant Remains from Northern Central Europe

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    Data Collection is part of ArchaeoBotLand. Catalogue of photographs of archaeological and modern plant parts taken by and for Kiel archaeobotanists

    3D surface scan data (file format: *.sur) of mandibles from crickets that received specific pelleted diets in a controlled feeding experiment

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    This is the accompanying filtered surface data of cricket mandibles associated with the publication “Mandible microwear texture analysis of crickets raised on diets of different abrasiveness reveals universality of diet-induced wear” by Daniela E. Winkler, Hitomi Seike, Shinji Nagata, and Mugino O. Kubo, pblished in Interface Focus, DOI: 10.1098/rsfs.2023.0065

    SowOrientation: An Image Dataset for the Automated detection of Sow Body Parts and Newborn Piglets

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    If you use this dataset, please reference: Wutke, M., Lensches, C., Hartmann, U. and Traulsen, I., 2024. Towards automatic farrowing monitoring - a Noisy Student approach for improving detection performance of newborn piglets, PLOS ONE, 10.1371/journal.pone.031081

    Instance-level Medical Image Classification for Text-based Retrieval in a Medical Data Integration Center

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    A medical data center receives a large volume of medical images from various clinical departments, encompassing X-rays, CT scans, and MRI scans. Ideally, all images should be properly filled in indexing fields with standard clinical terms. Nonetheless, some of these images attached with bad annotation or even missed the complete annotation, posing challenges in search functionality and data integration tasks in a medical data center. To tackle this issue, accurate and meaningful descriptors are needed for these indexing fields, so that users can efficiently search for their desired images and integrate them to other international standards. This paper aims to provide concise annotation in missing or incorrect indexing fields with essential instance-level information, including radiology modalities (e.g. X-rays), anatomical regions (e.g. chest), and body orientations (e.g. lateral), by using a deep learning classification method. In order to showcase the capability of our deep learning algorithm in generating annotations for indexing fields, we conducted three experiments. These experiments utilized two open-source datasets, namely the ROCO dataset and the IRMA dataset, along with a custom SNOMED CT dataset. While the outcomes of the three experiments are satisfying in the context of less critical tasks and serve as a valuable testing ground for image retrieval, they also highlight the need for further exploration of potential challenges. This essay further elaborates on the identified issues and presents well-founded recommendations aimed at refining and advancing our proposed approach

    Prozessmodelle – Schleswig-Holsteinische Landesinitiative zum Forschungsdatenmanagement

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    Die Erstellung der Prozessmodelle mithilfe von BPMN (Business Process Model and Notation) dienten der FDM-SH Community als Grundlage zur Diskussion der Erfüllung der Aufgaben der Gremien innerhalb der Landesinitiative zum Forschungsdatenmanagement (FDM-SH). Sie verdeutlichen Entscheidungs- und Kommunikationsprozesse innerhalb von FDM-SH

    ArdMarks (in ArchaeoBotLand) 2023

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    Data Collection is part of ArchaeoBotLand. Compilation of information on traces of ards/ploughs and ard marks in prehistory. Data extracted from published sources

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