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            "title": {
                "en": "Mechanobiological model for simulation of injured cartilage degradation via pro-inflammatory cytokines and mechanical stimulus: experimental data, computational model results, and files to generate the models"
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                "fi": "__Introduction__\n\nThis dataset, called INTEL-TAU is a set of 7022 scenes in total, which makes it the largest available dataset for illumination estimation research. The variety of scenes captured using three different camera models, i.e., Canon 5DSR, Nikon D810, and Sony IMX135, makes the dataset appropriate for evaluating the camera and scene invariance of the different illumination estimation techniques. Privacy masking is done for sensitive information, e.g., faces. Thus, it is coherent with the General Data Protection Regulation(GDPR) regulations. Furthermore, the effect of color shading for mobile images can be evaluated with INTEL-TAU, as we provide both corrected and uncorrected versions of the raw data. \n\n__Organization of the Dataset__\n\nThe images in the dataset are organized as follows:\n'RootPath/CameraName/SetName'\n\n-CameraName: Indicates the name of the camera used to take the image, and it is one of the following: \n1) Canon_5DSR \n\n2) Nikon_D180 \n\n3) Sony_IMX135\n\n4) Sony_IMX135_BLCCSC: Sony_IMX135 images after color shading correction.\n\n-SetName: Indicates the name of the set (category) of images and can take following names: \n\n1) field_1_cameras:  scenes unique for the camera model.\n\n2) field_3_cameras: common  scenes acquired by the three cameras\n\n3) lab_printouts: lab printouts.\n\n4) lab_realscene: lab real scenes.\n\n\n\nThe contents are as follows for each image, and follow the above annotation with corresponding extensions:\n\n1) Color Correction Matrix: The color correction matrix from sensor RGB to sRGB. It is stored as a 1x9 vector. Extension: '.ccm'\n\n2) JPEG Image: These images underwent demosaicing, black level correction, saturation point stretching operations, white balancing, color correction, and gamma correction. These images are only shared for illustration of how a color corrected image should look like. Extension: '.jpg'\n\n3) Ground truth: This file contains the white point in [R/G, B/G] format. Extension: '.wp'\n\n4) RAW Image:  2 bytes per pixel raw format, storing the actual raw Bayer layout, the values can be read as uint16. Extension: '.plain16'. \n\nNote: The 'RootPath/CameraName/Info/Info/CameraName_frame_format_ .mat files contain the width and height information, as well as the Bayer order and other needed frame format information needed to correctly read the raw image.  \n\nAdditional Information: \n\nThe additional folder 'RootPath/Info' has additional information: Spectral Light Source Data and Spectral Responses of the Cameras.\n \n__Citation__\n\nAny work that uses the dataset should cite the following publication:\nFiras Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, and Moncef Gabbouj.  Intel-tau:  A Color Constancy Dataset, 2019      \nhttp://arxiv.org/abs/1910.10404"
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                "en": "Morphologically and syntactically annotated corpus of the modern Russian language. \n\nAccess location: http://www.ling.helsinki.fi/projects/hanco/index_e.html.\n\nOriginality status: The corpus has been creating since 2001 at the Slavonic and Baltic Department, U of Helsinki.\n\nDescription of size and extent: Proportion which has been automatically/manually annotated/verified with respect to \n- morphology: 80 % automatically annotated / 20 % manually annotated. 80 % manually verified \n-syntax: 60 % automatically annotated / 40 % manually annotated. 80 % manually verified\n\nStorage format: Electronic: MySql database, Access database\n\n(Estimated) time invested in the collection and processing of the resource: 70 person months\n\n(Main) references to published articles or other written works describing the resource itself or research based on its use:\nA. Kopotev, M. The Helsinki Annotated Corpus of Russian Texts HANCO: a tool for teaching and learning of Russian \nB. Мустайоки, А., Копотев, М.В. ‘Принципы создания Хельсинкского аннотированного корпуса русских текстов (ХАНКО) в сети Интернет (Principles of the Creation of the Helsinki Annotated Corpus HANCO)’ Научно-техническая информация. Сер. 2: Информационные системы и процессы. № 6: Корпусная лингвистика в России, 2003, c. 33-37 \nC. Копотев. М. В. ‘Несмотря на «потому что», или Многокомпонентные единицы в аннотированном корпусе русских текстов (In Spite of potomu čto, Or Compounds in the Helsinki Annotated Corpus of Russan Text HANCO)’ Компьютерная лингвистика и интеллектуальные технологии. Труды международной конференции Диалог-2004, Москва: Наука, 2004. с. 335-339. \nD. Копотев. М.В. ‘Принципы синтаксической разметки Хельсинкского аннотированного корпуса русских текстов ХАНКО (Principles of the syntactic annotation in the Helsinki Annotated Corpus HANCO)’ Компьютерная лингвистика и интеллектуальные технологии. Труды международной конференции Диалог–2006, Москва: изд-во РГГУ, 2006, с. 280–284.\n\nLink(s) to more extensive/thorough descriptions of the resource in the Internet (which may be in any language): http://www.helsinki.fi/~kopotev/hanco.pdf\n\nlog\n26.11.2018 links http://www.helsinki.fi/venaja/russian/e-material/hanco/index.htm and http://www.helsinki.fi/venaja/english/e-material/hanco/index.htm, and http://islrn.org/resources/401-067-943-468-8 removed"
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