doi: 10.13025/21373
handle: 10379/16102
Understanding the sentiment of a comment from a video or an image is an essential task in many applications. Sentiment analysis of a text can be useful for various decision-making processes. One such application is to analyse the popular sentiments of videos on social media based on viewer comments. However, comments from social media do not follow strict rules of grammar, and they contain mixing of more than one language, often written in non-native scripts. Non-availability of annotated code-mixed data for a low-resourced language like Tamil also adds difficulty to this problem. To overcome this, we created a gold standard Tamil-English code-switched, sentiment-annotated corpus containing 15,744 comment posts from YouTube. In this paper, we describe the process of creating the corpus and assigning polarities. We present inter-annotator agreement and show the results of sentiment analysis trained on this corpus as a benchmark
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This Re-InVEST Policy Brief explores our Participatory Action Human Rights and Capability Approach (PAHRCA) approach to research and knowledge construction which we implemented in 13 countries over the 2015-2018 period. We briefly outline key concepts underpinning the PAHCRA approach, discuss how it was operationalised, and then reflect on the degree to which co-construction of knowledge is a form of ‘enabling research’ that enhances the collective agency of vulnerable groups in their fight for a more equitable society. Our specific social co-construction of knowledge illuminated how policies and practices can produce distinct experiences from the perspective of the most vulnerable.
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Mechanical stress within biological tissue can indicate an anomaly, or can be vital of its function, such as stresses in arteries. Measuring these stresses in tissue is challenging due to the complex, and often unknown, nature of the material properties. Recently, a method called the angled shear wave identity was proposed to predict the stress by measuring the speed of two small amplitude shear waves. The method does not require prior knowledge of the material's constitutive law, making it ideal for complex biological tissues. We extend this method, and the underlying identity, to include viscous dissipation, which can be significant for biological tissues. To generalise the identity, we consider soft viscoelastic solids described by a generalised Newtonian viscous stress, and account for transverse isotropy, a feature that is common in muscle tissue, for instance. We then derive the dispersion relationship for small-amplitude shear waves superimposed on a large static deformation. Similarly to the elastic case, the identity is recovered when the stress in the material is coaxial with the transverse anisotropy. A key result in this paper is that to predict the stress in a viscous materials one would need to measure the wave attenuation as well as the wave speed.
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Solar UV Calculator to predict the spectral irradiance inside solar disinfection water plastic containers as a function of the plastic composition and thickness.
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A Year of Progress 2020-2021 Though the pandemic has been a difficult time for all, we have been hard at work developing a platform that will work with unemployed people, rather than on them. Updates: HECAT Platform Publications Project Deliverables
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SY Cha is a T Tauri star surrounded by a protoplanetary disk with a large cavity seen in the millimeter continuum but has the spectral energy distribution (SED) of a full disk. Here we report the first results from JWST-MIRI Medium Resolution Spectrometer (MRS) observations taken as part of the MIRI mid-INfrared Disk Survey (MINDS) GTO Program. The much improved resolution and sensitivity of MIRI-MRS compared to Spitzer enables a robust analysis of the previously detected H2O, CO, HCN, and CO2 emission as well as a marginal detection of C2H2. We also report the first robust detection of mid-infrared OH and ro-vibrational CO emission in this source. The derived molecular column densities reveal the inner disk of SY Cha to be rich in both oxygen and carbon bearing molecules. This is in contrast to PDS 70, another protoplanetary disk with a large cavity observed with JWST, which displays much weaker line emission. In the SY Cha disk, the continuum, and potentially the line, flux varies substantially between the new JWST observations and archival Spitzer observations, indicative of a highly dynamic inner disk.
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SHARING SOLUTIONS Toolkit is an online platform which contains tools and generates reports to help food sharing initiatives estimate, communicate and improve their sustainability impacts. Whether the initiative supports growing, cooking, eating food together or re-distributing surplus food, they can use the SHARING SOLUTIONS Toolkit to document the impacts these activities create.
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Abstracts for the Second Workshop on Implementing Machine Ethics
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Manage, Improve and Open up your Research Data PARTHENOS Archived snapshot of the ‘Manage, Improve and Open up your Research Data’ module, which is part of the PARTHENOS Training suite [1], which was developed as part of Work Package 7 in the PARTHENOS project [2]. This module will look at emerging trends and best practice in data management, quality assessment and IPR issues. We will look at policies regarding data management and their implementation, particularly in the framework of a Research Infrastructure. By the end of this module, you should be able to: Understand and describe the FAIR Principles and what they are used for Understand and describe what a Data Management Plan is, and how they are used Understand and explain what Open Data, Open Access and Open Science means for researchers Describe best practices around data management Understand and explain how Research Infrastructures interact with and inform policy on issues around data management Background: The PARTHENOS project [3] recognised that over the past ten years, researchers, institutional leaders and policymakers have begun to speak more and more about infrastructure. As more voices join the conversation, however, it can sometimes become more difficult, rather than less, to understand what exactly research infrastructure is and does. In particular in the humanities, and the digital humanities, the term is used to cover a lot of different projects, resources and approaches. To address this gap, the PARTHENOS cluster of humanities research infrastructure projects devised a series of training modules and resources for researchers, educators, managers, and policy makers who want to learn more about research infrastructures and the issues and methods around them. The modules, which have been released on a rolling basis from late 2016, cover a wide range of awareness levels, requirements and topic areas within the landscape of research infrastructure. This deposit is never intended to replace the online version of the training material on the PARTHENOS website, and is intended as an archive of content. Except where otherwise noted, PARTHENOS content is licensed under a Creative Commons Attribution 4.0 International license CC BY-NC 4.0. [1] https://training.parthenos-project.eu/ [2] WP7 – Skills, Professional Development and Advancement: http://www.parthenos-project.eu/resources/projects-deliverables#1523355756261-be477222-2866 [3] http://www.parthenos-project.eu/ [This is an archived snapshot of an online course. The online course may be updated over time, and though new versions will be created to reflect major changes, the archived version may not match exactly the content of the online version] Supplementary materials: PARTHENOS-owned: Videos: https://youtu.be/JFxunuPF2gw https://youtu.be/3HMbLvcf5is https://youtu.be/AsuJCTs2Ztw https://youtu.be/nfiFOW5xs6w THIRD PARTY: Images: http://training.parthenos-project.eu/wp-content/uploads/2017/07/big-data-EU-Webnerd-small.jpg https://training.parthenos-project.eu/wp-content/uploads/2017/09/laptop-2561018_1920-720x450.jpg https://training.parthenos-project.eu/wp-content/uploads/2017/09/hospice-1793998_1920-720x450.jpg Videos https://vimeo.com/36752317 https://youtu.be/pbBa6Oam7-w https://youtu.be/VFLTJ7D2y5s https://vimeo.com/230736351
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doi: 10.13025/21373
handle: 10379/16102
Understanding the sentiment of a comment from a video or an image is an essential task in many applications. Sentiment analysis of a text can be useful for various decision-making processes. One such application is to analyse the popular sentiments of videos on social media based on viewer comments. However, comments from social media do not follow strict rules of grammar, and they contain mixing of more than one language, often written in non-native scripts. Non-availability of annotated code-mixed data for a low-resourced language like Tamil also adds difficulty to this problem. To overcome this, we created a gold standard Tamil-English code-switched, sentiment-annotated corpus containing 15,744 comment posts from YouTube. In this paper, we describe the process of creating the corpus and assigning polarities. We present inter-annotator agreement and show the results of sentiment analysis trained on this corpus as a benchmark
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This Re-InVEST Policy Brief explores our Participatory Action Human Rights and Capability Approach (PAHRCA) approach to research and knowledge construction which we implemented in 13 countries over the 2015-2018 period. We briefly outline key concepts underpinning the PAHCRA approach, discuss how it was operationalised, and then reflect on the degree to which co-construction of knowledge is a form of ‘enabling research’ that enhances the collective agency of vulnerable groups in their fight for a more equitable society. Our specific social co-construction of knowledge illuminated how policies and practices can produce distinct experiences from the perspective of the most vulnerable.
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Mechanical stress within biological tissue can indicate an anomaly, or can be vital of its function, such as stresses in arteries. Measuring these stresses in tissue is challenging due to the complex, and often unknown, nature of the material properties. Recently, a method called the angled shear wave identity was proposed to predict the stress by measuring the speed of two small amplitude shear waves. The method does not require prior knowledge of the material's constitutive law, making it ideal for complex biological tissues. We extend this method, and the underlying identity, to include viscous dissipation, which can be significant for biological tissues. To generalise the identity, we consider soft viscoelastic solids described by a generalised Newtonian viscous stress, and account for transverse isotropy, a feature that is common in muscle tissue, for instance. We then derive the dispersion relationship for small-amplitude shear waves superimposed on a large static deformation. Similarly to the elastic case, the identity is recovered when the stress in the material is coaxial with the transverse anisotropy. A key result in this paper is that to predict the stress in a viscous materials one would need to measure the wave attenuation as well as the wave speed.
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Solar UV Calculator to predict the spectral irradiance inside solar disinfection water plastic containers as a function of the plastic composition and thickness.
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