Matching Items (6)
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- All Subjects: accessibility
- Creators: Mann, Annika
- Creators: Panchanathan, Sethuraman
- Member of: Theses and Dissertations
Description
This paper focuses on feudalist structure and values within this system in George R. R. Martin's fantasy novel series A Song of Ice and Fire and Shakespeare's play King Richard the Third. The paper is structured into three arguments that focus on different characters from each work. The first argument is focused on Tyrion Lannister and Richard III's deformity, and how they violate feudalist values. This argument ultimately comes to the discussion of whether or not these characters are monstrous and by what values. The second argument is focused on Daenerys Targaryen and Margaret, discussing why both authors give these women a supernatural power. The authors give women these powers because they believe that women should have power. Martin argues that women need to remake the structure, while Shakespeare believes women can change their place in the structure through collective action. The last argument focuses on Petyr Baelish and Richard III, and how they both represent a chaos attacking feudalism. Petyr is a chaos that comes outside the system, exploiting the values of the system, while Richard is a chaos within the system because he violates feudal values, while trying to hold positions where he needs to embody feudalist value. The authors come to different conclusions of what is trying to take down feudalist structure and how this could be fixed. Martin finds feudalism cannot be fixed and that other systems are not much better because they still create violence. Shakespeare comes to the conclusion that feudalism cannot be fixed because people continue to violate its values, so a new system must be put in place.
ContributorsPittaro, James Vincent (Author) / Mann, Annika (Thesis director) / Kirsch, Sharon (Committee member) / Barrett, The Honors College (Contributor) / School of Social and Behavioral Sciences (Contributor) / School of Humanities, Arts, and Cultural Studies (Contributor)
Created2015-05
Description
This thesis/creative project is a guide for other universities to follow in making their campuses more inclusive and accessible via maps. This guide will be offered in different formats (ex – PDF, a website, audio, etc.) to accommodate the disabled community. Hopefully, this guide will serve as inspiration and starting point for universities around the country to better the college experience for all.
ContributorsTaylor, RaNiyah (Author) / Allison, Adero (Thesis director) / Mann, Annika (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Politics and Global Studies (Contributor) / Sanford School of Social and Family Dynamics (Contributor)
Created2021-12
ContributorsTaylor, RaNiyah (Author) / Allison, Adero (Thesis director) / Mann, Annika (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor)
Created2021-12
ContributorsTaylor, RaNiyah (Author) / Allison, Adero (Thesis director) / Mann, Annika (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor)
Created2021-12
Description
Over the past decade, advancements in neural networks have been instrumental in achieving remarkable breakthroughs in the field of computer vision. One of the applications is in creating assistive technology to improve the lives of visually impaired people by making the world around them more accessible. A lot of research in convolutional neural networks has led to human-level performance in different vision tasks including image classification, object detection, instance segmentation, semantic segmentation, panoptic segmentation and scene text recognition. All the before mentioned tasks, individually or in combination, have been used to create assistive technologies to improve accessibility for the blind.
This dissertation outlines various applications to improve accessibility and independence for visually impaired people during shopping by helping them identify products in retail stores. The dissertation includes the following contributions; (i) A dataset containing images of breakfast-cereal products and a classifier using a deep neural (ResNet) network; (ii) A dataset for training a text detection and scene-text recognition model; (iii) A model for text detection and scene-text recognition to identify product images using a user-controlled camera; (iv) A dataset of twenty thousand products with product information and related images that can be used to train and test a system designed to identify products.
This dissertation outlines various applications to improve accessibility and independence for visually impaired people during shopping by helping them identify products in retail stores. The dissertation includes the following contributions; (i) A dataset containing images of breakfast-cereal products and a classifier using a deep neural (ResNet) network; (ii) A dataset for training a text detection and scene-text recognition model; (iii) A model for text detection and scene-text recognition to identify product images using a user-controlled camera; (iv) A dataset of twenty thousand products with product information and related images that can be used to train and test a system designed to identify products.
ContributorsPatel, Akshar (Author) / Panchanathan, Sethuraman (Thesis advisor) / Venkateswara, Hemanth (Thesis advisor) / McDaniel, Troy (Committee member) / Arizona State University (Publisher)
Created2020
Description
Individuals with voice disorders experience challenges communicating daily. These challenges lead to a significant decrease in the quality of life for individuals with dysphonia. While voice amplification systems are often employed as a voice-assistive technology, individuals with voice disorders generally still experience difficulties being understood while using voice amplification systems. With the goal of developing systems that help improve the quality of life of individuals with dysphonia, this work outlines the landscape of voice-assistive technology, the inaccessibility of state-of-the-art voice-based technology and the need for the development of intelligibility improving voice-assistive technologies designed both with and for individuals with voice disorders. With the rise of voice-based technologies in society, in order for everyone to participate in the use of voice-based technologies individuals with voice disorders must be included in both the data that is used to train these systems and the design process. An important and necessary step towards the development of better voice assistive technology as well as more inclusive voice-based systems is the creation of a large, publicly available dataset of dysphonic speech. To this end, a web-based platform to crowdsource voice disorder speech was developed to create such a dataset. This dataset will be released so that it is freely and publicly available to stimulate research in the field of voice-assistive technologies. Future work includes building a robust intelligibility estimation model, as well as employing that model to measure, and therefore enhance, the intelligibility of a given utterance. The hope is that this model will lead to the development of voice-assistive technology using state-of-the-art machine learning models to help individuals with voice disorders be better understood.
ContributorsMoore, Meredith Kay (Author) / Panchanathan, Sethuraman (Thesis advisor) / Berisha, Visar (Committee member) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Arizona State University (Publisher)
Created2020