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- Accessibility awareness (1)
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Articles 1 - 7 of 7
Full-Text Articles in Social and Behavioral Sciences
From The Tree Of Knowledge And The Golem Of Prague To Kosher Autonomous Cars: The Ethics Of Artificial Intelligence Through Jewish Eyes, Nachshon Goltz, John Zeleznikow, Tracey Dowdeswell
From The Tree Of Knowledge And The Golem Of Prague To Kosher Autonomous Cars: The Ethics Of Artificial Intelligence Through Jewish Eyes, Nachshon Goltz, John Zeleznikow, Tracey Dowdeswell
Research outputs 2014 to 2021
This article discusses the regulation of artificial intelligence from a Jewish perspective, with an emphasis on the regulation of machine learning and its application to autonomous vehicles and machine learning. Through the Biblical story of Adam and Eve as well as Golem legends from Jewish folklore, we derive several basic principles that underlie a Jewish perspective on the moral and legal personhood of robots and other artificially intelligent agents. We argue that religious ethics in general, and Jewish ethics in particular, show us that the dangers of granting moral personhood to robots and in particular to autonomous vehicles lie not …
Interpreting Health Events In Big Data Using Qualitative Traditions, Roschelle L. Fritz, Gordana Dermody
Interpreting Health Events In Big Data Using Qualitative Traditions, Roschelle L. Fritz, Gordana Dermody
Research outputs 2014 to 2021
© The Author(s) 2020. The training of artificial intelligence requires integrating real-world context and mathematical computations. To achieve efficacious smart health artificial intelligence, contextual clinical knowledge serving as ground truth is required. Qualitative methods are well-suited to lend consistent and valid ground truth. In this methods article, we illustrate the use of qualitative descriptive methods for providing ground truth when training an intelligent agent to detect Restless Leg Syndrome. We show how one interdisciplinary, inter-methodological research team used both sensor-based data and the participant’s description of their experience with an episode of Restless Leg Syndrome for training the intelligent agent. …
Self-Supervised Learning To Detect Key Frames In Videos, Xiang Yan, Syed Zulqarnain Gilani, Mingtao Feng, Liang Zhang, Hanlin Qin, Ajmal Mian
Self-Supervised Learning To Detect Key Frames In Videos, Xiang Yan, Syed Zulqarnain Gilani, Mingtao Feng, Liang Zhang, Hanlin Qin, Ajmal Mian
Research outputs 2014 to 2021
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Detecting key frames in videos is a common problem in many applications such as video classification, action recognition and video summarization. These tasks can be performed more efficiently using only a handful of key frames rather than the full video. Existing key frame detection approaches are mostly designed for supervised learning and require manual labelling of key frames in a large corpus of training data to train the models. Labelling requires human annotators from different backgrounds to annotate key frames in videos which is not only expensive and time consuming but …
Divergence Of Safety And Security, David J. Brooks, Michael Coole
Divergence Of Safety And Security, David J. Brooks, Michael Coole
Research outputs 2014 to 2021
© 2020, The Author(s). Safety and security have similar goals, to provide social wellness through risk control. Such similarity has led to views of professional convergence; however, the professions of safety and security are distinct. Distinction arises from variances in concept definition, risk drivers, body of knowledge, and professional practice. This chapter explored the professional synergies and tensions between safety and security professionals, using task-related bodies of knowledge. Findings suggest that safety and security only have commonalities at the overarching abstract level. Common knowledge does exist with categories of risk management and control; however, differences are explicit. In safety, risk …
No Soldiers Left Behind: An Iot-Based Low-Power Military Mobile Health System Design, James Jin Kang, Wencheng Yang, Gordana Dermody, Mohammadreza Ghasemian, Sasan Adibi, Paul Haskell-Dowland
No Soldiers Left Behind: An Iot-Based Low-Power Military Mobile Health System Design, James Jin Kang, Wencheng Yang, Gordana Dermody, Mohammadreza Ghasemian, Sasan Adibi, Paul Haskell-Dowland
Research outputs 2014 to 2021
© 2013 IEEE. There has been an increasing prevalence of ad-hoc networks for various purposes and applications. These include Low Power Wide Area Networks (LPWAN) and Wireless Body Area Networks (WBAN) which have emerging applications in health monitoring as well as user location tracking in emergency settings. Further applications can include real-Time actuation of IoT equipment, and activation of emergency alarms through the inference of a user's situation using sensors and personal devices through a LPWAN. This has potential benefits for military networks and applications regarding the health of soldiers and field personnel during a mission. Due to the wireless …
Quantifying The Need For Supervised Machine Learning In Conducting Live Forensic Analysis Of Emergent Configurations (Eco) In Iot Environments, Victor R. Kebande, Richard A. Ikuesan, Nickson M. Karie, Sadi Alawadi, Kim-Kwang Raymond Choo, Arafat Al-Dhaqm
Quantifying The Need For Supervised Machine Learning In Conducting Live Forensic Analysis Of Emergent Configurations (Eco) In Iot Environments, Victor R. Kebande, Richard A. Ikuesan, Nickson M. Karie, Sadi Alawadi, Kim-Kwang Raymond Choo, Arafat Al-Dhaqm
Research outputs 2014 to 2021
© 2020 The Author(s) Machine learning has been shown as a promising approach to mine larger datasets, such as those that comprise data from a broad range of Internet of Things devices, across complex environment(s) to solve different problems. This paper surveys existing literature on the potential of using supervised classical machine learning techniques, such as K-Nearest Neigbour, Support Vector Machines, Naive Bayes and Random Forest algorithms, in performing live digital forensics for different IoT configurations. There are also a number of challenges associated with the use of machine learning techniques, as discussed in this paper.
Web Content Management System And Accessibility Awareness: A Comparative Study Of Novice Users And Accessibility Outcomes, Fatima Artiba Diaz
Web Content Management System And Accessibility Awareness: A Comparative Study Of Novice Users And Accessibility Outcomes, Fatima Artiba Diaz
Theses: Doctorates and Masters
Since its creation, the Web has progressively developed and become a vital source of information in every domain and for almost all people. It is crucial to guarantee that the information contained on the Web is available for everyone, especially for people with special needs. Removing accessibility barriers is fundamentally based on tools, skills and support of all contributors, particularly the content creators, to ensure information is navigable and usable in the context of the end users experience. Web Content Management Systems play a significant role in structuring, storing and provision content to the Web and have evolved to address …