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210 results on '"Mubin, Omar"'

202. Roomba is not a Robot; AIBO is still Alive! Anthropomorphic Language in Online Forums

Author

Fink, Julia, Mubin, Omar, Kaplan, Frédéric, and Dillenbourg, Pierre

Subjects
human-robot interaction, human-computer interaction, anthropomorphism, InformationSystems_MISCELLANEOUS
Abstract

Anthropomorphism describes people’s tendency to ascribe humanlike qualities to non-human artifacts, such as robots. We investigated anthropomorphic language in 750 posts of online forums about the Roomba robotic vacuum cleaner, the AIBO robotic dog and the iPad tablet computer. Results of this content analysis suggest a significant difference for anthropomorphic language usage among the three technologies. In contrast to Roomba and iPad, the specific characteristics of the robotic dog enhanced a more social interaction and lead people to use considerably more anthropomorphic language.

204. PMD: Designing a Portable Medicine Dispenser for Persons Suffering from Alzheimer's Disease

Author

de Beer, Roel, Keijers, Roy, Shahid, Suleman, Al Mahmud, Abdullah, and Mubin, Omar

Subjects
User-centred design, medicine dispenser, memory impairment, alzheimer's disease, prototype, older adults
Abstract

In this paper we present the user-centred design of a medicine dispenser for persons suffering from Alzheimer's disease. The prototype was evaluated in two phases with two caregivers and two Alzheimer's patients. Caregivers evaluated the device positively. The Alzheimer's patients faced usability problems while completing tasks due to the virtual interaction medium of the medicine dispenser. However, patients and caregivers found the concept useful for medication intake.

206. Friend forever

Author

Shahid, Suleman, Mubin, Omar, and Al Mahmud, Abdullah

208. Who is more expressive during child-robot interaction.

Author

Shahid, Suleman, Krahmer, Emiel, Swerts, Marc, and Mubin, Omar

Abstract

In this study we have tried to determine if the cultural background of children has an influence on how they interact with robots. Children of different age groups and cultures played a card guessing game with a robot (iCat). By using perception tests to evaluate the children's emotional response it was revealed that children from South Asia (Pakistani) were much more expressive than European children (Dutch) and younger children were more expressive than the older ones in the context of child robot interaction. [ABSTRACT FROM AUTHOR]

Published
2011
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209. Towards an Agenda for Sci-Fi Inspired HCI Research

Author

Morten Fjeld, Wolmet Barendregt, Philipp Jordan, Mark Billinghurst, Thommy Eriksson, Omar Mubin, Mohammad Obaid, Daniel Sjolle, Simeon J. Simoff, Patricia Alves-Oliveria, 13th International Conference on Advances in Computer Entertainment Technology Osaka, Japan 8-12 November 2016, Mubin, Omar, Obaid, Mohammad, Jordan, Philipp, Alves-Oliveria, Patricia, Eriksson, Thommy, Barendregt, Wolmet, Sjolle, Daniel, Fjeld, Morten, Simoff, Simeon, and Billinghurst, Mark

Subjects
Long lasting, HCI, Computer science, 05 social sciences, 020207 software engineering, 02 engineering and technology, Interaction design, Sci-Fi, Interactive technology, science fiction, Human–computer interaction, Action plan, 0202 electrical engineering, electronic engineering, information engineering, Position paper, interaction design, 0501 psychology and cognitive sciences, Engineering ethics, 050107 human factors
Abstract

Science fiction media has had a long lasting influence on the progression of interactive technology, however recently contradictions are emerging in the development of the two disciplines. Therefore, in this exploratory position paper we report on the insights attained through a day long workshop amongst scientists and researchers on how the collaboration between science fiction and Human Computer Interaction (HCI) can be advanced. Discussions in the workshop focused on detailing the relationship between HCI and science fiction. In conclusion, as our main contribution an action plan and agenda is presented for facilitating deeper influences amongst the two disciplines. Refereed/Peer-reviewed

Published
2016

210. Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.

Author

Alsinglawi B, Alnajjar F, Mubin O, Novoa M, Alorjani M, Karajeh O, and Darwish O

Subjects
Coronary Care Units, Electronic Health Records, Humans, Length of Stay, Intensive Care Units, Machine Learning
Abstract

Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to the coronary care unit (CCU) or (cardiac intensive care units CICU) is deemed as a challenging task to hospital management systems globally. Recently, few studies examined the length of stay (LOS) predictive analytics for cardiovascular inpatients in ICU. However, there are almost scarcely real attempts utilized machine learning models to predict the likelihood of heart failure patients length of stay in ICU hospitalization. This paper introduces a predictive research architecture to predict Length of Stay (LOS) for heart failure diagnoses from electronic medical records using the state-of-art- machine learning models, in particular, the ensembles regressors and deep learning regression models. Our results showed that the gradient boosting regressor (GBR) outweighed the other proposed models in this study. The GBR reported higher R-squared value followed by the proposed method in this study called Staking Regressor. Additionally, The Random forest Regressor (RFR) was the fastest model to train. Our outcomes suggested that deep learning-based regressor did not achieve better results than the traditional regression model in this study. This work contributes to the field of predictive modelling for electronic medical records for hospital management systems.

Published
2020
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