Asma Baccouche
Tweets Sentiment Analysis March - July 2017
Keywords: Text mining - Twitter sentiment - Analysis using deep learning
This study is preparing dataset, preprocess and clean tweets related on health In Arabic, French and English. Applying deep learning algorithm RNN/ CNN for sentiment analysis and classification.
I'm analyzing one of the social media network: twitter, in, order to classify the opinion of the user who talks about health. To do that, we use the enhancement of the deep learning algorithms to clarify the tweets/texts in three languages and compare between the results across the chosen topics.
Sophia Zahia
3D Reconstruction and Machine Learning Spring 2017
Keywords: Medical imaging - 3D reconstruction - Deep learning
In order to make it easier and affordable to hospitals the main purpose of our research is to create an application on mobile devices with dual cameras which will enable its user to accurately measure, depth and volume of pressure injuries and classify their tissue types. By using different techniques for point matching on only a single pair of stereo image, we managed to efficiently achieve a 3D shape reconstruction and retrieve its characteristics.
Yi(Joy) Li
Affective Gaming in Virtual Reality Spring 2017
Keywords: Virtual Reality - Health Application - Emotion Recognition
This main purpose of this project is towards designing interactive VR games adaptive to user emotion feedbacks based on experiments and analysis on psychophysiological reactivity. The outcome of the research will lead to a new approach of gaming design, and potential new training method that adjusts contents or difficulties according to an extra dimension.
Publications
Sokhadze, E. M., Casanova, M. F., Kelly, D. L., Sokhadze, G. E., Li, Y., Elmaghraby, A. S., &El-Baz, A. S. (2016). “Chapter 18 Virtual reality with psychophysiological monitoring as an approach to evaluate emotional reactivity, social skills, and joint attention in autism spectrum disorder“. In Autism Imaging and Devices (pp. 371-396). CRC Press
Li, Y., Elmaghraby, A. S., El-Baz, A. S., Casanova, M. F., & Sokhadze, E. M. (2016, December). Virtual Reality as a Tool for Investigation of Autonomic Reactivity in Autism. In APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK (Vol. 41, No. 4, pp. 444-444). 233 SPRING ST, NEW YORK, NY 10013 USA: SPRINGER/PLENUM PUBLISHERS.
Li, Y., Elmaghraby, A. S., El-Baz, A., & Sokhadze, E. M. (2015, December). Using physiological signal analysis to design affective VR games. In Signal Processing and Information Technology (ISSPIT), 2015 IEEE International Symposium on (pp. 57-62). IEEE.
Li, Y., Elmaghraby, A. S., & Sokhadze, E. M. (2015, July). Designing immersive affective environments with biofeedback. In Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES), 2015 (pp. 73-77). IEEE.
Li, Y., & Elmaghraby, A. S. (2014, July). A framework for using games for behavioral analysis of autistic children. In Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES), 2014 (pp. 1-4). IEEE.
Li, Y. (2012, July). Multi-scenario gesture recognition using Kinect. In Computer Games (CGAMES), 2012 17th International Conference on (pp. 126-130). IEEE.
Li, Y. (2012, June). Hand gesture recognition using Kinect. In Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on (pp. 196-199). IEEE.
Ornela Bardhi
Cancer: Activating Technology for Connected Health (CATCH ITN) Spring 2015
Keywords: New Technology - Healtcare - Medecine
This is a Horizon2020 funded project call Cancer: Activating Technology for Connected Health (CATCH ITN). This project combines technology with medicine and involves academia, industry and healthcare providers. The PhD is being conducted between University of Deusto (Spain) and BEACON Hospital (Ireland).
Ornela is a Marie Curie research fellow, her research focus is on application of machine learning and deep learning in medicine, particularly on cancer patients' care pathways, to optimize and personalize them according to patients' needs and perspectives. Other research interests include health and ICT for sustainability.
Moataz Mohamed
Reliability of Cloud Computing Spring 2015
Keywords: Distributed systems - Cloud computing
Moataz's research focusses on enhance the reliability of cloud computing. A reliability is most related with the rate of failures and the repair time of failure event. The failures in cloud are classified execution failure and scheduling failure. The execution failure produces from overloading machines due to submitted jobs or configuration error when software installed. The critical issue with overloading machine that the object is reducing load with save energy consumption at save time. The enchantment reliability with reducing energy consumption is critical tradeoff in cloud computing environment.
The scheduling error coming from the high rate of tasks requested from cloud provider which due to the queue is follow up and some task will kill for long waiting time in queue. The high rate of requested tasks is can result from distributed denial of services (DDoS). The prevention and detection DDoS is primary defense keeping the reliability from degration.
Publications
Moataz H.Khalil, Adel S. Elmaghraby, Auto Resource Management for Enhancing Reliability and Energy in Heterogamous Cloud Computing, (submitted)
Moataz H.Khalil, Adel S. Elmaghraby, Charactering and model for Hardware Failure in Large Scale Cloud Computing Environment, In processing of 16th IEEE International Symposium on Signal Processing and Information Technology, Cyprus, December - 2016.
Moataz Hassan Khalil, Walaa Sheta, Adel S. Elmaghraby , Performance Analysis for Dynamic Task Migration in Cloud Computing, In Processing of 31st International Conference on Computers and Their Applications (CATA), 4-6 April, Las Vegas, April -2016.
M. ELSayed Youssef, Moataz H.Khalil, Khairia E.AL-NAdi, Neural Network Modeling for Proton Exchange Membrane Fuel Cell (PEMFC), Advances in information Sciences and Services Sciences, Vol. 2, No. 2, June 2010.
M. ELSayed Youssef, Khairia E.AL-NAdi, Moataz H.Khalil, Lumped Model for Proton Exchange Membrane Fuel Cell (PEMFC) , International Journal of Electrochemical Science, Vol.5 , NO.1, January 2010.