Outputs (119)

Deterministic Leader Election in Programmable Matter (2019)
Presentation / Conference Contribution
Emek, Y., Kutten, S., Lavi, R., & Moses Jr., W. K. (2019). Deterministic Leader Election in Programmable Matter. In C. Baier, I. Chatzigiannakis, P. Flocchini, & S. Leonardi (Eds.), . https://doi.org/10.4230/lipics.icalp.2019.140

Towards History-Aware Self-Adaptation with Explanation Capabilities (2019)
Presentation / Conference Contribution
García-Domínguez, A., Bencomo, N., Ullauri, J. M. P., & Paucar, L. H. G. (2019). Towards History-Aware Self-Adaptation with Explanation Capabilities. . https://doi.org/10.1109/fas-w.2019.00018

ECG-based affective computing for difficulty level prediction in Intelligent Tutoring Systems (2019)
Presentation / Conference Contribution
Alqahtani, F., Katsigiannis, S., & Ramzan, N. (2019). ECG-based affective computing for difficulty level prediction in Intelligent Tutoring Systems. . https://doi.org/10.1109/ucet.2019.8881872

Volenti non fit injuria: Ransomware and its Victims (2019)
Presentation / Conference Contribution
Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2019). Volenti non fit injuria: Ransomware and its Victims. . https://doi.org/10.1109/bigdata47090.2019.9006298

With the recent growth in the number of malicious activities on the internet, cybersecurity research has seen a boost in the past few years. However, as certain variants of malware can provide highly lucrative opportunities for bad actors, significan... Read More about Volenti non fit injuria: Ransomware and its Victims.

A General Transductive Regularizer for Zero-Shot Learning (2019)
Presentation / Conference Contribution
Mao, H., Zhang, H., Long, Y., Wang, S., & Yang, L. (2019). A General Transductive Regularizer for Zero-Shot Learning.

ARRoW: automatic runtime reappraisal of weights for self-adaptation (2019)
Presentation / Conference Contribution
Paucar, L. H. G., Bencomo, N., & Yuen, K. K. F. (2019). ARRoW: automatic runtime reappraisal of weights for self-adaptation. In C. Hung, & G. A. Papadopoulos (Eds.), . https://doi.org/10.1145/3297280.3299743

An architectural framework for quality-driven adaptive continuous experimentation (2019)
Presentation / Conference Contribution
Jiménez, M. A., Rivera, L. F., Villegas, N. M., Tamura, G., Müller, H. A., & Bencomo, N. (2019). An architectural framework for quality-driven adaptive continuous experimentation. . https://doi.org/10.1109/rcose/ddree.2019.00012

FAT-WSN: A Non Destructive and Secure Aggregation Strategy for Energy Saving in WSN (2019)
Presentation / Conference Contribution
Ma, D., Han, G., Xiao, A., Hu, Y., Ahmed, S. H., Aujla, G. S., & Cao, H. (2019). FAT-WSN: A Non Destructive and Secure Aggregation Strategy for Energy Saving in WSN. . https://doi.org/10.1109/gcwkshps45667.2019.9024492

Preface to 9th International Workshop on Model-Driven Requirements Engineering (2019)
Presentation / Conference Contribution
Bencomo, N., Mussbacher, G., Moreira, A., Araújo, J., & Sánchez, P. (2019). Preface to 9th International Workshop on Model-Driven Requirements Engineering. . https://doi.org/10.1109/rew.2019.00009

Author-Profiling of Learners’ Gender on a MOOC Platform based on their Comments (2019)
Presentation / Conference Contribution
Aljohani, T., Yu, J., & Alrajhi, L. (2019, December). Author-Profiling of Learners’ Gender on a MOOC Platform based on their Comments. Paper presented at ACM-Women UK Inspire 2019, Canterbury,England