Outputs (665)

Usability of a robot's realistic facial expressions and peripherals in autistic children's therapy (2020)
Presentation / Conference Contribution
Li, J., Davison, D., Schadenberg, B., Chevalier, P., Alcorn, A., Williams, A., Petrovic, S., Dimitrijevic, S. B., Shen, J., Pellicano, L., & others. (2019, March). Usability of a robot's realistic facial expressions and peripherals in autistic children's therapy. Paper presented at 2nd Workshop on Social Robots in Therapy and Care. 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2019), Daegu, Korea

Robot-assisted therapy is an emerging form of therapy for autistic children, although designing effective robot behaviors is a challenge for effective implementation of such therapy. A series of usability tests assessed trends in the effectiveness of... Read More about Usability of a robot's realistic facial expressions and peripherals in autistic children's therapy.

Multi-criteria Strategic Framework for Improving Residential Buildings Operational Energy Efficiency (Case Study Damascus Residential Youth Buildings) [In Arabic] (2020)
Journal Article
Khadour, L. A. (2020). Multi-criteria Strategic Framework for Improving Residential Buildings Operational Energy Efficiency (Case Study Damascus Residential Youth Buildings) [In Arabic]. Damascus University Journal for Engineering Sciences, 36(1), 57-72

The poor thermal performance of traditional residential buildings has led to residents' complaints in light of the post-war energy shortage and the increasing periods of power cuts. Therefore, improving residential building energy efficiency is a key... Read More about Multi-criteria Strategic Framework for Improving Residential Buildings Operational Energy Efficiency (Case Study Damascus Residential Youth Buildings) [In Arabic].

A comprehensive evaluation of incremental speech recognition and diarization for conversational AI (2020)
Presentation / Conference Contribution
Addlesee, A., Yu, Y., & Eshghi, A. (2020, December). A comprehensive evaluation of incremental speech recognition and diarization for conversational AI. Presented at 28th International Conference on Computational Linguistics, Barcelona, Spain (Online)

Automatic Speech Recognition (ASR) systems are increasingly powerful and more accurate, but also more numerous with several options existing currently as a service (e.g. Google, IBM, and Microsoft). Currently the most stringent standards for such sys... Read More about A comprehensive evaluation of incremental speech recognition and diarization for conversational AI.

Soziale Medien in der empirischen Forschung (2020)
Book Chapter
Zeller, F. (2020). Soziale Medien in der empirischen Forschung. In J.-H. Schmidt, & M. Taddicken (Eds.), Handbuch Soziale Medien (1-21). Springer. https://doi.org/10.1007/978-3-658-03895-3_21-2

Der Beitrag bietet einen Überblick zu sozialen Medien in der empirischen Forschung mit einem methodologischen und instrumentellen Fokus. Er diskutiert die unterschiedlichen Methoden, welche in der Kommunikationswissenschaft bereits angewandt werden,... Read More about Soziale Medien in der empirischen Forschung.

Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks (2020)
Presentation / Conference Contribution
Nguyen, N.-T., Nguyen, D. N., Hoang, D. T., Van Huynh, N., Nguyen, H.-N., Nguyen, Q. T., & Dutkiewicz, E. (2020, December). Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks. Presented at GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan

In this paper, an economic model is proposed to jointly optimize profits for participants in a heterogeneous IoT wireless-powered backscatter communication network. In the network under considerations, a power beacon and IoT devices (with various com... Read More about Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks.

Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning (2020)
Presentation / Conference Contribution
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2020, December). Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning. Presented at GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan

This paper develops a beam association framework for mm Wave vehicular networks to improve the system performance in terms of handover, disconnection time, and data rate under the high mobility of vehicles. In particular, we recruit the semi Markov d... Read More about Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning.

A review of polymorphic malware detection techniques (2020)
Journal Article
Alrzini, J. R. S., & Pennington, D. (2020). A review of polymorphic malware detection techniques. International Journal of Advanced Research in Engineering and Technology, 11(12), 1238-1247. https://doi.org/10.34218/IJARET.11.12.2020.119

Despite the continuous updating of anti-detection systems for malicious programs (malware), malware has moved to an abnormal threat level; it is being generated and spread faster than before. One of the most serious challenges faced by anti-detection... Read More about A review of polymorphic malware detection techniques.

An ML Model for Predicting Information Check-Worthiness using a Variety of Features (2020)
Presentation / Conference Contribution
Ullah, M. Z. (2020, February). An ML Model for Predicting Information Check-Worthiness using a Variety of Features. Presented at Workshop on Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media, Toulouse, France

In this communication, we introduce the important problem of information check-worthiness. We present the method we developed to automatically answer this problem. This method makes use of an elaborated information representation that combines the “i... Read More about An ML Model for Predicting Information Check-Worthiness using a Variety of Features.

Exploiting various word embedding models for query expansion in microblog (2020)
Presentation / Conference Contribution
Ahmed, S., Chy, A. N., & Ullah, M. Z. (2020, December). Exploiting various word embedding models for query expansion in microblog. Presented at 2020 IEEE 8th R10 Humanitarian Technology Conference (R10-HTC), Kuching, Malaysia

Microblogs, especially Twitter, make it easier to communicate with others in a real-time manner and is treated as a valuable information source. With the increasing amount of tweets, it would be fascinating to be able to extract essential information... Read More about Exploiting various word embedding models for query expansion in microblog.

Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project (2020)
Presentation / Conference Contribution
Demestichas, K., Hoang, T. B. N., Mothe, J., Teste, O., & Ullah, M. Z. (2020, July). Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project. Presented at CIRCLE'20, Samatan, France

This paper presents the on going work within PREVISION H2020 project. The mission of PREVISION is to empower the analysts and investigators of agencies with tools and solutions not commercially available today, to handle and capitalize on the massive... Read More about Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project.