Outputs (653)

RSSI based Trilateration Technique to Localize Nodes in Underwater Wireless Sensor Networks through Optical Communication (2021)
Presentation / Conference Contribution
Aman, M., Gang, Q., Mian, S., Muzzammil, M., Tariq, M. O., & Khan, M. S. (2021, December). RSSI based Trilateration Technique to Localize Nodes in Underwater Wireless Sensor Networks through Optical Communication. Presented at 2021 16th International Conference on Emerging Technologies (ICET), Islamabad, Pakistan

In the past few decades, optical communication with high data rates up to Gb/s in underwater wireless sensor networks (UWSN) has been extensively investigated. However, now a days researchers are highly focused on proposing/implementing localization... Read More about RSSI based Trilateration Technique to Localize Nodes in Underwater Wireless Sensor Networks through Optical Communication.

Towards intelligibility-oriented audio-visual speech enhancement (2021)
Presentation / Conference Contribution
Hussain, T., Gogate, M., Dashtipour, K., & Hussain, A. (2021, September). Towards intelligibility-oriented audio-visual speech enhancement. Presented at The Clarity Workshop on Machine Learning Challenges for Hearing Aids (Clarity-2021), Online

Existing deep learning (DL) based approaches are generally optimised to minimise the distance between clean and enhanced speech features. These often result in improved speech quality however they suffer from a lack of generalisation and may not deli... Read More about Towards intelligibility-oriented audio-visual speech enhancement.

Migrating Models: A Decentralized View on Federated Learning (2021)
Presentation / Conference Contribution
Kiss, P., & Horváth, T. (2021, September). Migrating Models: A Decentralized View on Federated Learning. Presented at ECML PKDD 2021, Online

Federated learning (FL) researches attempt to alleviate the increasing difficulty of training machine learning models, when the training data is generated in a massively distributed way. The key idea behind these methods is moving the training to loc... Read More about Migrating Models: A Decentralized View on Federated Learning.

Algorithmic machines: From binary communication designs to human-robot interactions (2021)
Book Chapter
Zeller, F. (2021). Algorithmic machines: From binary communication designs to human-robot interactions. In M. Taddicken, & C. Schumann (Eds.), Algorithms and Communication (95-132). Digital Communication Research. https://doi.org/10.48541/dcr.v9.4

This article discusses aspects of future research in communication sciences related to a popular and omnipresent artefact of algorithmic machines, social robots. Social robots are defined in this article as physical entities or machines, which may re... Read More about Algorithmic machines: From binary communication designs to human-robot interactions.

Ethical Frameworks for Artificial Intelligence (AI) and Social Robots in Children’s Healthcare Experiences (2021)
Presentation / Conference Contribution
Zeller, F., Petrick, R. P., Harris Smith, D., Stinson, J., Ellen Foster, M., & Ali, S. (2021, March). Ethical Frameworks for Artificial Intelligence (AI) and Social Robots in Children’s Healthcare Experiences. Presented at HRI 2021 Workshop on Measuring Child-Robot Relationships, Online

This multi-disciplinary project aims to develop and evaluate an ethical, AI-enhanced, socially intelligent robot designed to alleviate children’s distress and pain in a clinical setting. Spanning different disciplines such as HRI, communication scien... Read More about Ethical Frameworks for Artificial Intelligence (AI) and Social Robots in Children’s Healthcare Experiences.

Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks (2021)
Presentation / Conference Contribution
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2021, December). Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks. Presented at GLOBECOM 2021 - 2021 IEEE Global Communications Conference, Madrid, Spain

This paper proposes a novel framework that can effectively address key challenges for the development of distributed learning over wireless edge networks. In particular, we first introduce a highly effective distributed learning model leveraging the... Read More about Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks.

The Opportunity of Cadmium Stannate as Transparent Conducting Oxide for Perovskite-Based Concentrated Photovoltaic System (2021)
Presentation / Conference Contribution
Khalid, M., Roy, A., Sundaram, S., & Mallick, T. K. (2021, September). The Opportunity of Cadmium Stannate as Transparent Conducting Oxide for Perovskite-Based Concentrated Photovoltaic System. Presented at 38th European Photovoltaic Solar Energy Conference and Exhibition 2021, Online

The relative scarcity and high cost associated with indium or fluorine, fabrication approaches surface roughness, and low adhesion to polymeric materials are significant drawbacks for indium tin oxide (ITO) and fluorine tin oxide (FTO)-based transpar... Read More about The Opportunity of Cadmium Stannate as Transparent Conducting Oxide for Perovskite-Based Concentrated Photovoltaic System.

Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems (2021)
Presentation / Conference Contribution
Strathearn, C., & Gkatzia, D. (2021, August). Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems. Presented at 14th International Conference on Natural Language Generation, Aberdeen

Conversational systems aim to generate responses that are accurate, relevant and engaging, either through utilising neural end-to-end models or through slot filling. Human-to-human conversations are enhanced by not only the latest utterance of the in... Read More about Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems.

An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction (2021)
Presentation / Conference Contribution
Kanwal, S., Rashid, J., Kim, J., Nisar, M. W., Hussain, A., Batool, S., & Kanwal, R. (2021, November). An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction. Presented at 2021 International Conference on Innovative Computing (ICIC), Lahore, Pakistan

One of the most challenging problems in the telecommunications industry is predicting customer churn (CCP). Decision-makers and business experts stressed that acquiring new clients is more expensive than maintaining current ones. From current churn d... Read More about An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction.

Multiscale Modeling for the Statics of Nanostructures (2021)
Book Chapter
Hoang, K.-Q., & Kadapa, C. (2021). Multiscale Modeling for the Statics of Nanostructures. In S. Chakraverty (Ed.), Nano Scaled Structural Problems: Static and Dynamic Behaviors (1-38). AIP Publishing. https://doi.org/10.1063/9780735422865_002

Characterization of mechanical properties of materials is essential toward understanding their deformation behavior when subjected to external forces. For a complete understanding of the behavior of materials from the interaction of atoms at the nano... Read More about Multiscale Modeling for the Statics of Nanostructures.