Skip to main content

Research Repository

Advanced Search

All Outputs (193)

Metal Coated Fabric Based Supercapacitors (2020)
Presentation / Conference Contribution
Pullanchiyodan, A., Manjakkal, L., & Dahiya, R. (2020). Metal Coated Fabric Based Supercapacitors. In 2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS). https://doi.org/10.1109/fleps49123.2020.9239537

This work reports the fabric-based supercapacitors (FSCs) using silver coated textile as the current collector. The electrochemical properties of the device in PVA-KCl gel electrolyte was studied. The performance of the device was further improved by... Read More about Metal Coated Fabric Based Supercapacitors.

Glycine-based Flexible Biocompatible Piezoelectric Pressure Sensor for Healthcare Applications (2020)
Presentation / Conference Contribution
Hosseini, E. S., Manjakkal, L., Shakthivel, D., & Dahiya, R. (2020, August). Glycine-based Flexible Biocompatible Piezoelectric Pressure Sensor for Healthcare Applications. Presented at 2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS), Manchester, UK

This work presents biocompatible flexible piezoelectric composite fabricated by self-assembly of amino acid glycine molecules inside natural chitosan polymer. Piezoelectric composite film consists of glycine spherulite structure embedded in chitosan... Read More about Glycine-based Flexible Biocompatible Piezoelectric Pressure Sensor for Healthcare Applications.

Flexible Potentiostat Readout Circuit Patch for Electrochemical and Biosensor Applications (2020)
Presentation / Conference Contribution
Escobedo, P., Manjakkal, L., Ntagios, M., & Dahiya, R. (2020, August). Flexible Potentiostat Readout Circuit Patch for Electrochemical and Biosensor Applications. Presented at 2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS), Manchester, United Kingdom

This paper presents a miniaturized potentiostat readout circuit patch developed for electrochemical or biosensors. The presented patch has been fabricated on a flexible polyimide substrate using off-the-shelf electronics. In contrast to the tradition... Read More about Flexible Potentiostat Readout Circuit Patch for Electrochemical and Biosensor Applications.

PlanCurves: An Interface for End-Users to Visualise Multi-Agent Temporal Plans (2020)
Presentation / Conference Contribution
Le Bras, P., Carreno, Y., Lindsay, A., Petrick, R. P. A., & Chantler, M. J. (2020, October). PlanCurves: An Interface for End-Users to Visualise Multi-Agent Temporal Plans. Presented at ICAPS 2020 Workshop on Knowledge Engineering for Planning and Scheduling (KEPS 2020), Nancy, France [Online]

In operational contexts, there is a growing need to make automatically generated plans available for assessment, verification, and accountability purposes, in order to evaluate the risks associated with such plans prior to their execution. However, t... Read More about PlanCurves: An Interface for End-Users to Visualise Multi-Agent Temporal Plans.

Data Generation Using Gene Expression Generator (2020)
Presentation / Conference Contribution
Farou, Z., Mouhoub, N., & Horváth, T. (2020, November). Data Generation Using Gene Expression Generator. Presented at IDEAL 2020: 21st International Conference on Intelligent Data Engineering and Automated Learning, Guimarães, Portugal

Generative adversarial networks (GANs) could be used efficiently for image and video generation when labeled training data is available in bulk. In general, building a good machine learning model requires a reasonable amount of labeled training data.... Read More about Data Generation Using Gene Expression Generator.

A Novel Evaluation Metric for Synthetic Data Generation (2020)
Presentation / Conference Contribution
Galloni, A., Lendák, I., & Horváth, T. (2020, November). A Novel Evaluation Metric for Synthetic Data Generation. Presented at IDEAL 2020: 21st International Conference on Intelligent Data Engineering and Automated Learning, Guimarães, Portugal

Differentially private algorithmic synthetic data generation (SDG) solutions take input datasets Dp consisting of sensitive, private data and generate synthetic data Ds with similar qualities. The importance of such solutions is increasing both becau... Read More about A Novel Evaluation Metric for Synthetic Data Generation.

On the Robustness and Training Dynamics of Raw Waveform Models (2020)
Presentation / Conference Contribution
Loweimi, E., Bell, P., & Renals, S. (2020). On the Robustness and Training Dynamics of Raw Waveform Models. In Proc. Interspeech 2020 (1001-1005). https://doi.org/10.21437/interspeech.2020-17

We investigate the robustness and training dynamics of raw waveform acoustic models for automatic speech recognition (ASR). It is known that the first layer of such models learn a set of filters, performing a form of time-frequency analysis. This lay... Read More about On the Robustness and Training Dynamics of Raw Waveform Models.

Raw Sign and Magnitude Spectra for Multi-Head Acoustic Modelling (2020)
Presentation / Conference Contribution
Loweimi, E., Bell, P., & Renals, S. (2020). Raw Sign and Magnitude Spectra for Multi-Head Acoustic Modelling. In Proc. Interspeech 2020 (1644-1648). https://doi.org/10.21437/interspeech.2020-18

In this paper we investigate the usefulness of the sign spectrum and its combination with the raw magnitude spectrum in acoustic modelling for automatic speech recognition (ASR). The sign spectrum is a sequence of ±1s, capturing one bit of the phase... Read More about Raw Sign and Magnitude Spectra for Multi-Head Acoustic Modelling.

Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2020, October). Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. Presented at Interspeech 2020, Shanghai, China

In this paper, we present VIsual Speech In real nOisy eNvironments (VISION), a first of its kind audio-visual (AV) corpus comprising 2500 utterances from 209 speakers, recorded in real noisy environments including social gatherings, streets, cafeteri... Read More about Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System..

Corralling Culture as a Concept in LIS Research (2020)
Presentation / Conference Contribution
Salzano, R., Hall, H., & Webster, G. (2020, October). Corralling Culture as a Concept in LIS Research. Presented at 83rd Annual Meeting of the Association of Information Science and Technology, Virtual

Individuals’ cultural backgrounds influence their use of societal resources, including libraries. A literature search and review was completed on the treatment of culture in library and information science (LIS) in the body of work on information beh... Read More about Corralling Culture as a Concept in LIS Research.

Research Impact Value and Library and Information Science (RIVAL): development, implementation and outcomes of a Scottish network for LIS researchers and practitioners (2020)
Presentation / Conference Contribution
Hall, H., & Ryan, B. (2020, October). Research Impact Value and Library and Information Science (RIVAL): development, implementation and outcomes of a Scottish network for LIS researchers and practitioners. Presented at 83rd Annual Meeting of the Association for Information Science and Technology (ASIS&T)

The research-practice gap in Library and Information Science (LIS) is well documented, especially in respect of the difficulties of translating research into practice, and resultant lost opportunities. While many researchers attempt to explain this r... Read More about Research Impact Value and Library and Information Science (RIVAL): development, implementation and outcomes of a Scottish network for LIS researchers and practitioners.

Attribute-Based Symmetric Searchable Encryption (2020)
Presentation / Conference Contribution
Dang, H., Ullah, A., Bakas, A., & Michalas, A. (2020). Attribute-Based Symmetric Searchable Encryption. In Applied Cryptography and Network Security Workshops (318-336). https://doi.org/10.1007/978-3-030-61638-0_18

Symmetric Searchable Encryption (SSE) is an encryption technique that allows users to search directly on their outsourced encrypted data while preserving the privacy of both the files and the queries. Unfortunately, majority of the SSE schemes allows... Read More about Attribute-Based Symmetric Searchable Encryption.

A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network (2020)
Presentation / Conference Contribution
Thomson, C., Wadhaj, I., Al-Dubai, A., & Tan, Z. (2020, April). A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network. Presented at IEEE 6th World Forum on Internet of Things, New Orleans, Louisiana, USA

The issue of energy holes, or hotspots, in wireless sensor networks is well referenced. As is the proposed mobilisa-tion of the sink node in order to combat this. However, as the sink node shall still pass some nodes more closely and frequently than... Read More about A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network.

Visual Encodings for Networks with Multiple Edge Types (2020)
Presentation / Conference Contribution
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020, October). Visual Encodings for Networks with Multiple Edge Types. Presented at International Conference on Advanced Visual Interfaces, Napkes, Italy

This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real problems in computational biology. We focus on encodings in adjacency matrices, s... Read More about Visual Encodings for Networks with Multiple Edge Types.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data (2020)
Presentation / Conference Contribution
Briggs, C., Fan, Z., & Andras, P. (2020, July). Federated learning with hierarchical clustering of local updates to improve training on non-IID data. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion - as is typic... Read More about Federated learning with hierarchical clustering of local updates to improve training on non-IID data.

Deep Neural Network Driven Binaural Audio Visual Speech Separation (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., Bell, P., & Hussain, A. (2020, July). Deep Neural Network Driven Binaural Audio Visual Speech Separation. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

The central auditory pathway exploits the auditory signals and visual information sent by both ears and eyes to segregate speech from multiple competing noise sources and help disambiguate phonological ambiguity. In this study, inspired from this uni... Read More about Deep Neural Network Driven Binaural Audio Visual Speech Separation.

Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features (2020)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2020, July). Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features. Presented at International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK

Industrial Control Systems have become a priority domain for cybersecurity practitioners due to the number of cyber-attacks against those systems has increased over the past few years. This paper proposes a real-time anomaly intrusion detector for a... Read More about Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features.

Impact of Content Popularity on Content Finding in NDN: Default NDN vs. Vicinity-based Enhanced NDN (2020)
Presentation / Conference Contribution
Suwannasa, A., Broadbent, M., & Mauthe, A. (2020, September). Impact of Content Popularity on Content Finding in NDN: Default NDN vs. Vicinity-based Enhanced NDN. Presented at 2020 10th International Conference on Information Science and Technology (ICIST), Bath, London, and Plymouth, UK

Named Data Networking allows a consumer to locate a desired content object by its name prefix. By using the best route strategy of the default NDN architecture, an Interest packet is forwarded along a default path indicated by the packet's name to fi... Read More about Impact of Content Popularity on Content Finding in NDN: Default NDN vs. Vicinity-based Enhanced NDN.

Design of direct-drive wind turbine electrical generator structures using topology optimization techniques (2020)
Presentation / Conference Contribution
Jaen-Sola, P., McDonald, A. S., & Oterkus, E. (2020, September). Design of direct-drive wind turbine electrical generator structures using topology optimization techniques. Presented at The Science of Making Torque from Wind (TORQUE 2020), Online

Reducing the structural mass of low speed multi-MW electrical machines for renewable energy purposes have become an important object of study as with the drop in mass a substantial decrease in the machine capital cost can be achieved. Direct-drive wi... Read More about Design of direct-drive wind turbine electrical generator structures using topology optimization techniques.