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Ongoing Research Projects supported by Research IT

Listing of project codes and abstracts, describing work undertaken which use the resources of the compute clusters hosted by the Research IT team.

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Showing 10 of 423 Results
Project Title Transmit Beamforming in mmWave networks
Project Code HPC_17_00995
Principal Investigator Prof Linda Doyle
Start Date 2017-10-18
End Date 2017-10-30
Abstract In this work, we want to perform analysis of small-cell ultra-dense networks, using transmit beamforming in mmWave bands.
Project Title Improving Social Communication through Executive Function Training in Autism
Project Code HPC_17_00994
Principal Investigator Assistant Professor Clare Kelly
Start Date 2017-10-06
End Date 2018-09-01
Abstract The proposed research project will explore the benefits of a computerized training (CT) as intervention for individuals with autism spectrum disorder (ASD), it will add to the literature regarding the interplay between higher level executive function skills and social functioning in ASD, and it will utilise state-of-the-art neuroimaging techniques to elucidate associated brain behaviour relationships. The project was designed to be a natural progression of the my current skill set, but to also expand, elevate, and introduce techniques and tactics to help me achieve mastery of skills that are required to be a successful and innovative independent investigator. In addition to the research outcomes of the project, there will also be positive societal and economic impacts. Validation of the proposed CT programme will increase the availability and quality of therapy for adolescents with ASD; the independence of individuals with ASD; and the employability of high functioning individuals with ASD.
Project Title High Entropy Magnetic Alloys
Project Code HPC_17_00993
Principal Investigator Prof Stefano Sanvito
Start Date 2017-09-26
End Date 2017-12-31
Abstract Steel is usually considered as a highly mechanically performing material, with a large yield strength and fracture toughness. Recently a new class of metallic alloys have seriously challenged such performances and have established themselves as new star materials for a wide range of applications. These are the so-called high-entropy alloys [1, 2], made by mixing in equal proportion five or more transition metals (either from the 3d or the 4d family). Remarkably such alloys, whose thermodynamical stability at high temperature is driven by their large entropy, have remarkable mechanical properties.
Project Title High Entropy Magnetic Alloys
Project Code HPC_17_00992
Principal Investigator Prof Stefano Sanvito
Start Date 2017-09-26
End Date 2017-12-31
Abstract Steel is usually considered as a highly mechanically performing material, with a large yield strength and fracture toughness. Recently a new class of metallic alloys have seriously challenged such performances and have established themselves as new star materials for a wide range of applications. These are the so-called high-entropy alloys [1, 2], made by mixing in equal proportion five or more transition metals (either from the 3d or the 4d family). Remarkably such alloys, whose thermodynamical stability at high temperature is driven by their large entropy, have remarkable mechanical properties.
Project Title DFT simulations of Cu(111) surface
Project Code HPC_17_00991
Principal Investigator Prof David O'Regan
Start Date 2017-09-19
End Date 2018-09-24
Abstract Experimental images of the Cu(111) surface have been obtained using a scanning tunneling microscope (STM) and a number of interesting features require DFT simulations for further investigation.
Project Title Service Discovery in Smart Cities
Project Code HPC_17_00990
Principal Investigator Professor Siobhan Clarke
Start Date 2017-09-04
End Date 2019-02-28
Abstract In smart cities, a plethora of services are likely to be deployed in large, dynamic, heterogeneous, and distributed environments. Service discovery requirements are likely to be complex with context playing a key role, and human intervention infeasible. Existing research on service discovery has proposed solutions that focus either on semantic methods to improve accuracy, with performance negatively affected, or vice versa. In this scenario, we identify a trade-off between search accuracy and performance in service discovery. We propose a novel approach to address this trade-off by extending both service distribution and discovery processes. Service distribution will use additional semantic information to spread service descriptions at the right urban-places; service discovery will use this model to forward requests where they are more likely to be solved, and to perform service matching using the additional semantic information. This model will respond to city dynamics and citizens' behaviour self-organising the service information distribution according to users requests, and offering services to the citizens according to their surrounding urban-places in a proactive fashion. This approach will be evaluated against current approaches that organise and discover services using network or service properties such as location (e.g., coordinates), service functionalities (e.g., I/O signature) or service domain (e.g., service type). This evaluation will take place in a simulated environment using the Simonstrator platform
Project Title Inversion of Block Tridiagonal Matrices.
Project Code HPC_17_00989
Principal Investigator Prof Stefano Sanvito
Start Date 2017-08-31
End Date 2017-12-25
Abstract A parallel matrix inversion algorithm that has been implemented to be part of a matrix inverse library used by the SMEAGOL ab initio electronic code. SMEAGOL is developed by the computational spintronics group in Trinity College, Dublin. Matrix inversion must be used in order to obtain the Green's function required by the SMEAGOL code. Efficient parallel scaling of the SMEAGOL code requires that the matrix inverse be calculated in parallel. In many cases, only the block tridiagonal part of inverse is needed. This algorithm provides the block tridiagonal subset of the inverse of a sparse non-Hermitian block tridiagonal matrix.
Project Title Random Heusler Alloys
Project Code HPC_17_00988
Principal Investigator Prof Stefano Sanvito
Start Date 2017-08-09
End Date 2017-08-31
Abstract Using VASP software to study the electronic and magnetic structure of random Heusler alloys.
Project Title The application of UAV-mount access points in dense cellular networks
Project Code HPC_17_00987
Principal Investigator Prof Luiz Da Silva
Start Date 2017-07-25
End Date 2018-09-01
Abstract Wireless access points on unmanned aerial vehicles (UAVs) are being considered for mobile service provisioning in commercial networks. To be able to efficiently use these devices in cellular networks it is necessary to first have a qualitative and quantitative understanding of how their design parameters reflect on the service quality experienced by the end user. This research work focuses on setting up scenarios where UAV access points are deployed in urban environments to provide service to users and analysing performance as a function of different parameters of the network.
Project Title Plasmonic waveguide for sub-wavelength light confinement
Project Code HPC_17_00986
Principal Investigator Prof John Donegan
Start Date 2017-07-07
End Date 2017-12-31
Abstract Plasmonic waveguide for sub-wavelength light confinement | We propose channel plasmonic waveguide for nano-focusing. The plasmonic waveguide is a metal-insulator-metal (MIM) structure which is formed with two Gold cladding layers and a dielectric core. This structure can effectively confine the light in the dielectric channel owing to the excited surface plasmon between the metal and dielectric layers.