Leo Creedon | Institute of Technology, Sligo (original) (raw)
Papers by Leo Creedon
Journal of algebra and its applications, Feb 1, 2024
Bulletin, Dec 31, 2022
Committee changes: From January 2024, the Officers of the Society remain unchanged. Thanks to Mar... more Committee changes: From January 2024, the Officers of the Society remain unchanged. Thanks to Martin Mathieu and Ray Ryan for their many years of service to the Society, including decades of service as committee members, Officers and Editors of the Bulletin. Christopher Boyd (UCD) and Thomas Huettemann (QUB) are new committee members of the IMS, having been elected at the AGM on September 1, 2023.
arXiv (Cornell University), Aug 16, 2018
Publicationes mathematicae, 2024
<p>Coastal areas are socially, economically, and environmentally in... more <p>Coastal areas are socially, economically, and environmentally intensive zones. Their risk to various natural coastal hazards like coastal flooding, erosion, and storm surges has increased due to climate-induced changes in their forcing agents or hazard drivers (e.g. sea-level rise). The increased exposure (e.g. dense population living near the coast) and vulnerability (e.g. insufficient adaptation) to these hazards in the coastal areas have complicated the adaptation challenges.</p><p>Thus, monitoring coastal hazards is essential to inform suitable adaptation to increase the climate resilience of the coastal areas. In monitoring coastal climate hazards to develop coastal climate resilience, both the forcing agents and the coastal responses should be observed.</p><p>As coastal monitoring is often expensive and challenging, creating a database through a systematic analysis of low-cost sensing technologies, like UAV photogrammetry for monitoring the hazards and their drivers would be beneficial to the stakeholders. Real-time information from these low-cost sensors in complement to the existing institutional sensors will facilitate better adaptation policies including the development of early warning support for building coastal resilience. In addition, it would also provide a valuable dataset for validating coastal numerical models and providing insights into the relationship between these hazards and forcing agents. Additionally, such low-cost sensors would also create opportunities for engaging citizens in the data collection process, for efficient data collection, and increasing scientific literacy amongst the general public. For instance, in the Sensing Storm Surge Project (SSSP), citizen science was used to collect technical data to characterise estuarine storm surges, generating data useable in peer-reviewed Oceanography journals. Coastal areas show complex morphological changes in response to the forcing agents over a wide range of temporal and spatial scales. Thus, monitoring the hazards with a sufficient temporal and spatial resolution is imperative to distinguish the changes in these hazards/drivers due to climate change from natural variability. This will not only help address the response strategies to these hazards but also adjust these response strategies according to the changing vulnerability of a particular region.</p><p>The database of the low-lost sensors thus created is in no way exhaustive since those have been retrieved through a certain combination of keywords in databases like Sciencedirect, Web of Science, and Scopus, nonetheless it is useful as these are the latest low-cost sensors available to monitor the major coastal hazards in the vulnerable coastal regions.</p>
Finite Fields and Their Applications, Mar 1, 2019
This paper classifies the derivations of group algebras in terms of the generators and defining r... more This paper classifies the derivations of group algebras in terms of the generators and defining relations of the group. If RG is a group ring, where R is commutative and S is a set of generators of G then necessary and sufficient conditions on a map from S to RG are established, such that the map can be extended to an R-derivation of RG. Derivations are shown to be trivial for semisimple group algebras of abelian groups. The derivations of finite group algebras are constructed and listed in the commutative case and in the case of dihedral groups. In the dihedral case, the inner derivations are also classified. Lastly, these results are applied to construct well known binary codes as images of derivations of group algebras.
Polymer Testing, Aug 1, 2018
A soft sensor for prediction of mechanical properties of extruded PLA sheet using an instrumented... more A soft sensor for prediction of mechanical properties of extruded PLA sheet using an instrumented slit die and machine learning algorithms,
Sensors, Apr 7, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This paper classifies the derivations of group algebras in terms of the generators and defining r... more This paper classifies the derivations of group algebras in terms of the generators and defining relations of the group. If RG is a group ring, where R is commutative and S is a set of generators of G then necessary and sufficient conditions on a map from S to RG are established, such that the map can be extended to an R-derivation of RG. Derivations are shown to be trivial for semisimple group algebras of abelian groups. The derivations of finite group algebras are constructed and listed in the commutative case and in the case of dihedral groups. In the dihedral case, the inner derivations are also classified. Lastly, these results are applied to construct well known binary codes as images of derivations of group algebras.
2023 34th Irish Signals and Systems Conference (ISSC)
Sustainability
Changes in streamflow within catchments can have a significant impact on agricultural production,... more Changes in streamflow within catchments can have a significant impact on agricultural production, as soil moisture loss, as well as frequent drying and wetting, may have an effect on the nutrient availability of many soils. In order to predict future changes and explore the impact of different scenarios, machine learning techniques have been used recently in the hydrological sector for simulation streamflow. This paper compares the use of four different models, namely artificial neural networks (ANNs), support vector machine regression (SVR), wavelet-ANN, and wavelet-SVR as surrogate models for a geophysical hydrological model to simulate the long-term daily water level and water flow in the River Shannon hydrological system in Ireland. The performance of the models has been tested for multi-lag values and for forecasting both short- and long-term time scales. For simulating the water flow of the catchment hydrological system, the SVR-based surrogate model performs best overall. Reg...
Cells, Dec 2, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Sensors
PLA (polylactide) is a bioresorbable polymer used in implantable medical and drug delivery device... more PLA (polylactide) is a bioresorbable polymer used in implantable medical and drug delivery devices. Like other bioresorbable polymers, PLA needs to be processed carefully to avoid degradation. In this work we combine in-process temperature, pressure, and NIR spectroscopy measurements with multivariate regression methods for prediction of the mechanical strength of an extruded PLA product. The potential to use such a method as an intelligent sensor for real-time quality analysis is evaluated based on regulatory guidelines for the medical device industry. It is shown that for the predictions to be robust to processing at different times and to slight changes in the processing conditions, the fusion of both NIR and conventional process sensor data is required. Partial least squares (PLS), which is the established ’soft sensing’ method in the industry, performs the best of the linear methods but demonstrates poor reliability over the full range of processing conditions. Conversely, both...
<p>Coastal areas are socially, economically, and environmentally in... more <p>Coastal areas are socially, economically, and environmentally intensive zones. Their risk to various natural coastal hazards like coastal flooding, erosion, and storm surges has increased due to climate-induced changes in their forcing agents or hazard drivers (e.g. sea-level rise). The increased exposure (e.g. dense population living near the coast) and vulnerability (e.g. insufficient adaptation) to these hazards in the coastal areas have complicated the adaptation challenges.</p><p>Thus, monitoring coastal hazards is essential to inform suitable adaptation to increase the climate resilience of the coastal areas. In monitoring coastal climate hazards to develop coastal climate resilience, both the forcing agents and the coastal responses should be observed.</p><p>As coastal monitoring is often expensive and challenging, creating a database through a systematic analysis of low-cost sensing technologies, like UAV photogrammetry for monitoring the hazards and their drivers would be beneficial to the stakeholders. Real-time information from these low-cost sensors in complement to the existing institutional sensors will facilitate better adaptation policies including the development of early warning support for building coastal resilience. In addition, it would also provide a valuable dataset for validating coastal numerical models and providing insights into the relationship between these hazards and forcing agents. Additionally, such low-cost sensors would also create opportunities for engaging citizens in the data collection process, for efficient data collection, and increasing scientific literacy amongst the general public. For instance, in the Sensing Storm Surge Project (SSSP), citizen science was used to collect technical data to characterise estuarine storm surges, generating data useable in peer-reviewed Oceanography journals. Coastal areas show complex morphological changes in response to the forcing agents over a wide range of temporal and spatial scales. Thus, monitoring the hazards with a sufficient temporal and spatial resolution is imperative to distinguish the changes in these hazards/drivers due to climate change from natural variability. This will not only help address the response strategies to these hazards but also adjust these response strategies according to the changing vulnerability of a particular region.</p><p>The database of the low-lost sensors thus created is in no way exhaustive since those have been retrieved through a certain combination of keywords in databases like Sciencedirect, Web of Science, and Scopus, nonetheless it is useful as these are the latest low-cost sensors available to monitor the major coastal hazards in the vulnerable coastal regions.</p>
Membranes, 2022
A significant growth in the future demand for water resources is expected. Hence researchers have... more A significant growth in the future demand for water resources is expected. Hence researchers have focused on finding new technologies to develop water filtration systems by using experimental and simulation methods. These developments were mainly on membrane-based separation technology, and photocatalytic degradation of organic pollutants which play an important role in wastewater treatment by means of adsorption technology. In this work, we provide valuable critical review of the latest experimental and simulation methods on wastewater treatment by adsorption on nanomaterials for the removal of pollutants. First, we review the wastewater treatment processes that were carried out using membranes and nanoparticles. These processes are highlighted and discussed in detail according to the rate of pollutant expulsion, the adsorption capacity, and the effect of adsorption on nanoscale surfaces. Then we review the role of the adsorption process in the photocatalytic degradation of polluta...
Journal of algebra and its applications, Feb 1, 2024
Bulletin, Dec 31, 2022
Committee changes: From January 2024, the Officers of the Society remain unchanged. Thanks to Mar... more Committee changes: From January 2024, the Officers of the Society remain unchanged. Thanks to Martin Mathieu and Ray Ryan for their many years of service to the Society, including decades of service as committee members, Officers and Editors of the Bulletin. Christopher Boyd (UCD) and Thomas Huettemann (QUB) are new committee members of the IMS, having been elected at the AGM on September 1, 2023.
arXiv (Cornell University), Aug 16, 2018
Publicationes mathematicae, 2024
<p>Coastal areas are socially, economically, and environmentally in... more <p>Coastal areas are socially, economically, and environmentally intensive zones. Their risk to various natural coastal hazards like coastal flooding, erosion, and storm surges has increased due to climate-induced changes in their forcing agents or hazard drivers (e.g. sea-level rise). The increased exposure (e.g. dense population living near the coast) and vulnerability (e.g. insufficient adaptation) to these hazards in the coastal areas have complicated the adaptation challenges.</p><p>Thus, monitoring coastal hazards is essential to inform suitable adaptation to increase the climate resilience of the coastal areas. In monitoring coastal climate hazards to develop coastal climate resilience, both the forcing agents and the coastal responses should be observed.</p><p>As coastal monitoring is often expensive and challenging, creating a database through a systematic analysis of low-cost sensing technologies, like UAV photogrammetry for monitoring the hazards and their drivers would be beneficial to the stakeholders. Real-time information from these low-cost sensors in complement to the existing institutional sensors will facilitate better adaptation policies including the development of early warning support for building coastal resilience. In addition, it would also provide a valuable dataset for validating coastal numerical models and providing insights into the relationship between these hazards and forcing agents. Additionally, such low-cost sensors would also create opportunities for engaging citizens in the data collection process, for efficient data collection, and increasing scientific literacy amongst the general public. For instance, in the Sensing Storm Surge Project (SSSP), citizen science was used to collect technical data to characterise estuarine storm surges, generating data useable in peer-reviewed Oceanography journals. Coastal areas show complex morphological changes in response to the forcing agents over a wide range of temporal and spatial scales. Thus, monitoring the hazards with a sufficient temporal and spatial resolution is imperative to distinguish the changes in these hazards/drivers due to climate change from natural variability. This will not only help address the response strategies to these hazards but also adjust these response strategies according to the changing vulnerability of a particular region.</p><p>The database of the low-lost sensors thus created is in no way exhaustive since those have been retrieved through a certain combination of keywords in databases like Sciencedirect, Web of Science, and Scopus, nonetheless it is useful as these are the latest low-cost sensors available to monitor the major coastal hazards in the vulnerable coastal regions.</p>
Finite Fields and Their Applications, Mar 1, 2019
This paper classifies the derivations of group algebras in terms of the generators and defining r... more This paper classifies the derivations of group algebras in terms of the generators and defining relations of the group. If RG is a group ring, where R is commutative and S is a set of generators of G then necessary and sufficient conditions on a map from S to RG are established, such that the map can be extended to an R-derivation of RG. Derivations are shown to be trivial for semisimple group algebras of abelian groups. The derivations of finite group algebras are constructed and listed in the commutative case and in the case of dihedral groups. In the dihedral case, the inner derivations are also classified. Lastly, these results are applied to construct well known binary codes as images of derivations of group algebras.
Polymer Testing, Aug 1, 2018
A soft sensor for prediction of mechanical properties of extruded PLA sheet using an instrumented... more A soft sensor for prediction of mechanical properties of extruded PLA sheet using an instrumented slit die and machine learning algorithms,
Sensors, Apr 7, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This paper classifies the derivations of group algebras in terms of the generators and defining r... more This paper classifies the derivations of group algebras in terms of the generators and defining relations of the group. If RG is a group ring, where R is commutative and S is a set of generators of G then necessary and sufficient conditions on a map from S to RG are established, such that the map can be extended to an R-derivation of RG. Derivations are shown to be trivial for semisimple group algebras of abelian groups. The derivations of finite group algebras are constructed and listed in the commutative case and in the case of dihedral groups. In the dihedral case, the inner derivations are also classified. Lastly, these results are applied to construct well known binary codes as images of derivations of group algebras.
2023 34th Irish Signals and Systems Conference (ISSC)
Sustainability
Changes in streamflow within catchments can have a significant impact on agricultural production,... more Changes in streamflow within catchments can have a significant impact on agricultural production, as soil moisture loss, as well as frequent drying and wetting, may have an effect on the nutrient availability of many soils. In order to predict future changes and explore the impact of different scenarios, machine learning techniques have been used recently in the hydrological sector for simulation streamflow. This paper compares the use of four different models, namely artificial neural networks (ANNs), support vector machine regression (SVR), wavelet-ANN, and wavelet-SVR as surrogate models for a geophysical hydrological model to simulate the long-term daily water level and water flow in the River Shannon hydrological system in Ireland. The performance of the models has been tested for multi-lag values and for forecasting both short- and long-term time scales. For simulating the water flow of the catchment hydrological system, the SVR-based surrogate model performs best overall. Reg...
Cells, Dec 2, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Sensors
PLA (polylactide) is a bioresorbable polymer used in implantable medical and drug delivery device... more PLA (polylactide) is a bioresorbable polymer used in implantable medical and drug delivery devices. Like other bioresorbable polymers, PLA needs to be processed carefully to avoid degradation. In this work we combine in-process temperature, pressure, and NIR spectroscopy measurements with multivariate regression methods for prediction of the mechanical strength of an extruded PLA product. The potential to use such a method as an intelligent sensor for real-time quality analysis is evaluated based on regulatory guidelines for the medical device industry. It is shown that for the predictions to be robust to processing at different times and to slight changes in the processing conditions, the fusion of both NIR and conventional process sensor data is required. Partial least squares (PLS), which is the established ’soft sensing’ method in the industry, performs the best of the linear methods but demonstrates poor reliability over the full range of processing conditions. Conversely, both...
<p>Coastal areas are socially, economically, and environmentally in... more <p>Coastal areas are socially, economically, and environmentally intensive zones. Their risk to various natural coastal hazards like coastal flooding, erosion, and storm surges has increased due to climate-induced changes in their forcing agents or hazard drivers (e.g. sea-level rise). The increased exposure (e.g. dense population living near the coast) and vulnerability (e.g. insufficient adaptation) to these hazards in the coastal areas have complicated the adaptation challenges.</p><p>Thus, monitoring coastal hazards is essential to inform suitable adaptation to increase the climate resilience of the coastal areas. In monitoring coastal climate hazards to develop coastal climate resilience, both the forcing agents and the coastal responses should be observed.</p><p>As coastal monitoring is often expensive and challenging, creating a database through a systematic analysis of low-cost sensing technologies, like UAV photogrammetry for monitoring the hazards and their drivers would be beneficial to the stakeholders. Real-time information from these low-cost sensors in complement to the existing institutional sensors will facilitate better adaptation policies including the development of early warning support for building coastal resilience. In addition, it would also provide a valuable dataset for validating coastal numerical models and providing insights into the relationship between these hazards and forcing agents. Additionally, such low-cost sensors would also create opportunities for engaging citizens in the data collection process, for efficient data collection, and increasing scientific literacy amongst the general public. For instance, in the Sensing Storm Surge Project (SSSP), citizen science was used to collect technical data to characterise estuarine storm surges, generating data useable in peer-reviewed Oceanography journals. Coastal areas show complex morphological changes in response to the forcing agents over a wide range of temporal and spatial scales. Thus, monitoring the hazards with a sufficient temporal and spatial resolution is imperative to distinguish the changes in these hazards/drivers due to climate change from natural variability. This will not only help address the response strategies to these hazards but also adjust these response strategies according to the changing vulnerability of a particular region.</p><p>The database of the low-lost sensors thus created is in no way exhaustive since those have been retrieved through a certain combination of keywords in databases like Sciencedirect, Web of Science, and Scopus, nonetheless it is useful as these are the latest low-cost sensors available to monitor the major coastal hazards in the vulnerable coastal regions.</p>
Membranes, 2022
A significant growth in the future demand for water resources is expected. Hence researchers have... more A significant growth in the future demand for water resources is expected. Hence researchers have focused on finding new technologies to develop water filtration systems by using experimental and simulation methods. These developments were mainly on membrane-based separation technology, and photocatalytic degradation of organic pollutants which play an important role in wastewater treatment by means of adsorption technology. In this work, we provide valuable critical review of the latest experimental and simulation methods on wastewater treatment by adsorption on nanomaterials for the removal of pollutants. First, we review the wastewater treatment processes that were carried out using membranes and nanoparticles. These processes are highlighted and discussed in detail according to the rate of pollutant expulsion, the adsorption capacity, and the effect of adsorption on nanoscale surfaces. Then we review the role of the adsorption process in the photocatalytic degradation of polluta...