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Current Search:	All of 'Electronic' and 'Engineering' in all fields;

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Displaying Results 1476 - 1480 of 1480 on page 60 of 60

Marked Mark

Data linkage in medical science using the resource description framework: the AVERT model (2018)

O'Sullivan, Declan; Little, Mark; Hederman, Lucy

Data linkage in medical science using the resource description framework: the AVERT model (2018)

O'Sullivan, Declan; Little, Mark; Hederman, Lucy

Abstract:

There is an ongoing challenge as to how best manage and understand ?big data? in precision medicine settings. This paper describes the potential for a Linked Data approach, using a Resource Description Framework (RDF) model, to combine multiple datasets with temporal and spatial elements of varying dimensionality. This ?AVERT model? provides a framework for converting multiple standalone files of various formats, from both clinical and environmental settings, into a single data source. This data source can thereafter be queried effectively, shared with outside parties, more easily understood by multiple stakeholders using standardized vocabularies, incorporating provenance metadata and supporting temporo-spatial reasoning. The approach has further advantages in terms of data sharing, security and subsequent analysis. We use a case study relating to anti-Glomerular Basement Membrane (GBM) disease, a rare autoimmune condition, to illustrate a technical proof of concept for the AVERT m...

http://hdl.handle.net/2262/87256

Marked Mark

Analysis of EHR Free-text Data with Supervised Deep Neural Networks (2019)

Wallace, Duncan; Kechadi, Tahar

Analysis of EHR Free-text Data with Supervised Deep Neural Networks (2019)

Wallace, Duncan; Kechadi, Tahar

Abstract:

CSCE'18: The 2018 World Congress in Computer Science, Computer Engineering & Applied Computing, Las Vegas, Nevada, USA, 30 July - 02 August 2018
In this paper we present an efficient supervised deep neural network architecture to classify patients based solely on free-text notes extracted from their Electronic Health Records (EHRs). In particular, a three-layer Recurrent Neural Network was used in conjunction with the aggregated EHRs of about 127,149 patients from a medical data warehouse. The result forms a key component of an application we name PANNACEA. We evaluated this neural network in the context of competing neural network architectures, comparing the performance of multilayer perceptrons, convolutional neural networks, and recurrent neural networks in relation to the dataset under investigation. We performed evaluation our program to successfully classify the suitability of these patients to the medical service offered based upon a single medical episode.
...

http://hdl.handle.net/10197/10788

Marked Mark

Optimized single-layer MoS2 field-effect transistors by non-covalent functionalisation (2018)

Duesberg, Georg; Mc Evoy, Niall; O'Brien, Maria; Kim, HyunJeong; Yim, Chanyoung; M...

Optimized single-layer MoS2 field-effect transistors by non-covalent functionalisation (2018)

Duesberg, Georg; Mc Evoy, Niall; O'Brien, Maria; Kim, HyunJeong; Yim, Chanyoung; Marcia, Mario; Hauke, Frank; Hirsh, Andreas; Kim, Gyu-Tae; Duesberg, Georg S.; Kim, WungYeon

Abstract:

Field-effect transistors (FETs) with non-covalently functionalised molybdenum disulfide (MoS2) channels grown by chemical vapourdeposition (CVD) on SiO2are reported. The dangling-bond-freesurface of MoS2was functionalised with a perylene bisimidederivative to allow for the deposition of Al2O3dielectric. Thisallowed the fabrication of top-gated, fully encapsulated MoS2FETs. Furthermore, by the definition of vertical contacts on MoS2,devices, in which the channel area was never exposed to polymers,were fabricated. The MoS2FETs showed some of the highest mobi-lities for transistors fabricated on SiO2with Al2O3as the top-gatedielectric reported so far. Thus, gate-stack engineering using inno-vative chemistry is a promising approach for the fabrication ofreliable electronic devices based on 2D materials.

http://hdl.handle.net/2262/89565

Marked Mark

Noise in nonsmooth dynamical systems (2020)

Staunton, Eoghan J.

Noise in nonsmooth dynamical systems (2020)

Staunton, Eoghan J.

Abstract:

This article-based thesis comprises a collection of four articles, each of which constitutes a chapter, written and formatted in pre-print manuscript form. The general aim underlying these articles is to understand how noise affects the dynamics of nonsmooth dynamical systems. Nonsmooth dynamical systems arise naturally when modelling systems in engineering and applied sciences and are characterised by sudden changes in system properties. Examples of naturally arising nonsmooth systems include mechanical systems involving impacts or friction, economic or sociological systems with decision thresholds, switching electronic systems and climate systems with sharp ice-cap boundaries. The dynamical systems resulting from these models exhibit several unique behaviours including new types of bifurcations called discontinuity induced bifurcations, which can be considered the hallmark of nonsmooth systems. A level of noise or randomness is also ubiquitous in real-world systems and has been sh...

http://hdl.handle.net/10379/15739

Marked Mark

Varying Variants for AncDE with MDV Between Target and Trial Vector (MDV) Measurement (2018)

Salleh, Siti Khadijah Mohd; O'Donoghue, Diarmuid; Shibghatullah, Abdul Samad; Abas...

Varying Variants for AncDE with MDV Between Target and Trial Vector (MDV) Measurement (2018)

Salleh, Siti Khadijah Mohd; O'Donoghue, Diarmuid; Shibghatullah, Abdul Samad; Abas, Zuraida Abal

Abstract:

This paper compares standard Differential Evolution algorithm with AncDE, which adds a separate cache of recent ancestors that serve as an additional source of highquality genetic information. We compare the solutions produced by both DE and AncDE algorithms using benchmarks of 15 different numeric optimisation problems. Two distinct explorations are presented. The first test is distinct algorithmic variants of AncDE. The second part of this paper defines an MDV attribute and results are presented indicating some interesting differences in MDV between the DE and AncDE algorithms. Our findings indicate that ancestors can help to overcome some of the local variations in solutions quality and improve solution quality by improving population diversity.

http://mural.maynoothuniversity.ie/13082/