ORCID Profile
0000-0002-9704-7651
Current Organisation
Queen's University Belfast
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Publisher: IEEE
Date: 10-2021
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: IEEE
Date: 11-2015
DOI: 10.1109/CCBD.2015.33
Publisher: IEEE
Date: 03-2011
DOI: 10.1109/AINA.2011.20
Publisher: MDPI AG
Date: 21-06-2022
DOI: 10.3390/S22134677
Abstract: Human movement is generally evaluated through both observations and clinical assessment scales to identify the state and deterioration of a patient’s motor control. Lately, technological systems for human motion analysis have been used in clinics to identify abnormal movement states, while they generally suffer from privacy challenges and concerns especially at home or in remote places. This paper presents a novel privacy preservation and quantification methodology that imitates the forgetting process of human memory to protect privacy in patient-centric healthcare. The privacy preservation principle of this methodology is to change the traditional data analytic routines into a distributed and disposable form (i.e., DnD) so as to naturally minimise the disclosure of patients’ health data. To help judge the efficacy of DnD-based privacy preservation, the researchers further developed a risk-driven privacy quantification framework to supplement the existing privacy quantification techniques. To facilitate validating the methodology, this research also involves a home-care-oriented movement analysis system that comprises a single inertial measurement sensor and a mobile application. The system can acquire personal information, raw data of movements and indexes to evaluate the risk of falls and gait at homes. Moreover, the researchers conducted a technological appreciation survey of 16 health professionals to help understand the perception of this research. The survey obtains positive feedback regarding the movement analysis system and the proposed methodology as suitable for home-care scenarios.
Publisher: ASTES Journal
Date: 02-2018
DOI: 10.25046/AJ030163
Publisher: Canadian Center of Science and Education
Date: 22-09-2013
Publisher: Springer Singapore
Date: 26-10-2021
Publisher: IEEE
Date: 04-2018
Publisher: Elsevier BV
Date: 07-2014
Publisher: IEEE
Date: 12-2017
Publisher: Elsevier BV
Date: 10-2018
Publisher: IEEE
Date: 10-2020
Publisher: Royal Society of Chemistry (RSC)
Date: 2010
DOI: 10.1039/C0DT00838A
Abstract: A range of androgen conjugates with non-conventional platinum(II) complexes have been synthesised with the aim of targeting tumour cells since many display elevated levels of the androgen receptor. The androgenic platinum conjugates are delivered into selected cells with improved efficiency (when compared to their non-steroidal analogues). The act of conjugating an androgen to a platinum(II) complex resulted in synergistic effects between the metallic centre and the steroidal ligand, creating highly potent platinum(II) complexes from the inactive components.
Publisher: Inderscience Publishers
Date: 2012
Publisher: IEEE
Date: 07-2018
Publisher: IEEE
Date: 12-2010
Publisher: Institute of Advanced Engineering and Science
Date: 02-12-2013
Publisher: Wiley
Date: 02-05-2021
DOI: 10.1002/CPE.5323
Publisher: IEEE
Date: 06-2013
Publisher: IEEE
Date: 11-2019
Publisher: IEEE
Date: 03-2013
DOI: 10.1109/AINA.2013.99
Publisher: IEEE
Date: 06-2016
Publisher: IEEE
Date: 12-2012
Publisher: Services Society
Date: 04-2016
Publisher: Elsevier BV
Date: 04-2016
Publisher: IEEE
Date: 12-2013
Publisher: ACM
Date: 18-12-2021
Publisher: IEEE
Date: 04-2014
Publisher: Wiley
Date: 13-05-2016
Publisher: IEEE
Date: 05-2022
Publisher: IEEE
Date: 12-2017
Publisher: IEEE
Date: 12-2017
Publisher: IEEE
Date: 2010
DOI: 10.1109/ICIW.2010.59
Publisher: ACM
Date: 21-06-2010
Publisher: Services Society
Date: 10-2014
Publisher: Springer International Publishing
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IGI Global
Date: 07-2013
Abstract: Appropriate performance evaluations of commercial Cloud services are crucial and beneficial for both customers and providers to understand the service runtime, while suitable experimental design and analysis would be vital for practical evaluation implementations. However, there seems to be a lack of effective methods for Cloud services performance evaluation. For ex le, in most of the existing evaluation studies, experimental factors (also called parameters or variables) were considered randomly and intuitively, experimental s le sizes were determined on the fly, and few experimental results were comprehensively analyzed. To address these issues, the authors suggest applying Design of Experiments (DOE) to Cloud services evaluation. To facilitate applying DOE techniques, this paper introduces an experimental factor framework and a set of DOE application scenarios. As such, new evaluators can explore and conveniently adapt our work to their own experiments for performance evaluation of commercial Cloud services.
Publisher: Royal Society of Chemistry (RSC)
Date: 2010
DOI: 10.1039/C0DT00839G
Abstract: Previously a range of androgen conjugates with non-conventional platinum(II) complexes have been synthesised with the aim of enhancing cellular delivery, and which have shown increased cytotoxic activity compared with non-steroidal compounds (M. J. Hannon et al., Dalton Trans., 2010, DOI: 10.1039/c0dt00838a). To further study this, the complexes have been assessed for their ability to bind to and alter the structure of DNA. All platinum(II) complexes studied herein bind to model nucleo-bases and DNA, but to our surprise, testosterone-based complexes caused the DNA helix to undergo significant unwinding and bending, whereas non-steroidal control complexes caused minimal structural alterations. These effects are similar to those cisplatin induces on DNA structure despite the fact that these compounds produce a monofunctional lesion. This ability attributed to interactions between the DNA helix and bulky steroidal skeleton of testosterone, coupled with the enhanced cellular delivery induced by the steroid make the steroid approach an exciting way to explore non-conventional platinum drug delivery.
Publisher: MDPI AG
Date: 26-10-2023
DOI: 10.3390/F14112133
Publisher: IEEE
Date: 11-2012
DOI: 10.1109/CSC.2012.33
Publisher: Springer Science and Business Media LLC
Date: 19-11-2017
Publisher: ACM
Date: 07-11-2022
Publisher: IEEE
Date: 03-2021
Publisher: Association for Computing Machinery (ACM)
Date: 25-02-2016
Abstract: Software engineering considers performance evaluation to be one of the key portions of software quality assurance. Unfortunately, there seems to be a lack of standard methodologies for performance evaluation even in the scope of experimental computer science. Inspired by the concept of "instantiation" in object-oriented programming, we distinguish the generic performance evaluation logic from the distributed and ad-hoc relevant studies, and develop an abstract evaluation methodology (by analogy of "class") we name Domain Knowledge-driven Methodology (DoKnowMe). By replacing five predefined domain-specific knowledge artefacts, DoKnowMe could be instantiated into specific methodologies (by analogy of "object") to guide evaluators in performance evaluation of different software and even computing systems. We also propose a generic validation framework with four indicators (i.e. usefulness, feasibility, effectiveness and repeatability), and use it to validate DoKnowMe in the Cloud services evaluation domain. Given the positive and promising validation result, we plan to integrate more common evaluation strategies to improve DoKnowMe and further focus on the performance evaluation of Cloud autoscaler systems.
Publisher: Springer International Publishing
Date: 2015
Publisher: IEEE
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
Publisher: IEEE
Date: 12-2018
Publisher: Springer Science and Business Media LLC
Date: 02-12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2014
DOI: 10.1109/TSC.2013.39
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2016
Publisher: Elsevier BV
Date: 09-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Elsevier BV
Date: 11-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2017
Publisher: Elsevier BV
Date: 03-2022
Publisher: IEEE
Date: 06-2012
Publisher: MDPI AG
Date: 13-08-2021
DOI: 10.3390/APP11167461
Abstract: Machine learning techniques generally require or assume balanced datasets. Skewed data can make machine learning systems never function properly, no matter how carefully the parameter tuning is conducted. Thus, a common solution to the problem of high skewness is to pre-process data (e.g., log transformation) before applying machine learning to deal with real-world problems. Nevertheless, this pre-processing strategy cannot be employed for online machine learning, especially in the context of edge computing, because it is barely possible to foresee and store the continuous data flow on IoT devices on the edge. Thus, it will be crucial and valuable to enable skewness monitoring in real time. Unfortunately, there exists a surprising gap between practitioners’ needs and scientific research in running statistics for monitoring real-time skewness, not to mention the lack of suitable remedies for skewed data at runtime. Inspired by Welford’s algorithm, which is the most efficient approach to calculating running variance, this research developed efficient calculation methods for three versions of running skewness. These methods can conveniently be implemented as skewness monitoring modules that are affordable for IoT devices in different edge learning scenarios. Such an IoT-friendly skewness monitoring eventually acts a cornerstone for developing the research field of skewness-aware online edge learning. By initially validating the usefulness and significance of skewness awareness in edge learning implementations, we also argue that conjoint research efforts from relevant communities are needed to boost this promising research field.
Publisher: Springer Science and Business Media LLC
Date: 06-2020
Publisher: IEEE
Date: 05-2021
Publisher: IEEE
Date: 12-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
Publisher: Springer Berlin Heidelberg
Date: 2015
Publisher: IEEE
Date: 09-2012
DOI: 10.1109/GRID.2012.15
Publisher: IEEE
Date: 03-2017
DOI: 10.1109/AINA.2017.79
Publisher: IEEE
Date: 10-2015
Publisher: IEEE
Date: 11-2016
Publisher: MDPI AG
Date: 06-03-2019
DOI: 10.3390/S19051134
Abstract: The ubiquitous Internet of Things (IoT) devices nowadays are generating various and numerous data from everywhere at any time. Since it is not always necessary to centralize and analyze IoT data cumulatively (e.g., the Monte Carlo analytics and Convergence analytics demonstrated in this article), the traditional implementations of big data analytics (BDA) will suffer from unnecessary and expensive data transmissions as a result of the tight coupling between computing resource management and data processing logics. Inspired by software-defined infrastructure (SDI), we propose the “microservice-oriented platform” to break the environmental monolith and further decouple data processing logics from their underlying resource management in order to facilitate BDA implementations in the IoT environment (which we name “IoBDA”). Given predesigned standard microservices with respect to specific data processing logics, the proposed platform is expected to largely reduce the complexity in and relieve inexperienced practices of IoBDA implementations. The potential contributions to the relevant communities include (1) new theories of a microservice-oriented platform on top of SDI and (2) a functional microservice-oriented platform for IoBDA with a group of predesigned microservices.
Publisher: Springer Science and Business Media LLC
Date: 12-03-2021
DOI: 10.1186/S13677-021-00241-X
Abstract: Adding buffers to networks is part of the fundamental advance in data communication. Since edge cloud computing is based on the heterogeneous collaboration network model in a federated environment, it is natural to consider buffer-aided data communication for edge cloud applications. However, the existing studies generally pursue the beneficial features of buffering at a cost of time, not to mention that many investigations are focused on lower-layer data packets rather than application-level communication transactions. Driven by our argument against the claim that buffers “can introduce additional delay to the communication between the source and destination”, this research aims to investigate whether or not (and if yes, to what extent) the application-level buffering mechanism can improve the time efficiency in edge-cloud data transmissions. To collect empirical evidence for the theoretical discussion, we built up a testbed to simulate a remote health monitoring system, and conducted both experimental and modeling investigations into the first-in-first-served (FIFS) and buffer-aided data transmissions at a relay node in the system. An empirical inequality system is established for revealing the time efficiency of buffer-aided edge cloud communication. For ex le, given the reference of transmitting the 11th data entity in the FIFS manner, the inequality system suggests buffering up to 50 data entities into one transmission transaction on our testbed. Despite the trade-off benefits (e.g., energy efficiency and fault tolerance) of buffering data, our investigation argues that the buffering mechanism can also speed up data transmission under certain circumstances, and thus it would be worth taking data buffering into account when designing and developing edge cloud applications even in the time-critical context.
Publisher: IEEE
Date: 07-2019
Publisher: IEEE
Date: 06-2010
DOI: 10.1109/SOSE.2010.29
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Location: China
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2018
End Date: End date not available
Funder: Fondo Nacional de Desarrollo Científico y Tecnológico
View Funded Activity