ORCID Profile
0000-0001-5005-5809
Current Organisation
University of Hertfordshire
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Publisher: IEEE
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 04-2017
Publisher: MDPI AG
Date: 04-2023
DOI: 10.3390/S22218138
Abstract: This paper proposes a methodology for sentiment analysis with emphasis on the emotional aspects of people visiting the Herculaneum Archaeological Park in Italy during the period of the COVID-19 pandemic. The methodology provides a valuable means of continuous feedback on perceived risk of the site. A semantic analysis on Twitter text messages provided input to the risk management team with which they could respond immediately mitigating any apparent risk and reducing the perceived risk. A two-stage approach was adopted to prune a massively large dataset from Twitter. In the first phase, a social network analysis and visualisation tool NodeXL was used to determine the most recurrent words, which was achieved using polarity. This resulted in a suitable subset. In the second phase, the subset was subjected to sentiment and emotion mapping by survey participants. This led to a hybrid approach of using automation for pruning datasets from social media and using a human approach to sentiment and emotion analysis. Whilst suffering from COVID-19, equally, people suffered due to loneliness from isolation dictated by the World Health Organisation. The work revealed that despite such conditions, people’s sentiments demonstrated a positive effect from the online discussions on the Herculaneum site.
Publisher: IEEE
Date: 10-2019
Publisher: IEEE
Date: 10-2018
Publisher: IEEE
Date: 06-2011
Publisher: IEEE
Date: 03-2012
Publisher: IEEE
Date: 10-2017
Publisher: Springer International Publishing
Date: 25-10-2018
Publisher: IEEE
Date: 10-2014
Publisher: IEEE
Date: 10-2012
Publisher: IEEE
Date: 08-2010
Publisher: InTech
Date: 04-04-2012
DOI: 10.5772/35448
Publisher: IEEE
Date: 12-2010
Publisher: IEEE
Date: 10-2018
Publisher: IEEE
Publisher: IEEE
Date: 10-2016
Publisher: Elsevier BV
Date: 02-2000
Publisher: IEEE
Date: 12-2010
Publisher: IEEE
Date: 10-2016
Publisher: IEEE
Publisher: Springer International Publishing
Date: 25-10-2018
Publisher: IEEE
Date: 10-2019
Publisher: MDPI AG
Date: 14-09-2020
DOI: 10.3390/S20185252
Abstract: IoT systems differ from traditional Internet systems in that they are different in scale, footprint, power requirements, cost and security concerns that are often overlooked. IoT systems inherently present different fail-safe capabilities than traditional computing environments while their threat landscapes constantly evolve. Further, IoT devices have limited collective security measures in place. Therefore, there is a need for different approaches in threat assessments to incorporate the interdependencies between different IoT devices. In this paper, we run through the design cycle to provide a security-focused approach to the design of IoT systems using a use case, namely, an intelligent solar-panel project called Daedalus. We utilise STRIDE/DREAD approaches to identify vulnerabilities using a thin secure element that is an embedded, t er proof microprocessor chip that allows the storage and processing of sensitive data. It benefits from low power demand and small footprint as a crypto processor as well as is compatible with IoT requirements. Subsequently, a key agreement based on an asymmetric cryptographic scheme, namely B-SPEKE was used to validate and authenticate the source. We find that end-to-end and independent stand-alone procedures used for validation and encryption of the source data originating from the solar panel are cost-effective in that the validation is carried out once and not several times in the chain as is often the case. The threat model proved useful not so much as a panacea for all threats but provided the framework for the consideration of known threats, and therefore appropriate mitigation plans to be deployed.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2006
Publisher: IEEE
Date: 2005
Publisher: IEEE
Date: 2005
Publisher: IEEE
Date: 10-2013
DOI: 10.1109/SMC.2013.750
Publisher: IEEE
Date: 10-2016
Publisher: IEEE
Date: 10-2017
Publisher: Institution of Engineering and Technology (IET)
Date: 03-2013
Publisher: IEEE
Publisher: IEEE
Date: 10-2012
Publisher: World Scientific Pub Co Pte Lt
Date: 10-2002
DOI: 10.1142/S0219467802000809
Abstract: To use the Hough transform to detect shapes we need to accumulate votes for the edge passing a specific bin. Most existing Hough transform techniques use a sharp (crisp) cutoff to determine whether the bin has received a vote or not. This results in considerable errors. In this paper, we propose a new line Hough transform (LHT) using evidence accumulation and fuzzy aggregation function. The resulting voting process is dependent on the distance ρ from the grid centers. This effectively handles uncertainty in the accumulation process and achieves a better performance. To show the effectiveness this approach, we present our experimental results for a set of 2D parametric and 3D nonparametric objects.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Soodamani Ramalingam.