Outputs (111)

Topology for preserving feature correlation in tabular synthetic data. (2022)
Presentation / Conference Contribution
ARIFEEN, M. and PETROVSKI, A. 2022. Topology for preserving feature correlation in tabular synthetic data. In Proceedings of the 15th IEEE (Institute of Electrical and Electronics Engineers) International conference on security of information and networks 2022 (SINCONF 2022), 11-13 November 2022, Sousse, Tunisia. Piscataway: IEEE [online], pages 61-66. Available from: https://doi.org/10.1109/SIN56466.2022.9970505

Tabular synthetic data generating models based on Generative Adversarial Network (GAN) show significant contributions to enhancing the performance of deep learning models by providing a sufficient amount of training data. However, the existing GAN-ba... Read More about Topology for preserving feature correlation in tabular synthetic data..

Programming language evaluation criteria for safety-critical software in the air domain. (2022)
Presentation / Conference Contribution
ASHMORE, R., HOWE, A., CHILTON, R. and FAILY, S. 2022. Programming language evaluation criteria for safety-critical software in the air domain. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) International symposium on software reliability engineering workshops (ISSREW 2022), 31 October - 3 November 2022, Charlotte, NC, USA. Los Alamitos: IEEE Computer Society [online], pages 230-237. Available from: https://doi.org/10.1109/ISSREW55968.2022.00072

Safety-critical software in the air domain typically conforms to RTCA DO-178C. However, latent failures might arise based on assumptions underpinning the programming language used to write the software, whereas the lack of empirical data may constrai... Read More about Programming language evaluation criteria for safety-critical software in the air domain..

Implementing spot the differences game using Yolo algorithm. (2022)
Presentation / Conference Contribution
KONDAPANENI, C.S., TEJA, M.V.S., KAVURI, R., TINNAVALLI, D. and BANO, S. 2022. Implementing spot the differences game using YOLO algorithm. In Kumar, A., Ghinea, G., Merugu, S. and Hashimoto, T. (eds.) Proceedings of the 2021 International conference on cognitive and intelligent computing (ICCIC 2021), 11-12 December 2021, Hyderabad, India. Volume 1. Singapore: Springer [online], pages 707-719. Available from: https://doi.org/10.1007/978-981-19-2350-0_67

The requirement for object detection has been expanding with computational force. Object identification is a technique that identifies the semantic class of the objects in the image or video. In this work, we talk about implementing an application th... Read More about Implementing spot the differences game using Yolo algorithm..

Privacy goals for the data lifecycle. (2022)
Journal Article
HENRIKSEN-BULMER, J., YUCEL, C., FAILY, S. and CHALKIAS, I. 2022. Privacy goals for the data lifecycle. Future internet [online], 14(11), article number 315. Available from: https://doi.org/10.3390/fi14110315

The introduction of Data Protection by Default and Design (DPbDD) brought in as part of the General Data Protection Regulation (GDPR) in 2018, has necessitated that businesses review how best to incorporate privacy into their processes in a transpare... Read More about Privacy goals for the data lifecycle..

Bi-level optimisation and machine learning in the management of large service-oriented field workforces. (2022)
Thesis
AINSLIE, R.T. 2022. Bi-level optimisation and machine learning in the management of large service-oriented field workforces. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1880200

The tactical planning problem for members of the service industry with large multi-skilled workforces is an important process that is often underlooked. It sits between the operational plan - which involves the actual allocation of members of the wor... Read More about Bi-level optimisation and machine learning in the management of large service-oriented field workforces..

Employing multi-modal sensors for personalised smart home health monitoring. (2022)
Thesis
FORBES, G. 2022. Employing multi-modal sensors for personalised smart home health monitoring. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2071646

Smart home systems are employed worldwide for a variety of automated monitoring tasks. FITsense is a system that performs personalised smart home health monitoring using sensor data. In this thesis, we expand upon this system by identifying the limit... Read More about Employing multi-modal sensors for personalised smart home health monitoring..

A novel gradient-guided post-processing method for adaptive image steganography. (2022)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H. and LI, R. 2023. A novel gradient-guided post-processing method for adaptive image steganography. Signal processing [online], 203, article 108813. Available from: https://doi.org/10.1016/j.sigpro.2022.108813

Designing an effective cost function has always been the key in image steganography after the development of the near-optimal encoders. To learn the cost maps automatically, the Generative Adversarial Networks (GAN) are often trained from the given c... Read More about A novel gradient-guided post-processing method for adaptive image steganography..

Content type profiling of data-to-text generation datasets. (2022)
Presentation / Conference Contribution
UPADHYAY, A. and MASSIE, S. 2022. Content type profiling of data-to-text generation datasets. In N. Calzolari, C.-R. Huang, H. Kim. et al. (eds.) Proceedings of the 29th International conference on computational linguistics (COLING 2022), 12-17 October 2022, Gyeongju, Republic of Korea. Stroudsburg, PA: International Committee on Computational Linguistics [online], 29(1), pages 5770–5782. Available from: https://aclanthology.org/2022.coling-1.pdf

Data-to-Text Generation (D2T) problems can be considered as a stream of time-stamped events with a text summary being produced for each. The problem becomes more challenging when event summaries contain complex insights derived from multiple records... Read More about Content type profiling of data-to-text generation datasets..

Influencing student academic integrity choices using ethics scenarios. (2022)
Presentation / Conference Contribution
DANIELS, M., BERGLUND, A. and MCDERMOTT, R. 2022. Influencing student academic integrity choices using ethics scenarios. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2022), 8-11 October 2022, Uppsala, Sweden. Piscataway: IEEE [online], article 9962607. Available from: https://doi.org/10.1109/FIE56618.2022.9962607

Academic misconduct seems to have increased substantially during the pandemic, with a worldwide upsurge in reported cases. The aim of this project is to construct a framework for helping students engage with issues concerning academic integrity and a... Read More about Influencing student academic integrity choices using ethics scenarios..

Phronesis: deliberative judgement as a key competence in the post-Covid educational environment. (2022)
Presentation / Conference Contribution
MCDERMOTT, R. and DANIELS, M. 2022. Phronesis: deliberative judgement as a key competence in the post-Covid educational environment. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2022), 8-11 October 2022, Uppsala, Sweden. Piscataway: IEEE [online], article 9962515. Available from: https://doi.org/10.1109/FIE56618.2022.9962515

The global Covid19 pandemic which began in early 2020 is one of the most socially disruptive events to have occurred since the Second World War. It has left a profound mark on the institutions of society, including those charged with education, and i... Read More about Phronesis: deliberative judgement as a key competence in the post-Covid educational environment..