Outputs (130)

NLP-based prediction of medical specialties at hospital admission using triage notes (2021)
Presentation / Conference Contribution

Data Analytics is rapidly expanding within the healthcare domain to help develop strategies for improving the quality of care and curbing costs as well. Natural Language Processing (NLP) solutions have received particular attention whereas a large pa... Read More about NLP-based prediction of medical specialties at hospital admission using triage notes.

Art as data set, data set as art: Training machine vision systems to see as artists (2021)
Presentation / Conference Contribution

Technology enhance learning: A case study of the potentials of mobile technologies in Nigerian College of Education (2021)
Thesis

Technology has proven to be an effective tool and a driving force for developments in the education sector, hence the term “technology enhanced learning” (TEL). Despite the continuous impact of technology in education, the lack of TEL in teacher educ... Read More about Technology enhance learning: A case study of the potentials of mobile technologies in Nigerian College of Education.

Stimulating fungi Pleurotus ostreatus with hydrocortisone (2021)
Journal Article

Fungi cells can sense extracellular signals via reception, transduction, and response mechanisms, allowing them to communicate with their host and adapt to their environment. They feature effective regulatory protein expressions that enhance and regu... Read More about Stimulating fungi Pleurotus ostreatus with hydrocortisone.

Comparison of agent deployment strategies for collaborative prognosis (2021)
Presentation / Conference Contribution

Collaborative prognosis is a technique that enables the industrial assets to learn from similar other assets in a fleet, and improve their data-driven prognosis models. When collaborative prognosis is implemented in a computationally distributed fram... Read More about Comparison of agent deployment strategies for collaborative prognosis.

A fitted radiance and attenuation model for realistic atmospheres (2021)
Journal Article

We present a fitted model of sky dome radiance and attenuation for realistic terrestrial atmospheres. Using scatterer distribution data from atmospheric measurement data, our model considerably improves on the visual realism of existing analytical cl... Read More about A fitted radiance and attenuation model for realistic atmospheres.

A comparative analysis for binary search operators used in artificial bee colony (2021)
Presentation / Conference Contribution

Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications... Read More about A comparative analysis for binary search operators used in artificial bee colony.

Feature vulnerability and robustness assessment against adversarial machine learning attacks (2021)
Presentation / Conference Contribution

Whilst machine learning has been widely adopted for various domains, it is important to consider how such techniques may be susceptible to malicious users through adversarial attacks. Given a trained classifier, a malicious attack may attempt to craf... Read More about Feature vulnerability and robustness assessment against adversarial machine learning attacks.

"Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems (2021)
Presentation / Conference Contribution

In March 2020, the COVID-19 pandemic led to a dramatic shift in educational practice, whereby home-schooling and remote working became the norm. Many typical schools outreach projects to encourage uptake of learning cyber security skills therefore we... Read More about "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems.

Unsupervised one-class learning for anomaly detection on home IoT network devices (2021)
Presentation / Conference Contribution

In this paper we study anomaly detection methods for home IoT devices. Specifically, we address unsupervised one-class learning methods due to their ability to learn deviations from a single normal class. In a home IoT environment, this consideration... Read More about Unsupervised one-class learning for anomaly detection on home IoT network devices.