Maintaining privacy for a recommender system diagnosis using blockchain and deep learning. (2023)
Journal Article
MANTEY, E.A., ZHOU, C., MANI, V., ARTHUR, J.K. and IBEKE, E. 2023. Maintaining privacy for a recommender system diagnosis using blockchain and deep learning. Human-centric computing and information science [online], 13, article number 47. Available from: https://doi.org/10.22967/HCIS.2023.13.047

The healthcare sector has been revolutionized by Blockchain and AI technologies. Artificial intelligence uses algorithms, recommender systems, decision-making abilities, and big data to display a patient's health records using blockchain. Healthcare... Read More about Maintaining privacy for a recommender system diagnosis using blockchain and deep learning..

COVID-19 in the UK: sentiment and emotion analysis of Tweets over time. (2023)
Presentation / Conference Contribution
AMUJO, O., IBEKE, E., IWENDI, C. and BOULOUARD, Z. 2023. COVID-19 in the UK: sentiment and emotion analysis of Tweets over time. In Iwendi, C., Boulouard, Z. and Kryvinska, N. (eds.) Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTE'23): new artificial intelligence and the Internet of things based perspective and solutions, 23-24 February 2023, Bolton UK. Lecture notes in networks and systems, 735. Cham: Springer [online], pages 519-535. Available from: https://doi.org/10.1007/978-3-031-37164-6_38

We performed an analysis of tweets concerning the COVID-19 pandemic in the UK over a two-year period, selecting fifteen timelines. Over 110,000 tweets were obtained from Twitter and analysed using BERT and Text2Emotions for sentiment and emotion anal... Read More about COVID-19 in the UK: sentiment and emotion analysis of Tweets over time..

Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect. (2023)
Journal Article
AMUJO, O., IBEKE, E., FUZI, R., OGARA, U. and IWENDI, C. 2023. Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect. Sustainability [online], 15(4), article 3212. Available from: https://doi.org/10.3390/su15043212

This study aimed to analyse public sentiments of UK-originated tweets related to COVID-19 vaccines, and it applied six chronological time periods, between January and December 2021. The dates were related to six BBC news reports about the most signif... Read More about Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect..

Covid-19 fake news sentiment analysis. (2022)
Journal Article
IWENDI, C., MOHAN, S., KHAN, S., IBEKE, E., AHMADIAN, A. and CIANO, T. 2022. COVID-19 fake news sentiment analysis. Computers and electrical engineering [online], 101, article 107967. Available from: https://doi.org/10.1016/j.compeleceng.2022.107967

’Fake news’ refers to the misinformation presented about issues or events, such as COVID-19. Meanwhile, social media giants claimed to take COVID-19 related misinformation seriously, however, they have been ineffectual. This research uses the Informa... Read More about Covid-19 fake news sentiment analysis..

Recurrent neural network and reinforcement learning model for COVID-19 prediction. (2021)
Journal Article
KUMAR, R.L., KHAN, F., DIN, S., BAND, S.S., MOSAVI, A. and IBEKE, E. 2021. Recurrent neural network and reinforcement learning model for COVID-19 prediction. Frontiers in public health [online], 9, article 744100. Available from: https://doi.org/10.3389/fpubh.2021.744100

Detection and prediction of the novel Coronavirus present new challenges for the medical research community due to its widespread across the globe. Methods driven by Artificial Intelligence can help predict specific parameters, hazards, and outcomes... Read More about Recurrent neural network and reinforcement learning model for COVID-19 prediction..

Tackling pandemics in smart cities using machine learning architecture. (2021)
Journal Article
NGABO, D., DONG, W., IBEKE, E., IWENDI, C. and MASABO, E. 2021. Tackling pandemics in smart cities using machine learning architecture. Mathematical biosciences and engineering [online], 18(6): the advances in cybersecurity theory and applications, pages 8444-8461. Available from: https://doi.org/10.3934/mbe.2021418

With the recent advancement in analytic techniques and the increasing generation of healthcare data, artificial intelligence (AI) is reinventing the healthcare system for tackling pandemics securely in smart cities. AI tools continue register numerou... Read More about Tackling pandemics in smart cities using machine learning architecture..

E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions. (2021)
Presentation / Conference Contribution
UGOCHUKWU-IBE, I.M. and IBEKE, E. 2021. E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions. In Xhina, E. and Hoxha, K. (eds.) Recent trends and applications in computer science and information technology: proceedings of 4th Recent trends and applications in computer science and information technology international conference 2021 (RTA-CSIT 2021), 21-22 May 2021 [virtual conference]. CEUR workshop proceedings, 2872. Aachen: CEUR-WS [online], pages 46-51. Available from: http://ceur-ws.org/Vol-2872/paper07.pdf

This paper examines the challenges of teaching technical courses through e-learning in Nigerian tertiary institutions during the COVID-19 pandemic lockdown. The COVID-19 pandemic has widespread after-effect on education systems all over the world, wi... Read More about E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions..