Outputs (25)

Assessing the capabilities of ChatGPT in recognising customer intent in a small training data scenario. (2024)
Presentation / Conference
EZENKWU, C.P., IBEKE, E. and IWENDI, C. 2024. Assessing the capabilities of ChatGPT in recognising customer intent in a small training data scenario. To be presented at the 3rd International conference on advanced communication and intelligent systems (ICACIS 2024), 16-17 May 2024, New Delhi, India.

This study addresses the issue of recognising customer intent when only limited training data is available. The performance of ChatGPT was evaluated in this scenario, and it was found to be better than traditional machine learning algorithms and the... Read More about Assessing the capabilities of ChatGPT in recognising customer intent in a small training data scenario..

Using entropy to measure text readability in Bahasa Malaysia for year one students. (2024)
Journal Article
BARAWI, M.H., OSMAN, S.N.M., ABD YUSOF, N.F., IBEKE, E. and FADHLI, M. 2024. Using entropy to measure text readability in Bahasa Malaysia for year one students. Journal of cognitive sciences and human development [online], 10(1), pages 103-123. Available from: https://doi.org/10.33736/jcshd.6817.2024

Text readability is essential for effective learning and communication, especially for beginner readers. However, there are no known measures to calculate the readability of Bahasa Malaysia, the national language of Malaysia. This research proposes a... Read More about Using entropy to measure text readability in Bahasa Malaysia for year one students..

Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies. (2024)
Journal Article
EZENKWU, C.P., CANNON, S. and IBEKE, E. 2024. Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies. Environmental monitoring and assessment [online], 196(3), article number 231. Available from: https://doi.org/10.1007/s10661-024-12388-6

Across the globe, governments are developing policies and strategies to reduce carbon emissions to address climate change. Monitoring the impact of governments' carbon reduction policies can significantly enhance our ability to combat climate change... Read More about Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies..

Agriculture in Africa: the emerging role of artificial intelligence. (2023)
Book Chapter
ADEBOLA, T. and IBEKE, E. 2023. Agriculture in Africa: the emerging role of artificial intelligence. In Ncube, C., Oriakhogba, D., Rutenberg, I. and Schonwetter, T. (eds.) Artificial intelligence and the law in Africa. Johannesburg: Lexis Nexis [online], Chapter 14. Available from: https://myacademic.co.za/product/artificial-intelligence-and-the-law-in-africa/

This chapter critically considers the application of artificial intelligence (AI) to agriculture in Africa. It contends that, while African countries can utilise AI to address agricultural challenges, realising the full potential of AI in agriculture... Read More about Agriculture in Africa: the emerging role of artificial intelligence..

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..

Bibliometric analysis of scientific literature on mental health research in Africa. (2023)
Conference Proceeding
EGWUOGU, C., IBEKE, E., CHAURASIA, P., IWENDI, C. and BOULOUARD, Z. 2023. Bibliometric analysis of scientific literature on mental health research in Africa. In Iwendi, C., Boulouard, Z. and Kryvinska, N. (eds.) Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTCE'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 469-489. Available from: https://doi.org/10.1007/978-3-031-37164-6_35

This bibliometric study presents a comprehensive summary of literature published on mental health research in Africa. The region has a large number of scientific studies conducted in this area. The purpose of this study was to investigate the contrib... Read More about Bibliometric analysis of scientific literature on mental health research in Africa..

COVID-19 in the UK: sentiment and emotion analysis of Tweets over time. (2023)
Conference Proceeding
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..

A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications. (2023)
Conference Proceeding
HAI, T., WANG, D., SEETHARAMAN, T., AMELESH, M, SREEJITH, P.M., SHARMA, V., IBEKE, E. and LIU, H. 2023. A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications. In Iwendi, C., Boulouard, Z. and Kryvinska, N. (eds.) Proceedings of the 2023 International conference on advances in communication technology and computer engineering (ICACTCE'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 105-118. Available from: https://doi.org/10.1007/978-3-031-37164-6_9

The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for... Read More about A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications..

An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm. (2023)
Journal Article
HAI, T., ZHOU, J., LU, Y., JAWAWI, D., WANG, D., SELVARAJAN, S., MANOHARAN, H. and IBEKE, E. 2023. An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm. Journal of cloud computing [online], 12, article 73. Available from: https://doi.org/10.1186/s13677-023-00449-z

Numerous users are experiencing unsafe communications due to the growth of big network mediums, where no node communication is detected in emergency scenarios. Many people find it difficult to communicate in emergency situations as a result of such c... Read More about An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm..

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..