All Outputs (31)

Assessing the impact of artificial intelligence technology in education. [Dataset] (2024)
Data
ABOLLE-OKOYEAGU, C.J., EZENKWU, C.P., IBEKE, E. and ONOJA, O.P. 2024. Assessing the impact of artificial intelligence technology in education. [Dataset]. Hosted on Mendeley Data [online], version 1. Available from: https://doi.org/10.17632/zwjkbstpw4.1

This research seeks to understand how artificial intelligence (AI) technology impacts teaching and learning in education. Data was collected by survey of participants with engineering education experience.

A systematic review on blockchain-based access control systems in cloud environment. (2024)
Journal Article
PUNIA, A., GULIA, P., GILL, N.S., IBEKE, E., IWENDI, C. and SHUKLA, P.K. 2024. A systematic review on blockchain-based access control systems in cloud environment. Journal of cloud computing [online], 13, article number 146. Available from: https://doi.org/10.1186/s13677-024-00697-7

The widespread adoption of cloud computing has dramatically altered how data is stored, processed, and accessed in an era. The rapid development of digital technologies characterizes all this. The widespread adoption of cloud services has introduced... Read More about A systematic review on blockchain-based access control systems in cloud environment..

Assessing the research scene of green AI via bibliometric analysis. (2024)
Presentation / Conference Contribution
ABDULMALIK, M.R., IBEKE, E., EZENKWU, C.P. and IWENDI, C. [2024]. Assessing the research scene of green AI via bibliometric analysis. To be published in the Proceedings of the 2024 International conference on advances in communication technology and computer engineering (ICACTCE'24), 29-30 November 2024, Marrakech, Morocco. Lecture notes in networks and systems (LNNS). Cham: Springer [online], (accepted). To be made available from: https://www.springer.com/series/15179

The environmental impact of artificial intelligence (AI) continues to rise as more people embrace the technology. The optimization of AI models to be more efficient, use less energy, and emit low carbon is essential. This bibliometric study presents... Read More about Assessing the research scene of green AI via bibliometric analysis..

Investigating key contributors to hospital appointment no-shows using explainable AI. (2024)
Presentation / Conference Contribution
YIYE, V., UGBOMEH, O., EZENKWU, C.P., IBEKE, E., SHARMA, V. and ALKHAYYAT, A. 2024. Investigating key contributors to hospital appointment no-shows using explainable AI. In Proceedings of the 2024 International conference on electrical, electronics and computing technologies (ICEECT 2024), 29-31 August 2024, Greater Noida, India. Piscataway: IEEE [online], article 10739123. Available from: https://doi.org/10.1109/ICEECT61758.2024.10739123

The healthcare sector has suffered from wastage of resources and poor service delivery due to the significant impact of appointment no-shows. To address this issue, this paper uses explainable artificial intelligence (XAI) to identify major predictor... Read More about Investigating key contributors to hospital appointment no-shows using explainable AI..

Machine learning algorithms for stroke risk prediction leveraging on explainable artificial intelligence techniques (XAI). (2024)
Presentation / Conference Contribution
UGBOMEH, O., YIYE, V., IBEKE, E., EZENKWU, C.P., SHARMA, V. and ALKHAYYAT, A. 2024. Machine learning algorithms for stroke risk prediction leveraging on explainable artificial intelligence techniques (XAI). In Proceedings of the 2024 International conference on electrical, electronics and computing technologies (ICEECT 2024), 29-31 August 2024, Greater Noida, India. Piscataway: IEEE [online], article 10739320. Available from: https://doi.org/10.1109/ICEECT61758.2024.10739320

Stroke poses a significant global health challenge, contributing to widespread mortality and disability. Identifying predictors of stroke risk is crucial for enabling timely interventions, thereby reducing the increasing impact of strokes. This resea... Read More about Machine learning algorithms for stroke risk prediction leveraging on explainable artificial intelligence techniques (XAI)..

Assessing the capabilities of ChatGPT in recognising customer intent in a small training data scenario. (2024)
Presentation / Conference Contribution
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..

CIA security for internet of vehicles and blockchain-AI integration. (2024)
Journal Article
HAI, T., AKSOY, M., IWENDI, C., IBEKE, E. and MOHAN, S. 2024. CIA security for internet of vehicles and blockchain-AI integration. Journal of grid computing [online], 22(2), article number 43. Available from: https://doi.org/10.1007/s10723-024-09757-3

The lack of data security and the hazardous nature of the Internet of Vehicles (IoV), in the absence of networking settings, have prevented the openness and self-organization of the vehicle networks of IoV cars. The lapses originating in the areas of... Read More about CIA security for internet of vehicles and blockchain-AI integration..

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)
Presentation / Conference Contribution
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..

A novel and innovative blockchain-empowered federated learning approach for secure data sharing in smart city applications. (2023)
Presentation / Conference Contribution
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..

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..

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..

Voice spoofing countermeasure for voice replay attacks using deep learning. (2022)
Journal Article
ZHOU, J., HAI, T., JAWAWI, D.N.A., WANG, D., IBEKE, E. and BIAMBA, C. 2022. Voice spoofing countermeasure for voice replay attacks using deep learning. Journal of cloud computing: advances, systems and applications [online], 11, article number 51. Available from: https://doi.org/10.1186/s13677-022-00306-5

In our everyday lives, we communicate with each other using several means and channels of communication, as communication is crucial in the lives of humans. Listening and speaking are the primary forms of communication. For listening and speaking, th... Read More about Voice spoofing countermeasure for voice replay attacks using deep learning..

Fintech application on banking stability using big data of an emerging economy. (2022)
Journal Article
YIN, F., JIAO, X., ZHOU, J., YIN, X., IBEKE, E., IWENDI, M.G. and BIAMBA, C. 2022. Fintech application on banking stability using big data of an emerging economy. Journal of cloud computing [online], 11, article number 43. Available from: https://doi.org/10.1186/s13677-022-00320-7

The rapid growth and development of financial technological advancement (Fintech) services and innovations have attracted the attention of scholars who are now on a quest to analyse their impact on the banking sector. This study conducts several kind... Read More about Fintech application on banking stability using big data of an emerging economy..

Tourism cloud management system: the impact of smart tourism. (2022)
Journal Article
YIN, F., YIN, X., ZHOU, J., ZHANG, X., ZHANG, R., IBEKE, E., IWENDI, M.G. and SHAH, M. 2022. Tourism cloud management system: the impact of smart tourism. Journal of cloud computing: advances, systems and applications [online], 11, article number 37. Available from: https://doi.org/10.1186/s13677-022-00316-3

This study investigates the possibility of supporting tourists in a foreign land intelligently by using the Tourism Cloud Management System (TCMS) to enhance and better their tourism experience. Some technologies allow tourists to highlight popular t... Read More about Tourism cloud management system: the impact of smart tourism..

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..