Towards autonomous developmental artificial intelligence: case study for explainable AI.

Starkey, Andrew; Ezenkwu, Chinedu Pascal

doi:10.1007/978-3-031-34107-6_8

Cost optimisation in offshore wind through procurement data analytics. (2023)
Conference Proceeding
SHITTU, Q. and EZENKWU, C.P. [2024]. Cost optimisation in offshore wind through procurement data analytics. In Proceedings of the 12th Computing conference (Computing 2024), 11-12 July 2024, London, UK. Lecture notes in networks and systems, [volume TBC]. Cham: Springer [online], (forthcoming).

Governments have implemented a variety of national and international efforts to reduce carbon emissions (so as to prevent the damaging effects of climate change on the environment and the global economy) through the execution of several policies, inc... Read More about Cost optimisation in offshore wind through procurement data analytics..

Performance and energy modelling for a low energy acoustic network for the underwater Internet of Things. (2023)
Conference Proceeding
STEWART, C., FOUGH, N., ERDOGAN, N. and PRABHU, R. 2023. Performance and energy modelling for a low energy acoustic network for the underwater Internet of Things. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea (MetroSea 2023); learning to measure sea health parameters, 4-6 October 2023, Valletta, Malta. Piscataway: IEEE [online], pages 110-115. Available from: https://doi.org/10.1109/MetroSea58055.2023.10317266

As the Internet of Things (IoT) continues to find new applications, there is academic and industrial interest in expanding these concepts to the oceanic environment where data is traditionally challenging to communicate wirelessly, establishing an Un... Read More about Performance and energy modelling for a low energy acoustic network for the underwater Internet of Things..

A green AI model selection strategy for computer-aided mpox detection. (2023)
Conference Proceeding
EZENKWU, C.P., STEPHEN, B.U.-A., AFFIAH, I. and DANIEL, B. 2023. A green AI model selection strategy for computer-aided mpox detection. In Proceedings of the 16th IEEE Africon conference (IEEE AFRICON 2023): advancing technology in Africa towards presence on the global stage, 20-22 September 2023, Nairobi, Kenya. Piscataway: IEEE [online], document number 10293707. Available from: https://doi.org/10.1109/AFRICON55910.2023.10293707

With the recent global surge in mpox (formerly monkeypox) cases, researchers have proposed deep learning technologies for early detection of the disease from skin lesion images. However, many of these researchers follow the current Red AI trend of se... Read More about A green AI model selection strategy for computer-aided mpox detection..

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..

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..

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..

Towards expert systems for improved customer services using ChatGPT as an inference engine. (2023)
Conference Proceeding
EZENKWU, C.P. 2023. Towards expert systems for improved customer services using ChatGPT as an inference engine. In Proceedings of the 2023 IEEE (Institute of electrical and Electronics Engineers) International conference on digital applications, transformation and economy (ICDATE 2023), 14-16 July 2023, Miri, Malaysia, article 10248647. Available from: https://doi.org/10.1109/ICDATE58146.2023.10248647

By harnessing both implicit and explicit customer data, companies can develop a more comprehensive understanding of their consumers, leading to better customer engagement and experience, and improved loyalty. As a result, businesses have embraced man... Read More about Towards expert systems for improved customer services using ChatGPT as an inference engine..

Towards autonomous developmental artificial intelligence: case study for explainable AI. (2023)
Conference Proceeding
STARKEY, A. and EZENKWU, C.P. 2023. Towards autonomous developmental artificial intelligence: case study for explainable AI. In Maglogiannis, I., Iliadis, L., MacIntyre, J. and Dominguez, M. (eds.) Artificial intelligence applications and innovations: proceedings of the 19th IFIP (International Federation for Information Processing) WG 12.5 Artificial intelligence applications and innovations international conference (AIAI 2023), 14-17 June 2023, León, Spain. IFIP advances in information and communication technology, 676. Cham: Springer [online], pages 94-105. Available from: https://doi.org/10.1007/978-3-031-34107-6_8

State-of-the-art autonomous AI algorithms such as reinforcement learning and deep learning techniques suffer from high computational complexity, poor explainability ability, and a limited capacity for incremental adaptive learning. In response to the... Read More about Towards autonomous developmental artificial intelligence: case study for explainable AI..

All Outputs (8)