Cyberbullying poses critical urban safety challenges, with current cloud-based detection systems creating privacy concerns and infrastructure dependencies that particularly affect under-resourced communities. This paper presents a comparative study of DistilBERT and Gemma-3-270M for mobile cyberbullying detection, addr...
Emmanuel Chibuike Edeh, P. Asuquo, Princewill Ahumaraeze et al.· E3S Web of Conferences· 0 citations
Accurate minimum miscibility pressure (MMP) estimation is essential for designing and screening miscible gas injection EOR projects, particularly CO2 and N2 flooding. Empirical correlations provide quick estimates but are often inaccurate due to limited calibration ranges, oversimplified compositions, and poor represen...
Ifiok Etim, Anietie Okon, Kilaliba Tugwell et al.· Gazi university journal of s...· 0 citations
The scarcity of weather stations in many developing countries poses a significant obstacle to obtaining precise temperature data. Akwa Ibom State in Nigeria faces this challenge leading to reliance on satellite weather data (NASA POWER) and ground-truth measurements for temperature predictions. The study helps to predi...
Joshua Ezugwu E, Williams Adaji-Agbane, P. Asuquo et al.· E3S Web of Conferences· 0 citations
This study proposes an integrated CPDP framework that combines Particle Swarm Optimization with Domain Knowledge (PSO+DK) for feature selection and Adaptive Synthetic Sampling (ADASYN) for class imbalance handling that enhanced the discriminative power of the models.
E. Obot, Victor Anaga, Sadiq Thomas et al.· E3S Web of Conferences· 0 citations
In the near term, quantum devices come with some strict limits on how big and complex the molecular systems can be when we use variational quantum algorithms. In this study, we apply the Variational Quantum Eigensolver (VQE) to ethylene (C2H4), which is a simple π-conjugated molecule. We chose it as a straightforward b...
Abasianie Samuel Etuk, Abasi-ibiangake Etuk, B. Stephen et al.· E3S Web of Conferences· 0 citations
A lightweight ensemble machine learning framework integrating Light Gradient Boosting, Histogram-based Gradient Boosting, and Categorical Boosting to detect both sensor-based and broader cyber-attack types in UAV environments is proposed, introducing an interpretable, high-performance detection framework capable of ope...
C. Chidimma, P. Asuquo, Ihemereze Chijioke Nnanna et al.· E3S Web of Conferences· 0 citations
Financial fraud detection in transaction networks is challenging due to evolving attack strategies, complex relational structures, and extreme class imbalance. We propose a hybrid deep learning model that fuses Graph Convolutional Neural Networks (GCNNs) with bidirectional LSTMs enhanced by temporal attention, enabling...
Ofonime Dominic Okon, Imo Enang, B. Stephen et al.· E3S Web of Conferences· 0 citations
The development of an ensemble machine learning pipeline for predicting resistance gene functions using the Comprehensive Antibiotic Resistance Database (CARD) demonstrates superior performance while maintaining computational efficiency, making it suitable for deployment in resourceconstrained environments.
Princewill Ahumaraeze, Ofonime Dominic Okon, P. Asuquo et al.· E3S Web of Conferences· 0 citations
By combining a formalized measure of epistemic integrity – via the Epistemic Integrity Index (EII) – with this normative framework, the paper bridges philosophy, ethics, and policy, offering a new model for understanding and regulating AI’s role in the epistemic dimension of modern conflict.
Abasianie Samuel Etuk, B. Stephen, Emmanuel Udoh et al.· E3S Web of Conferences· 0 citations
A deep learning-based failure prediction model that integrates Convolutional Neural Networks and Bidirectional Long Short-Term Memory networks to identify job failures before they occur is presented, improving the performance of cloud computing applications by reducing job failures and optimising resource utilisation.
Wunukhen Shehu Awudu, P. Asuquo, B. Agbor et al.· E3S Web of Conferences· 0 citations
Experimental evaluation demonstrates up to 95% detection accuracy, a 50% reduction in response latency, and scalability to over 100,000 IoT devices without performance degradation, highlighting the suitability of SC-ARS for deployment in smart cities, industrial IoT, and decentralized critical infrastructures where tru...
S. Bassey, B. Stephen, Emediong Bassey Obot et al.· E3S Web of Conferences· 0 citations
A comprehensive evaluation of deep learning architectures for DDoS attack detection in AMI environments, focusing on Convolutional Neural Network, CNN-Long Short-Term Memory (CNN-LSTM), and CNN-Gated Recurrent Unit (CNN-GRU) hybrid approaches.
S. Bassey, P. Asuquo, Victor Anaga et al.· E3S Web of Conferences· 0 citations
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