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View All FeaturedCandid video instruction as a measure of students' academic achievement in mathematics ogun state
Project work has been defended ...just for publishing only and readjustment
Predictive Modeling of Emerging Contaminants (Pharmaceuticals, Microplastics) Fate in Constructed Wetlands using Hybrid AI-Mass Balance Models.
This study combines AI and mass balance models to predict the fate of emerging contaminants in constructed wetlands.
Wasserstein-Based Systemic Risk Measures on Financial Networks: Theory, Computation, and Economic Implications via Optimal Transport
This paper develops a Wasserstein-based systemic risk framework for financial networks grounded in Optimal Transport theory. Unlike classical approach...
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Artificial Intelligence-Assisted Isolation and Structure Elucidation of Bioactive Alkaloids using High-Resolution Mass Spectrometry and Molecular Networking
AI assists in isolating and elucidating the structures of bioactive alkaloids using HR-MS and molecular networking approaches.
Physics-Informed Neural Networks (PINNs) for Multi-Physics Modeling of Additively Manufactured Functionally Graded Materials
This project leverages PINNs to model heat transfer, elasticity, and material heterogeneity in additively manufactured functionally graded materials f...
Reinforcement Learning for Adaptive Control of Advanced Oxidation Processes (AOPs) in Wastewater Treatment: A Digital Twin Approach.
This project uses reinforcement learning and digital twin technology to optimize AOPs in wastewater treatment.
Multi-Objective Evolutionary Algorithms for Dynamic Resource Allocation in Cloud Computing Environments: A Comparative Study with Deep Reinforcement Learning
This study applies multi-objective evolutionary algorithms to dynamic cloud resource allocation and compares performance against deep reinforcement le...
Machine Learning Enhanced Passive Sampling Devices for High Resolution Spatiotemporal Monitoring of Emerging Organic Contaminants in Urban Water Systems with Human Health Risk Assessment
ML-enhanced passive sampling devices for monitoring emerging organic contaminants in urban waters, integrated with human health risk assessment.
Predictive Modeling of the Pharmacokinetics and Toxicity (ADMET) of Natural Product Libraries using Transformer-Based Deep Learning Models
Transformer-based deep learning models predict ADMET properties of natural product libraries for drug discovery.
Design and Optimization of Magnetic Nanoscale Zero Valent Iron Composites Using Response Surface Methodology and Artificial Neural Networks for In Situ Remediation of Chlorinated Solvents in Contamina
Magnetic nZVI composites optimized via RSM and ANN for in situ remediation of chlorinated solvents in aquifers.
Candid video instruction as a measure of students' academic achievement in mathematics ogun state
Project work has been defended ...just for publishing only and readjustment
Single-Cell Transcriptomic Analysis Combined with Graph Neural Networks to Map Tumor Microenvironment Heterogeneity and Predict Immunotherapy Response in Colorectal Cancer
Graph neural networks analyze single-cell transcriptomics to map tumor microenvironment heterogeneity and predict patient response to immunotherapy in...
Deep Learning-Guided Discovery of Natural Product-Based Inhibitors of PD-1/PD-L1 Interaction from Medicinal Plants for Cancer Immunotherapy
This project applies deep learning to identify natural product-based inhibitors of PD-1/PD-L1 interactions from medicinal plants for cancer immunother...
Ethical Governance of Generative AI in Academic Writing: Balancing Innovation, Integrity, and Epistemic Trust
Develop frameworks for ethical governance of generative AI in academic writing while maintaining trust and integrity.
Deep Learning Driven Non Targeted Analysis of Environmental Exposomes Using High Resolution Mass Spectrometry for Characterizing the Chemical Landscape of Underserved Communities
DL-driven non-targeted analysis using HRMS to profile chemical exposomes in underserved communities.