Machine Learning-Based Climate Impact Analysis on Solar Power Generation: A Case Study of Kano State, Nigeria (2021-2023)
This research evaluated the impact of meteorological conditions on photovoltaic solar panel electricity generation in Kano State, Nigeria, using high-resolution data of 1,051,200 one-minute observations over a two-year timeframe to validate six supervised machine learning models for predictive accuracy: Linear Regression, Ridge Regression, Random Forest, Gradient Boosting, XGBoost, and LightGBM. A feature engineering pipeline was […]
Acoustic AI for Biodiversity: Deep Learning Applications in Insect Monitoring
The global insect biodiversity crisis demands scalable monitoring solutions. Passive Acoustic Monitoring (PAM) generates vast data through insect sounds, but analyzing this “data deluge” requires automated methods. This review outlines the deep learning (DL) pipeline for insect bioacoustics, including data acquisition, pre-processing (denoising, segmentation), and feature representation (e.g., spectrograms and adaptive frontends such as LEAF). […]
A Gender-Aware Support Vector Machine Classification Framework for Lung Cancer Diagnosis: A Bias Evaluation Study
The use of artificial intelligence in healthcare raises ethical concerns, particularly around bias toward protected characteristics such as gender, race, and ethnicity. Gender bias remains common, as unconscious beliefs held by patients, clinicians, researchers, and administrators can shape care delivery and influence health outcomes. This study examined 309 lung cancer patient records from a Kaggle […]
Neural networks as continuous solvers for the algorithmic lattice
The transition toward 2nm nodes and complex Gate-All-Around (GAA) architectures exposes the limitations of traditional mesh-based solvers, such as Finite Element Analysis (FEA), which struggle with the” curse of dimensionality” and high computational overhead. This paper introduces a paradigm shift in semiconductor modeling by re-imagining the device as a continuous, differentiable manifold rather than a […]
Deep learning architectures and imaging modalities for plant disease detection: A systematic review
Plant diseases pose a significant threat to global food security, resulting in annual yield losses of 20–40% worldwide. Early and accurate detection is essential for advancing precision agriculture and promoting sustainable crop management. This PRISMA-guided systematic review synthesizes findings from 155 peer-reviewed studies (2020-2025) examining advances in Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and […]
A comparative time series analysis and forecasting of inflation and temperature dynamics
Time series forecasting plays a central role in economics and environmental sciences, where reliable predictions can inform policy and planning decisions. This study analyzes two monthly time series with contrasting characteristics: a non-seasonal series, the Consumer Price Index (CPI) for all urban consumers in the United States, and a strongly seasonal series, the monthly average […]
Racial bias and fairness in logistic regression models for AI-Based income prediction
The use of artificial intelligence (AI) systems to aid socioeconomic decision-making is expanding; there are substantial ethical concerns because AI systems can replicate existing discrepancies among biased data and modelling procedures. This study uses logistic regression to assess model bias and fairness. An AI-based income categorisation model was built using the University of California, Irvine […]
An optimized classification of user’s feedback to support mobile app evolution using convolutional neural network
Google Play and Apple App Store allow their users to rate apps using a rating scale from one to five, along with a user’s feedback, i.e., app review. These reviews are a vital source of information, although often present in an unstructured format, making it a challenge to extract useful information from them. However, analyzing […]
An improved wireless charging parking system for electric vehicles
This is necessary in light of the growing global demand for environmentally friendly and sustainable transportation systems that are supported by efficient and convenient charging infrastructure. The rapid rise in electric vehicle (EV) adoption has exposed several limitations in the conventional fixed charging infrastructure, particularly regarding convenience, scalability, and accessibility. To address these challenges, a […]
Histopathological images classification using aggressive transfer learning
Breast cancer is among the most common and deadly diseases that attack women worldwide. Recent epidemiological statistics show that millions of women are diagnosed with the disease every year, and over half a million women die directly of the disease every year. Proper and timely diagnosis, especially the distinction between benign and malignant breast lesions […]