3 citations · 6 across the 10 of their papers we have counts for
14 papers
Full Characterisation of the Polarisation Primary Beam of the GRAO 32-m Telescope
Theophilus Ansah-Narh, Nia Imara, Benedicta Woode +4
Direction-dependent instrumental polarisation is a major systematic limitation in high-fidelity single-dish radio polarimetry, yet a unified characterisation of beam leakage and th…
Unsupervised Detection of Groundwater Storage Anomalies in Ghana Using GRACE Satellite Data
George Yamoah Afrifa, Theophilus Ansah-Narh, Marcellin Atemkeng
Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater storage anomalies using GRACE-deriv…
Unsupervised Consensus-Based Anomaly Detection for Spatiotemporal Malaria Incidence in Ghana
T. Ansah-Narh, Y. Asare Afrane
A consensus anomaly detection framework was applied to monthly malaria surveillance data from Ghana (2014-2023) to identify atypical transmission patterns. Anomalies were highly st…
Digital Beam Pattern Optimisation for the GRAO 32-m Telescope: A Comparative Analysis of FIR Filter Design Methods
Theophilus Ansah-Narh, Nia Imara, Benedicta Woode +1
The scientific utility of large single-dish radio telescopes depends critically on the stability and fidelity of their beam patterns, which govern angular resolution, sensitivity,…
Hybrid Probabilistic Forecasting of Under-Five Malaria Admissions in Ghana: A Gaussian Process Regression with Holt-Winters Smoothing
T. Ansah-Narh, Y. Asare Afrane, J. Bremang Tandoh
Accurate malaria forecasting remains a major challenge in sub-Saharan Africa, where strong seasonality, reporting uncertainty, and non-stationary transmission dynamics reduce the r…
Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler
T. Ansah-Narh, Y. Asare Afrane, J. Bremang Tandoh
Reliable quantification of malaria dynamics in sub-Saharan Africa is hindered by short, noisy, and spatially heterogeneous surveillance records. In Ghana, health-facility data from…
Bayesian estimation of spectral parameters of the 6.7-GHz methanol maser G339.884-1.259 from GRAO observations
Theophilus Ansah-Narh, Stephen Sottie, Nia Imara +1
Accurate decomposition of methanol maser spectra is essential for understanding high-mass star-forming regions, especially in complex blended spectra where small differences alter…
Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
T. Ansah-Narh, G. Y. Afrifa, J. B. Tandoh +6
Groundwater in the Densu Basin is increasingly threatened by heavy metal contamination, but conventional methods fail to capture the statistical complexity and spatial heterogeneit…
Unsupervised Electrofacies Classification and Porosity Characterization in the Offshore Keta Basin Using Wireline Logs
Hamdiya Adams, Theophilus Ansah-Narh, Daniel Kwadwo Asiedu +6
This study presents an unsupervised machine learning workflow for electrofacies analysis in the offshore Keta Basin, Ghana, where core data are scarce. Six standard wireline logs f…
Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment
Isaac Tettey Adjokatse, Samuel Senyo Koranteng, George Yamoah Afrifa +6
Soil contamination by heavy metals poses a persistent environmental and public health concern in rapidly urbanising regions of Ghana, particularly at unregulated waste disposal sit…
The Ghana Radio Astronomy Observatory
Emmanuel Proven-Adzri, Nia Imara, Theophilus Ansah-Narh +7
The Ghana Radio Astronomy Observatory (GRAO) marks a pivotal advance in African radio astronomy through the successful transformation of a decommissioned 32 m satellite communicati…
Label Assisted Autoencoder for Anomaly Detection in Power Generation Plants
Marcellin Atemkeng, Victor Osanyindoro, Rockefeller Rockefeller +5
One of the critical factors that drive the economic development of a country and guarantee the sustainability of its industries is the constant availability of electricity. This is…
Predicting Fuel Consumption in Power Generation Plants using Machine Learning and Neural Networks
Gabin Maxime Nguegnang, Marcellin Atemkeng, Theophilus Ansah-Narh +2
The instability of power generation from national grids has led industries (e.g., telecommunication) to rely on plant generators to run their businesses. However, these secondary g…
Large deviations, Basic information theorem for fitness preferential attachment random networks
K. Doku-Amponsah, F. O. Mettle, T. Narh-Ansah
For fitness preferential attachment random networks, we define the empirical degree and pair measure, which counts the number of vertices of a given degree and the number of edges…