Electrical & Electronics Engineering
Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/130
Electrical & Electronics Engineering
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Item Robust Multi-Target Tracking with a Kalman-Gain CPHD Filter: Simulation and Experimental Validation(2025-04-19) Abdullahi DaniyanWe introduce a novel cardinalized implementation of the Kalman-gain-aided particle probability hypothesis density (KG-SMC-PHD) filter, extending it to form the Kalman-Gain Particle Cardinalized Probability Hypothesis Density (KG- SMC-CPHD) filter. This new approach significantly enhances multi-target tracking by combining the particle-based state correction mechanism with the propagation of both the PHD and target cardinality distribution. Unlike conventional particle filters that require a large number of particles for acceptable performance, our method intelligently corrects selected particles during the weight update stage, resulting in a more accurate posterior with substantially fewer particles. Through comprehensive evaluations on both simulated and experimental datasets, the KG-SMC-CPHD filter demonstrates superior robustness and accuracy, particularly in high-clutter environments and nonlinear target dynamics. Notably, it offers improved cardinality estimation and maintains the computational efficiency and performance advantages of its predecessor, the KG-SMC-PHD filter, making it a powerful tool for advanced multi-target tracking applications.Item Bayesian data driven modelling of kinetochore dynamics: space-time organisation of the human metaphase plate(PLOS Biology, 2025-01-23) Constandina Koki; Alessio V Inchingolo; Abdullahi Daniyan; Enyu Li; Andrew D. McAinsh; Nigel J BurroughsMitosis is a complex self-organising process that achieves high fidelity separation of duplicated chromosomes into two daughter cells through capture and alignment of chromosomes to the spindle mid-plane. Chromosome movements are driven by kinetochores, multi-protein machines that attach chromosomes to microtubules (MTs), both controlling and generating directional forces. Using lattice light sheet microscopy imaging and automated near-complete tracking of kinetochores at fine spatio-temporal resolution, we produce a detailed atlas of kinetochore metaphase-anaphase dynamics in untransformed human cells (RPE1). We fitted 18 biophysical models of kinetochore metaphase-anaphase dynamics to experimental data using Bayesian inference, and determined support for the models with model selection methods, demonstrating substantial sister force asymmetry and time dependence of the mechanical parameters. Our analysis shows that K-fiber pulling and pushing strengths are inversely correlated and that there is substantial spatial organisation of KT dynamic properties both within, and transverse to the metaphase plate. Further, K-fiber forces are tuned over the last 5 mins of metaphase towards a set point, which we refer to as the anaphase ready state.Item Probability hypothesis density filter for parameter estimation of multiple hazardous sources(Elsevier, 2024-08-30) Abdullahi Daniyan; Cunjia Liu; Wen-Hua ChenThis study introduces an advanced methodology for estimating the source term of multiple, variable-number biochemical hazard releases, where the exact count of sources is not predetermined. Focusing on environments monitored via a network of sensors, we tackle this challenge through a multi-source Bayesian filtering paradigm, employing the theory of random finite sets (RFS). Our novel approach leverages a modified particle filter-based probability hypothesis density (PHD) filter within the RFS framework, enabling simultaneous estimation of critical source characteristics (such as location, emission rate, and effective release height) and the quantification of source numbers. This method not only accurately estimates pertinent source parameters but is also adept at identifying the emergence of new sources and the cessation of existing ones within the monitored area. The efficacy of our approach is validated through extensive simulations, which mimic a range of scenarios with varying and unknown source counts, highlighting the proposed method’s robustness and precision.