Computational intelligent systems : evolving dynamic Bayesian networks by Osunmakinde, Isaac Olusegun

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Automated learning rates in machine learning for dynamic mini-batch sub-sampled losses

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Efficient radio resource management in integrated terrestrial and non-terrestrial networks by Birabwa, Denise Joanitah

“…Second, since the greedy heuristic solution to the user association sub-problem does not ordinarily produce an optimal solution, the work further proposes a polynomial-time solution based on the genetic algorithm (GA). …”
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An object-oriented library for shared-memory parallel simulations by Machanick, Philip

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Clients' returning for cervical screening results : a focus group study exploring the reasons why women spontaneously return for their results at the Khayelitsha Cervical Cancer Sc... by Honikman, Simone

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Efficient access network selection and data demand prediction for 5G systems by Paul, Udita

“…Based on the traffic analysis, the ideal placement of the data centre is formulated as a facility location problem and solved using the Weiszfeld’s algorithm. Additionally, based on the traffic analysis, the optimal dimensions of the data centre in different regions are heuristically obtained. …”
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End-to-End Autonomous Quadcopter using Reinforcement Learning by Chawa, Mohamed Marwan

“…We compare state-of-the-art RL algorithms, specifically Proximal Policy Optimization (PPO), against traditional Proportional-Integral-Derivative (PID) controllers across three tasks: hovering, slow trajectory following, and fast trajectory following. …”
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Joint call admission control incorporating pricing for congestion control to enhance QoS and ensure revenue for network operators in next generation wireless networks by Kabahuma, Sarah

“…Joint Call Admission Control (JCAC) approach has been adopted to jointly allocate or handle the radio resources amongst the different RATs in an NGWN. A number of JCAC algorithms have been proposed in the literature with the objective of enabling efficient utilisation of the radio resources and ensuring that required QoS requirements are met . …”
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Project Leanness Score: A Machine Learning Approach by Said, Julia

“…Lean construction is a philosophy, backed with principles and tools, aiming at maximizing value, eliminating waste, optimizing efficiency, and seeking continuous improvement. …”
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Parametric Yield and Tolerance Optimisation of Electromagnetic Devices using Feature-based Non-Linear Partial Least Squares Polynomial Chaos Expansion Surrogates by Nfanyana, Ketshabile

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Adaptive radio resource management schemes for the downlink of the OFDMA-based wireless communication systems by Isaac, Bernard Nyakundi

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Mixed-Criticality Scheduling Using Reinforcement Learning by ElSeadawy, Omar

“…Our customized Ape-X model is capable of successfully scheduling sets of jobs of size 50 with an average accuracy of 95% in comparison to other Reinforcement learning algorithms benchmarks conducted, e.g., Augmented Random Search, Proximal Policy Optimization, and Deep Q Networks. …”
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Machine learning methods for large deviations by Cloete, Daniël Willem Hendrik

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AN EFFICIENT INTERFERENCE AVOIDANCE SCHEME FOR DEVICE-TODEVICE ENABLED FIFTH GENERATION NARROWBAND INTERNET OF THINGS NETWOKS’ by unknown

“…Second, a bisection search approach is used to find the best power control that maximizes the network sum rate, and third, the Hungarian algorithm is used to build a maximum bipartite matching strategy to choose the optimal pairing pattern between the sets of NUEs and the D2D pairs. …”
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Load balancing using cell range expansion in LTE advanced heterogeneous networks by Nyembe, Wiseman Nkosingiphile

“…Then, we use cell range expansion, and logarithmic utility functions to design a load balancing algorithm. …”
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Detecting network attacks using high-resolution time series by Lorgat, Mohamed Wasim

“…The aim of this thesis is therefore to provide an underlying theory for understanding a single class of detection algorithms, in particular, anomaly-based network intrusion detection algorithms that utilise high-resolution time series data. …”
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A review of three machine learning models using UAV derived photogrammetry for detecting and measuring tree stumps by Hubbard, Alan John

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Improving the scalability of MAC protocols in wireless mesh network by Velempini, Mthulisi

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Machine learning methods for individual acoustic recognition in a species of field cricket by Dlamini, Gciniwe

“…The task of acoustic animal identifications thus requires the utilisation of models that are well suited for training large datasets. …”
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Process-based decomposition and multicore performance : case studies from Stringology

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