Transformerless series dip/sag compensation with a multilevel cascaded inverter by Visser, Abraham Johannes

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A comparative study of recurrent neural networks and statistical techniques for forecasting the stock prices of JSE-listed securities by Galant, Rushin

“…This is likely the result of the unforeseen impact of the covid-19 pandemic on financial markets that would not have been factored into the training sets of the machine learning algorithms. . . .…”
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A computer vision framework towards automated scene understanding & analysis by Sarah-lee de Greeff

“…Most computer vision algorithms are deep learning based approaches but differ significantly in architecture. …”
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Detecting Electrical Submersible Pump (ESP) Failures and Estimating Run Life Using Artificial Neural Networks by Sobhy, Mostafa Ahmed

“…Concurrently, the failure classification module identifies ten distinct failure types with F1 scores exceeding 0.95, utilizing a suite of complementary algorithms. The datasets were cleaned and preprocessed to address missing values, inconsistencies, and other data quality issues. …”
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Dynamics and Energy Management of Electric Vehicles by Van Schalkwyk, Daniel Jacobus

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Pharmacogenomics of warfarin: comprehensive evaluation of important warfarin genomic response factors by Ndadza, Arinao

“…Data on variants that specifically affect warfarin dose variability among Africans is lacking, with no dosing algorithms tailored specifically for Africans developed to date. …”
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A Multimodal Immune System Inspired Defense Architecture for Detecting and Deterring Digital Pathogens in Container Hosted Web Services by Khalil, Islam

“…In our work, we propose an architecture for a containerization platform that utilizes various concepts derived from the human immune system. …”
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Impact analysis of motor faults on the DC Bus in electric vehicle drivetrains by Pugin, Devon

“…Although more sophisticated algorithms can address errors within a system, they are unable to conceal the presence of errors in the DC bus fully, particularly in the case of short inter-turn faults. …”
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Novel motion capture methods for sports analysis : case studies of cycling and rugby goal kicking by Cockroft, Stephen John

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A domain specific language for facilitating automatic parallelization and placement of SDR patterns into heterogeneous computing architectures by Mohapi, Lerato Jerfree

“…Advanced task and data parallel patterns were applied in the OptiSDR dataflow MoCs, which are especially suitable for SDR computations where FPGA-based realtime data acquisition systems feed data into multi-GPUs for implementation of parallel DSP algorithms. Furthermore, the research methodology involved an evaluation process that was used to determine the OptiSDR language's expressive power, efficiency, performance, accuracy, and ease of use in SDR applications, such as radar pulse compression and radio frequency sweeping algorithms. …”
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Using machine learning to predict the risk severity of late effects o f childhood cancer survivors by Nortje, Lene

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Considerations towards the development of a forensic evidence management system

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Study of the TR Synchronization and Video Conversion Unit by Abraham, Justin Kuruvilla

“…A new SVCU architecture, utilizing high speed ADCs and digital integrators, was then tested. …”
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APIC: A method for automated pattern identification and classification by Goss, Ryan Gavin

“…While concepts such as Deep Learning have existed for many years, the computational power for realising the utility of these algorithms in real-world applications has only recently become available. …”
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Slotted time based protocol and polling strategies for low speed, narrow band applications by Ragadza, Ntakadzeni Ronald

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Blaze-DEM : a GPU based large scale 3D discrete element particle transport framework

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Hyperlink-extended pseudo relevance feedback for improved microblog retrieval by Elganainy, Tarek

“…Results also showed that utilizing hyperlinked documents attached to the top relevant tweets in query expansion improves the results over traditional PRF. …”
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Bayesian analysis of historical functional linear models with application to air pollution forecasting by Junglee, Yovna

“…The efficiency of the MCMC algorithms is increased by implementing a Cholesky decomposition to sample from high-dimensional Gaussian distributions and by taking advantage of the orthogonal properties of the functional principal components used to model the functional covariates. …”
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