Welcome to Boloka, the open access Institutional Repository of the North-West University (NWU-IR). This is a digital archive that collects, preserves and distributes research material created by members of the NWU.
The aim of the NWU-IR is to increase the visibility, availability and impact of the research output of the North-West University through Open Access, search engine indexing and harvesting by several initiatives.
Communities in NWU-IR
Select a community to browse its collections.
Africana Collection [366]
Conference Papers [782]
Inaugural Lectures [368]
Journals [4064]
Publications [28]
Research Output [13229]
Self-Submission [5]
Recently Added
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An investigation of the levels of financial literacy among school teachers in the Johannesburg Central District
(North-West University (South Africa), 2016)"Abstract not copied" -
Awareness and Willingness to Pay for Moringa as a Leafy Vegetable in Limpopo Province
(North-West University (South Africa), 2017)Moringa has been used to fight against malnutrition in developing countries as a result of its high nutrient content. The move to use Moringa was seen as both feasible and effective. However, it is not commonly consumed ... -
Optimising word embeddings for recognised multilingual speech
(Southern African Conference for Artificial Intelligence Research, 2020)Word embeddings are widely used in natural language processing (NLP) tasks. Most work on word embeddings focuses on monolingual languages with large available datasets. For embeddings to be useful in a multilingual ... -
Classifying recognised speech with deep neural networks
(Southern African Conference for Artificial Intelligence Research, 2020)We investigate whether word embeddings using deep neural networks can assist in the analysis of text produced by a speechrecognition system. In particular, we develop algorithms to identify which words are incorrectly ... -
Exploring neural network training dynamics through binary node activations
(South African Conference for Artificial Intelligence Research, 2020)Each node in a neural network is trained to activate for a specific region in the input domain. Any training samples that fall within this domain are therefore implicitly clustered together. Recent work has highlighted ...
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