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Recent Submissions
Development of a face mask detection and masked facial recognition model based on a hybrid convolutional neural network
(2024) Pillay, Chezlyn; Joseph, Seena; Van Niekerk, Brett
In the context of enhancing security authentication, facial recognition technology has become
pivotal, replacing conventional authentication methods such as passwords, security tokens and
PINs across various sectors. However, the rapid growth of facial recognition technology faced
hindrances due to the COVID-19 pandemic, where mandatory face mask usage obscured facial
features, challenging existing authentication methods. Regardless, the existence of several
methods for face mask detection and recognition highlighted prevalent issues such as poor lighting,
varied angles, failed detection for improper use of face masks, computational complexity,
difficulty in detecting smaller faces and low-resolution targets have led to suboptimal accuracy
rates. Hence, this study aims to address these challenges by introducing a hybrid Convolutional
Neural Network (CNN) architecture tailored for Face Mask Detection (FMD) and Masked Facial
Recognition (MFR). The models used MobileNetV2 and FaceNet InceptionResNetV1 respectively
for FMD and MFR. The proposed models leverage advanced FMD and MFR technologies,
contributing to the real-world need for enhanced security in scenarios where traditional methods
are insufficient. The models underwent training using five distinct datasets, comprising a total of
10,980 images for FMD across two datasets, and 26,523 images for MFR across three datasets. In
the FMD phase, the model achieved exceptional results, attaining a perfect 100% across evaluation
metrics such as accuracy, precision, recall, and the f1-score within a training timeframe of an hour.
Transitioning to the MFR phase, where the model required approximately one hour and 30
minutes, maintained an outcome of 99.68% across the aforementioned metrics, surpassing the
accuracy level of existing models within the meta-analysis. Furthermore, the model underwent
testing on a real-time custom dataset designed for MFR evaluation, consisting of 5500 images (i.e.,
4400 for training, 550 for validation and 550 for testing) in real-life scenarios. Robustness was
assessed under various conditions, resulting in an impressive 99.82% accuracy. The model
demonstrated high accuracy in real-time testing. Notably, both the models excel in detecting and
recognising masked participants from diverse angles and lighting conditions with minimal
computational complexity. Leveraging the pre-trained MobileNetV2 for FMD and FaceNet
InceptionResNetV1 with CNN for MFR, the CNN models provide a comprehensive solution. The
proposed models surpass existing methods, excelling in accuracy under challenging conditions.
This study contributes a versatile and efficient solution, addressing limitations in current
approaches and providing robust models for FMD and MFR in diverse sectors.
The effect of internal control systems on the monitoring of financial resources at a higher education institution
(2024) Pillay, Farisha; Nyide, Celani John
The main objective of the study was to assess the effectiveness of internal control
systems in monitoring financial resources at the Durban University of Technology. It
explored the current processes and systems of internal control used at DUT. The
study identified the challenges of implementing internal control systems and examined
the factors affecting the implementation. The study adopted a quantitative research
design where a questionnaire was used to collect data from respondents to attain the
research objectives. The study used a positivism research philosophy were a
deductive research approach and descriptive survey design was utilised. The targeted
population of the study consisted of eighty-five staff who are employed in the Finance
department at DUT. The study used non-sampling method were census sampling was
use to select a sample size of 85 respondents. Questionnaire was the main research
instrument and SPSS was utilised to analyse data. From the findings, the study
concludes that while the organization has several effective control measures in place,
there are areas of improvement needed to strengthen risk assessment procedures,
staff awareness of policies, and the adequacy of internal controls to cover all
operations. The challenges in implementing controls are acknowledged as inherent
due to human factors and the potential for collusion. The study highlights the
organization's lack of proper risk assessment procedures and recommends
developing policies, training employees, addressing control limitations, employing
technology, offering governance training, ensuring fair compensation, reducing
pressure, rotating personnel, and improving key factors affecting control systems
through communication, monitoring, values, support, oversight, structure, audit, and
policies.
Analysing factors affecting the wide adoption of ICT among learners in developing countries
(2024) Ndlovu, Khanyisani Innocent; Adeliyi, Timothy Temitope; Singh, Alveen
The evolution of Africa from a largely neglected economy to a serious contender in the global
digital and knowledge economy is hinged on enabling quality education. Education is a primer
for innovation, and entrepreneurship and builds the economy through applied skills and
knowledge, an undisputable foundation for recognition among the international community.
Technological advances in learning and teaching have regularly featured in the African
education context and huge amounts of resources are invested year after year. However, the
expected improvement is mostly unrealised. This doldrum persists because the sudden and
rapid insertion of technology is not well understood. This extends to a problem of stalled
widespread educational ICT adoption by learners, particularly in rural secondary schools.
This study appreciates advanced ICTs as a key function to support the effective improvement
and transformation of secondary school education in Africa. This study aims to identify the key
factors affecting the adoption of ICT among learners in rural secondary schools. The
distinctiveness of this study in a burgeoned discourse is a focus on unearthing adoption factors
unique to developing African countries. A lack of understanding of these factors is presented
as a knowledge gap.
A systematic literature review was conducted using the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) framework. 491 relevant publications were
identified from 2017 to 2023, with 84 studies selected for inclusion in the analysis after
applying exclusion criteria. From these studies, 38 factors influencing ICT adoption were
identified. Principal Component Analysis (PCA) was employed to reduce dimensionality and
rank the factors based on their significance. The results discovered that over-digitalization of
education, funding (support), health challenges (barriers), cognitive barriers, and time
constraints are the top five factors that significantly affect ICT adoption among learners in rural
secondary schools. These findings align with the results of the application of the Unified
Theory of Acceptance and Use of Technology (UTAUT) framework which, more significantly,
highlights additional challenges.
This study found additional challenges, such as the lack of ICT infrastructure which remains a
major obstacle. Based on the analysis, the study proposes an extension of the UTAUT
framework to better address the unique challenges faced by learners in these regions. In
conclusion, the study highlights critical areas that need to be addressed to improve the wide
adoption of ICT in education. By extending the UTAUT framework, the study provides a more
comprehensive model that could guide policymakers, educators and Government entities in
implementing effective strategies for ICT integration thus contributing to lessening the digital
divide in education between Africa and the rest of the developed world.
Exploring knowledge transfer and retention strategies for postgraduate supervisors in higher education institutions : a global perspective
(Emerald, 2025-1-1) Mpungose, Bongekile; Phaladi, Malefetjane Phineas; Chisita, Collence Takaingenhamo; Omarsaib, Mousin; Mhlongo, Patrick Mbongwa
Purpose – This study aims to systematically review extant global literature on knowledge transfer and retention in the context of postgraduate supervision in the higher education institutions (HEIs) sector.
Design/methodology/approach – To rationally explore knowledge transfer and retention in higher education, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis technique was used as a methodology.
Findings – The research findings of the study point to limited verified research in the global literature linking knowledge transfer, retention and postgraduate supervision in HEIs. Knowledge management is underdeveloped within the context of postgraduate supervision scholarship, albeit with potential serious knowledge loss risks within the HEIs sector. Moreover, knowledge transfer, retention and postgraduate supervision in HEIs are blurred. Therefore, future interdisciplinary studies are recommended to advance the scholarship of knowledge transfer and retention and postgraduate supervision in HEIs.
Research limitations/implications – Future research directions should focus on the critical role and capabilities of the supervisor, the student and other atmospherics.
Practical implications – This study proposes that 21st-century higher education systems depend heavily on the design of organisational knowledge-driven structures, transfer, retention strategies and policies within the context of postgraduate supervision.
Originality/value – This study presents global insights relating to knowledge transfer and strategies in the context of postgraduate supervision scholarship. Moreover, there is limited knowledge transfer and retention research aligned to ageing postgraduate supervisors and voluntary turnover in HEIs globally. Future interdisciplinary studies are recommended to advance the scholarship of knowledge transfer and retention and postgraduate supervision in HEIs.
Critical skills and knowledge to succeed in the township liquor retail industry
(2018-4-1) Mrasi, Andiswa P.; Mason, Robert Bruce; Jere, Albertina
The township market makes the largest contribution to liquor sales in South Africa, but growth, sustainability and success of this market is unsatisfactory. The sector needs assistance to improve their performance. This paper aims at identifying the critical skills and knowledge specific to township liquor retailing. Data was collected through qualitative semi-structured interviews; participants included representatives from provincial government, the top three liquor manufacturers and distributors, and forty liquor retail owners from Khayelitsha and Mitchell's Plain townships. The findings reveal that skills and knowledge (customised to suit township are the foundation for better management of these businesses). The critical skills and knowledge are Operating Capital, Operations Management and Human Resource. Township liquor retailers fail as a result of mistakes that could be avoided through acquiring the right skills and knowledge. The current government and supplier skills and knowledge programmes should be improved and tailored to suit the profile of these entrepreneurs.