A framework to guide cybersecurity governance efforts in non-profit organisations
- Authors: le Roux, Wickus
- Date: 2019
- Subjects: Computer security , Information technology Nonprofit organizations -- security measures
- Language: English
- Type: Thesis , Masters , MPhil
- Identifier: http://hdl.handle.net/10948/44918 , vital:38188
- Description: The average non-profit organisation is faced with the same cybersecurity challenges as an international multi-corporation that generates income. However, it may lack the competencies or resources to fully utilise, implement, monitor, or evaluate cybersecurity governance to a satisfactory or acceptable level. A literature review revealed limited publicly accessible documents to guide NPOs in particular in the task of cybersecurity governance. Therefore, the problem addressed by this research is the lack of a framework to guide cybersecurity governance efforts in non-profit organisations. This real-world problem was approached using the design science paradigm. It was important to identify, firstly, factors unique to the general context of non-profit organisations, including the constraints and limitations faced by non-profit organisations. Secondly, the key cyber risks for non-profit organisations and how they can materialise through the use of emails, social media, and BYODs in the NPO context, were identified. As a third step, available cybersecurity governance guidelines were analysed to determine best practices. This investigation also revealed the people, process, and technology elements as the pillars of information security. This resulted in the development of a framework (the PotLer framework) to guide cybersecurity governance efforts in non-profit organisations based on the input of the three points mentioned above. The framework was constructed around four conceptual elements, namely information security governance; people, process, and technology; governance elements; and key risks. The PotLer framework expands the high-level generic constructs beyond the conceptual space and provides implementation guidance in the form of a questionnaire to be completed by NPOs. The questionnaire was developed as an interactive spreadsheet that requires “Yes” or “No” responses from participants and generates a recommendation based on these answers. To evaluate the PotLer framework, the aforementioned questionnaire was completed by four NPOs. An additional questionnaire obtained their input on the utility and comprehensiveness of the framework.
- Full Text:
- Date Issued: 2019
- Authors: le Roux, Wickus
- Date: 2019
- Subjects: Computer security , Information technology Nonprofit organizations -- security measures
- Language: English
- Type: Thesis , Masters , MPhil
- Identifier: http://hdl.handle.net/10948/44918 , vital:38188
- Description: The average non-profit organisation is faced with the same cybersecurity challenges as an international multi-corporation that generates income. However, it may lack the competencies or resources to fully utilise, implement, monitor, or evaluate cybersecurity governance to a satisfactory or acceptable level. A literature review revealed limited publicly accessible documents to guide NPOs in particular in the task of cybersecurity governance. Therefore, the problem addressed by this research is the lack of a framework to guide cybersecurity governance efforts in non-profit organisations. This real-world problem was approached using the design science paradigm. It was important to identify, firstly, factors unique to the general context of non-profit organisations, including the constraints and limitations faced by non-profit organisations. Secondly, the key cyber risks for non-profit organisations and how they can materialise through the use of emails, social media, and BYODs in the NPO context, were identified. As a third step, available cybersecurity governance guidelines were analysed to determine best practices. This investigation also revealed the people, process, and technology elements as the pillars of information security. This resulted in the development of a framework (the PotLer framework) to guide cybersecurity governance efforts in non-profit organisations based on the input of the three points mentioned above. The framework was constructed around four conceptual elements, namely information security governance; people, process, and technology; governance elements; and key risks. The PotLer framework expands the high-level generic constructs beyond the conceptual space and provides implementation guidance in the form of a questionnaire to be completed by NPOs. The questionnaire was developed as an interactive spreadsheet that requires “Yes” or “No” responses from participants and generates a recommendation based on these answers. To evaluate the PotLer framework, the aforementioned questionnaire was completed by four NPOs. An additional questionnaire obtained their input on the utility and comprehensiveness of the framework.
- Full Text:
- Date Issued: 2019
A framework to implement information security awareness, education and training within the Limpopo economic development agency group
- Authors: Mokobane, Ntsewa Benjamin
- Date: 2019
- Subjects: Computer security , Computer networks -- Security measures Data protection
- Language: English
- Type: Thesis , Masters , MPhil
- Identifier: http://hdl.handle.net/10948/42063 , vital:36622
- Description: Cybersecurity awareness, education and training of employees is key in reducing and preventing cyber-attack opportunities. The ignorance and/or lack of understanding of employees about the information security risks around them might expose the LEDA Group to cyber-attacks. This led to the problem that the level of awareness of employees regarding information security was not known. The implication of this not knowing was that an argument for the nature of an intervention to ensure awareness, as well as to educate and train employees regarding information security was not possible. The aim of this treatise was to develop a framework as an effective guideline for the implementation of cybersecurity awareness, education and training of employees. In the study, the LEDA Group employees were surveyed to determine their cybersecurity knowledge gap. An online questionnaire was randomly sent to 314 LEDA Group employees. The survey was voluntary and confidential. One hundred and thirty seven (137) employees completed the survey. The results of the survey were analysed to determine the gap between the current cybersecurity knowledge of the LEDA Group employees and state-of-the-art cybersecurity knowledge. The gap was used in the development of the framework for the implementation of the cybersecurity awareness, education and training (F-CSAET). Central to F-CSAET is the governance principles guided by best practices such as King IV, COBIT5, ISO27001, ISO27005, ISO27008 and ISO27032 and the compliance requirements to POPIA, the Copyright Act and the Cybercrimes and Cybersecurity Bill. The F-CSAET has six steps, namely Assess, Analyse, Create, Plan, Implement and Reinforce. The framework was evaluated for applicability by the team called the cyber security interest team, which was established specifically for the purpose of the F-CSAET.
- Full Text:
- Date Issued: 2019
- Authors: Mokobane, Ntsewa Benjamin
- Date: 2019
- Subjects: Computer security , Computer networks -- Security measures Data protection
- Language: English
- Type: Thesis , Masters , MPhil
- Identifier: http://hdl.handle.net/10948/42063 , vital:36622
- Description: Cybersecurity awareness, education and training of employees is key in reducing and preventing cyber-attack opportunities. The ignorance and/or lack of understanding of employees about the information security risks around them might expose the LEDA Group to cyber-attacks. This led to the problem that the level of awareness of employees regarding information security was not known. The implication of this not knowing was that an argument for the nature of an intervention to ensure awareness, as well as to educate and train employees regarding information security was not possible. The aim of this treatise was to develop a framework as an effective guideline for the implementation of cybersecurity awareness, education and training of employees. In the study, the LEDA Group employees were surveyed to determine their cybersecurity knowledge gap. An online questionnaire was randomly sent to 314 LEDA Group employees. The survey was voluntary and confidential. One hundred and thirty seven (137) employees completed the survey. The results of the survey were analysed to determine the gap between the current cybersecurity knowledge of the LEDA Group employees and state-of-the-art cybersecurity knowledge. The gap was used in the development of the framework for the implementation of the cybersecurity awareness, education and training (F-CSAET). Central to F-CSAET is the governance principles guided by best practices such as King IV, COBIT5, ISO27001, ISO27005, ISO27008 and ISO27032 and the compliance requirements to POPIA, the Copyright Act and the Cybercrimes and Cybersecurity Bill. The F-CSAET has six steps, namely Assess, Analyse, Create, Plan, Implement and Reinforce. The framework was evaluated for applicability by the team called the cyber security interest team, which was established specifically for the purpose of the F-CSAET.
- Full Text:
- Date Issued: 2019
A framework to measure human behaviour whilst reading
- Salehzadeh, Seyed Amirsaleh, Greyling, Jean
- Authors: Salehzadeh, Seyed Amirsaleh , Greyling, Jean
- Date: 2019
- Subjects: Computational intelligence , Machine learning Artificial intelligence Neural networks (Computer science)
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/43578 , vital:36921
- Description: The brain is the most complex object in the known universe that gives a sense of being to humans and characterises human behaviour. Building models of brain functions is perhaps the most fascinating scientific challenge in the 21st century. Reading is a significant cognitive process in the human brain that plays a critical role in the vital process of learning and in performing some daily activities. The study of human behaviour during reading has been an area of interest for researchers in different fields of science. This thesis is based upon providing a novel framework, called ARSAT (Assisting Researchers in the Selection of Appropriate Technologies), that measures the behaviour of humans when reading text. The ARSAT framework aims at assisting researchers in the selection and application of appropriate technologies to measure the behaviour of a person who is reading text. The ARSAT framework will assist to researchers who investigate the reading process and find it difficult to select appropriate theories, metrics, data collection methods and data analytics techniques. The ARSAT framework enhances the ability of its users to select appropriate metrics indicating the effective factors on the characterisation of different aspects of human behaviour during the reading process. As will be shown in this research study, human behaviour is characterised by a complicated interplay of action, cognition and emotion. The ARSAT framework also facilitates selecting appropriate sensory technologies that can be used to monitor and collect data for the metrics. Moreover, this research study will introduce BehaveNet, a novel Deep Learning modelling approach, which can be used for training Deep Learning models of human behaviour from the sensory data collected. In this thesis, a comprehensive literature study is presented that was conducted to acquire adequate knowledge for designing the ARSAT framework. In order to identify the contributing factors that affect the reading process, an overview of some existing theories of the reading process is provided. Furthermore, a number of sensory technologies and techniques that can be applied to monitoring the changes in the metrics indicating the factors are also demonstrated. Only, the technologies that are commercially available on the market are recommended by the ARSAT framework. A variety of Machine Learning techniques were also investigated when designing the BehaveNet. The BehaveNet takes advantage of the complementarity of Convolutional Neural Networks, Long Short-Term Memory networks and Deep Neural Networks. The design of a Human Behaviour Monitoring System (HBMS), by utilising the ARSAT framework for recognising three attention-seeking activities of humans, is also presented in this research study. Reading printed text, as well as speaking out loudly and watching a programme on TV were proposed as activities that a person unintentionally may shift his/her attention from reading into distractions. Between sensory devices recommended by the ARSAT framework, the Muse headband which is an Electroencephalography (EEG) and head motion-sensing wearable device, was selected to track the forehead EEG and a person’s head movements. The EEG and 3-axes accelerometer data were recorded from eight participants when they read printed text, as well as the time they performed two other activities. An imbalanced dataset consisting over 1.2 million rows of noisy data was created and used to build a model of the activities (60% training and 20% validating data) and evaluating the model (20% of the data). The efficiency of the framework is demonstrated by comparing the performance of the models built by utilising the BehaveNet, with the models built by utilising a number of competing Deep Learning models for raw EEG and accelerometer data, that have attained state-of-the-art performance. The classification results are evaluated by some metrics including the classification accuracy, F1 score, confusion matrix, Receiver Operating Characteristic curve, and Area under Curve (AUC) score. By considering the results, the BehaveNet contributed to the body of knowledge as an approach for measuring human behaviour by using sensory devices. In comparison with the performance of the other models, the models built by utilising the BehaveNet, attained better performance when classifying data of two EEG channels (Accuracy = 95%; AUC=0.99; F1 = 0.95), data of a single EEG channel (Accuracy = 85%; AUC=0.96; F1 = 0.83), accelerometer data (Accuracy = 81%; AUC = 0.9; F1 = 0.76) and all of the data in the dataset (Accuracy = 97%; AUC = 0.99; F1 = 0.96). The dataset and the source code of this project are also published on the Internet to help the science community. The Muse headband is also shown to be an economical and standard wearable device that can be successfully used in behavioural research.
- Full Text:
- Date Issued: 2019
- Authors: Salehzadeh, Seyed Amirsaleh , Greyling, Jean
- Date: 2019
- Subjects: Computational intelligence , Machine learning Artificial intelligence Neural networks (Computer science)
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/43578 , vital:36921
- Description: The brain is the most complex object in the known universe that gives a sense of being to humans and characterises human behaviour. Building models of brain functions is perhaps the most fascinating scientific challenge in the 21st century. Reading is a significant cognitive process in the human brain that plays a critical role in the vital process of learning and in performing some daily activities. The study of human behaviour during reading has been an area of interest for researchers in different fields of science. This thesis is based upon providing a novel framework, called ARSAT (Assisting Researchers in the Selection of Appropriate Technologies), that measures the behaviour of humans when reading text. The ARSAT framework aims at assisting researchers in the selection and application of appropriate technologies to measure the behaviour of a person who is reading text. The ARSAT framework will assist to researchers who investigate the reading process and find it difficult to select appropriate theories, metrics, data collection methods and data analytics techniques. The ARSAT framework enhances the ability of its users to select appropriate metrics indicating the effective factors on the characterisation of different aspects of human behaviour during the reading process. As will be shown in this research study, human behaviour is characterised by a complicated interplay of action, cognition and emotion. The ARSAT framework also facilitates selecting appropriate sensory technologies that can be used to monitor and collect data for the metrics. Moreover, this research study will introduce BehaveNet, a novel Deep Learning modelling approach, which can be used for training Deep Learning models of human behaviour from the sensory data collected. In this thesis, a comprehensive literature study is presented that was conducted to acquire adequate knowledge for designing the ARSAT framework. In order to identify the contributing factors that affect the reading process, an overview of some existing theories of the reading process is provided. Furthermore, a number of sensory technologies and techniques that can be applied to monitoring the changes in the metrics indicating the factors are also demonstrated. Only, the technologies that are commercially available on the market are recommended by the ARSAT framework. A variety of Machine Learning techniques were also investigated when designing the BehaveNet. The BehaveNet takes advantage of the complementarity of Convolutional Neural Networks, Long Short-Term Memory networks and Deep Neural Networks. The design of a Human Behaviour Monitoring System (HBMS), by utilising the ARSAT framework for recognising three attention-seeking activities of humans, is also presented in this research study. Reading printed text, as well as speaking out loudly and watching a programme on TV were proposed as activities that a person unintentionally may shift his/her attention from reading into distractions. Between sensory devices recommended by the ARSAT framework, the Muse headband which is an Electroencephalography (EEG) and head motion-sensing wearable device, was selected to track the forehead EEG and a person’s head movements. The EEG and 3-axes accelerometer data were recorded from eight participants when they read printed text, as well as the time they performed two other activities. An imbalanced dataset consisting over 1.2 million rows of noisy data was created and used to build a model of the activities (60% training and 20% validating data) and evaluating the model (20% of the data). The efficiency of the framework is demonstrated by comparing the performance of the models built by utilising the BehaveNet, with the models built by utilising a number of competing Deep Learning models for raw EEG and accelerometer data, that have attained state-of-the-art performance. The classification results are evaluated by some metrics including the classification accuracy, F1 score, confusion matrix, Receiver Operating Characteristic curve, and Area under Curve (AUC) score. By considering the results, the BehaveNet contributed to the body of knowledge as an approach for measuring human behaviour by using sensory devices. In comparison with the performance of the other models, the models built by utilising the BehaveNet, attained better performance when classifying data of two EEG channels (Accuracy = 95%; AUC=0.99; F1 = 0.95), data of a single EEG channel (Accuracy = 85%; AUC=0.96; F1 = 0.83), accelerometer data (Accuracy = 81%; AUC = 0.9; F1 = 0.76) and all of the data in the dataset (Accuracy = 97%; AUC = 0.99; F1 = 0.96). The dataset and the source code of this project are also published on the Internet to help the science community. The Muse headband is also shown to be an economical and standard wearable device that can be successfully used in behavioural research.
- Full Text:
- Date Issued: 2019
A gatherer's paradise? Early humans and plant foraging on the cape south coast, South Africa
- Authors: Gummow, William Thomas
- Date: 2019
- Subjects: Soil amendments , Plants -- Nutrition Plant physiology
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/39687 , vital:35348
- Description: South Africa is a semi-arid country that is experiencing population growth and the associated pressure of producing sufficient crops to sustain the population. Furthermore, poor land management has also led to increased degradation of valuable arable land. To improve poor soil quality and possibly avoid or reverse degradation and ultimately desertification, it was suggested that soil amendments are a potential solution to some of these problems. Although soil amendment is a relatively well-known practice to improve soil quality, the use of rubber crumb as a soil amendment is not well studied. Rubber crumb is produced from end-of-life tyres that have been ground up to fine particles and as such can be used as a secondary resource to replace the use of virgin materials. Rubber crumb has been used in an array of industries, however, the present study investigated the possibility that rubber crumb might be used as a soil amendment to alleviate various forms of soil degradation, specifically soil compaction and crusting, and potentially improve crop establishment and growth.To determine this, a soil that is prone to crusting and compaction was amended with rubber crumb at rates of 5%, 15% and 25%. Various soil physical characteristics, such as bulk density, particle density, porosity, field capacity and penetration resistance were investigated and it was determined that as the percentage rubber crumb increases in the soil, so do the beneficial characteristics of the soil. Furthermore, the rubber crumb was also treated in various ways in order to determine how the treatments might affect the chemical properties of the soil, as well as the amount of zinc that is leached from the rubber crumb. It was found that washing the rubber with a weak acid or even water prior to adding it to the soil resulted in more desirable chemical condition compared to untreated rubber crumb. Lastly, maize (Zea mays L.) was used to determine whether amending soil with pre-treated rubber crumb in different percentages had an influence on the germination success and growth rate of maize. In terms of germination success, amending soil with rubber crumb does not seem to have a significant influence, however, growth rate decreased as the percentage rubber crumb increased, while treating the rubber with a weak acid or water prior to adding it to soil had the most positive effect on plant growth. It can therefore be concluded that rubber crumb amendment rates between 5% and 15% resulted in the most desirable soil physical properties and plant growth amongst the amendments. However the best plant growth was still seen in the control soil, to which no rubber crumb had been added.
- Full Text:
- Date Issued: 2019
- Authors: Gummow, William Thomas
- Date: 2019
- Subjects: Soil amendments , Plants -- Nutrition Plant physiology
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/39687 , vital:35348
- Description: South Africa is a semi-arid country that is experiencing population growth and the associated pressure of producing sufficient crops to sustain the population. Furthermore, poor land management has also led to increased degradation of valuable arable land. To improve poor soil quality and possibly avoid or reverse degradation and ultimately desertification, it was suggested that soil amendments are a potential solution to some of these problems. Although soil amendment is a relatively well-known practice to improve soil quality, the use of rubber crumb as a soil amendment is not well studied. Rubber crumb is produced from end-of-life tyres that have been ground up to fine particles and as such can be used as a secondary resource to replace the use of virgin materials. Rubber crumb has been used in an array of industries, however, the present study investigated the possibility that rubber crumb might be used as a soil amendment to alleviate various forms of soil degradation, specifically soil compaction and crusting, and potentially improve crop establishment and growth.To determine this, a soil that is prone to crusting and compaction was amended with rubber crumb at rates of 5%, 15% and 25%. Various soil physical characteristics, such as bulk density, particle density, porosity, field capacity and penetration resistance were investigated and it was determined that as the percentage rubber crumb increases in the soil, so do the beneficial characteristics of the soil. Furthermore, the rubber crumb was also treated in various ways in order to determine how the treatments might affect the chemical properties of the soil, as well as the amount of zinc that is leached from the rubber crumb. It was found that washing the rubber with a weak acid or even water prior to adding it to the soil resulted in more desirable chemical condition compared to untreated rubber crumb. Lastly, maize (Zea mays L.) was used to determine whether amending soil with pre-treated rubber crumb in different percentages had an influence on the germination success and growth rate of maize. In terms of germination success, amending soil with rubber crumb does not seem to have a significant influence, however, growth rate decreased as the percentage rubber crumb increased, while treating the rubber with a weak acid or water prior to adding it to soil had the most positive effect on plant growth. It can therefore be concluded that rubber crumb amendment rates between 5% and 15% resulted in the most desirable soil physical properties and plant growth amongst the amendments. However the best plant growth was still seen in the control soil, to which no rubber crumb had been added.
- Full Text:
- Date Issued: 2019
A gatherer’s paradise? early humans and plant foraging on the Cape south coast, South Africa
- Authors: Botha, Maria Susan
- Date: 2019
- Subjects: Plant remains (Archaeology) -- South Africa , Plant physiology Plant ecology Botany -- South Africa
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/37139 , vital:34124
- Description: Humans were driven to refugia during the cold and dry glacial Marine Isotope Stage 6 (MIS6) (~195–125 ka); only a few places, including the Cape south coast, show archaeological evidence of continuous human occupation. It has been hypothesised that the Cape south coast provided the requisite shelter to ensure human’s earliest survival because it provided all the right ingredients. The shores offer abundant shellfish, the land a diverse array of plants, and the climate was ameliorated due to the proximity of the then exposed Palaeo-Agulhas Plain to the warm Agulhas current. The aim of this study is to determine whether the indigenous flora of this region could have provided a sufficient edible resource for early humans. Residents of the Cape south coast have genetic ancestry linking them to the Khoe-San, the original inhabitants of the area, and still have an extensive knowledge of the local edible plants. With their help, I set out to determine a) whether humans have been utilising the same plant species over time, b) what the foraging potential of the edible plants in the region is and c) how resilient these plants are to human foraging. If we know whether the plant species known and used today were the same as those that were utilised by past humans, we can then use the contemporary knowledge to make predictions about past utilisation. To answer this question, I collated two databases: archaeological (all plant species found in archaeological sites [dating 0 to 80,000 BP]) and contemporary (all plant species in the modern-day ethnographic literature [last 400 years]) that occur within the Greater Cape Floristic Region(GCFR). I found a significant number of plant species shared between the two databases, which suggests that at least some plant species have been used by humans over a long period of time. To determine the indigenous plant foraging potential of the region, I foraged for food in the Cape south coast (451 bouts) monthly over a two-year period with the help of local inhabitants. The findings show that edible plant resources are distributed patchily and focusing on specific vegetation types would greatly enhance chances of harvesting 2,000 kcal per day, which is considered the daily calorific requirements for a typical hunter-gatherer. I then sought to understand how resilient these plants [(with an emphasis on plants with an underground storage organ (USO)] would be to human foraging. To do this, I set out plots and harvested all edible foods for three consecutive years with the help of foragers. Results indicate that there was a significant reduction in edible weight only in the third year of consecutive harvesting. In conclusion, using various approaches, this study investigates the plant food potential of the Cape south coast from the perspective of early human consumers. The findings suggest that knowledge regarding useful plants dates back to at least 80,000 BP. Food resources are patchily distributed across the main vegetation types found within the Cape south coast and occur in hotspots, i.e. concentrated areas hosting high densities of edible plant foods, surrounded by areas with very low plant food densities. Foragers could have harvested their daily calorific quota more easily if they focused their harvesting efforts in specific vegetation types found in the Cape south coast. Furthermore, many USOs circumvent climatic fluctuations, herbivory or both by staggering their emergence over multiple years, which implies they have some resilience to human foraging.
- Full Text:
- Date Issued: 2019
- Authors: Botha, Maria Susan
- Date: 2019
- Subjects: Plant remains (Archaeology) -- South Africa , Plant physiology Plant ecology Botany -- South Africa
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10948/37139 , vital:34124
- Description: Humans were driven to refugia during the cold and dry glacial Marine Isotope Stage 6 (MIS6) (~195–125 ka); only a few places, including the Cape south coast, show archaeological evidence of continuous human occupation. It has been hypothesised that the Cape south coast provided the requisite shelter to ensure human’s earliest survival because it provided all the right ingredients. The shores offer abundant shellfish, the land a diverse array of plants, and the climate was ameliorated due to the proximity of the then exposed Palaeo-Agulhas Plain to the warm Agulhas current. The aim of this study is to determine whether the indigenous flora of this region could have provided a sufficient edible resource for early humans. Residents of the Cape south coast have genetic ancestry linking them to the Khoe-San, the original inhabitants of the area, and still have an extensive knowledge of the local edible plants. With their help, I set out to determine a) whether humans have been utilising the same plant species over time, b) what the foraging potential of the edible plants in the region is and c) how resilient these plants are to human foraging. If we know whether the plant species known and used today were the same as those that were utilised by past humans, we can then use the contemporary knowledge to make predictions about past utilisation. To answer this question, I collated two databases: archaeological (all plant species found in archaeological sites [dating 0 to 80,000 BP]) and contemporary (all plant species in the modern-day ethnographic literature [last 400 years]) that occur within the Greater Cape Floristic Region(GCFR). I found a significant number of plant species shared between the two databases, which suggests that at least some plant species have been used by humans over a long period of time. To determine the indigenous plant foraging potential of the region, I foraged for food in the Cape south coast (451 bouts) monthly over a two-year period with the help of local inhabitants. The findings show that edible plant resources are distributed patchily and focusing on specific vegetation types would greatly enhance chances of harvesting 2,000 kcal per day, which is considered the daily calorific requirements for a typical hunter-gatherer. I then sought to understand how resilient these plants [(with an emphasis on plants with an underground storage organ (USO)] would be to human foraging. To do this, I set out plots and harvested all edible foods for three consecutive years with the help of foragers. Results indicate that there was a significant reduction in edible weight only in the third year of consecutive harvesting. In conclusion, using various approaches, this study investigates the plant food potential of the Cape south coast from the perspective of early human consumers. The findings suggest that knowledge regarding useful plants dates back to at least 80,000 BP. Food resources are patchily distributed across the main vegetation types found within the Cape south coast and occur in hotspots, i.e. concentrated areas hosting high densities of edible plant foods, surrounded by areas with very low plant food densities. Foragers could have harvested their daily calorific quota more easily if they focused their harvesting efforts in specific vegetation types found in the Cape south coast. Furthermore, many USOs circumvent climatic fluctuations, herbivory or both by staggering their emergence over multiple years, which implies they have some resilience to human foraging.
- Full Text:
- Date Issued: 2019
A historical sociolinguistic study on the conceptualisation and application of justice and law kwisizwe samaXhosa as documented in and extracted From SEK Mqhayi And W.W. Gqoba’s selected writings
- Authors: Ntshingana, Sanele
- Date: 2019
- Subjects: Gqoba, William Wellington , Mqhayi, S. E. K. , Xhosa literature -- History and criticism , Law in literature , Justice in literature
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/115339 , vital:34115
- Description: This study seeks to investigate the original meanings contained in lexical terms relating to law (umthetho) and justice (ubulungisa) and their application in the precolonial Xhosa social society as they make appearance in SEK Mqhayi’s novel Ityala lamawele (1914) and WW Gqoba’s Isizwe esinembali, (1873-188/2015). Both of these works were written and initially published at the early point of contact of amaXhosa with the art of writing, and so are set in a ‘traditional’ setting (in the case of Mqhayi) and at early contact with European societies in Eastern Nguni region. This academic endeavour is undertaken by employing critical discourse theoretical framework. The purpose is to investigate the conceptualisation of law and justice amongst amaXhosa, and the extent to which this conceptualisation reflects the philosophical worldview of amaXhosa, as embedded in their language. The paper makes inferences about conceptualisation of law and justice in precolonial Xhosa social settings, and offers proposals on what this conceptual understanding could mean if its potential contribution to the contemporary understanding and application of law and justice in South Africa could be tapped into. The motivation for this study emanates from the current intellectual contestations in higher education that today’s curricula present western knowledge systems as universal while marginalising indigenous epistemologies in teaching, learning and research practices. At the centre of these debates is how research, social and scientific thinking in humanities, is profoundly shaped by imported, racist, western “canonical” texts and theories. The arguments presented by various scholars argue that this enterprise firmly roots the collective imagination of students about the past and present in racist Eurocentric schematic frames, thus creating a problem of identity loss, and an intentional distortion of historical truths. The space for knowledge systems and experiences reflecting African memory and imagination is not only neglected, but distorted too. In this context, the study seeks to delve deeper into how African languages can be used to reconstruct knowledge systems that reflect African ways of understanding society as part of creating a curriculum that depicts “multiversal” ways of knowing (Tisani 2000; Santos, 2014). This study makes several findings, chief amongst which is that the legal and justice systems of the precolonial Xhosa society was both corrective as opposed to today’s punitive court system that South Africa inherited, largely from the West. It seeks to prove that AmaXhosa’s precolonial legal and justice system was focused more on reintegrating the offender back into society. The study further will show how the precolonial amaXhosa justice system was embedded in the concepts of ubulungisa (correct and re-intergrate) and isohlwayo (that which brings one to basics). Through discourse analysis of the early literary isiXhosa texts, the thesis discovers that the application of ubulungisa amongst amaXhosa back then was consistent with the philosophies embedded in the concepts. By exposing the collaboration networks between the white missionaries and the colonial administrators of the nineteenth century, the thesis will show how conspiracies were directed at erasing and displacing these indigenous epistemologies and to replacing them with colonial memories. To this end, missionary accounts, explorer diary entries and reports and early lexicographic material were produced and archived. Furthermore, this study makes a proposition that early written Xhosa texts be entrenched in the today’s curricula in order inform the process of making sense of the social experiences and knowledge systems of the indigenous people of South Africa, from the precolonial-past to the present. Throughout the study, the thesis presents a proposition these early Xhosa texts be studied in relation to their intellectual contributions. This, it is hoped, will boldly challenge the canonised knowledge and racist assumptions about the African knowledge systems and experiences.
- Full Text:
- Date Issued: 2019
- Authors: Ntshingana, Sanele
- Date: 2019
- Subjects: Gqoba, William Wellington , Mqhayi, S. E. K. , Xhosa literature -- History and criticism , Law in literature , Justice in literature
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/115339 , vital:34115
- Description: This study seeks to investigate the original meanings contained in lexical terms relating to law (umthetho) and justice (ubulungisa) and their application in the precolonial Xhosa social society as they make appearance in SEK Mqhayi’s novel Ityala lamawele (1914) and WW Gqoba’s Isizwe esinembali, (1873-188/2015). Both of these works were written and initially published at the early point of contact of amaXhosa with the art of writing, and so are set in a ‘traditional’ setting (in the case of Mqhayi) and at early contact with European societies in Eastern Nguni region. This academic endeavour is undertaken by employing critical discourse theoretical framework. The purpose is to investigate the conceptualisation of law and justice amongst amaXhosa, and the extent to which this conceptualisation reflects the philosophical worldview of amaXhosa, as embedded in their language. The paper makes inferences about conceptualisation of law and justice in precolonial Xhosa social settings, and offers proposals on what this conceptual understanding could mean if its potential contribution to the contemporary understanding and application of law and justice in South Africa could be tapped into. The motivation for this study emanates from the current intellectual contestations in higher education that today’s curricula present western knowledge systems as universal while marginalising indigenous epistemologies in teaching, learning and research practices. At the centre of these debates is how research, social and scientific thinking in humanities, is profoundly shaped by imported, racist, western “canonical” texts and theories. The arguments presented by various scholars argue that this enterprise firmly roots the collective imagination of students about the past and present in racist Eurocentric schematic frames, thus creating a problem of identity loss, and an intentional distortion of historical truths. The space for knowledge systems and experiences reflecting African memory and imagination is not only neglected, but distorted too. In this context, the study seeks to delve deeper into how African languages can be used to reconstruct knowledge systems that reflect African ways of understanding society as part of creating a curriculum that depicts “multiversal” ways of knowing (Tisani 2000; Santos, 2014). This study makes several findings, chief amongst which is that the legal and justice systems of the precolonial Xhosa society was both corrective as opposed to today’s punitive court system that South Africa inherited, largely from the West. It seeks to prove that AmaXhosa’s precolonial legal and justice system was focused more on reintegrating the offender back into society. The study further will show how the precolonial amaXhosa justice system was embedded in the concepts of ubulungisa (correct and re-intergrate) and isohlwayo (that which brings one to basics). Through discourse analysis of the early literary isiXhosa texts, the thesis discovers that the application of ubulungisa amongst amaXhosa back then was consistent with the philosophies embedded in the concepts. By exposing the collaboration networks between the white missionaries and the colonial administrators of the nineteenth century, the thesis will show how conspiracies were directed at erasing and displacing these indigenous epistemologies and to replacing them with colonial memories. To this end, missionary accounts, explorer diary entries and reports and early lexicographic material were produced and archived. Furthermore, this study makes a proposition that early written Xhosa texts be entrenched in the today’s curricula in order inform the process of making sense of the social experiences and knowledge systems of the indigenous people of South Africa, from the precolonial-past to the present. Throughout the study, the thesis presents a proposition these early Xhosa texts be studied in relation to their intellectual contributions. This, it is hoped, will boldly challenge the canonised knowledge and racist assumptions about the African knowledge systems and experiences.
- Full Text:
- Date Issued: 2019
A hydrogeological investigation of Grahamstown, assessing both the dynamics and quality of the local groundwater system
- Authors: Smetherham, Kyle Norman
- Date: 2019
- Subjects: Hydrogeology -- South Africa -- Makhanda , Water quality -- South Africa -- Makhanda , Groundwater -- Quality -- South Africa -- Makhanda
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/94444 , vital:31045
- Description: In many parts of South Africa, complete allocation of surface water reservoirs together with current drought conditions has led to serious water shortages and subsequent awareness regarding the importance to save water. Grahamstown is no different, with water problems relating to low supply and high demand being compounded by insufficient treatment capacity and aging infrastructure. Groundwater is an alternative water resource that could potentially act as a supplementary and/or emergency supply to the town, reducing the reliability on surface reservoirs. Groundwater however, is a hidden resource and requires an understanding of various aquifer properties and continuous monitoring and modelling so not to permanently disrupt the natural system but rather achieve sustainable management. Grahamstown is situated towards the northern extent of the Cape Fold Belt (CFB) system, within a synclinal fold structure. The local geology forms two local aquifer systems beneath Grahamstown that directly influence both the dynamics and quality of the groundwater. These underground reservoirs are the Witpoort and Dwyka aquifers and can be described as a semi-confined, fractured, quartzitic sandstone aquifer and an unconfined, fractured, tillite aquifer, respectively. Separating these aquifer systems is a shale aquitard, although due to the fractured nature of the rocks in the region there is most likely some groundwater interaction between them. Evaluation of geological formations together with the monitoring of 31 local boreholes presented a valuable conceptualisation of the local system and allowed for the application of methods to estimate recharge. Recharge estimation is one of the most crucial factors when managing aquifer systems as it can be used to determine what proportion of rainfall contributes to the subsurface reservoir and therefore, the sustainable amount that can be extracted. Various methods have been developed to estimate recharge, however due to the uncertainty surrounding groundwater systems, especially fractured aquifers, it was important to apply multiple methods to validate results. The water-table fluctuation (WTF) and cumulative rainfall departure (CRD) are two methods that were used in the present study to determine recharge. These methods rely on water-table changes in boreholes and specifically how they respond to rainfall events. Along with the WTF and CRD methods, a modelling approach was also used to estimate recharge which focused on the dynamics of a natural groundwater outlet, termed the Fairview Spring. This natural spring system is located just outside the main town of Grahamstown, within the Witpoort aquifer system, and is an important water resource to many residents due to poor supply and quality of municipal water. Monitoring the discharge of this spring allowed for the development of a model which attempts to recreate the discharge conditions observed. Along with groundwater recharge, other processes added to the model include evapotranspiration, storage, interflow spring outflow and groundwater outflow. Several different model simulation scenarios provided valuable insight into the greater groundwater dynamics. In terms of groundwater quality, nine borehole samples and one spring sample were analysed for major ions (Ca, Na, K, Cl, Mg, SO4, HCO3), metals (Cu, Fe, Mn) as well as pH and electrical conductivity. Overall electrical conductivity levels and major ion concentrations were lower in the Witpoort aquifer indicating a better groundwater quality compared to that of the Dwyka aquifer. Of the three metals included in the analysis, Mn proved to be the most significant and the highest concentrations were produced for samples that intersected the shale aquitard unit, suggesting that Mn-containing groundwater is drawn from this geological layer. Development of a supplementary and/or emergency groundwater supply requires careful consideration of the geology, quantity, quality, and recharge in the study site. All these aspects were assessed as well as deliberation into the potential infrastructural costs involved. Through conceptualisation of the system; evidence gathered during basic monitoring; and a simple spring model, the current study aimed to explore certain management strategies and recommend potential options going forward. The hidden nature of the resource together with the heterogeneity of fracture networks creates an inevitable uncertainty surrounding the system. Proper development and management of the aquifer can only be achieved if the system is continually monitored, modelled and utilised sustainably.
- Full Text:
- Date Issued: 2019
- Authors: Smetherham, Kyle Norman
- Date: 2019
- Subjects: Hydrogeology -- South Africa -- Makhanda , Water quality -- South Africa -- Makhanda , Groundwater -- Quality -- South Africa -- Makhanda
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/94444 , vital:31045
- Description: In many parts of South Africa, complete allocation of surface water reservoirs together with current drought conditions has led to serious water shortages and subsequent awareness regarding the importance to save water. Grahamstown is no different, with water problems relating to low supply and high demand being compounded by insufficient treatment capacity and aging infrastructure. Groundwater is an alternative water resource that could potentially act as a supplementary and/or emergency supply to the town, reducing the reliability on surface reservoirs. Groundwater however, is a hidden resource and requires an understanding of various aquifer properties and continuous monitoring and modelling so not to permanently disrupt the natural system but rather achieve sustainable management. Grahamstown is situated towards the northern extent of the Cape Fold Belt (CFB) system, within a synclinal fold structure. The local geology forms two local aquifer systems beneath Grahamstown that directly influence both the dynamics and quality of the groundwater. These underground reservoirs are the Witpoort and Dwyka aquifers and can be described as a semi-confined, fractured, quartzitic sandstone aquifer and an unconfined, fractured, tillite aquifer, respectively. Separating these aquifer systems is a shale aquitard, although due to the fractured nature of the rocks in the region there is most likely some groundwater interaction between them. Evaluation of geological formations together with the monitoring of 31 local boreholes presented a valuable conceptualisation of the local system and allowed for the application of methods to estimate recharge. Recharge estimation is one of the most crucial factors when managing aquifer systems as it can be used to determine what proportion of rainfall contributes to the subsurface reservoir and therefore, the sustainable amount that can be extracted. Various methods have been developed to estimate recharge, however due to the uncertainty surrounding groundwater systems, especially fractured aquifers, it was important to apply multiple methods to validate results. The water-table fluctuation (WTF) and cumulative rainfall departure (CRD) are two methods that were used in the present study to determine recharge. These methods rely on water-table changes in boreholes and specifically how they respond to rainfall events. Along with the WTF and CRD methods, a modelling approach was also used to estimate recharge which focused on the dynamics of a natural groundwater outlet, termed the Fairview Spring. This natural spring system is located just outside the main town of Grahamstown, within the Witpoort aquifer system, and is an important water resource to many residents due to poor supply and quality of municipal water. Monitoring the discharge of this spring allowed for the development of a model which attempts to recreate the discharge conditions observed. Along with groundwater recharge, other processes added to the model include evapotranspiration, storage, interflow spring outflow and groundwater outflow. Several different model simulation scenarios provided valuable insight into the greater groundwater dynamics. In terms of groundwater quality, nine borehole samples and one spring sample were analysed for major ions (Ca, Na, K, Cl, Mg, SO4, HCO3), metals (Cu, Fe, Mn) as well as pH and electrical conductivity. Overall electrical conductivity levels and major ion concentrations were lower in the Witpoort aquifer indicating a better groundwater quality compared to that of the Dwyka aquifer. Of the three metals included in the analysis, Mn proved to be the most significant and the highest concentrations were produced for samples that intersected the shale aquitard unit, suggesting that Mn-containing groundwater is drawn from this geological layer. Development of a supplementary and/or emergency groundwater supply requires careful consideration of the geology, quantity, quality, and recharge in the study site. All these aspects were assessed as well as deliberation into the potential infrastructural costs involved. Through conceptualisation of the system; evidence gathered during basic monitoring; and a simple spring model, the current study aimed to explore certain management strategies and recommend potential options going forward. The hidden nature of the resource together with the heterogeneity of fracture networks creates an inevitable uncertainty surrounding the system. Proper development and management of the aquifer can only be achieved if the system is continually monitored, modelled and utilised sustainably.
- Full Text:
- Date Issued: 2019
A leadership development model to enhance ethical governance in South Africa
- Authors: Els, Ryno Juan
- Date: 2019
- Subjects: Leadership -- South Africa , Public administration -- Moral and ethical aspects Corporate governance Business ethics -- South Africa Africa Professional ethics Organizational behavior -- Moral and ethical aspects
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/39863 , vital:35489
- Description: From the United States of America’s White House to the Vatican in Vatican City, from Harare, Zimbabwe to the Union buildings in South Africa, to large organisations like Volkswagen, BP and KPMG, leadership failures are prolific. Globalised and local leadership failures and scandals are plagued by narcissistic, toxic, corrupt and dishonest behaviour by heads of state, CEOs and clergy. The effect of executive leadership failures is that they set the tone for a corrupt culture that spirals negatively down to grass-roots level. Unethical leadership in organisations manifests in various ways including misconduct, deception and cheating. Apart from regular exposés of leadership scandals globally, there has been a notable increase in ethical leadership derailments caused by unethical behaviour. The question is why leaders, who are considered to understand value-based morality, engage in unethical behaviour when confronted with the opportunity. In recent, empirical research in behavioural ethics and moral psychology, it was found that morally sound leaders often indulge in unethical behaviour. Unethical leadership behaviour includes misdemeanours in tax returns, overstating performance, inflating business expense accounts, involvement in corruption, counter-productive work behaviour, being morally disengaged and being untruthful during negotiations. Recent research indicates that unethical leadership leads to an increase in poor governance and propels vicious cycles that have a negative impact on human development, economic growth and the environment. This research study includes traditional and contemporary leadership theories that have been evaluated as well as an in-depth discussion of the necessity and importance of ethical governance. An innovative, ethical leadership development model has been designed and aligned with servant, ethical, authentic and integrated leadership styles where spiritual, cultural and emotional intelligences play a significant role in leadership maturity. A fresh perspective on the King IV Report (2016) as an international benchmark together with other authoritative literature and case studies of unethical governance have been discussed to shed light on the latest leadership theories and ethics in the 21st century. The findings of this study have been tested statistically by means of structural equation modelling (SEM). The findings confirmed empirically that accountability, stakeholders’ interests and the regulatory environment need to be implemented by ethical leaders in order to enhance ethical governance. The lack of a practical, outcome-based, leadership development model provided an opportunity to develop an ethical leadership development model that would have a positive impact on ethical governance, thereby contributing to the body of knowledge.
- Full Text:
- Date Issued: 2019
- Authors: Els, Ryno Juan
- Date: 2019
- Subjects: Leadership -- South Africa , Public administration -- Moral and ethical aspects Corporate governance Business ethics -- South Africa Africa Professional ethics Organizational behavior -- Moral and ethical aspects
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/39863 , vital:35489
- Description: From the United States of America’s White House to the Vatican in Vatican City, from Harare, Zimbabwe to the Union buildings in South Africa, to large organisations like Volkswagen, BP and KPMG, leadership failures are prolific. Globalised and local leadership failures and scandals are plagued by narcissistic, toxic, corrupt and dishonest behaviour by heads of state, CEOs and clergy. The effect of executive leadership failures is that they set the tone for a corrupt culture that spirals negatively down to grass-roots level. Unethical leadership in organisations manifests in various ways including misconduct, deception and cheating. Apart from regular exposés of leadership scandals globally, there has been a notable increase in ethical leadership derailments caused by unethical behaviour. The question is why leaders, who are considered to understand value-based morality, engage in unethical behaviour when confronted with the opportunity. In recent, empirical research in behavioural ethics and moral psychology, it was found that morally sound leaders often indulge in unethical behaviour. Unethical leadership behaviour includes misdemeanours in tax returns, overstating performance, inflating business expense accounts, involvement in corruption, counter-productive work behaviour, being morally disengaged and being untruthful during negotiations. Recent research indicates that unethical leadership leads to an increase in poor governance and propels vicious cycles that have a negative impact on human development, economic growth and the environment. This research study includes traditional and contemporary leadership theories that have been evaluated as well as an in-depth discussion of the necessity and importance of ethical governance. An innovative, ethical leadership development model has been designed and aligned with servant, ethical, authentic and integrated leadership styles where spiritual, cultural and emotional intelligences play a significant role in leadership maturity. A fresh perspective on the King IV Report (2016) as an international benchmark together with other authoritative literature and case studies of unethical governance have been discussed to shed light on the latest leadership theories and ethics in the 21st century. The findings of this study have been tested statistically by means of structural equation modelling (SEM). The findings confirmed empirically that accountability, stakeholders’ interests and the regulatory environment need to be implemented by ethical leaders in order to enhance ethical governance. The lack of a practical, outcome-based, leadership development model provided an opportunity to develop an ethical leadership development model that would have a positive impact on ethical governance, thereby contributing to the body of knowledge.
- Full Text:
- Date Issued: 2019
A local portrait of South African counselling psychologists’ endorsement of the values and scope of practice of their profession in relation to their career satisfaction
- Authors: Ngobeni, Nhlori
- Date: 2019
- Subjects: Counseling psychology -- South Africa , Counseling psychologists -- South Africa , Psychology -- South Africa , Psychologists -- South Africa
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/94350 , vital:31038
- Description: The 2011 revision to the scope of practice of counselling psychology in South Africa has renewed debates about what is it that should distinguish counselling psychology as a distinctive area of practice and research in South Africa. This study reports the findings of a survey of a sample of 228 South African registered counselling psychologists, including the extent to which they endorse the traditional values of their category, the extent to which they endorse the current scope of practice for counselling psychology, and measures of career satisfaction. Findings are that women and white practitioners comprise the large majority of the category. Counselling psychologists strongly endorse most of the traditional values of the category and are generally highly satisfied with their careers. Surprisingly, given these findings, only a large minority indicate that they would choose counselling psychology again knowing what they know now. Most significant, the findings of a multiple regression analysis indicate that endorsement of the scope of practice most strongly predicts career satisfaction scores, followed closely by black racial identification, years of experience, and then endorsement of counselling psychology values. Logistic regression analysis to predict which counselling psychologists would choose counselling psychology again knowing what they know now, revealed that only endorsement of counselling psychology values and endorsement of the scope practice made a significant contribution to predictions. This study provides a snapshot of the current status of South African counselling psychology today and it remains that in the next ten years, there will be significant changes as the category changes across the globe.
- Full Text:
- Date Issued: 2019
- Authors: Ngobeni, Nhlori
- Date: 2019
- Subjects: Counseling psychology -- South Africa , Counseling psychologists -- South Africa , Psychology -- South Africa , Psychologists -- South Africa
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/94350 , vital:31038
- Description: The 2011 revision to the scope of practice of counselling psychology in South Africa has renewed debates about what is it that should distinguish counselling psychology as a distinctive area of practice and research in South Africa. This study reports the findings of a survey of a sample of 228 South African registered counselling psychologists, including the extent to which they endorse the traditional values of their category, the extent to which they endorse the current scope of practice for counselling psychology, and measures of career satisfaction. Findings are that women and white practitioners comprise the large majority of the category. Counselling psychologists strongly endorse most of the traditional values of the category and are generally highly satisfied with their careers. Surprisingly, given these findings, only a large minority indicate that they would choose counselling psychology again knowing what they know now. Most significant, the findings of a multiple regression analysis indicate that endorsement of the scope of practice most strongly predicts career satisfaction scores, followed closely by black racial identification, years of experience, and then endorsement of counselling psychology values. Logistic regression analysis to predict which counselling psychologists would choose counselling psychology again knowing what they know now, revealed that only endorsement of counselling psychology values and endorsement of the scope practice made a significant contribution to predictions. This study provides a snapshot of the current status of South African counselling psychology today and it remains that in the next ten years, there will be significant changes as the category changes across the globe.
- Full Text:
- Date Issued: 2019
A maintenance strategy assessment that supports quality electricity generation and availability
- Authors: Hendricks, Hubert
- Date: 2019
- Subjects: Electric power distribution -- South Africa , Electric power production -- South Africa Electric power consumption -- South Africa Electric power -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/40305 , vital:36133
- Description: This paper seeks to contribute to the solutions of some of the challenges faced within Eskom Generation with regards to sustainably supplying electricity to South Africa and the neighbouring countries – the approach used in this paper is to improve quality within the maintenance sphere, considering quality workmanship and high quality standard equipment normally increases reliability and availability – With an increased reliability and availability, there is a strong likelihood that Eskom equipment will be able to produce electricity sustainably. Furthermore, the research found that there are a number of aspects to incorporate into the business in order to have a well-rounded quality system within the business. The Maintenance department would need to have a strategy that is founded on the type of assets and life of the assets, the department needs to have a computerised maintenance management system that integrates with other relevant departments such as Finance who needs to guarantee correct budgets for the respective maintenance plans, Stores who will have to ensure correct stock levels to carry out maintenance works, and Procurement who will need to know which services and goods to prioritise among purchase requisitions and purchase orders. HR also plays an important role, as per the research, when it comes to training and development that can improve the abilities of the employees to provide a speedier and accurate service when he/she is more competent; Maintenance management along with engineers then have the crucial role of marrying these aspects to provide the maintenance philosophy for the business that is most suited to the equipment in the plant. If any of these aspects are missing, it becomes a bit challenging to have a complete quality result. Some of the tools that the research considered are TQM and TPM with a strong focus on WM pillar. WM provides for equipment to be part of a Preventative Maintenance schedule to ensure all equipment is properly cared for, and to ensure history and trends are captured for future planning. Even though this research was limited to assess Tutuka EMD strategy, the above principles are applicable and helpful for maintenance departments on a global scale, and not only limited to power industries.
- Full Text:
- Date Issued: 2019
- Authors: Hendricks, Hubert
- Date: 2019
- Subjects: Electric power distribution -- South Africa , Electric power production -- South Africa Electric power consumption -- South Africa Electric power -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/40305 , vital:36133
- Description: This paper seeks to contribute to the solutions of some of the challenges faced within Eskom Generation with regards to sustainably supplying electricity to South Africa and the neighbouring countries – the approach used in this paper is to improve quality within the maintenance sphere, considering quality workmanship and high quality standard equipment normally increases reliability and availability – With an increased reliability and availability, there is a strong likelihood that Eskom equipment will be able to produce electricity sustainably. Furthermore, the research found that there are a number of aspects to incorporate into the business in order to have a well-rounded quality system within the business. The Maintenance department would need to have a strategy that is founded on the type of assets and life of the assets, the department needs to have a computerised maintenance management system that integrates with other relevant departments such as Finance who needs to guarantee correct budgets for the respective maintenance plans, Stores who will have to ensure correct stock levels to carry out maintenance works, and Procurement who will need to know which services and goods to prioritise among purchase requisitions and purchase orders. HR also plays an important role, as per the research, when it comes to training and development that can improve the abilities of the employees to provide a speedier and accurate service when he/she is more competent; Maintenance management along with engineers then have the crucial role of marrying these aspects to provide the maintenance philosophy for the business that is most suited to the equipment in the plant. If any of these aspects are missing, it becomes a bit challenging to have a complete quality result. Some of the tools that the research considered are TQM and TPM with a strong focus on WM pillar. WM provides for equipment to be part of a Preventative Maintenance schedule to ensure all equipment is properly cared for, and to ensure history and trends are captured for future planning. Even though this research was limited to assess Tutuka EMD strategy, the above principles are applicable and helpful for maintenance departments on a global scale, and not only limited to power industries.
- Full Text:
- Date Issued: 2019
A Model for Crime Management in Smart Cities
- Authors: Westraadt, Lindsay
- Date: 2019
- Subjects: Smart cities , Computer networks -- security measures
- Language: English
- Type: Thesis , Doctoral , PHD
- Identifier: http://hdl.handle.net/10948/45635 , vital:38922
- Description: The main research problem addressed in this study is that South African cities are not effectively integrating and utilising available, and rapidly emerging smart city data sources for planning and management. To this end, it was proposed that a predictive model, that assimilates data from traditionally isolated management silos, could be developed for prediction and simulation at the system-of-systems level. As proof of concept, the study focused on only one aspect of smart cities, namely crime management. Subsequently, the main objective of this study was to develop and evaluate a predictive model for crime management in smart cities that effectively integrated data from traditionally isolated management silos. The Design Science Research process was followed to develop and evaluate a prototype model. The practical contributions of this study was the development of a prototype model for integrated decision-making in smart cities, and the associated guidelines for the implementation of the developed modelling approach within the South African IDP context. Theoretically, this work contributed towards the development of a modelling paradigm for effective integrated decision-making in smart cities. This work also contributed towards developing strategic-level predictive policing tools aimed at proactively meeting community needs, and contributed to the body of knowledge regarding complex systems modelling.
- Full Text:
- Date Issued: 2019
- Authors: Westraadt, Lindsay
- Date: 2019
- Subjects: Smart cities , Computer networks -- security measures
- Language: English
- Type: Thesis , Doctoral , PHD
- Identifier: http://hdl.handle.net/10948/45635 , vital:38922
- Description: The main research problem addressed in this study is that South African cities are not effectively integrating and utilising available, and rapidly emerging smart city data sources for planning and management. To this end, it was proposed that a predictive model, that assimilates data from traditionally isolated management silos, could be developed for prediction and simulation at the system-of-systems level. As proof of concept, the study focused on only one aspect of smart cities, namely crime management. Subsequently, the main objective of this study was to develop and evaluate a predictive model for crime management in smart cities that effectively integrated data from traditionally isolated management silos. The Design Science Research process was followed to develop and evaluate a prototype model. The practical contributions of this study was the development of a prototype model for integrated decision-making in smart cities, and the associated guidelines for the implementation of the developed modelling approach within the South African IDP context. Theoretically, this work contributed towards the development of a modelling paradigm for effective integrated decision-making in smart cities. This work also contributed towards developing strategic-level predictive policing tools aimed at proactively meeting community needs, and contributed to the body of knowledge regarding complex systems modelling.
- Full Text:
- Date Issued: 2019
A Model for Intrusion Detection in IoT using Machine Learning
- Authors: Nkala, Junior Ruddy
- Date: 2019
- Subjects: Internet of things
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17180 , vital:40863
- Description: The Internet of Things is an open and comprehensive global network of intelligent objects that have the capacity to auto-organize, share information, data and resources. There are currently over a billion devices connected to the Internet, and this number increases by the day. While these devices make our life easier, safer and healthier, they are expanding the number of attack targets vulnerable to cyber-attacks from potential hackers and malicious software. Therefore, protecting these devices from adversaries and unauthorized access and modification is very important. The purpose of this study is to develop a secure lightweight intrusion and anomaly detection model for IoT to help detect threats in the environment. We propose the use of data mining and machine learning algorithms as a classification technique for detecting abnormal or malicious traffic transmitted between devices due to potential attacks such as DoS, Man-In-Middle and Flooding attacks at the application level. This study makes use of two robust machine learning algorithms, namely the C4.5 Decision Trees and K-means clustering to develop an anomaly detection model. MATLAB Math Simulator was used for implementation. The study conducts a series of experiments in detecting abnormal data and normal data in a dataset that contains gas concentration readings from a number of sensors deployed in an Italian city over a year. Thereafter we examined the classification performance in terms of accuracy of our proposed anomaly detection model. Results drawn from the experiments conducted indicate that the size of the training sample improves classification ability of the proposed model. Our findings noted that the choice of discretization algorithm does matter in the quest for optimal classification performance. The proposed model proved accurate in detecting anomalies in IoT, and classifying between normal and abnormal data. The proposed model has a classification accuracy of 96.51% which proved to be higher compared to other algorithms such as the Naïve Bayes. The model proved to be lightweight and efficient in-terms of being faster at training and testing as compared to Artificial Neural Networks. The conclusions drawn from this research are a perspective from a novice machine learning researcher with valuable recommendations that ensure optimal classification of normal and abnormal IoT data.
- Full Text:
- Date Issued: 2019
- Authors: Nkala, Junior Ruddy
- Date: 2019
- Subjects: Internet of things
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17180 , vital:40863
- Description: The Internet of Things is an open and comprehensive global network of intelligent objects that have the capacity to auto-organize, share information, data and resources. There are currently over a billion devices connected to the Internet, and this number increases by the day. While these devices make our life easier, safer and healthier, they are expanding the number of attack targets vulnerable to cyber-attacks from potential hackers and malicious software. Therefore, protecting these devices from adversaries and unauthorized access and modification is very important. The purpose of this study is to develop a secure lightweight intrusion and anomaly detection model for IoT to help detect threats in the environment. We propose the use of data mining and machine learning algorithms as a classification technique for detecting abnormal or malicious traffic transmitted between devices due to potential attacks such as DoS, Man-In-Middle and Flooding attacks at the application level. This study makes use of two robust machine learning algorithms, namely the C4.5 Decision Trees and K-means clustering to develop an anomaly detection model. MATLAB Math Simulator was used for implementation. The study conducts a series of experiments in detecting abnormal data and normal data in a dataset that contains gas concentration readings from a number of sensors deployed in an Italian city over a year. Thereafter we examined the classification performance in terms of accuracy of our proposed anomaly detection model. Results drawn from the experiments conducted indicate that the size of the training sample improves classification ability of the proposed model. Our findings noted that the choice of discretization algorithm does matter in the quest for optimal classification performance. The proposed model proved accurate in detecting anomalies in IoT, and classifying between normal and abnormal data. The proposed model has a classification accuracy of 96.51% which proved to be higher compared to other algorithms such as the Naïve Bayes. The model proved to be lightweight and efficient in-terms of being faster at training and testing as compared to Artificial Neural Networks. The conclusions drawn from this research are a perspective from a novice machine learning researcher with valuable recommendations that ensure optimal classification of normal and abnormal IoT data.
- Full Text:
- Date Issued: 2019
A model for retaining employees in an organisation within the aviation industry
- Authors: Makalima, Odwa Vuyolwethu
- Date: 2019
- Subjects: Employee retention , Labor turnover Job satsifaction Employee motivation
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/40800 , vital:36238
- Description: Staff turnover affects even the best of organisations. It results in positions with high employee turnover rates being left open for months on end in other cases with other employees being appointed to act in those positions. Even after appointments are made there is a time period before appointees are proficient in the company operations and procedures. Staff turnover not only affects management but the organisation as a whole. It can sometimes lead to a decrease in organisational efficiency and a drop in the performance of the remaining staff. Employee retention is amongst the issues facing organisational managers as a result of a shortage of skilled workers, economic growth and high employee turnover. Organisations can no longer afford to leave the responsibility of retaining skilled and high performing employees to the Human Resources department. Management needs to take accountability for reducing loss of talent. The aim of this study is to improve employee retention by investigating factors that affect intention to resign in an aviation organisation. The study specifically examined how independent variables such as trust in management, organisational values, growth and advancement opportunities, effective communication, and work-life balance will influence the intent to resign of employees in an aviation organisation. An empirical study, consisting of a mail survey was conducted amongst 151 employees of an organisation in the aviation industry based across all nine provinces. The purpose was to investigate the determinants of intent to resign among employees in the aviation industry. The key findings indicate that growth and advancement opportunities and work-life balance are key variables for reducing intent to resign and thereby improving retention in aviation organisations. Trust in management, organisational values and effective communication were found to not have a significant relationship with employees’ intent to resign. Recommendations were made to management to ensure that they pay specific attention to growth and advancement opportunities as well as work-life balance in order to improve the retention of their employees.
- Full Text:
- Date Issued: 2019
- Authors: Makalima, Odwa Vuyolwethu
- Date: 2019
- Subjects: Employee retention , Labor turnover Job satsifaction Employee motivation
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/40800 , vital:36238
- Description: Staff turnover affects even the best of organisations. It results in positions with high employee turnover rates being left open for months on end in other cases with other employees being appointed to act in those positions. Even after appointments are made there is a time period before appointees are proficient in the company operations and procedures. Staff turnover not only affects management but the organisation as a whole. It can sometimes lead to a decrease in organisational efficiency and a drop in the performance of the remaining staff. Employee retention is amongst the issues facing organisational managers as a result of a shortage of skilled workers, economic growth and high employee turnover. Organisations can no longer afford to leave the responsibility of retaining skilled and high performing employees to the Human Resources department. Management needs to take accountability for reducing loss of talent. The aim of this study is to improve employee retention by investigating factors that affect intention to resign in an aviation organisation. The study specifically examined how independent variables such as trust in management, organisational values, growth and advancement opportunities, effective communication, and work-life balance will influence the intent to resign of employees in an aviation organisation. An empirical study, consisting of a mail survey was conducted amongst 151 employees of an organisation in the aviation industry based across all nine provinces. The purpose was to investigate the determinants of intent to resign among employees in the aviation industry. The key findings indicate that growth and advancement opportunities and work-life balance are key variables for reducing intent to resign and thereby improving retention in aviation organisations. Trust in management, organisational values and effective communication were found to not have a significant relationship with employees’ intent to resign. Recommendations were made to management to ensure that they pay specific attention to growth and advancement opportunities as well as work-life balance in order to improve the retention of their employees.
- Full Text:
- Date Issued: 2019
A model for secure and usable passphrases for multilingual users
- Authors: Maoneke, Pardon Blessings
- Date: 2019
- Subjects: Computers -- Access control -- Passwords Computer security
- Language: English
- Type: Thesis , Doctoral , PhD (Information Systems)
- Identifier: http://hdl.handle.net/10353/12571 , vital:39289
- Description: Research on more than 100 million passwords that have been leaked to the public domain has uncovered various security limitations associated with user-generated short passwords. Long passwords (passphrases) are considered an alternative solution that could provide a balance between security and usability. However, the literature shows a lack of consistency in the security and usability contributions of passphrases. For example, studies that investigated passphrase security focusing on structural dependencies at character level found passphrases to be secure. Inversely, other research findings suggest that passphrase security could be compromised by the use of predictable grammatical rules, popular words in a natural language and keyboard patterns. This is further exacerbated by research on passphrases that is focused on the Global North. This is a huge concern given that results from inter-cultural studies suggest that local languages do influence password structure and to some extent, password usability and security. To address these gaps in the literature, this study used socio-technical theory which emphasised both the social and technical aspects of the phenomenon under study. Psychological studies show that the memory has limited capacity, something that threatens password usability; hence, the need to utilise information that is already known during password generation. Socio-cultural theory suggests that the information that is already known by users is contextually informed, hence sociocultural theory was applied to understand the contextual factors that could be used to enhance passphrase security and usability. With reference to the Southern African context, this study argues that system designers should take advantage of a multilingual user group and encourage the generation of passphrases that are based on substrings from different languages. This study went on to promote the use of multilingual passphrases instead of emphasising multi-character class passwords. This study was guided by design science research. Participants were invited to take part in a short password and multilingual passphrase generation and recall experiment that was made available using a web-based application. These passwords were generated by participants under pre-specified conditions. Quantitative and qualitative data was gathered. The study findings showed the use of both African and Indo-European languages in multilingual passphrases and short passwords. English oriented passwords and substrings dominated the multilingual passphrase and short password corpora. In addition, some of the short passwords and substrings in the multilingual passphrase corpora were found among the most common passwords of 2016, 2017 and 2018. Usability tests showed that multilingual passphrases are usable, even though they were not easy to create and recall when compared to short passwords. A high rate of password reuse during short password generation by participants might have worked in favour of short passwords. Nonetheless, participants appear to reflect better usability with multilingual passphrases over time due to repeated use. Females struggled to recall short passwords and multilingual passphrases when compared to their male counterparts. Security tests using the Probabilistic Context-Free Grammar suggest that short passwords are weaker, with just more than 50% of the short passwords being guessed, while none 4 Final Submission of Thesis, Dissertation or Research Report/Project, Conference or Exam Paper of the multilingual passphrases were guessed. Further analysis showed that short passwords that were oriented towards an IndoEuropean language were more easily guessed than African language-oriented short passwords. As such, this study encourages orienting passwords towards African languages while the use of multilingual passphrases is expected to offer more security. The use of African languages and multilingual passphrases by a user group that is biased towards English-oriented passwords could enhance security by increasing the search space.
- Full Text:
- Date Issued: 2019
- Authors: Maoneke, Pardon Blessings
- Date: 2019
- Subjects: Computers -- Access control -- Passwords Computer security
- Language: English
- Type: Thesis , Doctoral , PhD (Information Systems)
- Identifier: http://hdl.handle.net/10353/12571 , vital:39289
- Description: Research on more than 100 million passwords that have been leaked to the public domain has uncovered various security limitations associated with user-generated short passwords. Long passwords (passphrases) are considered an alternative solution that could provide a balance between security and usability. However, the literature shows a lack of consistency in the security and usability contributions of passphrases. For example, studies that investigated passphrase security focusing on structural dependencies at character level found passphrases to be secure. Inversely, other research findings suggest that passphrase security could be compromised by the use of predictable grammatical rules, popular words in a natural language and keyboard patterns. This is further exacerbated by research on passphrases that is focused on the Global North. This is a huge concern given that results from inter-cultural studies suggest that local languages do influence password structure and to some extent, password usability and security. To address these gaps in the literature, this study used socio-technical theory which emphasised both the social and technical aspects of the phenomenon under study. Psychological studies show that the memory has limited capacity, something that threatens password usability; hence, the need to utilise information that is already known during password generation. Socio-cultural theory suggests that the information that is already known by users is contextually informed, hence sociocultural theory was applied to understand the contextual factors that could be used to enhance passphrase security and usability. With reference to the Southern African context, this study argues that system designers should take advantage of a multilingual user group and encourage the generation of passphrases that are based on substrings from different languages. This study went on to promote the use of multilingual passphrases instead of emphasising multi-character class passwords. This study was guided by design science research. Participants were invited to take part in a short password and multilingual passphrase generation and recall experiment that was made available using a web-based application. These passwords were generated by participants under pre-specified conditions. Quantitative and qualitative data was gathered. The study findings showed the use of both African and Indo-European languages in multilingual passphrases and short passwords. English oriented passwords and substrings dominated the multilingual passphrase and short password corpora. In addition, some of the short passwords and substrings in the multilingual passphrase corpora were found among the most common passwords of 2016, 2017 and 2018. Usability tests showed that multilingual passphrases are usable, even though they were not easy to create and recall when compared to short passwords. A high rate of password reuse during short password generation by participants might have worked in favour of short passwords. Nonetheless, participants appear to reflect better usability with multilingual passphrases over time due to repeated use. Females struggled to recall short passwords and multilingual passphrases when compared to their male counterparts. Security tests using the Probabilistic Context-Free Grammar suggest that short passwords are weaker, with just more than 50% of the short passwords being guessed, while none 4 Final Submission of Thesis, Dissertation or Research Report/Project, Conference or Exam Paper of the multilingual passphrases were guessed. Further analysis showed that short passwords that were oriented towards an IndoEuropean language were more easily guessed than African language-oriented short passwords. As such, this study encourages orienting passwords towards African languages while the use of multilingual passphrases is expected to offer more security. The use of African languages and multilingual passphrases by a user group that is biased towards English-oriented passwords could enhance security by increasing the search space.
- Full Text:
- Date Issued: 2019
A model for smart factories in the pharmaceutical manufacturing sector
- Authors: Mugwagwa, Basil
- Date: 2019
- Subjects: Internet of things , Manufacturing processes -- Automation Drug factories Pharmaceutical technology
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/41897 , vital:36607
- Description: Since the turn of the century, the manufacturing industry has metamorphosed from manually driven systems to digitalisation. Product life cycles have shortened and customer demands have become more intense. Globalisation has brought about challenges that drive the need for smart manufacturing. Industry 4.0 has emerged as a response to these demands. The integration of various processes, facilities and systems throughout the value chain and digitalisation of physical systems is promoted in Industry 4.0. Due to increased competitive pressures, organisations are strategically looking at automation to deliver competitive advantage in delivering products at the right cost, quality, time and volumes to the customers. Organisations are therefore looking for manufacturing solutions that are technology driven, such as cyber-physical systems, big data, collaborative robots and the Internet of Things. This allows autonomous communication throughout the value chain between machine-to-machine and human-to-machine. The smart factory, a component of Industry 4.0, is a self-organised, modular, highly flexible and reconfigurable factory that enables the production of customised products at low cost, therefore maximising profitability. Smart manufacturing can bring about competitive advantages for an organisation. Labour concerns have been raised against automation and smart manufacturing, citing potential job losses, workforce redundancy and potential employee lay-offs. This unease, in turn, influences the employees’ attitude towards technology, which could lead either to its acceptance or refusal. The purpose of this research is to enhance the understanding of smart factories in the pharmaceutical industry by conducting a systematic analysis of the factors which influence the attitude of those involved towards a smart factory implementation. This study focuses on the perceptions among employees and management. The research is a quantitative study consisting of a literature review of the key concepts related to Industry 4.0, smart factories and technology-acceptance theories. The empirical study consisted of surveys completed by management and employees of one of the pharmaceutical manufacturers in South Africa. The questionnaire used in this research consists of questions regarding demographic data and questions regarding the perception of change and factors influencing attitudes towards the acceptance of technology, within the pharmaceutical manufacturing company. Descriptive statistics were used to summarise the data into a more condensed form, which could simplify the identification of patterns in the data. Inferential statistics were used to validate if the conclusions made from the sample data could be inferred to a larger population. Various factors influence perceptions about ease of use and usefulness, which then, in turn, influence attitudes and the intention to use technology. These factors have been examined by numerous authors in the technology acceptance literature. Recommended factors based on the statistical analysis of the questionnaire results were identified. A model, supported by Exploratory Factor Analysis, Correlations and ANOVA Testing identified the following factors as having an influence on the Attitude towards the Positive Impact of Smart Factories, within the pharmaceutical manufacturing company: Training and Development, Individual Characteristics, Trust, Organisational Culture, Resources and Costs and Job Security. The importance of each factor was identified to understand its function how to improve the implementation of smart factories. The research results indicated that the perception of management and employees is different on factors like such as Training, Individual Characteristics, Trust, Resources and Costs, Automation and Support and Parent Company in relation to technology acceptance. There was however no difference in perception between managers and employees on Security, Government Laws and Regulations, Organisational Culture, Peer Support and Organisational Support in relation to technology acceptance. The research study contributed to the identification and understanding of the factors influencing the implementation of smart factories in the pharmaceutical industry.
- Full Text:
- Date Issued: 2019
- Authors: Mugwagwa, Basil
- Date: 2019
- Subjects: Internet of things , Manufacturing processes -- Automation Drug factories Pharmaceutical technology
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/41897 , vital:36607
- Description: Since the turn of the century, the manufacturing industry has metamorphosed from manually driven systems to digitalisation. Product life cycles have shortened and customer demands have become more intense. Globalisation has brought about challenges that drive the need for smart manufacturing. Industry 4.0 has emerged as a response to these demands. The integration of various processes, facilities and systems throughout the value chain and digitalisation of physical systems is promoted in Industry 4.0. Due to increased competitive pressures, organisations are strategically looking at automation to deliver competitive advantage in delivering products at the right cost, quality, time and volumes to the customers. Organisations are therefore looking for manufacturing solutions that are technology driven, such as cyber-physical systems, big data, collaborative robots and the Internet of Things. This allows autonomous communication throughout the value chain between machine-to-machine and human-to-machine. The smart factory, a component of Industry 4.0, is a self-organised, modular, highly flexible and reconfigurable factory that enables the production of customised products at low cost, therefore maximising profitability. Smart manufacturing can bring about competitive advantages for an organisation. Labour concerns have been raised against automation and smart manufacturing, citing potential job losses, workforce redundancy and potential employee lay-offs. This unease, in turn, influences the employees’ attitude towards technology, which could lead either to its acceptance or refusal. The purpose of this research is to enhance the understanding of smart factories in the pharmaceutical industry by conducting a systematic analysis of the factors which influence the attitude of those involved towards a smart factory implementation. This study focuses on the perceptions among employees and management. The research is a quantitative study consisting of a literature review of the key concepts related to Industry 4.0, smart factories and technology-acceptance theories. The empirical study consisted of surveys completed by management and employees of one of the pharmaceutical manufacturers in South Africa. The questionnaire used in this research consists of questions regarding demographic data and questions regarding the perception of change and factors influencing attitudes towards the acceptance of technology, within the pharmaceutical manufacturing company. Descriptive statistics were used to summarise the data into a more condensed form, which could simplify the identification of patterns in the data. Inferential statistics were used to validate if the conclusions made from the sample data could be inferred to a larger population. Various factors influence perceptions about ease of use and usefulness, which then, in turn, influence attitudes and the intention to use technology. These factors have been examined by numerous authors in the technology acceptance literature. Recommended factors based on the statistical analysis of the questionnaire results were identified. A model, supported by Exploratory Factor Analysis, Correlations and ANOVA Testing identified the following factors as having an influence on the Attitude towards the Positive Impact of Smart Factories, within the pharmaceutical manufacturing company: Training and Development, Individual Characteristics, Trust, Organisational Culture, Resources and Costs and Job Security. The importance of each factor was identified to understand its function how to improve the implementation of smart factories. The research results indicated that the perception of management and employees is different on factors like such as Training, Individual Characteristics, Trust, Resources and Costs, Automation and Support and Parent Company in relation to technology acceptance. There was however no difference in perception between managers and employees on Security, Government Laws and Regulations, Organisational Culture, Peer Support and Organisational Support in relation to technology acceptance. The research study contributed to the identification and understanding of the factors influencing the implementation of smart factories in the pharmaceutical industry.
- Full Text:
- Date Issued: 2019
A model for the alignment of information security requirements within South African small, medium and micro enterprises
- Authors: Speckman, Timothy Harambee
- Date: 2019
- Subjects: Computer security -- Management , Data protection -- Management Small business -- South Africa Knowledge management
- Language: English
- Type: Thesis , Masters , MIT
- Identifier: http://hdl.handle.net/10948/44012 , vital:37092
- Description: Small, medium and micro enterprises (SMMEs) are reported to be the hope of the economy in many developing countries, such as South Africa (SA). The unique characteristics of SMMEs such as their ability to evolve rapidly, and to employ larger labour forces as they grow, make these enterprises valuable to the SA economy, in which poverty and unemployment rates are alarmingly high. Like most modern enterprises, SA SMMEs make use of information and communication technology (ICT) systems - as a vehicle to store, transmit and process information, which is an asset that is critical to their business operations. Thus, the vulnerabilities of these ICT systems need to be addressed, in order to protect the information assets of enterprises. However, SMMEs are known to only implement measures to protect their information assets on an ad hoc basis and frequently as reactive measures to information security incidents. This can be attributed to the fact that most of these enterprises lack the ability to establish their unique information security requirements. Information security requirements are a measure of the level of security needed to adequately protect the information assets of an enterprise. Furthermore, it is reported that information security best practices and standards, which provide guidance on information security, are too complex for SA SMMEs to implement and for SMMEs to use for establishing their unique information security requirements.
- Full Text:
- Date Issued: 2019
- Authors: Speckman, Timothy Harambee
- Date: 2019
- Subjects: Computer security -- Management , Data protection -- Management Small business -- South Africa Knowledge management
- Language: English
- Type: Thesis , Masters , MIT
- Identifier: http://hdl.handle.net/10948/44012 , vital:37092
- Description: Small, medium and micro enterprises (SMMEs) are reported to be the hope of the economy in many developing countries, such as South Africa (SA). The unique characteristics of SMMEs such as their ability to evolve rapidly, and to employ larger labour forces as they grow, make these enterprises valuable to the SA economy, in which poverty and unemployment rates are alarmingly high. Like most modern enterprises, SA SMMEs make use of information and communication technology (ICT) systems - as a vehicle to store, transmit and process information, which is an asset that is critical to their business operations. Thus, the vulnerabilities of these ICT systems need to be addressed, in order to protect the information assets of enterprises. However, SMMEs are known to only implement measures to protect their information assets on an ad hoc basis and frequently as reactive measures to information security incidents. This can be attributed to the fact that most of these enterprises lack the ability to establish their unique information security requirements. Information security requirements are a measure of the level of security needed to adequately protect the information assets of an enterprise. Furthermore, it is reported that information security best practices and standards, which provide guidance on information security, are too complex for SA SMMEs to implement and for SMMEs to use for establishing their unique information security requirements.
- Full Text:
- Date Issued: 2019
A model for using learners' online behaviour to inform differentiated instructional design in MOODLE
- Authors: Leppan, Ronald George
- Date: 2019
- Subjects: Cyberspace -- Psychological aspects , Web applications in libraries Moodle Special education -- Computer programs Computer-assisted instruction -- Computer programs Open source software
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/40393 , vital:36155
- Description: This thesis proposes a learning analytics-based process model, derived from a web analytics process, which aims to build a learner profile of attributes from Moodle log files that can be used for differentiated instructional design in Moodle. Commercial websites are rife with examples of personalisation based on web analytics, while the personalisation of online learning has not yet gained such widespread adoption. Several Instructional Design Models recommend that, in addition to taking prior knowledge and learning outcomes into account, instruction should also be informed by learner attributes. Learning design choices should be made based on unique learner attributes that influence their learning processes. Learner attributes are generally derived from well-known learning styles and associated learning style questionnaires. However, there are some criticisms of learning style theories and the use of questionnaires to create a learner profile. Attributes that can be inferred from learners’ online behaviour could provide a more dynamic learner profile. Education institutions are increasingly using Learning Management Systems, such as Moodle, to deliver and manage online learning. Moodle is not designed to create a learner profile or provide differentiated instruction. However, the abundant data generated by learners accessing course material presented in Moodle provides an opportunity for educators to build such a dynamic learner profile. Individual learner profiles can be used by educators who desire to tailor instruction to the needs of their learners. The proposed model was developed and evaluated using an iterative design focused approach that incorporates characteristics of a web analytics process, instructional design models, Learning Management Systems, educational data mining and adaptive education technologies. At each iteration, the model was evaluated using a technical risk and efficacy strategy. This strategy proposes a formative evaluation in an artificial setting. Evaluation criteria used include relevance, consistency, practicality and utility. The contributions of this thesis address the lack of prescriptive guidance on how to analyse learner online behaviours in order to differentiate learning design in Moodle. The theoretical contribution is a model for a dynamic data-driven approach to profile building and a phased differentiated learning design in a Learning Management System. The practical contribution is an evaluation of the expected practicality and utility of learner modelling from Moodle log files and the provision of tailored instruction using standard Moodle tools. The proposed model recommends that educators should define goals, develop Key Performance Indicators (KPI) to measure goal attainment, collect and analyse suitable metrics towards KPIs, test optional alternative hypotheses and implement actionable insights. To enable differentiated instruction, two phases are necessary: learner modelling and differentiated learning design. Both phases rely on the selection of suitable attributes which influence learning processes, and which can be dynamically inferred from online behaviours. In differentiated learning design, the selection/creation and sequencing of Learning Objects are influenced by the learner attributes. In learner modelling, the data sources and data analysis techniques should enable the discovery of the learner attributes that was catered for in the learning design. Educators who follow the steps described in the proposed model will be capable of building a learner profile from Moodle log files that can be used for differentiated instruction based on any learning style theory.
- Full Text:
- Date Issued: 2019
A model for using learners' online behaviour to inform differentiated instructional design in MOODLE
- Authors: Leppan, Ronald George
- Date: 2019
- Subjects: Cyberspace -- Psychological aspects , Web applications in libraries Moodle Special education -- Computer programs Computer-assisted instruction -- Computer programs Open source software
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/40393 , vital:36155
- Description: This thesis proposes a learning analytics-based process model, derived from a web analytics process, which aims to build a learner profile of attributes from Moodle log files that can be used for differentiated instructional design in Moodle. Commercial websites are rife with examples of personalisation based on web analytics, while the personalisation of online learning has not yet gained such widespread adoption. Several Instructional Design Models recommend that, in addition to taking prior knowledge and learning outcomes into account, instruction should also be informed by learner attributes. Learning design choices should be made based on unique learner attributes that influence their learning processes. Learner attributes are generally derived from well-known learning styles and associated learning style questionnaires. However, there are some criticisms of learning style theories and the use of questionnaires to create a learner profile. Attributes that can be inferred from learners’ online behaviour could provide a more dynamic learner profile. Education institutions are increasingly using Learning Management Systems, such as Moodle, to deliver and manage online learning. Moodle is not designed to create a learner profile or provide differentiated instruction. However, the abundant data generated by learners accessing course material presented in Moodle provides an opportunity for educators to build such a dynamic learner profile. Individual learner profiles can be used by educators who desire to tailor instruction to the needs of their learners. The proposed model was developed and evaluated using an iterative design focused approach that incorporates characteristics of a web analytics process, instructional design models, Learning Management Systems, educational data mining and adaptive education technologies. At each iteration, the model was evaluated using a technical risk and efficacy strategy. This strategy proposes a formative evaluation in an artificial setting. Evaluation criteria used include relevance, consistency, practicality and utility. The contributions of this thesis address the lack of prescriptive guidance on how to analyse learner online behaviours in order to differentiate learning design in Moodle. The theoretical contribution is a model for a dynamic data-driven approach to profile building and a phased differentiated learning design in a Learning Management System. The practical contribution is an evaluation of the expected practicality and utility of learner modelling from Moodle log files and the provision of tailored instruction using standard Moodle tools. The proposed model recommends that educators should define goals, develop Key Performance Indicators (KPI) to measure goal attainment, collect and analyse suitable metrics towards KPIs, test optional alternative hypotheses and implement actionable insights. To enable differentiated instruction, two phases are necessary: learner modelling and differentiated learning design. Both phases rely on the selection of suitable attributes which influence learning processes, and which can be dynamically inferred from online behaviours. In differentiated learning design, the selection/creation and sequencing of Learning Objects are influenced by the learner attributes. In learner modelling, the data sources and data analysis techniques should enable the discovery of the learner attributes that was catered for in the learning design. Educators who follow the steps described in the proposed model will be capable of building a learner profile from Moodle log files that can be used for differentiated instruction based on any learning style theory.
- Full Text:
- Date Issued: 2019
A monitoring and control system for an accelerated weather test chamber
- Authors: Harvey, Luke Gareth
- Date: 2019
- Subjects: Materials -- Deterioration -- Testing , Motor vehicles -- Testing Motor vehicles -- Automatic control Intelligent control systems
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/40360 , vital:36152
- Description: In the Automotive Sector, weathering tests of components are of paramount importance. The most critical components to the overall comfort and durability of a vehicle are the interior components and thus is important to guarantee the quality of these components. The interior components are generally made of plastic, fabric, leather and various painted components. These components are prone to fading, cracking and distortion which is caused by natural factors such as solar radiation, temperature and moisture. This is known as natural weathering. Over the years many weathering tests have been carried out on automotive components to address critical issues during the design process. Many of these tests are simulated in chambers to mimic real life cycles. Although these accelerated tests provide somewhat accurate results in much shorter periods, natural weathering is still essential as it is uncontrolled and unpredictable. This dissertation looks at the method of a metallic chamber used to carry out weathering tests on automotive components and to simulate the conditions inside a vehicle. It addresses the current state and improvement: accurate tracking, intelligent fuzzy logic control and cloud-based monitoring. Currently weather testing chambers are stationery, which does not allow for maximum exposer to solar radiation. Therefore, a system was designed to allow the weather testing chamber to track the azimuth and elevation of the sun to increase the solar radiation on the components tested, a GPS will achieve this. Currently systems lack remote monitoring. A further shortcoming is the lack of controlling the temperature and humidity inside the chamber for sufficient tests. The use of a fuzzy logic controller was implemented to achieve this. The fuzzy logic was compared to other types of logic controllers. To further IoT integration, two main control devices were used, these control devices were two Arduino Mega’s. One Arduino Mega was used for the intelligent fuzzy logic control and the second for solar tracking. The weathering system and controllers were powered by using solar power. The fuzzy logic controller was tested while tracking the sun and then not tracking the sun. The results obtained were compared and it was seen that the fuzzy logic performed very well in both instances, however, the test with tracking the sun performed better. A second test was performed. The second test was similar to the previously mentioned test, but the fuzzy logic had a set point control. It was concluded that both tests performed as expected as the fuzzy logic controlled the temperature and humidity at the given setpoint, but during the solar tracking test the fuzzy logic control performed the best. The fuzzy logic worked well in general use as well as set point control, both for tracking and non-tracking. The tracking performed better than the non-tracking.
- Full Text:
- Date Issued: 2019
- Authors: Harvey, Luke Gareth
- Date: 2019
- Subjects: Materials -- Deterioration -- Testing , Motor vehicles -- Testing Motor vehicles -- Automatic control Intelligent control systems
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/40360 , vital:36152
- Description: In the Automotive Sector, weathering tests of components are of paramount importance. The most critical components to the overall comfort and durability of a vehicle are the interior components and thus is important to guarantee the quality of these components. The interior components are generally made of plastic, fabric, leather and various painted components. These components are prone to fading, cracking and distortion which is caused by natural factors such as solar radiation, temperature and moisture. This is known as natural weathering. Over the years many weathering tests have been carried out on automotive components to address critical issues during the design process. Many of these tests are simulated in chambers to mimic real life cycles. Although these accelerated tests provide somewhat accurate results in much shorter periods, natural weathering is still essential as it is uncontrolled and unpredictable. This dissertation looks at the method of a metallic chamber used to carry out weathering tests on automotive components and to simulate the conditions inside a vehicle. It addresses the current state and improvement: accurate tracking, intelligent fuzzy logic control and cloud-based monitoring. Currently weather testing chambers are stationery, which does not allow for maximum exposer to solar radiation. Therefore, a system was designed to allow the weather testing chamber to track the azimuth and elevation of the sun to increase the solar radiation on the components tested, a GPS will achieve this. Currently systems lack remote monitoring. A further shortcoming is the lack of controlling the temperature and humidity inside the chamber for sufficient tests. The use of a fuzzy logic controller was implemented to achieve this. The fuzzy logic was compared to other types of logic controllers. To further IoT integration, two main control devices were used, these control devices were two Arduino Mega’s. One Arduino Mega was used for the intelligent fuzzy logic control and the second for solar tracking. The weathering system and controllers were powered by using solar power. The fuzzy logic controller was tested while tracking the sun and then not tracking the sun. The results obtained were compared and it was seen that the fuzzy logic performed very well in both instances, however, the test with tracking the sun performed better. A second test was performed. The second test was similar to the previously mentioned test, but the fuzzy logic had a set point control. It was concluded that both tests performed as expected as the fuzzy logic controlled the temperature and humidity at the given setpoint, but during the solar tracking test the fuzzy logic control performed the best. The fuzzy logic worked well in general use as well as set point control, both for tracking and non-tracking. The tracking performed better than the non-tracking.
- Full Text:
- Date Issued: 2019
A multi-factor model for range estimation in electric vehicles
- Authors: Smuts, Martin Bradley
- Date: 2019
- Subjects: Electric vehicles , Hybrid electric vehicles Energy consumption Machine learning Information technology -- Management
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/43589 , vital:36926
- Description: Electric vehicles (EVs) are well-known for their challenges related to trip planning and energy consumption estimation. Range anxiety is currently a barrier to the adoption of EVs. One of the issues influencing range anxiety is the inaccuracy of the remaining driving range (RDR) estimate in on-board displays. RDR displays are important as they can help drivers with trip planning. The RDR is a parameter that changes under environmental and behavioural conditions. Several factors (for example, weather, and traffic) can influence the energy consumption of an EV that are not considered during the RDR estimation in traditional on-board computers or third-party applications, such as navigation or mapping applications. The need for accurate RDR estimation is growing, since this can reduce the range anxiety of drivers. One way of overcoming range anxiety is to provide trip planning applications that provide accurate estimations of the RDR, based on various factors, and which adapt to the users’ driving behaviour. Existing models used for estimating the RDR are often simplified, and do not consider all the factors that can influence it. Collecting data for each factor also presents several challenges. Powerful computing resources are required to collect, transform, and analyse the disparate datasets that are required for each factor. The aim of this research was to design a Multi-factor Model for range estimation in EVs. Five main factors that influence the energy consumption of EVs were identified from literature, namely, Route and Terrain, Driving Behaviour, Weather and Environment, Vehicle Modelling, and Battery Modelling. These factors were used throughout this research to guide the data collection and analysis processes. A Multi-factor Model was proposed based on four main components that collect, process, analyse, and visualise data from available data sources to produce estimates relating to trip planning. A proof-of-concept RDR system was developed and evaluated in field experiments, to demonstrate that the Multi-factor Model addresses the main aim of this research. The experiments were performed to collect data for each of the five factors, and to analyse their impact on energy consumption. Several machine learning techniques were used, and evaluated, for accuracy in estimating the energy consumption, from which the RDR can be derived, for a specified trip. A case study was conducted with an electric mobility programme (uYilo) in Port Elizabeth, South Africa (SA). The case study was used to investigate whether the available resources at uYilo were sufficient to provide data for each of the five factors. Several challenges were noted during the data collection. These were shortages of software applications, a lack of quality data, technical interoperability and data access between the data collection instruments and systems. Data access was a problem in some cases, since proprietary systems restrict access to external developers. The theoretical contribution of this research is a list of factors that influence RDR and a classification of machine learning techniques that can be used to estimate the RDR. The practical contributions of this research include a database of EV trips, proof-of-concept RDR estimation system, and a deployed machine learning model that can be accessed by researchers and EV practitioners. Four research papers were published and presented at local and international conferences. In addition, one conference paper was published in an accredited journal: NextComp 2017 (Appendix C), Conference Paper, Pointe aux Piments (Mauritius); SATNAC 2017 (Appendix F), Conference Paper, Barcelona (Spain); GITMA 2018 (Appendix B), Conference Paper, Mexico City (Mexico); SATNAC 2018 (Appendix G), Conference Paper, George (South Africa), and IFIP World Computer Congress 2018 (Appendix E), Journal Article.
- Full Text:
- Date Issued: 2019
- Authors: Smuts, Martin Bradley
- Date: 2019
- Subjects: Electric vehicles , Hybrid electric vehicles Energy consumption Machine learning Information technology -- Management
- Language: English
- Type: Thesis , Doctoral , DPhil
- Identifier: http://hdl.handle.net/10948/43589 , vital:36926
- Description: Electric vehicles (EVs) are well-known for their challenges related to trip planning and energy consumption estimation. Range anxiety is currently a barrier to the adoption of EVs. One of the issues influencing range anxiety is the inaccuracy of the remaining driving range (RDR) estimate in on-board displays. RDR displays are important as they can help drivers with trip planning. The RDR is a parameter that changes under environmental and behavioural conditions. Several factors (for example, weather, and traffic) can influence the energy consumption of an EV that are not considered during the RDR estimation in traditional on-board computers or third-party applications, such as navigation or mapping applications. The need for accurate RDR estimation is growing, since this can reduce the range anxiety of drivers. One way of overcoming range anxiety is to provide trip planning applications that provide accurate estimations of the RDR, based on various factors, and which adapt to the users’ driving behaviour. Existing models used for estimating the RDR are often simplified, and do not consider all the factors that can influence it. Collecting data for each factor also presents several challenges. Powerful computing resources are required to collect, transform, and analyse the disparate datasets that are required for each factor. The aim of this research was to design a Multi-factor Model for range estimation in EVs. Five main factors that influence the energy consumption of EVs were identified from literature, namely, Route and Terrain, Driving Behaviour, Weather and Environment, Vehicle Modelling, and Battery Modelling. These factors were used throughout this research to guide the data collection and analysis processes. A Multi-factor Model was proposed based on four main components that collect, process, analyse, and visualise data from available data sources to produce estimates relating to trip planning. A proof-of-concept RDR system was developed and evaluated in field experiments, to demonstrate that the Multi-factor Model addresses the main aim of this research. The experiments were performed to collect data for each of the five factors, and to analyse their impact on energy consumption. Several machine learning techniques were used, and evaluated, for accuracy in estimating the energy consumption, from which the RDR can be derived, for a specified trip. A case study was conducted with an electric mobility programme (uYilo) in Port Elizabeth, South Africa (SA). The case study was used to investigate whether the available resources at uYilo were sufficient to provide data for each of the five factors. Several challenges were noted during the data collection. These were shortages of software applications, a lack of quality data, technical interoperability and data access between the data collection instruments and systems. Data access was a problem in some cases, since proprietary systems restrict access to external developers. The theoretical contribution of this research is a list of factors that influence RDR and a classification of machine learning techniques that can be used to estimate the RDR. The practical contributions of this research include a database of EV trips, proof-of-concept RDR estimation system, and a deployed machine learning model that can be accessed by researchers and EV practitioners. Four research papers were published and presented at local and international conferences. In addition, one conference paper was published in an accredited journal: NextComp 2017 (Appendix C), Conference Paper, Pointe aux Piments (Mauritius); SATNAC 2017 (Appendix F), Conference Paper, Barcelona (Spain); GITMA 2018 (Appendix B), Conference Paper, Mexico City (Mexico); SATNAC 2018 (Appendix G), Conference Paper, George (South Africa), and IFIP World Computer Congress 2018 (Appendix E), Journal Article.
- Full Text:
- Date Issued: 2019
A multi-threading software countermeasure to mitigate side channel analysis in the time domain
- Authors: Frieslaar, Ibraheem
- Date: 2019
- Subjects: Computer security , Data encryption (Computer science) , Noise generators (Electronics)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71152 , vital:29790
- Description: This research is the first of its kind to investigate the utilisation of a multi-threading software-based countermeasure to mitigate Side Channel Analysis (SCA) attacks, with a particular focus on the AES-128 cryptographic algorithm. This investigation is novel, as there has not been a software-based countermeasure relying on multi-threading to our knowledge. The research has been tested on the Atmel microcontrollers, as well as a more fully featured system in the form of the popular Raspberry Pi that utilises the ARM7 processor. The main contributions of this research is the introduction of a multi-threading software based countermeasure used to mitigate SCA attacks on both an embedded device and a Raspberry Pi. These threads are comprised of various mathematical operations which are utilised to generate electromagnetic (EM) noise resulting in the obfuscation of the execution of the AES-128 algorithm. A novel EM noise generator known as the FRIES noise generator is implemented to obfuscate data captured in the EM field. FRIES comprises of hiding the execution of AES-128 algorithm within the EM noise generated by the 512 Secure Hash Algorithm (SHA) from the libcrypto++ and OpenSSL libraries. In order to evaluate the proposed countermeasure, a novel attack methodology was developed where the entire secret AES-128 encryption key was recovered from a Raspberry Pi, which has not been achieved before. The FRIES noise generator was pitted against this new attack vector and other known noise generators. The results exhibited that the FRIES noise generator withstood this attack whilst other existing techniques still leaked out secret information. The visual location of the AES-128 encryption algorithm in the EM spectrum and key recovery was prevented. These results demonstrated that the proposed multi-threading software based countermeasure was able to be resistant to existing and new forms of attacks, thus verifying that a multi-threading software based countermeasure can serve to mitigate SCA attacks.
- Full Text:
- Date Issued: 2019
- Authors: Frieslaar, Ibraheem
- Date: 2019
- Subjects: Computer security , Data encryption (Computer science) , Noise generators (Electronics)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71152 , vital:29790
- Description: This research is the first of its kind to investigate the utilisation of a multi-threading software-based countermeasure to mitigate Side Channel Analysis (SCA) attacks, with a particular focus on the AES-128 cryptographic algorithm. This investigation is novel, as there has not been a software-based countermeasure relying on multi-threading to our knowledge. The research has been tested on the Atmel microcontrollers, as well as a more fully featured system in the form of the popular Raspberry Pi that utilises the ARM7 processor. The main contributions of this research is the introduction of a multi-threading software based countermeasure used to mitigate SCA attacks on both an embedded device and a Raspberry Pi. These threads are comprised of various mathematical operations which are utilised to generate electromagnetic (EM) noise resulting in the obfuscation of the execution of the AES-128 algorithm. A novel EM noise generator known as the FRIES noise generator is implemented to obfuscate data captured in the EM field. FRIES comprises of hiding the execution of AES-128 algorithm within the EM noise generated by the 512 Secure Hash Algorithm (SHA) from the libcrypto++ and OpenSSL libraries. In order to evaluate the proposed countermeasure, a novel attack methodology was developed where the entire secret AES-128 encryption key was recovered from a Raspberry Pi, which has not been achieved before. The FRIES noise generator was pitted against this new attack vector and other known noise generators. The results exhibited that the FRIES noise generator withstood this attack whilst other existing techniques still leaked out secret information. The visual location of the AES-128 encryption algorithm in the EM spectrum and key recovery was prevented. These results demonstrated that the proposed multi-threading software based countermeasure was able to be resistant to existing and new forms of attacks, thus verifying that a multi-threading software based countermeasure can serve to mitigate SCA attacks.
- Full Text:
- Date Issued: 2019