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
A novel axially palladium (II)-Schiff base complex substituted silicon (IV) phthalocyanine
- Sen, Pinar, Nyokong, Tebello
- Authors: Sen, Pinar , Nyokong, Tebello
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/186813 , vital:44536 , xlink:href="https://doi.org/10.1016/j.poly.2019.114135"
- Description: In this study, a novel silicon(IV) phthalocyanine is reported for the first time as a phthalocyanine derivative bearing axially a palladium(II)-Schiff base complex. The photophysical and photochemical properties of the new Si(IV)Pc, such as absorption, fluorescence, singlet oxygen quantum yields, triplet state quantum yields and exited state lifetimes were measured in DMSO. The new silicon phthalocyanine displayed very low fluorescence, showing efficient intersystem crossing resulting in high triplet and high singlet oxygen quantum yields in DMSO. When compared with the unsubstituted SiPcCl2, the singlet oxygen quantum yield value (UD = 0.47) in relation to the triplet quantum yield (UT = 0.82), which is an important determinant for PDT applications, increased. The photodynamic antimicrobial chemotherapy activity (PACT) of new Si(IV)Pc towards Staphylococcus aureus was determined in comparison to the unsubstituted SiPcCl2. The results of the photodynamic antimicrobial effect study demonstrated that the Pd(II) complex substituted SiPc (5) possesses excellent photodynamic activity with a reduction percentage value of 99.94% and a log red value of 3.26.
- Full Text:
- Date Issued: 2019
- Authors: Sen, Pinar , Nyokong, Tebello
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/186813 , vital:44536 , xlink:href="https://doi.org/10.1016/j.poly.2019.114135"
- Description: In this study, a novel silicon(IV) phthalocyanine is reported for the first time as a phthalocyanine derivative bearing axially a palladium(II)-Schiff base complex. The photophysical and photochemical properties of the new Si(IV)Pc, such as absorption, fluorescence, singlet oxygen quantum yields, triplet state quantum yields and exited state lifetimes were measured in DMSO. The new silicon phthalocyanine displayed very low fluorescence, showing efficient intersystem crossing resulting in high triplet and high singlet oxygen quantum yields in DMSO. When compared with the unsubstituted SiPcCl2, the singlet oxygen quantum yield value (UD = 0.47) in relation to the triplet quantum yield (UT = 0.82), which is an important determinant for PDT applications, increased. The photodynamic antimicrobial chemotherapy activity (PACT) of new Si(IV)Pc towards Staphylococcus aureus was determined in comparison to the unsubstituted SiPcCl2. The results of the photodynamic antimicrobial effect study demonstrated that the Pd(II) complex substituted SiPc (5) possesses excellent photodynamic activity with a reduction percentage value of 99.94% and a log red value of 3.26.
- Full Text:
- Date Issued: 2019
A novel technique for artificial pack formation in African wild dogs using odour familiarity:
- Marneweck, Courtney J, Marchal, Antoine F J, Marneweck, David G, Beverley, Grant, Davies-Mostert, Harriet T, Parker, Daniel M
- Authors: Marneweck, Courtney J , Marchal, Antoine F J , Marneweck, David G , Beverley, Grant , Davies-Mostert, Harriet T , Parker, Daniel M
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/150060 , vital:38935 , https://doi.org/10.3957/056.049.0116
- Description: Reintroductions are recognized tools for species recovery. However, operations are costly, difficult to implement, and failures are common and not always understood. Their success for group-living species depends on the mimicry of natural processes that promote social integration. Due to fragmented landscapes, human mediated (i.e. artificial) group formation is often required.
- Full Text:
- Date Issued: 2019
- Authors: Marneweck, Courtney J , Marchal, Antoine F J , Marneweck, David G , Beverley, Grant , Davies-Mostert, Harriet T , Parker, Daniel M
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/150060 , vital:38935 , https://doi.org/10.3957/056.049.0116
- Description: Reintroductions are recognized tools for species recovery. However, operations are costly, difficult to implement, and failures are common and not always understood. Their success for group-living species depends on the mimicry of natural processes that promote social integration. Due to fragmented landscapes, human mediated (i.e. artificial) group formation is often required.
- Full Text:
- Date Issued: 2019
A nutrition education tool for practical application of the food based dietary guidelines for primary school teachers in Nelson Mandela Bay
- Authors: Joubert, Tayla Kate
- Date: 2019
- Subjects: Nutrition -- Education
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/44616 , vital:38152
- Description: Background: The South Africa Food-Based Dietary Guidelines (SAFBDG) was developed to promote better food choices for a healthy lifestyle and are included in the school syllabus. Schools remain viable platforms for nutrition education with teachers playing significant roles, but research has shown that teachers do not necessarily know about the SAFBDG and how to incorporate these into the teaching programme. Aim: The aim of this study was to develop a tool in the form of a nutrition education guide for primary school teachers, aimed at the practical application of the SAFBDG, in order to enhance the nutrition knowledge, attitudes and dietary practices of the teachers. Research design and methodology: A quasi-experimental, one group, quantitative design was employed. Forty-six teachers were conveniently chosen from schools in previously disadvantaged areas of Nelson Mandela Bay. The study design consisted of four phases. Phase one consisted of a pre-test where the teachers’ nutrition knowledge, nutrition attitudes, dietary practices, staff wellness and physical activity were determined by means of a standardised questionnaire. A nutritional assessment was also conducted in phase one. In phase two, the nutrition guide, which was Curriculum Assessment Policy Statement compliant for grades four to seven, was developed. In phase three, the guide was used in a workshop to train the teachers that attended phase one of the study, on how to use the nutrition education guide. In phase four, a post-test was conducted after the training to evaluate the effectiveness of the training and to determine whether there has been an increase in the teachers’ nutrition knowledge. Data from the questionnaires were analysed on Microsoft Excel 2016 MSO (16.0.4639.1000). Ethical approval for this study was obtained from the Faculty Postgraduate Studies Committee (FPGSC) of the Faculty of Health Sciences, Nelson Mandela University (Ethics clearance reference number: H18-HEA-DIET-005) and all ethical principles were upheld according to the Belmont report and the Declaration of Helsinki. Results: Of the 46 teachers who participated 36 (78 %) were obese. The mean waist circumference and waist-to-hip ratio was 109.99 and 0.887 respectively (± 17.32 and ± 0.089). The teachers obtained a relatively high mean overall score in the pre-test of 69 % (± 10.78). Only 42 % of the teachers had heard of the SAFBDG before the study. There was an overall statistical significant increase in knowledge of 6 % (p = 0.03) from the pre-test to the post-test. The dietary practice was obtained through a food frequency questionnaire (FFQ), which showed under-reporting. The most neglected food groups were legumes, dairy and vegetables/ fruit. Hypertension was the highest self-reported condition, with just under a quarter of the teachers having hypertension (high blood pressure). There was no statistical significance between the teachers’ BMI and their nutrition knowledge as well as no statistical significance between their BMI and their physical activity level. Conclusion and recommendations: Even though the teachers obtained a relatively high mean overall score in their pre-test, there were still gaps in their nutrition knowledge. These gaps in the teachers’ knowledge results in insufficient nutrition knowledge being provided to the learners, leading to poor dietary practices and misconceptions regarding different foods among the learners as well as the teachers. By providing training for the teachers, it will not only improve their nutrition knowledge but potentially also help to improve their lifestyle. With enhanced nutrition knowledge, the teachers can communicate sufficient information to their learners. The DoBE need to advocate for a healthier school environment in which the SAFBDG are implemented more extensively in the curriculum as well as part of school food policies.
- Full Text:
- Date Issued: 2019
- Authors: Joubert, Tayla Kate
- Date: 2019
- Subjects: Nutrition -- Education
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/44616 , vital:38152
- Description: Background: The South Africa Food-Based Dietary Guidelines (SAFBDG) was developed to promote better food choices for a healthy lifestyle and are included in the school syllabus. Schools remain viable platforms for nutrition education with teachers playing significant roles, but research has shown that teachers do not necessarily know about the SAFBDG and how to incorporate these into the teaching programme. Aim: The aim of this study was to develop a tool in the form of a nutrition education guide for primary school teachers, aimed at the practical application of the SAFBDG, in order to enhance the nutrition knowledge, attitudes and dietary practices of the teachers. Research design and methodology: A quasi-experimental, one group, quantitative design was employed. Forty-six teachers were conveniently chosen from schools in previously disadvantaged areas of Nelson Mandela Bay. The study design consisted of four phases. Phase one consisted of a pre-test where the teachers’ nutrition knowledge, nutrition attitudes, dietary practices, staff wellness and physical activity were determined by means of a standardised questionnaire. A nutritional assessment was also conducted in phase one. In phase two, the nutrition guide, which was Curriculum Assessment Policy Statement compliant for grades four to seven, was developed. In phase three, the guide was used in a workshop to train the teachers that attended phase one of the study, on how to use the nutrition education guide. In phase four, a post-test was conducted after the training to evaluate the effectiveness of the training and to determine whether there has been an increase in the teachers’ nutrition knowledge. Data from the questionnaires were analysed on Microsoft Excel 2016 MSO (16.0.4639.1000). Ethical approval for this study was obtained from the Faculty Postgraduate Studies Committee (FPGSC) of the Faculty of Health Sciences, Nelson Mandela University (Ethics clearance reference number: H18-HEA-DIET-005) and all ethical principles were upheld according to the Belmont report and the Declaration of Helsinki. Results: Of the 46 teachers who participated 36 (78 %) were obese. The mean waist circumference and waist-to-hip ratio was 109.99 and 0.887 respectively (± 17.32 and ± 0.089). The teachers obtained a relatively high mean overall score in the pre-test of 69 % (± 10.78). Only 42 % of the teachers had heard of the SAFBDG before the study. There was an overall statistical significant increase in knowledge of 6 % (p = 0.03) from the pre-test to the post-test. The dietary practice was obtained through a food frequency questionnaire (FFQ), which showed under-reporting. The most neglected food groups were legumes, dairy and vegetables/ fruit. Hypertension was the highest self-reported condition, with just under a quarter of the teachers having hypertension (high blood pressure). There was no statistical significance between the teachers’ BMI and their nutrition knowledge as well as no statistical significance between their BMI and their physical activity level. Conclusion and recommendations: Even though the teachers obtained a relatively high mean overall score in their pre-test, there were still gaps in their nutrition knowledge. These gaps in the teachers’ knowledge results in insufficient nutrition knowledge being provided to the learners, leading to poor dietary practices and misconceptions regarding different foods among the learners as well as the teachers. By providing training for the teachers, it will not only improve their nutrition knowledge but potentially also help to improve their lifestyle. With enhanced nutrition knowledge, the teachers can communicate sufficient information to their learners. The DoBE need to advocate for a healthier school environment in which the SAFBDG are implemented more extensively in the curriculum as well as part of school food policies.
- Full Text:
- Date Issued: 2019
A nutrition education tool for practical application of the food based dietary guidelines for primary school teachers in Nelson Mandela Bay
- Authors: Joubert, Tayla Kate
- Date: 2019
- Subjects: Malnutrition -- South Africa -- Port Elizabeth , Nutrition—Evaluation Nutrition -- Evaluation Nutrition -- South Africa -- Port Elizabeth
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/45019 , vital:38226
- Description: The South Africa Food-Based Dietary Guidelines (SAFBDG) was developed to promote better food choices for a healthy lifestyle and are included in the school syllabus. Schools remain viable platforms for nutrition education with teachers playing significant roles, but research has shown that teachers do not necessarily know about the SAFBDG and how to incorporate these into the teaching programme. The aim of this study was to develop a tool in the form of a nutrition education guide for primary school teachers, aimed at the practical application of the SAFBDG, in order to enhance the nutrition knowledge, attitudes and dietary practices of the teachers. A quasi-experimental, one group, quantitative design was employed. Forty-six teachers were conveniently chosen from schools in previously disadvantaged areas of Nelson Mandela Bay. The study design consisted of four phases. Phase one consisted of a pre-test where the teachers’ nutrition knowledge, nutrition attitudes, dietary practices, staff wellness and physical activity were determined by means of a standardised questionnaire. A nutritional assessment was also conducted in phase one. In phase two, the nutrition guide, which was Curriculum Assessment Policy Statement compliant for grades four to seven, was developed. In phase three, the guide was used in a workshop to train the teachers that attended phase one of the study, on how to use the nutrition education guide. In phase four, a post-test was conducted after the training to evaluate the effectiveness of the training and to determine whether there has been an increase in the teachers’ nutrition knowledge. Data from the questionnaires were analysed on Microsoft Excel 2016 MSO (16.0.4639.1000). Ethical approval for this study was obtained from the Faculty Postgraduate Studies Committee (FPGSC) of the Faculty of Health Sciences, Nelson Mandela University (Ethics clearance reference number: H18-HEA-DIET-005) and all ethical principles were upheld according to the Belmont report and the Declaration of Helsinki. Results of the research 46 teachers who participated 36 (78 %) were obese. The mean waist circumference and waist-to-hip ratio was 109.99 and 0.887 respectively (± 17.32 and ± 0.089). The teachers obtained a relatively high mean overall score in the pre-test of 69 % (± 10.78). Only 42 % of the teachers had heard of the SAFBDG before the study. There was an overall statistical significant increase in knowledge of 6 % (p = 0.03) from the pre-test to the post-test. The dietary practice was obtained through a food frequency questionnaire (FFQ), which showed under-reporting. The most neglected food groups were legumes, dairy and vegetables/ fruit. Hypertension was the highest self-reported condition, with just under a quarter of the teachers having hypertension (high blood pressure). There was no statistical significance between the teachers’ BMI and their nutrition knowledge as well as no statistical significance between their BMI and their physical activity level. Even though the teachers obtained a relatively high mean overall score in their pre-test, there were still gaps in their nutrition knowledge. These gaps in the teachers’ knowledge results in insufficient nutrition knowledge being provided to the learners, leading to poor dietary practices and misconceptions regarding different foods among the learners as well as the teachers. By providing training for the teachers, it will not only improve their nutrition knowledge but potentially also help to improve their lifestyle. With enhanced nutrition knowledge, the teachers can communicate sufficient information to their learners. The DoBE need to advocate for a healthier school environment in which the SAFBDG are implemented more extensively in the curriculum as well as part of school food policies.
- Full Text:
- Date Issued: 2019
- Authors: Joubert, Tayla Kate
- Date: 2019
- Subjects: Malnutrition -- South Africa -- Port Elizabeth , Nutrition—Evaluation Nutrition -- Evaluation Nutrition -- South Africa -- Port Elizabeth
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/45019 , vital:38226
- Description: The South Africa Food-Based Dietary Guidelines (SAFBDG) was developed to promote better food choices for a healthy lifestyle and are included in the school syllabus. Schools remain viable platforms for nutrition education with teachers playing significant roles, but research has shown that teachers do not necessarily know about the SAFBDG and how to incorporate these into the teaching programme. The aim of this study was to develop a tool in the form of a nutrition education guide for primary school teachers, aimed at the practical application of the SAFBDG, in order to enhance the nutrition knowledge, attitudes and dietary practices of the teachers. A quasi-experimental, one group, quantitative design was employed. Forty-six teachers were conveniently chosen from schools in previously disadvantaged areas of Nelson Mandela Bay. The study design consisted of four phases. Phase one consisted of a pre-test where the teachers’ nutrition knowledge, nutrition attitudes, dietary practices, staff wellness and physical activity were determined by means of a standardised questionnaire. A nutritional assessment was also conducted in phase one. In phase two, the nutrition guide, which was Curriculum Assessment Policy Statement compliant for grades four to seven, was developed. In phase three, the guide was used in a workshop to train the teachers that attended phase one of the study, on how to use the nutrition education guide. In phase four, a post-test was conducted after the training to evaluate the effectiveness of the training and to determine whether there has been an increase in the teachers’ nutrition knowledge. Data from the questionnaires were analysed on Microsoft Excel 2016 MSO (16.0.4639.1000). Ethical approval for this study was obtained from the Faculty Postgraduate Studies Committee (FPGSC) of the Faculty of Health Sciences, Nelson Mandela University (Ethics clearance reference number: H18-HEA-DIET-005) and all ethical principles were upheld according to the Belmont report and the Declaration of Helsinki. Results of the research 46 teachers who participated 36 (78 %) were obese. The mean waist circumference and waist-to-hip ratio was 109.99 and 0.887 respectively (± 17.32 and ± 0.089). The teachers obtained a relatively high mean overall score in the pre-test of 69 % (± 10.78). Only 42 % of the teachers had heard of the SAFBDG before the study. There was an overall statistical significant increase in knowledge of 6 % (p = 0.03) from the pre-test to the post-test. The dietary practice was obtained through a food frequency questionnaire (FFQ), which showed under-reporting. The most neglected food groups were legumes, dairy and vegetables/ fruit. Hypertension was the highest self-reported condition, with just under a quarter of the teachers having hypertension (high blood pressure). There was no statistical significance between the teachers’ BMI and their nutrition knowledge as well as no statistical significance between their BMI and their physical activity level. Even though the teachers obtained a relatively high mean overall score in their pre-test, there were still gaps in their nutrition knowledge. These gaps in the teachers’ knowledge results in insufficient nutrition knowledge being provided to the learners, leading to poor dietary practices and misconceptions regarding different foods among the learners as well as the teachers. By providing training for the teachers, it will not only improve their nutrition knowledge but potentially also help to improve their lifestyle. With enhanced nutrition knowledge, the teachers can communicate sufficient information to their learners. The DoBE need to advocate for a healthier school environment in which the SAFBDG are implemented more extensively in the curriculum as well as part of school food policies.
- Full Text:
- Date Issued: 2019
A phenomenological study of Senior Primary school teachers’ understandings of an English Across the Curriculum approach to language teaching in Namibia
- Authors: Kambonde, Emily
- Date: 2019
- Subjects: English teachers -- Training of -- Namibia , English language -- Study and teaching (Elementary) -- Namibia
- Language: English
- Type: text , Thesis , Masters , MEd
- Identifier: http://hdl.handle.net/10962/92381 , vital:30718
- Description: This is a phenomenological study designed to investigate English teachers’ understandings of the concept of English Across the Curriculum (EAC), and the extent to which such understandings inform their pedagogic practices at the Senior Primary phase, in a Namibian context. The study was located within the qualitative, interpretive paradigm, using a multi-method approach of semi-structured interviews, classroom observations and documentary evidence as research instruments. The participants were three English second-language teachers at a primary school in a suburban area. Findings from the study revealed that there were several understandings of EAC, and though there might have been an underlying understanding of the concept, classroom practices were incongruent with what EAC requires. It was also found that there are documents based on social constructivist and Genre Theory in the National Professional Standards for teachers, but teachers were not familiar with the content of these documents and they were not used by teachers as guiding documents on how they need to implement EAC. It is recommended that English teachers receive continuous professional development courses on language development theories and EAC, as well as specific training to implement EAC so that “every teacher can be a language teacher”.
- Full Text:
- Date Issued: 2019
- Authors: Kambonde, Emily
- Date: 2019
- Subjects: English teachers -- Training of -- Namibia , English language -- Study and teaching (Elementary) -- Namibia
- Language: English
- Type: text , Thesis , Masters , MEd
- Identifier: http://hdl.handle.net/10962/92381 , vital:30718
- Description: This is a phenomenological study designed to investigate English teachers’ understandings of the concept of English Across the Curriculum (EAC), and the extent to which such understandings inform their pedagogic practices at the Senior Primary phase, in a Namibian context. The study was located within the qualitative, interpretive paradigm, using a multi-method approach of semi-structured interviews, classroom observations and documentary evidence as research instruments. The participants were three English second-language teachers at a primary school in a suburban area. Findings from the study revealed that there were several understandings of EAC, and though there might have been an underlying understanding of the concept, classroom practices were incongruent with what EAC requires. It was also found that there are documents based on social constructivist and Genre Theory in the National Professional Standards for teachers, but teachers were not familiar with the content of these documents and they were not used by teachers as guiding documents on how they need to implement EAC. It is recommended that English teachers receive continuous professional development courses on language development theories and EAC, as well as specific training to implement EAC so that “every teacher can be a language teacher”.
- Full Text:
- Date Issued: 2019
A phenomenological study on the experiences of adults, in Nongoma KwaZulu Natal who headed households in their childhood
- Authors: Buthelezi, Nondumiso
- Date: 2019
- Subjects: Orphanages Households
- Language: English
- Type: Thesis , Masters , MSoc. Sci (Psychology)
- Identifier: http://hdl.handle.net/10353/17652 , vital:41132
- Description: The aim of this study was to explore the lived experiences of adults who headed households in their childhood. The phenomenon of child-headed households is intricate and multidimensional. Not only does it have implications on the family system, it also impacts on the community and has insightful consequences for the welfare of children, as well as the realisation of their rights. The rationale for the study was to explore the phenomena of child-headed households from a reflective perspective, from previous child headers of households. In order to carry out this aim, the researcher utilised the systems theory, kinship theory, as well as the African philosophy of Ubuntu to anchor the study. Interpretative Phenomenological Analysis (IPA) was used as a qualitative research methodology in this study. Data was generated through in-depth semi-structured interviews with the four purposively selected participants. The interviews with the participants were recorded and further transcribed verbatim. The IPA data analysis, as set out by Jonathan Smith, was applied manually to the transcribed extracts. The findings of the study indicated that headers of child households face challenges related to psychological well-being, emotional well-being as well as educational difficulties. It is recommended that government strengthen policies that will support and protect children who are heading families
- Full Text:
- Date Issued: 2019
- Authors: Buthelezi, Nondumiso
- Date: 2019
- Subjects: Orphanages Households
- Language: English
- Type: Thesis , Masters , MSoc. Sci (Psychology)
- Identifier: http://hdl.handle.net/10353/17652 , vital:41132
- Description: The aim of this study was to explore the lived experiences of adults who headed households in their childhood. The phenomenon of child-headed households is intricate and multidimensional. Not only does it have implications on the family system, it also impacts on the community and has insightful consequences for the welfare of children, as well as the realisation of their rights. The rationale for the study was to explore the phenomena of child-headed households from a reflective perspective, from previous child headers of households. In order to carry out this aim, the researcher utilised the systems theory, kinship theory, as well as the African philosophy of Ubuntu to anchor the study. Interpretative Phenomenological Analysis (IPA) was used as a qualitative research methodology in this study. Data was generated through in-depth semi-structured interviews with the four purposively selected participants. The interviews with the participants were recorded and further transcribed verbatim. The IPA data analysis, as set out by Jonathan Smith, was applied manually to the transcribed extracts. The findings of the study indicated that headers of child households face challenges related to psychological well-being, emotional well-being as well as educational difficulties. It is recommended that government strengthen policies that will support and protect children who are heading families
- Full Text:
- Date Issued: 2019
A physiological study on a commercial reef fish to quantify the relationship between exploitation and climate change resilience
- Authors: Duncan, Murray Ian
- Date: 2019
- Subjects: Chrysoblephus laticeps -- Climatic factors , Chrysoblephus laticeps -- Physiology , Sparidae -- South Africa -- Climatic factors , Reef fishes -- South Africa -- Climatic factors , Fish populations -- South Africa -- Climatic factors , Fish populations -- Measurement , Fish populations -- Monitoring , Fisheries -- South Africa -- Environmental aspects , Ocean temperature -- Physiological effect -- South Africa
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/76541 , vital:30599
- Description: The persistence of harvested fish populations in the Anthropocene will be determined, above all, by how they respond to the interacting effects of climate change and fisheries exploitation. Predicting how populations will respond to both these threats is essential for any adaptive and sustainable management strategy. The response of fish populations to climate change is underpinned by physiological rates and tolerances, and emerging evidence suggests there may be physiological-based selection in capture fisheries. By quantifying important physiological rates of a model species, the endemic seabream, Chrysoblephus laticeps, across ecologically relevant thermal gradients and from populations subjected to varying intensities of commercial exploitation, this thesis aimed to 1) provide the first physiologically grounded climate resilience assessment for a South African linefish species, and 2) elucidate whether exploitation can drive populations to less physiologically resilient states in response to climate change. To identify physiologically limiting sea temperatures and to determine if exploitation alters physiological trait distributions, an intermittent flow respirometry experiment was used to test the metabolic response of spatially protected and exploited populations of C. laticeps to acute thermal variability. Exploited populations showed reduced metabolic phenotype diversity, fewer high-performance aerobic scope phenotypes, and a significantly lower aerobic scope curve across all test temperatures. Although both populations maintained a relatively high aerobic scope across a wide thermal range, their metabolic rates were compromised when extreme cold events were simulated (8 °C), suggesting that predicted future increases in upwelling frequency and intensity may be the primary limiting factor in a more thermally variable future ocean. The increment widths of annuli in the otoliths of C. laticeps from contemporary and historic collections were measured, as a proxy for the annual growth rate of exploited and protected populations. Hierarchical mixed models were used to partition growth variation within and among individuals and ascribe growth to intrinsic and extrinsic effects. The best model for the protected population indicated that the growth response of C. laticeps was poorer during years characterised by a high cumulative upwelling intensity, and better during years characterised by higher mean autumn sea surface temperatures. The exploited population growth chronology was too short to identify an extrinsic growth driver. The growth results again highlight the role of thermal variability in modulating the response of C. laticeps to its ambient environment and indicate that the predicted increases in upwelling frequency and intensity may constrain future growth rates of this species. A metabolic index (ϕ), representing the ratio of O2 supply to demand at various temperatures and oxygen concentrations, was estimated for exploited and protected populations of C. laticeps and used to predict future distribution responses. There was no difference in the laboratory calibrations of ϕ between populations, and all data was subsequently combined into a single piecewise (12 °C) calibrated ϕ model. To predict the distribution of C. laticeps, ϕ was projected across a high-resolution ocean model of the South African coastal zone, and a species distribution model implemented using the random forest algorithm and C. laticeps occurrence points. The future distribution of C. laticeps was estimated by predicting trained models across ocean model projections up to 2100. The best predictor of C. laticeps’ current distribution was minimum monthly ϕ and future predictions indicated only a slight range contraction on either edge of C. laticeps’ distribution by 2100. In order to provide policy makers, currently developing climate change management frameworks for South Africa’s ocean, with a usable output, the results of all research chapters were combined into a marine spatial model. The spatial model identified areas where C. laticeps is predicted to be resilient to climate change in terms of physiology, growth and distribution responses, which can then be prioritised for adaptation measures, such as spatial protection from exploitation. While these results are specific to C. laticeps, the methodology developed to identify areas of climate resilience has broad applications across taxa. From a global perspective, perhaps the most salient points to consider from this case study are the evidence of selective exploitation on physiological traits and the importance of environmental variability, rather than long-term mean climate changes, in affecting organism performance. These ideas are congruent with the current paradigm shift in how we think of the ocean, selective fisheries, and how they relate to organism climate resilience.
- Full Text:
- Date Issued: 2019
- Authors: Duncan, Murray Ian
- Date: 2019
- Subjects: Chrysoblephus laticeps -- Climatic factors , Chrysoblephus laticeps -- Physiology , Sparidae -- South Africa -- Climatic factors , Reef fishes -- South Africa -- Climatic factors , Fish populations -- South Africa -- Climatic factors , Fish populations -- Measurement , Fish populations -- Monitoring , Fisheries -- South Africa -- Environmental aspects , Ocean temperature -- Physiological effect -- South Africa
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/76541 , vital:30599
- Description: The persistence of harvested fish populations in the Anthropocene will be determined, above all, by how they respond to the interacting effects of climate change and fisheries exploitation. Predicting how populations will respond to both these threats is essential for any adaptive and sustainable management strategy. The response of fish populations to climate change is underpinned by physiological rates and tolerances, and emerging evidence suggests there may be physiological-based selection in capture fisheries. By quantifying important physiological rates of a model species, the endemic seabream, Chrysoblephus laticeps, across ecologically relevant thermal gradients and from populations subjected to varying intensities of commercial exploitation, this thesis aimed to 1) provide the first physiologically grounded climate resilience assessment for a South African linefish species, and 2) elucidate whether exploitation can drive populations to less physiologically resilient states in response to climate change. To identify physiologically limiting sea temperatures and to determine if exploitation alters physiological trait distributions, an intermittent flow respirometry experiment was used to test the metabolic response of spatially protected and exploited populations of C. laticeps to acute thermal variability. Exploited populations showed reduced metabolic phenotype diversity, fewer high-performance aerobic scope phenotypes, and a significantly lower aerobic scope curve across all test temperatures. Although both populations maintained a relatively high aerobic scope across a wide thermal range, their metabolic rates were compromised when extreme cold events were simulated (8 °C), suggesting that predicted future increases in upwelling frequency and intensity may be the primary limiting factor in a more thermally variable future ocean. The increment widths of annuli in the otoliths of C. laticeps from contemporary and historic collections were measured, as a proxy for the annual growth rate of exploited and protected populations. Hierarchical mixed models were used to partition growth variation within and among individuals and ascribe growth to intrinsic and extrinsic effects. The best model for the protected population indicated that the growth response of C. laticeps was poorer during years characterised by a high cumulative upwelling intensity, and better during years characterised by higher mean autumn sea surface temperatures. The exploited population growth chronology was too short to identify an extrinsic growth driver. The growth results again highlight the role of thermal variability in modulating the response of C. laticeps to its ambient environment and indicate that the predicted increases in upwelling frequency and intensity may constrain future growth rates of this species. A metabolic index (ϕ), representing the ratio of O2 supply to demand at various temperatures and oxygen concentrations, was estimated for exploited and protected populations of C. laticeps and used to predict future distribution responses. There was no difference in the laboratory calibrations of ϕ between populations, and all data was subsequently combined into a single piecewise (12 °C) calibrated ϕ model. To predict the distribution of C. laticeps, ϕ was projected across a high-resolution ocean model of the South African coastal zone, and a species distribution model implemented using the random forest algorithm and C. laticeps occurrence points. The future distribution of C. laticeps was estimated by predicting trained models across ocean model projections up to 2100. The best predictor of C. laticeps’ current distribution was minimum monthly ϕ and future predictions indicated only a slight range contraction on either edge of C. laticeps’ distribution by 2100. In order to provide policy makers, currently developing climate change management frameworks for South Africa’s ocean, with a usable output, the results of all research chapters were combined into a marine spatial model. The spatial model identified areas where C. laticeps is predicted to be resilient to climate change in terms of physiology, growth and distribution responses, which can then be prioritised for adaptation measures, such as spatial protection from exploitation. While these results are specific to C. laticeps, the methodology developed to identify areas of climate resilience has broad applications across taxa. From a global perspective, perhaps the most salient points to consider from this case study are the evidence of selective exploitation on physiological traits and the importance of environmental variability, rather than long-term mean climate changes, in affecting organism performance. These ideas are congruent with the current paradigm shift in how we think of the ocean, selective fisheries, and how they relate to organism climate resilience.
- Full Text:
- Date Issued: 2019
A pilot wide-field VLBI survey of the GOODS-North field
- Authors: Akoto-Danso, Alexander
- Date: 2019
- Subjects: Radio astronomy , Very long baseline interferometry , Radio interometers , Imaging systems in astronomy , Hubble Space Telescope (Spacecraft) -- Observations
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/72296 , vital:30027
- Description: Very Long Baseline Interferometry (VLBI) has significant advantages in disentangling active galactic nuclei (AGN) from star formation, particularly at intermediate to high-redshift due to its high angular resolution and insensitivity to dust. Surveys using VLBI arrays are only just becoming practical over wide areas with numerous developments and innovations (such as multi-phase centre techniques) in observation and data analysis techniques. However, fully automated pipelines for VLBI data analysis are based on old software packages and are unable to incorporate new calibration and imaging algorithms. In this work, the researcher developed a pipeline for VLBI data analysis which integrates a recent wide-field imaging algorithm, RFI excision, and a purpose-built source finding algorithm specifically developed for the 64kx64k wide-field VLBI images. The researcher used this novel pipeline to process 6% (~ 9 arcmin2 of the total 160 arcmin2) of the data from the CANDELS GOODS- North extragalactic field at 1.6 GHz. The milli-arcsec scale images have an average rms of a ~ 10 uJy/beam. Forty four (44) candidate sources were detected, most of which are at sub-mJy flux densities, having brightness temperatures and luminosities of >5x105 K and >6x1021 W Hz-1 respectively. This work demonstrates that automated post-processing pipelines for wide-field, uniform sensitivity VLBI surveys are feasible and indeed made more efficient with new software, wide-field imaging algorithms and more purpose-built source- finders. This broadens the discovery space for future wide-field surveys with upcoming arrays such as the African VLBI Network (AVN), MeerKAT and the Square Kilometre Array (SKA).
- Full Text:
- Date Issued: 2019
- Authors: Akoto-Danso, Alexander
- Date: 2019
- Subjects: Radio astronomy , Very long baseline interferometry , Radio interometers , Imaging systems in astronomy , Hubble Space Telescope (Spacecraft) -- Observations
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/72296 , vital:30027
- Description: Very Long Baseline Interferometry (VLBI) has significant advantages in disentangling active galactic nuclei (AGN) from star formation, particularly at intermediate to high-redshift due to its high angular resolution and insensitivity to dust. Surveys using VLBI arrays are only just becoming practical over wide areas with numerous developments and innovations (such as multi-phase centre techniques) in observation and data analysis techniques. However, fully automated pipelines for VLBI data analysis are based on old software packages and are unable to incorporate new calibration and imaging algorithms. In this work, the researcher developed a pipeline for VLBI data analysis which integrates a recent wide-field imaging algorithm, RFI excision, and a purpose-built source finding algorithm specifically developed for the 64kx64k wide-field VLBI images. The researcher used this novel pipeline to process 6% (~ 9 arcmin2 of the total 160 arcmin2) of the data from the CANDELS GOODS- North extragalactic field at 1.6 GHz. The milli-arcsec scale images have an average rms of a ~ 10 uJy/beam. Forty four (44) candidate sources were detected, most of which are at sub-mJy flux densities, having brightness temperatures and luminosities of >5x105 K and >6x1021 W Hz-1 respectively. This work demonstrates that automated post-processing pipelines for wide-field, uniform sensitivity VLBI surveys are feasible and indeed made more efficient with new software, wide-field imaging algorithms and more purpose-built source- finders. This broadens the discovery space for future wide-field surveys with upcoming arrays such as the African VLBI Network (AVN), MeerKAT and the Square Kilometre Array (SKA).
- Full Text:
- Date Issued: 2019
A platform for women’s experiences? a case of the hip hop scene in Grahamstown, Eastern Cape
- Authors: Kabwato, Sasha Nyasha
- Date: 2019
- Subjects: Hip-hop -- South Africa -- Makhanda , Popular culture -- South Africa -- Makhanda , Rap musicians -- South Africa -- Makhanda , Musicians, Black -- South Africa -- Makhanda , Women musicians, Black -- South Africa -- Makhanda , Women, Black -- South Africa -- Makhanda -- Psychology
- Language: English
- Type: text , Thesis , Masters , MSocSc
- Identifier: http://hdl.handle.net/10962/96503 , vital:31287
- Description: The main aim of this research is to examine the hip hop scene in Grahamstown, Eastern Cape and whether hip hop can serve as a significant platform to discuss women’s lived experiences. This study also places focus on how female rappers construct their rap personas, as well as how they are perceived by their male counterparts. In order to understand the multifaceted viewpoints, it was necessary to interview both male and female hip hop artists. Eight interviews were conducted with eight young black rappers who are actively involved in the Grahamstown hip hop scene. It was found that hip hop, like any other art form, is a significant platform for women to express themselves, however gender constraints limit who is willing to listen to and promote their music. Male rappers advocate for women to talk about their stories, yet are more unlikely to listen because it does not relate to their struggles. In addition, there seem to be four specific tropes that female rappers choose to construct their identities from. Female rappers tend to create their personas around: Queen Mother, Fly Sista, Bitch with Attitude, and Lesbian. However, these categories are fluid and it was found that women navigate these categories depending on their audience and message they want to convey at a particular moment. Lastly, there is a split between Grahamstown West (Rhodes University) and Grahamstown East (township). University students are unlikely to perform in the township, and township residents rarely perform at organised events in Grahamstown West. In addition, Rhodes University students are more likely to feature on the university run radio station, rather than Radio Grahamstown, the local community radio.
- Full Text:
- Date Issued: 2019
- Authors: Kabwato, Sasha Nyasha
- Date: 2019
- Subjects: Hip-hop -- South Africa -- Makhanda , Popular culture -- South Africa -- Makhanda , Rap musicians -- South Africa -- Makhanda , Musicians, Black -- South Africa -- Makhanda , Women musicians, Black -- South Africa -- Makhanda , Women, Black -- South Africa -- Makhanda -- Psychology
- Language: English
- Type: text , Thesis , Masters , MSocSc
- Identifier: http://hdl.handle.net/10962/96503 , vital:31287
- Description: The main aim of this research is to examine the hip hop scene in Grahamstown, Eastern Cape and whether hip hop can serve as a significant platform to discuss women’s lived experiences. This study also places focus on how female rappers construct their rap personas, as well as how they are perceived by their male counterparts. In order to understand the multifaceted viewpoints, it was necessary to interview both male and female hip hop artists. Eight interviews were conducted with eight young black rappers who are actively involved in the Grahamstown hip hop scene. It was found that hip hop, like any other art form, is a significant platform for women to express themselves, however gender constraints limit who is willing to listen to and promote their music. Male rappers advocate for women to talk about their stories, yet are more unlikely to listen because it does not relate to their struggles. In addition, there seem to be four specific tropes that female rappers choose to construct their identities from. Female rappers tend to create their personas around: Queen Mother, Fly Sista, Bitch with Attitude, and Lesbian. However, these categories are fluid and it was found that women navigate these categories depending on their audience and message they want to convey at a particular moment. Lastly, there is a split between Grahamstown West (Rhodes University) and Grahamstown East (township). University students are unlikely to perform in the township, and township residents rarely perform at organised events in Grahamstown West. In addition, Rhodes University students are more likely to feature on the university run radio station, rather than Radio Grahamstown, the local community radio.
- Full Text:
- Date Issued: 2019