The use of simulators and artificial intelligence in leadership feedback
- Authors: Ntombana, Sixolile
- Date: 2022-10-14
- Subjects: Artificial intelligence , Leadership , Employees Rating of , Communication in industrial relations , Qualitative reasoning Technological innovations , Chatbots
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/357685 , vital:64767
- Description: Leadership is a key factor in team success. For leadership to succeed, leaders need to possess the requisite competencies that can facilitate their performance. Team skills is identified as a leadership competency that is prioritised and most sought after by leaders. This follows studies that confirm that team skills are vital for leadership and team success. For leadership to develop team skills, feedback must be provided. Feedback is identified as information that is provided by an observer on a particular performance. The role of feedback in leadership development serves the purposes of engagement and self-reflection and evaluation of a leader’s performance. In this light, feedback cannot be separated from leadership as it is an essential part of communication in a leadership context. The nature and source of feedback can affect how the feedback is received, as shown by studies that suggest that the effectiveness of feedback goes beyond the content or nature (good/bad feedback) of the feedback. This study looks at two feedback sources: humans and artificial intelligence (AI) using students as the population. Humans have been the traditional source in feedback provision. Thus, in a team setting peers provide feedback on their peers’ performances. Unprecedented technological advancements have seen the improvement of AI capabilities to being able to give feedback. This has made AI a feedback source. Following these developments, this research assessed the way in which humans and AI provide feedback and the way in which students react to feedback provided by humans and AI. The research used chatbot AI, a Skills Simulator Assessment, launched by Kotlyar (2018). Students registered for Management One at Rhodes University in 2021 were the population for this research. The research was comprised of two phases where in phase one they were assessed by the Skill Simulator Assessment and in phase two they were assessed by their peers. This research found that students are not averse to feedback from AI, although they prefer peer feedback. It was further found that peer feedback tends to be tainted by lenience, while AI is not affected by lenience. This finding marked a significant development of AI in feedback provision. , Thesis (MCom) -- Faculty of Commerce, Management, 2022
- Full Text:
- Date Issued: 2022-10-14
- Authors: Ntombana, Sixolile
- Date: 2022-10-14
- Subjects: Artificial intelligence , Leadership , Employees Rating of , Communication in industrial relations , Qualitative reasoning Technological innovations , Chatbots
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/357685 , vital:64767
- Description: Leadership is a key factor in team success. For leadership to succeed, leaders need to possess the requisite competencies that can facilitate their performance. Team skills is identified as a leadership competency that is prioritised and most sought after by leaders. This follows studies that confirm that team skills are vital for leadership and team success. For leadership to develop team skills, feedback must be provided. Feedback is identified as information that is provided by an observer on a particular performance. The role of feedback in leadership development serves the purposes of engagement and self-reflection and evaluation of a leader’s performance. In this light, feedback cannot be separated from leadership as it is an essential part of communication in a leadership context. The nature and source of feedback can affect how the feedback is received, as shown by studies that suggest that the effectiveness of feedback goes beyond the content or nature (good/bad feedback) of the feedback. This study looks at two feedback sources: humans and artificial intelligence (AI) using students as the population. Humans have been the traditional source in feedback provision. Thus, in a team setting peers provide feedback on their peers’ performances. Unprecedented technological advancements have seen the improvement of AI capabilities to being able to give feedback. This has made AI a feedback source. Following these developments, this research assessed the way in which humans and AI provide feedback and the way in which students react to feedback provided by humans and AI. The research used chatbot AI, a Skills Simulator Assessment, launched by Kotlyar (2018). Students registered for Management One at Rhodes University in 2021 were the population for this research. The research was comprised of two phases where in phase one they were assessed by the Skill Simulator Assessment and in phase two they were assessed by their peers. This research found that students are not averse to feedback from AI, although they prefer peer feedback. It was further found that peer feedback tends to be tainted by lenience, while AI is not affected by lenience. This finding marked a significant development of AI in feedback provision. , Thesis (MCom) -- Faculty of Commerce, Management, 2022
- Full Text:
- Date Issued: 2022-10-14
A model for recommending related research papers: A natural language processing approach
- Authors: Van Heerden, Juandre Anton
- Date: 2022-04
- Subjects: Machine learning , Artificial intelligence
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/55668 , vital:53405
- Description: The volume of information generated lately has led to information overload, which has impacted researchers’ decision-making capabilities. Researchers have access to a variety of digital libraries to retrieve information. Digital libraries often offer access to a number of journal articles and books. Although digital libraries have search mechanisms it still takes much time to find related research papers. The main aim of this study was to develop a model that uses machine learning techniques to recommend related research papers. The conceptual model was informed by literature on recommender systems in other domains. Furthermore, a literature survey on machine learning techniques helped to identify candidate techniques that could be used. The model comprises four phases. These phases are completed twice, the first time for learning from the data and the second time when a recommendation is sought. The four phases are: (1) identify and remove stopwords, (2) stemming the data, (3) identify the topics for the model, and (4) measuring similarity between documents. The model is implemented and demonstrated using a prototype to recommend research papers using a natural language processing approach. The prototype underwent three iterations. The first iteration focused on understanding the problem domain by exploring how recommender systems and related techniques work. The second iteration focused on pre-processing techniques, topic modeling and similarity measures of two probability distributions. The third iteration focused on refining the prototype, and documenting the lessons learned throughout the process. Practical lessons were learned while finalising the model and constructing the prototype. These practical lessons should help to identify opportunities for future research. , Thesis (MIT) -- Faculty of Engineering the Built Environment and Technology, Information Technology, 2022
- Full Text:
- Date Issued: 2022-04
- Authors: Van Heerden, Juandre Anton
- Date: 2022-04
- Subjects: Machine learning , Artificial intelligence
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/55668 , vital:53405
- Description: The volume of information generated lately has led to information overload, which has impacted researchers’ decision-making capabilities. Researchers have access to a variety of digital libraries to retrieve information. Digital libraries often offer access to a number of journal articles and books. Although digital libraries have search mechanisms it still takes much time to find related research papers. The main aim of this study was to develop a model that uses machine learning techniques to recommend related research papers. The conceptual model was informed by literature on recommender systems in other domains. Furthermore, a literature survey on machine learning techniques helped to identify candidate techniques that could be used. The model comprises four phases. These phases are completed twice, the first time for learning from the data and the second time when a recommendation is sought. The four phases are: (1) identify and remove stopwords, (2) stemming the data, (3) identify the topics for the model, and (4) measuring similarity between documents. The model is implemented and demonstrated using a prototype to recommend research papers using a natural language processing approach. The prototype underwent three iterations. The first iteration focused on understanding the problem domain by exploring how recommender systems and related techniques work. The second iteration focused on pre-processing techniques, topic modeling and similarity measures of two probability distributions. The third iteration focused on refining the prototype, and documenting the lessons learned throughout the process. Practical lessons were learned while finalising the model and constructing the prototype. These practical lessons should help to identify opportunities for future research. , Thesis (MIT) -- Faculty of Engineering the Built Environment and Technology, Information Technology, 2022
- Full Text:
- Date Issued: 2022-04
Robot Rights, an approach appealing to Animal Rights Theory
- Authors: Millin, Murray David
- Date: 2021-10-29
- Subjects: Artificial intelligence , Singer, Peter, 1946- , Dennett, D C (Daniel Clement) , Animal rights , Ethics , Asimov, Isaac, 1920-1992 Criticism and interpretation , Asimov, Isaac, 1920-1992. Bicentennial man , Asimov, Isaac, 1920-1992. Sally , Preference utilitarianism
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/191854 , vital:45172
- Description: This thesis proposes that Peter Singer’s theory of preference utilitarianism, which is designed to be universally applicable to humans and animals, can be applied to robots of a particular kind — such as those seen in Isaac Asimov’s work. I shall do this by using Singer’s conception of interests as a framework, and appealing to Daniel Dennett’s intentional stance to deal with methodological issues about other minds. I shall then apply those theories to Isaac Asimov’s Sally and The Bicentennial Man. These two narratives show the importance of the intentional stance as an ethical tool and provide an example of how we might talk about the interests of a robot. Sally’s behaviour and ethical status is examined according to how she is perceived, and so I shall investigate how various persons engage with her and why they do so in those manners. This narrative demonstrates the value of the intentional and design stance as methods to approach other minds problems with regards to ethical status. The Bicentennial Man’s Andrew allows us to look for interests in a more concrete way. I look to see how he situates himself in his world, as well as investigate how and why he makes the demand to be morally considerable. This will be done by examining his creativity, personal development and drive for mortality throughout the narrative. , Thesis (MA) -- Faculty of Humanities, Philosophy, 2021
- Full Text:
- Date Issued: 2021-10-29
- Authors: Millin, Murray David
- Date: 2021-10-29
- Subjects: Artificial intelligence , Singer, Peter, 1946- , Dennett, D C (Daniel Clement) , Animal rights , Ethics , Asimov, Isaac, 1920-1992 Criticism and interpretation , Asimov, Isaac, 1920-1992. Bicentennial man , Asimov, Isaac, 1920-1992. Sally , Preference utilitarianism
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10962/191854 , vital:45172
- Description: This thesis proposes that Peter Singer’s theory of preference utilitarianism, which is designed to be universally applicable to humans and animals, can be applied to robots of a particular kind — such as those seen in Isaac Asimov’s work. I shall do this by using Singer’s conception of interests as a framework, and appealing to Daniel Dennett’s intentional stance to deal with methodological issues about other minds. I shall then apply those theories to Isaac Asimov’s Sally and The Bicentennial Man. These two narratives show the importance of the intentional stance as an ethical tool and provide an example of how we might talk about the interests of a robot. Sally’s behaviour and ethical status is examined according to how she is perceived, and so I shall investigate how various persons engage with her and why they do so in those manners. This narrative demonstrates the value of the intentional and design stance as methods to approach other minds problems with regards to ethical status. The Bicentennial Man’s Andrew allows us to look for interests in a more concrete way. I look to see how he situates himself in his world, as well as investigate how and why he makes the demand to be morally considerable. This will be done by examining his creativity, personal development and drive for mortality throughout the narrative. , Thesis (MA) -- Faculty of Humanities, Philosophy, 2021
- Full Text:
- Date Issued: 2021-10-29
A smart home environment simulation tool to support the recognition of activities of daily living
- Authors: Ho, Brandon
- Date: 2020
- Subjects: Artificial intelligence , Internet of things Home automation
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/49334 , vital:41622
- Description: The prevalence of internet of things technologies and internet-connected devices enables the potential of introducing intelligence to a wide range of applications and fields. Smart homes are popular application of internet of things. Smart homes refer to domestic environments that can monitor their own state and the state of their inhabitants. Smart homes are identified as a promising solution for assisting inhabitants in completing daily activities and improving quality of life for inhabitants. This dissertation discusses the design and implementation of smart home simulation tool prototype, called smart environment stimulation (SESim). SESim is designed to conduct smart home simulation and generate synthetic sensor datasets which describe activity performances. This dissertation also discusses the evaluation of SESim, which focused on validating the utility of conducting smart home simulations and generating sensor datasets.
- Full Text: false
- Date Issued: 2020
- Authors: Ho, Brandon
- Date: 2020
- Subjects: Artificial intelligence , Internet of things Home automation
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/49334 , vital:41622
- Description: The prevalence of internet of things technologies and internet-connected devices enables the potential of introducing intelligence to a wide range of applications and fields. Smart homes are popular application of internet of things. Smart homes refer to domestic environments that can monitor their own state and the state of their inhabitants. Smart homes are identified as a promising solution for assisting inhabitants in completing daily activities and improving quality of life for inhabitants. This dissertation discusses the design and implementation of smart home simulation tool prototype, called smart environment stimulation (SESim). SESim is designed to conduct smart home simulation and generate synthetic sensor datasets which describe activity performances. This dissertation also discusses the evaluation of SESim, which focused on validating the utility of conducting smart home simulations and generating sensor datasets.
- Full Text: false
- Date Issued: 2020
The fourth industrial revolution: assessing the intelligences of engineers in the South African automotive industry
- Authors: Kapp, Jaco
- Date: 2018
- Subjects: Technological innovations -- Economic aspects -- South Africa , Artificial intelligence , Emotional intelligence , Automobile industry and trade -- Economic aspects -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/22288 , vital:29937
- Description: The Fourth Industrial Revolution (4IR) is a new phenomenon that will impact human society drastically. It is complex, highly dynamic and constantly evolving at an everincreasing pace. To date the majority of research on the topic of the 4IR is focused on technological and scientific topics, with little to no work done on the human behavioural aspects such as intelligence. At the commencement of this paper only one other author published papers on the intelligences that are required to cope with the disruption associated with the 4IR. This paper is therefore the first known study paper which aims to determine the level of physical-, contextual-, emotional- and inspired intelligence of engineers in the South African automotive industry. Two comprehensive literature reviews were performed in this study. The first literature review aimed to create the context of this study by describing the historical significance, impact, drivers, critical emerging technologies and likely manufacturing scenarios of the 4IR. The second literature review investigated the theories of intelligence including the single factor approach as well as the theory of multiple intelligences. Additionally, the 4IR intelligence proposition is described and the application thereof in this study justified. A mixed method empirical study, consisting of 101 respondents, was conducted. Descriptive statistics were used to comprehensively describe the level of awareness, timeframe, emerging technologies and likely manufacturing scenarios. Furthermore, the thematic analysis of open-ended responses was used to identify the potential positive and negative implications associated with the 4IR. After the level and importance of the four intelligence components were established, inferential statistical tests were performed to establish the relationship between the four intelligences as well as to identify any deviance in the responses based on demographic variables. The study concludes by making various managerial recommendations that could be applied by managers in the automotive sector in order for their companies to survive and prosper in the disruption to be caused by the 4IR. As it is clear that the 4IR will have an impact upon the South African automotive industry in the very near future, it is of the utmost importance that this topic be included into the organisations’ strategic dialogues as a matter of urgency. This study found the level of perceived intelligence of South African engineers to be high. Additionally, this cohort indicated a heightened level of awareness and in-depth knowledge surrounding the 4IR. Therefore, this study recommends that organisations leverage these strategic resources to their fullest benefit. Joint 4IR task teams should be setup comprising of engineers and individuals from other departments such as Information Technology (IT) and Human Resources (HR). These teams should spearhead pilot projects in line with the advances associated with the 4IR. Management should further take into cognisance, monitor and pro-actively investigate the possible behavioural and psychological implications associated with the increased use of technology. It is therefore recommended that regular surveys, open dialogues and possible voluntary psychometric evaluations be conducted wherever these new technologies are piloted. This study also found that the 4IR might lead to the loss of unskilled jobs which would have a broader socio-economic impact. In sharp contrast to popular belief, humans will still play an important role in the 4IR and as such organisations should, therefore, openly commit to educating and upskilling their lower skilled employees in line with the needs of the 4IR as this would be mutually beneficial for the organisation and employees. This would demonstrate the companies’ long-term commitment to their lesser skilled employees and reassure them of their job security, thereby reducing the risk of job losses and potential industrial action.
- Full Text:
- Date Issued: 2018
- Authors: Kapp, Jaco
- Date: 2018
- Subjects: Technological innovations -- Economic aspects -- South Africa , Artificial intelligence , Emotional intelligence , Automobile industry and trade -- Economic aspects -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/22288 , vital:29937
- Description: The Fourth Industrial Revolution (4IR) is a new phenomenon that will impact human society drastically. It is complex, highly dynamic and constantly evolving at an everincreasing pace. To date the majority of research on the topic of the 4IR is focused on technological and scientific topics, with little to no work done on the human behavioural aspects such as intelligence. At the commencement of this paper only one other author published papers on the intelligences that are required to cope with the disruption associated with the 4IR. This paper is therefore the first known study paper which aims to determine the level of physical-, contextual-, emotional- and inspired intelligence of engineers in the South African automotive industry. Two comprehensive literature reviews were performed in this study. The first literature review aimed to create the context of this study by describing the historical significance, impact, drivers, critical emerging technologies and likely manufacturing scenarios of the 4IR. The second literature review investigated the theories of intelligence including the single factor approach as well as the theory of multiple intelligences. Additionally, the 4IR intelligence proposition is described and the application thereof in this study justified. A mixed method empirical study, consisting of 101 respondents, was conducted. Descriptive statistics were used to comprehensively describe the level of awareness, timeframe, emerging technologies and likely manufacturing scenarios. Furthermore, the thematic analysis of open-ended responses was used to identify the potential positive and negative implications associated with the 4IR. After the level and importance of the four intelligence components were established, inferential statistical tests were performed to establish the relationship between the four intelligences as well as to identify any deviance in the responses based on demographic variables. The study concludes by making various managerial recommendations that could be applied by managers in the automotive sector in order for their companies to survive and prosper in the disruption to be caused by the 4IR. As it is clear that the 4IR will have an impact upon the South African automotive industry in the very near future, it is of the utmost importance that this topic be included into the organisations’ strategic dialogues as a matter of urgency. This study found the level of perceived intelligence of South African engineers to be high. Additionally, this cohort indicated a heightened level of awareness and in-depth knowledge surrounding the 4IR. Therefore, this study recommends that organisations leverage these strategic resources to their fullest benefit. Joint 4IR task teams should be setup comprising of engineers and individuals from other departments such as Information Technology (IT) and Human Resources (HR). These teams should spearhead pilot projects in line with the advances associated with the 4IR. Management should further take into cognisance, monitor and pro-actively investigate the possible behavioural and psychological implications associated with the increased use of technology. It is therefore recommended that regular surveys, open dialogues and possible voluntary psychometric evaluations be conducted wherever these new technologies are piloted. This study also found that the 4IR might lead to the loss of unskilled jobs which would have a broader socio-economic impact. In sharp contrast to popular belief, humans will still play an important role in the 4IR and as such organisations should, therefore, openly commit to educating and upskilling their lower skilled employees in line with the needs of the 4IR as this would be mutually beneficial for the organisation and employees. This would demonstrate the companies’ long-term commitment to their lesser skilled employees and reassure them of their job security, thereby reducing the risk of job losses and potential industrial action.
- Full Text:
- Date Issued: 2018
A genetic algorithm to obtain optimum parameters for a halcon vision system
- Authors: Fulton, Dale Meares
- Date: 2017
- Subjects: Genetic algorithms , Artificial intelligence , Automation , User interfaces (Computer systems)
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/29751 , vital:30774
- Description: This report discusses the optimisation of a HALCON vision system using artificial intelligence, specifically a genetic algorithm. Within industrial applications, vision systems are often used for automated part inspection and quality control. A number of vision system parameters are to be selected when setting up a vision system. Since each vision system application differs, there is no specific set of optimal parameters. Parameters are selected during installation using a trial and error method. As a result, there is a need for an automated process for obtaining suitable vision system parameters. Within this report, research was conducted on both vision systems, genetic algorithms and integration of the two. A physical vision system was designed and developed utilising HALCON vision software. A genetic algorithm was then developed and integrated with the vision system. After integration, experimental testing was performed on the genetic algorithm in order to determine the ideal genetic algorithm control parameters which yield ideal genetic algorithm performance. Once the ideal genetic algorithm was obtained, the genetic algorithm was applied to the vision system in order to obtain optimal vision system parameters. Results showed that applying the genetic algorithm to the vision system optimised the vision system performance well.
- Full Text:
- Date Issued: 2017
- Authors: Fulton, Dale Meares
- Date: 2017
- Subjects: Genetic algorithms , Artificial intelligence , Automation , User interfaces (Computer systems)
- Language: English
- Type: Thesis , Masters , MEng
- Identifier: http://hdl.handle.net/10948/29751 , vital:30774
- Description: This report discusses the optimisation of a HALCON vision system using artificial intelligence, specifically a genetic algorithm. Within industrial applications, vision systems are often used for automated part inspection and quality control. A number of vision system parameters are to be selected when setting up a vision system. Since each vision system application differs, there is no specific set of optimal parameters. Parameters are selected during installation using a trial and error method. As a result, there is a need for an automated process for obtaining suitable vision system parameters. Within this report, research was conducted on both vision systems, genetic algorithms and integration of the two. A physical vision system was designed and developed utilising HALCON vision software. A genetic algorithm was then developed and integrated with the vision system. After integration, experimental testing was performed on the genetic algorithm in order to determine the ideal genetic algorithm control parameters which yield ideal genetic algorithm performance. Once the ideal genetic algorithm was obtained, the genetic algorithm was applied to the vision system in order to obtain optimal vision system parameters. Results showed that applying the genetic algorithm to the vision system optimised the vision system performance well.
- Full Text:
- Date Issued: 2017
A framework for the development of a personal information security agent
- Authors: Stieger, Ewald Andreas
- Date: 2011
- Subjects: Computer networks -- Security measures , Information storage and retrieval systems , Artificial intelligence
- Language: English
- Type: Thesis , Masters , MTech
- Identifier: vital:9803 , http://hdl.handle.net/10948/d1012326 , Computer networks -- Security measures , Information storage and retrieval systems , Artificial intelligence
- Description: Nowadays information is everywhere. Organisations process, store and create information in unprecedented quantities to support their business processes. Similarly, people use, share and synthesise information to accomplish their daily tasks. Indeed, information and information technology are the core of business activities, and a part of daily life. Information has become a crucial resource in today‘s information age and any corruption, destruction or leakage of information can have a serious negative impact on an organisation. Thus, information should be kept safe. This requires the successful implementation of information security, which ensures that information assets are only used, modified and accessed by authorised people. Information security faces many challenges; and organisations still have not successfully addressed them. One of the main challenges is the human element. Information security depends to a large extent on people and their ability to follow and apply sound security practices. Unfortunately, people are often not very security-conscious in their behaviour; and this is the cause of many security breaches. There are a variety of reasons for this such as a lack of knowledge and a negative attitude to security. Many organisations are aware of this; and they attempt to remedy the situation by means of information security awareness programs. These programs aim to educate, train and increase the security awareness of individuals. However, information security awareness programs are not always successful. They are not a once-off remedy that can quickly cure information security. The programs need to be implemented effectively, and they require an ongoing effort. Unfortunately, this is where many organisations fail. Furthermore, changing individuals‘ security behaviour is difficult due to the complexity of factors that influence everyday behaviour. In view of the above, this research project proposes an alternative approach in the form of a personal information security agent. The goal of this agent is to influence individuals to adopt more secure behaviour. There are a variety of factors that need to be considered, in order to achieve this goal, and to positively influence security behaviour. Consequently, this research establishes criteria and principles for such an agent, based on the theory and practice. From a theoretical point of view, a variety of factors that influence human behaviour such as self-efficacy and normative beliefs were investigated. Furthermore, the field of persuasive technology has provided for strategies that can be used by technology to influence individuals. On the practical side, a prototype of a personal information security agent was created and evaluated through a technical software review process. The evaluation of the prototype showed that the theoretical criteria have merit but their effectiveness is largely dependent on how they are implemented. The criteria were thus revised, based on the practical findings. The findings also suggest that a personal information security agent, based on the criteria, may be able to positively influence individuals to be more secure in their behaviour. The insights gained by the research are presented in the form of a framework that makes both theoretical and practical recommendations for developing a personal information security agent. One may, consequently, conclude that the purpose of this research is to provide a foundation for the development of a personal information security agent to positively influence computer users to be more security-conscious in their behavior.
- Full Text:
- Date Issued: 2011
- Authors: Stieger, Ewald Andreas
- Date: 2011
- Subjects: Computer networks -- Security measures , Information storage and retrieval systems , Artificial intelligence
- Language: English
- Type: Thesis , Masters , MTech
- Identifier: vital:9803 , http://hdl.handle.net/10948/d1012326 , Computer networks -- Security measures , Information storage and retrieval systems , Artificial intelligence
- Description: Nowadays information is everywhere. Organisations process, store and create information in unprecedented quantities to support their business processes. Similarly, people use, share and synthesise information to accomplish their daily tasks. Indeed, information and information technology are the core of business activities, and a part of daily life. Information has become a crucial resource in today‘s information age and any corruption, destruction or leakage of information can have a serious negative impact on an organisation. Thus, information should be kept safe. This requires the successful implementation of information security, which ensures that information assets are only used, modified and accessed by authorised people. Information security faces many challenges; and organisations still have not successfully addressed them. One of the main challenges is the human element. Information security depends to a large extent on people and their ability to follow and apply sound security practices. Unfortunately, people are often not very security-conscious in their behaviour; and this is the cause of many security breaches. There are a variety of reasons for this such as a lack of knowledge and a negative attitude to security. Many organisations are aware of this; and they attempt to remedy the situation by means of information security awareness programs. These programs aim to educate, train and increase the security awareness of individuals. However, information security awareness programs are not always successful. They are not a once-off remedy that can quickly cure information security. The programs need to be implemented effectively, and they require an ongoing effort. Unfortunately, this is where many organisations fail. Furthermore, changing individuals‘ security behaviour is difficult due to the complexity of factors that influence everyday behaviour. In view of the above, this research project proposes an alternative approach in the form of a personal information security agent. The goal of this agent is to influence individuals to adopt more secure behaviour. There are a variety of factors that need to be considered, in order to achieve this goal, and to positively influence security behaviour. Consequently, this research establishes criteria and principles for such an agent, based on the theory and practice. From a theoretical point of view, a variety of factors that influence human behaviour such as self-efficacy and normative beliefs were investigated. Furthermore, the field of persuasive technology has provided for strategies that can be used by technology to influence individuals. On the practical side, a prototype of a personal information security agent was created and evaluated through a technical software review process. The evaluation of the prototype showed that the theoretical criteria have merit but their effectiveness is largely dependent on how they are implemented. The criteria were thus revised, based on the practical findings. The findings also suggest that a personal information security agent, based on the criteria, may be able to positively influence individuals to be more secure in their behaviour. The insights gained by the research are presented in the form of a framework that makes both theoretical and practical recommendations for developing a personal information security agent. One may, consequently, conclude that the purpose of this research is to provide a foundation for the development of a personal information security agent to positively influence computer users to be more security-conscious in their behavior.
- Full Text:
- Date Issued: 2011
OVR : a novel architecture for voice-based applications
- Authors: Maema, Mathe
- Date: 2011 , 2011-04-01
- Subjects: Telephone systems -- Research , User interfaces (Computer systems) -- Research , Expert systems (Computer science) , Artificial intelligence , VoiceXML (Document markup language) , Application software -- Development
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4671 , http://hdl.handle.net/10962/d1006694 , Telephone systems -- Research , User interfaces (Computer systems) -- Research , Expert systems (Computer science) , Artificial intelligence , VoiceXML (Document markup language) , Application software -- Development
- Description: Despite the inherent limitation of accessing information serially, voice applications are increasingly growing in popularity as computing technologies advance. This is a positive development, because voice communication offers a number of benefits over other forms of communication. For example, voice may be better for delivering services to users whose eyes and hands may be engaged in other activities (e.g. driving) or to semi-literate or illiterate users. This thesis proposes a knowledge based architecture for building voice applications to help reduce the limitations of serial access to information. The proposed architecture, called OVR (Ontologies, VoiceXML and Reasoners), uses a rich backend that represents knowledge via ontologies and utilises reasoning engines to reason with it, in order to generate intelligent behaviour. Ontologies were chosen over other knowledge representation formalisms because of their expressivity and executable format, and because current trends suggest a general shift towards the use of ontologies in many systems used for information storing and sharing. For the frontend, this architecture uses VoiceXML, the emerging, and de facto standard for voice automated applications. A functional prototype was built for an initial validation of the architecture. The system is a simple voice application to help locate information about service providers that offer HIV (Human Immunodeficiency Virus) testing. We called this implementation HTLS (HIV Testing Locator System). The functional prototype was implemented using a number of technologies. OWL API, a Java interface designed to facilitate manipulation of ontologies authored in OWL was used to build a customised query interface for HTLS. Pellet reasoner was used for supporting queries to the knowledge base and Drools (JBoss rule engine) was used for processing dialog rules. VXI was used as the VoiceXML browser and an experimental softswitch called iLanga as the bridge to the telephony system. (At the heart of iLanga is Asterisk, a well known PBX-in-a-box.) HTLS behaved properly under system testing, providing the sought initial validation of OVR. , LaTeX with hyperref package
- Full Text:
- Date Issued: 2011
- Authors: Maema, Mathe
- Date: 2011 , 2011-04-01
- Subjects: Telephone systems -- Research , User interfaces (Computer systems) -- Research , Expert systems (Computer science) , Artificial intelligence , VoiceXML (Document markup language) , Application software -- Development
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4671 , http://hdl.handle.net/10962/d1006694 , Telephone systems -- Research , User interfaces (Computer systems) -- Research , Expert systems (Computer science) , Artificial intelligence , VoiceXML (Document markup language) , Application software -- Development
- Description: Despite the inherent limitation of accessing information serially, voice applications are increasingly growing in popularity as computing technologies advance. This is a positive development, because voice communication offers a number of benefits over other forms of communication. For example, voice may be better for delivering services to users whose eyes and hands may be engaged in other activities (e.g. driving) or to semi-literate or illiterate users. This thesis proposes a knowledge based architecture for building voice applications to help reduce the limitations of serial access to information. The proposed architecture, called OVR (Ontologies, VoiceXML and Reasoners), uses a rich backend that represents knowledge via ontologies and utilises reasoning engines to reason with it, in order to generate intelligent behaviour. Ontologies were chosen over other knowledge representation formalisms because of their expressivity and executable format, and because current trends suggest a general shift towards the use of ontologies in many systems used for information storing and sharing. For the frontend, this architecture uses VoiceXML, the emerging, and de facto standard for voice automated applications. A functional prototype was built for an initial validation of the architecture. The system is a simple voice application to help locate information about service providers that offer HIV (Human Immunodeficiency Virus) testing. We called this implementation HTLS (HIV Testing Locator System). The functional prototype was implemented using a number of technologies. OWL API, a Java interface designed to facilitate manipulation of ontologies authored in OWL was used to build a customised query interface for HTLS. Pellet reasoner was used for supporting queries to the knowledge base and Drools (JBoss rule engine) was used for processing dialog rules. VXI was used as the VoiceXML browser and an experimental softswitch called iLanga as the bridge to the telephony system. (At the heart of iLanga is Asterisk, a well known PBX-in-a-box.) HTLS behaved properly under system testing, providing the sought initial validation of OVR. , LaTeX with hyperref package
- Full Text:
- Date Issued: 2011
Predictability of Geomagnetically Induced Currents using neural networks
- Authors: Lotz, Stefanus Ignatius
- Date: 2009
- Subjects: Advanced Composition Explorer (Artificial satellite) , Geomagnetism , Electromagnetic induction , Neural networks (Computer science) , Artificial intelligence
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5483 , http://hdl.handle.net/10962/d1005269 , Advanced Composition Explorer (Artificial satellite) , Geomagnetism , Electromagnetic induction , Neural networks (Computer science) , Artificial intelligence
- Description: It is a well documented fact that Geomagnetically Induced Currents (GIC’s) poses a significant threat to ground-based electric conductor networks like oil pipelines, railways and powerline networks. A study is undertaken to determine the feasibility of using artificial neural network models to predict GIC occurrence in the Southern African power grid. The magnitude of an induced current at a specific location on the Earth’s surface is directly related to the temporal derivative of the geomagnetic field (specifically its horizontal components) at that point. Hence, the focus of the problem is on the prediction of the temporal variations in the horizontal geomagnetic field (@Bx/@t and @By/@t). Artificial neural networks are used to predict @Bx/@t and @By/@t measured at Hermanus, South Africa (34.27◦ S, 19.12◦ E) with a 30 minute prediction lead time. As input parameters to the neural networks, insitu solar wind measurements made by the Advanced Composition Explorer (ACE) satellite are used. The results presented here compare well with similar models developed at high-latitude locations (e.g. Sweden, Finland, Canada) where extensive GIC research has been undertaken. It is concluded that it would indeed be feasible to use a neural network model to predict GIC occurrence in the Southern African power grid, provided that GIC measurements, powerline configuration and network parameters are made available.
- Full Text:
- Date Issued: 2009
- Authors: Lotz, Stefanus Ignatius
- Date: 2009
- Subjects: Advanced Composition Explorer (Artificial satellite) , Geomagnetism , Electromagnetic induction , Neural networks (Computer science) , Artificial intelligence
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5483 , http://hdl.handle.net/10962/d1005269 , Advanced Composition Explorer (Artificial satellite) , Geomagnetism , Electromagnetic induction , Neural networks (Computer science) , Artificial intelligence
- Description: It is a well documented fact that Geomagnetically Induced Currents (GIC’s) poses a significant threat to ground-based electric conductor networks like oil pipelines, railways and powerline networks. A study is undertaken to determine the feasibility of using artificial neural network models to predict GIC occurrence in the Southern African power grid. The magnitude of an induced current at a specific location on the Earth’s surface is directly related to the temporal derivative of the geomagnetic field (specifically its horizontal components) at that point. Hence, the focus of the problem is on the prediction of the temporal variations in the horizontal geomagnetic field (@Bx/@t and @By/@t). Artificial neural networks are used to predict @Bx/@t and @By/@t measured at Hermanus, South Africa (34.27◦ S, 19.12◦ E) with a 30 minute prediction lead time. As input parameters to the neural networks, insitu solar wind measurements made by the Advanced Composition Explorer (ACE) satellite are used. The results presented here compare well with similar models developed at high-latitude locations (e.g. Sweden, Finland, Canada) where extensive GIC research has been undertaken. It is concluded that it would indeed be feasible to use a neural network model to predict GIC occurrence in the Southern African power grid, provided that GIC measurements, powerline configuration and network parameters are made available.
- Full Text:
- Date Issued: 2009
An analysis of neural networks and time series techniques for demand forecasting
- Authors: Winn, David
- Date: 2007
- Subjects: Time-series analysis , Neural networks (Computer science) , Artificial intelligence , Marketing -- Management , Marketing -- Data processing , Marketing -- Statistical methods , Consumer behaviour
- Language: English
- Type: Thesis , Masters , MCom
- Identifier: vital:5572 , http://hdl.handle.net/10962/d1004362 , Time-series analysis , Neural networks (Computer science) , Artificial intelligence , Marketing -- Management , Marketing -- Data processing , Marketing -- Statistical methods , Consumer behaviour
- Description: This research examines the plausibility of developing demand forecasting techniques which are consistently and accurately able to predict demand. Time Series Techniques and Artificial Neural Networks are both investigated. Deodorant sales in South Africa are specifically studied in this thesis. Marketing techniques which are used to influence consumer buyer behaviour are considered, and these factors are integrated into the forecasting models wherever possible. The results of this research suggest that Artificial Neural Networks can be developed which consistently outperform industry forecasting targets as well as Time Series forecasts, suggesting that producers could reduce costs by adopting this more effective method.
- Full Text:
- Date Issued: 2007
- Authors: Winn, David
- Date: 2007
- Subjects: Time-series analysis , Neural networks (Computer science) , Artificial intelligence , Marketing -- Management , Marketing -- Data processing , Marketing -- Statistical methods , Consumer behaviour
- Language: English
- Type: Thesis , Masters , MCom
- Identifier: vital:5572 , http://hdl.handle.net/10962/d1004362 , Time-series analysis , Neural networks (Computer science) , Artificial intelligence , Marketing -- Management , Marketing -- Data processing , Marketing -- Statistical methods , Consumer behaviour
- Description: This research examines the plausibility of developing demand forecasting techniques which are consistently and accurately able to predict demand. Time Series Techniques and Artificial Neural Networks are both investigated. Deodorant sales in South Africa are specifically studied in this thesis. Marketing techniques which are used to influence consumer buyer behaviour are considered, and these factors are integrated into the forecasting models wherever possible. The results of this research suggest that Artificial Neural Networks can be developed which consistently outperform industry forecasting targets as well as Time Series forecasts, suggesting that producers could reduce costs by adopting this more effective method.
- Full Text:
- Date Issued: 2007
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