An evaluation of the factors affecting student success at a South African higher education institution : implications for management
- Authors: Watkiss, Sheralyn Ann
- Date: 2011
- Subjects: Education, Higher -- South Africa , College dropout -- Prevention , Management -- Education (Higher) -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: vital:8817 , http://hdl.handle.net/10948/d1018826
- Description: The context of this study centres on Higher Education in South Africa, the role that this sector plays in terms of economic development and the implications that face Institutional management in retaining students in the Higher Education system. Central to this study is the notion that student development theory can be used as a basis towards understanding the customers of Higher Education, how to better serve the customers needs and finally, retain students in the system through more effective management practices. The education sector is growing at an increasingly rapid rate as a result of strategic goals of countries and organisations such as the United Nations promoting the notion of education for all people (Altbach, Reisberg & Rumbley, 2009). The aim of the strategic goals adopted by developing countries in particular is to enhance the human capital or skills and knowledge of its people since education is a known contributor towards economic, social and political development. Higher Education in particular is known to contribute towards the human capital and economic development of a country. The Higher Education sector in South Africa for instance contributes approximately 1.5 percent to the country‟s gross domestic product (GDP), significantly higher than other industry sectors (apart from gold and agriculture) in the country (van Heerden, Bohlmann, Giesecke, Makochekanwa, & Roos, 2007). Figure 1.1 provides a context of the relevant importance of the higher education sector towards economic growth.
- Full Text:
- Date Issued: 2011
- Authors: Watkiss, Sheralyn Ann
- Date: 2011
- Subjects: Education, Higher -- South Africa , College dropout -- Prevention , Management -- Education (Higher) -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: vital:8817 , http://hdl.handle.net/10948/d1018826
- Description: The context of this study centres on Higher Education in South Africa, the role that this sector plays in terms of economic development and the implications that face Institutional management in retaining students in the Higher Education system. Central to this study is the notion that student development theory can be used as a basis towards understanding the customers of Higher Education, how to better serve the customers needs and finally, retain students in the system through more effective management practices. The education sector is growing at an increasingly rapid rate as a result of strategic goals of countries and organisations such as the United Nations promoting the notion of education for all people (Altbach, Reisberg & Rumbley, 2009). The aim of the strategic goals adopted by developing countries in particular is to enhance the human capital or skills and knowledge of its people since education is a known contributor towards economic, social and political development. Higher Education in particular is known to contribute towards the human capital and economic development of a country. The Higher Education sector in South Africa for instance contributes approximately 1.5 percent to the country‟s gross domestic product (GDP), significantly higher than other industry sectors (apart from gold and agriculture) in the country (van Heerden, Bohlmann, Giesecke, Makochekanwa, & Roos, 2007). Figure 1.1 provides a context of the relevant importance of the higher education sector towards economic growth.
- Full Text:
- Date Issued: 2011
The process of relational play therapy between a trainee therapist and a maltreated child : a case study
- Authors: Watkiss, Sheralyn Ann
- Date: 2014
- Subjects: Play therapy , Therapist and patient , Abused children
- Language: English
- Type: Thesis , Masters , MA
- Identifier: vital:9970 , http://hdl.handle.net/10948/d1020977
- Description: Research in the field of attachment theory and object relations theory has indicated that early attachments between a child and his or her primary caregiver have significant implications for the development of that child. Early relationships begin to shape the child’s sense of self and other and healthy relationships lead to secure attachments. However, children who encounter early maltreatment or a disruption in caregivers are particularly vulnerable to developing insecure attachments and a disrupted sense of self and other, which has consequences for their subsequent psychological development. In the South African context, increasing numbers of children are being orphaned or placed in formal foster care with many children at risk for insecure attachments. This has implications for therapeutic work with an increased need to promote secure attachment relationships and a stable sense of self and other. The current case study aimed to describe the relational experience of play therapy that took place between a maltreated five year old female child and a female trainee therapist with this purpose in mind. The therapeutic process was embedded within a relational therapy framework which included object relations and attachment theory. The researcher made use of a qualitative descriptive dialogic research approach to conduct the research. The data were analysed using content analysis, where the play therapy sessions were analysed according to concepts relating to Fairbairn’s (1963) object relations theory as well as Winnicott’s (1965) object relations theory. Prominent themes that emerged included the role of the holding environment, splitting of good and bad objects and the presence of a false self versus a true self. In addition, the conflicting presence of two repressed ego structures, namely the libidinal and antilibidinal ego structure were noted throughout the therapeutic process.
- Full Text:
- Date Issued: 2014
- Authors: Watkiss, Sheralyn Ann
- Date: 2014
- Subjects: Play therapy , Therapist and patient , Abused children
- Language: English
- Type: Thesis , Masters , MA
- Identifier: vital:9970 , http://hdl.handle.net/10948/d1020977
- Description: Research in the field of attachment theory and object relations theory has indicated that early attachments between a child and his or her primary caregiver have significant implications for the development of that child. Early relationships begin to shape the child’s sense of self and other and healthy relationships lead to secure attachments. However, children who encounter early maltreatment or a disruption in caregivers are particularly vulnerable to developing insecure attachments and a disrupted sense of self and other, which has consequences for their subsequent psychological development. In the South African context, increasing numbers of children are being orphaned or placed in formal foster care with many children at risk for insecure attachments. This has implications for therapeutic work with an increased need to promote secure attachment relationships and a stable sense of self and other. The current case study aimed to describe the relational experience of play therapy that took place between a maltreated five year old female child and a female trainee therapist with this purpose in mind. The therapeutic process was embedded within a relational therapy framework which included object relations and attachment theory. The researcher made use of a qualitative descriptive dialogic research approach to conduct the research. The data were analysed using content analysis, where the play therapy sessions were analysed according to concepts relating to Fairbairn’s (1963) object relations theory as well as Winnicott’s (1965) object relations theory. Prominent themes that emerged included the role of the holding environment, splitting of good and bad objects and the presence of a false self versus a true self. In addition, the conflicting presence of two repressed ego structures, namely the libidinal and antilibidinal ego structure were noted throughout the therapeutic process.
- Full Text:
- Date Issued: 2014
Rhodes University Graduation Ceremony 1992
- Authors: Rhodes University
- Date: 1992
- Language: English
- Type: text
- Identifier: vital:8126 , http://hdl.handle.net/10962/d1006751
- Description: Rhodes University Graduation Ceremonies Friday, 10 April 1992 at 10:30 a.m. [and] 08:15 p.m. [and] Saturday, 11 April 1992 at 10:30 a.m. in the 1820 Settlers National Monument. , Rhodes University East London Graduation Ceremony Saturday, 16 May 1992 at 11:00 a.m. in the Guild Theatre.
- Full Text:
- Date Issued: 1992
- Authors: Rhodes University
- Date: 1992
- Language: English
- Type: text
- Identifier: vital:8126 , http://hdl.handle.net/10962/d1006751
- Description: Rhodes University Graduation Ceremonies Friday, 10 April 1992 at 10:30 a.m. [and] 08:15 p.m. [and] Saturday, 11 April 1992 at 10:30 a.m. in the 1820 Settlers National Monument. , Rhodes University East London Graduation Ceremony Saturday, 16 May 1992 at 11:00 a.m. in the Guild Theatre.
- Full Text:
- Date Issued: 1992
The generalization ability of artificial neural networks in forecasting TCP/IP network traffic trends
- Authors: Moyo, Vusumuzi
- Date: 2014
- Language: English
- Type: Thesis , Masters , MSc (Computer Science)
- Identifier: vital:11404 , http://hdl.handle.net/10353/d1021127
- Description: Artificial Neural Networks (ANNs) have been used in many fields for a variety of applications, and proved to be reliable. They have proved to be one of the most powerful tools in the domain of forecasting and analysis of various time series. The forecasting of TCP/IP network traffic is an important issue receiving growing attention from the computer networks. By improving upon this task, efficient network traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. The use of ANNs requires some critical decisions on the part of the user. These decisions, which are mainly concerned with the determinations of the components of the network structure and the parameters defined for the learning algorithm, can significantly affect the ability of the ANN to generalize, i.e. to have the outputs of the ANN approximate target values given inputs that are not in the training set. This has an impact on the quality of forecasts produced by the ANN. Although there are some discussions in the literature regarding the issues that affect network generalization ability, there is no standard method or approach that is universally accepted to determine the optimum values of these parameters for a particular problem. This research examined the impact a selection of key design features has on the generalization ability of ANNs. We examined how the size and composition of the network architecture, the size of the training samples, the choice of learning algorithm, the training schedule and the size of the learning rate both individually and collectively affect the ability of an ANN to learn the training data and to generalize well to novel data. To investigate this matter, we empirically conducted several experiments in forecasting a real world TCP/IP network traffic time series and the network performance validated using an independent test set. MATLAB version 7.4.0.287’s Neural Network toolbox version 5.0.2 (R2007a) was used for our experiments. The results are found to be promising in terms of ease of design and use of ANNs. Our results indicate that in contrast to Occam’s razor principle for a single hidden layer an increase in number of hidden neurons produces a corresponding increase in generalization ability of ANNs, however larger networks do not always improve the generalization ability of ANNs even though an increase in number of hidden neurons results in a concomitant rise in network generalization. Also, contradicting commonly accepted guidelines, networks trained with a larger representation of the data, exhibit better generalization than networks trained on smaller representations, even though the larger networks have a significantly greater capacity. Furthermore, the results obtained indicate that the learning rate, momentum, training schedule and choice of learning algorithm have as much a significant effect on ANN generalization ability. A number of conclusions were drawn from the results and later used to generate a comprehensive set of guidelines that will facilitate the process of design and use of ANNs in TCP/IP network traffic forecasting. The main contribution of this research lies in the identification of optimal strategies for the use of ANNs in forecasting TCP/IP network traffic trends. Although the information obtained from the tests carried out in this research is specific to the problem considered, it provides users of back-propagation networks with a valuable guide on the behaviour of networks under a wide range of operating conditions. It is important to note that the guidelines accrued from this research are of an assistive and not necessarily restrictive nature to potential ANN modellers.
- Full Text:
- Date Issued: 2014
- Authors: Moyo, Vusumuzi
- Date: 2014
- Language: English
- Type: Thesis , Masters , MSc (Computer Science)
- Identifier: vital:11404 , http://hdl.handle.net/10353/d1021127
- Description: Artificial Neural Networks (ANNs) have been used in many fields for a variety of applications, and proved to be reliable. They have proved to be one of the most powerful tools in the domain of forecasting and analysis of various time series. The forecasting of TCP/IP network traffic is an important issue receiving growing attention from the computer networks. By improving upon this task, efficient network traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. The use of ANNs requires some critical decisions on the part of the user. These decisions, which are mainly concerned with the determinations of the components of the network structure and the parameters defined for the learning algorithm, can significantly affect the ability of the ANN to generalize, i.e. to have the outputs of the ANN approximate target values given inputs that are not in the training set. This has an impact on the quality of forecasts produced by the ANN. Although there are some discussions in the literature regarding the issues that affect network generalization ability, there is no standard method or approach that is universally accepted to determine the optimum values of these parameters for a particular problem. This research examined the impact a selection of key design features has on the generalization ability of ANNs. We examined how the size and composition of the network architecture, the size of the training samples, the choice of learning algorithm, the training schedule and the size of the learning rate both individually and collectively affect the ability of an ANN to learn the training data and to generalize well to novel data. To investigate this matter, we empirically conducted several experiments in forecasting a real world TCP/IP network traffic time series and the network performance validated using an independent test set. MATLAB version 7.4.0.287’s Neural Network toolbox version 5.0.2 (R2007a) was used for our experiments. The results are found to be promising in terms of ease of design and use of ANNs. Our results indicate that in contrast to Occam’s razor principle for a single hidden layer an increase in number of hidden neurons produces a corresponding increase in generalization ability of ANNs, however larger networks do not always improve the generalization ability of ANNs even though an increase in number of hidden neurons results in a concomitant rise in network generalization. Also, contradicting commonly accepted guidelines, networks trained with a larger representation of the data, exhibit better generalization than networks trained on smaller representations, even though the larger networks have a significantly greater capacity. Furthermore, the results obtained indicate that the learning rate, momentum, training schedule and choice of learning algorithm have as much a significant effect on ANN generalization ability. A number of conclusions were drawn from the results and later used to generate a comprehensive set of guidelines that will facilitate the process of design and use of ANNs in TCP/IP network traffic forecasting. The main contribution of this research lies in the identification of optimal strategies for the use of ANNs in forecasting TCP/IP network traffic trends. Although the information obtained from the tests carried out in this research is specific to the problem considered, it provides users of back-propagation networks with a valuable guide on the behaviour of networks under a wide range of operating conditions. It is important to note that the guidelines accrued from this research are of an assistive and not necessarily restrictive nature to potential ANN modellers.
- Full Text:
- Date Issued: 2014
Updating the ionospheric propagation factor, M(3000)F2, global model using the neural network technique and relevant geophysical input parameters
- Oronsaye, Samuel Iyen Jeffrey
- Authors: Oronsaye, Samuel Iyen Jeffrey
- Date: 2013
- Subjects: Neural networks (Computer science) , Ionospheric radio wave propagation , Ionosphere , Geophysics , Ionosondes
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5434 , http://hdl.handle.net/10962/d1001609 , Neural networks (Computer science) , Ionospheric radio wave propagation , Ionosphere , Geophysics , Ionosondes
- Description: This thesis presents an update to the ionospheric propagation factor, M(3000)F2, global empirical model developed by Oyeyemi et al. (2007) (NNO). An additional aim of this research was to produce the updated model in a form that could be used within the International Reference Ionosphere (IRI) global model without adding to the complexity of the IRI. M(3000)F2 is the highest frequency at which a radio signal can be received over a distance of 3000 km after reflection in the ionosphere. The study employed the artificial neural network (ANN) technique using relevant geophysical input parameters which are known to influence the M(3000)F2 parameter. Ionosonde data from 135 ionospheric stations globally, including a number of equatorial stations, were available for this work. M(3000)F2 hourly values from 1976 to 2008, spanning all periods of low and high solar activity were used for model development and verification. A preliminary investigation was first carried out using a relatively small dataset to determine the appropriate input parameters for global M(3000)F2 parameter modelling. Inputs representing diurnal variation, seasonal variation, solar variation, modified dip latitude, longitude and latitude were found to be the optimum parameters for modelling the diurnal and seasonal variations of the M(3000)F2 parameter both on a temporal and spatial basis. The outcome of the preliminary study was applied to the overall dataset to develop a comprehensive ANN M(3000)F2 model which displays a remarkable improvement over the NNO model as well as the IRI version. The model shows 7.11% and 3.85% improvement over the NNO model as well as 13.04% and 10.05% over the IRI M(3000)F2 model, around high and low solar activity periods respectively. A comparison of the diurnal structure of the ANN and the IRI predicted values reveal that the ANN model is more effective in representing the diurnal structure of the M(3000)F2 values than the IRI M(3000)F2 model. The capability of the ANN model in reproducing the seasonal variation pattern of the M(3000)F2 values at 00h00UT, 06h00UT, 12h00UT, and l8h00UT more appropriately than the IRI version is illustrated in this work. A significant result obtained in this study is the ability of the ANN model in improving the post-sunset predicted values of the M(3000)F2 parameter which is known to be problematic to the IRI M(3000)F2 model in the low-latitude and the equatorial regions. The final M(3000)F2 model provides for an improved equatorial prediction and a simplified input space that allows for easy incorporation into the IRI model.
- Full Text:
- Date Issued: 2013
- Authors: Oronsaye, Samuel Iyen Jeffrey
- Date: 2013
- Subjects: Neural networks (Computer science) , Ionospheric radio wave propagation , Ionosphere , Geophysics , Ionosondes
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5434 , http://hdl.handle.net/10962/d1001609 , Neural networks (Computer science) , Ionospheric radio wave propagation , Ionosphere , Geophysics , Ionosondes
- Description: This thesis presents an update to the ionospheric propagation factor, M(3000)F2, global empirical model developed by Oyeyemi et al. (2007) (NNO). An additional aim of this research was to produce the updated model in a form that could be used within the International Reference Ionosphere (IRI) global model without adding to the complexity of the IRI. M(3000)F2 is the highest frequency at which a radio signal can be received over a distance of 3000 km after reflection in the ionosphere. The study employed the artificial neural network (ANN) technique using relevant geophysical input parameters which are known to influence the M(3000)F2 parameter. Ionosonde data from 135 ionospheric stations globally, including a number of equatorial stations, were available for this work. M(3000)F2 hourly values from 1976 to 2008, spanning all periods of low and high solar activity were used for model development and verification. A preliminary investigation was first carried out using a relatively small dataset to determine the appropriate input parameters for global M(3000)F2 parameter modelling. Inputs representing diurnal variation, seasonal variation, solar variation, modified dip latitude, longitude and latitude were found to be the optimum parameters for modelling the diurnal and seasonal variations of the M(3000)F2 parameter both on a temporal and spatial basis. The outcome of the preliminary study was applied to the overall dataset to develop a comprehensive ANN M(3000)F2 model which displays a remarkable improvement over the NNO model as well as the IRI version. The model shows 7.11% and 3.85% improvement over the NNO model as well as 13.04% and 10.05% over the IRI M(3000)F2 model, around high and low solar activity periods respectively. A comparison of the diurnal structure of the ANN and the IRI predicted values reveal that the ANN model is more effective in representing the diurnal structure of the M(3000)F2 values than the IRI M(3000)F2 model. The capability of the ANN model in reproducing the seasonal variation pattern of the M(3000)F2 values at 00h00UT, 06h00UT, 12h00UT, and l8h00UT more appropriately than the IRI version is illustrated in this work. A significant result obtained in this study is the ability of the ANN model in improving the post-sunset predicted values of the M(3000)F2 parameter which is known to be problematic to the IRI M(3000)F2 model in the low-latitude and the equatorial regions. The final M(3000)F2 model provides for an improved equatorial prediction and a simplified input space that allows for easy incorporation into the IRI model.
- Full Text:
- Date Issued: 2013
On the association of graphs to rings
- Authors: Mzulwini, Sboniso
- Date: 2020
- Subjects: Categories (Mathematics)
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/47060 , vital:39779
- Description: Let R be a commutative ring with nonzero identity, and let Z (R) be the set of its zerodivisors. There exists an association between a simple graph (R) and the set Z(R) of nonzero zero-divisors of R. In this dissertation we investigate how the properties of R a⁄ect the properties of (R) and vice versa. There are other graphs that are associated with R. Some of these are shown to be special cases of the congruence-based zero-divisor graph.
- Full Text:
- Date Issued: 2020
- Authors: Mzulwini, Sboniso
- Date: 2020
- Subjects: Categories (Mathematics)
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/47060 , vital:39779
- Description: Let R be a commutative ring with nonzero identity, and let Z (R) be the set of its zerodivisors. There exists an association between a simple graph (R) and the set Z(R) of nonzero zero-divisors of R. In this dissertation we investigate how the properties of R a⁄ect the properties of (R) and vice versa. There are other graphs that are associated with R. Some of these are shown to be special cases of the congruence-based zero-divisor graph.
- Full Text:
- Date Issued: 2020
Elie Wiesel's fictional universe : the paradox of the mute narrator
- Authors: Berman, Mona
- Date: 1986
- Subjects: Wiesel, Elie, 1928- -- Criticism and interpretation , Holocaust, Jewish (1939-1945) -- Personal narratives , Auschwitz , Narration , Silence , English literature , Criticism
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: vital:2178 , http://hdl.handle.net/10962/d1001829
- Description: The approach I have chosen for my study is to analyse the narrative techniques in Wiesel's fiction, with particular emphasis on the role of the narrator and listener in the narratives. This will not only highlight aspects of his authorial strategy involving the reader's response to various dimensions of the Holocaust, but will allow an appraisal of the literary merit of Wiesel's novels. The hushed reverence that tends to accompany allusions to Auschwitz and its literature has impeded certain theoretical investigations, with the result that most critical studies undertaken on Wiesel's works have dealt predominantly with themes and content rather than with form. A narrative approach, however, while it accounts for themes, does so within the narrative process of the work. Form and content are examined as interwoven entities in the particular context of an individual work. My decision to adopt this pursuit is based on the conviction that Wiesel's fiction is a significant contribution to the literature of testimony, not only because of its subject matter, but also because of the way in which his narrators unfold their stories with words suspended by silence in the text. The paradox of the mute narrator, the title of my study, is intended to convey the paradoxical quality of Wiesel's fiction and to show how silence, which is manifested in the themes of his work, is concretized by his strategy of entrusting the transmission of the tale to narrators, who, for various reasons have been silenced. A mute by definition cannot emit an articulate sound. A narrator, on the other hand, is a storyteller who is reliant on verbal articulation for communication. This contradiction in terms is dramatized in the novels and is symptomatic of the dilemma of Wiesel's narrators who are compelled to bear testimony through their silence. In my study of Wiesel's fiction, I will follow the chronological sequence in which the novels were written, although I will not be using a developmental approach, except to point out that the trilogy which marks the beginning of his exploration into narrative strategies, and The Testament, the last book I will be dealing with, are a culmination of his previous fictional techniques. While a developmental analysis of his fiction, particularly from a thematic point of view, enables the reader to gain insight into his background, which is important in a comprehensive study of his works, I feel that this avenue of investigation has been competently dealt with by other critics. Ellen Fine's Legacy of Night, one of the first book-length studies of Wiesel, puts forward a convincing argument for examining his fiction in chronological sequence as a kind of serialized journey from being a witness in l'univers concentrationnaire to bearing - witness in a post-Holocaust world. Furthermore, it is possible to trace the direction Wiesel's fiction follows, as in each book the seeds are sown for new ideas which are expanded upon in subsequent books. My discussion, however, will deal with the narrative process of each novel as an individual work in its own particular context. Apart from the trilogy which is examined in one chapter, and The Testament which serves as a conclusion to the study, I have not used cross references to Wiesel's other fiction when analysing specific books. Moreover, I have deliberately avoided including Wiesel's comments on his works and references to them in his essays, interviews and non-fiction writing. The reason for this approach is that I consider each novel to be a separate narrative work which merits an interpretative response that is independent of the comparative criteria that has up to now influenced the assessment of his fiction. (Introduction, p. 12-14)
- Full Text:
- Date Issued: 1986
- Authors: Berman, Mona
- Date: 1986
- Subjects: Wiesel, Elie, 1928- -- Criticism and interpretation , Holocaust, Jewish (1939-1945) -- Personal narratives , Auschwitz , Narration , Silence , English literature , Criticism
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: vital:2178 , http://hdl.handle.net/10962/d1001829
- Description: The approach I have chosen for my study is to analyse the narrative techniques in Wiesel's fiction, with particular emphasis on the role of the narrator and listener in the narratives. This will not only highlight aspects of his authorial strategy involving the reader's response to various dimensions of the Holocaust, but will allow an appraisal of the literary merit of Wiesel's novels. The hushed reverence that tends to accompany allusions to Auschwitz and its literature has impeded certain theoretical investigations, with the result that most critical studies undertaken on Wiesel's works have dealt predominantly with themes and content rather than with form. A narrative approach, however, while it accounts for themes, does so within the narrative process of the work. Form and content are examined as interwoven entities in the particular context of an individual work. My decision to adopt this pursuit is based on the conviction that Wiesel's fiction is a significant contribution to the literature of testimony, not only because of its subject matter, but also because of the way in which his narrators unfold their stories with words suspended by silence in the text. The paradox of the mute narrator, the title of my study, is intended to convey the paradoxical quality of Wiesel's fiction and to show how silence, which is manifested in the themes of his work, is concretized by his strategy of entrusting the transmission of the tale to narrators, who, for various reasons have been silenced. A mute by definition cannot emit an articulate sound. A narrator, on the other hand, is a storyteller who is reliant on verbal articulation for communication. This contradiction in terms is dramatized in the novels and is symptomatic of the dilemma of Wiesel's narrators who are compelled to bear testimony through their silence. In my study of Wiesel's fiction, I will follow the chronological sequence in which the novels were written, although I will not be using a developmental approach, except to point out that the trilogy which marks the beginning of his exploration into narrative strategies, and The Testament, the last book I will be dealing with, are a culmination of his previous fictional techniques. While a developmental analysis of his fiction, particularly from a thematic point of view, enables the reader to gain insight into his background, which is important in a comprehensive study of his works, I feel that this avenue of investigation has been competently dealt with by other critics. Ellen Fine's Legacy of Night, one of the first book-length studies of Wiesel, puts forward a convincing argument for examining his fiction in chronological sequence as a kind of serialized journey from being a witness in l'univers concentrationnaire to bearing - witness in a post-Holocaust world. Furthermore, it is possible to trace the direction Wiesel's fiction follows, as in each book the seeds are sown for new ideas which are expanded upon in subsequent books. My discussion, however, will deal with the narrative process of each novel as an individual work in its own particular context. Apart from the trilogy which is examined in one chapter, and The Testament which serves as a conclusion to the study, I have not used cross references to Wiesel's other fiction when analysing specific books. Moreover, I have deliberately avoided including Wiesel's comments on his works and references to them in his essays, interviews and non-fiction writing. The reason for this approach is that I consider each novel to be a separate narrative work which merits an interpretative response that is independent of the comparative criteria that has up to now influenced the assessment of his fiction. (Introduction, p. 12-14)
- Full Text:
- Date Issued: 1986
Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition
- Authors: Buys, Stefan
- Date: 2012
- Subjects: Genetic algorithms , Software architecture
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:9648 , http://hdl.handle.net/10948/d1008356 , Genetic algorithms , Software architecture
- Description: Object or part recognition is of major interest in industrial environments. Current methods implement expensive camera based solutions. There is a need for a cost effective alternative to be developed. One of the proposed methods is to overcome the hardware, camera, problem by implementing a software solution. Artificial Neural Networks (ANN) are to be used as the underlying intelligent software as they have high tolerance for noise and have the ability to generalize. A colleague has implemented a basic ANN based system comprising of an ANN and three cost effective laser distance sensors. However, the system is only able to identify 3 different parts and needed hard coding changes made by trial and error. This is not practical for industrial use in a production environment where there are a large quantity of different parts to be identified that change relatively regularly. The ability to easily train more parts is required. Difficulties associated with traditional mathematically guided training methods are discussed, which leads to the development of a Genetic Algorithm (GA) based evolutionary training method that overcomes these difficulties and makes accurate part recognition possible. An ANN hybridised with GA training is introduced and a general solution encoding scheme which is used to encode the required ANN connection weights. Experimental tests were performed in order to determine the ideal GA performance and control parameters as studies have indicated that different GA control parameters can lead to large differences in training accuracy. After performing these tests, the training accuracy was analyzed by investigation into GA performance as well as hardware based part recognition performance. This analysis identified the ideal GA control parameters when training an ANN for the purpose of part recognition and showed that the ANN generally trained well and could generalize well on data not presented to it during training.
- Full Text:
- Date Issued: 2012
- Authors: Buys, Stefan
- Date: 2012
- Subjects: Genetic algorithms , Software architecture
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:9648 , http://hdl.handle.net/10948/d1008356 , Genetic algorithms , Software architecture
- Description: Object or part recognition is of major interest in industrial environments. Current methods implement expensive camera based solutions. There is a need for a cost effective alternative to be developed. One of the proposed methods is to overcome the hardware, camera, problem by implementing a software solution. Artificial Neural Networks (ANN) are to be used as the underlying intelligent software as they have high tolerance for noise and have the ability to generalize. A colleague has implemented a basic ANN based system comprising of an ANN and three cost effective laser distance sensors. However, the system is only able to identify 3 different parts and needed hard coding changes made by trial and error. This is not practical for industrial use in a production environment where there are a large quantity of different parts to be identified that change relatively regularly. The ability to easily train more parts is required. Difficulties associated with traditional mathematically guided training methods are discussed, which leads to the development of a Genetic Algorithm (GA) based evolutionary training method that overcomes these difficulties and makes accurate part recognition possible. An ANN hybridised with GA training is introduced and a general solution encoding scheme which is used to encode the required ANN connection weights. Experimental tests were performed in order to determine the ideal GA performance and control parameters as studies have indicated that different GA control parameters can lead to large differences in training accuracy. After performing these tests, the training accuracy was analyzed by investigation into GA performance as well as hardware based part recognition performance. This analysis identified the ideal GA control parameters when training an ANN for the purpose of part recognition and showed that the ANN generally trained well and could generalize well on data not presented to it during training.
- Full Text:
- Date Issued: 2012
Optimization of salbutamol sulfate dissolution from sustained release matrix formulations using an artificial neural network
- Chaibva, Faith A, Burton, Michael, Walker, Roderick B
- Authors: Chaibva, Faith A , Burton, Michael , Walker, Roderick B
- Date: 2010
- Subjects: Neural networks (Computer science)
- Language: English
- Type: Article
- Identifier: vital:6352 , http://hdl.handle.net/10962/d1006034
- Description: An artificial neural network was used to optimize the release of salbutamol sulfate from hydrophilic matrix formulations. Model formulations to be used for training, testing and validating the neural network were manufactured with the aid of a central composite design with varying the levels of Methocel® K100M, xanthan gum, Carbopol® 974P and Surelease® as the input factors. In vitro dissolution time profiles at six different sampling times were used as target data in training the neural network for formulation optimization. A multi layer perceptron with one hidden layer was constructed using Matlab®, and the number of nodes in the hidden layer was optimized by trial and error to develop a model with the best predictive ability. The results revealed that a neural network with nine nodes was optimal for developing and optimizing formulations. Simulations undertaken with the training data revealed that the constructed model was useable. The optimized neural network was used for optimization of formulation with desirable release characteristics and the results indicated that there was agreement between the predicted formulation and the manufactured formulation. This work illustrates the possible utility of artificial neural networks for the optimization of pharmaceutical formulations with desirable performance characteristics.
- Full Text:
- Date Issued: 2010
- Authors: Chaibva, Faith A , Burton, Michael , Walker, Roderick B
- Date: 2010
- Subjects: Neural networks (Computer science)
- Language: English
- Type: Article
- Identifier: vital:6352 , http://hdl.handle.net/10962/d1006034
- Description: An artificial neural network was used to optimize the release of salbutamol sulfate from hydrophilic matrix formulations. Model formulations to be used for training, testing and validating the neural network were manufactured with the aid of a central composite design with varying the levels of Methocel® K100M, xanthan gum, Carbopol® 974P and Surelease® as the input factors. In vitro dissolution time profiles at six different sampling times were used as target data in training the neural network for formulation optimization. A multi layer perceptron with one hidden layer was constructed using Matlab®, and the number of nodes in the hidden layer was optimized by trial and error to develop a model with the best predictive ability. The results revealed that a neural network with nine nodes was optimal for developing and optimizing formulations. Simulations undertaken with the training data revealed that the constructed model was useable. The optimized neural network was used for optimization of formulation with desirable release characteristics and the results indicated that there was agreement between the predicted formulation and the manufactured formulation. This work illustrates the possible utility of artificial neural networks for the optimization of pharmaceutical formulations with desirable performance characteristics.
- Full Text:
- Date Issued: 2010
Empirically modelled Pc3 activity based on solar wind parameters
- Heilig, B, Lotz, S I, Verő, J, Sutcliffe, P, Reda, J, Pajunpää, G, Raita, T
- Authors: Heilig, B , Lotz, S I , Verő, J , Sutcliffe, P , Reda, J , Pajunpää, G , Raita, T
- Date: 2010
- Language: English
- Type: text , Article
- Identifier: vital:6814 , http://hdl.handle.net/10962/d1004324
- Description: It is known that under certain solar wind (SW)/interplanetary magnetic field (IMF) conditions (e.g. high SW speed, low cone angle) the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock). Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through upstream waves.
- Full Text:
- Date Issued: 2010
- Authors: Heilig, B , Lotz, S I , Verő, J , Sutcliffe, P , Reda, J , Pajunpää, G , Raita, T
- Date: 2010
- Language: English
- Type: text , Article
- Identifier: vital:6814 , http://hdl.handle.net/10962/d1004324
- Description: It is known that under certain solar wind (SW)/interplanetary magnetic field (IMF) conditions (e.g. high SW speed, low cone angle) the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock). Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through upstream waves.
- Full Text:
- Date Issued: 2010
J L B Smith: his life, work, bibliography and list of new species
- Authors: Smith, Margaret Mary
- Date: 1969
- Subjects: Smith, J.L.B. (James Leonard Brierley), 1897-1968
- Language: English
- Type: Text
- Identifier: vital:15051 , http://hdl.handle.net/10962/d1020233
- Full Text:
- Date Issued: 1969
- Authors: Smith, Margaret Mary
- Date: 1969
- Subjects: Smith, J.L.B. (James Leonard Brierley), 1897-1968
- Language: English
- Type: Text
- Identifier: vital:15051 , http://hdl.handle.net/10962/d1020233
- Full Text:
- Date Issued: 1969
Resisting the desire for the unambiguous: productive gaps in researcher, teacher and student interpretations of a number story task
- Authors: Graven, Mellony , Coles, Alf
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/69673 , vital:29564 , https://DOI: 10.1007/s11858-017-0863-7
- Description: This article offers reflections on task design in the context of a Grade R (reception year) in-service numeracy project in South Africa. The research explores under what conditions, and for what learning purpose, a task designed by someone else may be recast and how varying given task specifications may support or inhibit learning, as a result of that recasting. This question is situated within a two-pronged task design challenge as to emerging gaps between the task designer’s intentions and teacher’s actions and secondly between the teachers’ intentions and students’ actions. Through analysing two teachers and their respective Grade R students’ interpretations of a worksheet task, provided to teachers in the project, we illuminate the way explicit constraints, in the form of task specifications, can be both enabling and constraining of learning. In so doing we recast this ‘double gap’ as enabling productive learning spaces for teacher educators, teachers and students.
- Full Text:
- Date Issued: 2017
- Authors: Graven, Mellony , Coles, Alf
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/69673 , vital:29564 , https://DOI: 10.1007/s11858-017-0863-7
- Description: This article offers reflections on task design in the context of a Grade R (reception year) in-service numeracy project in South Africa. The research explores under what conditions, and for what learning purpose, a task designed by someone else may be recast and how varying given task specifications may support or inhibit learning, as a result of that recasting. This question is situated within a two-pronged task design challenge as to emerging gaps between the task designer’s intentions and teacher’s actions and secondly between the teachers’ intentions and students’ actions. Through analysing two teachers and their respective Grade R students’ interpretations of a worksheet task, provided to teachers in the project, we illuminate the way explicit constraints, in the form of task specifications, can be both enabling and constraining of learning. In so doing we recast this ‘double gap’ as enabling productive learning spaces for teacher educators, teachers and students.
- Full Text:
- Date Issued: 2017
An artificial neural network approach to predict the effects of formulation and process variables on prednisone release from a multipartite system
- Manda, Arthur, Walker, Roderick B, Khamanga, Sandile M
- Authors: Manda, Arthur , Walker, Roderick B , Khamanga, Sandile M
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/183237 , vital:43933 , xlink:href="https://doi.org/10.3390/pharmaceutics11030109"
- Description: The impact of formulation and process variables on the in-vitro release of prednisone from a multiple-unit pellet system was investigated. Box-Behnken Response Surface Methodology (RSM) was used to generate multivariate experiments. The extrusion-spheronization method was used to produce pellets and dissolution studies were performed using United States Pharmacopoeia (USP) Apparatus 2 as described in USP XXIV. Analysis of dissolution test samples was performed using a reversed-phase high-performance liquid chromatography (RP-HPLC) method. Four formulation and process variables viz., microcrystalline cellulose concentration, sodium starch glycolate concentration, spheronization time and extrusion speed were investigated and drug release, aspect ratio and yield were monitored for the trained artificial neural networks (ANN). To achieve accurate prediction, data generated from experimentation were used to train a multi-layer perceptron (MLP) using back propagation (BP) and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) 57 training algorithm until a satisfactory value of root mean square error (RMSE) was observed. The study revealed that the in-vitro release profile of prednisone was significantly impacted by microcrystalline cellulose concentration and sodium starch glycolate concentration. Increasing microcrystalline cellulose concentration retarded dissolution rate whereas increasing sodium starch glycolate concentration improved dissolution rate. Spheronization time and extrusion speed had minimal impact on prednisone release but had a significant impact on extrudate and pellet quality. This work demonstrated that RSM can be successfully used concurrently with ANN for dosage form manufacture to permit the exploration of experimental regions that are omitted when using RSM alone.
- Full Text:
- Date Issued: 2019
- Authors: Manda, Arthur , Walker, Roderick B , Khamanga, Sandile M
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/183237 , vital:43933 , xlink:href="https://doi.org/10.3390/pharmaceutics11030109"
- Description: The impact of formulation and process variables on the in-vitro release of prednisone from a multiple-unit pellet system was investigated. Box-Behnken Response Surface Methodology (RSM) was used to generate multivariate experiments. The extrusion-spheronization method was used to produce pellets and dissolution studies were performed using United States Pharmacopoeia (USP) Apparatus 2 as described in USP XXIV. Analysis of dissolution test samples was performed using a reversed-phase high-performance liquid chromatography (RP-HPLC) method. Four formulation and process variables viz., microcrystalline cellulose concentration, sodium starch glycolate concentration, spheronization time and extrusion speed were investigated and drug release, aspect ratio and yield were monitored for the trained artificial neural networks (ANN). To achieve accurate prediction, data generated from experimentation were used to train a multi-layer perceptron (MLP) using back propagation (BP) and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) 57 training algorithm until a satisfactory value of root mean square error (RMSE) was observed. The study revealed that the in-vitro release profile of prednisone was significantly impacted by microcrystalline cellulose concentration and sodium starch glycolate concentration. Increasing microcrystalline cellulose concentration retarded dissolution rate whereas increasing sodium starch glycolate concentration improved dissolution rate. Spheronization time and extrusion speed had minimal impact on prednisone release but had a significant impact on extrudate and pellet quality. This work demonstrated that RSM can be successfully used concurrently with ANN for dosage form manufacture to permit the exploration of experimental regions that are omitted when using RSM alone.
- Full Text:
- Date Issued: 2019
Comparison of the Therapeutic Effectiveness of Abacavir and Stavudine as part of the First Line Antiretroviral Therapy Nucleoside Reverse Transcriptase Backbone for Children in East London, South Africa
- Authors: Cheree Ann Goldswain
- Date: 2016
- Subjects: Paediatrics, Medicine
- Language: English
- Type: Thesis, Masters
- Identifier: http://hdl.handle.net/11260/2137 , vital:40902
- Full Text: false
- Authors: Cheree Ann Goldswain
- Date: 2016
- Subjects: Paediatrics, Medicine
- Language: English
- Type: Thesis, Masters
- Identifier: http://hdl.handle.net/11260/2137 , vital:40902
- Full Text: false
Modelling storm-time TEC changes using linear and non-linear techniques
- Authors: Uwamahoro, Jean Claude
- Date: 2019
- Subjects: Magnetic storms , Astronomy -- Computer programs , Imaging systems in astronomy , Ionospheric storms , Electrons -- Measurement , Magnetosphere -- Observations
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/92908 , vital:30762
- Description: Statistical models based on empirical orthogonal functions (EOF) analysis and non-linear regression analysis (NLRA) were developed for the purpose of estimating the ionospheric total electron content (TEC) during geomagnetic storms. The well-known least squares method (LSM) and Metropolis-Hastings algorithm (MHA) were used as optimization techniques to determine the unknown coefficients of the developed analytical expressions. Artificial Neural Networks (ANNs), the International Reference Ionosphere (IRI) model, and the Multi-Instrument Data Analysis System (MIDAS) tomographic inversion algorithm were also applied to storm-time TEC modelling/reconstruction for various latitudes of the African sector and surrounding areas. This work presents some of the first statistical modeling of the mid-latitude and low-latitude ionosphere during geomagnetic storms that includes solar, geomagnetic and neutral wind drivers.Development and validation of the empirical models were based on storm-time TEC data derived from the global positioning system (GPS) measurements over ground receivers within Africa and surrounding areas. The storm criterion applied was Dst 6 −50 nT and/or Kp > 4. The performance evaluation of MIDAS compared with ANNs to reconstruct storm-time TEC over the African low- and mid-latitude regions showed that MIDAS and ANNs provide comparable results. Their respective mean absolute error (MAE) values were 4.81 and 4.18 TECU. The ANN model was, however, found to perform 24.37 % better than MIDAS at estimating storm-time TEC for low latitudes, while MIDAS is 13.44 % more accurate than ANN for the mid-latitudes. When their performances are compared with the IRI model, both MIDAS and ANN model were found to provide more accurate storm-time TEC reconstructions for the African low- and mid-latitude regions. A comparative study of the performances of EOF, NLRA, ANN, and IRI models to estimate TEC during geomagnetic storm conditions over various latitudes showed that the ANN model is about 10 %, 26 %, and 58 % more accurate than EOF, NLRA, and IRI models, respectively, while EOF was found to perform 15 %, and 44 % better than NLRA and IRI, respectively. It was further found that the NLRA model is 25 % more accurate than the IRI model. We have also investigated for the first time, the role of meridional neutral winds (from the Horizontal Wind Model) to storm-time TEC modelling in the low latitude, northern and southern hemisphere mid-latitude regions of the African sector, based on ANN models. Statistics have shown that the inclusion of the meridional wind velocity in TEC modelling during geomagnetic storms leads to percentage improvements of about 5 % for the low latitude, 10 % and 5 % for the northern and southern hemisphere mid-latitude regions, respectively. High-latitude storm-induced winds and the inter-hemispheric blows of the meridional winds from summer to winter hemisphere have been suggested to be associated with these improvements.
- Full Text:
- Date Issued: 2019
- Authors: Uwamahoro, Jean Claude
- Date: 2019
- Subjects: Magnetic storms , Astronomy -- Computer programs , Imaging systems in astronomy , Ionospheric storms , Electrons -- Measurement , Magnetosphere -- Observations
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/92908 , vital:30762
- Description: Statistical models based on empirical orthogonal functions (EOF) analysis and non-linear regression analysis (NLRA) were developed for the purpose of estimating the ionospheric total electron content (TEC) during geomagnetic storms. The well-known least squares method (LSM) and Metropolis-Hastings algorithm (MHA) were used as optimization techniques to determine the unknown coefficients of the developed analytical expressions. Artificial Neural Networks (ANNs), the International Reference Ionosphere (IRI) model, and the Multi-Instrument Data Analysis System (MIDAS) tomographic inversion algorithm were also applied to storm-time TEC modelling/reconstruction for various latitudes of the African sector and surrounding areas. This work presents some of the first statistical modeling of the mid-latitude and low-latitude ionosphere during geomagnetic storms that includes solar, geomagnetic and neutral wind drivers.Development and validation of the empirical models were based on storm-time TEC data derived from the global positioning system (GPS) measurements over ground receivers within Africa and surrounding areas. The storm criterion applied was Dst 6 −50 nT and/or Kp > 4. The performance evaluation of MIDAS compared with ANNs to reconstruct storm-time TEC over the African low- and mid-latitude regions showed that MIDAS and ANNs provide comparable results. Their respective mean absolute error (MAE) values were 4.81 and 4.18 TECU. The ANN model was, however, found to perform 24.37 % better than MIDAS at estimating storm-time TEC for low latitudes, while MIDAS is 13.44 % more accurate than ANN for the mid-latitudes. When their performances are compared with the IRI model, both MIDAS and ANN model were found to provide more accurate storm-time TEC reconstructions for the African low- and mid-latitude regions. A comparative study of the performances of EOF, NLRA, ANN, and IRI models to estimate TEC during geomagnetic storm conditions over various latitudes showed that the ANN model is about 10 %, 26 %, and 58 % more accurate than EOF, NLRA, and IRI models, respectively, while EOF was found to perform 15 %, and 44 % better than NLRA and IRI, respectively. It was further found that the NLRA model is 25 % more accurate than the IRI model. We have also investigated for the first time, the role of meridional neutral winds (from the Horizontal Wind Model) to storm-time TEC modelling in the low latitude, northern and southern hemisphere mid-latitude regions of the African sector, based on ANN models. Statistics have shown that the inclusion of the meridional wind velocity in TEC modelling during geomagnetic storms leads to percentage improvements of about 5 % for the low latitude, 10 % and 5 % for the northern and southern hemisphere mid-latitude regions, respectively. High-latitude storm-induced winds and the inter-hemispheric blows of the meridional winds from summer to winter hemisphere have been suggested to be associated with these improvements.
- Full Text:
- Date Issued: 2019
A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results
- Habarulema, John B, McKinnell, Lee-Anne, Opperman, Ben D L
- Authors: Habarulema, John B , McKinnell, Lee-Anne , Opperman, Ben D L
- Date: 2009
- Language: English
- Type: text , Article
- Identifier: vital:6813 , http://hdl.handle.net/10962/d1004323
- Description: This paper attempts to describe the search for the parameter(s) to represent solar wind effects in Global Positioning System total electron content (GPS TEC) modelling using the technique of neural networks (NNs). A study is carried out by including solar wind velocity (Vsw), proton number density (Np) and the Bz component of the interplanetary magnetic field (IMF Bz) obtained from the Advanced Composition Explorer (ACE) satellite as separate inputs to the NN each along with day number of the year (DN), hour (HR), a 4-month running mean of the daily sunspot number (R4) and the running mean of the previous eight 3-hourly magnetic A index values (A8). Hourly GPS TEC values derived from a dual frequency receiver located at Sutherland (32.38° S, 20.81° E), South Africa for 8 years (2000–2007) have been used to train the Elman neural network (ENN) and the result has been used to predict TEC variations for a GPS station located at Cape Town (33.95° S, 18.47° E). Quantitative results indicate that each of the parameters considered may have some degree of influence on GPS TEC at certain periods although a decrease in prediction accuracy is also observed for some parameters for different days and seasons. It is also evident that there is still a difficulty in predicting TEC values during disturbed conditions. The improvements and degradation in prediction accuracies are both close to the benchmark values which lends weight to the belief that diurnal, seasonal, solar and magnetic variabilities may be the major determinants of TEC variability.
- Full Text:
- Date Issued: 2009
- Authors: Habarulema, John B , McKinnell, Lee-Anne , Opperman, Ben D L
- Date: 2009
- Language: English
- Type: text , Article
- Identifier: vital:6813 , http://hdl.handle.net/10962/d1004323
- Description: This paper attempts to describe the search for the parameter(s) to represent solar wind effects in Global Positioning System total electron content (GPS TEC) modelling using the technique of neural networks (NNs). A study is carried out by including solar wind velocity (Vsw), proton number density (Np) and the Bz component of the interplanetary magnetic field (IMF Bz) obtained from the Advanced Composition Explorer (ACE) satellite as separate inputs to the NN each along with day number of the year (DN), hour (HR), a 4-month running mean of the daily sunspot number (R4) and the running mean of the previous eight 3-hourly magnetic A index values (A8). Hourly GPS TEC values derived from a dual frequency receiver located at Sutherland (32.38° S, 20.81° E), South Africa for 8 years (2000–2007) have been used to train the Elman neural network (ENN) and the result has been used to predict TEC variations for a GPS station located at Cape Town (33.95° S, 18.47° E). Quantitative results indicate that each of the parameters considered may have some degree of influence on GPS TEC at certain periods although a decrease in prediction accuracy is also observed for some parameters for different days and seasons. It is also evident that there is still a difficulty in predicting TEC values during disturbed conditions. The improvements and degradation in prediction accuracies are both close to the benchmark values which lends weight to the belief that diurnal, seasonal, solar and magnetic variabilities may be the major determinants of TEC variability.
- Full Text:
- Date Issued: 2009
Margaret Ann Phillips (Isherwood)
- Subjects: Class reunions -- South Africa -- Grahamstown -- Photographs Grahamstown Teachers' Training College (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/28158 , vital:23620 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/A 2897_111
- Description: Photograph of Margaret Ann Phillips (Isherwood) sitting in a high chair , Leila Kerr (Linington) (Donor)
- Full Text: false
- Subjects: Class reunions -- South Africa -- Grahamstown -- Photographs Grahamstown Teachers' Training College (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/28158 , vital:23620 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/A 2897_111
- Description: Photograph of Margaret Ann Phillips (Isherwood) sitting in a high chair , Leila Kerr (Linington) (Donor)
- Full Text: false
Mary Ann Matthews
- Subjects: Class reunions -- South Africa -- Grahamstown -- Photographs Grahamstown Teachers' Training College (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/28587 , vital:23663 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/A 2897_124
- Description: Photograph of Mary Ann Matthews (presumably the daughter of Gladys Hobbs) , Leila Kerr (Linington) (Donor)
- Full Text: false
- Subjects: Class reunions -- South Africa -- Grahamstown -- Photographs Grahamstown Teachers' Training College (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/28587 , vital:23663 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/A 2897_124
- Description: Photograph of Mary Ann Matthews (presumably the daughter of Gladys Hobbs) , Leila Kerr (Linington) (Donor)
- Full Text: false
Unidentified old ladies, possibly relatives of Ann Palm
- Subjects: Old people
- Type: Image
- Identifier: http://hdl.handle.net/10962/16189 , vital:22120 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/M 5221
- Full Text: false
- Subjects: Old people
- Type: Image
- Identifier: http://hdl.handle.net/10962/16189 , vital:22120 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/M 5221
- Full Text: false
Ann Evans back from UK at Stewart Memorial, Alice
- Subjects: Alice (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/11615 , vital:21714 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/M 5204
- Full Text: false
- Subjects: Alice (South Africa) -- Photographs
- Type: Image
- Identifier: http://hdl.handle.net/10962/11615 , vital:21714 , This image is held at the Cory Library for Humanities Research at Rhodes University. For further information contact cory@ru.ac.za. The digitisation of this image was made possible through a generous grant received from the Andrew W. Mellon Foundation 2014-2017. , PIC/M 5204
- Full Text: false