‘That mountain cannot be beautiful for nothing’: Zakes Mda’s aesthetics of liberation
- Dilinga, Siyamthanda Iribagiza
- Authors: Dilinga, Siyamthanda Iribagiza
- Date: 2019
- Subjects: Mda, Zakes -- Criticism and interpretation , South African fiction (English) -- History and criticism , South Africa -- In literature
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/70452 , vital:29662
- Description: Zakes Mda is a prominent post-apartheid black South African novelist whose style has been described as experimental. He also wrote plays intended to ‘rally people to action’ during the apartheid years. The changes in the political and social situation in South Africa since 1994 have had significant implications for those writers and artists who produced protest literature and art. The changes in Mda’s own practice and approach to art are themselves quite telling. His experimental novels place him among those African artists pioneering a new chapter for black South African art and the self-reflexive nature of his novels suggest that he is aware of the fact and is consciously forming and reforming his ideas about what it means to be an artist in post-apartheid South Africa. This study will unpack the role of the artist and the function of art in the becoming new South Africa as represented in Zakes Mda’s novels, thereby hypothesizing Mda’s aesthetic philosophy, as may be deduced from his practice, for what an African artist and art should be. This will be done first by locating Mda in the debates around art and literature within the sociopolitical context of a South Africa in transition. Despite the fact that when it comes to public action in the post-apartheid situation, Mda distinguishes between his own role in society as an artist who is a social activist and the role intended for his work, his own novels reveal a desire for the artefact (or artwork) to have a developmental, educational or conscientizing function. This is evident in representations of the effects of art in what this study proposes to be his extended South African black Kunstlerroman, which spans three novels. It is also demonstrated in his ekphrastic novel, The Madonna of Excelsior, in which visual art is interpreted in the process of description, thereby educating the reader. Not only that, but the reader is made into an ‘almost viewer’ and taught how to ‘see’ art. What emerges in the process of this study is Mda’s aesthetic philosophy or what may be termed his ‘aesthetics of liberation’ concerning the role of the artist in post-apartheid South Africa, a suitable African audience and how art works theoretically, as expressed through his fiction.
- Full Text:
- Date Issued: 2019
- Authors: Dilinga, Siyamthanda Iribagiza
- Date: 2019
- Subjects: Mda, Zakes -- Criticism and interpretation , South African fiction (English) -- History and criticism , South Africa -- In literature
- Language: English
- Type: text , Thesis , Masters , MA
- Identifier: http://hdl.handle.net/10962/70452 , vital:29662
- Description: Zakes Mda is a prominent post-apartheid black South African novelist whose style has been described as experimental. He also wrote plays intended to ‘rally people to action’ during the apartheid years. The changes in the political and social situation in South Africa since 1994 have had significant implications for those writers and artists who produced protest literature and art. The changes in Mda’s own practice and approach to art are themselves quite telling. His experimental novels place him among those African artists pioneering a new chapter for black South African art and the self-reflexive nature of his novels suggest that he is aware of the fact and is consciously forming and reforming his ideas about what it means to be an artist in post-apartheid South Africa. This study will unpack the role of the artist and the function of art in the becoming new South Africa as represented in Zakes Mda’s novels, thereby hypothesizing Mda’s aesthetic philosophy, as may be deduced from his practice, for what an African artist and art should be. This will be done first by locating Mda in the debates around art and literature within the sociopolitical context of a South Africa in transition. Despite the fact that when it comes to public action in the post-apartheid situation, Mda distinguishes between his own role in society as an artist who is a social activist and the role intended for his work, his own novels reveal a desire for the artefact (or artwork) to have a developmental, educational or conscientizing function. This is evident in representations of the effects of art in what this study proposes to be his extended South African black Kunstlerroman, which spans three novels. It is also demonstrated in his ekphrastic novel, The Madonna of Excelsior, in which visual art is interpreted in the process of description, thereby educating the reader. Not only that, but the reader is made into an ‘almost viewer’ and taught how to ‘see’ art. What emerges in the process of this study is Mda’s aesthetic philosophy or what may be termed his ‘aesthetics of liberation’ concerning the role of the artist in post-apartheid South Africa, a suitable African audience and how art works theoretically, as expressed through his fiction.
- Full Text:
- Date Issued: 2019
Machine learning methods for calibrating radio interferometric data
- Authors: Zitha, Simphiwe Nhlanhla
- Date: 2019
- Subjects: Calibration , Radio astronomy -- Data processing , Radio astronomy -- South Africa , Karoo Array Telescope (South Africa) , Radio telescopes -- South Africa , Common Astronomy Software Application (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/97096 , vital:31398
- Description: The applications of machine learning have created an opportunity to deal with complex problems currently encountered in radio astronomy data processing. Calibration is one of the most important data processing steps required to produce high dynamic range images. This process involves the determination of calibration parameters, both instrumental and astronomical, to correct the collected data. Typically, astronomers use a package such as Common Astronomy Software Applications (CASA) to compute the gain solutions based on regular observations of a known calibrator source. In this work we present applications of machine learning to first generation calibration (1GC), using the KAT-7 telescope environmental and pointing sensor data recorded during observations. Applying machine learning to 1GC, as opposed to calculating the gain solutions in CASA, has shown evidence of reducing computation, as well as accurately predict the 1GC gain solutions representing the behaviour of the antenna during an observation. These methods are computationally less expensive, however they have not fully learned to generalise in predicting accurate 1GC solutions by looking at environmental and pointing sensors. We call this multi-output regression model ZCal, which is based on random forest, decision trees, extremely randomized trees and K-nearest neighbor algorithms. The prediction error obtained during the testing of our model on testing data is ≈ 0.01 < rmse < 0.09 for gain amplitude per antenna, and 0.2 rad < rmse <0.5 rad for gain phase. This shows that the instrumental parameters used to train our model more strongly correlate with gain amplitude effects than phase.
- Full Text:
- Date Issued: 2019
- Authors: Zitha, Simphiwe Nhlanhla
- Date: 2019
- Subjects: Calibration , Radio astronomy -- Data processing , Radio astronomy -- South Africa , Karoo Array Telescope (South Africa) , Radio telescopes -- South Africa , Common Astronomy Software Application (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/97096 , vital:31398
- Description: The applications of machine learning have created an opportunity to deal with complex problems currently encountered in radio astronomy data processing. Calibration is one of the most important data processing steps required to produce high dynamic range images. This process involves the determination of calibration parameters, both instrumental and astronomical, to correct the collected data. Typically, astronomers use a package such as Common Astronomy Software Applications (CASA) to compute the gain solutions based on regular observations of a known calibrator source. In this work we present applications of machine learning to first generation calibration (1GC), using the KAT-7 telescope environmental and pointing sensor data recorded during observations. Applying machine learning to 1GC, as opposed to calculating the gain solutions in CASA, has shown evidence of reducing computation, as well as accurately predict the 1GC gain solutions representing the behaviour of the antenna during an observation. These methods are computationally less expensive, however they have not fully learned to generalise in predicting accurate 1GC solutions by looking at environmental and pointing sensors. We call this multi-output regression model ZCal, which is based on random forest, decision trees, extremely randomized trees and K-nearest neighbor algorithms. The prediction error obtained during the testing of our model on testing data is ≈ 0.01 < rmse < 0.09 for gain amplitude per antenna, and 0.2 rad < rmse <0.5 rad for gain phase. This shows that the instrumental parameters used to train our model more strongly correlate with gain amplitude effects than phase.
- Full Text:
- Date Issued: 2019
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