Influence of family structure on food security status of farming households in Alice, South Africa
- Authors: Ijila, Olusegun Jeremiah
- Date: 2018
- Subjects: Food security Families--South Africa--Eastern Cape Farms, Small
- Language: English
- Type: Thesis , Masters , Agricultural Economics
- Identifier: http://hdl.handle.net/10353/11537 , vital:39081
- Description: Achieving food security in sub-Saharan Africa remains a major challenge despite efforts made by a majority of the countries to reduce abject poverty and food insecurity. Just as these countries prioritized food security under the Millennium Development Goals (MDGs), they are equally putting it on top of the agenda under the Sustainable Development Goals (SDGs). In the face of the political and economic developments seen in the country since 1994, South Africa is overwhelmed by poverty and unemployment. But efforts to address these problems have not given due recognition to the question of family structure which is complex and varied, with immense potential implications for ownership and distribution of resources and the bargaining strength that are likely to determine the food security status of various farming households. Furthermore, the contribution of households towards agricultural production differs according to the way family organizes itself. This study was carried out to determine the influence of family structures on food security status of farming households in Alice, South Africa. Data were collected from 120 farming households’ selected using purposive sampling method. To collect data, a well-structured questionnaire was administered through face-to-face interviews. Consequent to that, the data were analyzed using descriptive statistics, and binary logistic regression model. The dominant family structures are nuclear, single-parent, working parent and cohabiting. The analysis revealed that nuclear family where father, mother and their children have access to labour and financial resources could be more comfortable than single parent family. Working parents would probably be more food secure because both parents are able to combine incomes while food insecurity might exist within cohabiting families since the union is less stable because of scarce resources occasioned by their inability to combine their resources to pursue a common goal. The results further revealed that single parent family structures and socio-economic characteristics like age, marital status and year of education of the household head were significant in terms of their influence on food security. The study therefore, recommends that old people should be encouraged to participate in agricultural production due to the wealth of experience gathered over the years. It is probably safe to conclude that encouraging marriage would provide better opportunities to raise the necessary capital to support positive productivity changes that would have implications for enhanced food availability and affordability.
- Full Text:
- Authors: Ijila, Olusegun Jeremiah
- Date: 2018
- Subjects: Food security Families--South Africa--Eastern Cape Farms, Small
- Language: English
- Type: Thesis , Masters , Agricultural Economics
- Identifier: http://hdl.handle.net/10353/11537 , vital:39081
- Description: Achieving food security in sub-Saharan Africa remains a major challenge despite efforts made by a majority of the countries to reduce abject poverty and food insecurity. Just as these countries prioritized food security under the Millennium Development Goals (MDGs), they are equally putting it on top of the agenda under the Sustainable Development Goals (SDGs). In the face of the political and economic developments seen in the country since 1994, South Africa is overwhelmed by poverty and unemployment. But efforts to address these problems have not given due recognition to the question of family structure which is complex and varied, with immense potential implications for ownership and distribution of resources and the bargaining strength that are likely to determine the food security status of various farming households. Furthermore, the contribution of households towards agricultural production differs according to the way family organizes itself. This study was carried out to determine the influence of family structures on food security status of farming households in Alice, South Africa. Data were collected from 120 farming households’ selected using purposive sampling method. To collect data, a well-structured questionnaire was administered through face-to-face interviews. Consequent to that, the data were analyzed using descriptive statistics, and binary logistic regression model. The dominant family structures are nuclear, single-parent, working parent and cohabiting. The analysis revealed that nuclear family where father, mother and their children have access to labour and financial resources could be more comfortable than single parent family. Working parents would probably be more food secure because both parents are able to combine incomes while food insecurity might exist within cohabiting families since the union is less stable because of scarce resources occasioned by their inability to combine their resources to pursue a common goal. The results further revealed that single parent family structures and socio-economic characteristics like age, marital status and year of education of the household head were significant in terms of their influence on food security. The study therefore, recommends that old people should be encouraged to participate in agricultural production due to the wealth of experience gathered over the years. It is probably safe to conclude that encouraging marriage would provide better opportunities to raise the necessary capital to support positive productivity changes that would have implications for enhanced food availability and affordability.
- Full Text:
Performance comparison of the residential types of air source heat pump water heaters in South Africa due to the refrigerant thermo-physical properties
- Authors: Sikhonza, Mandlenkosi
- Date: 2018
- Subjects: Heat pumps Water heaters
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/9275 , vital:34317
- Description: Globally hot water heating contributes enormously to the increase in energy consumption in the residential sector. Coal being a fossil fuel and non-renewable source of energy remains the major source used for electricity generation. The burning of coal is the primary cause of CO2 emission into the environment which causes climate change and global warming. Energy efficiency and renewable energy technologies were employed as one of the alternative ways of reducing global warming. In most residential areas in South Africa, the water heating generates 30 -50percent of the monthly electricity bill (Zhang and Huan, 2013). In this light, residential load management (RLM) is a significant part of the load management programme of Eskom’s overall demand side management strategy. Through RLM, the electricity load is being transferred from peak times to off times by switching the geysers during peak hours because geysers consume more electricity and contribute significantly to the national grid constraint problem (Eskom, 2012).
- Full Text:
- Authors: Sikhonza, Mandlenkosi
- Date: 2018
- Subjects: Heat pumps Water heaters
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/9275 , vital:34317
- Description: Globally hot water heating contributes enormously to the increase in energy consumption in the residential sector. Coal being a fossil fuel and non-renewable source of energy remains the major source used for electricity generation. The burning of coal is the primary cause of CO2 emission into the environment which causes climate change and global warming. Energy efficiency and renewable energy technologies were employed as one of the alternative ways of reducing global warming. In most residential areas in South Africa, the water heating generates 30 -50percent of the monthly electricity bill (Zhang and Huan, 2013). In this light, residential load management (RLM) is a significant part of the load management programme of Eskom’s overall demand side management strategy. Through RLM, the electricity load is being transferred from peak times to off times by switching the geysers during peak hours because geysers consume more electricity and contribute significantly to the national grid constraint problem (Eskom, 2012).
- Full Text:
Modelling false positive reduction in maritime object detection
- Authors: Nkele, Nosiphiwo
- Date: 20xx
- Subjects: Computer vision Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17168 , vital:40862
- Description: Target detection has become a very significant research area in computer vision with its applications in military, maritime surveillance, and defense and security. Maritime target detection during critical sea conditions produces a number of false positives when using the existing algorithms due to sea waves, dynamic nature of the ocean, camera motion, sea glint, sensor noise, sea spray, swell and the presence of birds. The main question that has been addressed in this research is how can object detection be improved in maritime environment by reducing false positives and promoting detection rate. Most of Previous work on object detection still fails to address the problem of false positives and false negatives due to background clutter. Most of the researchers tried to reduce false positives by applying filters but filtering degrades the quality of an image leading to more false alarms during detection. As much as radar technology has previously been the most utilized method, it still fails to detect very small objects and it may be applied in special circumstances. In trying to improve the implementation of target detection in maritime, empirical research method was proposed to answer questions about existing target detection algorithms and techniques used to reduce false positives in object detection. Visible images were retrained on a pre-trained Faster R-CNN with inception v2. The pre-trained model was retrained on five different sample data with increasing size, however for the last two samples the data was duplicated to increase size. For testing purposes 20 test images were utilized to evaluate all the models. The results of this study showed that the deep learning method used performed best in detecting maritime vessels and the increase of dataset improved detection performance and false positives were reduced. The duplication of images did not yield the best results; however, the results were promising for the first three models with increasing data.
- Full Text:
- Authors: Nkele, Nosiphiwo
- Date: 20xx
- Subjects: Computer vision Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17168 , vital:40862
- Description: Target detection has become a very significant research area in computer vision with its applications in military, maritime surveillance, and defense and security. Maritime target detection during critical sea conditions produces a number of false positives when using the existing algorithms due to sea waves, dynamic nature of the ocean, camera motion, sea glint, sensor noise, sea spray, swell and the presence of birds. The main question that has been addressed in this research is how can object detection be improved in maritime environment by reducing false positives and promoting detection rate. Most of Previous work on object detection still fails to address the problem of false positives and false negatives due to background clutter. Most of the researchers tried to reduce false positives by applying filters but filtering degrades the quality of an image leading to more false alarms during detection. As much as radar technology has previously been the most utilized method, it still fails to detect very small objects and it may be applied in special circumstances. In trying to improve the implementation of target detection in maritime, empirical research method was proposed to answer questions about existing target detection algorithms and techniques used to reduce false positives in object detection. Visible images were retrained on a pre-trained Faster R-CNN with inception v2. The pre-trained model was retrained on five different sample data with increasing size, however for the last two samples the data was duplicated to increase size. For testing purposes 20 test images were utilized to evaluate all the models. The results of this study showed that the deep learning method used performed best in detecting maritime vessels and the increase of dataset improved detection performance and false positives were reduced. The duplication of images did not yield the best results; however, the results were promising for the first three models with increasing data.
- Full Text:
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