Students with disabilities’ experience in South African higher education – a synthesis of literature

This state of the art review paper offers a synthesis of published studies on students with disabilities’ experience in South African higher education since 1994, when a democratically elected government came to office. The article presents a review of published studies describing the experiences of students with disabilities in South African higher education (SAHE) in the period 1994-2017. In order to obtain a perspective on the experiences of students with disabilities in South African higher education institutions, a synthesis of the findings and implications of South African studies relating to students with disabilities in SAHE is provided. Three aspects will be discussed namely: (a) conceptualisation of disability; (b) access, inclusion and participation in higher education; and (c) supporting mechanisms for students with disabilities. From this, challenges, areas needing further studies, lessons learnt, approaches and policy implications for policy-practitioners and institutions are suggested

Students with disabilities’ experience in South African higher education – a synthesis of literature

This state of the art review paper offers a synthesis of published studies on students with disabilities’ experience in South African higher education since 1994, when a democratically elected government came to office. The article presents a review of published studies describing the experiences of students with disabilities in South African higher education (SAHE) in the period 1994-2017. In order to obtain a perspective on the experiences of students with disabilities in South African higher education institutions, a synthesis of the findings and implications of South African studies relating to students with disabilities in SAHE is provided. Three aspects will be discussed namely: (a) conceptualisation of disability; (b) access, inclusion and participation in higher education; and (c) supporting mechanisms for students with disabilities. From this, challenges, areas needing further studies, lessons learnt, approaches and policy implications for policy-practitioners and institutions are suggested

Effects of different building blocks designs on the statistical characteristics of Automated Zone-design Tool output areas

Prior to any census, the country usually gets demarcated into small geographic units called census enumeration areas, districts or blocks. In most countries, these small geographic units are also used for census dissemination. In cases where they are not used for census release, they are normally used as building blocks for developing output areas or they are aggregated to higher spatial levels in an effort to preserve privacy or confidentiality. Buildings blocks are therefore, of significant importance towards results that could be drawn from either aggregated higher level or from output areas developed using these small geographic areas. This paper aimed at evaluating the effects of different building blocks on the statistical characteristics of output areas generated using the Automated Zone-design Tool (AZTool) computer program. Different spatial layers (such as Enumeration Areas (EAs), Small Area Layers (SALs) and SubPlaces) from the 2001 census data were used as building blocks for the generation of census output areas with AZTool program in both rural and urban areas of South Africa. One way-Analysis of Variance (ANOVA) was also performed to determine statistical significance of the AZTool results. Results showed that the AZTool output areas generated from smaller areas (EAs and SALs) tend to be more homogeneous than the ones generated from larger areas (SubPlaces) when using dwelling type and geotype as homogeneity variables. The output areas from smaller areas also had narrower population distribution and more compact shapes than their counter-parts. In addition, the AZTool optimised output areas from the smaller areas allowed a clear distinction of the scale effects than output areas from larger areas. It was concluded that indeed different building blocks did have an impact on the statistical qualities of the AZTool optimised output areas in both rural and urban settings in South Africa.Keywords: AZTool; Building blocks; Enumeration areas; Output areas; Scale effects; Small Area Layers; SubPlace

Land Use Land Cover Change in the fringe of eThekwini Municipality: Implications for urban green spaces using remote sensing

Concerns on urban environmental quality, increasing knowledge on impacts of climate change and pursuit for sustainable development have increased the need for past, current and future knowledge on the transformation of remnant urban fringe green ecosystems. Using land-cover change modeler and a Markov chain analysis on multi-temporal SPOT imagery, this study sought to determine a twenty two-year past and future land use and land cover trend and its implication on green spaces in an eThekwini Municipal Area’s peripheral settlement. Results show a consistent pattern of decline in land use and land cover types associated with green spaces and an increase in impervious surfaces. The study confirms recent urban bio-physical transformation and anticipated increased pressure on peripheral urban green spaces in eThekwini Municipality. These changes can be attributed to natural urban growth and government led efforts like the Reconstruction and Development Programme. Findings in the study highlight the challenges faced by eThekwini Municipality, and indeed other South Africa’s urban areas in maintaining urban green spaces and mitigating related implications like those associated with climate change. This study further demonstrates the value of multi-temporal remotely sensed datasets in planning, optimization and sustainable management of urban landscapes

Assessment of the Contribution of WorldView-2 Strategically Positioned Bands in Bracken fern (Pteridium aquilinum (L.) Kuhn) Mapping

In the eThekwini Metropolitan Area, mitigation of the Bracken fern (Pteridium aquilinum (L.) Kuhn) invasion within the KwaZulu-Natal Sandstone Sourveld (KZNSS) has been identified as a major environmental priority. To facilitate informed interventions, reliable Bracken fern spatial distribution is necessary. Earlier efforts to map the fern using lower spatial and spectral resolution imagery have been unsuccessful. Consequently, this study sought to determine the reliability of the “new generation” World View-2 (WV-2) image characterised by higher spatial and spectral resolution in delineating the fern invaded areas. The eight band WV2 image was atmospherically corrected and spectrally resized as the SPOT-5 wavebands, additional bands and all bands. The classification accuracy was compared to results from the SPOT-5 image. Results showed that classification based on WV-2s additional bands had superior classification accuracy than the rest of the categories. Furthermore, classification based on all the WV-2s bands and the traditional bands perfomed better than the SPOT-5 image in delineating areas covered by the fern. These findings indicate the value of of the “new generation” imagery characterised by higher spatial and spectral resolution in improving the accuracy of the fern invaded landscapes

Exploration of the academic lives of students with disabilities at South African universities: Lecturers' perspectives

Background: A decade has passed since South Africa signed and ratified the Convention on the Rights of Persons with Disabilities, a human rights treaty that protects the rights and dignity of people with disabilities. However, not much have changed for students with disabilities. Objectives: The aim of this study was to explore lecturers’ experiences with, and perspectives on, disability as well as with students with disabilities. It was hoped that this would contribute to the ongoing policy debates about diversity, inclusion and support for students with disabilities at universities. Methods: In an effort to understand the lives of students with disabilities better, a study which included students with disabilities, lecturers and disability supporting staff was conducted at two South African universities – University of the Free State and University of Venda. The paper takes a snapshot view of four lecturers and their perceptions of the lives of students with disabilities at their respective universities. Results and Conclusion: Although most disability literature report students with disabilities blaming lecturers for their failure to advance their needs, this paper highlights that the education system needs to be supportive to lecturers for the inclusive agenda to be realised. An argument is made for a more comprehensive approach towards a national disability policy in higher education involving many stakeholders. Without a broader understanding of disability, it will be difficult to engage with the complex ways in which inequalities emerge and are sustained

Discrimination of tomato plants (solanum lycopersicum) grown under anaerobic baffled reactor effluent, nitrified urine concentrate and commercial hydroponic fertilizer regimes using multi-source satellite data

We evaluate the detection and discriminative strength of three different satellite spectral settings, namely, HyspIRI, the forthcoming Landsat 9 and Sentinel 2-MSI, in mapping tomato (Solanum lycopersicum) plants grown under hydroponic system using humanexcreta derived materials (HEDM), namely, anaerobic baffled reactor (ABR) effluent and nitrified urine concentrate (NUC) and commercial hydroponic fertilizer mix (CHFM) as nutrient sources. Partial least squares – discriminant analysis (PLS-DA) and discriminant analysis (DA) were applied to discriminate tomatoes grown under these different nutrient sources. Results of this study showed that spectral settings of HyspIRI sensor can better discriminate tomatoes grown under different fertilizer regimes when compared to Landsat 9 OLI and Sentinel-2 MSI spectral configurations. For instance, based on DA algorithm, HyspIRI exhibited high overall accuracy of 0.99 and a kappa statistic of 0.99 whereas Landsat OLI and Sentinel-2 MSI exhibited over accuracies of 0.94 and 0.95 as well as kappa statistics of 0.79 and 0.85, respectively. Further, the performance of DA was significantly different (α = 0.05) from that of PLS-DA based on the MaNemar tests. Overall, the performance of HyspIRI, Landsat 9 OLI-2 and Sentinel-2 MSI data seem to bring new opportunities for crop monitoring at farm scale

The Problem of Data Extraction in Social Media: A Theoretical Framework

In today's rapidly evolving digital landscape, the pervasive growth of social media platforms has resulted in an era of unprecedented data generation. These platforms are responsible for generating vast volumes of data on a daily basis, forming intricate webs of patterns and connections that harbor invaluable insights crucial for informed decision-making. Recognizing the significance of exploring social media data, researchers have increasingly turned their attention towards leveraging this data to address a wide array of social research issues. Unlike conventional data collection methods such as questionnaires, interviews, or focus groups, social media data presents unique challenges and opportunities, demanding specialized techniques for its extraction and analysis. However, the absence of a standardized and systematic approach to collect and preprocess social media data remains a gap in the field. This gap not only compromises the quality and credibility of subsequent data analysis but also hinders the realization of the full potential inherent in social media data. This paper aims to bridge this gap by presenting a comprehensive framework designed for the systematic extraction and processing of social media data. The proposed framework offers a clear, step-by-step methodology for the extraction and processing of social media data for analysis. In an era where social media data serves as a pivotal resource for understanding human behavior, sentiment, and societal dynamics, this framework offers a foundational toolset for researchers and practitioners seeking to harness the wealth of insights concealed within the vast expanse of social media data

Institutionalizing Provider-Initiated HIV Testing and Counselling for Children: An Observational Case Study from Zambia

Background: Provider-initiated testing and counselling (PITC) is a priority strategy for increasing access for HIV-exposed children to prevention measures, and infected children to treatment and care interventions. This article examines efforts to scale-up paediatric PITC at a second-level hospital located in Zambia’s Southern Province, and serving a catchment area of 1.2 million people. Methods and Principal Findings: Our retrospective case study examined best practices and enabling factors for rapid institutionalization of PITC in Livingstone General Hospital. Methods included clinical observations, key informant interviews with programme management, and a desk review of hospital management information systems (HMIS) uptake data following the introduction of PITC. After PITC roll-out, the hospital experienced considerably higher testing uptake. In a 36-month period following PITC institutionalization, of total inpatient children eligible for PITC (n = 5074), 98.5 % of children were counselled, and 98.2 % were tested. Of children tested (n = 4983), 15.5 % were determined HIVinfected; 77.6 % of these results were determined by DNA polymerase chain reaction (PCR) testing in children under the age of 18 months. Of children identified as HIV-infected in the hospital’s inpatient and outpatient departments (n = 1342), 99.3 % were enrolled in HIV care, including initiation on co-trimoxazole prophylaxis. A number of good operational practices and enabling factors in the Livingstone General Hospital experience can inform rapid PIT

Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery

Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phenotyping efforts. The objective of this study was to select principal features extracted from UAV imagery and critical growth stages that contributed the most in explaining winter wheat grain yield. Five dates of multispectral images and seven dates of RGB images were collected by a UAV system during the spring growing season in 2018. Two classes of features (variables), totaling to 172 variables, were extracted for each plot from the vegetation index and plant height maps, including pixel statistics and dynamic growth rates. A parametric algorithm, LASSO regression (the least angle and shrinkage selection operator), and a non-parametric algorithm, random forest, were applied for variable selection. The regression coefficients estimated by LASSO and the permutation importance scores provided by random forest were used to determine the ten most important variables influencing grain yield from each algorithm. Results: Both selection algorithms assigned the highest importance score to the variables related with plant height around the grain filling stage. Some vegetation indices related variables were also selected by the algorithms mainly at earlier to mid growth stages and during the senescence. Compared with the yield prediction using all 172 variables derived from measured phenotypes, using the selected variables performed comparable or even better. We also noticed that the prediction accuracy on the adapted NE lines (r = 0.58–0.81) was higher than the other lines (r = 0.21–0.59) included in this study with different genetic backgrounds. Conclusions: With the ultra-high resolution plot imagery obtained by the UAS-based phenotyping we are now able to derive more features, such as the variation of plant height or vegetation indices within a plot other than just an averaged number, that are potentially very useful for the breeding purpose. However, too many features or variables can be derived in this way. The promising results from this study suggests that the selected set from those variables can have comparable prediction accuracies on the grain yield prediction than the full set of them but possibly resulting in a better allocation of efforts and resources on phenotypic data collection and processing