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25 September 2019 | Story Zamuxolo Feni | Photo Liza Crawley
Read More Photo SANRAL
SANRAL Chief Executive Officer Skhumbuzo Macozoma and UFS Rector and Vice-Chancellor Prof Francis Petersen cutting a cake to mark 10 years of collaboration between the two institutions.

The Science-for-the-Future (S4F) programme is fundamental to generating the required pipeline for technologically skilled entrepreneurs and workers by focusing on Mathematics and Science support to learners, teachers, and parents.

This is according to the South African National Roads Agency Limited (SANRAL) Chief Executive Officer, Skhumbuzo Macozoma, who delivered a keynote address at the Annual Science for the Future Summit held at the University of the Free State (UFS) on 20 September.

The S4F is a partnership between the UFS and SANRAL, with the fundamental purpose to train Maths and Science teachers and to support learners and parents. The programme has now been extended to six other universities, namely Nelson Mandela University and Walter Sisulu University in the Eastern Cape; the University of Limpopo, University of KwaZulu-Natal, and the two recently established universities, the University of Mpumalanga and the Sol Plaatje University in the Northern Cape.

Dr Cobus van Breda, the Programme Director for the UFS S4S, said they developed the Family Math and Key Concepts in Science programmes to address issues that prevent learners from excelling in these critical subjects. It seeks to improve the content knowledge of teachers and provide them with more skills-teaching resources.

Macozoma said: “I am proud and deeply honoured to stand before you today in the strength of a successful 10-year partnership with the University of the Free State which we are celebrating here today, together with the hosting of the Annual Science for the Future Summit.”  More than 300 teachers attended the summit.

Planning for the future

He indicated that SANRAL's long-term strategy, Horizon 2030, instructed the development of a new human-resources strategy for the organisation, which has identified three pillars that underpin SANRAL's human-capital development initiatives, namely people, skills, and performance.

“The strategic opportunities identified by SANRAL include capitalising on the opportunity presented by the digital revolution to create a new generation of technologically skilled entrepreneurs and workers; returning to good and ethical governance in both the public and private sectors; bringing back the prestige of serving the citizens of SA through state institutions: fashioning SANRAL as an employer of the future and delivering technical skills to address the glaring skills gap in engineering and other domains,” he said.

Macozoma stated that SANRAL has also decided to review and rationalise its support to institutions of higher learning in order to grow the footprint of its support programmes, increase the impact, and ensure equity.

Beyond this, he stated that SANRAL wanted to ensure that learners are equipped with fundamental competencies that are essential to complement academic teachings, including critical thinking, creativity, collaboration, communication, information literacy, media literacy, technology literacy, and flexibility.         

Facing 4IR head on

Macozoma said the most important characteristics of the Fourth Industrial Revolution that must be taken into consideration by those who aim to survive it, drive it, and benefit from it, is a smart customer – who is informed and dictates what services he/she wants and how they should be delivered; technology at the fingertips – which will enable rapid, real-time, borderless services to information, services, and technology as an enabler – bringing efficiency to logistics, mobility, medicine, education, industries, the economy, the military, global trade, and politics.  

Working closely with school and society

UFS Rector and Vice-Chancellor, Prof Francis Petersen, said the university has an important responsibility to generate knowledge that will impact society positively.

“We have a role to work closely with our schools and society so that we can understand each other’s needs,” he said.

“We need to strengthen collaboration with all our partners so that we can travel further and make an impact in our society,” said Prof Petersen.

One of the participating teachers in the S4F programme, Grace Molante, from a primary school in Zastron, said: “It is programmes such as these that instil hope in us as teachers. Some learners could find Maths and Science very difficult and challenging subjects, but this programme makes problem solving more enjoyable and practical.”

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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