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18 March 2020 | Story Leonie Bolleurs | Photo Supplied
Solar car Team
Excited about a first for the UFS, Team UFS is entering the 2020 Sasol Solar Challenge. From the left, front, are: Fouché Blignaut, Mechatronic Engineering; Nathan Bernstein, Agricultural Engineering; Lucas Erasmus, Physics; middle: Barend Crous, Manufacturing and Instrumentation; Hendrik van Heerden, Physics (team leader); Antonie Fourie, Physics; Prof Danie Vermeulen, Dean of the Faculty of Natural and Agricultural Sciences (team director); Prof Koos Terblans, Head of the Department of Physics; Theo Gropp, Mechanical Engineering; back: Louis Lagrange, Head of the Department of Engineering; and Mark Jacson, Electronics.

An interdepartmental team from the University of the Free State (UFS) has announced that it will enter and participate in the 2020 Sasol Solar Challenge, scheduled to take place from 11 to 19 September this year. 

For the challenge, Team UFS will build a self-propelled manned vehicle that uses solar power systems to travel from point A to point B. The 14-member team of the UFS will travel on public roads from Pretoria to Cape Town via a predefined route over eight days. They will compete against more than 15 other teams, both local and international. The team that finishes with the greatest distance covered within the allotted time, will win the race. Teams will race every day between 07:30 and 17:00.

The four drivers to operate the vehicles will be selected from participating UFS departments in the coming months.

First solar car for the UFS
Dr Hendrik van Heerden from the Department of Physics has been planning the solar car project – Lengau (meaning Cheetah in Sesotho) – over the past year. He will start assembling the car in the next month together with colleagues and students from both the Departments of Physics and Engineering Sciences (EnSci).

Not only is this a dream come true, but it is also an opportunity for the UFS to show that they can do this. “We do not need the backing of a large and long-established engineering department to build a car like this, a young and vibrant team can do just as much!”, says Dr Van Heerden, who plans to complete the car within a few months, ready to be calibrated and tested later in June.

Capacity in green and sustainable engineering
“The ability of Team UFS to participate is possible due to recent research developments on photovoltaic technologies (solar cells) in the Department of Physics, a well-established leader in the field of surface and material sciences. The university also has established capacity in the fields of photoluminescence and nanomaterials (nanomaterials in energy storage). Additionally, with the establishment of EnSci, the university has expanded into this field, which will bring building capacity in the area of green and sustainable engineering to the project,” says Dr Van Heerden.

Promoting development into green technologies and 4IR
According to Dr Van Heerden, it is clear that the university wishes to become a strong role player in the development and utilisation of green energy, as can be seen in the implementation of relevant technologies on its various campuses. “Thus, for the UFS to be recognised in this research area, it is important to participate in related ‘green’ events where staff and students can build their capacity of practical knowledge by constructing participation equipment such as the solar car.”

He believes that this project has the potential to become a strong base for student training and capacity building in all technological fields, which can promote base development to 4IR.

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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