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Innovative wool creations shine at Karoo Winter Wool Festival

25 June 2024 | Story Martinette Brits | Photo Carine van Zyl

OVK Innovation Competition Gala Event 2024 — The prize winners at the gala evening of the OVK Innovation Competition on 13 June 2024. From the left, in front: Emily Segame, Sophia Mekhoe, Sarah Lenong, Maserame Sebonyane, Ntabiseng Ndabeni. At the back: Elizabeth Mnwana, Carlize van Zyl (winner of the competition), Carien Vorster, Jana Vermaas, Doretha Jacobs, and Nelly Olayi.

The University of the Free State (UFS) Wool Wise Community Project was recognised for its innovative use of wool, receiving accolades at the OVK Innovation Competition held in conjunction with the Karoo Winter Wool Festival in Middelburg from 13–16 June 2024.According to Carien Vorster, project manager from the Department of Sustainable Food Systems and Development, participants were tasked with crafting practical items from wool. Their creativity shone through in their design of a lampshade, earning them second place. Doretha Jacobs, a lecturer in the Department of Sustainable Food Systems and Development, focused on making felt from Dorper fibre, noting that while Dorper sheep are primarily bred for meat, they sought to repurpose fibres that would otherwise be discarded.

The team achieved third place with their cushion, featuring a front made entirely of merino wool felt and a back crafted from upholstery fabric. “Each cushion contains a 100% duck feather inner, and their uniqueness lies in the hand-dyed wool and hand-placed designs on each felt piece,” explains Vorster.

Other notable entries from different teams included a duvet inner, shoe insoles, and oven gloves. The top prize went to a hand-felted coat.

Community project empowers local women in wool craft

The UFS Wool Wise Community Project originated as a spin-off from the Regional Universities Forum for Capacity Building (Ruforum) project, initiated in 2019 by the UFS Department for Sustainable Food Systems and Development.

According to Vorster, the Ruforum project encompasses various components such as research, farmer support, and community development, with a particular emphasis on community upliftment programmes. "Since 2019, we have conducted numerous wool workshops and training sessions where local women have participated to learn about wool processing," she explains.

"From these events, we identified women who are now integral to our programme. Their skills range from sewing, felt making, and hand embroidery, to knitting."

The project features eight women who create diverse products from scratch: Elizabeth Mnwana, Emily Segame, Georgina Collins, Maserame Sebonyane, Nelly Olayi, Sarah Lenong, Sophia Mekhoe, and Ntabiseng Ndabeni.

She emphasises that the project also manufactures conference bags for various events and stands as one of UFS's most successful community initiatives. "Ultimately, this project has the potential to become self-sustaining, with proceeds supporting the salaries of the eight women," Vorster concludes.

Competition boosts visibility and market reach

Participating in initiatives like the OVK Innovation Competition motivates them to stay current and benchmark their efforts against other businesses or individuals involved in felt product creation.

"Winning a competition can also significantly uplift team morale," remarks Vorster.

"Securing second and third place in this competition translates to increased visibility and marketing opportunities for us. This is crucial as we aim to expand our market reach and establish a sustainable income stream for the project," she concludes.

A worker packs the carded wool in layers preparing for the felting process.

The cushion (in front), secured the team third place at the OVK Innovation Competition.

The lampshade secured the team second place at the OVK Innovation Competition.

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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