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Celebrating diversity: UFS hosts vibrant Multilingual Mokete

25 September 2024 | Story Teboho Mositi | Photo Ian van Straaten

Qwaqwa Mokete 2024 — The University of the Free State Qwaqwa Campus celebrated diversity as the Academy of Multilingualism recently hosted the Kovsies Multilingual Mokete, themed: ‘Our Diversity is Our Strength.

The University of the Free State (UFS) Qwaqwa Campus pulsed with vibrant energy on 13 September 2024 as the Academy of Multilingualism hosted its annual Kovsies Multilingual Mokete. This year's theme, ‘Our Diversity is Our Strength’, resonated throughout the day, celebrating the richness of languages and cultures within the UFS community.

The event served as a platform for students and staff to showcase their diverse heritages through traditional attire, poetry, storytelling, drama, music, and dance. A delectable spread of cultural cuisine further enriched the experience, fostering a sense of belonging and acceptance.

Promoting inclusivity and multilingualism

The Mokete aligns with the UFS' multilingual language policy, implemented in 2016. This policy emphasises the importance of fostering inclusivity and social cohesion through language. It aims to create a dynamic learning environment that celebrates the diverse languages spoken within the UFS community.

In her welcome address, the Director of the Academy for Multilingualism, Dr Nomalungelo Ngubane, said the University of the Free State took a significant step in 2016 towards fostering a more inclusive and diverse campus by adopting a multilingual language policy. This policy recognised the importance of embracing multilingualism as a social asset and aimed to promote social cohesion, diversity, and inclusivity. “The Mokete Multilingual Festival serves as a tangible manifestation of this commitment. It provides a platform for all members of our UFS community to celebrate and appreciate the rich tapestry of languages, cultures, and traditions that we bring to our university. By showcasing our diverse languages, indigenous food, traditional outfits, and more, we not only honour our individual heritage but also strengthen our sense of belonging and unity,” explained Dr Ngubane.

The Mokete is more than just a cultural event; it is a purposeful act of embracing our diversity and educating one another about the value of multilingualism. Through this celebration, we strive to create a more inclusive and cohesive campus where everyone feels valued and respected.

"We want everyone to feel welcome on our campuses," stated Teboho Manchu, Campus Vice-Principal: Support Services, during his opening address. "The Mokete allows each culture and language group to learn from one another, preparing our students for a multilingual and multicultural world, while staying connected to their own heritage."

A celebration of talent and cultural expression

The day unfolded with heart-warming moments of appreciation. Manchu extended his gratitude to distinguished guests, colleagues, and students. The highlight of the event was Ntate Stunna, a captivating Sesotho musician who energised the audience with his music. Local artists Bomme ba Ipopeng and Tears of Joy also contributed to the electrifying atmosphere. Their performances, alongside the diverse cultural presentations, fostered a sense of pride and identity within the UFS community.

A commitment to a language-rich environment

The Kovsies Multilingual Mokete exemplifies the UFS' commitment to multilingualism. By celebrating diverse languages and cultures, the university fosters a sense of belonging and prepares its students for success in a globalised world.

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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