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19 November 2018
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Story Charlene Stanley
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Photo Charlene Stanley
Prof John Mubangizi, Dean of the Faculty of Law, encouraged delegates at the Fifth Annual International Mercantile Conference to share ideas on best international practice in their various fields.
“Don’t say anything online that you wouldn’t want plastered on a billboard with your face on it.”
This famous quote by international tech expert Erin Bury should be a guiding light when it comes to online habits in the workplace, according to Francois Cilliers, UFS Lecturer in Mercantile Law.
In his presentation Could Social Media be the Gateway to Employment Discrimination? he warned that employees have a responsibility not to bring their employers in disrepute through their comments on social media.
“Posts, updates, tweets, and comments are considered to be publications and can therefore never be seen as privileged information,” he explained.
Responsibility on employees and employers alike
He pointed out that employers also had a responsibility regarding the way in which they use the information about prospective employees obtained via social media.
“Nowadays, approximately 75% of companies hire through social media. In the US, recruiting companies spend hours researching candidates, making full use of what they can find on social media. It was found that 50–80% of employers frowned upon posts and pictures featuring drug and alcohol abuse, profanity, and bad grammar.”
He warned that employers needed to tread lightly, as a decision not to employ someone as a result of information on the prospective employee’s political views and sexual orientation could constitute unfair discrimination as set out in the Employment Equity Act.
“An employer who wishes to use a screening process (utilising social media) has to prove that the information and the process is objectively necessary and can be justified with reference to the inherent requirements of the job,” he explained.
“As technology and electronic systems advance, so too should the applicable labour laws.”
Cilliers’ presentation formed part of the Fifth Annual International Mercantile Law Conference recently hosted by the Faculty of Law on the Bloemfontein Campus.
Incorporating new technology in teaching and research
“This conference is an opportunity to share ideas on best practice in what is perceived as a ‘difficult’ field within Law,” said Prof John Mubangizi, Dean of the Faculty of Law, as he opened the proceedings. Topics in the discussion sessions ranged from Racism in the workplace and The underrepresentation of females in the judiciary, to Decriminalisation of cannabis: A recipe for healthy employer-employee relations?
“Conferences such as these help us to take advantage of the newest developments in technology to advance our teaching and research,” said Prof Mubangizi.
“To quote Einstein: ‘We can’t solve problems by using the same kind of thinking we used when we created them.’”
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
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.