https://ir.unisa.ac.za/handle/10500/460 Sun, 20 Sep 2026 08:13:03 GMT 2026-09-20T08:13:03Z https://ir.unisa.ac.za/handle/10500/32950 Development of a framework for ethical and cyber-safe robotics in the service industry Mordi, Emmanuel Ifie The increased use of service robotics in sectors like hospitality, healthcare, and logistics presents opportunities but also challenges in cyber-safety, ethics, and human-robot interaction (HRI). While progress has been made, current frameworks are fragmented or focus too much on technical efficiency, neglecting ethics, social issues, and data protection. This is especially true in emerging economies where imported robots often conflict with local cultural and regulatory standards. This study introduces a comprehensive conceptual framework called the Socio-Tactical Integrated Framework to guide ethical, cyber-safe, and contextually suitable deployment of service robotics (ACERBOTICS). A Design Science Research approach was used to develop a structured theoretical model that addresses gaps in the current research. The study includes a systematic literature review, which provides a basis for identifying and understanding existing critical gaps in the literature and design criteria for a proposed research artefact to address the gaps. Following the development of the research artefact, an expert evaluation was conducted using a questionnaire with both closed and open-ended questions to assess the relevance, clarity, applicability, and ethical robustness of the proposed framework. Expert evaluation (n = 47) demonstrated high coherence, ethical robustness, and practical feasibility, while also identifying areas of improvement, including contextual adaptability and operational scalability. These insights informed the development of a refined framework that integrates ethical governance, cyber-safety resilience, socio-technical alignment, and human-centred design principles. This study proposes a unified, theoretically grounded, and practically applicable framework for governing autonomous service robotics in diverse socio-technical environments. The proposed framework provides a basis for future empirical validation and policy development, particularly in African and other emerging-economy contexts. By integrating cyber-safety, ethics, and service robotics, this research advances scholarly understanding and promotes responsible innovation in the field of intelligent robotic systems in the service industry. Fri, 27 Feb 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32950 2026-02-27T00:00:00Z https://ir.unisa.ac.za/handle/10500/32937 A framework for end-user compliance with the information security policy in government institutions Lekhuleni, Sakhile Charity Dories Employees’ non-adherence causes most security breaches in both private and public organisations to information security policies (ISPs). The purpose of this research is to develop a framework for end-user compliance with ISPs in government departments. A framework that integrates all factors that enhance end-user compliance will assist organisations and information security managers in understanding the elements that affect end-user compliance. A systematic literature review was conducted using the PRISMA method to identify the factors and components contributing to the development of the framework. Moreover, semi-structured interviews were conducted with government officials from two Mpumalanga departments and with experts in information security and ISP compliance to refine and validate the framework. The outcome of the interviews with government officials and experts resulted in the inclusion of additional components and factors to the conceptual ECISP framework. The outcome of this process is a validated framework intended to enhance end-user compliance with ISPs within government institutions. The main aim of the research study is to integrate literature findings with practical insights from government officials and experts to develop, refine, and validate a framework for end-user compliance with ISPs in Government departments (the ECISP Framework). The ECISP Framework provides guidance that enables organisations to address specific challenges related to end-user compliance with ISPs, thereby improving the likelihood of achieving end-user compliance with ISPs. Thu, 01 Jan 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32937 2026-01-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/32818 I am a “Thou” Therefore “I am”: Embedding Values and Norms into Intelligent Systems Nkohla-Ramunenyiwa, Thando; Mnkandla , Ernest The Enlightenment Era ushered in a platform for science to mark its epistemological territory, which has gained a following in a number of disciplines. One of these disciplines is technology. Technological advancements have progressed exponentially, to the point that on the ethics front, it has become challenging to catch up with this growth. Intelligent systems are a dimension of technological advancements that have, on the one hand, brought a considerable amount of convenience for society and, on the other hand, presented ethical concerns that require attention. At times complementary with capitalistic ideals, intelligent systems seem to be more appealing to the consumer than to the individual as a moral agent. Consequently, this paper aims to recommend a way forward when it comes to embedding values and norms into intelligent systems. Mon, 29 Jul 2019 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32818 2019-07-29T00:00:00Z https://ir.unisa.ac.za/handle/10500/32778 Multi-lingual emotion detection in speech using hybrid neural network architectures Norval, Michael John The advancement of Deep Learning has revolutionised numerous fields, including humancomputer interaction (HCI) and emotion detection. In speech recognition, voice assistants such as Apple's Siri, Microsoft's Cortana, and Google's Assistant have become integral to everyday technology use. However, current emotion detection systems often need more support for African languages, presenting a significant research gap. The aim and objectives of the study are to develop a Speech Emotion Recognition (SER) system tailored to South African languages, with a specific focus on Afrikaans. The primary objective is to compile an Afrikaans speech corpus for emotion recognition. Furthermore, it explores hybrid neural network architectures combining CNN, Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks for improved accuracy. Finally, the aim is to investigate the optimisation of SER models for multilingual cross-language support. This study adopts a pragmatic research paradigm, utilising the Design Science Research Framework (DSR). Data is collected quantitatively. The literature review covers human speech, speech physiology, neural network architectures, speech corpus, and data extraction methods. Hybrid architectures and preprocessing techniques are examined to identify the most effective configurations. The Afrikaans speech corpus is sourced from Creative Commons (CC) sources, with data augmentation using Generative Adversarial Networks (GANs). The study successfully compiled an Afrikaans speech corpus. Synthetic speech samples were created using frameworks such as Tacotron 2 and the WaveNet vocoder, thereby enhancing sound quality. For the Hybrid Neural Network Architectures: The novel Dendritic Convolutional Long Short-Term Memory (DCLSTM) architecture outperformed traditional CNN and LSTM models, effectively capturing nuanced and long-term emotional dependencies in audio data. The second Kalman filter variant was identified as the optimal preprocessing technique for noisy speech signals. A final accuracy of 78.50% was achieved, improving on baseline CNN and LSTM models. For the Multilingual SER System, the DenCaps model achieved up to 71.91% accuracy on multilingual datasets, demonstrating improved generalisation and better capture of temporal dynamics and spatial hierarchies in emotional speech. The findings highlight the effectiveness of hybrid neural network architectures and advanced preprocessing techniques in improving SER accuracy. The development of the Afrikaans speech corpus and the introduction of the DenCaps model represent significant advancements in emotion detection. These results underscore the potential for creating robust, multilingual SER systems that cater to diverse linguistic needs. The research objectives were successfully achieved through the development of a specialised Afrikaans speech corpus, the exploration of innovative neural network architectures, and the optimisation of models for multilingual support. The academic contributions pave the way for more accurate, contextually aware human-computer interaction systems that address the research gap in emotion detection for African languages. Text and abstract in English Wed, 01 Jul 2026 00:00:00 GMT https://ir.unisa.ac.za/handle/10500/32778 2026-07-01T00:00:00Z