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Item Infrastructure in human settlements in South Africa(2024-07) Gibberd, JeremyThe purpose of this paper is to present research that develops and tests human settlement infrastructure policy statements as input for a new White Paper on Human Settlements in South Africa. The study develops infrastructure policy statements for human settlements. These are tested through an online survey of human settlement stakeholders. Data gathered through the survey are analysed to provide findings for the study and recommendations for human settlement policy development. The findings indicate that addressing infrastructure in human settlements in South Africa is a high priority. It shows that there is strong support for alternative delivery and operational models, increased involvement of the private sector and communities, innovative financing and the use of sustainable technologies and systems, in the development and operation of infrastructure in human settlements. The study is original as it explores new approaches to addressing infrastructure backlogs in human settlements in South Africa. It contributes new thinking on how the private sector and communities can be involved, alternative delivery models developed, and how sustainable technologies may be applied in addressing these backlogs.Item Microstructure and mechanical properties study of Ti-12Mo alloy for biomedical applications(2024-07) Raganya, Mampai L; Moshokoa, N; Obadele, B; Machaka, Ronald; Makhatha, EThe aim of the work was to study the microstructural characteristics and mechanical properties of Ti-10Mo and Ti-12Mo alloys. The stability of the β phase was predicted using the molybdenum equivalence, average electron concentration ratio, and d-electron approaches. Microstructural examination was conducted using scanning electron microscopy and electron backscatter diffraction, while phase analysis was performed by x-ray diffraction. Uniaxial tensile test machine was employed to conduct tensile tests. The microstructure of Ti-12Mo alloy revealed primary BCC beta (β) phase and some nanoparticles of martensitic α" phase and hexagonal omega (ω) phase precipitated in the β matrix. The precipitation hardening of the ω phase resulted in superior microhardness, tensile and yield strengths. Contrarily, the existence of the ω phase contributed to the brittle fracture that occurred during tensile tests, a higher elastic modulus and lower elastic admissible strain than those of the human bone. Nonetheless, the characteristics and mechanical properties observed of the studied β-type alloy qualify it as a promising candidate for biomedical applications.Item Rule-based spectrum allocation algorithms for heterogeneous cognitive radio wireless networks(2024-11) Masonta, Moshe TThe growing number of heterogeneous cognitive radio wireless network (CRWN) deployments sharing the same radio frequency spectrum band will lead to a number of new coexistence challenges when it comes to channel allocation. In this paper we propose rule-based spectrum allocation algorithms for CRWN. In the channel partitioning (CP) rule, white space (WS) channels with the biggest bandwidth are partitioned to the required bandwidth sizes before being allocated to a CRWN that requires smaller bandwidths. In the channel bonding (CB) rule, a number of WS channels are bonded together to meet the needs of the CRWNs requiring the widest bandwidth. Performance evaluation results show that the total number of WS channels allocated under rule-based scheme was equivalent to those allocated under an interference aware WS allocation scheme. However, in order to satisfy quality of service of secondary users, the rule-based scheme searches for the most suitable WS channels among the list of discovered channels through partitioning rules.Item Bootstrapping syntactic resources from isiZulu to Siswati(2024-05) Marais, Laurette; Pretorius, L; Posthumus, LCIsiZulu and Siswati are mutually intelligible languages that are considered under-resourced despite their status as official languages. Even so, the available digital and computational language resources for isiZulu significantly outstrip those for Siswati, such that it is worth investigating to what degree bootstrapping approaches can be leveraged to develop resources for Siswati. In this paper, we present the development of a computational grammar and parallel treebank, based on parallel linguistic descriptions of the two languages.Item Applying phonological feature embeddings for cross-lingual transfer in text-to-speech(2024-07) Louw, Johannes A; Wang, ZIn this work, we build upon our previous research where we introduced phonological features as input to text-to-speech systems. While the use of phonological features is not a novel concept in our research, our focus in this study is on the comprehensive analysis of the embeddings produced by the encoder model, which we believe offers novel insights into the model’s ability to capture and generalize phonological patterns across languages. Cross-lingual transfer experiments are conducted using both a resource-rich and a resource-constrained language to explore the model’s cross-lingual transfer capabilities across different linguistic families. The analysis of the embedding vectors produced by the encoder model is conducted using cluster maps to visualize the hierarchical clusters obtained using a clustering procedure. This analysis reveals the model’s learning patterns and provides insights into how phonological features contribute to the model’s ability to handle linguistic diversity and data scarcity.Item Review of a full-polarimetric calibration target for radar cross section measurements(2018-11) Blaauw, Ciara; Cilliers, Jacques E; Potgieter, MoniqueThis research investigated the feasibility of a passive calibration target to calibrate a fully-polarimetric bistatic Cband radar. A screw-like target, found in open literature, was utilized as it produced relatively high co- and cross-polarized radar cross section (RCS) returns. In this study the required elevation alignment accuracy of the receiver, relative to the transmitter-target plane, to produce good calibration results was also investigated. The target was slightly modified to possibly improve the elevation beam-width and peak RCS.Item iSinkwe: An application that synchronises text and audio for enhanced reading(2024-03) Kruger, Rynhardt P; Govender, Avashna; Van der Walt, Willem J; Wilken, IlanaWe present iSinkwe, a system to produce synchronised accessible EPUB 3 books of text and audio. With iSinkwe, users are able to synchronise EPUB 3 publications with human-narrated or computer-generated speech, via an accessible web interface. Documents in other formats can also be converted to EPUB 3. Developed specifically to address reading barriers experienced by users with print disabilities such as dyslexia and visual impairment, iSinkwe is also of particular importance for regions with low literacy such as South Africa. This paper describes the motivation and context for its creation, the components that make up iSinkwe, a discussion on the relevance it has for the accessibility community, and how users can interact with the system. A usability study was performed on a previous iteration of iSinkwe, with mixed results. We report on the lessons we learned, and subsequent improvements to the system. Finally, we describe future work planned to extend its functionality.Item MarCOSIO: Supporting coral bleaching monitoring in the Western Indian Ocean(2024-05) Smith, Marie E; Mbugua, JMarCOSIO is one of 2 marine consortia within the GMES&Africa programme and this project is lead by the CSIR (South Africa). The project represents 12 partners in 8 countries in Southern Africa and the Western Indian Ocean (WIO) region, and supports coral bleaching monitoring in the Western Indian Ocean.Item Accelerating the use of mobile phone capabilities to maximise the effectiveness of public emergency alerts in South Africa(2024-10) Mukange, Tsumbedzo; Mokoto, Bayanda T; Moipolai, Tumelo B; Ndamase, ZimasaAn emergency alert system (EAS) enables government authorities, its agencies, and community authorities at various levels to use communication platforms to inform people in threatened areas of imminent disaster. Disseminating emergency alerts to the public is crucial to ensure effective and efficient disaster management. The purpose of disseminating emergency alerts is to provide important and life-saving information to the public so they can take the necessary actions to ensure their safety. EAS uses various communication channels to disseminate alerts and warnings, including TVand radio, sirens and long-range acoustic devices, message signage and public address systems, the Internet, fixed phones, and mobile phones through cell broadcast services (CBS), SMS and mobile apps. The United Nations launched the Early Warning for All initiative that promotes the use of geo-located mobile-based early warning services, such as CBS and location-based SMS (LB SMS), to disseminate emergency alerts to all by 2027. The accessibility of mobile phones has accelerated the use of mobile phone capabilities to disseminate emergency alerts. In South Africa, using CBS and LB SMS capabilities to disseminate emergency information to targeted geographical areas by authorities is still an area of improvement. T hestudy aims to accelerate the adoption and use of cell broadcast and location-based SMS to maximize the effectiveness of public emergency alerts in South Africa. The study forms a basis to accelerate the adoption and use of CBSandLBSMStodisseminatepublic emergency alerts. Partial results show emergency alert message crafting and appropriate communication approaches are vital in influencing the public to comply with the alert. In addition, South Africa had implemented some components of emergency alert systems, but in isolation and focusing on specific types of emergency alerts.Item Towards a 5G equipped video surveillance UAV for public safety(2024-05) Makhalanyane, Thapelo; Mamushiane, Lusani; Kobo, Hlabishi I; Lysko, Albert ASouth Africa faces a severe crime problem, with persistent issues such as murder, hijacking, and CIT heists. This research examines existing surveillance strategies, including UAVs, and identifies their limitations. To address these shortcomings, we propose a novel solution that leverages 5G technology to enhance UAV capabilities, offering low latency and high bandwidth for improved surveillance. Our solution introduces a hybrid-VTOL surveillance UAV integrated with predictive policing techniques. Machine learning algorithms and statistical analysis will be employed to forecast crime-prone areas, enabling strategic UAV deployment. We will develop and evaluate this solution utilizing a CSIR-developed 5G testbed, focusing on Quality of Service (QoS) metrics. A UAV equipped with a 4K camera will act as User Equipment (UE), with functionality assessments carried out from a ground control station (GCS). Key performance indicators like RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), RSSI (Reference Signal Strength Indicator), packet loss, throughput, and control latency will measure the solution's effectiveness and its potential to make a positive impact on societal safety.Item A review of PFCP cyber attacks in 5G standalone for robotic telesurgery services(2024-10) Makondo, Ntshuxeko; Baloyi, Errol; Kobo, Hlabishi I; Mathonsi, TEThe emergence of fifth-generation technology (5G) has revolutionised telecommunication networks, offering enhanced mobile broadband, ultra-reliable (eMBB), ultra-lowlatency communications (uRLLC), and massive machine-type communication (mMTC) service classes. This breakthrough has garnered significant attention and investment worldwide, driving innovation and growth in the digital era. However, the adoption of cloud-based 5G core (5GC) networks, while offering scalability and deployment flexibility, has posed challenges to meeting stringent latency requirements, particularly for uRLLC services specifically for robotic telesurgery. To address this problem, mobile network operators (MNOs) have turned to edge computing (EC), using the control and user plane separation (CUPS) architecture introduced in the thirdgeneration partnership project (3GPP) release 14 specification. This architecture enables the deployment of the user plane function (UPF) closer to users, reducing latency, and improving quality of service (QoS). However, the deployment of the UPF as a standalone node on the edge of the network exposes the packet forwarding control protocol (PFCP) to cybersecurity attacks, which pose risks to telesurgery services and could even lead to loss of life. In the existing literature, only a few techniques focus on minimising these attacks when the UPF is deployed on the edge of the network far from the 5GC. Therefore, this paper reviews PFCP attacks and explores machine learning (ML) techniques to mitigate these security threats. This paper further provides recommendations and future research directions for mitigating these attacks.Item Flat Plate Flutter in a Supersonic Flow Field(2024-07) Ndebele, Bright BThe interaction of a two-dimensional cantilevered elastic flat plate with a supersonic flow field was investigated numerically using StarCCM+. The plate was 0.4 m in length and inclined at 15∘ to the freestream at three Mach numbers (1.2, 1.35, and 1.45). The flat plate was assumed to be aluminium. Using StarCCM+, the inviscid Navier-Stokes equations were solved, and the fluid-structure interaction resolved. This way, the flow field around the plate and the plate deflection were calculated. The results indicated that at Mach 1.2, the plate exhibited a steadystate deflection, while at the other investigated Mach numbers, limit cycles were observed. The deformation of the plate caused a flow compression at the top, resulting in a weak shock at Mach 1.2 and strong shocks at 1.35 and 1.45. These findings provide insight into the dynamic response of the plate and the corresponding flow characteristics at different Mach numbers.Item Innovations in financing land transport(2024-07) Kabinde, Elias V; Marole, Busisiwe CThe environmental impact of land transport has been widely explored in South Africa; however, implementation of mitigation is still lagging behind. Implementation of strategies requires funding. The National Revenue Fund (NRF) provides financial support for all government programs, including land transport. The allocation of funds for road infrastructure, public transportation, and transport-related research competes with other demands for service delivery funding. Section 28 of the National Land Transport Act allows municipalities to impose user charges on specific categories of motor vehicles as the need arises. Vehicle licensing can be used as one of the revenue generating methods by government. The underlying principles of vehicle licensing primarily aim to enhance road safety and, secondarily, to mitigate the carbon footprint of motor vehicles. Methods for implementing user charges are not explicitly outlined and therefore, allowing for flexibility and innovation in financing land transport. This study explores innovative ways to charge fees for the use of private transportation within Low Emission Zones (LEZs) and/or congested routes through a proficient vehicle licencing system, to reduce greenhouse gases that have a negative impact on the quality of the air. This paper aims to present the approach used to develop the fee charging technique with the use of existing vehicle data.Item Leveraging technology for safer roads for vulnerable road users in South Africa(2024-10) Ngobeni, Ntombifuthi; Marole, Busisiwe C; Bosilong, Keolebogile KJ; Nkuna, Hlulani TThis research aims to enhance road safety, particularly for Vulnerable Road Users (VRUs) such as pedestrians and cyclists, through the use of both cutting-edge technologies and consideration of conventional engineering methods and solutions. The study focuses on innovative solutions related to the road environment and their impact on VRU safety, piloted at selected sites in South Africa. The research investigates the use of technologies such as video cameras, video analysis software, artificial intelligence and machine learning to conduct route risk assessments. These assessments inform the selection and implementation of effective safety measures tailored to enhance VRU safety. By understanding the unique challenges faced by these users, targeted interventions are developed through various modeling techniques. The methodology involves conducting a pilot study, which includes the collection of extensive video data from South African roads. This data is crucial for examining the impact of various road environment factors and other factors on VRU safety. The pilot study emphasises establishing appropriate route risk criteria, accurately collecting and analysing video data from the pilot sites and recommending safety measures based on the criteria that directly influence VRUs safety. These measures provide deep insights into the factors contributing to crashes and facilitate the evaluation of targeted road safety interventions. Through detailed collection and analysis, the study uncovers the root causes of accidents and other safety concerns involving VRUs. This paper presents the findings from the pilot research study, which involved rigorous testing and evaluation to develop evidence-based solutions that address the specific needs of VRUs in South Africa. By leveraging technology and simulation tools, this research contributes to smarter decision-making in VRU road safety. Sharing our findings, we aim to support South African efforts in reducing road accidents and creating safer road environments for all users, particularly the most vulnerable.Item Decoupling store and parent aerodynamics for fast prediction of subsonic store trajectories(2024-09) Mthembu, N; Ndlovu, Hlamulo P; Ndebele, Bright B; Jamison, Kevin A; Zwane, LindokuhleA method optimised for efficient prediction of subsonic store separation trajectories is described and demonstrated using a wind-tunnel test case. The FastTraj method uses a decoupled flow field approach where it is assumed that in most attached flow subsonic store separation scenarios the presence of the store has little impact on the perturbed flow field generated by the parent aircraft. The inviscid perturbed flow field of the parent aircraft is computed using computational fluid dynamics codes and is captured using a grid. The store aerodynamic model is generated elsewhere and Missile Datcom is used to segment the store model to approximate the effect of the perturbed flow field changing along the length of the store. The 6-DOF trajectory solver interpolates the aerodynamic grid from the parent aircraft to determine the local flow vector at each reference point on the segmented store, in addition to the local flow vector due to the motion of each segment. Good comparisons with the wind-tunnel data are achieved showing that the method’s speed is not at the expense of accuracy and that it is necessary to segment the store to achieve good results.Item An analysis of a cryptocurrency giveaway scam: Use case(2024-06) Botha, Johannes G; Leenen, LA giveaway scam is a type of fraud leveraging social media platforms and phishing campaigns. These scams have become increasingly common and are now also prevalent in the crypto community where attackers attempt to gain crypto-enthusiasts’ trust with the promise of high-yield giveaways. Giveaway scams target individuals who lack technical familiarity with the blockchain. They take on various forms, often presenting as genuine cryptocurrency giveaways endorsed by prominent figures or organizations within the blockchain community. Scammers entice victims by promising substantial returns on a nominal investment. Victims are manipulated into sending cryptocurrency under the pretext of paying for "verification" or "processing fees." However, once the funds have been sent, the scammers disappear and leave victims empty-handed. This study employs essential blockchain tools and techniques to explore the mechanics of giveaway scams. A crucial aspect of an investigation is to meticulously trace the movement of funds within the blockchain so that illicit gains resulting from these scams can be tracked. At some point a scammer wants to “cash-out” by transferring the funds to an off-ramp, for example, an exchange. If the investigator can establish a link to such an exchange, the identity of the owner of cryptocurrency address could be revealed. However, in organised scams, criminals make use of mules and do not use their own identities. The authors of this paper select a use case and then illustrate a comprehensive approach to investigate the selected scam. This paper contributes to the understanding and mitigation of giveaway scams in the cryptocurrency realm. By leveraging the mechanics of blockchain technology, dissecting scammer tactics, and utilizing investigative techniques and tools, the paper aims to contribute to the protection of investors, the industry, and the overall integrity of the blockchain ecosystem. This research sheds light on the intricate workings of giveaway scams and proposes effective strategies to counteract them.Item Uncovering influential factors of civil unrest in South Africa: A machine learning and OSINT approach(2023-12) Ndlovu, Lungisani; De Kock, Antonie J; Mkuzangwe, Nenekazi NP; Thwala, Ntombizodwa; Mokoena, Chantel JM; Matimatjatji, Rethabile JContinuous monitoring of the risk of civil unrest events and predicting their occurrence is of paramount importance. This task involves identifying and understanding the primary factors that contribute to such events, especially in regions with unique dynamics, such as South Africa. Although many global and South African-specific studies have conducted research on predicting the frequency or probability of these events, there is a notable gap in identifying the influential factors behind them. This study unveiled several contributing factors, including demanding behaviour, power outages, service delivery, wage disputes, acts of violence, gender-based conflicts, and unemployment rates. These factors, individually or collectively, contribute to the complexity of civil unrest in the region. The 2021 South African unrest, also known as the July 2021 riots, the Zuma unrest, or Zuma riots, serves as an example. This event was triggered by the imprisonment of former president Jacob Zuma for contempt of court, inciting his followers to demand his release, a situation aligning with the 'demanding behaviour' influential factor identified in our study. We used advanced data analysis and machine learning techniques to explore these factors. Specifically, the Logit model was used to determine the coefficients that optimally fit the data, establishing significant relationships between these factors and incidents of civil unrest. Our research not only offers insights on influential factors, but also presents a predictive framework. We evaluated logistic regression, support vector clustering, decision tree classifier, and random forest classifier models to predict civil unrest. The results showed that the decision tree and the random forest classifiers perform better, achieving an accuracy of 98%, compared to logistic regression and support vector clustering, which have an accuracy of 97%.Item A comprehensive exploration of digital forensics investigations in embedded systems, ubiquitous computing, fog computing, and edge computing(2024-08) Nelufule, Nthatheni; Singano, Zothile T; Masango, Mfundo GThe rapid evolution of digital ecosystems, characterized by the intricate interplay of diverse technologies, has necessitated a shift in the digital forensics’ paradigm. Traditional investigative methods are inadequate to perform digital forensic exercises in the new paradigm of dynamic digital ecosystem landscapes. The emergence of complex digital ecosystems encompassing an array of interconnected devices and data repositories poses formidable challenges for conventional digital forensics. There is a dire need to adapt and advance digital forensic methodologies to effectively combat cybercrime because the evolving landscape of digital ecosystems presents a critical juncture for the field of digital forensics. This study proposes a systematic literature review to understand the extent of these challenges and proposes a collaborative and innovative approach to digital forensic investigation within the context of digital ecosystems. The proposed approach emphasizes collaboration across diverse sectors and integration of innovative technologies by combining a spectrum of digital forensic experts, technologists, and legal professionals to produce a massive wealth of collective intelligence.Item Artificial Intelligence impact on the realism and prevalence of deepfakes(2024-07) Mahlasela, Oyena N; Baloyi, Errol; Baloyi, Errol; Dawood, Zubeida CDeepfakes, synthetic media manipulated by Artificial Intelligence (AI), have become a growing concern in the information landscape. This paper explored the impact of AI on the realism and prevalence of deepfakes. Therefore, this study examined how AI advancements in machine learning and generative models have facilitated the creation of increasingly convincing deepfakes. The analysis looked at the rise of hyper-realistic deception and the societal impact of deepfakes. In addition to recognizing the challenges, a framework was developed for the detection of deepfakes. Finally, this study discussed the potential mitigation strategies, such as the development of deepfake detection tools and fostering media literacy.Item A review of dynamic RRA techniques on 5G and beyond mobile networks(2024-07) Nokane, Boikobo; Isong, B; Masonta, Moshe TThe 5G mobile network aims to enhance wireless communication by providing faster and more reliable connectivity. Open radio access network (RAN) architecture, which offers flexibility and innovation in Radio Resource Allocation (RRA), is central for optimal network performance. However, traditional RRA methods fall short of meeting the complex demands of 5G due to scalability issues. Incorporating machine learning (ML) techniques into open RAN can enhance adaptability and intelligence, ensuring that 5G networks meet high performance and service quality standards. This paper presents a comprehensive review of ML-based and traditional RRA methods in meeting the evolving demands of wireless networks. Literature from relevant articles was selected and analysed to highlight the techniques used, trends, strengths, and limitations. The findings reveal the potential and transformative impact of ML on the future of wireless communications, particularly in achieving the key performance indicators and quality of service expected from 5G and beyond networks. It also shows that research in ML-based RRA methods is at its infancy stage and more research is needed to advance the technology.