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Item Evaluating the efficacy of laboratory ageing of asphalt mix binders as a prediction for field ageing(2023-10) O'Connell, Johannes S; Maina, J; Bredenhann, SJ; Marais, H; Komba, JA Performance-grade Binder Specification (SATS 3208) for South Africa was finalised after CAPSA 2015 and launched at CAPSA 2019. A key feature of the performance-graded binder specification is the regulation of binder performance after long-term ageing, which is simulated in the laboratory using the pressure ageing vessel (PAV). This paper reports how this simulated long-term ageing relates to the ageing of binders in continuously-graded asphalt surfacing mixes in the field. Samples of asphalt surfacing mixes were obtained from ten sites in Gauteng, South Africa, which were constructed 5 to 30 years ago and selected based on the availability of the original binders. An ageing profile was developed for the original binders by characterising their rheology in the original state, after rolling thin film oven (RTFO) ageing and pressure ageing vessel (PAV) ageing after 20 hours, 40 hours and 80 hours. The ageing profiles were compared to the corresponding recovered binders. Rheological parameters used for comparison were Softening Point and Flexural Creep Stiffness / m-Value from the Bending Beam Rheometer (BBR) test.Item Relating the rheology of recovered binders from asphalt surfacing in the field to their fatigue performance(2024-10) O'Connell, Johannes S; Maina, J; Bredenhann, SJ; Marais, H; Komba, JG*.Sind and TC are two of many rheological parameters that have been proposed as potential specification properties for control of fatigue performance for hot mix asphalt. This paper assesses the extent of correlation between the values of these parameters and the presence of cracking in the hot mix asphalt surfacing from 11 sites carefully selected to represent a wide range of fatigue performance over periods ranging from 5 to 20 years. The binders were recovered using a modified Abson recovery process that accurately represents the properties of the aged in-situ binder. Results indicate that TC correlates better with the condition of the asphalt surfacing, compared with G*.Sind. The results also demonstrate that although binder fatigue parameters may be an indicator of fatigue performance, the actual fatigue performance is also determined by other factors such as binder film thickness of the mix, traffic loading, climate and rate of ageing.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 Deep learning vs. traditional learning for radio frequency fingerprinting(2024-05) Otto, A; Rananga, S; Masonta, Moshe TRadio Frequency (RF) fingerprinting is the theory of identifying a wireless device based on its unique transmitting characteristics. RF fingerprinting uses the validated concept that the physical components and configuration of a transmitting device can result in a distinct wireless emission. This research focuses on the application of machine learning algorithms, specifically Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs) for the task of RF fingerprinting. The primary aim of this research paper is to comparatively assess the performance of SVMs and CNNs in RF fingerprinting for wireless device identification, focusing on hyperparameters, accuracy and real-world applicability. The study includes an in-depth implementation and evaluation of the SVMs and CNNs models, considering their performance in a high-dimensional dataset of multiple transmissions and wireless devices. While the CNN model slightly outperformed the SVM in terms of classification accuracy, other metrics such as inference time and training duration made the SVM equally competitive. The high accuracy and competitive inference times affirm the real-world applicability of these models, and their need to be further explored.Item Building a dataset for misinformation detection in the low-resource language(2024-05) Mukwevho, M; Rananga, S; Mbooi, Mahlatse S; Isong, B; Marivate, VIn the modern digital age, the widespread dissemination of misinformation has become a serious issue. Most focus in identifying misinformation online has been targeted at the English language in contrast to low-resource languages like Tshivenda. In this paper, we create a new dataset for news in the Tshivenda language to assist in developing resources for misinformation in the language. In our proposed methodology, we leveraged conditional random fields (CRF), gated recurrent unit (GRU), and long short-term memory (LSTM) to collect and annotate social media content. By applying these deep learning approaches to existing Tshivenda posts, we can assess their effectiveness for identifying false news in a low-resource language setting. This paper emphasises the vital need to combat misinformation in languages with limited resources, such as Tshivenda. Through the creation of a specialised dataset and the use of advanced techniques, it aims to address the problem of the spread of misinformation in low represented language communities.Item Social media as a strategic advantage during cyberwarfare: A systematic literature review(2024-03) Baloyi, ErrolIn recent years, cyberspace has been shaped by a rapid and transformative technological evolution, which ushered in an era characterised by unparalleled connectivity and innovation. However, this remarkable progress has brought a concerning surge in cyberattacks that have fundamentally altered cyberspace dynamics and refined the nature of contemporary warfare. This refinement was vividly illustrated in the recent Russia-Ukraine conflict, where cyberspace played a pivotal role, blurring the traditional boundaries of conflict in the cyber age. As a result, this study used secondary data to examine how various social media platforms such as Twitter, Facebook, TikTok, and Telegram were used as a strategic advantage during the conflict. The findings disclosed that Russia employed offensive propaganda against Ukraine, while Ukraine adopted a defensive stance, effectively countering the narrative through an active online presence. Moreover, this study underscored the substantial role of social media in warfare and its continued significance in future conflicts. Furthermore, this study provided recommendations for nations to better prepare for such conflicts. The recommendations provide valuable insights to assist decision-makers and policymakers in enhancing cybersecurity awareness and practices within their respective countries.Item Data cleaning using OpenRefine: A case of blast incidents and explosives research data extraction from social media platforms(2023-05) Marengwa, Matshidiso SThe increase in explosive and blast incidents has resulted in the need for a method or tool to help monitor and keep track of said incidents to provide insight into the methodologies and devices used by attackers to develop counter-active measures. The prevalence of social media in society has harnessed the generation of data and information which can be applied by organisations to improve functions and processes which in turn helps aid decision-making. With regards to the field of explosives, more institutions and news outlets have opted for the use of social media and other online platforms to share real-time data pertaining to explosives and blast related incidents and events that occur on a global scale. This study presents a method for extracting and capturing data pertinent to the field of explosives research from social media sites and other online platforms through monitoring and highlighting any blast related incidents, events and trends. The data used in the paper was collected over a period of 10 months and retrieved and extracted using a predetermined form which specified the type of information that should be mined and processed. The data was then cleaned, visualised and presented using various techniques available on the OpenRefine application. This data then provided insight into, but not limited to questions such as: the most prevalent sources, types of blast incidents or events, the types of devices used; casualties etc. The results of the study helped improve operations within the unit through enabling the identification and improvement of training efforts by shedding light on the effective methodologies and techniques used by explosives ordnance disposal (EOD) groups. The results of the study also helped compile a list of tope perpetrators and users of explosives; potential suppliers and/or collaborators which can be used if the need prevails and the data regarding the countries with the highest incidents helped to shift the focus on which states to keep track of.Item Immunogenic profile of a plant-produced nonavalent African horse sickness viral protein 2 (VP2) vaccine in IFNAR-/-mice(2024-04) O’Kennedy, Martha M; Roth, Robyn; Ebersohn, K; Du Plessis, LH; Mamputha, Sipho; Rutkowska, Daria A; Du Preez, Ilse; Verschoor, JA; Lemmer, YolandyA safe, highly immunogenic multivalent vaccine to protect against all nine serotypes of African horse sickness virus (AHSV), will revolutionise the AHS vaccine industry in endemic countries and beyond. Plant-produced AHS virus-like particles (VLPs) and soluble viral protein 2 (VP2) vaccine candidates were developed that have the potential to protect against all nine serotypes but can equally well be formulated as mono- and bi-valent formulations for localised outbreaks of specific serotypes. In the first interferon a/ß receptor knock-out (IFNAR-/-) mice trial conducted, a nine-serotype (nonavalent) vaccine administered as two pentavalent (5 µg per serotype) vaccines (VLP/VP2 combination or exclusively VP2), were directly compared to the commercially available AHS live attenuated vaccine. In a follow up trial, mice were vaccinated with an adjuvanted nine-serotype multivalent VP2 vaccine in a prime boost strategy and resulted in the desired neutralising antibody titres of 1:320, previously demonstrated to confer protective immunity in IFNAR-/- mice. In addition, the plant-produced VP2 vaccine performed favourably when compared to the commercial vaccine. Here we provide compelling data for a nonavalent VP2-based vaccine candidate, with the VP2 from each serotype being antigenically distinguishable based on LC-MS/MS and ELISA data. This is the first preclinical trial demonstrating the ability of an adjuvanted nonavalent cocktail of soluble, plant-expressed AHS VP2 proteins administered in a prime-boost strategy eliciting high antibody titres against all 9 AHSV serotypes. Furthermore, elevated T helper cells 2 (Th2) and Th1, indicative of humoral and cell-mediated memory T cell immune responses, respectively, were detected in mouse serum collected 14 days after the multivalent prime-boost vaccination. Both Th2 and Th1 may play a role to confer protective immunity. These preclinical immunogenicity studies paved the way to test the safety and protective efficacy of the plant-produced nonavalent VP2 vaccine candidate in the target animals, horses.Item Difficulties monitoring short-term ageing in thin surfacing layers using asphalt concrete(2024-07-20) O'Connell, Johannes S; VdM Steyn, WJ; Maina, JAgeing has a profound effect on pavement performance, especially regarding cracking. Due to budgetary constraints, South Africa has pioneered the use of thin asphalt concrete layers. The research described in this paper is based on a short-term ageing study in South Africa, using data generated over a period of 6 years. During this time, polymer modified asphalt binders were increasingly employed in road construction, and rheological analyses from the dynamic shear rheometer were increasingly used to characterize asphalt binders. This study compared the complex shear modulus to the softening point as an ageing index property used to monitor the extent of short-term ageing of the recovered asphalt binder from newly laid asphalt concrete. The asphalt binder properties from 20 constructions sites were evaluated, whereby the recovered binder from the site shortly after construction was evaluated against the asphalt binder properties obtained in the laboratory after the rolling thin film oven treatment. The results indicate that the recovery process leads to a deterioration in the repeatability for the complex shear moduli obtained from recovered asphalt binders. The lower repeatability prevents meaningful conclusions from being made. Furthermore, the work shows that although the Rolling Thin Film Oven Test may be a good predictor of short-term ageing when using softening point as an ageing index property, it is only valid for unmodified asphalt binders in South Africa.Item The future of digital forensic investigations: Keeping the pace with technological advancements(2024-05) Nelufule, Nthatheni; Masango, Mfundo; Singano, Zothile TDigital forensics plays a crucial role in the justice system, providing digital evidence that can be used to prosecute and convict criminals. This field is rapidly evolving due to the increasing complexity of digital devices. These increasing complexities has presented new challenges for the digital forensic investigators because the devices are now equipped with multiple processors, advanced operating systems, and complex security features making it more difficult to extract digital evidence. The challenges posed by technological advancements have led to several problems in the field of digital forensics, including a backlog of evidence, quality of forensics investigations, credibility of digital evidence. The problems facing digital forensics have a significant impact on the justice system, because a lack of reliable digital evidence can lead to miscarriages of justice, both for the accused and for victims of crime. A comprehensive framework is proposed to address these challenges by emphasizing continuous innovation, continuous collaboration, continuous cybersecurity training and awareness.Item Investigating the effectiveness of detecting misinformation on social media using Tshivenda language(2024-05) Malange, M; Rananga, S; Mbooi, Mahlatse S; Isong, B; Marivate, VThe spread of misinformation on social media poses a major challenge to information integrity and public discourse. This study examines the effectiveness of detecting misinformation in Tshivenda language, which is one of the underrepresented languages in South Africa. The same applies also on social media platforms. We analyse misinformation patterns, adapt existing detection techniques, and examine the influence of Tshivenda language. Through an extensive literature review, we investigated the state of the art in misinformation detection and its applicability to languages with limited digital footprints. To address this gap, we used Long Short-Term Memory (LSTM) models, a type of recurrent neural network known for capturing long-range dependencies, for misinformation detection. Our research involved training and evaluating the LSTM model on the Tshivenda and English datasets. This comparative analysis provided valuable insights into the challenges and opportunities that linguistic diversity presents in detecting misinformation. Our results shed light on the effectiveness of using LSTM models to detect misinformation in underrepresented languages. By analysing the results from the Tshivenda and English datasets, we were able to gain valuable insight into the differences in performance and the impact of linguistic variation on the accuracy of misinformation detection.Item Digital forensics in industry 4.0 and industry 5.0: Major challenges and opportunities(2024-05) Nelufule, Nthatheni; Masango, Mfundo G; Singano, Zothile TThe rapid advancements in Industry 4.0 and 5.0, along with the increasing adoption of edge computing, have brought about a significant transformation in industrial landscapes. These advancements have ushered in a new era of interconnected devices, real-time data processing, and decentralized decision making, creating an unprecedented volume of digital data. This surge in data generation has also heightened the need for robust digital forensics capabilities to investigate and respond to cyberattacks, data breaches, and other security incidents. This paper provides an overview of digital forensics in the context of Industry 4.0, Industry 5.0, and edge computing. It discusses the challenges and opportunities associated with forensic investigations in these environments, highlighting the unique characteristics of these technologies and their impact on the collection, preservation, and analysis of digital evidence. The paper also explores the potential applications of digital forensics in these industries, including incident response, fraud detection, and regulatory compliance.Item On the zero-trust intranet certification problem(2024-03) Badenhorst, Danielle P; Barbour, Graham D; McDonald, André M; Gertenbach, Wian P; Buckinjohn, EthanSecuring corporate networks and ensuring the trustworthiness of network resources are critical security concerns for organisations in today's interconnected digital landscape. The zero-trust security model is an approach to designing and implementing ICT systems which prescribes that clients and servers cannot be trusted automatically, even when connected to networks traditionally considered trusted. The implementation of the zero-trust model within the corporate intranet requires a secure method to verify the identity of local servers. On the Internet, trust in the identity of public servers is established by well-known public Certificate Authorities (CAs), which issue digital certificates to securely identify servers. However, local intranet servers exist within the internal address space of the network. Consequently, it is impossible to naturally obtain digital certificates for these servers, validly signed by a public CA, without publicly disclosing sensitive information such as intranet server Domain Name System (DNS) records. This leaves organisations with the option of relying on endpoint management systems to install custom CA root certificates on all corporatre browsers or, in some cases, ignoring the problem altogether. In this paper, we draw on practical experience in the deployment of cybersecurity devices in corporate intranets to formally define the intranet certification problem. We specify five requirements that a solution to this problem must satisfy. We then conduct a comprehensive review of existing candidate solutions and academic research relevant to the intranet certification problem. Specifically, existing ICT systems for public key infrastructure and endpoint management are identified and evaluated with respect to their ability to meet the stated requirements for solving the intranet certification problem, as well as their cost. Our study reveals that solutions that meet the technical and security requirements of the intranet certification problem are beyond the reach of smaller private sector companies and public sector organisations in underdeveloped and emerging economies. The high cost and technical expertise required for their implementation and management render these solutions impractical. Consequently, by relying on servers with self-signed certificates, these entities inadvertently leave their servers susceptible to impersonation, information theft, and unauthorised resource access, thus violating the fundamental principles of the zero-trust model. We conclude that a gap exists for a simple, cost-effective, and easily managed solution to the intranet certification problem.Item Topic modelling of short texts in the health domain using LDA and bard(2024-03) Mbooi, Mahlatse S; Rangata, Mapitsi R; Sefara, Tshephisho JThis paper proposes a model for the topic modelling of tweets in the health and mental health domain using the Latent Dirichlet Allocation (LDA) method. The data were obtained from the sentiment140 project. The data were prepared for topic modelling by performing Natural Language Processing (NLP) tasks such as stemming and data cleaning. LDA method was trained on the data to create a cluster of topics. We explored 1 to 6 clusters and, after thorough analysis, three topics were chosen to create the LDA model. Each topic was labelled with a label name that is generated using Bard and coding analysis. This method can be used to label unlabelled data without using sophisticated supervised machine learning methods. Labelled data can be used to improve data management, information retrieval, supervised machine learning, and other techniques.Item Roundtable discussion: Integrating working with nature and nature-based solutions into long-term sustainable sediment management(2024-04) Magar, VS; Suedel, B; McQueen, A; Sittoni, L; Badmus, L; Ballegooyen, R; Weerts, StevenThis presentation mentions the Working with Nature (WwN) programme, which is a framework to design new infrastructure or rehabilitate existing infrastructure in a way that works with natural processes. It also speaks to Engineering with Nature (EWN), that is the intentional alignment of natural and engineering processes to efficiently and sustainably deliver economic, environmental and social benefits through collaboration.Item OpenAir interface for 4G core network and 4G/5G base stations(2023-11) Vilakazi, Mlamuli C; Olwal, TO; Mfupe, Luzango P; Lysko, Albert AWith the advent of the fourth industrial revolution (4IR), 5G networks are aiming to support a broad range of network services and applications. Network operators are looking to open-source implementations to expand on the flexibility and re-programmability of networks. This paper introduces an implementation including a 4G Core Network (using the OpenAir Interface (OAI) platform), OAI 4G and 5G Base Stations, and the 4G/5G User. This paper shows the steps followed to have a complete 4G/5G mobile network using OAI. We used Wireshark software for packet visualization when the two Base Stations connect/disconnect to the CN and when the phone is attached/detached from the network. Additionally, some installation pointers, current performance statistics, and video streaming (such as measured download/upload speed and latency between various system components) are included in this paper.Item Vertical handover algorithm in OpenAirInterface and neural network for 4G and 5G base stations(2024-01) Vilakazi, Mla; Olwal, TO; Mfupe, Luzango P; Lysko, Albert AThe fifth generation (5G) mobile network has been designed to offer individuals and objects with nearly ubiquitous, ultra-high bandwidth, and low latency access. In heterogeneous wireless networks, the demand for wireless communication devices has increased dramatically. This paper provides a Vertical Handover Algorithm (VHA) in OpenAirInterface (OAI) and Neural Network (NN) for heterogeneous 4G and 5G Radio Access Networks (RANs). The framework of the algorithm is built by configuring the network environment in which we employ network resources when switching between OAI 4G and OAI 5G base stations. Each base station establishes its three-layer backpropagation neural network model. Then, the user’s speed, signal-to-interference, and noise ratio (SINR), maximum transmission rate, minimum delay, coverage area, bit error rate, and packet loss rate are used as reference objects to participate in the setting of VHA using a backpropagation neural network model. The measured download/upload speeds are used to compare the performance of the two wireless networks, and the vertical handover algorithm then chooses the best wireless network for performing the vertical handover decision.Item Assessing the effectiveness of 4IR strategy on South African township economy: Smart Township perspective(2021-12) Mathibe, Motshedisi; Mochenje, Tonderai; Masonta, Moshe TAs the Coronavirus disease (COVID-19) pandemic changed how people and business interact, its impact severely impacted the global economy. The government imposed heavy lockdown regulations further damaged an already struggling informal sector economy as many livelihoods and informal businesses within the townships came to a halt. Though the South African government introduced various financial relief through the R500 billion support grant, there are township entrepreneurs who could not access the government grant to sustain their everyday business operations. Despite the invisibility of the informal sector, it is considered to contribute about 5 – 30% of the Gross Domestic Product (GDP). Hence, the need to develop a smart township strategy for the township economy will better prepare the township entrepreneurs with a creative and innovative way to survive any future pandemics. This chapter aims to identify factors and enablers that can catalyse critical and innovative thinking to safeguard the township economy and assess the maturity level of the national fourth industrial revolution (4IR) strategy towards building on a South African smart township economy. A digital infrastructure value chain model for building the smart township is proposed. The model also identified digital skills training and upskilling township entrepreneurs to reposition and align themselves within the smart township ecosystems. Furthermore, the chapter proposed key recommendations on how the policy makers could leverage on the 4IR strategy in enabling the township entrepreneurs to actively participate in the digital economy. The objective and significance of this chapter is to assist the policy makers (at provincial and local government level) in understanding both theoretically and practically technological innovation strategies and methods to adopt post-pandemic.Item A method to improve alignments between domain and foundational ontologies(2023-07) Bernabe, C; Keet, M; Dawood, Zubeida C; Mahlaza, ZFoundational ontologies can be used to enable semantic interoperability in modern information systems. Aligning a domain ontology to a foundational ontology is perceived difficult, however. Reasons include confusing underlying concepts, understanding the philosophical ideologies of foundational ontologies, and lack of alignment guidance. For BFO, there is a BFO Classifier tool for alignment, but users still face challenges. To uncover some of these user challenges, an experiment was performed using 10 BFO-aligned domain ontologies. The alignment of domain entities were analysed, revealing seven different types of mistakes in the alignments. To avoid them, the BFO classifier tool was altered to improve the questions and explanations for the core principles of BFO. Thereafter, the BFO classifier tool was evaluated to measure the effect on alignment with a use-case based approach, using the GORO and AWO ontologies. The evaluation revealed that alterations facilitated alignment, as users felt more confident in their results given the improved understanding of the questions and possible answers.Item Addressing accessibility, affordability and sustainability barriers for broadband internet access and penetration in rural areas(2023-10) Ngwenya, SO; Heymann, R; Swart, TG; Lysko, Albert AIt has been said that the spread of Information and Communications Technology (ICT) and global interconnectedness has a great potential to accelerate human progress, to bridge the “digital divide” and to develop knowledge societies, in countries where it is available. However, it has also been determined that certain barriers, more prevalent in rural communities, pose an incessant impediment to the access and penetration trends of broadband internet networks and infrastructure in rural areas. These barriers have been identified as ‘accessibility’, ‘affordability’, and ‘sustainability’. It is hereby asserted, therefore, that a concerted effort is required to address these barriers, with great deliberation and haste, if digital inclusion is to be achieved in rural areas. This paper proposes a broadband internet system that is aimed at addressing these barriers, through a proposed model, which is intended to be implemented as a Proof of Concept (PoC) in the rural area of Mbazwana, located in the province of KwaZulu-Natal (KZN), South Africa (SA). The model has been presented to the community, and subsequently followed by a survey to determine the feasibility of the implementation thereof. This paper will present the proposed model, as well as the results obtained from the research conducted.