Journal Articles

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A critical review on the applications of Sentinel satellite datasets for soil moisture assessment in crop production
(2025-07) Mkhwenkwana, A; Matongera, TN; Blaauw, Ciara; Mutanga, O
Understanding soil moisture dynamics in crop production is critical for optimising water resource management. The Sentinel satellite missions have significantly contributed to soil moisture monitoring by providing high-resolution, multi-sensor data. This review examines advancements in soil moisture assessment using Sentinel datasets, particularly in crop production. It highlights key challenges, evaluates their impact on monitoring accuracy, and explores potential methodological improvements. Findings indicate that Sentinel-1′s synthetic aperture radar (SAR) data, particularly VV and VH polarizations, and Sentinel-2′s multispectral indices, such as NDVI and NDMI, are widely integrated with machine learning algorithms to enhance soil moisture estimation. However, dense vegetation and complex topography reduce retrieval accuracy, necessitating sensor fusion and calibration for improved reliability. Sentinel-3 provides valuable surface temperature and land condition data for indirect soil moisture estimation, but its application remains limited due to higher uncertainty compared to SAR and multispectral approaches. Emerging trends suggest that machine and deep learning techniques, such as RF, SVR, and CNN, can enhance data fusion across Sentinel missions. Additionally, preprocessing steps such as RTC, speckle filtering, and the integration of multipolar and polarimetric data with physical backscattering models show promise in mitigating radar backscatter interference. Further development of robust retrieval models that incorporate topography, soil roughness, and texture are essential for improving soil moisture accuracy in diverse agricultural landscapes. This review underscores the need for continued methodological advancements to maximise the potential of Sentinel datasets for soil moisture monitoring in precision agriculture and water resource management.
A model-based systems engineering framework for technology roadmaps (MBSE-TRM): Application to electronic warfare systems
(2026-02) Reddy, Reeshen; Sinha, S
Technology-intensive industries face accelerating change driven by disruptive innovations, geopolitical shifts, and the dynamics of Industry 4.0. In this environment, managers require strategic tools that can align markets, products, and technologies over time while retaining adaptability. Technology roadmaps (TRMs) are widely used for this purpose; however, current practice remains largely qualitative, workshop-led, and reliant on subject matter expertise. This constrains their utility in dynamic environments. This paper develops a Model-Based Systems Engineering framework for Technology Roadmaps (MBSE-TRM) to address these limitations. The research advances theory by introducing a conceptual metamodel that captures the ontology of TRM, formalizing its structure and lifecycle using SysML, and demonstrating how tacit practitioner logic can be represented explicitly. Validation is undertaken in the domain of Electronic Warfare (EW) against radar, a technology-intensive field characterized by rapid innovation cycles and strategic importance. The findings show that MBSE-TRM enables improved transparency, traceability, and adaptability, supporting managers and engineers in steering innovation strategies under conditions of volatility. By bridging systems engineering principles with technology strategy, MBSE-TRM provides a structured yet flexible framework for aligning strategic intent with evolving technology options in Industry 4.0 and beyond.
A proposed bitcoin blockchain investigation methodology: Based on a case study approach
(2025-01) Botha, Johannes G; Singh, Kreaan D; Leenen, L
Criminal investigations involving cryptocurrencies are still premature with no standard investigative process to follow. This paper proposes a high-level methodology using open-source and analysed data to perform such investigations. It focuses on situations where Bitcoin is involved, but where other similar blockchains are concerned, the technical investigator should apply this methodology only after careful consideration. A case study approach is used to illustrate a cryptocurrency scamming platform, a giveaway scam, and divorce fraud. In all the cases, one needs to follow or trace the funds on the blockchain, referred to as on-chain analysis. The end goal of on-chain analysis is to find a destination address linked to identifiable information obtained from open-source data platforms—such as websites, social media, or a cryptocurrency exchange. Law enforcement can then be engaged to instruct the exchange to reveal all personal and transactional information linked to the address through a subpoena. A successful investigation will result in criminal prosecution and a potential recovery of funds. To maintain familiar investigation processes, the researchers looked at traditional (or non-technical) as well as technical investigation techniques.
Adding up the numbers: COVID-19 in South Africa
(2022-06) Suliman, Ridhwaan; Mtsweni, Jabu S
The SARS-CoV-2 pandemic has wreaked havoc globally, with over half a billion people infected and millions of lives lost. The pandemic has also interrupted every aspect of our lives, with most governments imposing various interventions and restrictions on people’s movement and behaviour to minimise the impact of the virus and save lives. The debate among scholars on the effectiveness of the interventions and restrictions, particularly in the context of a developing country like South Africa, continues. The data and scientific evidence indicate that non-pharmaceutical interventions, and particularly the implementation and adherence thereto, may have been ineffective in terms of containment in the South African context and had minimal impact in stopping the spread of the SARS-CoV-2 virus.
Advancing cybersecurity capabilities for South African organisations through R&D
(2022-03) Dawood, Zubeida C; Mkuzangwe, Nenekazi NP
There is a growth of cyber-attacks in South Africa. Seeing that there are over 38 million Internet users in South Africa, this is no surprise. The South African government has published the National Cybersecurity Policy Framework (NCPF) and Protection of Personal Information Act (POPIA) to move towards mitigating cyber threats due to the increase of the presence of South African organisations and citizens in cyber space. This demonstrates that there is a need for organisations to have a clear roadmap to implement and improve on their own cybersecurity capabilities. South African organisations need to take a proactive stance in cybersecurity because businesses rely heavily on technology for day-to-day operations. Currently cyber-attacks cost South African organisations over R2 billion, and the current work-from-home arrangement that most organisations have implemented will only worsen the situation. While a cybersecurity roadmap will differ in every organisation based on the organisation’s vision, goals, and objectives, along with their information technology (IT) and operations technology (OT), a starting point is perhaps the identification of key research and development (R&D) areas together with key activities that organisations can focus on in order to improve their cybersecurity capabilities. Cybersecurity capabilities are tools that organisations use to strengthen their organisation and protect themselves from potential cyber threats. The purpose of this study was to investigate R&D areas that organisations should invest in for the purpose of improving their cybersecurity capabilities. There are various subfields in cybersecurity that can be explored for organisations to advance their cybersecurity capabilities. Five integral R&D dimensions were identified together with key activities and are presented and discussed. A conceptual framework is also presented which maps the R&D dimensions and activities to the main pillars of cybersecurity, i.e., People, Processes, and Technology. South African organisations could reference the framework and adapt it for their business needs to protect themselves against potential cyber threats.
An aerodynamic CFD analysis of inlet swirl in a micro-gas turbine combustor
(2023-07) Meyers, Bronwyn C; Grobler, Jan-Hendrik; Snedden, GC
A combustor was designed for a 200N micro-gas turbine [1, 2] using the NREC preliminary combustor design method [1, 2, 3]. During the design process, there are various aspects where there are no definitive methodologies for specifying the design detail, such as the design of the hole-sets, and multiple options can be derived that can satisfy the required mass flow split and pressure drop for a particular hole-set.
Aerodynamic design of an electronics pod to maximise its carriage envelope on a fast-jet aircraft
(2024-12) Du Rand, R; Jamison, Kevin A; Huyssen, Barbara
The purpose of this paper is to reshape a fast-jet electronics pod’s external geometry to ensure compliance with aircraft pylon load limits across its carriage envelope while adhering to onboard system constraints and fitment specifications. Initial geometric layout determination used empirical methods. Performance approximation on the aircraft with added fairings and stabilising fin configurations was conducted using a panel code. Verification of loads was done using a full steady Reynolds-averaged Navier–Stokes solver, validated against published wind tunnel test data. Acceptable load envelope for the aircraft pylon was defined using two already-certified stores with known flight envelopes. Re-lofting the pod’s geometry enabled meeting all geometric and pylon load constraints. However, due to the pod's large size, re-lofting alone was not adequate to respect aircraft/pylon load limitations. A flight restriction was imposed on the aircraft’s roll rate to reduce yaw and roll moments within allowable limits. The geometry of an electronics pod was redesigned to maximise the permissible flight envelope on its carriage aircraft while respecting the safe carriage load limits determined for its store pylon. Aircraft carriage load constraints must be determined upfront when considering the design of fast-jet electronic pods. A process for determining the unknown load constraints of a carriage aircraft by analogy is presented, along with the process of tailoring the geometry of an electronics pod to respect aerodynamic load and geometric constraints.
An empirical evaluation of the main factors of a cybersecurity culture in South African E-health institutions using multiple linear regression
(2025-08) Mwim, NE; Mtsweni, Jabu S; Chimbo, B
E-health institutions are prominent targets for cybercriminals due to their reliance on information technology systems and issues related to the users have been identified as the biggest security weakest. Hence, while cybersecurity culture (CSC) research emphasizes the necessity of the human factor, limited empirical work has been done in the context of e-health in Africa. Therefore, an empirical evaluation was conducted to identify how preparedness, responsibility, management, technology and environment influence cybersecurity in South African e-health institutions. This quantitative research studied e-health institutions in the Mpumalanga province of South Africa. Various methods were used to investigate the multiple linear regression effects of the main factors of CSC and the results show that although the preparedness (Beta = 0.281; p-value < 0.05) and environment (Beta = 0.500; p-value < 0.05) factors had the greatest influence, management, technology and environment had a positive effect on CSC. These factors contributed 48.2 % to the variance (R-Squared). The study seems to be the first empirical study that combines the human factor domain framework (HFD) with other theoretical frameworks to identify critical factors of CSC. Furthermore, the impact of technology on CSC was empirically tested. The study is significant as it identified key factors that contributed to the institution’s CSC and quantified their impact. These results can enable e-health institutions to make decisions based on evidence regarding their cybersecurity interventions, strategy and practices. However, the empirical evaluation was limited to one context, namely the Mpumalanga province in South Africa and at two hospitals selected based on easy access (convenience) and purposive sampling with criteria based on work experience and knowledge of CSC limited the number of participants eligible to participate.
An optical gas imaging technique based on strobed illumination
(2024-12) Chirindo, Mathews; Cox, Ettienne; Duness, Kahesh
Gas leakage from equipment poses undesirable safety, environmental and operational impacts. Many optimal gas imaging techniques exist which detect and visualize gas plumes. However, most of these techniques struggle to produce clear images when the temperature gradient between the scene background and the gas plume is small. This paper presents an optical gas imaging technique that is based on strobed illumination, wherein the strobing frequency of the illuminating device is associated with the camera frame rate. Experimental test results are presented to show the improved detection of volatile organic compound gases during strobed illumination under dark room laboratory conditions where the percentage contrast value of the illuminated gas relative to its background varies by 50.8% The test results for the detection of sulphur hexafluoride gas and liquid petroleum gas under an outside environment are also presented.
Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality
(2023-03) Kgaphola, Motsoko J; Ramoelo, Abel; Odindi, J; Mwenge Kahinda, Jean-Marc; Seetal, Ashwin R
Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.
Assessing the quality of acquired images to improve ear recognition for children
(2023-06) Ntshangase, Cynthia S; Ndlovu, Lungisani; Stofile, Akhona
The use of biometrics to secure the identity of children is a continuous research worldwide. In the recent past, it has been realized that one of the promising biometrics is the shape of the ear, especially for children. This is be cause most of their biometrics change as they grow. However, there are shortcomings involved when using ear recognition in children, usually caused by the surrounding environment, and children can be at times uncooperative, such as moving during image acquisition. Consequently, the quality of acquired images might be affected by issues such as partial occlusions, blurriness, sharpness, and illumination. Therefore, in this paper, a method of image quality assessment is proposed. This method detects whether the images are affected by partial occlusions, blurriness, sharpness, or illumination. This method assesses the quality of the image to improve ear recognition for children. In this paper, four different test experiments were performed using the AIM database, IIT DELHI ear database, and ear images collected by Council for Scientific and Industrial Research (CSIR) researchers. The Gabor filter and Scale Invariant Feature Transform (SIFT) feature comparison methods were used to assess the quality of images. The experimental results showed that partial ear occlusions has less than 16 key points, resulting in low identification accuracy. Meanwhile, blurriness and sharpness were measured using the sharpness value of the image. Therefore, if the sharpness value is below 13, it means that the image is blurry. On the other hand, if the sharpness value is greater than 110, the image quality affects the ex tracted features and reduces the identification accuracy. Furthermore, it was discovered that the level of illumination in the image varies, the higher the illumination effect, such as the value above 100 affects the features and reduces the identification rate. The overall experimental evaluations demonstrated that image quality assessment is critical in improving ear recognition accuracy.
Assessing tools for detecting AI-generated content in higher education
(2025-01) Baloyi, Errol; Siphambili, Nokuthaba; Mahlasela, Oyena N
Artificial Intelligence (AI) has rapidly transformed the world, particularly following the introduction of Chat Generative Pre-Trained Transformer (ChatGPT) on November 30, 2022. This innovation has sparked a surge of interest in AI, leading to significant investments and attention in both the private and public sectors. AI applications are now widespread, ranging from smart farming to automated cyber threat detection. In higher education, AI has emerged as a potential game changer, enhancing learning experiences and expanding educational access to diverse communities. For example, some institutions have utilized AI to reduce dropout rates, while others have employed AI for student assistance. Research has also shown that students primarily use AI tools like ChatGPT for academic tasks, such as writing assignments and conducting research projects. In South Africa, a recent survey of educational leaders highlighted a growing push to integrate new AI tools, like ChatGPT, into the educational system. However, the use of AI has raised ethical concerns, particularly regarding plagiarism. For instance, some students at the University of South Africa (UNISA) faced disciplinary action after it was discovered that they had used AI tools inappropriately. A gap exists in the ethical use of AI in higher education, although some universities, such as the University of Cape Town (UCT), are making progress. UCT has published student guidelines on the ethical use of AI tools, which include ensuring that any final product is the student’s own work and not simply copied from an AI generator. Therefore, the objective of this paper is to evaluate free AI detection tools that can help students check their work and ensure they are not unknowingly submitting AI-generated content. This will also ensure that, if students do use AI, they properly acknowledge it, as another key clause in the UCT guidelines and similar policies requires individuals to acknowledge any use of AI in their work. Each tool was assessed based on its features, performance, usability, and support.
Assessment of homegarden agroforestry for sustainable land management intervention in a degraded landscape in South Africa
(2021-12) Musvoto, Constansia D; Kgaphola, Motsoko J; Mwenge Kahinda, Jean-Marc
Agroforestry-based sustainable land management (SLM) interventions provide opportunities for tackling land degradation and its associated socio-economic issues. Agroforestry is not a guaranteed SLM fix as every agroforestry practice is not automatically relevant to each context. It is critical to identify key considerations for ensuring a good fit between agroforestry and the receiving environment. This study identifies and analyses key factors for assessing the context-specific suitability of an agroforestry practice for SLM using a case-study of homegarden agroforestry in a degraded catchment. An analysis of biophysical and socio-economic characteristics of the catchment covering land degradation, SLM aspirations of residents, agriculture and agroforestry activities was conducted through literature review, field observations, GIS and remote sensing, stakeholder engagement and a questionnaire survey. Considerations in agroforestry practice assessment for SLM include agricultural and SLM objectives, which at our study site were increased crop production and arresting soil erosion. Availability of requisite resources, namely land, water and fencing; stakeholder interest in the tree and/or crop planting, species of interest and suitability of the species for the biophysical conditions should also be assessed. We propose a framework for systematically working through the relevant factors and assessing the suitability of an agroforestry practice for SLM intervention in a specific context. Based on the framework, homegarden agroforestry is an appropriate SLM intervention as it could meet stakeholders' SLM and agricultural objectives. Identification and systematic assessment of relevant factors are critical for ensuring the acceptability of agroforestry practice in a locality and the sustainability of associated SLM interventions.
Biaxial estimation of biomechanical constitutive parameters of passive porcine sclera soft tissue
(2022-02) Ndlovu, Z; Desai, D; Pandelani, Thanyani A; Ngwangwa, H; Nemavhola, F
This study assesses the modelling capabilities of four constitutive hyperelastic material models to fit the experimental data of the porcine sclera soft tissue. It further estimates the material parameters and discusses their applicability to a finite element model by examining the statistical dispersion measured through the standard deviation. Fifteen sclera tissues were harvested from porcine’ slaughtered at an abattoir and were subjected to equi-biaxial testing. The results show that all the four material models yielded very good correlations at correlations above 96%. The polynomial (anisotropic) model gave the best correlation of 98%. However, the estimated material parameters varied widely from one test to another such that there would be need to normalise the test data to avoid long optimisation processes after applying the average material parameters to finite element models. However, for application of the estimated material parameters to finite element models, there would be need to consider normalising the test data to reduce the search region for the optimisation algorithms. Although the polynomial (anisotropic) model yielded the best correlation, it was found that the Choi-Vito had the least variation in the estimated material parameters, thereby making it an easier option for application of its material parameters to a finite element model and requiring minimum effort in the optimisation procedure. For the porcine sclera tissue, it was found that the anisotropy was more influenced by the fiber-related properties than the background material matrix-related properties.
Biaxial estimation of biomechanical constitutive parameters of passive porcine sclera soft tissue
(2022-02) Ndlovu, Z; Desai, D; Pandelani, Thanyani A; Ngwangwa, H; Nemavhola, F
This study assesses the modelling capabilities of four constitutive hyperelastic material models to fit the experimental data of the porcine sclera soft tissue. It further estimates the material parameters and discusses their applicability to a finite element model by examining the statistical dispersion measured through the standard deviation. Fifteen sclera tissues were harvested from porcine’ slaughtered at an abattoir and were subjected to equi-biaxial testing. The results show that all the four material models yielded very good correlations at correlations above 96%. The polynomial (anisotropic) model gave the best correlation of 98%. However, the estimated material parameters varied widely from one test to another such that there would be need to normalise the test data to avoid long optimisation processes after applying the average material parameters to finite element models. However, for application of the estimated material parameters to finite element models, there would be need to consider normalising the test data to reduce the search region for the optimisation algorithms. Although the polynomial (anisotropic) model yielded the best correlation, it was found that the Choi-Vito had the least variation in the estimated material parameters, thereby making it an easier option for application of its material parameters to a finite element model and requiring minimum effort in the optimisation procedure. For the porcine sclera tissue, it was found that the anisotropy was more influenced by the fiber-related properties than the background material matrix-related properties.
Biometric recognition of infants using fingerprint, iris and ear biometrics
(2021-02) Moolla, Yaseen; De Kock, Antonie J; Mabuza-Hocquet, Gugulethu P; Ntshangase, Cynthia S; Nelufule, Nthatheni; Khanyile, Nontokozo P
Biometric recognition is often used for adults for a variety of purposes where an individual’s identity must be ascertained. However, the biometric recognition of children is an unsolved challenge. Solving this challenge could protect children from identity theft and identity fraud, help in reuniting lost children with their parents, improve border control systems in combatting child trafficking, and assist in electronic record-keeping systems. In order to begin the development of biometric recognition systems for children, researchers collected fingerprint, iris, and outer ear shape biometric information from infants. Each modality provides different challenges. Where possible, the performance of existing hardware and software that was developed for adults was assessed with infants. Where necessary, novel hardware or software was developed. For the ear modality, existing hardware and software which have previously been applied to adults were applied to children. For the iris modality, existing hardware was used to acquire the images, while adjustments to the existing preprocessing algorithms were applied to cater for the localisation and segmentation of infant irises. For the fingerprint modality, novel hardware and image processing software were developed to acquire fingerprints from infants, and convert the images into a format which is backward compatible with existing international standards for minutiae extraction and comparison. The advantages and disadvantages of using each of these modalities during the first year of life were compared, based on both qualitative assessments of usage, and quantitative assessments of performance. While there is no conclusively best modality, recommendations of usage for each modality were provided.
Bistatic RCS measurements of large targets in a compact range
(2025) Potgieter, Monique; Odendaal, JW; Blaauw, Ciara; Joubert, J
This communication illustrates the ability to perform bista tic radar cross-section (RCS) measurements at a fixed bistatic angle in a compact range. Literature regarding bistatic RCS measurements in compact ranges is limited. The traditional setup of a compact range was adapted to perform bistatic RCS measurements. These bistatic measurements were conducted on canonical and complex realistic scale airframe models. The targets were illuminated with a plane wave created by an offset parabolic dish reflector. The bistatic scattering of the targets was measured by placing a receive antenna at a fixed bistatic angle and finite distance in the compact range. This communication also investigates the effect of the finite separation between the targets and the receiver on the bistatic scattering measurements of large complex targets. The accuracy of the bistatic RCS measurements is compared to full-wave simulations conducted with FEKO using the multilevel fast multipole method solver. Quantitative comparisons are drawn between the simulations and measurements using the feature selective validation method.
CACC: Context-aware congestion control approach for lightweight CoAP/UDP-based Internet of Things traffic
(John Wiley and Sons Ltd, 2020-02) Akpakwu, GA; Hancke, GP; Abu-Mahfouz, Adnan MI
With the emerging applications of the Internet of Things (IoT), a congestion control mechanism becomes a critical phenomenon for efficient communication in networks of constrained devices. The Internet Engineering Task Force developed the constrained application protocol (CoAP) as a standard communication protocol that favors lightweight interoperability for accommodating resource‐constrained devices. However, the base CoAP specification congestion control is insensitive to various network conditions. Thus, differentiating the scenario of packet loss due to bit error rate and congestion, and identifying correct round trip time (RTT) of retransmitted message‐acknowledgement is quite essential to adapt the CoAP behavior based on the network status. In this paper, we present a context‐aware congestion control (CACC) approach for lightweight CoAP/user datagram protocol–based IoT traffic. The CACC proposes mechanisms that include retransmission timeout (RTO) estimator, retransmission count–based smoothed round‐trip‐time observation, lower bound RTO restriction approach, and aging concept. The proposed RTO estimators utilize the strong, weak, and failed RTT to identify exact network status and provide adaptive congestion control. The CACC incorporates the variable of retransmission count in request‐response interaction model to mitigate the negative variation in RTT due to the fluctuation in the IoT environment. Moreover, with lower bound RTO restriction approach, the unnecessary spurious retransmissions are avoided, and the aging mechanism limits the validity of the RTO value to improve the efficiency of the proposed scheme. The proposed model is validated against baseline CoAP and CoCoA+ using Contiki OS and the Cooja simulator. The results are impressive under different network topologies.
Comparative analysis of HTTP request handling in different Python frameworks
(2025-11) Malatjie, Patrick G; Faniso-Myaka, Zimbini
The Hypertext Transfer Protocol (HTTP) has become a fundamental component for client-server communication in web applications. This paper investigates the performance and suitability of HTTP request handling in three popular Python frameworks: Flask, Django, and FastAPI. Through comparative analysis, we evaluate the effectiveness of each framework based on speed, scalability, and ease of implementation, providing recommendations for its use in various development scenarios.
Conceptual mapping of the cybersecurity culture to human factor domain framework
(2023-03) Mwim, EN; Mtsweni, Jabu S; Chimbo, B
Human related vulnerability challenges continue to increase as organisations intensify their use of interconnected technologies for operations particularly due to the emergence of COVID-19 pandemic. Notwithstanding the challenge of a human problem on cybersecurity, existing cybersecurity measures predominately focused on technological solutions which on their own have proven to be insufficient. To ensure all-inclusive cybersecurity solution, efforts are shifting to accommodate human angle which complements technological efforts towards eradicating cybersecurity challenges hence the move to cybersecurity culture (CSC). The importance of the human-related factor on the security of information and IT system has been emphasised by various research leading to the development of Human Factor Diamond (HFD) framework. This paper at the conceptual level mapped the articulated list of identified CSC factors to the HFD framework to determine the CSC factors that are associated with the different domains of human factor framework. The mapping depicts that each domain of human factor framework has CSC factors associated to it. Management appeared as the domain with the predominate number of factors, followed by responsibility, environment and preparedness respectively.

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