Showing items 1 - 20 of 150

Your selections:

A Practical Use for AI-Generated Images

  • Authors: Boby, Alden , Brown, Dane L , Connan, James
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/463345 , vital:76401 , xlink:href="https://link.springer.com/chapter/10.1007/978-3-031-43838-7_12"
  • Description: Collecting data for research can be costly and time-consuming, and available methods to speed up the process are limited. This research paper compares real data and AI-generated images for training an object detection model. The study aimed to assess how the utilisation of AI-generated images influences the performance of an object detection model. The study used a popular object detection model, YOLO, and trained it on a dataset with real car images as well as a synthetic dataset generated with a state-of-the-art diffusion model. The results showed that while the model trained on real data performed better on real-world images, the model trained on AI-generated images, in some cases, showed improved performance on certain images and was good enough to function as a licence plate detector on its own. The study highlights the potential of using AI-generated images for data augmentation in object detection models and sheds light on the trade-off between real and synthetic data in the training process. The findings of this study can inform future research in object detection and help practitioners make informed decisions when choosing between real and synthetic data for training object detection models.
  • Full Text:
  • Date Issued: 2023

Activated carbon-decorated polyacrylonitrile fibers and their porphyrin-immobilized composites for removal of methylene blue dye and Ciprofloxacin in water

  • Authors: Oyim, James , Amuhaya, Edith K , Nyokong, Tebello
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/${Handle} , vital:65077 , xlink:href="https://doi.org/10.1080/10601325.2023.2183868"
  • Description: Photocatalyst adsorbents are an appealing group of materials for environmental applications. Herein, we study a new simple, inexpensive, yet very effective adsorbent photocatalyst based on porphyrin immobilized activated carbon-decorated polyacrylonitrile, InP(PAN/AC), for removal of methylene blue dye and Ciprofloxacin in water under Xe-lamp and sunlight irradiation (the latter for Ciprofloxacin only). Our results shed light on developing the most effective and sustainable adsorbent photocatalysts that can easily be industrialized due to the ease of preparation through electrospinning coupled with the readily available preparation materials. After five cycles, the InP(PAN/AC) maintained high methylene dye removal efficiency and structural integrity. Significantly, we propose the coordinated contribution of singlet oxygen and hydroxyl radical in the photodegradation process and highlight the importance of such an integrated system with adsorption and photodegradation capabilities for water treatment.
  • Full Text:
  • Date Issued: 2023

Agent-based model development of a complex socio-ecological system: Methods for overcoming data and domain limitations

  • Authors: James, C. L , Bradshaw, Karen L
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/440189 , vital:73755 , xlink:href="https://doi.org/10.1016/j.ecoinf.2023.102224"
  • Description: Agent-based models (ABMs) are appropriate tools for modelling socio-ecological systems due to their ability to handle complexity. However, development of such models is often an intensive process. There are many tutorials on the general methods and steps in ABM development but there are not necessarily practical details on how to overcome certain challenges. Honeybush (Cyclopia spp.), a kind of fynbos vegetation found in the Western and Eastern Cape mountains, is an important ecological and agricultural product in South Africa. It is considered a complex system due to its variability and unpredictability. The honeybush tea industry faces the challenge of meeting emerging market demands while maintaining sustainable harvesting practices, in the midst of an uncertain future due to climate change. We created a prototype model, HoneybushModel, using the MARS framework, a C# multi-agent simulation toolkit. The model was validated using historic data. Whilst outlining the development processes used to create the Honeybush Model, this paper provides a methodology for the development of such models and demonstrates techniques for addressing data, domain and framework limitations. The implemented model also acts as a case study for similar systems that could be modelled using an ABM.
  • Full Text:
  • Date Issued: 2023

Agent-Based Modeling and Simulation for Transmission Dynamics and Surveillance of Dengue: Conceptual and Design Model

  • Authors: Pascoe, Luba , Nyambo, Devotha G , Bradshaw, Karen L , Clemen, Thomas
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/440200 , vital:73756 , xlink:href="https://doi.org/10.1109/AFRICON55910.2023.10293299"
  • Description: African countries need to strengthen surveillance and control of arboviral diseases such as dengue due to increased outbreaks and spread of arboviruses. Climatic, socio-environment, and ecological variables influence the spread of dengue fever in Sub-Saharan Africa. This paper presents an Agent-Based conceptual and design model for dengue fever developed using the Multi-Agent Research and Simulation (MARS) framework. The study analyzes dengue fever's spatial distribution and identifies the causal relationship between the disease and its climatic and environmental variables. Agent-based modeling (ABM) was used to comprehend the spatial patterns of variation to determine the ecological association between the observed spatio-temporal variations in dengue fever. The domain and design model of an ABM for the surveillance of dengue fever is presented based on the Overview, Design Concepts, and Details (ODD) protocol. Model input parameters and input data for the study area are also presented. The dengue ABM can be adopted and reused for modeling other diseases and other complex problems from different domains while ensuring that their unique characteristics and appropriate modifications are considered to ensure the model's validity and relevance to the new context.
  • Full Text:
  • Date Issued: 2023

Agricultural disturbance affects taxonomic and functional diversity of Afrotropical macroinvertebrate composition in a South African river system

  • Authors: Akamagwuna, Frank C , Odume, Oghenekaro N , Richoux, Nicole B
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/454293 , vital:75333 , xlink:href="https://doi.org/10.1016/j.indic.2023.100251"
  • Description: Developing species-level biomonitoring tools to monitor riverine systems threatened by anthropogenic pollution, including local agricultural activities in the Afrotropical region, remain a critical challenge. Here we explored the utility of taxonomic-based (diversity, richness, and composition) as well as functional-based (functional diversity) indices to examine the effects of agricultural disturbance on macroinvertebrate communities in the Kat River, Eastern Cape Province of South Africa. We collected physicochemical parameters and macroinvertebrates from eight sites delineated into four land-use categories (highly impacted, HIC; impacted category, IC; moderately impacted, MIC and least impacted, LIC) using agricultural land cover. We recorded 70 macroinvertebrate taxa belonging to 49 families and 48 genera in the Kat River. Redundancy analysis (RDA) and Pearson correlation analysis revealed that species of Lymnaeidae, Belostomatidae, Planorbidae and Libellulidae families and class Oligochaeta were tolerant to agricultural disturbance, as they were dominant in the highly impacted sites and were significantly associated with high salinity, temperature, total dissolved solids (TDS), flow velocity and nutrients. Conversely, species of Baetidae, Caenidae and Potamonautidae were negatively associated with the highly impacted sites and high salinity, temperature, and nutrients. On the other hand, taxonomic indices showed more sensitivity to indicators of agricultural pollution than functional indices, with taxon richness, Shannon index, Simpson's index and Margalef's index declining significantly in the highly disturbed sites (p less than 0.05). They were negatively associated with high electrical conductivity, large river width, and high nitrite and nitrate concentrations; hence they were identified as indicator metrics sensitive to agricultural pollution. Overall, our study revealed that agricultural disturbance could differentially affect the structure and function of macroinvertebrates, and indicator taxonomic and functional indices were identified for long-term monitoring of rivers that drain agricultural landscapes.
  • Full Text:
  • Date Issued: 2023

An Automated System for Detecting and Preventing Phishing Attempts on Steam Accounts

  • Authors: Sonne, Kabir , Chindipha, Stones D
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/473729 , vital:77676 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10389578"
  • Description: In recent years Steam has become a giant in the gaming industry. The Valve-owned digital distribution platform held an estimated 75% of market share in 2013, and continues to grow. However, with such a large user base comes the ever-increasing threat of security breaches in both the Steam database and individual Steam user accounts. While Steam does make use of a mobile authentication app, users are still susceptible to malware and/or phishing attempts that can cause users to lose access to their accounts through manipulation or gaining access to recovery email accounts. This project aims to investigate how the authentication process can be improved or if a solution can be created to help prevent the worst-case scenario when users become victims of phishing attacks.
  • Full Text:
  • Date Issued: 2023

An Evaluation of Machine Learning Methods for Classifying Bot Traffic in Software Defined Networks

  • Authors: Van Staden, Joshua , Brown, Dane L
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/463357 , vital:76402 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-19-7874-6_72"
  • Description: Internet security is an ever-expanding field. Cyber-attacks occur very frequently, and so detecting them is an important aspect of preserving services. Machine learning offers a helpful tool with which to detect cyber attacks. However, it is impossible to deploy a machine-learning algorithm to detect attacks in a non-centralized network. Software Defined Networks (SDNs) offer a centralized view of a network, allowing machine learning algorithms to detect malicious activity within a network. The InSDN dataset is a recently-released dataset that contains a set of sniffed packets within a virtual SDN. These sniffed packets correspond to various attacks, including DDoS attacks, Probing and Password-Guessing, among others. This study aims to evaluate various machine learning models against this new dataset. Specifically, we aim to evaluate their classification ability and runtimes when trained on fewer features. The machine learning models tested include a Neural Network, Support Vector Machine, Random Forest, Multilayer Perceptron, Logistic Regression, and K-Nearest Neighbours. Cluster-based algorithms such as the K-Nearest Neighbour and Random Forest proved to be the best performers. Linear-based algorithms such as the Multilayer Perceptron performed the worst. This suggests a good level of clustering in the top few features with little space for linear separability. The reduction of features significantly reduced training time, particularly in the better-performing models.
  • Full Text:
  • Date Issued: 2023

An Exploration of Flow Control Using Machine Learning and Computational Fluid Dynamics

  • Authors: Bradshaw, Karen L , Cornfield Matthew
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/440211 , vital:73757 , xlink:href="https://doi.org/10.59200/ICARTI.2023.017"
  • Description: Although numerous studies relating to computational fluid dynamics and machine learning have been conducted in relation to automotive development, the majority focus on either early development using completed 3D models, or the final testing stages of development, or machine learning accelerated computational fluid dynamic simulations. While this approach is helpful in software development and simulation, it is not easily adaptable to automotive design where the final model is constantly changing and being modified. Consequently, the aim of this study is to propose a method for conducting computational fluid dynamics and machine learning concurrently to accelerate the development process. The proposed method is used to design and improve the aerodynamic efficiency of an object. The approach focuses on developing, implementing, and comparing machine learning models capable of generating optimised three-dimensional objects with the required geometry to direct airflow paths required in applications such as pressure generation, as needed for both active and passive flow control. The study concludes that both decision tree regression and long short-term memory (LSTM) autoencoder models could be used to optimise the aerodynamic efficiency of solid bodies, but that the LSTM autoencoder performs better overall. An undesirable effect of the shape optimisation is an overall reduction in shape size as optimization increases.
  • Full Text:
  • Date Issued: 2023

Analyzing agricultural financing for resettled farmers in Zimbabwe: the case of targeted Command Agricultural program in Mutare District

  • Authors: Mafirakurewa, Tariro https://orcid.org/0009-0000-6587-4524
  • Date: 2023
  • Subjects: Agricultural administration--Finance , Farmers -- Zimbabwe , Agriculture -- Economic aspects
  • Language: English
  • Type: Master's theses , text
  • Identifier: http://hdl.handle.net/10353/28255 , vital:73985
  • Description: Agriculture plays a paramount role in the economy of many countries including Zimbabwe where more than 70 percent of the population depends on agricultural activities for their livelihoods. Smallholder farmers’ access to agricultural credit is vital for the development and growth of Zimbabwe’s agricultural sector, hence agricultural financing is crucial in rural development. Despite the Government’s efforts to provide affordable agricultural credit services to its majority smallholder farmers’ participation is still meager. The aim of this study is to analyze agricultural financing for resettled farmers in Zimbabwe, with special focus on the command agricultural loans in the Mutare district. A multistage sampling technique was employed in this study. Firstly purposive selection of Manicaland province was carried out because it is endowed with the five natural farming regions found in Zimbabwe. The second stage involved a random selection of 4 out of 7 districts with favorable climatic conditions for maize production. Thirdly, the study also carried out a purposive selection of Mutare district among the four districts with favorable climatic conditions, given the time and financial constraints. The last stage involved the use of stratified sampling technique, where the sample was divided into two strata. Stratum 1 with A1 farmers and stratum two consisting of A2 farmers, and a random sample was selected from each stratum. The study involved 301 A1 farmers and 49 A2 farmers, making a total sample of 350 farmers used for this study. Double hurdle was employed to examine the factors influencing A1 and A2 farmers` participation in command agriculture loans in the study area. Multinomial logistic regression model was also applied to investigate the determinants of command agriculture loan repayment, while propensity score matching technique was used to examine the impacts of command agriculture loans on maize productivity and profitability of A1 and A2 farmers. The results revealed that family size, and distance from the market GMB positively influence farmers likelihood to participate in in the command agricultural loan. While family size, farmer type and distance from the market were proven to have a positive significant influence on the extent of participation in command agriculture. Also training on the command agriculture loan and gender were proven to have a negative signification influence on the extent of farmers` participation in command agriculture loan. The maximum likelihood estimates of the multinomial logistic regression revealed that age and output levels significantly influence resettled farmers` likelihood to partly pay their loans. Also, the likelihood estimates of the multinomial logistic regression showed that distance from the market and output levels have a positive influence on resettled farmers` likelihood of fully paying the command agriculture loan. Access to extension services to extension services was proven to negatively influence farmers` likelihood to fully pay the loan. The results also revealed that participating in command agriculture significantly impacted productivity at the 1 percent level, while it was not significant in the participants' profitability. The results show that participating in command agriculture increases productivity by 0.93 tonnes hectare. The study recommends the intensification of extension service supply to ensure that farmers are receiving relevant agricultural training, mainly on climate change adaptation strategies. This will help resettled farmers to adjust and adapt to their new farming environments and, in turn, have a positive impact on their production levels. Also, to improve farmers’ profitability the GMB selling price should be in American dollars USD and not paid in part RTGS and part USD, because the RTGS part is always outstripped by inflation. , Thesis (MSc) -- Faculty of Science and Agriculture, 2023
  • Full Text:
  • Date Issued: 2023

Asymmetrical zinc phthalocyanine conjugated to various nanomaterials for applications in phototransformation of organic pollutants and photoinactivation of bacteria

  • Authors: Mgidlana, Sithi , Openda, Yolande Ikala , Nyokong, Tebello
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/360344 , vital:65081 , xlink:href="https://doi.org/10.1016/j.molstruc.2022.134850"
  • Description: Zinc phthalocyanine (ZnPc) complexes are linked to metallic nanoparticles covalently via amide and ester bonds. The photocatalytic activity of the conjugates of ZnPc complexes with NiWO4, Ag2WO4, CoWO4 and Ag-Fe3O4 nanoparticles are evaluated for photodegradation of methylene blue, tetracycline, and dibenzothiophene. The photocatalytic efficiencies of the prepared phthalocyanine complexes increased in the presence of nanoparticles. This work also reports on the photodynamic antimicrobial chemotherapy activity of these materials against Staphylococcus aureus (S. aureus) bacteria. The results indicate that Ag2WO4 based nanoconjugates exhibit high antimicrobial activity with higher log reduction compared to NiWO4, CoWO4 and Ag-Fe3O4 based materials.
  • Full Text:
  • Date Issued: 2023

Best practices in the use and exchange of microorganism biological control genetic resources

  • Authors: Mason, Peter G , Hill, Martin P , Smith, David , Silvestri, Luciano C , Weyl, Philip S R , Brodeur, Jacques , Vitorino, Marcello Diniz
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/417927 , vital:71495 , xlink:href="https://doi.org/10.1007/s10526-023-10197-3"
  • Description: The Nagoya Protocol actions the third objective of the Convention on Biological Diversity and provides a framework to effectively implement the fair and equitable sharing of benefits arising out of the use of genetic resources. This includes microorganisms used as biological control agents. Thus biological control practitioners must comply with access and benefit-sharing regulations that are implemented by countries providing microbial biological control agents. A review of best practices and guidance for the use and exchange of microorganisms used for biological control has been prepared by the IOBC Global Commission on Biological Control and Access and Benefit-Sharing to demonstrate commitment to comply with access and benefit-sharing requirements, and to reassure the international community that biological control is a very successful and environmentally safe pest management strategy that uses biological resources responsibly and sustainably. We propose that best practices include the following elements: collaboration to facilitate information exchange about the availability of microbial biological control agents and where they may be sourced; freely sharing available knowledge in databases about successes and failures; collaborative research with provider countries to develop capacity; and production technology transfer to provide economic opportunities. We recommend the use of model concept agreements for accessing microorganisms for scientific research and non-commercial release into nature where access and benefit-sharing regulations exist and where regulations are not restrictive or do not exist. We also recommend a model agreement for deposition of microbial biological control agents into culture collections.
  • Full Text:
  • Date Issued: 2023

Co phthalocyanine mediated electrochemical detection of the HER2 in the presence of Au and CeO2 nanoparticles and graphene quantum dots

  • Authors: Centane, Sixolile , Nyokong, Tebello
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/360372 , vital:65083 , xlink:href="https://doi.org/10.1016/j.bioelechem.2022.108301"
  • Description: In this work, cobalt tetra phenoxy acetic acid phthalocyanine (CoTAPc) is investigated as an electron mediator, immobilization platform for an HB5 aptamer and to enhance the electrochemical signal for the detection of human epidermal growth factor receptor 2 (HER2). Furthermore, the CoTAPc was combined individually with sulphur/nitrogen doped graphene quantum dots (SNGQDs), gold nanoparticles (AuNPs) and cerium oxide nanoparticles (CeO2NPs), on a glassy carbon electrode (GCE) via sequential adsorption. The CoTAPc and SNGQDs were also π-π stacked, used for electrode modification similarly to the rest of the other surfaces and applied towards the electrochemical detection of HER2. The designed sensors were characterized using electrochemical impedance spectroscopy (EIS). The designed aptasensors showed detection limits as low as 6.0 pg/mL. The real life applicability of the designed aptasensors was tested in human serum samples. The aptasensors showed great storage stability, sensitivity and specificity towards HER2, implying great potential for applications in early diagnosis of breast cancer.
  • Full Text:
  • Date Issued: 2023

Combination of photodynamic antimicrobial chemotherapy and ciprofloxacin to combat S. aureus and E. coli resistant biofilms

  • Authors: Openda, Yolande Ikala , Nyokong, Tebello
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/360384 , vital:65084 , xlink:href="https://doi.org/10.1016/j.pdpdt.2022.103142"
  • Description: Photodynamic antimicrobial chemotherapy (PACT) coupled with an antibiotic, ciprofloxacin (CIP), was investigated using two indium metallated cationic photosensitizers, a porphyrin (1) and a phthalocyanine (2). Applying PACT followed by the antibiotic treatment led to a remarkable reduction in the biofilm cell survival of two antibiotic-resistant bacterial strains, S. aureus (Gram-positive) and E. coli (Gram-nenative). Treating both bacteria strains with PACT alone showed no significant activity at 32 µM with 15 min irradiation, while CIP alone exhibited a minimum biofilm inhibition concentration (MBIC) at 4 and 8 µg/mL on S. aureus and E. coli, respectively following 24 h incubation. The combined treatment resulted in the complete eradication of the matured biofilms with high log10 reduction values of 7.05 and 7.20 on S. aureus and E. coli, respectively, at low concentrations. It was found that 15 min PACT irradiation of 8 µM of complexes (1 and 2) combined with 2 µg/mL of CIP have a 100% reduction of the resistant S. aureus biofilms. Whereas the total killing of E. coli was obtained when combining 8 µM of complex 1 and 16 µM of complex 2 both combined with 4 µg/mL of CIP.
  • Full Text:
  • Date Issued: 2023

Comparative situational analysis of comprehensive abortion care in four Southern African countries

  • Authors: Macleod, Catriona I , Reuvers, Megan , Reynolds, John H , Lavelanet, Antonella , Delate, Richard
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/441199 , vital:73865 , xlink:href="https://doi.org/10.1080/17441692.2023.2217442"
  • Description: We report on a comparative situational analysis of comprehensive abortion care (CAC) in Botswana, Eswatini, Lesotho and Namibia. We conducted systematic literature searches and country consultations and used a reparative health justice approach (with four dimensions) for the analysis. The following findings pertain to all four countries, except where indicated. Individual material dimension: pervasive gender-based violence (GBV); unmet need for contraception (15−17%); high HIV prevalence; poor abortion access for rape survivors; fees for sexual and reproductive health (SRH) services (Eswatini). Collective material dimension: no clear national budgeting for SRH; over-reliance on donor funding (Eswatini; Lesotho); no national CAC guidelines or guidance on legal abortion access; poor data collection and management systems; shortage and inequitable distribution of staff; few facilities providing abortion care. Individual symbolic dimension: gender norms justify GBV; stigma attached to both abortion and unwed or early pregnancies. Collective symbolic dimension: policy commitments to reducing unsafe abortion and to post-abortion care, but not to increasing access to legal abortion; inadequate research; contradictions in abortion legislation (Botswana); inadequate staff training in CAC. Political will to ensure CAC within the country’s legislation is required. Reparative health.
  • Full Text:
  • Date Issued: 2023

Contrasting effects of climate change on the invasion risk and biocontrol potential of the invasive Iris pseudacorus L. between Northern and Southern Hemisphere

  • Authors: Minuti, Gianmarco , Coetzee, Julie A , Stiers, Iris
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/423329 , vital:72048 , xlink:href="https://doi.org/10.1016/j.biocontrol.2023.105290"
  • Description: Iris pseudacorus is both a prized ornamental and an invasive aquatic plant that tends to grow dense monospecific stands, displacing the local vegetation and altering the hydrology of freshwater ecosystems. Originally from Europe, this species has historically invaded North America, China and Japan, and more recently spread through Argentina, South Africa and Australasia, where it is now a target for biological control. Field surveys within its native range have led to the selection of three candidate biocontrol agents. Prioritizing the best candidates for different regions constitutes a critical step, which could save significant time and resources before further cost-intensive experimental studies are conducted. Climate change is seldom taken into consideration in the prioritization process. In this regard, climatic suitability can be used to model the potential distributions of weeds and their candidate agents, both in space and time, thus allowing to identify areas at risk of invasion and predict where agents will be able to establish long-term. Accordingly, the objectives of this work were (i) to predict I. pseudacorus invasions and range shifts in the context of climate change; (ii) to identify wetland areas most at risk of invasion under present and future climatic conditions; and (iii) to prioritize the best suite of candidate biocontrol agents for different invaded ranges, worldwide. To do so, we modelled the present and future (2040–2060) climatic suitability of I. pseudacorus and its candidate agents using the software MaxEnt. Our results highlight a clear distinction between predictions for the Northern and Southern Hemispheres. In North America and eastern Asia, the area climatically suitable for I. pseudacorus is expected to increase and shift northwards. As for its biocontrol agents, very low suitability is predicted across these regions, further decreasing under future climatic conditions. On the other hand, climatically suitable areas for the plant in South America, southern Africa and Australasia are predicted, on average, to reduce in response to climate change. A decrease in climatic suitability is also expected for its candidate biocontrol agents which, however, would still maintain a significant range overlap with their host. These results can be used to prioritize areas most at risk of invasion and identify which combination of candidates could potentially provide the best level of control across different invaded ranges.
  • Full Text:
  • Date Issued: 2023

Count me in: Leopard population density in an area of mixed land‐use, Eastern Cape, South Africa

  • Authors: Bouderka, Safia , Perry, Travis W , Parker, Daniel M , Beukes, Maya , Mgqatsa, Nokubonga
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/462591 , vital:76317 , xlink:href="https://doi.org/10.1111/aje.13078"
  • Description: Although the leopard (Panthera pardus) has the widest range of any felid in the world is designated as a vulnerable species, mainly because of human-induced conflict (Jacobson et al., 2016). Our study focuses on a population of leopards on privately owned, mixed-use farmland (Baviaanskloof Hartland–BH hereafter) which is adjacent to the Baviaanskloof Mega Reserve (BMR) in the Baviaanskloof UNESCO World Heritage Site of the Eastern Cape, South Africa. Given the unique make-up of the region, with sometimes conflicting management objectives, the status of leopards in the broader Baviaanskloof is of particular interest to a range of stakeholders. However, despite the need for management decisions to be based on reliable and regular population monitoring efforts (Elliot et al., 2020), the last formal assessment of the leopard population in the Baviaanskloof was performed in 2011/2012 but published 9 years later (Devens et al., 2018). The only other assessment of the status of leopards in the region was an unpublished Master's project (McManus, 2009). Here, we use photographic captures of leopards and a Spatially Explicit Capture Recapture (SECR) analytical framework in the mixed-use BH region of the Baviaanskloof to generate an up-to-date leopard population density estimate that can inform conservation management of the species in this important World Heritage Site.
  • Full Text:
  • Date Issued: 2023

Cryptojacking Detection in Cloud Infrastructure Using Network Traffic

  • Authors: Kwedza, Philip , Chindipha, Stones D
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/473762 , vital:77679 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10389593"
  • Description: Cryptomining is a way to obtain cryptocurrency, by performing computationally complex puzzles in exchange for a reward. To perform this requires expensive specialised hardware to become profitable but most times, this is not viable. Cryptojacking is a cybercrime in which an attacker uses devices to mine cryptocurrency without permission. This attack can be extended to use the resources of networks and cloud infrastructure. This research aimed to develop a model that could detect cryptojacking automatically in a cloud environment, utilising network traffic. The models in this paper solved this by developing a machine learning model that could analyse cryptojacking in a dataset of network traffic from an attacked cloud server.
  • Full Text:
  • Date Issued: 2023

Crystal structure, Hirshfeld surface analysis and computational studies of (E)-2, 2-dimethyl-4-styryl-2, 3-dihydro-1H-benzo [b][1, 4] diazepine

  • Authors: Odame, Felix , Madanhire, T , Hosten, Eric C , Lobb, Kevin A
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/452677 , vital:75161 , xlink:href="https://doi.org/10.48317/IMIST.PRSM/morjchem-v11i3.40773"
  • Description: The crystal structure, Hirshfeld surface analysis, and computational studies of (E)-2,2-dimethyl-4-styryl-2,3-dihydro-1H-benzo[b][1,4]diazepine have been presented. The compound crystallized in the monoclinic space group P21/c with 8 molecules in it unit cell. A comparison of the experimental and computed bond lengths and bond angles showed good agreement among the results with varying deviations from each other. A discussion of the Hirshfeld surface analysis of the compound have been carried out to provide insight into the structural properties of the compound.
  • Full Text:
  • Date Issued: 2023

Crystal Structure, Hirshfeld Surface Analysis and Computational Studies of Two Benzo [b][1, 4] Diazepine Derivatives

  • Authors: Odame, Felix , Madanhire, T , Hosten, Eric C , Lobb, Kevin A
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/452689 , vital:75162 , xlink:href="https://doi.org/10.1134/S0022476623120041"
  • Description: The DFT computational studies, crystal structures and Hirshfeld surface analysis of (E)-4-(2-chlorostyryl)-2,2-dimethyl-2,3-dihydro-1H-benzo[b][1,4]diazepine (1) and (E)-4-(2-(2,2-dimethyl-2,3-dihydro-1H-benzo[b][1,4]diazepin-4-yl)vinyl)phenol (2) have been presented. The compounds crystallized in the monoclinic space group P21/c with 4 molecules in their unit cells each. The experimental and computed bond lengths and bond angles deviated from each other to some extent but also showed good agreement with each other in some cases. Hirshfeld surface analysis of the compounds provided further information about the structural properties of the compounds.
  • Full Text:
  • Date Issued: 2023

Darknet Traffic Detection Using Histogram-Based Gradient Boosting

  • Authors: Brown, Dane L , Sepula, Chikondi
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/464063 , vital:76472 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_59"
  • Description: The network security sector has observed a rise in severe attacks emanating from the darknet or encrypted networks in recent years. Network intrusion detection systems (NIDS) capable of detecting darknet or encrypted traffic must be developed to increase system security. Machine learning algorithms can effectively detect darknet activities when trained on encrypted and conventional network data. However, the performance of the system may be influenced, among other things, by the choice of machine learning models, data preparation techniques, and feature selection methodologies. The histogram-based gradient boosting strategy known as categorical boosting (CatBoost) was tested to see how well it could find darknet traffic. The performance of the model was examined using feature selection strategies such as correlation coefficient, variance threshold, SelectKBest, and recursive feature removal (RFE). Following the categorization of traffic as “darknet” or “regular”, a multi-class classification was used to determine the software application associated with the traffic. Further study was carried out on well-known machine learning methods such as random forests (RF), decision trees (DT), linear support vector classifier (SVC Linear), and long-short term memory (LST) (LSTM). The proposed model achieved good results with 98.51% binary classification accuracy and 88% multi-class classification accuracy.
  • Full Text:
  • Date Issued: 2023
  • Disclaimer
  • Privacy
  • Copyright
  • Contact