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Measurement of the average radiation dose to patients during intracranial aneurysm coil embolization
No full textThesis (MSc (Radiography))--Cape Peninsula University of Technology, 2019Introduction: Intracranial aneurysm coil embolization is a fluoroscopically guided interventional procedure that is often preferred over surgical clipping for the treatment of intracranial aneurysms. Fluoroscopically guided procedures are associated with high levels of radiation doses which have the potential to induce skin injuries; and this necessitates adherence to radiation protection measures, especially the optimization of radiation exposure during fluoroscopically guided procedures. Optimization of radiation exposure can be achieved by applying the as low as reasonably achievable (ALARA) principle and by implementing diagnostic reference levels (DRLs). Monitoring and documentation of radiation doses at the end of each procedure is also essential to identify patients that are at risk of developing radiation-induced injuries for possible follow-up. Aim: This research study aimed to determine the average radiation dose to patients' thyroid glands and skin during intracranial aneurysm coil embolization. The objectives were to establish preliminary DRLs for intracranial aneurysm coil embolization; to ascertain whether the anatomical location of the intracranial aneurysm had an effect on the radiation dose and to compare the measured thyroid gland and skin doses to the Monte Carlo calculated doses. Methods: A prospective quantitative research study was conducted on 34 participants who had intracranial aneurysms that required coil embolization during the study period. Radiation doses to the anterior neck of participants, over the thyroid gland region, were measured using lithium fluoride thermoluminescent dosimeters (TLDs). In addition, the air-kerma area product (KAP) values were used to determine the participants' skin dose and the DRLs. Considering that it is not possible to perform direct thyroid measurements on human beings, phantom-based simulation studies were performed to evaluate the difference between the dose measured on the anterior neck and the dose measured directly on the thyroid gland. Three different aneurysm coil embolization scenarios were simulated during the phantom-based simulation studies. TLDs were placed on the anterior neck and in the thyroid hole of the phantom, which represents the anatomical location of the thyroid gland, during each simulation. The thyroid and skin doses were also calculated using a Monte Carlo program. The measured thyroid gland and skin doses were compared to the doses obtained from Monte Carlo calculations. Results: The average percentage difference between the anterior neck doses and thyroid radiation doses was found to be 61%. This value was added to the radiation dose measured on the anterior neck of participants to obtain the thyroid absorbed doses during coil embolization procedures. The thyroid absorbed doses ranged between 3.2 and 20.95 mGy with a mean of 11.25 mGy. The KAP values ranged between 33 and 125 Gy.cm2. The DRL established during this study was 68 Gy.cm2, 616 image frames and 30 minutes of fluoroscopy time. There was no agreement between measured thyroid dose and calculated thyroid doses while there was strong positive correlation between measured and calculated skin doses. The results showed no statistically significant relationship between aneurysm location and the radiation dose. Conclusion: The skin doses in this research study were below the threshold doses suggested in the literature for deterministic effects of radiation. The study results therefore suggest that patients that undergo intracranial aneurysm coil embolization at the research site are not at risk of developing radiation-induced skin injuries. The established DRLs were also lower than internationally published DRLs for intracranial aneurysm coil embolization
Performance of the expanded public works programme in a selected department of the Western Cape Provincial Government, South Africa
No full textThesis (MTech (Public Management))--Cape Peninsula University of Technology, 2019.A socio-economic problem presently facing South Africa is the rate of youth unemployment, which is among the highest in the world. The South African Government has been involved in a number of initiatives, together with the advancement of a labour-intensive Expanded Public Works Programme (EPWP) in order to reduce unemployment and poverty. The EPWP was initiated in 2004 with the aim to place the jobless into productive work in the public sector social services where these EPWP beneficiaries are provided with relevant training and transfer of appropriate skills. However, the EPWP only creates temporary work opportunities that have limited influence on the lives of the beneficiaries. The main objective of the study was to examine the performance of the Youth Work Project (YWP) as an EPWP in a selected department of the Western Cape Provincial Government in order to determine its sustainability of job creation. The secondary aims of the study were to explain the process of the YWP as implemented through the EPWP by a selected department of the Western Cape Provincial Government. A third objective was to examine whether the Public Works employment opportunities enhance subsequent employability of participants once they exit this programme. Fourthly, recommendations was forwarded as to how best the EPWP can be used as a tool for helping unemployed youth with a permanent work opportunity. The sample frame computed of thirteen (13) individuals, therefore purposive sampling was considered the most suitable technique to use in this study. The semistructured interviews were conducted with five (5) management officials responsible for the EPWP and unstructured questionnaires were administered to eight (8) available EPWP beneficiaries placed at a selected department of the Western Cape Provincial Government
The utility of social network sites in facilitating business development: linkages between enterprise development and new media
Get PDFThesis (MTech (Entrepreneurship))--Cape Peninsula University of Technology, 2019SMEs are regarded as drivers of economies all over the world. They help to create employment and add to the gross domestic product of a country. But in Nigeria, many of these small business struggle to grow due to the many challenges they face such as inadequate power supply. This study was necessary because many small businesses keep closing in Nigeria because of lack of government support, inadequate marketing by their owners.
This study examined how small businesses in Nigeria can leverage social media to enhance their business and get more customers to buy their products.
A survey was used as a data collection instrument and was distributed to business owners and managers who were believed to be the decision makers in their enterprises. Consent letters were first distributed to the businesses, which in return gave permission to be part of the study. The questionnaire was given to the owners and managers via email and through a hand delivery process.
The findings of this study suggested many ways businesses can get potential customers to notice their brand online such as catchy posts, running online contests, and using hilarious pictures or videos. The findings also demonstrated that there is a link between the frequency of application of social media and effectiveness of the platform when used for promotional purposes. Furthermore, the factors that can cause businesses not to adopt social media were also given.
The findings indicated that businesses which run effective advertisements on social media, incorporating hilarious themes will get the attention of customers, and in return will make more sales and grow their enterprises.
Government agencies that deal with small businesses in Nigeria should also look at this research to find out the challenges faced by these SMEs, to enable them to create better policies that will foster the growth of small enterprises in Nigeria.
Future research should use a mixed method approach to find out more about the factors that can stop an enterprise from adopting new media technologies
E-mentoring as a platform for the development of novice teacher competencies at a rural school in the Western Cape
Get PDFThesis (MEd (Education)--Cape Peninsula University of Technology, 2019The focus of this study was to investigate the potential of an e-platform to mentor novice teachers in a rural school in the Western Cape. The premise of this study was that the Western Cape Education Department had no formal e-mentoring programmes in its basket of CPD programmes that specifically addresses the professional isolation of rural-based novice teachers. The problem was investigated by means of a literature review and empirical investigation, using a mixed method approach. The study had an explicit qualitative slant with a minor quantitative input.
The findings of the study reveal that novice teachers’ initial competencies and skills can be improved through e-platform support. Novice teachers operate in an era of social media immersion and are willing to embrace virtually based support through social media. The study recommends that social media has the potential to build rural based novice teachers’ competencies and skills, as a standalone exercise or part of a blended learning experience. Furthermore, in time, e-mentoring could make a meaningful contribution to the development of rural based teachers, whether novice or experienced
The influence of rotational speed in the Friction Stir Welding of 6082-T6 aluminium alloy joints
Get PDFThesis (MEng (Mechanical Engineering))--Cape Peninsula University of Technology, 2019Friction Stir Welding is regarded as a great welding technique compared to other welding processes. As a welding technique, it has good advantages as well as lesser disadvantages. It is categorised as a solid-joining technique with the aid of applied force and friction. A non-deteriorating rotating tool is plunged between two materials (similar or dissimilar) to be joined at a specific rotational and welding speed. The tool is moved through the material rubbing against them, causing them to soften and fuse before they solidify. This technique is mostly used in the welding of aluminium alloys especially in the automotive, aerospace and marine industries; as it produces high-quality welds with very low porosity, lesser change in material, low distortion and low shrinkage.
This research reports on the influence of rotational speeds on friction stir welded 6082-T6 Aluminium Alloy plates of 6 mm thickness. The different rotational speeds tested were, 600, 700, 800, 900, 1000 and 1200 rotation per minute (rpm). The microstructure and macrostructure were also evaluated under optical microscopes and compared. The 6082 aluminium alloy specimens were tensile tested, using the Hounsfield machine. The fractured tensile specimens underwent fracture analysis taking fractographs using the Scanning Electron Microscope (SEM). The material's hardness was tested using the Rockwell B hardness (HRB). Results show that high rotational speeds with a welding speed of 80 mm/min have a negative effect on the welds at the start and middle of weld but positive effect at the end for tensile properties and grain sizes. Rotational speed of 600 rpm was found to produce welds with higher tensile properties with smaller grain sizes. While 1000 rpm was found to be suitable to get high hardness values
Factors associated with malnutrition amongst children six months to five years of age in a semi-rural area of the Western Cape
Get PDFThesis (MTech (Health and Science))--Cape Peninsula University of Technology, 2019Malnutrition is a global concern and particularly in children. It impacts negatively on mortality, morbidity, educability and productivity, and it affects millions of children in South Africa. As part of our Millennium Development Goals set by the Department of Health and WHO, it is vital to combat malnutrition by eradicating extreme poverty and hunger. Malnutrition is regarded as a change in nutritional status that carries the penalty of illness, dysfunction or death. Child malnutrition poses one of the biggest challenges in South Africa according to the WHO and has been well documented over the past 20 years. A lack of knowledge from parents or caregivers on the nutritional needs of children and the levels of poverty contribute to childhood malnutrition; the extent of hunger has also been associated with low energy intake, low micronutrient intake and poor income levels. This affects growth patterns negatively. Thus, this study aims to examine the key factors that are causing malnutrition in children in a semi-rural community in the Western Cape. A combination of both qualitative and quantitative research approaches were used. Qualitative data were collected through group interviews and quantitative data were collected through a self-administered questionnaire from 105 parents and caregivers. Thematic content analysis was used for qualitative data analysis and SPSS was used to analyse the quantitative data.
The results revealed that the associated factors to malnutrition amongst children six months to five years of age included obesity, underweight, stunting, severe acute malnutrition and moderate acute malnutrition. The results further indicated that the majority of households were single mothers with low income and a poor educational background. This study recommended that health education and health promotion should be done at all heath facilities with regular intervals as well as within the community. Authorities should provide a platform for all clinicians to go for regular updates and to participate in continuous development programmes to combat malnutrition. The findings of this study could contribute to the existing body of knowledge with regard to the factors that contribute to malnutrition. The results could improve health care practices in the communities of the Western Cape and the South African context at large
Online content clustering using variant K-Means Algorithms
Get PDFThesis (MTech)--Cape Peninsula University of Technology, 2019We live at a time when so much information is created. Unfortunately, much of the information is redundant. There is a huge amount of online information in the form of news articles that discuss similar stories. The number of articles is projected to grow. The growth makes it difficult for a person to process all that information in order to update themselves on a subject matter. There is an overwhelming amount of similar information on the internet. There is need for a solution that can organize this similar information into specific themes. The solution is a branch of Artificial intelligence (AI) called machine learning (ML) using clustering algorithms. This refers to clustering groups of information that is similar into containers. When the information is clustered people can be presented with information on their subject of interest, grouped together. The information in a group can be further processed into a summary.
This research focuses on unsupervised learning. Literature has it that K-Means is one of the most widely used unsupervised clustering algorithm. K-Means is easy to learn, easy to implement and is also efficient. However, there is a horde of variations of K-Means. The research seeks to find a variant of K-Means that can be used with an acceptable performance, to cluster duplicate or similar news articles into correct semantic groups.
The research is an experiment. News articles were collected from the internet using gocrawler. gocrawler is a program that takes Universal Resource Locators (URLs) as an argument and collects a story from a website pointed to by the URL. The URLs are read from a repository. The stories come riddled with adverts and images from the web page. This is referred to as a dirty text.
The dirty text is sanitized. Sanitization is basically cleaning the collected news articles. This includes removing adverts and images from the web page. The clean text is stored in a repository, it is the input for the algorithm. The other input is the K value. All K-Means based variants take K value that defines the number of clusters to be produced.
The stories are manually classified and labelled. The labelling is done to check the accuracy of machine clustering. Each story is labelled with a class to which it belongs. The data collection process itself was not unsupervised but the algorithms used to cluster are totally unsupervised. A total of 45 stories were collected and 9 manual clusters were identified. Under each manual cluster there are sub clusters of stories talking about one specific event.
The performance of all the variants is compared to see the one with the best clustering results. Performance was checked by comparing the manual classification and the clustering results from the algorithm.
Each K-Means variant is run on the same set of settings and same data set, that is 45 stories. The settings used are, • Dimensionality of the feature vectors,
• Window size,
• Maximum distance between the current and predicted word in a sentence,
• Minimum word frequency,
• Specified range of words to ignore,
• Number of threads to train the model.
• The training algorithm either distributed memory (PV-DM) or distributed bag of words (PV-DBOW),
• The initial learning rate. The learning rate decreases to minimum alpha as training progresses,
• Number of iterations per cycle, • Final learning rate,
• Number of clusters to form,
• The number of times the algorithm will be run,
• The method used for initialization.
The results obtained show that K-Means can perform better than K-Modes. The results are tabulated and presented in graphs in chapter six.
Clustering can be improved by incorporating Named Entity (NER) recognition into the K-Means algorithms. Results can also be improved by implementing multi-stage clustering technique. Where initial clustering is done then you take the cluster group and further cluster it to achieve finer clustering results
Automated weigh-in-motion through vehicular telematics and machine learning
Get PDFThesis (DPhil (Informatics))--Cape Peninsula University of Technology, 2019Road safety is one of the major concerns in today’s world. Driving an overloaded vehicle causes various ill-effects to road safety. Various kinds of Weigh-in-motion (WIM) systems are used to control and reduce the impacts of overloaded driving. Existing WIM systems are either expensive or slower and influenced by various factors. Advancement in network connectivity and sensor devices led to the development of the Internet of Vehicles (IoV), a subfield of the growing Internet of Things (IoT). IoV is powered by Vehicular Telematics (VT), also known as flying car data. VT data is used by the transport industries for many reasons such as fleet management, insurance (pay as you drive), driving behaviour detection, and road anomaly detection. Intelligent Transportation System (ITS) uses both IoV and Machine Learning (ML) techniques to build an automated Artificially Intelligent (AI) transportation system.
According to the Newtonians’ physics and literature, under certain conditions, the driving force needed by a vehicle to obtain a particular acceleration is influenced by the total weight of the vehicle. That implies that if driving force and other influencing parameters are known, we could infer the weight of a vehicle. VT data can be used to obtain many features, including the driving force. This dissertation discusses the effort taken to validate the idea of inferring the weight of a vehicle using VT and ML. This research involved designing and testing the prototype artefact. The Design Science Research (DSR) methodology was used in this research. The C-K design theory was used in this DSR. The application of C-K theory in DSR has shown the different dimension for approaching applied research. A pragmatist approach was used in the design and development of this research.
According to the C-K design theory, with all the knowledge, K0, from literature and the laws of physics, we formed an initial concept C0: “A new WIM solution using VT and ML”, with the propositions p1: “faster”, p2: “economical/cheaper”, p3: “Ubiquitous”. The concept was tested by designing and developing the prototype (artefact). A backend to process VT data using ML was developed as a by-product of this research. We have tested several ML algorithms during the development stage, and an Artificial neural network (ANN) architecture of three hidden layers with 30 nodes in each layer has shown astounding performance with Accuracy = 0.945, R-Squared = 0.97, Adjusted R-Squared = 0.97, Mean Squared Error = 34.68, Residual Standard Error = 6.03. The ANN outperformed all other tested ML algorithms on the collected VT dataset. We can infer the weight using the smaller dataset obtained from the context of a small car. Results from small cars show the supports for the concept theory
The impact of people-focused leadership style on employee performance in project-based industries in the Cape Metropole
No full textThesis (MTech (Business Administration in Project Management))--Cape Peninsula University of Technology, 2018.Leadership is arguably the most studied discipline and yet is equally the least understood subject since it involves unpredictable human beings. In the same vein, as managers and leaders operate, they operate within the context of followers who have their own expectations from leadership. Consequently, many leadership theories have been developed and at best they are largely a variety of the other with extremities in other aspects. Because there are other people apart from the leader, it means consideration should be made of the characteristics of the followership. There is therefore a need for congruency between the leadership and the followership if the leader is to be influential. Interpersonal skills are critical for this type of leadership, and some research findings indicated that extroverts who are people centered are likely to be more effective. In the process, the leader needs to build relationships as evidenced by the way the leader will encourage, appreciate, forgive, understand others, and be prepared to listen to peers and followers. This papers posits that people oriented leaders develop closeness to the followers and are empathetic, whilst they try to get their work done. The preliminary findings established that a people focused leader will have more influence on the followership, and is most likely to be empathetic to his subordinates
FTO supported Co3O4 thin film biosensor for detection of fructose
No full textThesis (Master of Engineering in Chemical Engineering)--Cape Peninsula University of Technology, 2018.Electrochemical and non-enzymatic fructose detection has evoked keen interest in the scientific literature. Several authors have reported on different methods of electrode preparation for fructose sensors. However, little systematic study has been conducted to design a cheap, efficient method of depositing metal oxides to detect fructose. To address the challenge, a Co3O4 thin film was fabricated using a simple solution step deposition on Fluorine doped Tin oxide (FTO) glass electrode.
In this study, a report on the selective oxidation of fructose on Co3O4 thin film electrode surface is presented. Electrode characterization was done using X-ray diffraction (XRD), High Resolution Transmission Electron Microscopy (HR-TEM), Scanning Electron Microscope (SEM), Atomic Fluorescence Microscopy (AFM), and Electrochemical Impedance Spectroscopy (EIS). All cyclic voltammetry (CVs) and chronoamperometry tests were carried out by the use of an AUTOLAB POTENTIOSTAT 302 N, controlled by Nova 2.0 software instrumentation using a customized 50 cm3 electrochemical cell. The cell consisted of a graphite rod as the counter electrode (CE), 3 M Ag/AgCl reference electrode (RE) and the fabricated Co3O4/FTO as the working electrode (WE). All experiments were carried out at 25±2 ⁰C.
From the results, the constructed sensor exhibited two distinctive linear ranges in the ranges of 0.021 – 1.74 mM and from 1.74 - ~15 mM, covering a wide linear range of up to ~15 mM at an applied potential of +0.6V vs. Ag/AgCl in 0.1M NaOH solution. The sensor demonstrated a high, reproducible and repeatable sensitivity of 495 (lower concentration range) & 53 (higher concentration range) μA cm-2 mM-1 for a low R.S.D of 5 %. The Co3O4 thin film produced a low detection limit of ~1.7 μM for a signal to noise ratio of 3 (S/N = 3); a fast response time of 6s and long term stability. The repeatability and stability of the electrode resulted from the chemical stability of Co3O4 thin film. The study showed that the sensor was highly selective towards fructose compared to the presence of other key interferences i.e. AA, AC, and UA. Because of such a favourable electrocatalysis of the Co3O4 sensor towards fructose, the ease of the electrode fabrication and reproducibility makes it a future candidate for commercial applications in the food and beverages sector