Showing items 1 - 20 of 55

Your selections:

Traditional decision making versus artificial intelligence aided decision making in management of firms : A narrative overview

- Denhere, Varaidzo

  • Authors: Denhere, Varaidzo
  • Date: 2021
  • Subjects: Artificial intelligence , Fourth industrial revolution , Management practices
  • Language: English
  • Type: Journal article
  • Identifier: http://hdl.handle.net/10210/493647 , uj:45007 , Citation: Denhere, V. 2021. Traditional decision making versus artificial intelligence aided decision making in management of firms : A narrative overview.
  • Description: Abstract: There has been a lot of talk about possible ways that Artificial Intelligence (AI) will disrupt the workforce by automating some jobs. In the same vein, literature has also indicated that a lot of studies have been conducted on artificial intelligence systems from different perspectives. However, there are still some research opportunities that could be pursued to further knowledge in the area as artificial intelligence continues to evolve with technological advances. Consequently, this conceptual paper aimed at advancing understanding of artificial intelligence aided decision making versus traditional decision making in the management of firms in the era of Big Data. A general overview of the concept of management practices involving decision making was done, followed by traditional decision making styles. Then, this was followed by an overview of artificial intelligence aided decision making processes. The differences between these two decision making processes were highlighted in the discussion. Methodology: Using a desk-review, this study analysed existing data from secondary sources including peer-reviewed journal articles, textbooks and online blogs. In this paper, the role of the literature review was to unravel the components of the decision making process by management in firms. Results: Findings indicated that despite artificial intelligence aided decision making having many merits, some managers did not trust it due to some of its demerits and challenges that go with its adoption. As a result, they were reluctant to employ it. Conclusion/- and Recommendations: The paper recommends further research on how AI could be used in other management practices which are outside decision making.
  • Full Text:

The plug-in plantation : a proposal for a resilient infrastructural system achieved via the participation-driven robotic reforestation of residual space along Johannesburg's Main Reef Road

- Jonker, Pieter Jacobus

The integration of AI on workforce performance for a South African banking institution

- Mamela, Tebogo Lucky, Sukdeo, Nita, Mukwakungu, Sambil Charles

  • Authors: Mamela, Tebogo Lucky , Sukdeo, Nita , Mukwakungu, Sambil Charles
  • Date: 2020
  • Subjects: Artificial intelligence , Robotics , Banks
  • Language: English
  • Type: Conference proceedings
  • Identifier: http://hdl.handle.net/10210/450798 , uj:39641 , Citation: Mamela, T.L., Sukdeo, N. & Mukwakungu, S.C. 2020. The integration of AI on workforce performance for a South African banking institution.
  • Description: Abstract: Artificial Intelligence (AI) advanced technologies are growing and changing many industries. This paper will assess the relationship in which artificial intelligence impacts the performance of the workforce in a South African bank. The research explores the aspects that contribute to which a worker has improved productivity and performance through the adoption and use of artificial intelligence. The research considers the aspects of artificial intelligence toolset and their influence on the workforce performance. In addition, the paper assesses these aspect as to how they contribute towards the productivity with considerations to the integration of analytical and organized strategies that advance the workforces performance. The purpose is to improve the workforce’s quality performance in the banking institution of South Africa. The research has applied the descriptive statistics with the use of frequency distribution tables and graphical representations to analyze and present the information on the variables. The outcomes are evaluated with regards to the descriptive statistics and inferential statistics based on the variables which show that artificial intelligence has a relatively strong impact on workforce performance. Therefore, it is essential and recommended for banks to integrate them. The next frontier for shared services may be far more exciting, incorporating greater computing power and artificial intelligence into robotics, so that the lines between human judgment and automation become blurred.
  • Full Text:

The implications of the fourth industrial revolution on diplomacy

- Williams, Robyn Ehryn

  • Authors: Williams, Robyn Ehryn
  • Subjects: Artificial intelligence , Industry 4.0 , Industrial revolution
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/477811 , uj:43185
  • Description: Abstract: Diplomacy has succeeded historical events and industrial revolutions. However, the impacts of the fourth industrial revolution (4IR) threaten to be more wide-spanning and destructive than any other industrial revolution. The study explores the implications of 4IR on the theory and practice of diplomacy. The study is guided by three research questions: how does 4IR impact diplomacy; what technologies trigger a change in diplomacy; and do costs act as a barrier to states? Making use of qualitative methods, through the exploration of primary and secondary data, the study explores 4IR’s implications on diplomacy. The implications are categorized into five pillars which are considered integral aspects of diplomatic theory and practice. The pillars are communication, interdependence, domestic and international frameworks, new ‘new’ diplomacy and diplomatic functions. The study concludes that diplomacy may be impacted by 4IR in all five pillars of diplomacy. 4IR may not diminish the practice of diplomacy but rather complement it. A highly digitized diplomacy with cyber tools may result in a more efficient and effective type of diplomacy. Technologies such as artificial intelligence, big data and information and communication technologies are the key drivers of change in diplomacy... , M.A. (Politics and International Relations)
  • Full Text:

The Fourth Industrial Revolution and the achievement of equality for woman in work

- Khoabane, Kagiso

  • Authors: Khoabane, Kagiso
  • Date: 2019
  • Subjects: South Africa. Employment Equity Act, 1998 , Discrimination in employment - Law and legislation - South Africa , Affirmative action programs - Law and legislation - South Africa , Labor laws and legislation - South Africa , Technological innovations - Social aspects - South Africa , Artificial intelligence
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/413480 , uj:34835
  • Description: Abstract: The fourth industrial revolution has ushered in a technological era which promises a broader and quicker transfer of data and information captured in modern day systems than the third industrial age. This era promises great opportunity throughout numerous spheres of life with its greatest shortcoming being imparting the necessary skills and education on workers so as to survive in this era. The focus of this investigation is centred on the inequalities that women continue to face in the world of employment and the policies such as affirmative action and treaties that have been implemented to nullify these prejudices. Throughout history, women have succumbed to unequal working conditions as a result of unequal pay when compared to their male counterparts which further includes gender based acts such as harassment. To this end, women still face less favourable working conditions to that of men. The purpose of this study is to explore and understand the influence of the fourth industrial revolution on the future of the inequalities women face in work while analysing and deconstructing the implications of the Employment Equality Act alongside treaties as tools to reduce gender inequality in employment. The importance of higher education and skills development as solutions to alleviate the inequities women face in working conditions were investigated. A fundamental study further evaluated how legal reasoning interacts with social hierarchies based on gender and gender based implications. In doing so, the writer was able to assess the gender gaps experienced between men and women in employment. A law reform approach through work policy introductions were suggested in attempt to find solutions to aid women in work. Fundamental research was utilised in analysing the introduction of the fourth industrial revolution and the social impact it would have not only on women nationally but in African communities as well. The research study revealed that despite policies like the Employment Equity Act and the SADC Protocol on Gender and Development being implemented to aid in achieving equality for women in work, closing the gender based gap would prove challenging. The reason hereto is because men still dominate industries like Science, Technology, Engineering and Mathematics (or STEM fields) which are important for growth in an evolving society thus hampering the sustainable development of women. A country like South Africa, and most 4 | P a g e likely the rest of the African continent, will struggle to adapt to the advances imposed by the fourth industrial revolution due to a lack of resources and tools such as reliable infrastructure and electrical driven technologies to accommodate the new industrial age. Despite the suggestion of improving skills development and higher education in our society, unemployment and patriarchy still serve as obstacles toward achieving equal rights in employment for our women. In short, for newly suggested policies to work in light of the fourth industrial revolution, a legal and social reform will have to be adopted in society as a whole. , LL.M. (Commercial Law)
  • Full Text:

The extraction of quantitative mineralogical parameters from X-ray micro-tomography data using image processing techniques in three dimensions

- Shipman, William John

  • Authors: Shipman, William John
  • Date: 2017
  • Subjects: Computer algorithms , Computer graphics , Machine learning , Artificial intelligence
  • Language: English
  • Type: Doctoral (Thesis)
  • Identifier: http://hdl.handle.net/10210/263159 , uj:27815
  • Description: D.Ing. (Electrical Engineering) , Abstract: Process Mineralogy is the application of mineralogical techniques to the exploration of ore deposits and the design and optimisation of mineral processing flowsheets. Samples can be drill cores, rocks and milled particles, to give a few examples. X-ray microtomography has emerged as a complementary technique to the existing two-dimensional imaging modalities and bulk mineralogical methods. The applications of analysing X-ray micro-tomography scans include analysing packed particle beds to determine particlesize distributions, mineral exposure and liberation, as well as analysing the pore network within ores targeted by the oil and gas industry. X-ray micro-tomography suffers from several artefacts, including beam hardening, blurring and streaks, of which beam hardening and streaks are particularly problematic and common when scanning metal-bearing ores. A fundamental step in analysing a tomogram is to segment the different groups of minerals that are present within the sample. This is necessary to measure mineral grain properties and as a precursor to segmenting and analysing particles in a crushed or milled sample. In order for X-ray micro-tomography to provide accurate measurements, this first step of segmenting minerals must be performed accurately. Machine learning has been used in image processing for a variety of applications, including the analysis of optical microscopy images for medical purposes, and recently the analysis of tomograms. The primary focus of this work is the application of machine learning algorithms to the segmentation of minerals, as well as a means for measuring the accuracy of those algorithms. Four main problem areas were identified in this work. The first is the need for a suitable algorithm for filtering tomograms to reduce the quantity of noise that is present while minimising the additional blurring of the edges of mineral grains. The second problem statement focuses specifically on machine learning, while the third problem statement is directed at the description of voxels by means of several features. The fourth problem area is measuring the accuracy of any measurements made on the segmented tomograms. Without an analysis of the measurement accuracy, X-ray micro-tomography will not be accepted by the industry at large. This work demonstrates a method by which back-scattered electron images from a scanning electron microscope may be aligned to a tomogram, and used to quantify the accuracy of mineral segmentation algorithms...
  • Full Text:

The commercialisation lifecycle of a knowledge management consulting firm in the fourth industrial revolution

- De Koker, Lucian Theodoric

  • Authors: De Koker, Lucian Theodoric
  • Date: 2018
  • Subjects: Knowledge management , Industrial revolution , Artificial intelligence , Internet of things
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/415004 , uj:35021
  • Description: Abstract: Current situation in business, economies and the world indicate that artificial intelligence (AI), the Internet of Things (IoT) and robotics are some of the technologies that is and will continue to have a tremendous impact on businesses, economies and everyday human life. These technologies amongst others are reshaping the global landscape and business ecosystems and the manner in which business is conducted in the fourth industrial revolution (4IR). Generic commercialisation lifecycles and business models require adaptation in the 4IR, which will aid successful business for a knowledge management (KM) consulting firm. The study focussed on conceptualising and developing a commercialisation lifecycle (CLC) for a KM consulting firm in the 4IR. The research objective was to conceptualise a business model canvas (BMC) and develop an IKM framework that can be used specifically by a KM consulting firm, including entrepreneurs, small businesses and professional business consulting firms in the 4IR. Literature shows that commercialisation lifecycles and business models need to change continuously, especially on the front of the 4IR. To remain competitive and sustain a healthy business, KM consulting firms will need to upskill and improve current business operations. Upskilling, changing and preparing for the 4IR, give competitive advantage over competitors. New technologies need to be embraced and harnessed to exploit the innovative capabilities and value add new technologies offer. With an improved, adapted and updated CLC and BMC in place, a KM consulting firm will be able to provide innovative services to clients, ensuring profitability. The research methodology for the study was qualitative in nature, with an inductive and exploratory approach. Grounded in the interpretivist paradigm, the inductive approach allowed the study to explore a specific phenomenon and identify themes in order to explain patterns. A conceptual framework was developed, using existing literature, to conceptualise a CLC for a KM consulting firm in the 4IR. Data was collected through content analysis and in-depth faceto- face interviews, through multi-method qualitative research. Purposive sampling was selected to determine the 4 participants for the interviews, through critical case sampling, allowing 3 participants to be interviewed and the fourth participant to be used for testing the findings of the interviews. Interviews and testing of the interviews were transcribed, coded, and categorised through the Data Analysis Spiral. Research findings, through triangulation found that the conceptualisation and development of a CLC is crucial; that the conceptualisation of a BMC is crucial; and that new services and the development of an IKM framework is crucial; which will allow a KM consulting firm, including entrepreneurs, small businesses and professional business consulting firms to be successful in the 4IR. Results showed that the CLC, the BMC, new services and the IKM framework, need... , M.Phil. (Information Management)
  • Full Text:

The application of machine learning technologies in project risk management

- Mhlari, Ericson Vusimuzi Zamulele

  • Authors: Mhlari, Ericson Vusimuzi Zamulele
  • Date: 2020
  • Subjects: Project management - Data processing , Artificial intelligence , Risk management
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/479315 , uj:43348
  • Description: Abstract: Risk management is a crucial process to any organisation. Risks are prevalent where uncertainty is present; i.e. the dynamic nature of a project environment exposes projects to ongoing risks. Although regulated by industry-wide standards and internal organisational guidelines, inefficiencies in monitoring of project risks have an adverse effect on the management of risks. Industry 4.0 is transforming the way in which organisations execute projects and artificial intelligence is one of the leading industry 4.0 technologies which is rapidly accelerating organisational performance. Artificial intelligence (AI) technologies are the driving force behind organisational advancement in the upcoming digital economy. As such, this research aims to establish the pertinent risk monitoring challenges facing project risk management practitioners and to investigate whether the use of AI technologies can address these challenges... , M.Ing. (Engineering Management)
  • Full Text:

The application of artificial intelligence within information security.

- De Ru, Willem Gerhardus

  • Authors: De Ru, Willem Gerhardus
  • Date: 2012-08-17
  • Subjects: Artificial intelligence , Computer security , Fuzzy logic , Information resources management , Electronic data processing departments - Security measures
  • Type: Thesis
  • Identifier: uj:2641 , http://hdl.handle.net/10210/6087
  • Description: D.Phil. , Computer-based information systems will probably always have to contend with security issues. Much research have already gone into the field of information security. These research results have yielded some very sophisticated and effective security mechanisms and procedures. However, due to the ever increasing sophistication of criminals, combined with the ever changing and evolving information technology environment, some limitations still exist within the field of information security. Recent years have seen the proliferation of products embracing so-called artificial intelligence technologies. These products are in fields as diverse as engineering, business and medicine. The successes achieved in these fields pose the question whether artificial intelligence has a role to play within the field of information security. This thesis discusses limitations within information security and proposes ways in which artificial intelligence can be effectively applied to address these limitations. Specifically, the fields of authentication and risk analysis are identified as research fields where artificial intelligence has much to offer. These fields are explored in the context of their limitations and ways in which artificial intelligence can be applied to address these limitations. This thesis identifies two mainstream approaches in the attainment of artificial intelligence. These mainstream approaches are referred to as the "traditional" approach and the "non-traditional" approach. The traditional approach is based on symbolic processing, as opposed to the non-traditional approach, which is based on an abstraction of human reasoning. A representative technology from each of these mainstream approaches is selected to research their applicability within information security. Actual working prototypes of artificial intelligence techniques were developed to substantiate the results obtained in this research.
  • Full Text:

The ambit of copyright protection for works generated by artificial intelligence

- Maher, Mikayla

  • Authors: Maher, Mikayla
  • Date: 2020
  • Subjects: Copyright , Technology - Law and legislation , Copyright infringement , Artificial intelligence
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/475476 , uj:42893
  • Description: Abstract: There has been a rise in technological advancements, specifically the implementation of Artifical intelligence (AI) across a multitiude of industries. One of the advantages of AI and its advanced capabilities is to incorporate this in and/or have this assume control over some or all of the processes in the generation of works. This minor dissertation seeks to discuss the issue of works generated by Artificial Intelligence (AI) that would in the normal course qualify for copyright protection. The preliminary issue arising from AI in the spectrum of copyright is whether such works so generated, are in fact awarded copyright protection and if so, who or what is awarded ownership of the work. Copyright protection and ownership is put into question specifically due to the fact that the generation of the work may be viewed as too far removed from the human author... , LL.M. (Intellectual Property Law)
  • Full Text:

South African inflation forecasting using genetically optimised neural networks

- Molwantoa, Lebogang

  • Authors: Molwantoa, Lebogang
  • Date: 2014-03-03
  • Subjects: Neural networks (Computer science) , Artificial intelligence , Inflation (Finance) - Forecasting , Genetic algorithms , Inflation (Finance) - South Africa
  • Type: Thesis
  • Identifier: uj:4219 , http://hdl.handle.net/10210/9577
  • Description: M.Com. (Financial Economics) , Forecasting inflation is an important concern for economists and business alike throughout the world. Despite the relative success of macroeconomic forecasting models in forecasting inflation, there is potential to improve these models to account for nonlinear relationships between inflation and the chosen independent variables. Artificial neural networks (ANNs) have found increased applicability as a potential nonlinear forecasting tool that accounts for nonlinearity found in data. In this study, we investigate the ability of genetically optimised neural networks to forecast South African inflation. The results were compared to economic forecasts obtained from traditional econometric models as well as macroeconomic structural models. The results obtained show that the genetically optimised neural networks indicate some ability to be used as potential forecasting tools. Their biggest advantage over the traditional forecasting techniques is that they do not impose the restriction of linearity on the data to be forecasted.
  • Full Text:

SAIIB : symbiotic, affective, and immunologically influenced behaviours in computer games

- Sampath, Sanish

  • Authors: Sampath, Sanish
  • Date: 2021
  • Subjects: Computer games - Design , Computer games - Programming , Intelligent agents (Computer software) , Artificial intelligence
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/484328 , uj:43987
  • Description: Abstract: The dissertation provides a view over what symbiotic agents, immunological computation and affective computing are, and how each are used in computer games. The dissertation focuses of the design and implementation of a symbiotic agent that uses immunological computation and affective computing to influence the decisions taken by a non-player character (NPC) in a computer game. The dissertation discusses what intelligent agents are, and their use with artificial intelligence (AI) techniques in computer games. The roles that NPCs have are discussed in the dissertation focusing how the role of the NPC creates the sense of immersion the player has in a computer game. The next section of the dissertation after the research, was the design of the symbiotic affective immunological influenced behaviour (SAIIB) model. The SAIIB model is designed as a symbiotic agent and consists of symbiont agents that are designed using immunological computation and affective computing. The objective of the SAIIB model is to use affective computing and immunological computation to influence the learning and decision-making components to cause the SAIIB model NPC to make rational or irrational decisions to an action of the player... , M.Sc. (Information Technology)
  • Full Text:

Role of artificial intelligence in operations environment : a review and bibliometric analysis

- Bag, S., Dhamija, P.

  • Authors: Bag, S. , Dhamija, P.
  • Date: 2020
  • Subjects: Artificial intelligence , Operations management , Network analysis
  • Language: English
  • Type: Article
  • Identifier: http://hdl.handle.net/10210/436427 , uj:37860 , Citation: Bag, S. & Dhamija, P. 2020. Role of artificial intelligence in operations environment: a review and bibliometric analysis.
  • Description: Abstract: Purpose - ‘Technological Intelligence’ is the capacity to appreciate and adapt technological advancements, and ‘Artificial Intelligence’ is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave, and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its societal and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have we reached with respect to artificial intelligence research. Present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals, and citation statistics...
  • Full Text:

Reusable component oriented agents: a new architecture

- Boshoff, Willem Hendrik

  • Authors: Boshoff, Willem Hendrik
  • Date: 2008-05-13T08:40:46Z
  • Subjects: Artificial intelligence , Intelligent agents (Computer software) , Plug-ins (Computer programs)
  • Type: Thesis
  • Identifier: uj:7094 , http://hdl.handle.net/10210/368
  • Description: Researchers in artificial intelligence and agent technologies are presented with a massive array of various technologies that they might use for their research projects. It is difficult for researchers to test their theories effectively in the field. It takes a great deal of time to develop the platform on which the newly created agent will be tested, with little or no time left for troubleshooting and the investigation of further solutions. Every time a new technique or agent is researched, the agent has to be redeveloped from the ground up. This makes it difficult for researchers to compare their own theories with previously developed components. With the wide range of technologies and techniques available, there is no easy way to effectively make use of the various components, as each tool uses different technologies that cannot be combined easily. This dissertation outlines the new plug-in oriented agent architecture (POAA) and describes the agents that use the POAA. POAA agents make extensive use of functional and controller-based plug-ins in order to extend the functionality and behaviour of the agent. The architecture was designed to facilitate machine learning and agent mobility techniques. POAA agents are created by mounting newly created dynamic plug-in components into the static structure of the agent. The static structure of the agent serves as the basis of agent functionality and as the controller for the agent’s life cycle. The static and dynamic components of the POAA agent interact with each other in order to perform the agent’s required tasks. The use of plug-ins will greatly improve the effectiveness of researchers, as only a single, standard architecture will exist. Researchers only need design and develop the plug-in required for their specific agent to function as desired. This will also facilitate the comparison of various tools and methods, as only the components being reviewed need to be interchanged to measure system performance. The use of different plug-in architectures is also investigated. This includes deciding if the plug-in base will be configured at application run-time or at the time of application compilation. This dissertation focuses on techniques that will facilitate machine learning and agent mobility. For these purposes, extensive use is made of the machine learning tool WEKA developed by University of Waikato in New Zealand [Wi00]. The use of Java in the prototype will also facilitate the cross platform capability of the proposed agents. , Prof. E.M. Ehlers
  • Full Text:

Photovoltaic system maximum power point tracking under partial shaded weather conditions using machine learning algorithms

- Nkambule, Mpho Sam

  • Authors: Nkambule, Mpho Sam
  • Date: 2019
  • Subjects: Photovoltaic cells , Photovoltaic power systems , Artificial intelligence , Machine learning
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/418317 , uj:35462
  • Description: Abstract: The rapid growth of demand of electrical energy and depletion of fossil opened door for renewable energy. The expeditious broadening of Photovoltaic (PV) energy has attracted the private and government precinct world-wide, due to the reduction of costs and being cleaner source of energy. However, most of the maximum power point tracking (MPPT) controllers are inefficient under rapidly changing environmental conditions. In addition, under partial shading conditions (PSC) MPPT controllers fail to track global maximum power point (GMPP). Therefore, it is essential to propose an MPPT controller that will be able to locate GMPP using historical weather data. The work is undertaken to investigate the feasibility of using machine learning (ML) based MPPT techniques to harness maximum power on a PV system under PSC. If successful, the ML based MPPT algorithms could lead to a reduction in power losses in a PV system. In this dissertation, certain contributions to the field of PV systems and ML based were made by introducing two online and eleven artificial intelligence (AI) MPPT techniques, by presenting four experiments under different weather conditions. The first contribution is concerned with an MPPT system that harvests maximum power under PSC, using Johannesburg real-time weather data. The system consists of an MPPT controller cascaded with a PID controller, to reduce errors of the MPPT algorithms, to improve the system’s performance. First, the system evaluates and compares the online [Perturb & Observe (P&O) and Incremental Conductance (INC)], to determine the most powerful MPPT algorithm. Secondly, the system validates the performance of the eleven AI MPPT methods [Fuzzy Logic Control (FLC) and Recurrent Neural Network (RNN), Support Vector Machines (SVM), the Weighted K-nearest neighbour (WK-NN), a Gaussian process regression (GPR), Decision Tree (DT), Multivariate linear regression (MLR), Linear discriminant analysis (LDA), Naïve Bayes classifier (NBC), Bagged Tree (BT) and Boosted Tree (BoT)] under PSC. The ML based techniques are evaluated using four types of error [root mean squared error (RMSE), mean absolute error (MAE), Mean squared error (MSE) and R-squared (𝑅2)]. For the first experiment, online methods are empirically compared in the form of four case studies conducted under various weather conditions. The results showed that INC performed significantly better than P&O under PSC. INC overperformed P&O in all case studies in terms of power extraction. Nevertheless, P&O has less settling time around maximum power point... , M.Phil. (Electrical and Electronic Engineering)
  • Full Text:

Performance prediction of trace metals and cod in wastewater treatment using artificial neural network.

- Matheri, Anthony Njuguna, Ntuli, Freeman, Ngila, Jane Catherine, Seodigeng, Tumisang, Zvinowanda, Caliphs

Paradigm shift in higher education in the context of the Fourth Industrial Revolution

- Du Preez, J., Sihna, S.

LinkedIn: A link to the knowledge economy

- Dinath, Wafeequa

Leadership capabilities and opportunity realisation in the Fourth Industrial Revolution

- Venter, Johannes

  • Authors: Venter, Johannes
  • Date: 2019
  • Subjects: Leadership , Technological innovations - Management , Industrial revolution , Artificial intelligence , Coal mines and mining - South Africa
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/446406 , uj:39090
  • Description: M.Com. (Business Management) , Abstract: The study explored the leadership capabilities required to realise opportunities brought by the fourth industrial revolution in the South African coal mining sector. A qualitative research paradigm methodology was used. During the literature review references by other researchers were used to form a basic understanding of the origins of 4IR as well as how 4IR is used to modernise the mining sector, considering the current mining industry economic condition. The governments involvement as well as other industries like manufacturing in Industry 4.0 were also explored. Leadership evolution, risks and challenges through the industrial revolutions were furthermore researched and broaden the study’s knowledge base. A total of ten leadership professionals in the coal mining industry that has expert knowledge and experience with 4IR was interviewed and provided valuable input to the study. The research data transcripts were analysed for themes and subthemes that emerged repeatedly...
  • Full Text:

Knowledge-based automation and new workforce implementation at a financial institution

- Elsworth, Catherine

  • Authors: Elsworth, Catherine
  • Date: 2018
  • Subjects: Industrial revolution , Artificial intelligence , Banks and banking - Technological innovations , Banks and banking - Customer services , Knowledge management , Banks and banking - Information technology
  • Language: English
  • Type: Masters (Thesis)
  • Identifier: http://hdl.handle.net/10210/402839 , uj:33730
  • Description: Abstract : Intelligent Automation (IA) entails advanced knowledge-based technologies associated with the so-called Fourth Industrial Revolution (4IR). In this study, the phrase “IA journey” refers to the processes of knowledge-based automation and new workforce implementation. The study’s unit of analysis is not as much the IA journey itself, rather it is an analysis of what constitutes a balanced approach to IA implementation and adoption within an organisation. For example, employees’ feelings of uncertainty during an organisation’s IA journey could cause an imbalance in staff morale and resistance from employees to adapt to the changes. Therefore, the main research question of this study is: What are the components of a balanced approach to knowledge-based automation and new workforce implementation of a financial institution? The research question aligns to the world of service delivery that is changing at an alarming rate, with customers expecting fast, personalised, digital service. The landscape for financial institutions is changing, for example, traditional competitors are taking steps to meet customer demands and non-traditional competitors are entering the market place, threatening the existence of traditional financial institutions, commonly referred to as banks. The literature reveals that the evolution of Internet usage and the influence of social media and smart phones have increased the significance of technology and digital service in the financial services industry. Adoptions of these technologies is vital if traditional banks want to remain relevant in the market where financial technologies companies (Fintechs), and small, digitally nimble start-ups can provide the quick, personalised service that customers expect. Already many financial institutions have started to investigate the opportunities that technologies such as IA and chatbots provide. The potential of chatbot technology to improve customer experience and reduce operational costs make it an attractive option for organisations to consider. Literature reveals that the cost of implementation of this technology is a fraction of the cost of legacy system re-writes. The ability of this technology to integrate with existing systems and improve turnaround time and service to customers makes the IA journey a favourable choice. The IA journey of one South African Financial Institution (SAFI) formed the focus of this study. Research was conducted within the SAFI into the application of this technology across the organisation to understand the impact that the changes experienced had on the employees of the organisation. Understanding how these changes impact employees helps in determining the best ways to manage the changes in order to develop a balanced approach to implementation and adaption of IA within an organisation. The empirical study followed a qualitative research design, featuring qualitative data collection and analysis techniques. Secondary data were collected and displayed in order to show case v hoe IA project were implemented into the organisation. The philosophical paradigm that suited a study of this nature was interpretivism as the research was socially constructed in its aim to understand the adoption processes of the organisation implementing an IA programme. The research followed an inductive approach as the study’s conceptual framework was developed based on data collected and conclusions drawn through the analysis of this data. The study involved the collection of data through the use of interviews conducted across junior and senior management levels within the business units impacted by the changes associated with the IA journey. The aim of these interviews was to gain an understanding of employees’ perceptions of the IA journey across the organisation as well as understand the experiences of those involved in the IA programme. Secondary data was also collected from five SAFI use cases, which provided a rich source for quantitative data. The presentation of results regarding the outcomes of use cases implemented across the organisation is in accordance to the University of Johannesburg Code of Academic and Research Ethics. The research findings informed the development of a conceptual framework, which can be used to encourage a balanced approach towards IA implementation and adoption throughout an organisation that is experiencing major changes. This study reveals that employees’ fears of the changes need to be identified and managed early in order to avoid resistance to the changes and negative perceptions of the technology being created. The conceptual framework identifies the components that a financial institution can use in its balanced approach to increase adoption and reduce fears. Moreover, the study revealed the need for organisations to invest in technologies of the future and the benefits that this technology can have for the organisation. Customer experience and expectations form a vital part of any organisation and the lessons learnt in the value this technology can provide in creating a great customer experience are invaluable. The study revealed that there is a difference between digitisation and automation and that knowledge-based automation technology plays a key role in enabling a digital customer experience... , M.Phil. (Information Management)
  • Full Text:
  • Disclaimer
  • Privacy
  • Copyright
  • Contact