Computer Science

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A Survey of the University Students’ Perspectives about Using Digital Technologies in Education: Zimbabwean Case
(2017) Dube, S; Scott, E
This study investigated the perspectives of university students on the use of digital technologies as tools for teaching and learning. Digital technologies are an essential asset for academic institutions as they can support strategic teaching and learning objectives for education institutions. Studies have shown that limited use of digital technologies could lead to a second order digital divide. This problem negatively impacts the Government and university efforts and initiatives of increased technological investment. There is therefore a need to uncover and obtain a deeper insight into university students’ perspectives due to the sparse literature discussing this problem within the Zimbabwean context. Quantitative data on student perspectives was collected using 100 questionnaires administered to students at a single university of technology in Zimbabwe. Although the findings concur with existing literature that students highly value the integration of technology into their learning process, there were issues that appeared to be peculiar to the surveyed environment. For example, the surveyed students professed disappointment with the current traditional teaching methods despite the high availability and accessibility to digital technologies within the institution. They indicated their frustration emanating from the disconnection between commonly used teaching methods and the digital technologies effective for teaching and learning
An ontology-based framework for mobile learning in rural secondary schools
(2015) Ngwenya, S; Mangena, S.B.; Trimble, J.; Hlatywayo, D.; Chilumani, K.R.
In some countries mobile learning is becoming an important issue in academic institutions, as teachers and students get connected to networks through smart phones that combine telephony, computing, messaging and multimedia. However, in rural areas the process of designing, communicating and presenting learning resources, content services and learning content for mobile learners poses challenges. Teachers and students are not able to connect to networks for the purposes of learning and teaching. Therefore an enabler framework for this purpose becomes necessary. Those who connect to the Internet are not able to get precise and relevant content that meets their requirements and needs. This is due to poor internet connectivity, lack of semantics on content, inaccurate searches and information overload. This paper proposes a solution to some of the challenges by designing a conceptual ontology-based framework for mobile learning which could be used in rural secondary schools. The framework takes into account the following: a knowledge base, ontology, software agents, learning resources and learning/teaching content. Agents search for learning objects and extract knowledge according to learner and teacher/instructor profiles. The proposed framework would facilitate collaboration, sharing of ideas, instruction flow and access to learning and teaching content with accuracy, anytime from anywhere.
Beacon Frame Manipulation to Mitigate Rogue Access Points: Case of Android Smartphone Rogue Access Points
(Compusoft, 2014-02) Nyathi, Thambo; Ndlovu, Siqabukile
The use of wireless devices to access corporate network resources is now part of the norm within corporate environments. When wireless users need to connect to a network they hardly question the source of their connectivity. Mobile phones, particularly smartphones allow users to access network resources. These harmless looking wireless devices can be a source of major threats if configured to be so. The Internet is awash with mobile apps capable of performing packet sniffing. These applications, coupled with the capability of the smartphone to be configured as an access point, can present a Smartphone Rogue Access Point. Access Points advertise their availability using what is called a beacon frame. This research paper proposes a solution which restructures this beacon frame to include an Authentic Access Point Value which can be used to defend against Rogue Access Points.
Bio-metric Implementation of Bayesian Networks for Face Recognitionon Android Mobile Devices
(2013-02-01) Masundire, Daniel; Chilumani, Khesani R.; Nyathi, Thambo
Face recognition is a field that receives attention and inquiry by Artificial Intelligence, Computer Security and Intelligent Data Processing researchers. Its application as a biometric has also grown due to the growth of the camera technologies. The digital camera’s resolution and noise reduction in images makes the camera view the world in more or less the same as a human being. However, this technology has been difficult to implement on mobile devices, phones in particular. This has been chiefly because of the computational complexity of the algorithms used. The memory size and processing speed of the mobile phones has been a constraint as well. There has been a huge growth experienced in the mobile phones’ industry with respect to the gadgets’ processing power. Face detection has been implemented using other statistical methods but this research uses the Bayesian network. This method is graphical and uses probabilistic inference. This helps in reasoning with incomplete and unknown information. The Bayesian Network is applied on data that would have acquired from a face image using Principal Component Analysis (PCA). PCA is used to reduce the dimensions of the image. The co-variances matrix from the principal components is used in the Bayesian network. The Bayesian network uses prior knowledge and the weights on the nodes are modified using weights formulated by a probability distribution function. This means, unlike other neural networks, the weights of a Bayesian network are not constants. We formulate our problem as the maximum a posteriori (MAP) estimate of a properly defined probability distribution function (PDF). A Bayesian network is used to represent the PDF as well as the domain knowledge needed for interpretation (Kumar and Desai, 1996). The development is done for Android-based mobile phones. The Android is an open source mobile phone operating system that runs on a Linux kernel. In this dissertation, we seek to improve face recognition for mobile devices by using dedicated statistical generative models. Gaussian Mixture Models (GMM) and Hidden Markov Models (HMM), which are classical generative models, have been successfully proven in face recognition. The GMM and HMM based models treat the facial features under investigation as independent. This is not consistent for a face because facial features are related to each other. Bayesian networks can be used to analyse and process the face as a graphical representation of dependent features. It only detects the frontal view of the face, that is, the face to be detected has to be showing the frontal features of the face. An appearance-based recognition and detection method is used. The prototype was built for Androidbased mobile phones. Mobile phones which run on Symbian, Windows and Apple (iOS) operating systems are not going to be covered.
Changing mindset- sets towards equity and equality at all levels at institutions.
(2014-09) Msongelwa – NJINI, Juliet B.
Gender issues gained momentum since the 1970s pushed by a wave of feminists. Ever since, gender issues have been discussed and debated in many foras. But, the Beijing International Conference (1995) was the climax that changed the landscape. Zimbabwe participated and was fully represented from all sectors of the population. The Conference came up with the ” Beijing Platform of Action”. This actually pushed the UN to quickly set up what we know today as “UNIFEM” the Women’s wing of the United Nations. UNIFEM in 2005, 10 years after Beijing declaration, reviewed the progress by setting up the Millennium Development Goals which were to be adhered to by all Countries who are members of the UN. These Goals are to be reviewed in 2015. This is the time of change and critical challenge for all women working in tertiary institutions for reviewing and evaluating the gains achieved to date and establish whatever gaps still exist.
Climate Variability Forecasting Using Bat Algorithm Optimised Artificial Neural Network.
(Zimbabwe Journal of Science & Technology, 2015) Kokera, N.; Chilumani, Khesani, R.; Mzelikahle, Kenman
This paper presents a summary and results of a study that was conducted in an attempt to forecast climate variability in Zimbabwe using the BAT Algorithm optimised Artificial Neural Network (BAT-ANN) analysis technique. Forecasts of climate ahead of time can potentially allow governments, farmers and other players in private and/or public sectors to make decisions to reduce unwanted impacts or take advantage of expected favourable climate. However, potential benefits of climate forecasts vary considerably because of many physical, biological, economic, social, and political factors. In a developing country, like Zimbabwe where agriculture is the base of the national economy, climate conditions play leading role for progressive and sustainable development, therefore climate variability forecasts are very important. The BAT-ANN was adapted and tested using the Zimbabwean meteorological dataset and results confirm that our proposed model has the potential for reliable climate forecasting for a 25 year period. The mean percentage accuracy was used to evaluate the performance of the trained climate forecasting neural network and proved sufficient. Therefore, in this paper, we present a new technique to climate variability assessment namely; the BAT-ANN. In this study, the approach employed to achieve objectives was; collecting quantitative data, adapting a BAT-ANN for analysis, and developing a Java program that employs the BAT-ANN for forecasting. The objectives of the study were met.
Cyber Security Awareness and Education Framework for Zimbabwe Universities: A Case of National University of Science and Technology
(2022-04-05) Mutunhu, B.; Dube, S.; Ncube N.; Sibanda, S.
Internet-related attacks have become prevalent and are expected to increase as the reliance on the internet also increases. Consequently, cyber security has become an essential concept in everyday life and cyber security awareness is key in the protection of people and systems against cyber threats. The study is sought to establish the current levels of cyber security awareness among students and staff in universities and propose a framework for conducting cyber security awareness and education programs. Data analysis was carried out using Statistical Package for Social Sciences (SPSS) and represented in descriptive and frequency ways as well as in percentage form. Based on research findings in this study, it has been established that students and staff at universities do not have the requisite knowledge and understanding of the importance of cyber security principles, their practical application in their day-to-day activities, and are not aware of how to protect their data. It is therefore recommended that universities should implement comprehensive awareness and education programs for the adoption of necessary safety measures and a framework for conducting such programs are proposed.
A distributed systems approach to knowledge-based systems for the Utilisation of south african wool
(AUTEX, 2009-06) Dlodlo, Nomusa; Hunter, Lawrance; Cele, Cyprian; Botha, Anton F.; Metelerkamp, Roger
Potential and present investors in the South African (S.A.) wool industry need up-to-date information on the production and properties of the wool they need for the particular end-products they manufacture or intend to manufacture. This article describes the concept and development of a knowledge-based advisory system on the utilisation of South African wool for the benefit of present and potential investors and other interested parties. The architecture of the system encompasses the concept of distributed systems and the related advantages in its general architecture and within its internal components. It marries both expert and general knowledge-based systems.
Openphone user engagement and requirements solicitation in low literacy users
(2005) Ndwe, T.; Barnard, Etienne; Dlodlo, Mqhele Mashao; Daniel, Kuun; Christiaan, Sharma
The OpenPhone project aims to design an Interactive Voice Response (IVR) health information system that enables people who are caregivers for HIV/AIDS infected children to access relevant information by using a telephone in their native language of Setswana in Botswana. The system lowers accessibility barriers since it is accessible to illiterate users and the community of the blind. The design utilizes usability engineering methodology in order to ascertain that the end product is usable, efficient, effective and satisfactory to the targeted users who are predominantly females, ranging from semi-literate to illiterate adults but nevertheless numerically literate. The paper describes the methodologies that were used to obtain information from the target user population. The contribution that was made by staff members of the clinic where the caregivers normally get information services is also discussed. This stakeholder information has design implications on the OpenPhone system. Based on the information gathered, we are now able to begin the initial design of the OpenPhone system.
Optimisation of a TV White Space Broadband Market Model for Rural Entrepreneurs
(River Publishers, 2014-12) Nleya, Sindiso M.; Bagula, Antoine; Zennaro, Marco; Pietrosemoli, Ermanno
Leveraging on recent TV white space communications developments in regulations, standards initiatives and technology, this paper considers a suitable next generation network comprising of two primary users (PUs) that compete to offer a service to a group of secondary users (SUs) in the form of mesh routers that belong to different entrepreneurs participating in a noncooperative TV white space trading. From a game theoretic perspective the non-cooperative interaction of the PUs is viewed as a pricing problem wherein each PU strives to maximize its own profit. Subsequently the problem is formulated as a Bertrand game in an oligopolistic market where the PUs are players who are responsible for selling TV white spectrum in the market while the SUs are the players who are the buyers of the TV white spectrum. The PUs strategise by way of price adjustment, so much such that SUs tend to favour the lowest price when buying. The inter- operator agreements are based on the delay and throughput QoS performance optimization metrics respectively. A performance evaluation of both models is comparatively performed with regards to parameters such as cost, generated revenue, profit, best response in price adjustments and channel quality. The throughput based analytic model fares better in terms of providing channel quality as it has a better strategy which is a decreased price value.
Optimisation of Self Organising Maps Using the Bat Algorithm
(2017) Mzelikahle, Kernan; Mapuma, Dunstan Junior; Hlatywayo, Dumisani J.; Trimble, John; Hlatywayo, Dumisani J.
Self Organising Maps are among the most widely used unsupervised neural network approaches to clustering. They have been shown to be efficient in handling large and high dimensional data. The Bat Algorithm is a swarm intelligence based, meta- heuristic optimisation algorithm. It is based on the echolocation behaviour of micro-bats with varying emission pulse rates and loudness. This paper gives a novel hybrid optimisation method which is here called the Bat Optimised Self-Organising Map. It combines the basic Self Organising Map learning algorithm with the Bat Algorithm. In this optimisation technique, the Bat Algorithm is used to initialise the weight vectors for a Self Organising Map to a near global optimum prior to the competition.
Optimisation of the Linear Probability Model for Credit Risk Management
(2014-11) Nyathi, K.T.; Ndlovu, Siqabukile; Moyo, S.; Nyathi, Thambo
One of the aims of the banking business is to provide loans to applicants. Credit risk management plays an important role in banks, as loans generally account for half to three quarters of the total value of bank assets. Credit scoring is a systematic method for evaluating credit risk and assists decision makers determine whether or not to provide loans to applicants. Scoring models are systematic means of evaluating the creditworthiness of a loan applicant. However, existing scoring models cause some loan applications to be rejected unnecessarily as their credit rates are lowered to rejection levels due to lack of information such as previous loan payment data. This might be refusal of good credit, which potentially can cause the loss of future profit margins. This study aims at optimising one such credit scoring model to ensure that it uses only the critical scoring criteria to determine a credit score. The optimised model will not only reduce the proportion of unsafe borrowers, but also identify profitable borrowers.
A rule-based expert system to establish the linkage between yarn Twist factor and end-use
(AUTEX, 2009-09) Dlodlo, Nomusa; Hunter, Lawrance; Botha, Anton F.; Cele, Cyprian; Metelerkamp, Roger
Optimising the technical and economic requirements to obtain a yarn with the appropriate twist level for sustained yarn quality and usage is of paramount importance. This paper describes the concepts and development of a rule-based expert system to establish the optimum linkage between the yarn twist factor and end-use of a yarn and determine the appropriate twist for the particular yarn.
A Semantic Web Solution for Circumventing Disparities between Electronic-Learning Systems and Mobile-Learning Systems
(2016) Ngwenya, Sibangiso; Mangena, Sikhulumani Bayeza; Chilumani, Khesani R.
Strategies for community focused postal service development
(National Inquiry Services Centre, 2015-11-16) Trimble, John; Chilumani, Khesani R.; Ngwenya, Sibangiso
To maintain its relevance, the postal system must look at ways to innovate and optimize. It must optimize its use of resources and delivery of current services. It must employ innovation to develop new opportunities and services. The key will be to leverage its infrastructure and build on its strong community linkage, while taking advantages of emerging trends in information and communication technology. This study uses information gathered from the postal systems in Africa and other less developed settings. It also draws on postal expansion options identified by the Universal Postal Union (UPU) in the areas of e-post, e-commerce, e-government and e-finance, as a basis for a framework orientated to community service in southern Africa. This framework is designed to facilitate the development of a more effective postal research strategy that is well integrated into the overall business strategy of the post office, building on existing services and incorporating new e-postal services. This overall process should encourage regional and continental integration of postal services and foster citizen and community empowerment.
Using Fuzzy ARTMAP for Symmetric Key Generation
(American Institute of Science., 2015) Mulopa, John; Ndlovu, Siqabukile; Mzelikahle, Kernan; Nyathi, Thambo
Neural cryptography deals with the problem of key exchange between two communicating neural networks using the mutual learning concept. It is the first algorithm for key generation over public channels which are not based on the number theory. The two networks exchange their outputs and the key between the two communicating parties is eventually presented in the final learned weights, when the two networks are synchronised. The security of neural synchronisation is put at risk if an attacker is capable of synchronising with any of the two parties during the training processes. However, the security of a cryptosystem is robust if the algorithm is strong and the keys are long, unpredictable, and random This research proposes use of two distant remote Adaptive Resonance Theory MAP (ARTMAP) architectures that are trained to learn from a unique data set and finally synchronise to same weights.

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