Computer Science Publications

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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.
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.
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.
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.
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.

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