A Neuro-Linguistic Model for Speech Recognition in Tone Language

The primary aim for this work is to develop a speech recognition system that exploits the computational paradigm with learning ability and the inherent robustness and parallelism in ANN coupled with the capability of fuzzy logic to model vagueness, handling uncertainness and support for human reasoning. This research made two unique contributions to the area of speech recognition. Firstly, we identified and specify entities in the speech recognition process using a neuro-linguistic approach. This approach not only offers a non-conflict degree for different speech recognition situation, it also provide stable integration mechanism for various level of speech unit. Secondly, this work is the first to illustrate speech recognition model using an African language, in this case Yoruba language. It is important, however, to note that this approach can also be used for any tone language and with little modification for all languages as well. (Botswana Journal of Technology: 2003 12(2): 32-39

Computational modelling of selected E-waste recycling process

E-wastes generation and management is still a major challenge for most developing countries. This paper discusses the development of a computational model for effective generation, accumulation and disposal of e-waste. This is with a view to providing information for managing the pattern of the e-waste growth and the recycling processes. Coloured Petri net (CPN) was used to model three selected e-waste recycling process. These models were simulated and analysed using the CPN Tools. The results of the simulation of the selected ewaste process models showed that the e-waste dynamics is a forward sequential and concurrent process. The model never can reach a state, which it is impossible to terminate with the correct result.Keywords: E-waste, Computational model, Recycling process, Simulation, State spaceVol. 26 No 1, June 201

The character and evolution of E-waste in Nigeria

Technologically developing nations are more vulnerable to the negative effects of e-waste because they are less able to manage or process e-waste generated. The complexity of e-waste in terms of the dynamics of its generation and growth, particularly in developing countries, is raising many concerns. A systematic study of the e-waste dynamics emerges in the context of the need for proper understanding of the problem and formulating an informed policy for managing the ewaste problem. Images and other data about e-waste were collected using digital cameras and three structured interviews of users and dealers. The data were collected at the Obafemi Awolowo University (OAU), Ile-Ife as the case study. Two hundred and ninety copies of questionnaires were administered and collated. The numerical data were analyzed using R data analysis and process tool. The results of the R analysis showed that at a 95% confidence level, the computer equipment that will be disposed on OAU campus by 2020 would be 417 units. Compared to the 800 units in circulation in 2014, 50% of personal computer (PC) components will become ewaste.Keywords: E-wastes, Hazardous, R Analysis, Disposal, Developing countryVol. 26, No 1, June 201