Assessment of household energy utilized for cooking in Ikeja, Lagos state, Nigeria

Household cooking energy accounts for a major part of the total energy consumed in Nigeria. Factors affecting the choice of Household energy utilized for cooking and the type preferred in Ikeja area of Lagos state were investigated in this study. Data were obtained through oral interview and administration of structured questionnaire on 250 randomly sampled households in the study area. MATLAB was used to conduct descriptive statistics, inferential statistics and percentage difference between used energy and preference energy. The study revealed that kerosene and Gas (LPG) were mostly used for daily cooking (48.60%) and (36.30%) respectively. Only a small proportion use Charcoal, firewood and electricity for their daily cooking, the percentage being 7.10%, 5.7% and 2.4% for charcoal, firewood and electricity respectively. However preference rating of household energy was highest in Gas followed by electricity, kerosene, charcoal and firewood respectively. Chi-test, linear-by-linear relationship test, likelihood ratio test revealed that level of income, level of education and type of employment affects the choice of fuel used for cooking and the type preferred. http://dx.doi.org/10.4314/njt.v35i4.1

Performance Modelling of Steam Turbine Performance using Fuzzy Logic Membership Functions

A Fuzzy Inference System for predicting the performance of steam turbinebased on Rankine cycle is developed using a 144-rule based in analyzing the generated data for different inlet and outlet conditions. The result of efficiency for different types of membership functions and defuzzification method was obtained. Centroid method of defuzzification gave good results irrespective of the type of membership function with error less than 5%. However, other defuzzification methods gave good result for some types of membership functions. Result of different input data tested do not vary significantly (P<<0.05). It can therefore be concluded that Fuzzy logic can be used to effectively predict performance of a steam turbine. ©JASE

Design and development of plantain fibre extraction machine

The traditional retting technique of extracting plantain fibres is faced with various constraints such as longer extraction time and poor fibre production rate. This study is targeted at overcoming the limitations associated with traditional methods of extracting plantain fibres through the development of electrically powered machine capable of extracting plantain fibres. The method employed involves the selection of appropriate materials, design, fabrication and assembly of the various components of the machine parts. From the analysis a 2 horsepower electric motor is required to drive the machine. The length of flat-belt required to drive the pulley was 1.47 m at an angle of lap on the smaller pulley of 2.87 rad. A resultant load of 174.87 N act on 11.6 mm diameter shaft with maximum bending moment of 10.33 Nm. The total weight of shaft, pulping drum and bearing on frame was 67.51 N. Also, a force of 150 N, 200 N and 250 N could pulp a thickness of plantain ribs of approximately, 6 mm, 6.5 mm and 7 mm, respectively. The test result showed that the machine could extract a sliced pseudo stem thickness between 4.0 mm and 10 mm at 27 and 42 seconds, respectively. It is expected that the plantain fibre extraction machine fabricated would save plantain fibre production time.Keywords: Plantain fibres, Pseudo stem, extraction machine, retting techniqu

Performance Modelling of Steam Turbine Performance using Fuzzy Logic Membership Functions.

A Fuzzy Inference System for predicting the performance of steam turbine based on Rankine cycle is developed using a 144-rule based in analyzing the generated data for different inlet and outlet conditions. The result of efficiency for different types of membership functions and defuzzification method was obtained. Centroid method of defuzzification gave good results irrespective of the type of membership function with error less than 5%. However, other defuzzification methods gave good result for some types of membership functions. Result of different input data tested do not vary significantly (P< <0.05). It can therefore be concluded that Fuzzy logic can be used to effectively predict performance of a steam turbine

Artificial Neural Network (ANN) Pathloss Prediction Model for LTE Network for Microcells in an Urban Environment

One of the challenges faced by telecommunication service providers is capacity. The capacity of a cell depends on the model used in planning the cell during deployment stage. This paper presents Artificial Neural Network (ANN) Pathloss Prediction model for Long Term Evolution (LTE) network for microcells in Benin city, Edo state, Nigeria. Received signal strength data collected with respect to distance, mobile station antenna height and base station antenna height was used to create a data base with pathloss estimated from the measured data. A feature variable consisting of   of measurement data collected was used to train a 4-32-1 multilevel perceptron artificial neural network with pathloss as the label using python language on Scientific python development environment interface (SPYDER).  The result of the  test data shows that artificial neural network is suitable for predicting pathloss in Benin City. This is as a result of root mean square error (RMSE) values and mean absolute error values of  and 0.42  obtained respectively which are less than the  error value allowed for network planning. It is recommended that the result of the study be adopted in designing or expanding LTE network capacity in the areas studied in this work. &nbsp