Modelling and predicting energy consumption in laboratory buildings using multiple linear regression

This study was carried to improve the energy saving by investigating the influence factors that contribute to high energy consumption in a building particularly related to the building in Technology Campus, UTeM. Correlation analysis was performed to measure the strength of relationship between the influence factors whereby all the factors proven to have a strong linear correlation with the energy consumption. The Stepwise Selection of Multiple Linear Regression (MLR) were used to determine and modelling the most influence factors that affects the energy consumption. The final linear regression models was developed based on the amount of lighting in a building and surrounding temperature in the building which is considered as major influence factors that affect the energy consumption. Comparing the actual and predicted energy consumption in Technology Campus, UTeM showed that the MLR model obtained can be used to predict energy consumption and accounted for around 81% of the variance

Lecturers’ Method of Teaching Mathematics: Engineering Technology Students’ Perceptions in UTeM

Teaching Mathematics courses at the tertiary level institutions nowadays can be quite challenging especially when the delivery method for the subject matter is known to always be very traditional using the chalk and board. This study examined the Engineering Technology (ET) students’ perceptions of their lecturers’ teaching method for Mathematics courses at the Faculty of Engineering Technology (FTK), Universiti Teknikal Malaysia Melaka, Malaysia (UTeM). A mini survey with quantitative research methods was utilized. 264 second year ET students with different fields of studies at FTK, UTeM, were asked to complete a set of questionnaires administered during the final week of the semester. A questionnaire consists of questions regarding how students perceive their lecturers’ teaching method during the class sessions. From the findings, conclusion has been drawn regarding the students’ perceptions of their Mathematics lecturers in promoting different methods in teaching Mathematics. The result shows that most of the mathematics lecturers incorporated both active and passive teaching methods in teaching of the subject matter. Keywords: perceptions, student-centred learning, teacher-centred learning, engineering technolog

ARAR Algorithm In Forecasting Electricity Load Demand In Malaysia

Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model

Comparative Performance Of ARIMA And DES Models In Forecasting Electricity Load Demand In Malaysia

Malaysia is a developing country which is having a high level of energy demand. Load demand forecasting is essential that is also in line with increasing demand of electricity. The purpose of the current study is to compare the performance of two time series models in forecasting electricity load demand in Malaysia. Two methods are considered, which are Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (DES). Using Mean Absolute Percentage Error (MAPE) as the forecasting performance measure, the study concludes that ARIMA is more appropriate model

Assessment Of Aboveground Biomass And Temperature In The Tropical Rainforest Of Malaysia

The relation between tropical rainforest to the climate variability is very important. This research aims to determine the relationship between aboveground biomass which prefer tree in the tropical rainforest and surrounding temperature. Diameter at breast height (DBH) of ten tree species and surrounding temperature collected data were taken to measure the correlation between the two variables by using statistical test. Furthermore, forest biomass estimation is also important towards the assessment of the productivity, structure and forest condition. The analysis in this research shows that simple linear regression model can be used to predict the future value of DBH for each species. The findings may help the reduction of greenhouse gas emissions with proper conservation and sustainable management

Green strength properties of waterjet abrasive waste as potential composition in green mould By Taguchi And ANOVA approach

The sand casting process still continues today due to the cost-effectiveness of materials and processes. There is a wide variety of castings related to composition and size, but silica sand is widely available from coastal line mining and has a negative impact on the environment. Moreover, waste from waterjet cutting of non-ferrous and ferrous metals is practically unhazardous and may potentially be used in sand casting mould. The aim of this paper is to optimize the proportion of coal dust, water and bentonite added to the silica sand mixture and the waterjet cutting abrasive waste as a new way of handling waste with the potential to be used in sand casting manufacturing. The method used was L9 orthogonal array optimization and the composition was qualitatively measured using a green compression strength test and a green shear strength test. Factors were evaluated using the analysis of variance (ANOVA) to find the the critical factors while confirmation test was conducted for the optimal material proportion. The study concluded that the ideal ratio for silica sand mixture with waterjet abrasive waste is bentonite-12%, coal dust-5%, and water-7% for green compression strength while bentonite-12%, coal dust-6%, water-7% for green shear strength. With proper selection, the incorporation of waterjet abrasive waste into the green sand mixture is promising to potentially be used in green sand mould casting without undermine the quality of mould

Variable selection using least absolute shrinkage and selection operator

Least Absolute Shrinkage and Selection Operator (LASSO) and Forward Selection are variable selection method that implement in this study. The objectives of this study are to apply forward selection method in variable selection for a regression model, to apply LASSO method in variable selection for a regression model using quadratic programming and leave one out cross validation and choosing the better model obtained from forward selection and LASSO method using least mean square error. The forward selection method implemented in the statistical package for social sciences (SPSS). Quadratic programming technique and leave one out cross validation from MATLAB software is applied to solve LASSO. The analyzed result showed forward selection and LASSO are chosen the same variable that should be included in the model. However the coefficient of the regression for both model differ. To choose between the two models, MSE is used as the criteria where the model with the smallest MSE is taken as the best model. The MSE for forward selection and LASSO are 0.4959 and 0.4765 respectively. Thus, LASSO is the better model compared to forward selection model

Applied TRIZ in Improving Productivity in Textile Industry

TRIZ is a methodology and a collection of problem solving tools and strategies that has been used in many other fields. Therefore, this paper proposes TRIZ method for improving the productivity in a textile industry. It focuses at the packing department in a textile company situated in Malaysia. The process was monitored and the problem was observed. TRIZ method is applied in this problem using Functional Analysis and trimming method. A comparison between before and after implementation is done in order to evaluate the productivity effectiveness

Applied TRIZ in Improving Productivity in Textile Industry

TRIZ is a methodology and a collection of problem solving tools and strategies that has been used in many other fields. Therefore, this paper proposes TRIZ method for improving the productivity in a textile industry. It focuses at the packing department in a textile company situated in Malaysia. The process was monitored and the problem was observed. TRIZ method is applied in this problem using Functional Analysis and trimming method. A comparison between before and after implementation is done in order to evaluate the productivity effectiveness