Mohd Khairul Amri Kamarudin

Selection of the Most Significant Variables of Air Pollutants Using Sensitivity Analysis

This study was conducted to determine the most significant parameters for the air-pollutant index (API) prediction in Malaysia using data covering a 7-year period (2006–2012) obtained from the Malaysian Department of Environment (DOE). The sensitivity analysis method coupled with the artificial neural network (ANN) was applied. Nine models (ANN-API-AP, ANN-API-LCO, ANN-API-LO3, ANN-API-LPM10, ANN-API-LSO2, ANN-API-LNO2, ANN-API-LCH4, ANN-API-LNmHC and ANN-API-LTHC) were carried out in the sensitivity analysis test. From the findings, PM10 and CO were identified as the most significant parameters in Malaysia. Three artificial neural network models (ANN-API-AP, ANN-API-LO, and ANN-API-DOE) were compared based on the performance criterion [R2, root-mean-square error (RMSE), and squared sum of all errors (SSE)] for the best prediction model selection. The ANN-API-AP, ANN-API-LO, and ANN-API-DOE models have R2 values of 0.733, 0.578, and 0.742, respectively; RMSE values of 8.689, 10.858, and 8.357, respectively; SSE values of 762,767.22, 1,191,280.60, and 705,600.05, respectively. The findings exhibit the ANN-API-LO model has a lower value in R2 and higher values in RMSE and SSE than others. ANN-API-LO model was considered as the best model of prediction because of fewer variables was utilized as input and far less complex than others. Hence, the use of fewer parameters of the API prediction has been highly practicable for air resource management because of its time and cost efficiency.

ASSESSMENT OF NATURAL GROUNDWATER RECHARGE IN TUDUN WADA LOCAL GOVERNMENT KANO STATE, NIGERIA

Water is important natural resources on earth which cater for all human endeavors. Estimation of groundwater recharge is an essential for efficient groundwater resources management. This research entails the assessment of natural groundwater recharge in Tudun Wada Kano, Nigeria. This study carried out on 2015 attempted to derive an empirical relationship to determine the groundwater recharge from rainfall in Tudun Wada based on seasonal groundwater balance using data from 2002 to 2013. This empirical relationship similar to Chaturvedi formula was derived by fitting the estimated values of rainfall recharge and the corresponding values of rainfall in the monsoon season through the non-linear regression techniques. The variance was found to be 29.50 %, and the recharge of groundwater commences at P = 15.28 inches and the relative errors was found to range from 0.95 to 28.43%.

Source apportionment of social support and quality of life index among drug abuse inmates using multiple linear regression

Drug addictions are some of the contributing factors to low level of quality of life (QoL) and other psychological problems in individuals. Studies on the influence of social support on the QoL of inmates with drug abuse dependency have identified that inmates who maintain close contact with their family and friends associated themselves with better satisfaction in interpersonal relationships. This study intends to show the effectiveness of Factor Analysis (FA) and Multiple Linear Regression (MLR) for the assessing quality of life indicator sources. The data from 12 prisons selected in Peninsular Malaysia was collected during the period April and June 2015. The 1753 respondents were selected using simple random sampling. The method of FA has identified five significant index categories- Excellent, Good, Moderate, Low and poor quality of life index (QoLi) were generated from FA. Keywords: social support; quality of life; multiple linear regression; inmates; factor analysis

Flood Management Using Data Driver Index: A Case Study in Kelantan, Malaysia

The deterioration of natures quality is among the contributing factors to environmental disasters arises from human attitude, which greedily developed the necessities of life without evaluating the risk of environmental damage including natural disasters such as floods. This will be more serious and life-threatening due to the changing surface and sub-surface of soil structure by human activities. This has caused the rain balance and running water to be disrupted. The river basins that are experiencing the rapid development such as in Kelantan, Terengganu, Pahang and Johor, will serious face environmental problems. Hence, the aim of this study is to identify the level of flood disaster management preparation in Kelantan state, December 2014. It involves three levels of preparation which are before, during and after at eight districts in Kelantan. According to Kelantan Strategic Research Centre, large flood events are due to the overflow of the Kelantan River which is the main source for the population around the river basin. The flood events have recorded the value of public utilities and property losses of almost 1 Billion Malaysian ringgit. This research used group sampling as the survey method, where the questionnaire was distributed to 434 respondents who were involved in the flood. The data analysis method uses principal component analysis (PCA) to determine the index value (MOF). The results of the analysis show that the highest indices of the pre flood recovery index is Mukim Melor, 1.11 while the lowest are Manek Urai and Ghucil, -0.62. The preparation during the Kadok flood is recorded as the highest at 0.96 and Ghucil the lowest, -0.80. While the post floods in Bunut Payung and Pasir Tumboh are recorded as 0.96 and -0.50 respectively. Hence, the documentation of flood management systems should be reconstructed at multi-tiered phases to minimize the management risk of natural disasters.

Spatial Model of Sky Brightness Magnitude in Langkawi Island, Malaysia

Sky brightness is an essential topic in the field of astronomy, especially for optical astronomical observations that need very clear and dark sky conditions. This study presents the spatial model of sky brightness magnitude in Langkawi Island, Malaysia. Two types of Sky Quality Meter (SQM) manufactured by Unihedron are used to measure the sky brightness on a moonless night (or when the Moon is below the horizon), when the sky is cloudless and the locations are at least 100 m from the nearest light source. The selected locations are marked by their GPS coordinates. The sky brightness data obtained in this study were interpolated and analyzed using a Geographic Information System (GIS), thus producing a spatial model of sky brightness that clearly shows the dark and bright sky areas in Langkawi Island. Surprisingly, our results show the existence of a few dark sites nearby areas of high human activity. The sky brightness of 21.45 mag arcsec −2 in the Johnson-Cousins V -band, as the average of sky brightness equivalent to 2.8 ×10 −4 cd m −2 over the entire island, is an indication that the island is, overall, still relatively dark. However, the amount of development taking place might reduce the number in the near future as the island is famous as a holiday destination.