The comprehensives of particulate matter studies are needed in predicting future haze occurrences in Malaysia. This paper presents the application of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) coupled with sensitivity analysis (SA) in order to recognize the pollutant relationship status over particulate matter (PM10) in eastern region. Eight monitoring studies were used, involving 14 input parameters as independent variables including meteorological factors. In order to investigate the efficiency of ANN and MLR performance, two different weather circumstances were selected; haze and non-haze. The performance evaluation was characterized into two steps. Firstly, two models were developed based on ANN and MLR which denoted as full model, with all parameters (14 variables) were used as the input. SA was used as additional feature to rank the most contributed parameter to PM10 variations in both situations. Next, the model development was evaluated based on selected model, where only significant variables were selected as input. Three mathematical indices were introduced (R2, RMSE and SSE) to compare on both techniques. From the findings, ANN performed better in full and selected model, with both models were completely showed a significant result during hazy and non-hazy. On top of that, UVb and carbon monoxide were both variables that mutually predicted by ANN and MLR during hazy and non-hazy days, respectively. The precise predictions were required in helping any related agency to emphasize on pollutant that essentially contributed to PM10 variations, especially during haze period.
The objectives of this study are to identify the significant variables and to verify the best statistical method for determining the effect of indoor air quality (IAQ) at 7 different locations in Universiti Sultan Zainal Abidin, Terengganu, Malaysia. The IAQ data were collected using in-situ measurement. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discrimination analysis (LDA), and agglomerative hierarchical clustering (AHC) were used to classify the significant variables as well as to compare the best method for determining IAQ levels. PCA verifies only 4 out of 9 parameters (PM 10 , PM 2.5 , PM 1.0 , and O 3 ) and is the significant variable in IAQ. The PLS-DA model classifies 89.05% correct of the IAQ variables in each station compared to LDA with only 66.67% correct. AHC identifies three cluster groups, which are highly polluted concentration (HPC), moderately polluted concentration (MPC), and low-polluted concentration (LPC) area. PLS-DA verifies the groups produced by AHC by identifying the variables that affect the quality at each station without being affected by redundancy. In conclusion, PLS-DA is a promising procedure for differentiating the group classes and determining the correct percentage of variables for IAQ.
At the end of December 2019, China faced severe acute respiratory syndrome Coronavirus-2 (COVID-19) which caused a "very high" risk assessment ranking. Unfortunately, it has spread all over the world and has caused a great number of fatalities. In view of this, a study of the non-parametric statistical method was carried out with the aim of detecting and quantifying the outbreak of COVID-19. From the univariate analysis, daily cases had the highest mean value indicating widespread data from the outbreak of COVID-19 in Malaysia. However, the worst output in the future during the RMO must be prepared with the help of the Government of Malaysia's Ministry of Health due to the high standard deviation value recorded. In addition, the western coast of Malaysia has been reported to have the most in comparison with the other regions. The Mann-Kendal test shows a declining trend pattern for new cases during RMO3 compared to RMO1, RMO2 and RMO4, with a dramatic increase in the Covid-19 outbreak during RMO1. Overall, the results show downward trends following the implementation of the RMO. These results have shown that the Malaysian Government has implemented an effective strategy to combat the COVID-19 outbreak.
Introduction Despite the health risks associated with second-hand smoke (SHS) exposure, smoking in the home is common in Malaysia, and almost exclusively a male behaviour. This study explored male smokers’ knowledge, beliefs and behaviours related to SHS exposure and smoking in the home, to guide future intervention development. Methods Twenty-four men who smoked and lived in Klang Valley, Kuantan or Kuala Terengganu took part in semi-structured interviews which explored knowledge and beliefs regarding SHS in the home, and associated home smoking behaviours. Data were managed and analysed using the framework approach. Results There was limited knowledge regarding the health risks associated with SHS: the smell of SHS in the home was a more prominent concern in most cases. Many had no rules in place restricting home-smoking, and some suggested that smoking in specific rooms and/or near windows meant SHS was not ‘shared’ with other household members. A few fathers had created but not maintained a smoke-free home prior to and/or after their children were born. Desire to smoke in the home conflicted with men’s sense of responsibility as the head of the household to protect others and set a good example to their children. Conclusions Men’s home-smoking behaviours are shaped by a lack of understanding of the health risks associated with SHS exposure. Gaining a broader understanding of the factors that shape men’s decisions to create a smoke-free home is important to facilitate the development of culturally-appropriate interventions that address their responsibility to protect other household members from SHS exposure. Implications Our findings highlight the need for public information campaigns in Malaysia to educate men who smoke regarding the health harms associated with SHS in the home and the ways in which SHS travels and lingers in household air. This is important given men’s concerns about SHS often focus on the smell of cigarette smoke in the home. Our findings suggest a number of potential avenues for future intervention development, including household and community-level initiatives which could build on men’s sense of responsibility as the head of the household and/or their general desire to protect their family.
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