Kelantan River Basin is affected by two significant monsoon seasons, namely the Northeast and Southwest monsoons that lead to flood and heavy downpour events. Consequently, analysis of rainfall series is gaining more attention from researchers. The aim of this study is to analyse the annual maximum series (AMS) and partial duration series (PDS) by fitting different probability distributions. Generalized Extreme Value (GEV), Generalized Pareto (GP), Log Pearson Type 3 (LP3), Log Normal (LN) and Log Normal 3 (LN3) were used in this study. The performances of these probability distributions were evaluated using different goodness-of-fit tests, namely the chi-square (χ2), Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) tests. Subsequently, the performances of probability distributions were compared and the best fit probability distribution was selected. The GEV and GP distributions were selected as the best fit probability distributions for AMS and PDS, respectively. The findings can provide useful information for flood mitigation and water resources management.
Noise Pollution is the high intensity of sound that is unnecessary and will cause harmful or danger towards human or nearby ecosystem. However, the occurrence of noise pollution is getting worse due to the process of country development. Noise pollution at construction site has become one of the noise pollution contributors in urban area where development in keep on going with the needs of construction projects. Area of study had been targeted at Klang Valley, Malaysia since it was one of the developing areas that consist huge amount of construction projects. Noise pollution produced at construction site is harmful to the health of those who involved in the construction projects and stay at the site for a long period of works. Thus, the main objectives of this study are to determine the factor of noise pollution at construction site and the effects of the noise towards those parties who involve such as engineer, contractor etc. The solutions to prevent or decrease the noise pollution at construction site were determined to help reducing its bad effects. Approximately 60 respondents had been collected in this survey to determine the most significant factor, effect and solution for noise pollution at construction site around Klang Valley. Based on the finding of this study, the significant factor caused noise pollution at construction site is due to heavy machinery operating. Respondents agreed that the noise pollution major affect is sleep disturbance. The significant solution against noise pollution at construction site is by applying muffler or silencer on construction machinery and equipment.
Flooding is one of the natural disasters that happens annually in Malaysia. Flooding is induced by the extreme rainfall event and this can cause severe impacts in terms of environment, society, health and safety. Consequently, investigating the best fit probability distribution for annual maximum rainfall can provide the fundamental ideas for government departments and relevant authorities to mitigate the flooding problems. The aim of this study is to investigate the best fit probability distribution in describing the characteristics of annual maximum rainfall for the period of 1994 to 2013 at the Kelantan River Basin. The Gamma, Gumbel, Generalized Extreme Value and Log Pearson Type-III distributions were fitted to the historical rainfall series. Three goodness of fit tests, namely the Kolmogorov-Smirnov, the Anderson-Darling and the Chi-Square tests were used to evaluate the probability distributions. The performances of each probability distribution generated by the goodness of fit tests were compared. Overall, the Generalized Extreme Value distribution seems to be the best fit probability distribution for the annual maximum rainfall at most of the rainfall stations except for the RPS Kuala Betis station that had the Log Pearson Type-III distribution as its best fit.
The construction industry is a risky and complex industry involving various parties characterized with different objectives, skills, cultures, and values. This requires effective communication management to facilitate interaction between them and ensure delivery of successful projects. The poor performance of the Malaysian construction sector has its root in poor communication. Poor communication may result in project failure. Therefore, this paper is essential to investigate the effects of communication issues in the construction industry. This research study was conducted and analysed using SPSS Software. The five-point Likert type scale has been adopted for the questions which is distributed to over 121 respondents who are working in the construction industry around Petaling Jaya, Klang Valley, Malaysia. A total of 8 effects of poor communication in the construction industry were identified. The most dominant effect is time overrun while other effects include project failure, cost overrun, fatal and non-fatal accidents, waste generation, increase carbon footprint and contribute to greenhouse effect. However, questionnaire surveys may result in dishonest answers. Hence, the study recommends conducting physical interviews to better understand respondents view on the negative impacts of poor communication and at the same time, raise awareness as a strategic approach to achieve successful construction projects.
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