Professional AssociationsThese publications feature articles on infrastructure projects, engineering developments and the latest on-goings in the Institution of Engineers Malaysia (IEM). Highlights on academic research and findings are also showcased in both publications which are distributed to the members regularly.http://dspace.unimap.edu.my:80/xmlui/handle/123456789/133902024-03-28T21:25:18Z2024-03-28T21:25:18ZPerformance of sandwiched kenaf fibre and sugarcane husk in treating pavement runoffNor Azlina, AliasBadronnis, Yusufhttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/802442024-03-05T00:29:21Z2022-01-01T00:00:00ZPerformance of sandwiched kenaf fibre and sugarcane husk in treating pavement runoff
Nor Azlina, Alias; Badronnis, Yusuf
Rapid urbanisation appears to cause more paved parking areas being provided which contributed into a greater impermeable surface area. Pavement runoff from the impermeable surface area does indeed have a high concentration of contaminants and it has been identified as a major cause of deterioration of nearby recipient water bodies. The more develop the country is, the poorer the water quality they have (Ashantha, et. al 2005). It carries pollutants, sediments, nutrients and heavy metals. An intensifying development in areas with impervious surface leads rainwater with small particles runs rapidly into drainages and rivers that may cause blockage that eventually leads to flash flood problem. Changes in land use increased the degree of soil imperviousness led to the increased of stormwater volume (Kundzewicz, et al., 2007). This study used a potential block system that is equipped with inner storage and expected to give minimal impact to the environment in order to improve the water quality and prevent ponding in the paved and impermeable areas. Figure 1 illustrates the simulation of pavement runoff was conducted to evaluate the performance of kenaf fibre and sugarcane husk that sandwiched in a modular block at a model scale in the hydraulic laboratory. The collected pavement runoff stored lower tank were tested and parameters observed were chemical oxygen demand, biological oxygen demand, amounts of suspended solids and turbidity. Water quality before and after being treated with the filtration media were compared. The performance and effectiveness of the two bio-composite materials as filter media were also assessed in decelerating the rate of runoff. Results show that the two proposed bio-composite
materials are capable in reducing surface runoff, storing water, and reducing pollutant concentrations. The kenaf fibre appears to perform better in treating the polluted pavement runoff while sugarcane husk has a better performance in storing runoff and reduce the peak flow of runoff.
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2022-01-01T00:00:00ZNoise pollution near to the construction site in an urban area (a case study in Shah Alam)Suhaila, NasimJanmaizatulriah, Janihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/802432024-03-04T08:47:42Z2022-01-01T00:00:00ZNoise pollution near to the construction site in an urban area (a case study in Shah Alam)
Suhaila, Nasim; Janmaizatulriah, Jani
In the contemporary era of Malaysia's rapid modernisation, a multitude of construction and urbanisation projects are underway, particularly in urban areas. As Malaysia strives to achieve its modernisation goals and join the ranks of developed nations, it is imperative to prioritise and mitigate noise emissions stemming from these construction and urban development endeavors.
Urban regions characterised by residential, commercial, educational zones, construction activities, and heavy traffic congestion often experience elevated noise levels. These multiple sources of noise have a detrimental impact on the health and well-being of the surrounding communities. The primary objectives of this study are to assess noise levels in areas near construction sites (specifically the Light Rail Transit (LRT) project), as well as away from construction sites, and to gauge the extent of noise disturbance experienced by the community. Additionally, the study seeks to measure the community's awareness of the effects of noise pollution. The chosen study areas encompassed the LRT-3 Shah Alam line construction site (coordinates: 3° 4'2.50 "N, 101°29'22.12 "E) and the non-construction site in Seksyen 9 (coordinates: 3°05'17.80" N, 101°31'24.42" E). Two methods were employed for data collection: first, the measurement of noise levels at the study areas using the Decibel X smartphone application, and second, the distribution of a questionnaire survey to the community residing near the construction site. The questionnaire aimed to evaluate the impact of noise pollution and the community's acceptance of noise emissions from the construction site. The findings revealed that the Equivalent Continuous Sound Pressure Level (LAeq) at the LRT-3 Shah Alam line construction site exceeded the permissible equivalent noise level (65 dB (A), registering at 83.44 dB (A) during weekdays and 74.82 dB (A) during weekends. In contrast, at the non-construction site in Seksyen 9, the LAeq remained below the permissible limit, with values of 54.13 dB (A) during weekdays and 49.42 dB (A) during weekends. The questionnaire survey indicated that a majority of the community living near the LRT-3 construction site were significantly disturbed by the construction activities and the additional noise stemming from vehicular traffic, given the site's proximity to a university. Respondents reported suffering from various effects of noise pollution, including headaches, stress, insomnia, diminished focus, and increased stress levels. The community expressed a consensus that raising awareness about the impacts of noise pollution from construction and urbanisation areas is essential, and they called upon the government to play a pivotal role in regulating noise emissions.
Link to publisher’s homepages at https://www.myiem.org.my/
2022-01-01T00:00:00ZInvestigation of causes and characteristics of monsoon extremes in Pakistan: a case study for monsoon 2022Haris Uddin, QureshiSyed Muzzamail, Hussain ShahMohamed, YassinSani Isah, AbbaZahiraniza, Mustaffahttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/802422024-03-04T08:37:29Z2022-01-01T00:00:00ZInvestigation of causes and characteristics of monsoon extremes in Pakistan: a case study for monsoon 2022
Haris Uddin, Qureshi; Syed Muzzamail, Hussain Shah; Mohamed, Yassin; Sani Isah, Abba; Zahiraniza, Mustaffa
Apart from the long-term changes in the climate patterns, the extreme weather conditions (heat waves, heavy precipitation, and droughts) have also emerged as a prominent consequence of the global climate change. Pakistan being listed among the most susceptible nations to the changing climate patterns has witnessed an increasing trend of extreme precipitation (particularly during monsoon). Therefore, this study was conducted to probe the major meteorological causes of extreme monsoon precipitation in Pakistan, with a special focus on the monsoon 2022, that lead to severe flooding and devastation of infrastructure, agriculture, and loss of lives. The methodology included an in-depth analysis of unusual atmospheric conditions that triggered exceptionally high precipitation. For this purpose, a number of 25 stations across the country lying in the southwest monsoon zone were selected. The analysis revealed that in April 2022, about 1.2 to 6.0 °C above normal temperature was observed in Balochistan, 2.0 to 4.5 °C in Sindh, and 3.0 to 5.8 °C in Punjab and KPK. Similarly, in May, about 1.0 to 3.5 °C above normal temperature was observed in Sindh and Balochistan, and 1.0 to 3.0 °C in Punjab and KPK. Due to this exceptional warming, an intense trough developed over the area. In April, about 0.5 to 2.5 mb below normal air pressure was observed in Sindh and Balochistan, and 1.5 to 2.2 mb in Punjab. In May, about 1.0 to 3.0 mb below normal air pressure was observed over the study area. For precipitation, the analysis unearthed that in July 2022, about 100 to 300 mm above normal monthly rainfall was received
in Sindh, 50 to 200 mm in Punjab and Balochistan, and 5 to 30 mm in KPK. In August, about 100 to 500 mm above normal rainfall was received in Sindh, and 50 to 250 mm in KPK and Balochistan. However, in September, about 15 to 75 mm above normal rainfall was received in Punjab, while the remaining stations showed a negative departure. Conclusively, the unusual pre-monsoon heating resulted in an intense depression over the plains that facilitated the excess moisture penetration from the Indian Ocean, and consequentially extreme precipitation in Pakistan in 2022. The study outcomes are expected to help in devising an effective climate change adaptation and mitigation strategy for the country and to conduct further research on the prediction and analysis of extreme weather conditions under the changing climate patterns.
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2022-01-01T00:00:00ZComparison of artificial intelligence (AI) based models for sediment transport prediction using swot and statistical analysesJie, Chin RenWei, Lee FooZee, Kwong KokHin, Lai Saihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/802412024-03-04T08:33:14Z2022-01-01T00:00:00ZComparison of artificial intelligence (AI) based models for sediment transport prediction using swot and statistical analyses
Jie, Chin Ren; Wei, Lee Foo; Zee, Kwong Kok; Hin, Lai Sai
The dynamics involved in sediment scour are complicated. Hence, it is a challenging task to create a general empirical optimisation algorithm for reliable sediment load estimation. This study aims to analyse the architectures of assorted artificial intelligence (AI) based model to predict suspended sediment load in fluvial system. An in-depth study on Artificial Neural Network (ANN), Adaptive NeuroFuzzy Inference System (ANFIS), and Support Vector Machine (SVM) was carried out. The
goal of this study is to evaluate the performance of AI-based models from various research using statistical as well as Strengths, Weaknesses, Opportunities, and Threats (SWOT) analyses. Three statistical measures of model prediction accuracy including coefficient of correlation (R), root mean square error (RMSE), and mean absolute error (MAE) were used. The results revealed that the SVM and ANFIS models outperformed the other soft computing and conventional models. It is concluded that the SVM and ANFIS models are preferred and may be successfully used to estimate the suspended sediment concentration for the research area.
Link to publisher’s homepages at https://www.myiem.org.my/
2022-01-01T00:00:00Z