Author
Muhamad Shirwan Abdullah Sani
Other affiliations: Universiti Putra Malaysia, Malaysian Ministry of Higher Education, International Institute of Minnesota
Bio: Muhamad Shirwan Abdullah Sani is an academic researcher from International Islamic University Malaysia. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 6, co-authored 22 publications receiving 133 citations. Previous affiliations of Muhamad Shirwan Abdullah Sani include Universiti Putra Malaysia & Malaysian Ministry of Higher Education.
Topics: Chemistry, Medicine, Food science, Chemometrics, Metabolomics
Papers
More filters
TL;DR: This is the first study carried out to assess the distribution and sources of LABs in surface sediments from Brunei Bay, Brunei, and showed L ABs concentrations variably due to the LABS intensity and anthropogenic influence along BruneiBay in recent years.
38 citations
TL;DR: The results of this paper highlighted the necessity of continuation of water treatment system improvement in Malaysia with respect to sewage molecular markers in surface sediments.
Abstract: This is the first extensive report on linear alkylbenzenes (LABs) as sewage molecular markers in surface sediments collected from the Perlis, Kedah, Merbok, Prai, and Perak Rivers and Estuaries in the west of Peninsular Malaysia. Sediment samples were extracted, fractionated, and analyzed using gas chromatography mass spectrometry (GC-MS). The concentrations of total LABs ranged from 68 to 154 (Perlis River), 103 to 314 (Kedah River), 242 to 1062 (Merbok River), 1985 to 2910 (Prai River), and 217 to 329 ng g−1 (Perak River) dry weight (dw). The highest levels of LABs were found at PI3 (Prai Estuary) due to the rapid industrialization and population growth in this region, while the lowest concentrations of LABs were found at PS1 (upstream of Perlis River). The LABs ratio of internal to external isomers (I/E) in this study ranged from 0.56 at KH1 (upstream of Kedah River) to 1.35 at MK3 (Merbok Estuary) indicating that the rivers receive raw sewage and primary treatment effluents in the study area. In general, the results of this paper highlighted the necessity of continuation of water treatment system improvement in Malaysia.
32 citations
TL;DR: In this article, the authors aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thoracica and Tetrigona binghami) based on physicochemical properties such as pH, moisture content, ash, total soluble solid and electrical conductivity.
31 citations
TL;DR: In this article, the distribution and sources of linear alkyl benzenes (LABs) were evaluated in surface sediments collected from Johor Bahru Coast and the Kim Kim River, Peninsular Malaysia.
28 citations
TL;DR: It is suggested that ANN was an effective tool to compute the MWQ in mangrove estuarine zone and a powerful alternative prediction model as compared to the other modelling methods.
27 citations
Cited by
More filters
708 citations
National University of Singapore1, Naturalis2, Curtin University3, University of the Ryukyus4, The Chinese University of Hong Kong5, Ramkhamhaeng University6, Vietnam Academy of Science and Technology7, American University in Cairo8, Davao del Norte State College9, Universiti Malaysia Sabah10, Hasanuddin University11, Indonesian Institute of Sciences12
TL;DR: This review highlights several key characteristics of urban coral reefs, including "reef compression" (a decline in bathymetric range with increasing turbidity and decreasing water clarity over time and relative to shore), dominance by domed coral growth forms and low reef complexity, variable city-specific inshore-offshore gradients.
151 citations
TL;DR: In this article, the applicability of Extreme Gradient Boosting (XGB) and Genetic Programming (GP) in obtaining feature importance, and abstracted input variables were imposed into the predictive model (the Extreme Learning Machine (ELM)) for the prediction of water quality index (WQI).
78 citations
TL;DR: In this paper, the authors compared the performance of multiple linear regression (MLR) and multi-layer perceptron (MLP) for predicting SO2 concentration in the air of the Tehran.
Abstract: Nowadays air quality is the main issue in urban areas that have been affecting human health, the environment, and the ecosystem. So, governmental authorities, environmental and health agencies usually need the prediction of daily air pollutants. This prediction is often based on statistical relations between various conditions and air pollution. This study aims to compare the performance of Multiple Linear Regression (MLR) and Multi-layer perceptron (MLP) for predicting SO2 concentration in the air of the Tehran. Different parameters namely meteorological parameters, urban traffic data, urban green space information, and time parameters were chosen for the prediction of SO2 daily concentration. Considering result, the correlation coefficient (R2), and root means square error (RMSE) of the MLR model are 0.708, and 6.025, respectively while these values for the MLP equal 0.9 and 0.42. According to the result of sensitivity analysis, the value of the one-day time delay, park indicator, season/year, and the total area parks were the main factors influencing SO2 concentration. MLP model suggested in this research could be applied to support, analysis, and improve predicting air pollution and air quality management. This study shows the importance of modeling and application of ANN in presenting management strategies to reduce urban pollution.
66 citations
TL;DR: The Selangor River was found to have higher sedimentary levels of PAHs and LABs during the wet season than in the dry season, which was primarily associated with the intensity of domestic wastewater discharge and high amounts of urban runoff washing the pollutants from the surrounding area.
64 citations