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Dive into the research topics where Mohamed Noor Hasan is active.

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Featured researches published by Mohamed Noor Hasan.


Talanta | 2013

Multi-walled carbon nanotube-impregnated agarose film microextraction of polycyclic aromatic hydrocarbons in green tea beverage

Saw Hong Loh; Mohd Marsin Sanagi; Wan Aini Wan Ibrahim; Mohamed Noor Hasan

A new microextraction procedure termed multi-walled carbon nanotube-impregnated agarose film microextraction (MWCNT-AFME) has been developed. The method utilized multi-walled carbon nanotubes (MWCNTs) immobilized in agarose film to serve as adsorbent in solid phase microextraction (SPME). The film was prepared by mixing the MWCNTs in agarose solution and drying the mixture in oven. Extraction of selected polycyclic aromatic hydrocarbons was performed by inserting a needle through circular MWCNT-impregnated agarose films (5 mm diameter) and the assembly was dipped into an agitated sample solution prior to micro high performance liquid chromatography-ultraviolet analysis. Back extraction was then performed using ultrasonication of the films in 100 μL of solvent. The film was discarded after single use, thus avoiding any analyte carry-over effect. Due to the mesoporous nature of the agarose film, the MWCNTs were immobilized easily within the film and thus allowing for close contact between adsorbent and analytes. Under the optimized extraction conditions, the technique achieved trace LODs in the range of 0.1 to 50 ng L(-1) for the targeted analytes, namely fluoranthene, phenanthrene and benzo[a]pyrene. The method was successfully applied to the analysis of spiked green tea beverage samples with good relative recoveries in the range of 91.1 to 107.2%. The results supported the feasibility of agarose to serve as adsorbent holder in SPME which then minimizes the consumption of chemicals and disposal cost of organic wastes.


Journal of Chromatography A | 2013

Solvent-impregnated agarose gel liquid phase microextraction of polycyclic aromatic hydrocarbons in water

Saw Hong Loh; Mohd Marsin Sanagi; Wan Aini Wan Ibrahim; Mohamed Noor Hasan

A new microextraction procedure termed agarose gel liquid phase microextraction (AG-LPME) combined with gas chromatography-mass spectrometry (GC-MS) was developed for the determination of selected polycyclic aromatic hydrocarbons (PAHs) in water. The technique utilized an agarose gel disc impregnated with the acceptor phase (1-octanol). The extraction procedure was performed by allowing the solvent-impregnated agarose gel disc to tumble freely in the stirred sample solution. After extraction, the agarose gel disc was removed and subjected to centrifugation to disrupt its framework and to release the impregnated solvent, which was subsequently withdrawn and injected into the GC-MS for analysis. Under optimized extraction conditions, the new method offered high enrichment factors (89-177), trace level LODs (9-14ngL(-1)) and efficient extraction with good relative recoveries in the range of 93.3-108.2% for spiked drinking water samples. AG-LPME did not exhibit any problems related to solvent dissolution, and it provided high extraction efficiencies that were comparable to those of hollow fiber liquid phase microextraction (HF-LPME) and significantly higher than those of agarose film liquid phase microextraction (AF-LPME). This technique employed a microextraction format and utilized an environmentally compatible solvent holder that supported the green chemistry concept.


Journal of Chromatography A | 2012

Agarose film liquid phase microextraction combined with gas chromatography-mass spectrometry for the determination of polycyclic aromatic hydrocarbons in water.

Mohd Marsin Sanagi; Saw Hong Loh; Wan Aini Wan Ibrahim; Mohamed Noor Hasan

Agarose film liquid phase microextraction (AF-LPME) procedure for the extraction and preconcentration of polycyclic aromatic hydrocarbons (PAHs) in water has been investigated. Agarose film was used for the first time as an interface between donor and acceptor phases in liquid phase microextraction which allowed for selective extraction of the analytes prior to gas chromatography-mass spectrometry. Using 1-octanol as acceptor phase, high enrichment factors in the range of 57-106 for the targeted analytes (fluorene, phenanthrene, fluoranthene and pyrene) were achieved. Under the optimum extraction conditions, the method showed good linearity in the range of 0.1-200 μgL(-1), good correlation coefficients in the range of 0.9963-0.9999, acceptable reproducibility (RSD 6.1-9.2%, n=3), low limits of detection (0.01-0.04 μgL(-1)) and satisfactory relative recoveries (92.9-104.7%). As the AF-LPME device was non-expensive, reuse or recycle of the film was not required, thus eliminating the possibility of analytes carry-over between runs. The AF-LPME technique is environment-friendly and compatible with the green chemistry concept as agarose is biodegradable polysaccharide extracted from seaweed and the procedure requires small volume of organic solvent and generates little waste. The validated method was successfully applied to the analysis of the four analytes in river water samples.


Journal of Chromatographic Science | 2013

Determination of Polycyclic Aromatic Hydrocarbons in Fresh Milk by Hollow Fiber Liquid-Phase Microextraction–Gas Chromatography Mass Spectrometry

Mohd Marsin Sanagi; Saw Hong Loh; Wan Aini Wan Ibrahim; Mohamed Noor Hasan; Hassan Y. Aboul Enein

In this work, a two-phase hollow fiber liquid-phase microextraction (HF-LPME) method combined with gas chromatography-mass spectrometry (GC-MS) is developed to provide a rapid, selective and sensitive analytical method to determine polycyclic aromatic hydrocarbons (PAHs) in fresh milk. The standard addition method is used to construct calibration curves and to determine the residue levels for the target analytes, fluorene, phenanthrene, fluoranthene, pyrene and benzo[a]pyrene, thus eliminating sample pre-treatment steps such as pH adjustment. The HF-LPME method shows dynamic linearity from 5 to 500 µg/L for all target analytes with R(2) ranging from 0.9978 to 0.9999. Under optimized conditions, the established detection limits range from 0.07 to 1.4 µg/L based on a signal-to-noise ratio of 3:1. Average relative recoveries for the determination of PAHs studied at 100 µg/L spiking levels are in the range of 85 to 110%. The relative recoveries are slightly higher than those obtained by conventional solvent extraction, which requires saponification steps for fluorene and phenanthrene, which are more volatile and heat sensitive. The HF-LPME method proves to be simple and rapid, and requires minimal amounts of organic solvent that supports green analysis.


international conference on computer communications | 2015

Comparison of PLS Discriminant Analysis and supervised SOMs for Blood Brain Barrier activity

Mohd Zuli Jaafar; Marina Mokhtar; Mohamed Noor Hasan; Nor Aziyah Bakhari; Richard G. Brereton

In the development of drugs compounds suitable for human being, many experiments have to be conducted to ensure drugs safe consumption and generally takes almost 10 to 12 years for a particular drugs to enter the market from laboratory. Therefore, the pattern recognition in QSAR is significant for analyzing the data and developing several necessary models, so that only novel drugs candidate will be synthesized. There are three important aspects for the classification of BBB activity in this work, (1) variable reduction by PCA (2) variable selection and class separation with comparison of three methods such as T-Statistics, Partial Least Squares Regression Coefficient (PLSRC) and newly invented Self Organising Maps Discriminatory Index (SOMDI). and (3) classification, a comparison of linear (PLSDA) and non linear (SuSOMs) methods. The number of PCA component determined by LOO cross-validations is seven. Based on PCA score, the variables selected by T-Statistics and SOMDI are more selective and can provide better separation for BBB activity than PLSRC. Models performances and validations, built through PLSDA and SOMs show that the consensually selected 7 descriptors in this work by using SOMDI, T-statistics and PLSRC were able to classify BBB penetration and non-penetration compounds.


international colloquium on signal processing and its applications | 2014

Signal processing strategies in FT-NIR and FTIR spectra of palm oils

Nor Fazila Rasaruddin; Mohamed Noor Hasan; Mas Ezatul Nadia Mohd Ruah; Sim Siong Fong; Mohd Zuli Jaafar

In the palm oil industry, iodine value (IV) has become an important parameter in quality control that measures the degree of unsaturation of the oils. However, it is difficult to obtain the IV chemically. In other hand, the use of instrumental analysis in IV determination accurately needs suitable data pre-processing. In this study, we proposed the strategy for pre-processing the FT-NIR and FTIR spectra data in analyzing the IV of non-fried and fried palm oils. The utility and effectiveness of four data pre-processing which are column standardization, mean centre and combination of row scaling with column standardization and mean centre were applied. The effect of data splitting methods which are duplex and kenstone was also investigated in the Partial Least Squares (PLS) regression model of palm oils. From the result, the use of different data pre-processing provides different quality of prediction model. Either the application of the row scaling and column scaling individually or combination of both methods may improve the quality of the model. It is concluded that the data pre-processing is context dependent which is depend on the nature of the dataset and there can be no single method for general use.


Malaysian Journal of Fundamental and Applied Sciences | 2014

Quantitative structure-activity relationship for antimalarial activity of artemisinin

Rosmahaida Jamaludin; Mohamed Noor Hasan

The increase in resistance to older drugs and the emergence of new types of infection have created an urgent need for discovery and development of new compounds with antimalarial activity. Quantitative-Structure Activity Relationship (QSAR) methodology has been performed to develop models that correlate antimalarial activity of artemisinin analogs and their molecular structures. In this study, the data set consisted of 197 compounds with their activities expressed as log RA (relative activity). These compounds were randomly divided into training set (n=157) and test set (n=40). The initial stage of the study was the generation of a series of descriptors from three-dimensional representations of the compounds in the data set. Several types of descriptors which include topological, connectivity indices, geometrical, physical properties and charge descriptors have been generated. The number of descriptors was then reduced to a set of relevant descriptors by performing a systematic variable selection procedure which includes zero test, pairwise correlation analysis and genetic algorithm (GA). Several models were developed using different combinations of modelling techniques such as multiple linear regression (MLR) and partial least square (PLS) regression. Statistical significance of the final model was characterized by correlation coefficient, r2 and root-mean-square error calibration, RMSEC. The results obtained were comparable to those from previous study on the same data set with r2 values greater than 0.8. Both internal and external validations were carried out to verify that the models have good stability, robustness and predictive ability. The cross-validated regression coefficient (r2 cv) and prediction regression coefficient (r2 test) for the external test set were consistently greater than 0.7. The QSAR models developed in this study should facilitate the search for new compounds with antimalarial activity.


Chromatographia | 2008

Rapid estimation of octanol-water partition coefficient for triazole fungicides by MEKC with sodium deoxycholate as surfactant

Wan Aini Wan Ibrahim; Dadan Hermawan; Mohamed Noor Hasan; Hassan Y. Aboul Enein; Mohd Marsin Sanagi


Educational Technology & Society | 2017

Review of mobile learning trends 2010-2015: A meta-analysis

Ken Nee Chee; Noraffandy Yahaya; Nor Hasniza Ibrahim; Mohamed Noor Hasan


Jurnal Teknologi | 2015

Theoretical and experimental studies of corrosion inhibition of thiohene-2-ethylamine on mild steel in acid media

Bishir Usman; Hasmerya Maarof; Hassan H. Abdallah; Rosmahaida Jamaludin; Mohamed Noor Hasan; Madzlan Aziz

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Mohd Marsin Sanagi

Universiti Teknologi Malaysia

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Wan Aini Wan Ibrahim

Universiti Teknologi Malaysia

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Nor Hasniza Ibrahim

Universiti Teknologi Malaysia

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Noraffandy Yahaya

Universiti Teknologi Malaysia

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Saw Hong Loh

Universiti Malaysia Terengganu

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Rosmahaida Jamaludin

Universiti Teknologi Malaysia

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Dadan Hermawan

Universiti Teknologi Malaysia

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Hasmerya Maarof

Universiti Teknologi Malaysia

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