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737 results on '"Othman, Nor"'

361. ISOTHERM STUDIES OF PYROGALLOL-IMPRINTED POLYMERS VIA PRECIPITATION POLYMERIZATION.

Author

Othman, Nor Amira, Yusof, Noor Fadilah, Daik, Rusli, and Mehamod, Faizatul Shimal

Subjects
ISOTHERMAL processes, PYROGALLOLS, POLYMERIZATION
Abstract

Molecularly imprinted polymers (MIPs) have been the most convenient and selected methods in detection and extraction for many types of specific targets in various fields. MIPs were prepared by mixing template molecule with functional monomer in the presence of cross-linker, solvent and initiator. The selectivity of MIPs is strongly influenced by the types of functional monomer, solvent and polymerization process used. Pyrogallol-imprinted polymer (Py-IP) and nonimprinted polymer (NIP) were synthesized via precipitation polymerization using 4- vinylpyridine (4-VP), divinylbenzene (DVB) and azobisisobutyronitrile (AIBN) as functional monomer, cross-linker and initiator, respectively. Pyrogallol (Py) was used as a target molecule. The synthesized polymers were characterized by Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and UV-Visible Spectroscopy (UV-Vis). In this study, adsorption capacity was measured by the dosage effect, contact time and selectivity study. Results showed that maximum adsorption capacity by Py-IP is above 50%. The Selectivity study shows that k' is >1, which indicates that Py-IP has a good selectivity towards pyrogallol. Therefore, it has a good potential to be used as an adsorbent. [ABSTRACT FROM AUTHOR]

Published
2017
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362. Application Of Artificial Neural Networks in the Classification of Cervical Cells Based on the Bethesda System

Author

Mat Isa, Nor Ashidi, Mashor, Mohd Yusoff, Othman, Nor Hayati, Zamli, Kamal Zuhairi, Mat Isa, Nor Ashidi, Mashor, Mohd Yusoff, Othman, Nor Hayati, and Zamli, Kamal Zuhairi

Abstract

Neural networks have been used in the medical field in various applications such as medical imaging processing and disease diagnostic technique. In this paper, we investigate the capability of two conventional neural networks as an intelligent diagnostic system. In particular, the radial basis function (RBF) and multilayered perceptron (MLP) neural networks were used to classify the type of cervical cancer in its early stage. The study is divided into two stages. In the first stage, we investigate the applicability of neural networks to classify cervical cells into normal and abnormal cells. In the second stage, we classify cervical cells abnormality into three classes based on The Bethesda Classification System; normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). Diagnosis obtained using RBF and MLP neural networks gave promising results. Nevertheless, classification of abnormal cells into LSIL and HSIL yielded unsatisfactory results. In order to address this problem, this study adopted two hybrid neural networks namely hybrid radial basis function (HRBF) and hybrid multilayered perceptron (HMLP) networks in order to improve the performances of conventional neural networks. The overall diagnostic performance was measured using accuracy, sensitivity, specificity, false negative and false positive analysis by comparing to the diagnoses made by pathologists. This study indicates that HMLP network produces better overall diagnostic performance than the MLP, RBF and HRBF networks.

Published
2006

390. Nuclear Power Plant Siting Guideline for Peninsular Malaysia

Author

Ahmad, Ir. Mohd Noh, primary, Abbas, Ahmad Rosly, additional, Ismail, Mohd Nadzari, additional, Yapandi, Md Fauzan Kamal Mohd, additional, Mohd Siam, Mohd Fadzil, additional, Setu, Anita, additional, Othman, Nor Azura, additional, Saleh, Syafiqa Mohd, additional, Su’ud, Zaki, additional, and Waris, A., additional

Published
2010
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398. Effect of Influenza Vaccination on Acute Respiratory Symptoms in Malaysian Hajj Pilgrims.

Author

Hasan, Habsah, Deris, Zakuan, Sulaiman, Siti, Abdul Wahab, Mohd, Naing, Nyi, Ab Rahman, Zulkefle, and Othman, Nor

Subjects
RESPIRATORY disease prevention, ANALYSIS of variance, CHI-squared test, FISHER exact test, IMMUNIZATION, INFLUENZA vaccines, ISLAM, NOMADS, SCIENTIFIC observation, RESEARCH funding, RESPIRATORY diseases, REPEATED measures design, DATA analysis software, DESCRIPTIVE statistics, SYMPTOMS
Abstract

Respiratory illness were a major problem and caused high hospital admission during hajj seasons. One of the contributing cause to this illness is infection. Various measures had been implemented to reduce respiratory infections. The aim on the study is to determine the effect of influenza vaccination against acute respiratory illness among Malaysian Hajj pilgrims. This is an observational cohort study. Influenza vaccination was given to pilgrims at least 2 weeks prior to departure. The occurrence of symptoms for respiratory illness such as cough, fever, sore throat and runny nose was monitored daily for 6 weeks during pilgrimage using a health diary. A total of 65 vaccinated hajj pilgrims and 41 controls were analyzed. There was no significant difference in pattern of occurrence of symptoms of respiratory illness by duration of pilgrimage as well as the number of symptoms between both groups. Hajj pilgrims have frequent respiratory symptoms. We were unable to document benefit from influenza vaccination, but our study was limited by a small sample size and lack of laboratory testing for influenza. [ABSTRACT FROM AUTHOR]

Published
2015
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