Displaying publications 101 - 120 of 390 in total

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  1. Predictors of handgrip strength among adults of a rural community in Malaysia
    Moy FM, Darus A, Hairi NN
    Asia Pac J Public Health, 2015 Mar;27(2):176-84.
    PMID: 24285778 DOI: 10.1177/1010539513510555
    Handgrip strength is useful for screening the nutritional status of adult population as it is strongly associated with physical disabilities and mortality. Therefore, we aimed to determine the predictors of handgrip strength among adults of a rural community in Malaysia using a cross-sectional study design with multistage sampling. All adults aged 30 years and older from 1250 households were invited to our study. Structured questionnaire on sociodemographic characteristics, medical history, occupation history, lifestyle practices, and measurements, including anthropometry and handgrip strength were taken. There were 2199 respondents with 55.2% females and majority were of Malay ethnicity. Their mean (standard deviation) age was 53.4 (13.2) years. The response rate for handgrip strength was 94.2%. Females had significantly lower handgrip strength than males (P < .05). In the multiple linear regression models, significant predictors of handgrip strength for males were age, height, job groups, and diabetes, while for females, the significant predictors were age, weight, height, and diabetes.
    Matched MeSH terms: Linear Models
  2. Predictive model for motorcycle accidents at three-legged priority junctions
    Harnen S, Umar RS, Wong SV, Wan Hashim WI
    Traffic Inj Prev, 2003 Dec;4(4):363-9.
    PMID: 14630586
    In conjunction with a nationwide motorcycle safety program, the provision of exclusive motorcycle lanes has been implemented to overcome link-motorcycle accidents along trunk roads in Malaysia. However, not much work has been done to address accidents at junctions involving motorcycles. This article presents the development of predictive model for motorcycle accidents at three-legged major-minor priority junctions of urban roads in Malaysia. The generalized linear modeling technique was used to develop the model. The final model reveals that motorcycle accidents are proportional to the power of traffic flow. An increase in nonmotorcycle and motorcycle flows entering the junctions is associated with an increase in motorcycle accidents. Nonmotorcycle flow on major roads had the highest effect on the probability of motorcycle accidents. Approach speed, lane width, number of lanes, shoulder width, and land use were found to be significant in explaining motorcycle accidents at the three-legged major-minor priority junctions. These findings should enable traffic engineers to specifically design appropriate junction treatment criteria for nonexclusive motorcycle lane facilities.
    Matched MeSH terms: Linear Models
  3. Fulltext Predictive equations for estimation of stature in Malaysian elderly people
    Shahar S, Pooy NS
    Asia Pac J Clin Nutr, 2003;12(1):80-4.
    PMID: 12737015
    Height is an important clinical indicator to derive body mass index (BMI), creatinine height index and also to estimate basal energy expenditure, basal metabolic rate and vital capacity through lung function. However, height measurement in the elderly may impose some difficulties and the reliability is doubtful. Equations estimating height from other anthropometric measures have been developed for Caucasians, but only one study has developed an equation (based on arm span only) for an Asian population. Therefore, a cross sectional study was conducted to develop equations using several anthropometric measurements for estimating stature in Malaysian elderly. A total of 100 adults (aged 30 to 49 y) and 100 elderly subjects (aged 60 to 86 y) from three major ethnic groups of Malays (52%), Chinese (38.5%) and Indians (9.5%) participated in this study. Anthropometric measurements included body weight, height, arm span, half arm span, demi span and knee height were carried out by trained nutritionists. Inter and intra observer errors and also % Coefficient Variation (%CV) were calculated for each anthropometric measurement. Equations to estimate stature were developed from the anthropometric measurements of arm span, demi span and knee height of adults using linear regression analysis according to sex. Elderly subjects were shorter and lighter compared to their younger counterparts. The %CV of anthropometric measurements in adults and elderly subjects ranged between 5 to 6%, with standing height having the lowest %CV. When the equations derived from adults were applied to elderly subjects, it was found that percentage difference between actual height and the estimated value ranged from 1.0 to 3.3%. However, the percentage difference between estimated height from the equations developed in this study compared to those derived from the equations of other populations ranged between 0.2 to 8.7%. In conclusion, standing height is an ideal technique for estimating the stature of individuals. However, in cases where its measurement is not possible or reliable, such as in elderly subjects, height can be estimated from proxy indicators of stature. In this study arm span showed the highest correlation with standing height, which is in agreement with other studies. It should be borne in mind that equations derived from taller statured populations (e.g. Caucasians) may be less accurate when applied to shorter statured populations.
    Matched MeSH terms: Linear Models
  4. Fulltext Predictive Equations for the Estimation of Basal Metabolic Rate of Malaysian Adolescents
    Malays J Nutr, 1999;5(1):-.
    MyJurnal
    A longitudinal study was conducted to relate basal metabolic rate (BMR) with growth during adolescence. Subjects comprise 70 boys and 69 girls aged between ten and thirteen years at the time of recruitment. Parameters studied include anthropometric measurements and BMR, which was measured by indirect calorimetry using the Deltatrac metabolic monitor. Measurements were carried out serially once every six months, with a total of 713 BMR data points collected over three years. Mean BMR of boys aged 11, 12, 13 and 14 years were 4.96 ± 0.63 MJ/day, 5.28 ± 0.71 MJ/day, 5.73 ± 0.68 MJ/day and 5.92 ± 0.63 MJ/day, respectively; while mean BMR of girls in the 10, 11, 12 and 13 year age groups were 4.96 ± 0.63 MJ/day, 4.85 ± 0.63 MJ/day, 5.05 ± 0.55 MJ/day and 4.94 ± 0.51 MJ/day, respectively. Comparison of measured BMR with BMR values predicted from the FAO/WHO/UNU (1985) equations shows that the predictive equations overestimated the BMR of Malaysian boys by 3% and that of girls by 5%. The Henry & Rees (1991) equations for populations in the tropics underestimated BMR of boys and girls by 1% and 2%, respectively. Linear regression equations to predict BMR based on body weight were derived according to sex and age groups. It is recommended that these predictive equations be used for the estimation of BMR of Malaysian adolescents.
    Matched MeSH terms: Linear Models
  5. Prediction of tuberculosis cases based on sociodemographic and environmental factors in gombak, Selangor, Malaysia: A comparative assessment of multiple linear regression and artificial neural network models
    Mohidem NA, Osman M, Muharam FM, Elias SM, Shaharudin R, Hashim Z
    Int J Mycobacteriol, 2021 12 18;10(4):442-456.
    PMID: 34916466 DOI: 10.4103/ijmy.ijmy_182_21
    Background: Early prediction of tuberculosis (TB) cases is very crucial for its prevention and control. This study aims to predict the number of TB cases in Gombak based on sociodemographic and environmental factors.

    Methods: The sociodemographic data of 3325 TB cases from January 2013 to December 2017 in Gombak district were collected from the MyTB web and TB Information System database. Environmental data were obtained from the Department of Environment, Malaysia; Department of Irrigation and Drainage, Malaysia; and Malaysian Metrological Department from July 2012 to December 2017. Multiple linear regression (MLR) and artificial neural network (ANN) were used to develop the prediction model of TB cases. The models that used sociodemographic variables as the input datasets were referred as MLR1 and ANN1, whereas environmental variables were represented as MLR2 and ANN2 and both sociodemographic and environmental variables together were indicated as MLR3 and ANN3.

    Results: The ANN was found to be superior to MLR with higher adjusted coefficient of determination (R2) values in predicting TB cases; the ranges were from 0.35 to 0.47 compared to 0.07 to 0.14, respectively. The best TB prediction model, that is, ANN3 was derived from nationality, residency, income status, CO, NO2, SO2, PM10, rainfall, temperature, and atmospheric pressure, with the highest adjusted R2 value of 0.47, errors below 6, and accuracies above 96%.

    Conclusions: It is envisaged that the application of the ANN algorithm based on both sociodemographic and environmental factors may enable a more accurate modeling for predicting TB cases.

    Matched MeSH terms: Linear Models
  6. Prediction of power generation and rotor angular speed of a small wind turbine equipped to a controllable duct using artificial neural network and multiple linear regression
    Siavash NK, Ghobadian B, Najafi G, Rohani A, Tavakoli T, Mahmoodi E, et al.
    Environ Res, 2021 05;196:110434.
    PMID: 33166537 DOI: 10.1016/j.envres.2020.110434
    Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.
    Matched MeSH terms: Linear Models
  7. Prediction of height increment using preoperative radiological parameters following selective thoracic fusion with alternate-level pedicle screw construct in Lenke 1 and 2 adolescent idiopathic scoliosis patients
    Keong KM, Aziz I, Yin Wei CC
    J Orthop Surg (Hong Kong), 2017 01 01;25(1):2309499016684431.
    PMID: 29185383 DOI: 10.1177/2309499016684431
    PURPOSE: This study aims to derive a formula to predict post-operative height increment in Lenke 1 and Lenke 2 adolescent idiopathic scoliosis (AIS) patients using preoperative radiological parameters.

    METHODS: This study involved 70 consecutive Lenke 1 and 2 AIS patients who underwent scoliosis correction with alternate-level pedicle screw instrumentation. Preoperative parameters that were measured included main thoracic (MT) Cobb angle, proximal thoracic (PT) Cobb angle, lumbar Cobb angle as well as thoracic kyphosis. Side-bending flexibility (SBF) and fulcrum-bending flexibility (FBF) were derived from the measurements. Preoperative height and post-operative height increment was measured by an independent observer using a standardized method.

    RESULTS: MT Cobb angle and FB Cobb angle were significant predictors ( p < 0.001) of height increment from multiple linear regression analysis ( R = 0.784, R2 = 0.615). PT Cobb angle, lumbar, SB Cobb angle, preoperative height and number of fused segment were not significant predictors for the height increment based on the multivariable analysis. Increase in post-operative height could be calculated by the formula: Increase in height (cm) = (0.09 × preoperative MT Cobb angle) - (0.04 x FB Cobb angle) - 0.5.

    CONCLUSION: The proposed formula of increase in height (cm) = (0.09 × preoperative MT Cobb angle) - (0.04 × FB Cobb angle) - 0.5 could predict post-operative height gain to within 5 mm accuracy in 51% of patients, within 10 mm in 70% and within 15 mm in 86% of patients.

    Matched MeSH terms: Linear Models
  8. Fulltext Prediction of damage cost of bronchitis due to haze in Malaysia
    Mohd Khairul Amri Kamarudin, Noorjima Abd Wahab, Khalid Abdul Rahim
    Malaysian Journal of Applied Sciences, 2018;1(2):1-8.
    MyJurnal
    Awareness of haze pollution and management increased in Southeast Asia since 1990. However, the
    focus on environmental management is decreasing especially in Malaysia due to the abundant
    resources and increased development pressure. The total health damage cost because of haze in the
    country became significantly high due to the long duration of haze events year by year. This paper
    discusses the health damage caused by bronchitis due to the haze events in Malaysia. The analysis
    shows positive coefficient of independent variables which indicates the positive relationship between
    dependent variable and independent variables. Multiple linear regression analysis shows that 45.3%
    variation in damage cost of bronchitis could be explained by FAI, GDPPC, and CO2.
    Matched MeSH terms: Linear Models
  9. Fulltext Prediction and explanation on adolescent aggression: a study protocol
    Fatimah Ahmad Fauzi, Nor Afiah Mohd Zulkefli, Anisah Baharom
    Malaysian Journal of Medicine and Health Sciences, 2020;16(1):106-114.
    MyJurnal
    Introduction: Adolescent aggression is an important public health concern with escalating prevalence of juvenile cases and violence among these age groups including robbery, homicide, and gang fights. The objectives of this study protocol are to determine the biopsychosocial predictors and explore the contextual factors of adolescent ag- gression among secondary school students in Hulu Langat. Methods: Explanatory mixed method study design will be used, consist of quantitative cross-sectional study followed by basic qualitative study. Proportionate population sampling among Form 4 secondary school students from selected public secondary schools in Hulu Langat will be executed. Questionnaires will be distributed to 481 students on aggression as the dependent variable, and several independent variables: demographic (ethnicity, family income), biological (sex, head injury, nutritional deficiency, breakfast skipping), psychological (attitude and normative beliefs, personality trait, emotional intelligence), and so- cial factors (family environment, single parent status, domestic violence, peer deviant affiliation, alcohol, smoking, substance abuse). Subsequently, participants with moderate to high aggression scores will be further explored on the contextual factors of adolescent aggression by in-depth interview. Multiple linear regression will be executed using SPSS to determine significant predictors whereas thematic analysis will be applied for qualitative data analysis on the context of adolescent aggression. Both findings will be further integrated and discussed to give comprehensive description on the phenomena. Conclusion: Better knowledge and understanding on adolescent aggression may generate new framework to drive more effective preventive strategies and unravel adolescent aggressive related Pub- lic Health problems.
    Matched MeSH terms: Linear Models
  10. Pharmacokinetics of phenytoin in routine clinic patients in Malaysia
    Ismail R, Rahman AF, Chand P
    J Clin Pharm Ther, 1994 Aug;19(4):245-8.
    PMID: 7989403
    We estimated individual and population Michaelis-Menten pharmacokinetic parameters for phenytoin (DPH) in epileptic patients attending our neurology clinic using the computer programme. OPT. Our results agreed well with literature values but were lower than those we obtained earlier in a smaller number of patients. The Km was independent of age, weight and sex but there was a weak, correlation between Vm and body weight. We conclude that the use of population Vm and Km in normograms could lead to errors in DPH dose estimations as they correlated very poorly with patient characteristics. OPT was easy to use and sufficiently accurate for deriving dose estimates in routine patients. Its use would enable practitioners to generate their patients' own parameters for use in individual dosage adjustments. The estimates can subsequently be updated as more data become available.
    Matched MeSH terms: Linear Models
  11. Permeability study of cancellous bone and its idealised structures
    Syahrom A, Abdul Kadir MR, Harun MN, Öchsner A
    Med Eng Phys, 2015 Jan;37(1):77-86.
    PMID: 25523865 DOI: 10.1016/j.medengphy.2014.11.001
    Artificial bone is a suitable alternative to autografts and allografts, however their use is still limited. Though there were numerous reports on their structural properties, permeability studies of artificial bones were comparably scarce. This study focused on the development of idealised, structured models of artificial cancellous bone and compared their permeability values with bone surface area and porosity. Cancellous bones from fresh bovine femur were extracted and cleaned following an established protocol. The samples were scanned using micro-computed tomography (μCT) and three-dimensional models of the cancellous bones were reconstructed for morphology study. Seven idealised and structured cancellous bone models were then developed and fabricated via rapid prototyping technique. A test-rig was developed and permeability tests were performed on the artificial and real cancellous bones. The results showed a linear correlation between the permeability and the porosity as well as the bone surface area. The plate-like idealised structure showed a similar value of permeability to the real cancellous bones.
    Matched MeSH terms: Linear Models
  12. Performance of univariate forecasting on seasonal diseases: the case of tuberculosis
    Permanasari AE, Rambli DR, Dominic PD
    Adv Exp Med Biol, 2011;696:171-9.
    PMID: 21431557 DOI: 10.1007/978-1-4419-7046-6_17
    The annual disease incident worldwide is desirable to be predicted for taking appropriate policy to prevent disease outbreak. This chapter considers the performance of different forecasting method to predict the future number of disease incidence, especially for seasonal disease. Six forecasting methods, namely linear regression, moving average, decomposition, Holt-Winter's, ARIMA, and artificial neural network (ANN), were used for disease forecasting on tuberculosis monthly data. The model derived met the requirement of time series with seasonality pattern and downward trend. The forecasting performance was compared using similar error measure in the base of the last 5 years forecast result. The findings indicate that ARIMA model was the most appropriate model since it obtained the less relatively error than the other model.
    Matched MeSH terms: Linear Models
  13. Fulltext Pengaruh ciri-ciri personal dan ciri-ciri program latihan terhadap prestasi belajar
    Siti Zuliana Md Z, Siti Fardaniah Abdul A
    Jurnal Psikologi Malaysia, 2018;32:12-24.
    The effectiveness of training is an important aspect in the development of training. After investing a lot of money to organize a training program, the organization often wants to know about the effectiveness of training given to trainee as well as how it can gives impact to the organization. This study was conducted to evaluate the effectiveness of training tested through learning performance among trainees that undergo a transition in the Perbadanan Hal Ehwal Bekas Angkatan Tentera (PERHEBAT). In this study, personal characteristics and training program characteristics acted as the independent variables in predicting learning performance. The instrument used in this study was adapted from Trainee Characteristic Scale, Training Program Characteristic Scale and Training Effectiveness Scale by Siti Fardaniah (2013) for personal characteristics, training program characteristics and learning performance. Questionnaires to measure the dimension of training transfer for the training characteristics was adapted from the Learning Transfer System Inventory (LTSI) by Holton et al. (2000). Data obtained were analyzed using Statistical Package for Social Sciences (SPSS) version 23. The multiple linear regression analysis indicated that extrinsic orientation, self-efficacy and organizational commitment have significant influence on learning performance. Relevance of training content and learning transfer design also affecedt learning performance. Findings in this study can be used as a reference to improve training effectiveness by focusing on personal characteristics and training characteristics conducted in PERHEBAT.
    Matched MeSH terms: Linear Models
  14. Penganggar MM bagi Model Linear dengan Titik Musnah dan Kecekapan yang Tinggi (A Robust MM Estimates for a Linear Model with High Breakdown Point and Efficiency)
    Habshah Binti Midi
    Sains Malaysiana, 1997;26.
    A robust MM estimates for the linear model is revisited. This estimates are defined by a three-stage procedures and posses the following properties: (i) they are highly efficient when the errors have a normal distribution and (ii) their breakdown-point is 0.5. A numerical examples are used to show that the MM estimates has a higher breakdown point and is more efficient than The RLS (Reweighted Least Squares Regression based on The Least Median Squares) estimates.
    Suatu penganggar teguh dalam model linear dinamakan Penganggar MM diperkenalkan kembali. Penganggar ini ditakrifkan menerusi pendekatan 3 peringkat dan mempunyai sifat sifat seperti berikut: i) kecekpan yang tinggi sekiranya ralat tertabur secara normal dan ii) titik musnah bersamaan 0.5. Contoh berangka telah digunakan ulituk menunjukkan bahawa penganggar ini mempunyai titik musnah yang tinggi dan lebih cekap daripada penganggar KDTB (Penganggar Kuasadua Terkecil Berpemberat berdasarkan Kaedah Kuasadua Terkecil).
    Matched MeSH terms: Linear Models
  15. Pemodelan dan analisis data penyerapan logam berat oleh sayuran berdaun terpilih
    Ahmad Mahir Razali, Khairiah Jusoh, Nor Asyikin A, Siti Adyani S, Wardatun Aathirah M, Maimon Abdullah, et al.
    Sains Malaysiana, 2008;37.
    Kajian yang dijalankan adalah berkaitan dengan penentuan model yang sesuai serta analisis data penyerapan logam berat oleh sayuran berdaun yang terpilih iaitu kangkung (Ipomea aquatica), sawi bunga (Brassica chinensis var parachinensis), bayam (Amaranthus oleraceus L) dan sawi putih (Brassica chinensis L.). Kajian ini bertujuan untuk menentukan dan membandingkan kandungan serta corak pengambilan logam berat yang diserap oleh sayuran dan juga bahagian-bahagiannya yang meliputi daun, batang dan akar. Penentuan model yang dibuat bertujuan bagi melihat corak penyerapan logam berat oleh sayuran atau bahagian sayuran tertentu. Logam berat yang dikaji terdiri daripada kadmium , kromium, kuprum, ferum , mangan, plumbum dan zink. Plot serakan digunakan bagi menentukan corak pengambilan logam berat dalam sayuran dan bahagian-bahagiannya. Selain itu ujian Kruskal-Wallis digunakan bagi membuat perbandingan median di antara logam berat yang diserap oleh sayuran yang dikaji. Nilai khi-kuasa dua dan juga nilai-p digunakan bagi menentukan sama ada sesuatu logam berat yang diserap itu berkait rapat dengan jenis sayuran secara signifikan. Secara umum bolehlah dikatakan bahawa logam Fe, Mn dan Zn adalah dominan dalam semua bahagian sayuran yang dikaji. Selain itu, melalui ujian Kruskal-Wallis didapati penyerapan kesemua logam berat pada setiap bahagian sayuran adalah berbeza secara signifikan. Penyuaian model regresi linear, kuadratik, kubik atau eksponen telah dilakukan terhadap data ini dan didapati kebanyakan data dapat disuaikan dengan baik oleh model kuadratik dan kubik berdasarkan nilai pekali penentuan (R2).
    Matched MeSH terms: Linear Models
  16. Passive smoking: directions for health education among Malaysian college students
    Kurtz ME, Johnson SM, Ross-Lee B
    Int J Health Serv, 1992;22(3):555-65.
    PMID: 1644515 DOI: 10.2190/JFRP-E61C-Y7R7-G7J8
    This study investigated knowledge, attitudes, and preventive efforts of Malaysian college students regarding health risks associated with passive smoking, as well as possible directions for intervention and health education programs. Students responded anonymously to a structured written questionnaire. Statistical analyses were conducted to examine (1) differences in knowledge, attitudes, and preventive efforts between smokers and nonsmokers and between men and women; (2) the relationship between smoking by parents, siblings, and friends, and students' knowledge, attitudes, and preventive efforts; and (3) relationships between knowledge, attitudes, and preventive efforts. Peer groups and siblings had a substantial influence on students' attitudes toward passive smoking and their preventive efforts when exposed to passive smoke. A regression analysis revealed a statistically significant linear dependence of preventive efforts on knowledge and attitudes, with the attitude component playing the dominant role. This research suggests that educational efforts on passive smoking, directed toward young college students in developing countries such as Malaysia, should concentrate heavily on changing attitudes and reducing the effects of peer group and sibling influences.
    Study site: Institut Teknologi Mara, Shah Alam; Stamford College, Petaling Jaya; Selangor, Malaysia
    Matched MeSH terms: Linear Models
  17. Fulltext Paraspinal back muscles in asymptomatic volunteers: quantitative and qualitative analysis using computed tomography (CT) and magnetic resonance imaging (MRI)
    Khil EK, Choi JA, Hwang E, Sidek S, Choi I
    BMC Musculoskelet Disord, 2020 Jun 26;21(1):403.
    PMID: 32590960 DOI: 10.1186/s12891-020-03432-w
    BACKGROUND: To evaluate paraspinal back muscles of asymptomatic subjects using qualitative and quantitative analysis on CT and MRI and correlate the results with demographic data.

    METHODS: Twenty-nine asymptomatic subjects were enrolled prospectively (age: mean 34.31, range 23-50; 14 men, 15 women) from August 2016 to April 2017. Qualitative analysis of muscles was done using Goutallier's system on CT and MRI. Quantitative analysis entailed cross sectional area (CSA) on CT and MRI, Hounsfield unit (HU) on CT, fat fraction using two-point Dixon technique on MRI. Three readers independently analyzed the images; intra- and inter-observer agreements were measured. Linear regression and Spearman's analyses were used for correlation with demographic data.

    RESULTS: CSA values were significantly higher in men (p 

    Matched MeSH terms: Linear Models
  18. Fulltext Paraoxonase 1 activity as a predictor of cardiovascular disease in type 2 diabetes
    Poh R, Muniandy S
    Southeast Asian J. Trop. Med. Public Health, 2010 Sep;41(5):1231-46.
    PMID: 21073045
    The role of paraoxonase 1 in cardiovascular disease complications in type 2 diabetes mellitus is not fully understood. We studied paraoxonase activity towards paraoxon in 188 non-diabetic and 140 diabetic subjects using general linear models and univariate analysis. Adjusting for age revealed a reduction in activity towards paraoxon was associated with a significant increase in risk (p = 0.023) for cardiovascular disease complications in diabetic patients. Multivariate analysis of two plasma measures of paraoxonase activity using paraoxon and diazoxon also showed reduced paraoxonase activity towards paraoxon was associated with a significant increase in risk (p = 0.045) for cardiovascular disease complications in diabetic patients. These analyses showed that a reduced paraoxonase activity towards paraoxon was associated with ethnicity. Based on multivariate analysis, subjects of Malay ethnic origin have significantly higher than expected activity (p = 0.008, compared to Indians), towards paraoxon than subjects of Chinese origin who in turn had higher than expected paraoxonase activity (p = 0.028, compared to Indians) Indian subjects.
    Matched MeSH terms: Linear Models
  19. Parameters optimization of rice husk ash (RHA)/CaO/CeO2 sorbent for predicting SO2/NO sorption capacity using response surface and neural network models
    Dahlan I, Ahmad Z, Fadly M, Lee KT, Kamaruddin AH, Mohamed AR
    J Hazard Mater, 2010 Jun 15;178(1-3):249-57.
    PMID: 20137857 DOI: 10.1016/j.jhazmat.2010.01.070
    In this work, the application of response surface and neural network models in predicting and optimizing the preparation variables of RHA/CaO/CeO(2) sorbent towards SO(2)/NO sorption capacity was investigated. The sorbents were prepared according to central composite design (CCD) with four independent variables (i.e. hydration period, RHA/CaO ratio, CeO(2) loading and the use of RHA(raw) or pretreated RHA(600 degrees C) as the starting material). Among all the variables studied, the amount of CeO(2) loading had the largest effect. The response surface models developed from CCD was effective in providing a highly accurate prediction for SO(2) and NO sorption capacities within the range of the sorbent preparation variables studied. The prediction of CCD experiment was verified by neural network models which gave almost similar results to those determined by response surface models. The response surface models together with neural network models were then successfully used to locate and validate the optimum hydration process variables for maximizing the SO(2)/NO sorption capacities. Through this optimization process, it was found that maximum SO(2) and NO sorption capacities of 44.34 and 3.51 mg/g, respectively could be obtained by using RHA/CaO/CeO(2) sorbents prepared from RHA(raw) with hydration period of 12h, RHA/CaO ratio of 2.33 and CeO(2) loading of 8.95%.
    Matched MeSH terms: Linear Models
  20. Outlier Detection in a Circular Regression Model
    Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin
    Sains Malaysiana, 2015;44:1027-1032.
    Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parameters. Hence, we intend to identify outliers in the model by looking at the effect of the outliers on the covariance matrix. The method resembles closely the COVRATIO statistic for the case of linear regression problem. The corresponding critical values and the performance of the outlier detection procedure are studied via simulations. For illustration, we apply the procedure on the wind data set.
    Matched MeSH terms: Linear Models
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