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Effect of malting conditions and quality characteristics of malt and roasted malt extract from 'acha' grains (Digitaria exilis Stapf)

Lasekan O, Salva JT, Abbas K

J Sci Food Agric, 2010 Apr 15;90(5):850-60.
PMID: 20355122 DOI: 10.1002/jsfa.3895

Considering the importance of malting and roasting on the quality of 'acha' beverages, a study was conducted to find optimum conditions for malting and the production of a high-quality roasted extract that could be used for an 'acha' beverage.

Matched MeSH terms: Models, Statistical
Fulltext Non-Mixture Cure Model Estimation in Bladder Cancer Patients: A Novel Approach with Exponentiated Weibull Exponential Distribution

Omer ME, Mustafa M, Ali N, Abd Rahman NH

Asian Pac J Cancer Prev, 2023 Dec 01;24(12):4167-4177.
PMID: 38156852 DOI: 10.31557/APJCP.2023.24.12.4167

OBJECTIVE: Cure models are frequently used in survival analysis to account for a cured fraction in the data. When there is a cure rate present, researchers often prefer cure models over parametric models to analyse the survival data. These models enable the ability to define the probability distribution of survival durations for patients who are at risk. Various distributions can be considered for the survival times, such as Exponentiated Weibull Exponential (EWE), Exponential Exponential (EE), Weibull and lognormal distribution. The objective of this research is to choose the most appropriate distribution that accurately represents the survival times of patients who have not been cured. This will be accomplished by comparing various non-mixture cure models that are based on the EWE distribution with its sub-distributions, and distributions distinct from those belonging to the EWE distribution family.
MATERIAL AND METHODS: A sample of 85 patients diagnosed with superficial bladder tumours was selected to be used in fitting the non-mixture cure model. In order to estimate the parameters of the suggested model, which takes into account the presence of a cure rate, censored data, and covariates, we utilized the maximum likelihood estimation technique using R software version 3.5.7.
RESULT: Upon conducting a comparison of various parametric models fitted to the data, both with and without considering the cure fraction and without incorporating any predictors, the EE distribution yields the lowest AIC, BIC, and HQIC values among all the distributions considered in this study, (1191.921/1198.502, 1201.692/1203.387, 1195.851/1200.467). Furthermore, when considering a non-mixture cure model utilizing the EE distribution along with covariates, an estimated ratio was obtained between the probabilities of being cured for placebo and thiotepa groups (and its 95% confidence intervals) were 0.76130 (0.13914, 6.81863).
CONCLUSION: The findings of this study indicate that EE distribution is the optimal selection for determining the duration of survival in individuals diagnosed with bladder cancer.

Matched MeSH terms: Models, Statistical*
Performance of two-samples pseudo-median procedure

Nor Aishah Ahad, Sharipah Soaad Syed Yahaya, Abdul Rahman Othman

Sains Malaysiana, 2012;41:1149-1154.

This article investigates the performance of two-sample pseudo-median based procedure in testing differences between groups. The procedure is a modification of the one-sample Wilcoxon procedure using the pseudo-median of differences between group values as the central measure of location. The test was conducted on two groups with moderate sample
sizes of symmetric and asymmetric distributions. The performance of the procedure was measured in terms of Type I error and power rates computed via Monte Carlo methods. The performance of the procedure was compared against the t-test and Mann-Whitney-Wilcoxon test. The findings from this study revealed that the pseudo-median procedure performed very
well in controlling Type I error rates close to the nominal value. The pseudo-median procedure outperformed the MannWhitney-Wilcoxon test and is comparable to the t-test in controlling Type I error and maintaining adequate power.

Matched MeSH terms: Models, Statistical
Fulltext Development of an edible coating based on chitosan-glycerol to delay ‘Berangan’ banana (Musa sapientum cv. Berangan) ripening process

Jafarizadeh Malmiri, H., Osman, A., Tan, C.P., Abdul Rahman, R.

International Food Research Journal, 2011;18(3):-.
MyJurnal

Response surface methodology (RSM) was used to optimize the concentrations of chitosan and glycerol for coating Berangan banana (Musa sapientum cv. Berangan). The effects of main edible coating components, chitosan (0.5-2.5%, w/w) and glycerol (0-2%, w/w) on weight loss, firmness, total colour difference, total soluble solids content (TSS) and titratable acidity (TA) of coated banana were studied during 10 days of storage at 26±2°C and 40-50% relative humidity. Results showed that the experimental data could be adequately fitted into a second-order polynomial model with coefficient of determination (R 2 ) ranging from 0.745 to 0.930 for all the variables studied. In general, the chitosan concentration appeared to be the most significant (P< 0.1) factor influencing all variables except for TSS. The optimum concentration of chitosan and glycerol were predicted to be 2.02% and 0.18%, respectively. Statistical assessment showed insignificant difference between experimental and predicted values.

Matched MeSH terms: Models, Statistical
Lead exposure among Malaysian school children using delta-aminolevulinic acid as an indicator

Ming LO, Surif S, Abdullah A

Sci Total Environ, 1997 Jan 30;193(3):207-13.
PMID: 9092077

A study on lead exposure among school children aged between 7 and 12 years from Kajang and Sepang in the state of Selangor, Malaysia was carried out using delta-aminolevulinic acid (delta-ALA) levels in the urine as an index. The delta-ALA levels in urine were linked to variables which could contribute to lead exposure. Out of 1628 school children studied [Kajang (43.5%) and Sepang (56.5%)], only 194 subjects (16 and 8.8% from Kajang and Sepang, respectively) had urinary delta-ALA levels between 0.6 and 2.0 mg/100 ml. However, chi 2 analysis demonstrated significant association between delta-ALA of this group to some of the variables. The strongest association was found in the habit of biting fingernails (P < 0.025). Other statistically significant correlations were found between delta-ALA and father's occupation (P < 0.05) and the amount of time spent playing in the field (P < 0.01). Generally, this study indicates that school children in Kajang and Sepang are still relatively safe from excessively high lead exposure. However, a more sensitive indicator, which is based on a lower tolerable lead limits, such as lead in blood, are necessary to affirm this finding.

Matched MeSH terms: Models, Statistical
Fulltext Transverse cerebellar diameter as a sonographic parameter for estimating gestational age: an experience from Yemeni population

Muneera A. S. Yahya, Husni A. Al- Goshae, Hameed M. Aklan, Maha Abdul-aziz, Abdullah A. Al-Mikhlafy

Malaysian Journal of Medicine and Health Sciences, 2020;16(107):23-27.
MyJurnal

Introduction: Estimation of gestational age (GA) is clinically crucial for managing pregnancy and assessing the foetal anatomy, growth and development. Transverse cerebellar diameter (TCD) has been reported as an accurate tool for dating the pregnancy. This study aimed to determine the accuracy of foetal TCD for dating the pregnancy and to con- struct a reference chart for GA of Yemeni foetuses. Methods: We conducted this prospective cross-sectional study among 400 Yemeni pregnant women between 18 and 40 weeks of gestation provided that they were with known last menstrual period and singleton normal pregnancies. Sonographic TCDs were measured for each foetus. The mean TCD was measured for gestational weeks separately, and a polynomial regression model was then used to predict the GA by TCD. Results: There was a robust correlation between GA and TCD (r = 0.995, p

Matched MeSH terms: Models, Statistical
A proposed hierarchical fuzzy inference system for the diagnosis of arthritic diseases

Lim CK, Yew KM, Ng KH, Abdullah BJ

Australas Phys Eng Sci Med, 2002 Sep;25(3):144-50.
PMID: 12416592 DOI: 10.1007/BF03178776

Development of computer-based medical inference systems is always confronted with some difficulties. In this paper, difficulties of designing an inference system for the diagnosis of arthritic diseases are described, including variations of disease manifestations under various situations and conditions. Furthermore, the need for a huge knowledge base would result in low efficiency of the inference system. We proposed a hierarchical model of the fuzzy inference system as a possible solution. With such a model, the diagnostic process is divided into two levels. The first level of the diagnosis reduces the scope of diagnosis to be processed by the second level. This will reduce the amount of input and mapping for the whole diagnostic process. Fuzzy relational theory is the core of this system and it is used in both levels to improve the accuracy.

Matched MeSH terms: Models, Statistical
Fulltext Determining optimum conditions for lipase-catalyzed synthesis of triethanolamine (TEA)-based esterquat cationic surfactant by a Taguchi robust design method

Masoumi HR, Kassim A, Basri M, Abdullah DK

Molecules, 2011 Jun 03;16(6):4672-80.
PMID: 21642941 DOI: 10.3390/molecules16064672

A Taguchi robust design method with an L₉ orthogonal array was implemented to optimize experimental conditions for the biosynthesis of triethanolamine (TEA)-based esterquat cationic surfactants using an enzymatic reaction method. The esterification reaction conversion% was considered as the response. Enzyme amount, reaction time, reaction temperature and molar ratio of substrates, [oleic acid: triethanolamine (OA:TEA)] were chosen as main parameters. As a result of the Taguchi analysis in this study, the molar ratio of substrates was found to be the most influential parameter on the esterification reaction conversion%. The amount of enzyme in the reaction had also a significant effect on reaction conversion%.

Matched MeSH terms: Models, Statistical
Heavy metals concentration relationship with Perna viridis physical properties in Mengkabong Lagoon, Sabah, Malaysia

Abdullah N, Tair R, Abdullah MH

Pak J Biol Sci, 2014 Jan 01;17(1):62-7.
PMID: 24783779

Perna viridis (P. viridis) has been identified as a good biological indicator in identifying environmental pollution, especially when there are various types of Heavy Metals Accumulations (HMA) inside its tissue. Based on the potential of P. viridis to accumulate heavy metals and the data on its physical properties, this study proffers to determine the relationships between both properties. The similarities of the physical properties are used to mathematical model their relationships, which included the size (length, width, height) and weight (wet and dry) of P. viridis, whilst the heavy metals are focused on concentrations of Pb, Cu, Cr, Cd and Zn. The concentrations of metal elements are detected by using Flame Atomic Adsorption Spectrometry. Results show that the mean concentration of Pb, Cu, Cr, Cd, Zn, length, width, height, wet weight and dry weight are: 1.12 +/- 1.00, 2.36 +/- 1.65, 2.12 +/- 2.74, 0.44 +/- 0.41 and 16.52 +/- 10.64 mg kg(-1) (dry weight), 105.08 +/- 14.35, 41.64 +/- 4.64, 28.75 +/- 3.92 mm, 14.56 +/- 3.30 and 2.37 +/- 0.86 g, respectively. It is also found out that the relationships between the Heavy Metals Concentrations (HMA) and the physical properties can be represented using Multiple Linear Regressions (MLR) models, relating that the HMA of Zinc has affected significantly the physical growth properties of P. viridis.

Matched MeSH terms: Models, Statistical
The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach

Taha Z, Musa RM, P P Abdul Majeed A, Alim MM, Abdullah MR

Hum Mov Sci, 2018 Feb;57:184-193.
PMID: 29248809 DOI: 10.1016/j.humov.2017.12.008

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme.

Matched MeSH terms: Models, Statistical
Fulltext Developing forecasting model for future pandemic applications based on COVID-19 data 2020-2022

Wan Mohamad Nawi WIA, K Abdul Hamid AA, Lola MS, Zakaria S, Aruchunan E, Gobithaasan RU, et al.

PLoS One, 2023;18(5):e0285407.
PMID: 37172040 DOI: 10.1371/journal.pone.0285407

Improving forecasting particularly time series forecasting accuracy, efficiency and precisely become crucial for the authorities to forecast, monitor, and prevent the COVID-19 cases so that its spread can be controlled more effectively. However, the results obtained from prediction models are inaccurate, imprecise as well as inefficient due to linear and non-linear patterns exist in the data set, respectively. Therefore, to produce more accurate and efficient COVID-19 prediction value that is closer to the true COVID-19 value, a hybrid approach has been implemented. Thus, aims of this study is (1) to propose a hybrid ARIMA-SVM model to produce better forecasting results. (2) to investigate in terms of the performance of the proposed models and percentage improvement against ARIMA and SVM models. statistical measurements such as MSE, RMSE, MAE, and MAPE then conducted to verify that the proposed models are better than ARIMA and SVM models. Empirical results with three real datasets of well-known cases of COVID-19 in Malaysia show that, compared to the ARIMA and SVM models, the proposed model generates the smallest MSE, RMSE, MAE and MAPE values for the training and testing datasets, means that the predicted value from the proposed model is closer to the actual value. These results prove that the proposed model can generate estimated values more accurately and efficiently. As compared to ARIMA and SVM, our proposed models perform much better in terms of error reduction percentages for all datasets. This is demonstrated by the maximum scores of 73.12%, 74.6%, 90.38%, and 68.99% in the MAE, MAPE, MSE, and RMSE, respectively. Therefore, the proposed model can be the best and effective way to improve prediction performance with a higher level of accuracy and efficiency in predicting cases of COVID-19.

Matched MeSH terms: Models, Statistical
Fulltext Application of statistical experimental designs for optimization of medium composition in biodegradation of procion red MX-8B

Khadijah, O., Lee, K.K., Abdullah, M.F.F.

ASM Science Journal, 2010;4(2):103-112.
MyJurnal

Two sequential statistical experimental designs were used to screen and investigate the dependence of the amount of biodegradation of Procion Red MX-8B (PR-MX8B) on the fermentation variables. Fourteen factors were screened using the Plackett-Burman design. Among these factors, the most significant variables which included yeast extract, corn steep solids and starch influencing PR-MX8B decolourisation were statistically elucidated for optimization. The optimum concentrations of 5.00 g/l yeast extract, 2.99 g/l starch and 1.89 g/l corn steep solids were predicted by applying the Box-Behnken design to the second order polynomial model fitted to the results obtained. The best predicted optimal conditions verified experimentally yielded 72.11% while the predicted value from the polynomial model was 79.17%. The experimental values were in good agreement with the predicted values with a 90.81% degree of accuracy.

Matched MeSH terms: Models, Statistical
Fulltext Extraction and purification of Cytotoxic compounds from Premna Serratifolia L. (Bebuas) for human breast cancer treatment

Salih, G.A., Ahmad-Raus, R., Shaban, M.N., Abdullah, N.

International Food Research Journal, 2017;24(101):0-0.
MyJurnal

Breast cancer is considered as one of the most common cancers all over the world. A huge effort has been made to create a safe and cost effective breast cancer treatment. All of these features exist in the plants sources. In this study, the effect of local vegetable salad, Premna serratifolia (Bebuas) against MCF-7 cells (human breast adenocarcinoma) was determined. The optimum condition to extract breast cancer cytotoxic compound from the plant was investigated and the exact cytotoxic compound was identified as well. To determine the plant cytotoxicity effect against MCF-7 cells, MTT assay was used. Two important parameters in the sonication extraction method which are duration of time and temperature were optimized by carrying out a series of experiments which were designed by Face Centered Central Composite Design (FCCCD). The extraction efficiency of each experiment was determined by measuring the yield of extract and the half maximal inhibitory concentration (IC50) of the extract against MCF-7 cells. The results obtained from the experiments were fitted to the second order polynomial model to generate equation that was used to determine best extraction processing condition. Based on the generated equation, the best sonication processing condition to extract the cytotoxic compound is at 30oC for 67 min. Analysis of variance (ANOVA) showed that the duration of extraction time has great influence (p

Matched MeSH terms: Models, Statistical
Improvement of production of citric acid from oil palm empty fruit bunches: optimization of media by statistical experimental designs

Bari MN, Alam MZ, Muyibi SA, Jamal P, Abdullah-Al-Mamun

Bioresour Technol, 2009 Jun;100(12):3113-20.
PMID: 19231166 DOI: 10.1016/j.biortech.2009.01.005

A sequential optimization based on statistical design and one-factor-at-a-time (OFAT) method was employed to optimize the media constituents for the improvement of citric acid production from oil palm empty fruit bunches (EFB) through solid state bioconversion using Aspergillus niger IBO-103MNB. The results obtained from the Plackett-Burman design indicated that the co-substrate (sucrose), stimulator (methanol) and minerals (Zn, Cu, Mn and Mg) were found to be the major factors for further optimization. Based on the OFAT method, the selected medium constituents and inoculum concentration were optimized by the central composite design (CCD) under the response surface methodology (RSM). The statistical analysis showed that the optimum media containing 6.4% (w/w) of sucrose, 9% (v/w) of minerals and 15.5% (v/w) of inoculum gave the maximum production of citric acid (337.94 g/kg of dry EFB). The analysis showed that sucrose (p<0.0011) and mineral solution (p<0.0061) were more significant compared to inoculum concentration (p<0.0127) for the citric acid production.

Matched MeSH terms: Models, Statistical
Fulltext A preliminary investigation of user perception and behavioral intention for different review types: customers and designers perspective

Qazi A, Raj RG, Tahir M, Waheed M, Waheed M, Khan SU, et al.

ScientificWorldJournal, 2014;2014:872929.
PMID: 24711739 DOI: 10.1155/2014/872929

Existing opinion mining studies have focused on and explored only two types of reviews, that is, regular and comparative. There is a visible gap in determining the useful review types from customers and designers perspective. Based on Technology Acceptance Model (TAM) and statistical measures we examine users' perception about different review types and its effects in terms of behavioral intention towards using online review system. By using sample of users (N = 400) and designers (N = 106), current research work studies three review types, A (regular), B (comparative), and C (suggestive), which are related to perceived usefulness, perceived ease of use, and behavioral intention. The study reveals that positive perception of the use of suggestive reviews improves users' decision making in business intelligence. The results also depict that type C (suggestive reviews) could be considered a new useful review type in addition to other types, A and B.

Matched MeSH terms: Models, Statistical
Polishing of treated palm oil mill effluent (POME) from ponding system by electrocoagulation process

Bashir MJ, Mau Han T, Jun Wei L, Choon Aun N, Abu Amr SS

Water Sci Technol, 2016;73(11):2704-12.
PMID: 27232407 DOI: 10.2166/wst.2016.123

As the ponding system used to treat palm oil mill effluent (POME) frequently fails to satisfy the discharge standard in Malaysia, the present study aimed to resolve this problem using an optimized electrocoagulation process. Thus, a central composite design (CCD) module in response surface methodology was employed to optimize the interactions of process variables, namely current density, contact time and initial pH targeted on maximum removal of chemical oxygen demand (COD), colour and turbidity with satisfactory pH of discharge POME. The batch study was initially designed by CCD and statistical models of responses were subsequently derived to indicate the significant terms of interactive process variables. All models were verified by analysis of variance showing model significances with Prob > F < 0.01. The optimum performance was obtained at the current density of 56 mA/cm(2), contact time of 65 min and initial pH of 4.5, rendering complete removal of colour and turbidity with COD removal of 75.4%. The pH of post-treated POME of 7.6 was achieved, which is suitable for direct discharge. These predicted outputs were subsequently confirmed by insignificant standard deviation readings between predicted and actual values. This optimum condition also permitted the simultaneous removal of NH3-N, and various metal ions, signifying the superiority of the electrocoagulation process optimized by CCD.

Matched MeSH terms: Models, Statistical
Fulltext The performance of expectation maximization (EM) Algorithm in Gaussian Mixed Models (GMM)

Mohd. Izhan Mohd. Yusoff, Mohd. Rizam Abu Bakar, Abu Hassan Shaari Mohd. Nor

Pertanika Journal of Science & Technology, 2009;17(2):-.
MyJurnal

Expectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. In this paper, the performance of the said algorithm in finding the Maximum Likelihood for the Gaussian Mixed Models (GMM), a probabilistic model normally used in fraud detection and recognizing a person’s voice in speech recognition field, is shown and discussed. At the end of the paper, some suggestions for future research works will also be given.

Matched MeSH terms: Models, Statistical
Fulltext Bayesian inference of the Weibull model based on interval-censored survival data

Guure CB, Ibrahim NA, Adam MB

Comput Math Methods Med, 2013;2013:849520.
PMID: 23476718 DOI: 10.1155/2013/849520

Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.

Matched MeSH terms: Models, Statistical
Application of the central composite design for condition optimization for semi-aerobic landfill leachate treatment using electrochemical oxidation

Mohajeri S, Aziz HA, Isa MH, Zahed MA, Bashir MJ, Adlan MN

Water Sci Technol, 2010;61(5):1257-66.
PMID: 20220248 DOI: 10.2166/wst.2010.018

In the present study, Electrochemical Oxidation was used to remove COD and color from semi-aerobic landfill leachate collected from Pulau Burung Landfill Site (PBLS), Penang, Malaysia. Experiments were conducted in a batch laboratory-scale system in the presence of NaCl as electrolyte and aluminum electrodes. Central composite design (CCD) under Response surface methodology (RSM) was applied to optimize the electrochemical oxidation process conditions using chemical oxygen demand (COD) and color removals as responses, and the electrolyte concentrations, current density and reaction time as control factors. Analysis of variance (ANOVA) showed good coefficient of determination (R(2)) values of >0.98, thus ensuring satisfactory fitting of the second-order regression model with the experimental data. In un-optimized condition, maximum removals for COD (48.77%) and color (58.21%) were achieved at current density 80 mA/cm(2), electrolyte concentration 3,000 mg/L and reaction time 240 min. While after optimization at current density 75 mA/cm(2), electrolyte concentration 2,000 mg/L and reaction time 218 min a maximum of 49.33 and 59.24% removals were observed for COD and color respectively.

Matched MeSH terms: Models, Statistical
Adsorption of copper (II), chromium (III), nickel (II) and lead (II) ions from aqueous solutions by meranti sawdust

Rafatullah M, Sulaiman O, Hashim R, Ahmad A

J Hazard Mater, 2009 Oct 30;170(2-3):969-77.
PMID: 19520510 DOI: 10.1016/j.jhazmat.2009.05.066

The present study proposed the use of meranti sawdust in the removal of Cu(II), Cr(III), Ni(II) and Pb(II) ions from synthetic aqueous solutions. Batch adsorption studies showed that meranti sawdust was able to adsorb Cu(II), Cr(III), Ni(II) and Pb(II) ions from aqueous solutions in the concentration range 1-200mg/L. The adsorption was favoured with maximum adsorption at pH 6, whereas the adsorption starts at pH 1 for all metal ions. The effects of contact time, initial concentration of metal ions, adsorbent dosage and temperature have been reported. The applicability of Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherm was tried for the system to completely understand the adsorption isotherm processes. The adsorption kinetics tested with pseudo-first-order and pseudo-second-order models yielded high R(2) values from 0.850 to 0.932 and from 0.991 to 0.999, respectively. The meranti sawdust was found to be cost effective and has good efficiency to remove these toxic metal ions from aqueous solution.

Matched MeSH terms: Models, Statistical

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