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Fulltext Some explicit conditions for a stationary representation of the unilateral second-order spatial ARMA model

Saidatulnisa Abdullah, Shitan, Mahendran

Pertanika Journal of Science & Technology, 2009;17(1):-.
MyJurnal

The analysis of the spatial data has been carried out in many disciplines such as demography, meteorology, geology and remote sensing. The spatial data modelling is important because it recognizes the phenomenon of spatial correlation in field experiments. Three main categories of the spatial models, namely, the simultaneous autoregressive (SAR) models (Whittle, 1954), the conditional autoregressive (CAR) models (Bartlett, 1971), and the moving average (MA) models (Haining, 1978) have been studied. Whittle (1954) presented a form of bilateral autoregressive (AR) models, whereas Basu and Reinsel (1993) considered the first-order autoregressive moving average (ARMA) model of the quadrant type. Awang, N. and Mahendran Shitan (2003) presented the second-order ARMA model, and established some explicit stationary conditions for the model. When fitting the spatial models and making prediction, it is assumed that, the properties of the process would not change with sites. Properties like stationarities have to be assumed, and for this reason, it was therefore imperative that the researchers had made certain that the process was stationary. This could be achieved by providing the explicit stationarity conditions for the model. The explicit conditions, for a stationary representation of the second-order spatial unilateral ARMA model denoted as ARMA(2,1;2,1), have been established (Awang, N. and Mahendran Shitan, 2003) and in this paper, some explicit conditions are established for a stationary representation of the second-order spatial unilateral ARMA model, denoted as ARMA(2,2;2,2).
Fulltext Spatial regression with conditional autoregressive (CAR) errors for annual mean relative humidity in Peninsular Malaysia

Shitan, Mahendran, Kok, Wei Ling

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

Modelling observed meteorological elements can be useful. For instance, modelling rainfall has
been an interest for many researchers. In a previous research, trend surface analysis was used and
it was indicated that the residuals might spatially be correlated. When dealing with spatial data, any
modelling technique should take spatial correlation into consideration. Hence, in this project, fitting
of spatial regression models, with spatially correlated errors to the annual mean relative humidity
observed in Peninsular Malaysia, is illustrated. The data used in this study comprised of the annual
mean relative humidity for the year 2000-2004, observed at twenty principal meteorological stations
distributed throughout Peninsular Malaysia. The modelling process was done using the S-plus
Spatial Statistics Module. A total of twelve models were considered in this study and the selection
of the model was based on the p-value. It was found that a possible appropriate model for the
annual mean relative humidity should include an intercept and a term of the longitude as covariate,
together with a conditional autoregressive error structure. The significance of the coefficient of the
covariate and spatial parameter was established using the Likelihood Ratio Test. The usefulness
of the proposed model is that it could be used to estimate the annual mean relative humidity at
places where observations were not recorded and also for prediction. Some other potential models
incorporating the latitude covariate have also been proposed as viable alternatives.
Fulltext Application of computer vision in the detection of chilling injury in bananas

Norhashila Hashim, Rimfiel B. Janius, Russly Abdul Rahman, Azizah Osman, Zude, Manuela, Shitan, Mahendran

Pertanika Journal of Science & Technology, 2013;21(1):111-118.
MyJurnal

Bananas were chilled at 6oC and the appearance of brown spots when exposed to ambient air, a
phenomenon known as chilling injury (CI), was detected using computer vision. The system consisted of a digital colour camera for acquiring images, an illumination set-up for uniform lighting, a computer for receiving, storing and displaying of images and software for analyzing the images. The RGB colour space values of the images were transformed into that of HSI colour space which is intuitive to human vision. Visual assessment of CI by means of a browning scale was used as a reference and correlation between this reference values and hue was investigated. Results of the computer vision study successfully demonstrate the potential of the system in substituting visual assessment in the evaluation of CI in bananas. The results indicate significant influence, at α=0.05, of treatment days and temperature on hue. A strong correlation was also found between hue and visual assessment with R>0.85.
Relative importance of demographic, socioeconomic and health factors on life expectancy in low- and lower-middle-income countries

Mondal MN, Shitan M

J Epidemiol, 2014;24(2):117-24.
PMID: 24390415

BACKGROUND: We attempted to identify the pathways by which demographic changes, socioeconomic inequalities, and availability of health factors influence life expectancy in low- and lower-middle-income countries.
METHODS: Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy.
RESULTS: All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy.
CONCLUSIONS: We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.
Fulltext Author's Response: Regarding the Relative Importance of Demographic, Socioeconomic and Health Factors on Life Expectancy in Low- and Lower-Middle-Income Countries

Mondal MN, Shitan M

J Epidemiol, 2015;25(6):460.
PMID: 25986157 DOI: 10.2188/jea.JE20150046
Fulltext Projection of human immunodeficiency virus among high-risk groups in Malaysia

Mondal MN, Shitan M

Jpn J Infect Dis, 2013;66(5):421-4.
PMID: 24047742

Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) presents a serious healthcare threat to young individuals in Malaysia and worldwide. This study aimed to identify trends in HIV-related risk behaviors among recognized high-risk groups and to estimate HIV transmission up to the year 2015. Data and necessary information were obtained from the Ministry of Health Malaysia, published reports from the World Health Organization and United Nations Program on HIV/AIDS, and other articles. The Estimation and Projection Package was used to estimate HIV transmission. The results of the present study revealed that within the high-risk groups, intravenous drug users (IDUs) had the highest prevalence rate of HIV transmission, followed by patients with sexually transmitted infections (STIs), female sex workers (SWs), and men who have sex with men (MSM). Within these at-risk populations, patients with STIs have the highest prevalence of HIV, followed by IDUs, MSM, and SWs. If the transmission rate continues to increase, the situation will worsen; therefore, there is an urgent need for a comprehensive prevention program to control HIV transmission in Malaysia.
Impact of Socio-Health Factors on Life Expectancy in the Low and Lower Middle Income Countries

Mondal MN, Shitan M

Iran J Public Health, 2013 Dec;42(12):1354-62.
PMID: 26060637

This study is concerned with understanding the impact of demographic changes, socioeconomic inequalities, and the availability of health factors on life expectancy (LE) in the low and lower middle income countries.
Fulltext The beta Burr type X distribution properties with application

Merovci F, Khaleel MA, Ibrahim NA, Shitan M

Springerplus, 2016;5(1):697.
PMID: 27347471 DOI: 10.1186/s40064-016-2271-9

We develop a new continuous distribution called the beta-Burr type X distribution that extends the Burr type X distribution. The properties provide a comprehensive mathematical treatment of this distribution. Further more, various structural properties of the new distribution are derived, that includes moment generating function and the rth moment thus generalizing some results in the literature. We also obtain expressions for the density, moment generating function and rth moment of the order statistics. We consider the maximum likelihood estimation to estimate the parameters. Additionally, the asymptotic confidence intervals for the parameters are derived from the Fisher information matrix. Finally, simulation study is carried at under varying sample size to assess the performance of this model. Illustration the real dataset indicates that this new distribution can serve as a good alternative model to model positive real data in many areas.
Fulltext Prediction of Hexaconazole Concentration in the Top Most Layer of Oil Palm Plantation Soil Using Exploratory Data Analysis (EDA)

Maznah Z, Halimah M, Shitan M, Kumar Karmokar P, Najwa S

PLoS One, 2017;12(1):e0166203.
PMID: 28060816 DOI: 10.1371/journal.pone.0166203

Ganoderma boninense is a fungus that can affect oil palm trees and cause a serious disease called the basal stem root (BSR). This disease causes the death of more than 80% of oil palm trees midway through their economic life and hexaconazole is one of the particular fungicides that can control this fungus. Hexaconazole can be applied by the soil drenching method and it will be of interest to know the concentration of the residue in the soil after treatment with respect to time. Hence, a field study was conducted in order to determine the actual concentration of hexaconazole in soil. In the present paper, a new approach that can be used to predict the concentration of pesticides in the soil is proposed. The statistical analysis revealed that the Exploratory Data Analysis (EDA) techniques would be appropriate in this study. The EDA techniques were used to fit a robust resistant model and predict the concentration of the residue in the topmost layer of the soil.
Discrimination of three Pegaga (Centella) varieties and determination of growth-lighting effects on metabolites content based on the chemometry of 1H nuclear magnetic resonance spectroscopy

H M, Khatib A, Shaari K, Abas F, Shitan M, Kneer R, et al.

J Agric Food Chem, 2012 Jan 11;60(1):410-7.
PMID: 22084897 DOI: 10.1021/jf200270y

The metabolites of three species of Apiaceae, also known as Pegaga, were analyzed utilizing (1)H NMR spectroscopy and multivariate data analysis. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) resolved the species, Centella asiatica, Hydrocotyle bonariensis, and Hydrocotyle sibthorpioides, into three clusters. The saponins, asiaticoside and madecassoside, along with chlorogenic acids were the metabolites that contributed most to the separation. Furthermore, the effects of growth-lighting condition to metabolite contents were also investigated. The extracts of C. asiatica grown in full-day light exposure exhibited a stronger radical scavenging activity and contained more triterpenes (asiaticoside and madecassoside), flavonoids, and chlorogenic acids as compared to plants grown in 50% shade. This study established the potential of using a combination of (1)H NMR spectroscopy and multivariate data analyses in differentiating three closely related species and the effects of growth lighting, based on their metabolite contents and identification of the markers contributing to their differences.
Fulltext A new mathematical evaluation of smoking problem based of algebraic statistical method

Mohammed MJ, Rakhimov IS, Shitan M, Ibrahim RW, Mohammed NF

Saudi J Biol Sci, 2016 Jan;23(1):S11-5.
PMID: 26858555 DOI: 10.1016/j.sjbs.2015.08.015

Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent.