Malaysian Journal of Applied Sciences (Journal of UniSZA - Universiti Sultan Zainal Abidin)
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Spatial Pattern Recognition of School Performance Based on Anthropometric and Motor Parameters using Multivariate Analysis and Kriging Interpolation Technique
Get PDFThe purpose of this study is to determine spatial pattern recognition of school performance based on children’s anthropometric and motor skills component. This study involved 93 primary schools with a total 2237 male students aged 7.30±0.28 years in Pahang, Malaysia. The parameters of anthropometric (weight and height) and motor component included low muscular power (standing broad jump), flexibility (sit and reach), coordination (hand wall toss) and speed (20 meter run) were selected. Cluster Analysis (CA) and Discriminat Analysis (DA) under Multivariate Method and technique of Kriging Interpolation in Geographic Interpolation Software (GIS) were used. CA revealed two clusters of school performance. There are a total 34 high performance schools (HPS) and 60 low performance schools (LPS). Then, the assigned groups were treated as independent variable (IV) while anthropometric and motor parameters were treated as dependent variable (DV) in DA. Standard mode of DA obtained 95.74% correctness of classification matrix with three discriminated variables (height, standing broad jump and 20 meter run) out of six variables. Meanwhile, forward and backward stepwise mode of DA discriminated only one (standing broad jump) out of six variables with 96.81% of classification correctness. The map output of Kriging interpolation has shown graphically the pattern of discriminated variables that greatly influence school performance. It exposed the ability of children develop their motor skills in particular region is higher than another region. This finding would suggest that follow up studies must be carried up to investigate the factors of these pattern could happened
Breakfast Intake and its Association with Body Mass Index among Pre-schoolers in Taska Permata Keluarga Kuala Nerus, Terengganu
Get PDFIn Malaysia, breakfast is the most frequently skipped meal. Skipping breakfast has been associated with an increased risk of childhood obesity. However, this relationship has not been investigated widely among preschoolers in Malaysia. Hence, this cross-sectional study aimed to determine the association between breakfast intake and Body Mass Index (BMI) among preschoolers in Taska Permata Keluarga (TPK), Kuala Nerus. A total of 131 Malays preschoolers aged four to six years old were recruited from nine TPK using convenience sampling method. Information on sociodemographic, breakfast intake pattern and anthropometric measurements (weight and height) were obtained. Respondents consisted of 74 (56.5%) boys and 57 (43.5%) girls. Anthropometric results showed that 8.4% preschoolers were overweight and obese. Among the preschoolers, 22.1% of them were breakfast skippers. In terms of gender breakdown, 20.3% boys and 24.6% girls skipped breakfast. There was a significant association between breakfast intake and BMI status among preschoolers (p = 0.003). This indicated that preschoolers that skipped breakfast were associated with overweight or obese compared to those who consumed breakfast daily. Breakfast consumption is a marker of a healthy lifestyle which can reduce the risk of childhood obesity. This habit should be inculcated during this critical period of life in which parents play a vital role in promoting breakfast consumption among preschoolers
In Vitro Cytotoxicity and Antioxidant Activities of Pestalotiopsis microspora Culture Filtrate
Get PDFEndophytic fungi have been studied to provide protection and survival conditions to their host plant by producing a plethora of substances which, once isolated and characterized, may also have potential for use in industry, agriculture, and medicine. In this study, the culture filtrate of an endophytic fungus (Pestalotiopsis microspora (PM)) was evaluated for its cytotoxic and antioxidant activities in vitro. The cytotoxic activity of PM was determined using brine shrimp lethality assay (BSLA), while its antioxidant effect was investigated against DPPH, reducing power and hydroxyl radicals. Judging by the LC50 value of 2.71 mgmL-1 for the BSLA, the culture filtrate could be considered highly potent. The PM also significantly scavenged free radicals and the effects elicited could be attributed to its phenolics and other phytoconstituents as revealed by the GC-MS results. It is thereby evident from the data presented that PM is endowed with chemotherapeutic constituents that could be potentially useful for the development of new lead anticancer agents
Extended Cox Modelling of Survival Data with Guarantee Time
Get PDFProportional Hazard regression model for censored survival data often specifies that covariates have a proportional fixed effect on the hazard function of the lifetime distribution of a subject. A modification of the proportional hazards model of Cox (1972) to accommodate the non-proportional effect on hazard with a time-varying covariate and the introduction of guarantee time into the Weibull distributed baseline hazard function. Simulations were conducted to investigate properties of the models. Our approach had shown to have the best asymptotic properties in a simulation study with mean, Absolute Bias (AB) and Mean Square Error (MSE) of the parameter estimates for the models (under different levels of censoring and sample sizes) using simulated data
Computing the Performance of FFNN for Classifying Purposes
Get PDF Classification is one of the most hourly encountered problems in real world. Neural networks have emerged as one of the tools that can handle the classification problem. Feed-Forward Neural Networks (FFNN's) have been widely applied in many different fields as a classification tool. Designing an efficient FFNN structure with the optimum number of hidden layers and minimum number of layer's neurons for a given specific application or dataset, is an open research problem and more challenging depend on the input data. The random selections of hidden layers and neurons may cause the problem of either under fitting or over fitting. Over fitting arises because the network matches the data so closely as to lose its generalization ability over the test data. In this research, the classification performance using the Mean Square Error (MSE) of Feed-Forward Neural Network (FFNN) with back-propagation algorithm with respect to the different number of hidden layers and hidden neurons is computed and analyzed to find out the optimum number of hidden layers and minimum number of layer's neurons to help the existing classification concepts by MATLAB version 13a. By this process, firstly the random data has been generated using an suitable matlab function to prepare the training data as the input and target vectors as the testing data for the classification purposes of FFNN. The generated input data is passed on to the output layer through the hidden layers which process these data. From this analysis, it is find out from the mean square error comparison graphs and regression plots that for getting the best performance form this network, it is better to use the high number of hidden layers and more neurons in the hidden layers in the network during designing its classifier but so more neurons in the hidden layers and the high number of hidden layers in the network makes it complex and takes more time to execute. So as the result it is suggested that three hidden layers and 26 hidden neurons in each hidden layers are better for designing the classifier of this network for this type of input data features
Maintenance and Physical Asset Management Issues in Project Commissioning
Get PDFThis study describes the review on maintenance related issues during design and construction stage within construction industry. The paper highlights the causes and errors made during design and construction stage and their impact during the operation/production/occupancy stage as well as the maintenance costs associated with it. The study identifies the mistakes in the working processes within design and construction stage leading to the errors that affect the durability, performance, reliability, maintainability, availability and safety of the systems. The paper presents a comprehensive review of the published literatures, journals, technical papers in the related areas in the construction field. The review highlights the new approaches and decision framework which link the designers and construction personnel that could reduce the errors and defects in construction which then lead to maintenance issues and asset management. The factors of accessibility, materials, design and documentation standardization have been discussed thoroughly for better understanding in improving maintenance and physical asset management in project commissioning
Temporal Variation and Pollution Levels of Some Heavy Metals on Irrigated Land Along Airport Road Kano State, Nigeria
Get PDFThis paper is aimed at evaluating the concentration of some heavy metals in order to assess the temporal variation, Contamination Factor (CF) and Pollution Load Index (PLI) of the heavy metals in the soil of the area. Soil samples were collected in two period 2009 and 2015 using composite sampling techniques, 10 samples were collected in each period and then analysed using standard laboratory procedures. The findings revealed that the mean values of Mn (52±7.2), Fe (281±19.4) and Cd (3.0±0.3) were found to be higher in soil sampled in 2009 while, Cu (100±16.3), Zn (161±47.7), Cr (20.8±1.5), Ni (53.9±9.7) and pH (9.0±0.56) were found to be higher in soil sampled in 2015. The CF shows that the soils of the area have low contamination level, moderately contaminated with Cd and the soils have low pollution level according to the PLI. From the finding it was concluded that there is gradual accumulation of Cu, Zn, Cr and Ni with reduction in Mn, Fe and Cd. The soils have low contamination level with all heavy metal except Cd that moderately contaminates the soil of the area according to contamination factor. The PLI values of the heavy metals in 2009 and 2015 are 0.0006 and 0.02 respectively, indicating increases in pollution load from 2009 to 2015 in the study area. Proper soil management such as increase of pH and organic matter as well as the avoidance of using contaminated water for irrigation were recommended in the area
Effect of Cetyle Trimethyl Ammonium Bromide (CTAB) Surfactant on Nanofiltration Membrane for Dye Removal
Get PDFNanofiltration membranes technology commonly used for wastewater treatment especially wastewater containing charged and/or uncharged species. Commonly, textile wastewater possesses high chemical oxygen demand (COD) and non-biodegradable compounds such as pigments and dyes which lead to environmental hazard and serious health problem. Therefore, the objective of this study was to investigate the effects of hydrophilic surfactant on the preparation and performance of Active Nanofiltration (ANF) membrane. The polymeric ANF membranes were prepared via dry/wet phase inversion technique by immersion precipitation process. The Cetyle trimethyl ammonium bromide (CTAB) as cationic surfactant was added in casting solution at concentrations from 0 to 2.5 wt%. The synthesized membrane performance was evaluated in terms of pure water permeation (PWP) and dye rejection. The experimental data showed that the membrane demonstrated good increment of PWP ranging from 0.27 to 10.28 L/m2h at applied pressure from 100 to 500 kPa, respectively. Meanwhile, the ANF membranes achieved high removal of Methyl Blue and Reactive Black 5 dye up to 99.5% and 91.6%, respectively.
Spatial Decision Support Systems for Locating Waste Landfills
Get PDFThe decision process to locate an undesirable facility like a waste landfill usually involves many stakeholders and many location criteria. The views of the stakeholders on the importance of the criteria often differ. Such a location problem is termed ‘a complex spatial problem’ and is solved by spatial multi-criteria based approaches. The objective of this paper is to provide a spatial decision support system (SDSS) that integrates multi-criteria and location-allocation (L-A) models to support the decision process of locating a waste landfill. The SDSS was applied to find a suitable location for a landfill in Ijebu-Ode, a medium sized city in Nigeria. The data input into the multi-criteria analysis model of the SDSS include three town planning regulatory constraint maps and four environmental factor maps. Data input into the L-A model include the location and amount of waste generated at nineteen waste collection points in the study area. Data on the road network was used to determine movements between the waste collection points and the landfill. To determine the most suitable area for the landfill, the factor maps were weighted by the stakeholders’ preferences and combined with the constraint maps to eliminate areas that cannot be used for the landfill. The result of the map combination and weighted overlay procedure, resulted into twenty seven environmentally suitable areas. To find the most efficient of the twenty seven suitable locations, the L-A model was applied. The chosen facility location is the most efficient for the waste management system in terms of transportation cost. The usefulness of SDSSs as a decision support tool in solving complex spatial problem has been demonstrated in this paper. Improvements in available data and existing GIS can encourage similar systems to be designed and used by decision makers, particularly in developing countries
New Bayesian Estimators for Randomized Response Technique
Get PDFThis paper proposed new Bayesian estimators of the population proportion of a sensitive attribute when life data were collected through the administration of questionnaires on abortion on 300 matured women in some selected hospitals in the metropolis. Assuming both the Kumaraswamy (KUMA) and the generalised (GLS) beta distributions as alternative beta priors, efficiency of the proposed Bayesian estimators was established for a wide interval of the values of the population proportion (. We observed that for small, medium as well as large sample sizes, the developed Bayesian estimators were better in capturing responses from respondents than the conventional simple beta estimator proposed by Hussain and Shabbir (2009a) as approaches one.