The oil palm trunk (OPT) currently represents a massive volume of agricultural waste with great potential to be rapidly developed in the wood composite industry. An improvement in sawing technology has potential to improve the yield of the commercially hard outer core of the OPT by about 27 % thus replacing the present sub-optimal square sawing pattern with a more efficient and higher-yielding polygon sawing pattern. To achieve this, a 'wedge' device was designed to be mounted on the existing sawing carriage. The proper methodology was followed including extraction of the design layout of the machine, development of the schematic drawing and wireframe model, modification of the design in computer-aided design (CAD) environment, the performance of stress, total deformation, and fatigue analysis, and production of a complete drawing for fabrication purpose. Results from the analysis showed that the designed part was safe to be fabricated with a small maximum equivalent stress of 2.546 MPa, maximum total deformation of 0.007935 mm and total life cycle of one million cycles. These evaluation results indicate that the material used for the wedge device (including the base part) satisfies the design requirements of static strength and is safe within its designed fatigue life.
This study aims to characterise the scattered dose distribution from a ceiling-mounted X-ray unit in a multi-bay resuscitation room. The finding of this study is essential for optimisation and safety of staff and patients. Simulation of phantom imaging was carried out using MCNP5 code. The calculated data were initially compared against the measurements carried out using a survey meter. Three measurement positions, denoted by T2, T3, and T4 were considered for the dose calculation. The data suggested that T2 received the highest scattered dose. This value (maximum value of less than 6 µGy) is lower than the annual dose limit for the public and radiation workers as well as natural background radiation dose. Meanwhile, T3 consistently received a higher scattered dose (maximum difference of 25.62%) than T4. The angles of the X-ray tube resulted in scattered doses less than 6 µGy for both 90° and 100° scattering angles. In conclusion, the scattered dose for a single exposure imaging inside the room is safe. Yet, consideration of the placement of a portable lead shielding between X-ray tube and treatment couch is strongly recommended. This is due to a high number of imaging procedures commonly performed daily in a busy hospital. Hence, the cumulative dose to the paramedic staff and patients may exceed the safe level.
Jackfruit straws are normally disposed as waste by food industries and vendors which may lead to serious environmental issue. In order to reduce the wastage and negative effects to the environment, jackfruit straw waste generated by jackfruit (Artocarpus heterophyllus) shows potential as bio-based film incorporated with starch. This work describes the effect of different starch and plasticizer contents on mechanical and thermal properties of jackfruit straw powder (JSP)/starch films. Film-forming solutions were prepared and cast by mixing JSP with tapioca starch at different ratios and for the plasticized films, ca. 15 - 40% of plasticizers including sorbitol and glycerol were incorporated into the JSP/starch films respectively. The tensile strength and modulus of JSP/starch films pronouncedly increased with increasing starch content, accompanied with a slight decreasing in the elongation at break. The result demonstrated that starch interacted with JSP, resulting in the formation of a new network to improve the properties of JSP films. FTIR spectrum analyses demonstrated the presence of hydrogen bonding in the JSP/starch film. The tensile strength of the plasticized JSP/starch films decreased with increasing sorbitol and glycerol content from 15% to 40%. However, the plasticizing effect of sorbitol became more significant than glycerol, particularly on the tensile properties and thermal stability. Thermal analysis by thermogravimetric showed an increment in the decomposition temperature with the addition of plasticizers into JSP/starch films. The results suggest that films containing JSP and starch have the potential for the development of edible food packaging materials.
The current study investigates the phytochemical composition of Malaysian stingless bee honey (Kelulut honey-KH), which consists of total phenolic (TPC) and total flavonoid content (TFC), and antioxidant activity. The honey was collected from five different regions in Malaysia i.e. south, central, eastern, northern and east coast regions. TPC and TFC were quantified by using Folin-Ciocalteu and the aluminum chloride colorimetric techniques, respectively. The antioxidant activity was investigated using two methods: 1) 1,1-diphenyl- 2-picrylhydrazyl (DPPH) radical scavenging assay; 2) ferric reducing/antioxidant power assay (FRAP). The findings indicated that there were significant differences in phytochemical compositions and antioxidant activities of KH between different regions. This implies that geographical location, as well as cultivation and treatment processes, have significant effects on the KH quality.
In the present research, microalgae protein hydrolysate of Nannochloropsis gaditana (MPH) was extracted via enzymatic hydrolysis using alcalase enzyme. Hydrolysis conditions like (pH, temperature, enzyme concentration and substrate concentration) were optimized by Response Surface Methodology (RSM) using Central Composite Design (CCD). Four range of independent variables namely; pH (7-9), temperature (45-55°C), substrate concentration (2-6 g/L) and enzyme concentration (0.2-0.4 g/L) were used to study the influence of these parameters on the degree of hydrolysis. The CCD consisted of twenty-four experimental points and six replicates of central points with the optimum conditions obtained from this experiment were at pH 8.14, a temperature 51.4°C, a substrate concentration 5.48 g/L and an enzyme concentration 0.26 g/L with maximum degree hydrolysis of 55.76%. All experiments were fixed at 24 hours reaction time. The degree of hydrolysis of MPH was analysed using O-phthaldehyde (OPA) method to quantify the cleavage of peptide bond. The optimized sample was evaluated for its antioxidant activity using 1,1-Diphenyl-2-picrylhydrazyl (DPPH) assay with 52.19% and 2, 2'- azino-bis (ethylbenzthiazoline-6-sulfonic acid (ABTS) assay with 14.13%. The bioactive peptides contained in Nannochloropsis gaditana have the ability to scavenge free radicals and act as good antioxidants.
Pomelo pomace (PP) from Malaysia Tambun White (PO52) variety, dried at different temperature under vacuum condition were evaluated. PP was obtained after extraction process and contained high moisture content (MC). Dried PP can be used as an alternative to livestock feed, hence, dried concentrated form was preferable. Nevertheless, drying process significantly affects the physico-chemical properties of a dried product. Therefore, the present study was carried out to discover the effects of drying temperature on the physico-chemical properties (MC, pH, vitamin C, browning index (BI) and total color change) of PP. The PP was dried at different drying temperature (50, 60, 70, 80 and 90°C) using a vacuum drying (VD) oven for 24 hr. The freeze drying (FD) process was used as a control. The result showed the MC gradually decreased with increasing drying temperature, of which similar trend was also observed for the water activity and total soluble solids (TSS). In contrast, pH showed increment in value with elevated drying temperature. Interestingly, at 90°C, vitamin C of VD (30.38 mg / 100 g DW) was higher than FD pomelo pomace (21.10 mg / 100 g DW). BI significantly increased as temperature increased. However, no significant changes were observed for total color change after VD. In conclusion, VD at 90°C showed the most recommended temperature because the composition of quality properties at this temperature was not significantly varied with control. These fundamentals information of pomelo pomace could be the guideline for postharvest technologist and food processing manufacturers for various applications.
In this paper, we present the absolute stability of the existing 2-point implicit block multistep step methods of step number k = 3 and k = 5 and solving special second order ordinary differential equations (ODEs). The methods are then trigonometrically fitted so that they are suitable for solving highly oscillatory problems arising from the special second order ODEs. Their explicit counterparts are also trigonometrically fitted so that in the implementation the methods can act as a predictor-corrector pairs. The numerical results based on the integration over a large interval are given to show the performance of the proposed methods. From the numerical results we can conclude that the new trigonometrically-fitted methods are superior in terms of accuracy and execution time, compared to the existing methods in the scientific literature when used for solving problems which are oscillatory in nature.
Parboiling process has been widely implemented in brown rice processing, but its effect on in vitro physiological antioxidant capacity of brown rice was not known. In this study, an in vitro method simulating the human physiological conditions was used to investigate the effect of parboiling on antioxidant capacity of brown rice in three Bario rice varieties. In this method, bacterial inocula were prepared from rat cecal contents. Results showed that parboiling process gave significant impacts on in vitro physiological antioxidant capacity of brown rice. The process improved total phenolic content at small intestine (Adan Halus), DPPH scavenging activity at both small and large intestines (Adan Halus and Bario Merah) and ferrous ion-chelating activity at large intestine (Bario Hitam). However, changes in antioxidant capacity were variety dependent, possibly due to different bran pigmentation. These suggested that parboiling process could improve physiological antioxidant capacity with in vitro simulation at small and large intestines by selecting a suitable rice variety and parboiled brown rice could offer good antioxidant properties to maintain physiological health.
Reliance on modern sophisticated equipment for making ‘discoveries’ has limited the human power of observing subtle clues in the environment that are capable of saving cost and labour that come with researching new resources and methods to improve life for all. Due to the growing scarcity of potable water, especially in African and Asian countries, newer, cheaper and reliable methods of investigating groundwater resources are becoming critical. One such potentially promising method is mapping the distribution of termite mounds in the environment. Termite mounds are conspicuous landscape features in tropical and sub-tropical regions of the world. Built from surrounding soils by several species of termite, the properties of mound soil are relatively different from the surrounding soil in most cases, indicating improved hydraulic properties. In this paper, the aim is to review the possibility of employing termite mounds as prospecting tools for groundwater search from three spatial scales of observation. From assessing the smallest to the highest scale of observation, it can be concluded that termite mounds’ prospect as surface indicators of groundwater is apparent. Review findings indicate increased surface water infiltration, presence of riparian tree vegetation and other trees with tap-root system around termite mounds, linear assemblage of termite mounds along aquiferous dykes and seep-lines as well as the dependence of termites on water but avoidance of places with risk of inundation. Whether they indicate permanent groundwater reserves in all cases or whether all species depend largely on water for their metabolism is a subject for further research.
The issue of classifying objects into groups when measured variables in an experiment are mixed has attracted the attention of statisticians. The Smoothed Location Model (SLM) appears to be a popular classification method to handle data containing both continuous and binary variables simultaneously. However, SLM is infeasible for a large number of binary variables due to the occurrence of numerous empty cells. Therefore, this study aims to construct new SLMs by integrating SLM with two variable extraction techniques, Principal Component Analysis (PCA) and two types of Multiple Correspondence Analysis (MCA) in order to reduce the large number of mixed variables, primarily the binary ones. The performance of the newly constructed models, namely the SLM+PCA+Indicator MCA and SLM+PCA+Burt MCA are examined based on misclassification rate. Results from simulation studies for a sample size of n=60 show that the SLM+PCA+Indicator MCA model provides perfect classification when the sizes of binary variables (b) are 5 and 10. For b=20, the SLM+PCA+Indicator MCA model produces misclassification rates of 0.3833, 0.6667 and 0.3221 for n=60, n=120 and n=180, respectively. Meanwhile, the SLM+PCA+Burt MCA model provides a perfect classification when the sizes of the binary variables are 5, 10, 15 and 20 and yields a small misclassification rate as 0.0167 when b=25. Investigations into real dataset demonstrate that both of the newly constructed models yield low misclassification rates with 0.3066 and 0.2336 respectively, in which the SLM+PCA+Burt MCA model performed the best among all the classification methods compared. The findings reveal that the two new models of SLM integrated with two variable extraction techniques can be good alternative methods for classification purposes in handling mixed variable problems, mainly when dealing with large binary variables.
Urbanisation increases the level of imperviousness in a catchment, and more runoff is converted from rainfall in urban areas. To mitigate this adverse situation, dispensed green infrastructure presents the best solution for delivering results in reducing stormwater impact. Green roofs and rain gardens are extensively studied and widely available in the literature, but this is not the case for green walls, which more often than not, are treated as ornaments. Thus, this study developed a computer-aided stormwater model that incorporates a green wall to investigate its effectiveness as an urban drainage system. The effectiveness of employing a green wall as a stormwater component is tested using USEPA SWMM 5.1 and the embedded bioretention cell interface. Four simulation models according to different conditions and precipitation input are tested, compared and discussed. The conditions include investigation of different soil types, average recurrence interval (ARI) and storm duration with design and observed rainfall. The results reveal that synthesis precipitation data, used in Scenario 1, 2 and 3, decreased runoff by more than half, at 55% on condition of one-year ARI and 5 minutes of storm duration. Meanwhile, Scenario 4 also shows a repetition of runoff reduction by half after the integration of the green wall using the observed rainfall data. Thus, it is verified that a green wall can be effectively used as an urban drainage system in reducing surface runoff.
Information on situation of air pollution is critically needed as input in four disciplines of research including risk management, risk evaluation, environmental epidemiology, as well as for status and trend analysis. Two normal practices were identified to evaluate daily air pollution situation; first, pollution magnitude has been treated as the common indicator, and second, the analysis was often conducted based on hourly average data. However, the information on the magnitude level alone to represent the pollution condition based on a rigid point data such as the average was seen as insufficient. Thus, to fill the gap, this study was conducted based on continuously measured data in the form of curves, which is also known as functional data, whereby pollution duration is emphasised. A statistical method based on curve ranking was used in the investigation. The application of the method at Klang, Petaling Jaya and Shah Alam air quality monitoring stations located in the Klang Valley, Malaysia, has shown that pollution duration decreases as the magnitude increases. Shah Alam has the longest pollution duration at low and medium magnitude levels. Meanwhile, all the three stations experienced quite a similar length of average pollution duration for the high magnitude level, that is, about 2.5 days. It was also shown that the occurrence of PM10 pollution at the area is significantly not random.
The aim of this study was to evaluate the value of MRI spectroscopy and association with the altered glucose metabolism on 18-FDG PET/CT in patients with suspicious breast cancer. Eight selected breast cancer patients with BIRADS 4 or 5 on mammogram were recruited and patients underwent 18F-FDG PET/CT MRI (spectroscopy). The standardise uptake value (SUVmax) was analysed to determine the degree of the altered glucose metabolism on the PET. The metabolites of tumor lesions were measured using in vivo proton MR spectroscopy (MRS) of the breast. There were eight females with a mean age of 55.3±12.2 years with a biopsy result of invasive ductal carcinoma (2), lobular carcinoma (1) and benign lesion (5). There was a significant difference between the mean of the malignant tumour (SUVmax 4.28±3.74 g/ml) and the mean of the benign tumour (SUVmax: 2.33±0.9 g/ml). On the per-lesional basis of the MRS correlate with SUVmax, the suspicious breast tissue exhibited raised creatinine metabolites (mean: 3.39±0.54u) with significant correlation SUVmax mean 3.06±2.34 as compared to N-acetyl Aspartate (NAA), (mean: 2.84±0.99u) and choline (mean: 2.46± 0.70 u). This study showed that high SUVmax was associated with malignant cancer and the high creatinine metabolite that correlated with the SUVmax could potentially be utilised as a surrogate marker in detecting breast cancer.
Takaful, the Islamic alternative to conventional insurance, is based on the concept of social solidarity, cooperation and mutual indemnification of losses of members. The ‘transparency’ offered in the Takaful system will eliminates the elements of gharar (uncertainty), maisir (gambling) and riba (usury). Due to the dynamicity and complexity of cash flows in the Takaful system, the application of system dynamic approach is used in order to discover any possible internal and external impacts in the assumptions used in determining contributions rate from the participants. The traditional approach, which is the deterministic approach, has limitations where changes of the actual experience may cause operators to stop issuing the contract or product. Using system dynamic, these possible effects from the actual experience can be determined in terms of the amounts transferred to shareholder’s fund and results obtained can assist the management to decide which assumptions to be used so that the operators will continue solvent and making profit at the same time. The results of System Dynamic simulation analysis in this paper represent the impacts of component changes in the Takaful model. The results can be used as decision tools for the Takaful operators to determine the best assumptions and strategies in order to maximise their profits.
Neurocomputing has been adjusted effectively in time series forecasting activities, yet the vicinity of exceptions that frequently happens in time arrangement information might contaminate the system preparing information. This is because of its capacity to naturally realise any example without earlier suspicions and loss of sweeping statement. In principle, the most widely recognised calculation for preparing the system is the backpropagation (BP) calculation, which inclines toward minimisation of standard slightest squares (OLS) estimator, particularly the mean squared mistake (MSE). Regardless, this calculation is not by any stretch of the imagination strong when the exceptions are available, and it might prompt bogus expectation of future qualities. In this paper, we exhibit another calculation which controls the firefly algorithm of least median squares (FFA-LMedS) estimator for neural system nonlinear autoregressive moving average (ANN-NARMA) model enhancement to provide betterment for the peripheral issue in time arrangement information. Moreover, execution of the solidified model in correlation with another hearty ANN-NARMA models, utilising M-estimators, Iterative LMedS and Particle Swarm Optimisation on LMedS (PSO-LMedS) with root mean squared blunder (RMSE) qualities, is highlighted in this paper. In the interim, the actual monthly information of Malaysian Aggregate, Sand and Roof Materials value was taken from January 1980 to December 2012 (base year 1980=100) with various levels of anomaly issues. It was found that the robustified ANN-NARMA model utilising FFA-LMedS delivered the best results, with the RMSE values having almost no mistakes at all in all the preparation, testing and acceptance sets for every single distinctive variable. Findings of the studies are hoped to assist the regarded powers including the PFI development tasks to overcome cost overwhelms.
PM10 has been identified as being a common problem in Malaysia and many other countries all over the world. A Markov chain probability model is found to fit the average daily PM10 concentrations data of urban station (Shah Alam) and background area station (Jerantut) in Malaysia. This study aims to identify the occurrence of polluted and non-polluted days affected by PM10 concentrations based on data for 12 years’ period (2002-2013). The first order transition probability matrix of a Markov chain model and a two-state Markov chain, which are polluted days (1) and non-polluted days (0), were used for this purpose. The threshold value used in this study is referring to WHO 2006 guidelines (50µgm-3). Results of the analysis shows that there is a high probability that the next day event depends on what has happened on the previous day. The recurrence of the polluted day for Shah Alam is 4-5 days, while 2-3 days for Jerantut. By fitting the first order of Markov chain model, the results show that the higher order of Markov chain model is needed in order to get the best fitted distribution of polluted events at these two monitoring stations. Thus, the prediction of PM10 concentrations event can be made by considering the conditions of the previous day event;
Feature selection has been widely applied in many areas such as classification of spam emails, cancer cells, fraudulent claims, credit risk, text categorisation and DNA microarray analysis. Classification involves building predictive models to predict the target variable based on several input variables (features). This study compares filter and wrapper feature selection methods to maximise the classifier accuracy. The logistic regression was used as a classifier while the performance of the feature selection methods was based on the classification accuracy, Akaike information criteria (AIC), Bayesian information criteria (BIC), Area Under Receiver operator curve (AUC), as well as sensitivity and specificity of the classifier. The simulation study involves generating data for continuous features and one binary dependent variable for different sample sizes. The filter methods used are correlation based feature selection and information gain, while the wrapper methods are sequential forward and sequential backward elimination. The simulation was carried out using R, an open-source programming language. Simulation results showed that the wrapper method (sequential forward selection and sequential backward elimination) methods were better than the filter method in selecting the correct features.
This paper is an attempt to perceive and order guns using a two-layer neural system model taking into account a feedforward backpropagation calculation. Numerical properties from the joined pictures were utilised for enhanced gun characterisation execution. Inputs of the system model were 747 pictures blackmailed from the discharging pin impression of five differing guns model, Parabellum Vector SPI 9mm. Components created from the dataset were further grouped into preparation set (523 components), testing set (112 components) and acceptance set (112 components). Under managed learning, exact results exhibited that a two-layer BPNN of 11-11-5 arrangement, with tansig/purelin exchange capacities and a “trainlm” preparing calculation, had productively delivered 87% right aftereffect of grouping. The order result serves to be progressed and contrasted with the previous works. Finally, the joined picture districts can offer some accommodating data on the grouping of gun.
This paper presents the application of active contours region-based method of image segmentation to Computed Tomography (CT) images. Previous researchers applied this region based method on Magnetic Resonance Image (MRI), in vivo images and synthetic images which contain intensity inhomogeneities. In this paper, a different modality known as Computed Tomography (CT) scan was applied. CT scan also produces images containing intensity inhomogeneity, and it is predicted that this method provide good segmentation results. The main objective of applying this method is to check its applicability on CT images. The segmentation process begins by finding the area of interest (black region). Results from this experiment are then used in estimating time of death. Experimental results show that this method has successfully segmented the black region when some parameters changed, provided that the regions are closed to each other. If the black regions are located far from each other, then this method will only segment certain areas.
One of the ways to calculate dividend for an investment is by using average lowest balance (ALB) concept. The existing calculation of dividend based on ALB concept can only be done yearly. This paper discusses on the development of a general formula to calculate the accumulated amount for any period of time, based on the ALB concept that considers different yearly dividend rates. The patterns for each variable and coefficient for the calculated yearly accumulated amount were analysed. The general forms of each variable and coefficient were then combined to form the general formula for calculating the accumulated amount. Validity of the general formula is confirmed by calculating the percentage errors and proven by using mathematical induction.