In this paper, the problem of forced convection flow of micropolar fluid of
lighter density impinging orthogonally on another heavier density of micropolar fluid
on a stretching surface is investigated. The boundary layer governing equations are
transformed from partial differential equations into a system of nonlinear ordinary
differential equations using similarity transformation and solved numerically using dsolve
function in maple software version 2016. The velocity, microrotation and temperature of
micropolar fluid are analyzed. It is found that both upper fluid and lower fluid display
opposite behaviour when micropolar parameter k various with strong concentration
n = 0, pr = 7 and stretching parameter = 0.5. The results also show that stretching
surface exert the force that increasing the velocity of micropolar fluid.
In this paper, we consider the system of Volterra-Fredholm integral equations
of the second kind (SVFI-2). We proposed fixed point method (FPM) to solve
SVFI-2 and improved fixed point method (IFPM) for solving the problem. In addition,
a few theorems and two new algorithms are introduced. They are supported by
numerical examples and simulations using Matlab. The results are reasonably good
when compared with the exact solutions.
In this paper, extended Runge-Kutta fourth order method for directly solving the fuzzy logistic problem is presented. The extended Runge-Kutta method has lower number of function evaluations, compared with the classical Runge-Kutta method. The numerical robustness of the method in parameter estimation is enhanced via error minimization in predicting growth rate and carrying capacity. The results of fuzzy logistic model with the estimated parameters have been compared with population growth data in Malaysia, which indicate that this method is more accurate that the data population. Numerical example is given to illustrate the efficiency of the proposed model. It is concluded that robust parameter estimation technique is efficient in modelling population growth.
Logging activity is one of the most important activities for tropical countries
including Malaysia, as it produces quality trees for papers. One of the important tree
species is the Acacia Mangium which it produces a soft tree for papermaking enterprises.
The papers are exported to Europe and countries which have high demand for paper
due to the rapid development of the printing industry. Thus we analyzed the height for
individual trees. We investigate the maximum height of the trees from 1990 to 2006
and we fit the data using extreme value model. Some of the data are missing and three
imputation methods we used to solve this problem.
Price stability is one of the main policy objectives that is targeted by policymakers in many countries. Price uncertainty occurs due to the changes in market structure and consumer preference and expectation, which may affect price stability. In this study, the researchers aimed to examine the effects of price uncertainty of consumer price disaggregation in Malaysian sectors. To be specific, the researchers were seeking to discover on how domestic and global commodity prices can affect sectoral Consumer Price Index (CPI) on price inflation in Malaysia and most importantly, whether the effect is different for economic sectors in Malaysia. In addition, the effects of other factors (i.e., internal and external factors) on Malaysian sectoral CPI inflation were also studied. The threshold generalized autoregressive conditional heteroscedasticity (TGARCH) model was used to generate the price uncertainties. For the purpose of analysis, the threshold regression approach was applied based on time series of each single sector, followed by a combination of panel data of all sectors. The results differed across sectors, revealing that the impact of price uncertainties was determined by the sensitivity of each sector towards the price uncertainties. The effect of price increase is larger than the effect of price decrease. Price fluctuations were obvious in sectors that were dependent on consumer price or commodity price. Exchange rate and oil price inflation had also greatly influenced the CPI inflation.
Rainfall is an interesting phenomenon to investigate since it is directly related
to all aspects of life on earth. One of the important studies is to investigate and under-
stand the rainfall patterns that occur throughout the year. To identify the pattern, it
requires a rainfall curve to represent daily observation of rainfall received during the year.
Functional data analysis methods are capable to convert discrete data intoa function that
can represent the rainfall curve and as a result, try to describe the hidden patterns of the
rainfall. This study focused on the distribution of daily rainfall amount using functional
data analysis. Fourier basis functions are used for periodic rainfall data. Generalized
cross-validation showed 123 basis functions were sufficient to describe the pattern of daily
rainfall amount. North and west areas of the peninsula show a significant bimodal pattern
with the curve decline between two peaks at the mid-year. Meanwhile,the east shows uni-
modal patterns that reached a peak in the last three months. Southern areas show more
uniform trends throughout the year. Finally, the functional spatial method is introduced
to overcome the problem of estimating the rainfall curve in the locations with no data
recorded. We use a leave one out cross-validation as a verification method to compare
between the real curve and the predicted curve. We used coefficient of basis functions
to get the predicted curve. It was foundthatthe methods ofspatial prediction can match
up with theexistingspatialpredictionmethodsin terms of accuracy,but it isbetterasthe new
approach provides a simpler calculation.
Analyzed the effects of thermal radiation, chemical reaction, heat gener-
ation/absorption, magnetic and electric fields on unsteady flow and heat transfer of
nanofluid. The transport equations used passively controlled. A similarity solution is
employed to transformed the governing equations from partial differential equations to
a set of ordinary differential equations, and then solve using Keller box method. It was
found that the temperature is a decreasing function with the thermal stratification due to
the fact the density of the fluid in the lower vicinity is much higher compared to the upper
region, whereas the thermal radiation, viscous dissipation and heat generation enhanced
the nanofluid temperature and thermal layer thickness.
Symmetric methods such as the implicit midpoint rule (IMR), implicit trapezoidal
rule (ITR) and 2-stage Gauss method are beneficial in solving Hamiltonian problems
since they are also symplectic. Symplectic methods have advantages over non-symplectic
methods in the long term integration of Hamiltonian problems. The study is to show
the efficiency of IMR, ITR and the 2-stage Gauss method in solving simple harmonic
oscillators (SHO). This study is done theoretically and numerically on the simple harmonic
oscillator problem. The theoretical analysis and numerical results on SHO problem
showed that the magnitude of the global error for a symmetric or symplectic method
with stepsize h is linearly dependent on time t. This gives the linear error growth when
a symmetric or symplectic method is applied to the simple harmonic oscillator problem.
Passive and active extrapolations have been implemented to improve the accuracy of the
numerical solutions. Passive extrapolation is observed to show quadratic error growth
after a very short period of time. On the other hand, active extrapolation is observed to
show linear error growth for a much longer period of time.
In this paper, the combined influences of biotic interactions, environmental components and harvesting strategy on the spread of Hantavirus are investigated. By employing a multi-species model consisting of (susceptible and infected) rodents and alien species, we show that interspecific competition from alien species has an effect in reducing the spread of infection, and this species could be employed as a potential biocontrol agent. Our analysis using numerical continuation and simulation also reveals the conditions under which Hantavirus infection occurs and disappears as the environmental conditions and the intensity of harvesting change. Without harvesting, infection emerges when environments are conducive. Inclusion of moderate harvesting in favourable environments can lead to disappearance of infection among rodent species. However, as the intensity of harvesting increases, this situation can cause extinction of all rodents species and consequently, jeopardise biodiversity. Overall, our results demonstrate how the interplay of different factors can combine to determine the spread of infectious diseases.
In this paper we consider a harvesting model of predator-prey fishery in which
the prey is directly infected by some external toxic substances. The toxic infection is
indirectly transmitted to the predator during the feeding process. The model is a modified
version from the classic Lotka-Volterra predator-prey model. The stability and bifurcation
analyses are addressed. Numerical simulations of the model are performed and bifurcation
diagrams are studied to investigate the dynamical behaviours between the predator and
the prey. The effects of toxicity and harvesting on the stability of steady states found in
the model are discussed.
The effect of oil shock on the global economy is evident through many studies. However, the effect is heterogeneous over time. One of the reasons that lead to such different impacts is due to the oil source that is either the oil shock is demand or supply- driven. Applying the structural vector autoregressive (SVAR) model to generate the three oil shocks based on the three oil sources (oil supply, oil demand and oil specific- demand), we extended the examination on the effect of oil shock on the global economy using the threshold regression. Our results reveal the threshold effects of oil directly and indirectly on the global economy. The impacts of oil shocks differ across sectors, implying oil intensity, as well as oil sources, are the factors that determine the impact of oil shocks on the global economy. Overall, the oil specific-demand shock is more influential among the three oil shocks. Hence, the global economy is oil demand-driven. Besides that, the impact of oil is relatively large in the energy sector when compared to the non-energy sector and precious metals industry. Despite that, the impact of oil shocks is small if compared to the non-oil shocks such as exchange rate changes and global consumer price inflation shock. Consequently, non-oil shocks are the main determinants of the global economic fluctuation. The study leads to a better understanding of the transmission of oil shock and its sources, the interaction between oil and economic indicators and the policy implication due to oil dependency/ intensity.
It has come to attention that Malaysia have been aiming to build its own
nuclear power plant (NPP) for electricity generation in 2030 to diversify the national
energy supply and resources. As part of the regulation to build a NPP, environmental
risk assessment analysis which includes the atmospheric dispersion assessment has to
be performed as required by the Malaysian Atomic Energy Licensing Board (AELB)
prior to the commissioning process. The assessment is to investigate the dispersion of
radioactive effluent from the NPP in the event of nuclear accident. This article will focus
on current development of locally developed atmospheric dispersion modeling code
based on Gaussian Plume model. The code is written in Fortran computer language
and has been benchmarked to a readily available HotSpot software. The radionuclide
release rate entering the Gaussian equation is approximated to the value found in the
Fukushima NPP accident in 2011. Meteorological data of Mersing District, Johor of
year 2013 is utilized for the calculations. The results show that the dispersion of radionuclide
effluent can potentially affect areas around Johor Bahru district, Singapore
and some parts of Riau when the wind direction blows from the North-northeast direction.
The results from our code was found to be in good agreement with the one
obtained from HotSpot, with less than 1% discrepancy between the two.
In this paper, we propose a method how to manage the convergence of
Newton’s method if its iteration process encounters a local extremum. This idea establishes
the osculating circle at a local extremum. It then uses the radius of the
osculating circle also known as the radius of curvature as an additional number of
the local extremum. It then takes that additional number and combines it with the
local extremum. This is then used as an initial guess in finding a root near to that
local extremum. This paper will provide several examples which demonstrate that the
proposed idea is successful and they perform to fulfill the aim of this paper.
The modelling of splicing systems is simulated by the process of cleaving and recombining DNA molecules with the presence of a ligase and restriction enzymes which are biologically called as endodeoxyribonucleases. The molecules resulting from DNA splicing systems are known as splicing languages. Palindrome is a sequence of strings that reads the same forward and backward. In this research, the splicing languages resulting from DNA splicing systems with one non-palindromic restriction enzyme are determined using the notation from Head splicing system. The generalisations of splicing languages for DNA splicing systems involving a cutting site and two non-overlapping cutting sites of one non-palindromic restriction enzyme are presented in the first and second theorems, respectively, which are proved using direct and induction methods. The result from the first theorem shows a trivial string which is the initial DNA molecule; while the second theorem determines a splicing language consisting of a set of resulting DNA molecules from the respective DNA splicing system.
The incorporation of non-linear pattern of early ages has led to new research
directions on improving the existing stochastic mortalitymodel structure. Several authors
have outlined the importance of encompassing the full age range in dealing with longevity
risk exposure, by not ignoring the dependence between young and old ages. In this study,
we consider the two extensions of the Cairns, Blake and Dowd model that incorporate the
irregularity profile seen at the mortality of lower ages, which are the Plat, and the O’Hare
and Li models respectively. The models’ performances in terms of in-sample fitting and
out-sample forecasts were examined and compared. The results indicated that the O’Hare
and Li model performs better as compared to the Plat model.
The well-known geostatistics method (variance-reduction method) is commonly used to determine the optimal rain gauge network. The main problem in geostatistics method to determine the best semivariogram model in order to be used in estimating the variance. An optimal choice of the semivariogram model is an important point for a good data evaluation process. Three different semivariogram models which are Spherical, Gaussian and Exponential are used and their performances are compared in this study. Cross validation technique is applied to compute the errors of the semivariograms. Rain-fall data for the period of 1975 – 2008 from the existing 84 rain gauge stations covering the state of Johor are used in this study. The result shows that the exponential model is the best semivariogram model and chosen to determine the optimal number and location of rain gauge station.
Abstract Demographers and actuaries are very much conscious of the trend of mortality in their own country or in the world in general. This is because mortality is the basis for longevity risk evaluation. Mortality is showing a declining trend and it is expected to further decline in the future. This will lead to continuous increase in life expectancy. Several stochastic models have been developed throughout the years to capture mortality and its variability. This includes Lee Carter (LC) model which has been extended by various researchers. This paper will be focusing on comparing LC model and another mortality model proposed by Cairns, Blake and Dowd (CBD). The LC uses the log of central rate of mortality and CBD uses logit of the mortality odds as dependent variable. Analysis of comparison is done using a few techniques including Akaike information criteria (AIC) and Bayesian information criterion (BIC). From the overall results, there is no model better than the other in every aspect tested. We illustrate this via visual inspection and in sample and outof sample analysis using Malaysian mortality data from 1980 to 2017.
Monthly data about oil production at several drilling wells is an example of
spatio-temporal data. The aim of this research is to propose nonlinear spatio-temporal
model, i.e. Feedforward Neural Network - VectorAutoregressive (FFNN-VAR) and FFNN
- Generalized Space-Time Autoregressive (FFNN-GSTAR), and compare their forecast
accuracy to linearspatio-temporal model, i.e. VAR and GSTAR. These spatio-temporal
models are proposed and applied for forecasting monthly oil production data at three
drilling wells in East Java, Indonesia. There are 60 observations that be divided to two
parts, i.e. the first 50 observations for training data and the last 10 observations for
testing data. The results show that FFNN-GSTAR(11) and FFNN-VAR(1) as nonlinear
spatio-temporal models tend to give more accurate forecast than VAR(1) and GSTAR(11)
as linear spatio-temporal models. Moreover, further research about nonlinear spatiotemporal
models based on neural networks and GSTAR is needed for developing new
hybrid models that could improve the forecast accuracy.
In this paper, Maxwell fluid over a flat plate for convective boundary layer
flow with pressure gradient parameter is considered. The aim of this study is to compare
and analyze the effects of the presence and absence of λ (relaxation time), and also the
effects of m (pressure gradient parameter) and Pr (Prandtl number)on the momentum
and thermal boundary layer thicknesses. An approximation technique namely Homotopy
Perturbation Method (HPM) has been used with an implementation of Adam and Gear
Method’s algorithms. The obtained results have been compared for zero relaxation time
and also pressure gradient parameter with the published work of Fathizadeh and Rashidi.
The current outcomes are found to be in good agreement with the published results.
Physical interpretations have been given for the effects of the m, Pr and β (Deborah
number) with λ. This study will play an important role in industrial and engineering
applications.
Let g be a finite group. The probability of a random pair of elements in g are
said to be co-prime when the greatest common divisor of order x and y where x and y in
g, is equal to one. Meanwhile the co-prime graph of a group is defined as a graph whose
vertices are elements of g and two distinct vertices are adjacent if and only if the greatest
common divisor of order x and y is equal to one. In this paper, the co-prime probability
and its graphs such as the types and the properties of the graph are determined.