The proposed modified methods of Cramer's rule consider the column vector as well as the coefficient matrix concurrently in the linear system. The modified methods can be applied since Cramer's rule is typically known for solving the linear systems in $WZ$ factorization to yield Z-matrix. Then, we presented our results to show that there is no tangible difference in performance time between Cramer's rule and the modified methods in the factorization from improved versions of MATLAB. Additionally, the Frobenius norm of the modified methods in the factorization is better than using Cramer's rule irrespective of the version of MATLAB used.
Preventive maintenance (PM) planning becomes a crucial issue in the real world of the manufacturing process. It is important in the manufacturing industry to maintain the optimum level of production and minimize its investments. Thus, this paper focuses on multiple jobs with a single production line by considering stochastic machine breakdown time. The aim of this paper is to propose a good integration of production and PM schedule that will minimize total completion time. In this study, a hybrid method, which is a genetic algorithm (GA), is used with the Monte Carlo simulation (MCS) technique to deal with the uncertain behavior of machine breakdown time. A deterministic model is adopted and tested under different levels of complexity. Its performance is evaluated based on the value of average completion time. The result clearly shows that the proposed integrated production with PM schedule can reduce the average completion time by 11.68% compared to the production scheduling with machine breakdown time.
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.
Cardiovascular disease (CVD) includes coronary heart disease, cerebrovascular disease (stroke), peripheral artery disease, and atherosclerosis of the aorta. All females face the threat of CVD. But becoming aware of symptoms and signs is a great challenge since most adults at increased risk of cardiovascular disease (CVD) have no symptoms or obvious signs especially in females. The symptoms may be identified by the assessment of their risk factors. The Bayesian approach is a specific way in dealing with this kind of problem by formalizing a priori beliefs and of combining them with the available observations. This study aimed to identify associated risk factors in CVD among female patients presenting with ST Elevation Myocardial Infarction (STEMI) using Bayesian logistic regression and obtain a feasible model to describe the data. A total of 874 STEMI female patients in the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry year 2006-2013 were analysed. Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied in the univariate and multivariate analysis. Model performance was assessed through the model calibration and discrimination. The final multivariate model of STEMI female patients consisted of six significant variables namely smoking, dyslipidaemia, myocardial infarction (MI), renal disease, Killip class and age group. Females aged 65 years and above have higher incidence of CVD and mortality is high among female patients with Killip class IV. Also, renal disease was a strong predictor of CVD mortality. Besides, performance measures for the model was considered good. Bayesian logistic regression model provided a better understanding on the associated risk factors of CVD for female patients which may help tailor prevention or treatment plans more effectively.
Replicated linear functional relationship model is often used to describe
relationships between two circular variables where both variables have error terms and
replicate observations are available. We derive the estimate of the rotation parameter
of the model using the maximum likelihood method. The performance of the proposed
method is studied through simulation, and it is found that the biasness of the estimates
is small, thus implying the suitability of the method. Practical application of the
method is illustrated by using a real data set.
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.
Heat and mass transfer of MHD boundary-layer flow of a viscous incompress-
ible fluid over an exponentially stretching sheet in the presence of radiation is investi-
gated. The two-dimensional boundary-layer governing partial differential equations are
transformed into a system of nonlinear ordinary differential equations by using similarity
variables. The transformed equations of momentum, energy and concentration are solved
by Homotopy Analysis Method (HAM). The validity of HAM solution is ensured by com-
paring the HAM solution with existing solutions. The influence of physical parameters
such as magnetic parameter, Prandtl number, radiation parameter, and Schmidt num-
ber on velocity, temperature and concentration profiles are discussed. It is found that
the increasing values of magnetic parameter reduces the dimensionless velocity field but
enhances the dimensionless temperature and concentration field. The temperature dis-
tribution decreases with increasing values of Prandtl number. However, the temperature
distribution increases when radiation parameter increases. The concentration boundary
layer thickness decreases as a result of increase in Schmidt number.
Topological indices are numerical values that can be analysed to predict the chemical properties of the molecular structure and the topological indices are computed for a graph related to groups. Meanwhile, the conjugacy class graph of is defined as a graph with a vertex set represented by the non-central conjugacy classes of . Two distinct vertices are connected if they have a common prime divisor. The main objective of this article is to find various topological indices including the Wiener index, the first Zagreb index and the second Zagreb index for the conjugacy class graph of dihedral groups of order where the dihedral group is the group of symmetries of regular polygon, which includes rotations and reflections. Many topological indices have been determined for simple and connected graphs in general but not graphs related to groups. In this article, the Wiener index and Zagreb index of conjugacy class graph of dihedral groups are generalized.
Life table is a table that shows mortality experience of a nation. However, in Malaysia, the information in this table is provided in the five-years age groups (abridged) instead of every one-year age. Hence, this study aims to estimate the one-year age mor- tality rates from the abridged mortality rates using several interpolation methods. We applied Kostaki method and the Akima spline method to five sets of Malaysian group mortality rates ranging from period of 2012 to 2016. The result were then compared with the one-year mortality rates. We found that the method by Akima is the best method for Malaysian mortality experience as it gives the least minimum of sum of square errors. The method does not only provide a good fit but also, shows a smooth mortality curve.
Regression is one of the basic relationship models in statistics. This paper focuses on the formation of regression models for the rice production in Malaysia by analysing the effects of paddy population, planted area, human population and domestic consumption. In this study, the data were collected from the year 1980 until 2014 from the website of the Department of Statistics Malaysia and Index Mundi. It is well known that the regression model can be solved using the least square method. Since least square problem is an unconstrained optimisation, the Conjugate Gradient (CG) was chosen to generate a solution for regression model and hence to obtain the coefficient value of independent variables. Results show that the CG methods could produce a good regression equation with acceptable Root Mean-Square Error (RMSE) value.
The hydromagnetic mixed convection flow of Cassonnano fluid under the influence of chemical reaction,thermal radiation and heat generation or absorption is investigated. The flow is induced due to unsteady nonlinearly stretching sheet saturated in a porous medium. The governing nonlinear coupled partial differential equations are converted into the system of coupled ordinary differential equations using similarity transformations and then solved numerically via Keller box method. The effects of pertinent parameters on velocity, temperature and nanoparticles concentration as well as wall shear stress, heat and mass transfer rate are analyzed and displayed graphically. The results for skin friction coefficient and local Nusselt number are compared with previously published work and found to be in good agreement. Findings demonstrate that increase in Casson parameter enhanced the friction factor and heat transfer rate. It is noticed that the heat transfer rate is declined with increment in Brownian motion and thermophoresis parameters. The nanoparticles concentration is seen to be higher in generative chemical reaction and opposite effect is observed in destructive chemical reaction. Increase in unsteadiness parameter decreased the fluid velocity, temperature and nanoparticles concentration. The magnitude of wall shear stress is also reduced with increase in unsteadiness and porous medium parameters.
Subsea cable laying is a risky and challenging operation faced by engineers, due to many uncertainties arise during the operation. In order to ensure that subsea cables are laid out diligently, the analysis of subsea cable tension during the laying operation is crucial. This study focuses on the fatigue failure of cables that will cause large hang-off loads based on catenary configuration after laying operation. The presented problem was addressed using mathematical modelling with consideration for a number of defining parameters, which include external forces such as current velocity and design parameters such as cable diameter. There were two types of subsea cable tension analyses studied: tensional analysis of catenary configurations and tensional analysis of lazy wave configurations. The latter involved a buoyancy module that was incorporated in the current catenary configuration that reduced subsea cable tension and enhanced subsea cable lifespan. Both analyses were solved using minimization through the gradient- based approach concerning on the tensional analysis of the subsea cable in different configurations. Lazy wave configurations were shown to successfully reduce cable tension, especially at the hang-off section.
Inventory Routing Problem (IRP) has been continuously developed and improved due to pressure from global warming issue particularly related to greenhouse gases (GHGs) emission. The burning of fossil fuel for transportations such as cars, trucks, ships, trains, and planes primarily emits GHGs. Carbon dioxide (CO2) from burning of fossil fuel to power transportation and industrial process is the largest contributor to global GHGs emission. Therefore, the focus of this study is on solving a multi-period inventory routing problem (MIRP) involving carbon emission consideration based on carbon cap and offset policy. Hybrid genetic algorithm (HGA) based on allocation first and routing second is used to compute a solution for the MIRP in this study. The objective of this study is to solve the proposed MIRP model with HGA then validate the effectiveness of the proposed HGA on data of different sizes. Upon validation, the proposed MIRP model and HGA is applied on real-world data. The HGA is found to be able to solve small size and large size instances effectively by providing near optimal solution in relatively short CPU execution time.
Recently, oil refining industry is facing with lower profit margin due to un-
certainty. This causes oil refinery to include stochastic optimization in making a decision
to maximize the profit. In the past, deterministic linear programming approach is widely
used in oil refinery optimization problems. However, due to volatility and unpredictability
of oil prices in the past ten years, deterministic model might not be able to predict the
reality of the situation as it does not take into account the uncertainties thus, leads to
non-optimal solution. Therefore, this study will develop two-stage stochastic linear pro-
gramming for the midterm production planning of oil refinery to handle oil price volatility.
Geometric Brownian motion (GBM) is used to describe uncertainties in crude oil price,
petroleum product prices, and demand for petroleum products. This model generates the
future realization of the price and demands with scenario tree based on the statistical
specification of GBM using method of moment as input to the stochastic programming.
The model developed in this paper was tested for Malaysia oil refinery data. The result
of stochastic approach indicates that the model gives better prediction of profit margin.
Blood flow through a bifurcated artery with the presence of an overlapping stenosis located at parent’s arterial lumen under the action of a uniform external magnetic field is studied in this paper. Blood is treated as an electrically conducting fluid which exhibits the Magnetohydrodynamics principle and it is characterized by a Newtonian fluid model. The governing equations are discretized using a stabilization technique of finite element known as Galerkin least-squares. The maximum velocity and pressure drop evaluated in this present study are compared with the results found in previous literature and COMSOL Multiphysics. The solutions found in a satisfactory agreement, thus verify the source code is working properly. The effects of dimensionless parameters of Hartmann and Reynolds numbers in the fluid’s velocity and pressure are examined in details with further scientific discussions.
An accurate forecasting of tropospheric ozone (O3) concentration is benefi-
cial for strategic planning of air quality. In this study, various forecasting techniques are
used to forecast the daily maximum O3 concentration levels at a monitoring station
in the Klang Valley, Malaysia. The Box-Jenkins autoregressive integrated movingaverage
(ARIMA) approach and three types of neural network models, namely, backpropagation
neural network, Elman recurrent neural network and radial basis function
neural network are considered. The daily maximum data, spanning from 1 January
2011 to 7 August 2011, was obtained from the Department of Environment, Malaysia.
The performance of the four methods in forecasting future values of ozone concentrations
is evaluated based on three criteria, which are root mean square error (RMSE),
mean absolute error (MAE) and mean absolute percentage error (MAPE). The findings
show that the Box-Jenkins approach outperformed the artificial neural network
methods.
Tumour cells behave differently than normal cells in the body. They grow and
divide in an uncontrolled manner (actively proliferating) and fail to respond to signal.
However, there are cells that become inactive and reside in quiescent phase (G0). These
cells are known as quiescence cells that are less sensitive to drug treatments (radiotherapy
and chemotherapy) than actively proliferation cells. This paper proposes a new mathe-
matical model that describes the interaction of tumour growth and immune response by
considering tumour population that is divided into three different phases namely inter-
phase, mitosis and G0. The model consists of a system of delay differential equations
where the delay, represents the time for tumour cell to reside interphase before entering
mitosis phase. Stability analysis of the equilibrium points of the system was performed
to determine the dynamics behaviour of system. Result showed that the tumour popu-
lation depends on number of tumour cells that enter active (interphase and mitosis) and
G0phases. This study is important for treatment planning since tumour cell can resist
treatment when they refuge in a quiescent state.
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.
In numerical methods, boundary element method has been widely used to solve
acoustic problems. However, it suffers from certain drawbacks in terms of computational
efficiency. This prevents the boundary element method from being applied to large-scale
problems. This paper presents proposal of a new multiscale technique, coupled with
boundary element method to speed up numerical calculations. Numerical example is
given to illustrate the efficiency of the proposed method. The solution of the proposed
method has been validated with conventional boundary element method and the proposed
method is indeed faster in computation.
Invadopodia are finger-like protrusions located at subcellular membrane which can lead to cancer cell invasion. The formation of invadopodia involves several steps such as actin polymerizations, degradation of extracellular matrix which produce ligand and signal stimulation that is occurred from the binding of ligand with epidermal growth factor receptor. In this paper, a mathematical model of signal transduction is investigated. Both signal and ligand are represented by Laplace equation with Dirichlet boundary condition for each region. The cell membrane is treated as free boundary surface to separate any activity that occurred in intracellular and extracellular regions. The motion of the interface is taken as gradient of interior signal and the cell membrane is set as zero level set function. The problem is solved numerically using finite difference scheme of upwind, interpolation and extrapolation methods. The results showed that the formation of invadopodia is formed when protrusions exist on the cell membrane.