International Journal of Modern Physics: Conference Series

The number of sequenced genomes of Archaea, Bacteria, and Fungi accumulates rapidly. Several thousands genomes of these unicellular organisms will be available in a few years. Due to the extremely large difference in genome size and gene content it is difficult to use the traditional alignment-based method to infer phylogeny from the genomes. An alignment-free and whole-genome-based approach called CVTree has been developed and successfully applied to these organisms. As CVTree has been successfully applied to genomes of viruses, chloroplasts, Bacteria, Archaea and fungi, in this brief review we will mainly touch on some mathematical problems related to the foundation of the new approach, including a few yet unsolved problems, such as the violation of the triangular inequalities of the dissimilarity measure used in the CVTree method.

The majority of viruses have protein containers, called capsids, in which proteins are arranged with icosahedral symmetry. The capsids of these viruses follow structural blueprints that can be modelled as subsets of 3-dimensional aperiodic lattices called quasicrystals. These, in turn, can be obained by projection from 6-dimensional Bravais lattices. In this work we apply the crystallographic theory of phase transitions to these 6D lattices, and via projection of these results derive information on the structural transitions of viruses important for infection.

In present paper, we discuss the spectral methods of measurement of the degree of speech and/or quality of sound by comparing the coefficient of performance indicators depending on energy distributions, ratio of energy of the fundamental tone and energy of overtones. Such a method is very efficient for string oscillation with different initial conditions and it is useful for justification of applications of Fourier analysis in plastic surgery in treatment of some medical diseases.

Kangkong, especially the upland type (Ipomoea reptans) is popularly consumed as a vegetable dish in the South East Asian countries for its quality related to Vitamins (A and C) and crude fiber contents. Higher fiber contents would prevent from the occurrence of colon cancer and diverticular disease. With young stem edible portion, its cell number and size contribute to the stem crude fiber content. The mathematical approach of allometry of cell size, number, and fiber content of stem could be used in determining the 'best' plant density pressure in producing the quality young stem to be consumed. Basically, allometry is the ratio of relative increment (growth or change) rates of two parameters, or the change rate associated to the log of measured variables relationship. Kangkog grown equal or lower than 55 plants m^-2 produced bigger individual plant and good quality (physical) kangkong leafy vegetable, but with lower total yield per unit area as compared to those grown at higher densities.

Cocoa pod growth modelling are useful in crop management, pest and disease management and yield forecasting. Recently, the Beta Growth Function has been used to determine the pod growth model due to its unique for the plant organ growth which is zero growth rate at both the start and end of a precisely defined growth period. Specific pod size (7cm to 10cm in length) is useful in cocoa pod borer (CPB) management for pod sleeving or pesticide spraying. The Beta Growth Function is well-fitted to the pods growth data of four different cocoa clones under non-linear function with time (t) as its independent variable which measured pod length and diameter weekly started at 8 weeks after fertilization occur until pods ripen. However, the same pod length among the clones did not indicate the same pod age since the morphological characteristics for cocoa pods vary among the clones. Depending on pod size for all the clones as guideline in CPB management did not give information on pod age, therefore it is important to study the pod age at specific pod sizes on different clones. Hence, Newton Raphson method is used to solve the non-linear equation of the Beta Growth Function of four different group of cocoa pod at specific pod size.

Data envelopment analysis (DEA) is an excellent approach for evaluating the performance of decision making units (DMUs) that use multiple inputs to produce multiple outputs. This research utilizes the DEA to analyze the operating efficiency of Caspian cattle feedlot farms in Iran. The inputs utilized by the farms are number of calve, number of labors, total metabolizable energy intake, total crude protein intake and total cost of hygiene-treatment of calve; and the output considered is total live weigh gain of calve. By using two DEA models, the efficiency score for each farm is calculated and the efficient farms are ranked.

A biomechanics model of six-link kinematic chain of human body is developed by using Kane's method. The kinematic data comprise of six segments; foot, calf, thigh, trunk, upper arm and forearm, are obtained through data collection of walking, running and jumping using the Vicon Nexus system. The motion capture system uses 12 Vicon MX-3+ cameras and 12 Vicon MX-F40 cameras, two DV (50 Hz) cameras and a force plate (100 Hz). Inverse dynamics approach is used to obtain the unknown value of torques produced by joint segments during walking, running and jumping activities. The results show that the largest value of torques produced occurs at the foot segment.

A 2-D model of a two-link kinematic chain is developed using two dynamics equations of motion, namely Kane's and Lagrange Methods. The dynamics equations are reduced to first order differential equation and solved using modified Euler and fourth order Runge Kutta to approximate the shoulder and elbow joint angles during a smash performance in badminton. Results showed that Runge-Kutta produced a better and exact approximation than that of modified Euler and both dynamic equations produced better absolute errors.

Bornean Hornbills (Family Bucerotidae) are omnivorous creatures, distinguished for their large size and large bill. In our study, only five out of eight species of Bornean hornbills were available. Our aims were to determine the taxonomic, morphological and sexual variations, among the species. Nine morphological features were measured from 83 specimens. Canonical Discriminant and Cluster analyses showed that the data were successfully clustered into 5 species. Logistic regression analyses showed that the diagnostic character differentiation is total length. Further results showed that males tend to be bigger than females.

Intelligence — algorithmic method of modeling of microkinetics for biotechnological processes (BTP) is considered. The generalized mathematical model of microkinetics of biotechnological processes received on the basis of the system approach is given. The question of regularization of a task of parametrical identification is considered.

The concept of splicing system was first introduced by Head in 1987 to model the biological process of DNA recombination mathematically. This model was made on the basis of formal language theory which is a branch of applied discrete mathematics and theoretical computer science. In fact, splicing system treats DNA molecule and the recombinant behavior by restriction enzymes and ligases in the form of words and splicing rules respectively. The notion of splicing systems was taken into account from different points of view by many mathematicians. Several modified definitions have been introduced by many researchers. In this paper, some properties of different kinds of splicing systems are presented and their relationships are investigated. Furthermore, these results are illustrated by some examples.

In this paper, we provide a family of ordinary and delay differential equations to describe the dynamics of tumor-growth and immunotherapy interactions. We explore the effects of adoptive cellular immunotherapy on the model and describe under what circumstances the tumor can be eliminated. The possibility of clearing the tumor, with a strategy, is based on two parameters in the model: the rate of influx of the effector cells, and the rate of influx of IL2. The critical tumor-growth rate, below which endemic tumor does not exist, has been found. One can use the model to make predictions about tumor-dormancy.

This research looks at the simulation of interval censored data when the survivor function of the survival time is known and attendance probability of the subjects for follow-ups can take any number between 0 to 1. Interval censored data often arise in the medical and biological follow-up studies where the event of interest occurs somewhere between two known times. Regardless of the methods used to analyze these types of data, simulation of interval censored data is an important and challenging step toward model building and prediction of survival time. The simulation itself is rather tedious and very computer intensive due to the interval monitoring of subjects at prescheduled times and subject's incomplete attendance to follow-ups. In this paper the simulated data by the proposed method were assessed using the bias, standard error and root mean square error (RMSE) of the parameter estimates where the survival time T is assumed to follow the Gompertz distribution function.

In this study a mathematical model for the release of drug from porous, nonswelling transdermal drug-delivery devices to a perfect sink is considered. The drug is postulated to diffuse in both the solvent-filled pores and the body of the polymer. The limit in which the dissolution of drug is the dominant process is considered and a moving boundary problem governing drug release is derived. This model is solved numerically under some spacial conditions. Furthermore, another limit case in which the dissolution process is not so rapid is investigated and analytical and numerical solutions based on Fourier series solution and finite differences method are derived. Finally, the numerical and analytical solutions are compared to show the ability of the proposed numerical procedures.

A model to describe the mechanism of conformational dynamics in secondary protein based on matter interactions is proposed. The approach deploys the lagrangian method by imposing certain symmetry breaking. The protein backbone is initially assumed to be nonlinear and represented by the Sine-Gordon equation, while the nonlinear external bosonic sources is represented by ϕ⁴ interaction. It is argued that the nonlinear source induces the folding pathway in a different way than the previous work with initially linear backbone. Also, the nonlinearity of protein backbone decreases the folding speed.

The internal motions of biomatter immersed in biofluid are investigated. The interactions between the fragments of biomatter and its surrounding biofluid are modeled using field theory. In the model, the biomatter is coupled to the gauge field representing the biofluid. It is shown that at non-relativistic limit various equation of motions, from the well-known Sine-Gordon equation to the simultaneous nonlinear equations, can be reproduced within a single framework.

Encoding proteins of amino acid sequence to predict classified into their respective families and subfamilies is important research area. However for a given protein, knowing the exact action whether hormonal, enzymatic, transmembranal or nuclear receptors does not depend solely on amino acid sequence but on the way the amino acid thread folds as well. This study provides a prototype system that able to predict a protein tertiary structure. Several methods are used to develop and evaluate the system to produce better accuracy in protein 3D structure prediction. The Bees Optimization algorithm which inspired from the honey bees food foraging method, is used in the searching phase. In this study, the experiment is conducted on short sequence proteins that have been used by the previous researches using well-known tools. The proposed approach shows a promising result.

Quadratic stochastic operators frequently arise in many models of mathematical genetics. We propose a constructive description of quadratic stochastic operators that allows a natural introduction of thermodynamics in studying some models of heredity. This construction allows one to elucidate the role of the absolute temperature in the analysis of quadratic stochastic operators.

The zinc transporters superfamily is divided into four subfamilies, and SLC39A is one of the subfamilies. The SLC39A subfamily has 9 members. Based on our computer searchers, all 9 sequences each contain 8 transmembranes domains. Since it is related to the zinc transporters superfamily, the SLC39A subfamily may have the same function that is to transport zinc ion. This paper focus on SLC39A13 studies and using the recombinant technology with CHO cells, it is shown that the recombinant protein, pcDNA5/FRT/V5-His-TOPO^®-SLC39A13, has 43kD molecular weight. A second study using immunofluorescence technique with MCF-7 cells, it is shown that the recombinant protein expresses intracellularly. Both studies demonstrate that SLC39A13 expresses in breast cancer cells line, therefore the gene has involvement in the development of breast cancer disease. In our computational studies which is divided into two; the homologous study and sequence analysis, both results are supporting our laboratory results. The homologous study using EMBL-EBI and UniProt tools concluded that SLC39A13 is a member to SLC39A subfamily and it is closely related to SLC39A7 member. Although the sequence analysis shows that the molecular weight of SLC39A13 is 38.35kD it is still comparable to our laboratory result. Separately, using Swiss-EMBnet tools, TMpred, has shown that SLC39A13 has 8 transmembranes domains similar to other family members of SLC39A subfamily. Another analysis using EMBL-EBI tools, PPsearch, shows that SLC39A13 has various protein motif such as the protein kinase C phospho, casein kinase II phospho, leucine zipper and ASN-glycosylation sites. These are the useful information that we need when we study its tertiary structure and simulation in the future.

The aim of this study was to develop a mathematical model of the arms during kayaking. Gordon's method has been used to develop the model. This model comprises of six kinematic chains of the arms that represent the right shoulder joint, right elbow joint, right wrist joint, left wrist joint, left elbow joint and left shoulder joint. The joints comprise of right upper arm, right lower arm, right hand-paddle, left hand-paddle, left lower arm and left upper arms.

The present paper studies the fundamental problem of the biomagnetic fluid flow in a channel under the influence of a spatially varying magnetic field. The solution of the problem is obtained using an improved finite difference method. This approach has successful handled the pressure of the flow which is the main problem in the finite difference method. Results concerning the velocity indicates that the presence of magnetic field appreciably influence the flow field. A distortion in terms of asymmetric flow profile was observed near the magnetic source. Also a vortex is demonstrated near the lower plate where the magnetic source is placed.

In the current work, the structure of the enzyme CC chemokine eotaxin-3 (1G2S) was chosen as a case study to investigate the effects of gas phase on the predicted protein conformation using molecular dynamics simulation. Generally, simulating proteins in the gas phase tend to suffer from various drawbacks, among which excessive numbers of protein-protein hydrogen bonds. However, current results showed that the effects of gas phase simulation on 1G2S did not amplify the protein-protein hydrogen bonds. It was also found that some of the hydrogen bonds which were crucial in maintaining the secondary structural elements were disrupted. The predicted models showed high values of RMSD, 11.5 Å and 13.5 Å for both vacuum and explicit solvent simulations, respectively, indicating that the conformers were very much different from the native conformation. Even though the RMSD value for the in vacuo model was slightly lower, it somehow suffered from lower fraction of native contacts, poor hydrogen bonding networks and fewer occurrences of secondary structural elements compared to the solvated model. This finding supports the notion that water plays a dominant role in guiding the protein to fold along the correct path.

A study on morphometrical variations of Malaysian Hylarana signata group was conducted to reveal the morphological relationships within the species group. Twenty-seven morphological characters from 18 individuals of H. signata and H. picturata were measured and recorded. The numerical data were analysed using Discriminant Function Analysis in SPSS program version 16.0 and UPGMA Cluster Analysis in Minitab program version 14.0. The results show the complexity clustering between the examined species that might be due to ancient polymorphism of the lineages or cryptic species within the group. Hence, further study should include more representatives in order to fully elucidate the morphological relationships of H. signata group.

Age-related macular degeneration and retinitis pigmentosa are two of the most common diseases that cause degeneration in the outer retina, which can lead to several visual impairments up to blindness. Vision restoration is an important goal for which several different research approaches are currently being pursued. We are concerned with restoration via retinal prosthetic devices. Prostheses can be implemented intraocularly and extraocularly, which leads to different categories of devices. Cortical Prostheses and Optic Nerve Prostheses are examples of extraocular solutions while Epiretinal Prostheses and Subretinal Prostheses are examples of intraocular solutions. Some of the prostheses that are successfully implanted and tested in animals as well as humans can restore basic visual functions but still have limitations. This paper will give an overview of the current state of art of Retinal Prostheses and compare the advantages and limitations of each type. The purpose of this review is thus to summarize the current technologies and approaches used in developing Retinal Prostheses and therefore to lay a foundation for future designs and research directions.

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

Cancer is becoming a leading cause of death among people in the whole world. It is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. Expert systems and machine learning techniques are gaining popularity in this field because of the effective classification and high diagnostic capability. This paper presents the application of rough set theory for clustering two cancer datasets. These datasets are taken from UCI ML repository. The method is based on MDA technique proposed by [11]. To select a clustering attribute, the maximal degree of the rough attributes dependencies in categorical-valued information systems is used. Further, we use a divide-and-conquer method to partition/cluster the objects. The results show that MDA technique can be used to cluster to the data. Further, we present clusters visualization using two dimensional plot. The plot results provide user friendly navigation to understand the cluster obtained.

In previous work, we presented an applicability of soft set theory for decision making of patients suspected influenza. The proposed technique is based on maximal supported objects by parameters. At this stage of the research, results are presented and discussed from a qualitative point of view against recent soft decision making techniques through an artificial dataset. In this paper, we present an extended application of our soft set-based decision making through a Boolean valued information system from a dataset of patients suspected ILI (Influenza-Like Illness). Using soft set theory and maximal symptoms co-occurences in patients, we explore how soft set-based decision making technique can be used to reduce the number of dispensable symptoms and further make a correct and fast decision. The result of this work can be used for recommendation of decision making based on the clusters decision captured. Finally, this technique may potentially contribute to lowering the complexity of medical decision making without loss of original information.

A Head splicing system (H-system)consists of a finite set of strings (words) written over a finite alphabet, along with a finite set of rules that acts on the strings by iterated cutting and pasting to create a splicing language. Any interpretation that is aligned with Tom Head's original idea is one in which the strings represent double-stranded deoxyribonucleic acid (dsDNA) and the rules represent the cutting and pasting action of restriction enzymes and ligase, respectively. A new way of writing the rule sets is adopted so as to make the biological interpretation transparent. This approach is used in a formal language- theoretic analysis of the hierarchy of certain classes of splicing systems, namely simple, semi-simple and semi-null splicing systems. The relations between such systems and their associated languages are given as theorems, corollaries and counterexamples.

In this paper, we consider tumor-immune interaction model systems. The numerical solutions for the tumor-immune interaction system are obtained by using the 2-point Block Backward Differentiation Formula (BBDF) methods developed by Zarina et al. in 2007. The numerical results are presented in terms of computational time and accuracy of the solutions.

We have developed an exact algorithm that solves certain instances of the Reversal Median Problem (RMP) when provided with additional input – the optimal sorting sequences between every pair of genomes. Our algorithm is able to provide an exact solution (the median genome) or determine that it is not able to do so for every instance of the problem. We have also proven the correctness of the algorithm in a theorem. RMP is the problem of finding an ancestral genome (the median) given the gene orders of three genomes. It is commonly encountered when constructing phylogeny, and is NP-hard. Two variations of the RMP were considered. In the first variation, we are given one sorting sequence for each pair of genomes. And in the second variation, we make use of a compact representation of all possible optimal sorting sequences for each pair of genomes that was developed by Braga et al.

In the present paper we study limit behavior of dissipative quadratic stochastic operators on 2D simplex. We show that dissipative quadratic stochastic operator, which is not linear, is either regular or has infinitely many fixed points. If dissipative quadratic stochastic operator is regular, it is shown that its unique fixed point is either a vertex of the simplex or the center of the face of the simplex.

In this research we introduce a new class of quadratic stochastic operators called ξ^s-QSO which are defined through coefficient of the operator from measure-theoretic (namely we are looking the coefficient as the measures which are absolute continuous or singular) point of view. We also study the limiting behaviour of ξ^s -QSO defined on 2D-simplex. We first describe ξ^s -QSO on 2D-simplex and classify them with respect to the conjugacy and renumeration of the coordinates. We find six non-isomorphic classes of such operators. Moreover, we investigate the behaviour of each operator from three classes and prove convergence of trajectories of these classes and study their certain properties. We showed trajectories of two classes converge to the equilibrium. For the third class, it is established only the negative trajectories converge to the equilibrium.

In clinical studies, a proportion of patients might be unsusceptible to the event of interest and can be considered as cured. The survival models that incorporate the cured proportion are known as cure rate models where the most widely used model is the mixture cure model. However, in cancer clinical trials, mixture model is not the appropriate model and the viable alternative is the Bounded Cumulative Hazard (BCH) model. In this paper we consider the BCH model to estimate the cure fraction based on the lognormal distribution. The parametric estimation of the cure fraction for survival data with right censoring with covariates is obtained by using EM algorithm.

Copepods are the most abundant microcrustaceans in the marine waters and are the major food resource for many commercial fish species. In addition, changes in the distribution and population composition of copepods may also serve as an indicator of global climate changes. Therefore, it is important to model the copepod distribution in different ecosystems. Copepod samples were collected from three different ecosystems (seagrass area, cage aquaculture area and coastal waters off shrimp aquaculture farm) along the coastal waters of the Malacca Straits over a one year period. In this study the major statistical analysis consisted of fitting different probability models. This paper highlights the fitting of probability distributions and discusses the adequateness of the fitted models. The usefulness of these fitted models would enable one to make probability statements about the distribution of copepods in three different ecosystems.

In this paper, we suggest a method to solve the multispecies Lotka-Voltera equations. The suggested method, which we call modified homotopy perturbation method, can be considered as an extension of the homotopy perturbation method (HPM) which is very efficient in solving a varety of differential and algebraic equations. The HPM is modified in order to obtain the approximate solutions of Lotka-Voltera equation response in a sequence of time intervals. In particular, the example of two species is considered. The accuracy of this method is examined by comparison with the numerical solution of the Runge-Kutta-Verner method. The results prove that the modified HPM is a powerful tool for the solution of nonlinear equations.

In this paper, we study mathematical model of ecology with a tritrophic food chain composed of a classical Lotka-Volterra functional response for prey and predator, and a Holling type-III functional response for predator and super predator. There are two equilibrium points of the system. In the parameter space, there are passages from instability to stability, which are called Hopf bifurcation points. For the first equilibrium point, it is possible to find bifurcation points analytically and to prove that the system has periodic solutions around these points. Furthermore the dynamical behaviors of this model are investigated. Models for biologically reasonable parameter values, exhibits stable, unstable periodic and limit cycles. The dynamical behavior is found to be very sensitive to parameter values as well as the parameters of the practical life. Computer simulations are carried out to explain the analytical findings.

The Lotka-Volterra (in short LV) model is a second order nonlinear differential equation frequently used to describe the dynamics of biological systems in which two groups of species, predators and their preys interact. One of the basic results of the LV model is that under suitable conditions the LV model can exhibit any asymptotical behavior such as equilibrium states, periodic cycles, and attractors. The discrete analogy of LV model has been considered by many researchers and has been called a quadratic LV model. In a discrete case, one of the unexpected results is that a quadratic LV model cannot exhibit a periodic cycle. In this paper we study nonlinear LV type models which include quadratic LV as a particular case. Unlike quadratic LV models, LV type models can exhibit any asymptotical behavior such as equilibrium states, periodic cycles, and attractors.

Stochastic spatial models are becoming a popular tool for understand the ecological and evolution of ecosystem problems. We consider the predator prey interactions in term of stochastic representation of this Lotka-Volterra model and explore the use of stochastic processes to extinction behavior of the interacting populations. Here, we present simulation of stochastic processes of continuous time Lotka-Volterra model. Euler method has been used to solve the predator prey system. The trajectory spiral graph has been plotted based on obtained solution to show the population cycle of predator as a function of time.

This paper explores the application of fuzzy differential equations in modeling of prey and predator populations. A new model, referred to as fuzzy predator-prey model is introduced. This model is then solved numerically by means of a fuzzy Euler method. Some numerical results are presented in order to show the evolution of the prey and predator populations over time. Finally, the stability of the new fuzzy model is studied and shown graphically in the fuzzy phase plane.

Aedes aegypti is the main vector in the transmission of dengue fever, a vector-borne disease affecting world population living in tropical and sub-tropical countries. Better understanding of the dynamics of its population growth will help in the efforts of controlling the spread of this disease. In looking at the population dynamics of Aedes aegypti, this paper explored the stage-structured modeling of the population growth of the mosquito using the matrix population model. The life cycle of the mosquito was divided into five stages: eggs, larvae, pupae, adult1 and adult2. Developmental rates were obtained for the average Malaysian temperature and these were used in constructing the transition matrix for the matrix model. The model, which was based only on temperature, projected that the population of Aedes aegypti will blow up with time, which is not realistic. For further work, other factors need to be taken into account to obtain a more realistic result.

As we know there are two kind of systems in modeling epidemic disease, deterministic systems and stochastic systems. This two systems relate to deterministic and stochastic epidemic disease models, respectively. Almost we use deterministic model for big population size and stochastic model for small population size. To use stochastic models for epidemic disease models, can obtain good results with less error. Study and solving of full stochastic models has not been yet investigated so more. In this article we use the homotopy analysis method to solve the full stochastic susceptible-infective epidemic disease model in disease-free equilibrium point.

In this paper, we study a system of differential equations that models the population dynamics of SEIR vector transmission of dengue fever. The model studied breeding value based on the number of reported cases of dengue fever in Selangor because the state had the highest case in Malaysia. The model explains that maximum level of human infection rate of dengue fever achieved in a very short period. It is also revealed that there existed suitability result between theoretical and empirical calculation using the model. The result of SEIR model will hopefully provide an insight into the spread of dengue fever in Selangor Malaysia and basic form for modeling this area.

Forestry is the art and science of managing forests, tree plantations, and related natural resources. The main goal of forestry is to create and implement systems that allow forests to continue a sustainable provision of environmental supplies and services. Forest area is land under natural or planted stands of trees, whether productive or not. Forest area of Malaysia has been observed over the years and it can be modeled using time series models. A new class of GARMA models have been introduced in the time series literature to reveal some hidden features in time series data. For these models to be used widely in practice, we illustrate the fitting of GARMA (1, 1; 1, δ) model to the Annual Forest Area data of Malaysia which has been observed from 1987 to 2008. The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation.

Dynamic causal modeling (DCM) was implemented on datasets obtained from an externally-triggered finger tapping functional MRI experiment performed by 5 male and female subjects. The objective was to model the effective connectivity between two significantly activated primary motor regions (M1). The left and right hemisphere M1s are found to be effectively and bidirectionally connected to each other. Both connections are modulated by the stimulus-free contextual input. These connectivities are however not gated (influenced) by any of the two M1s, ruling out the possibility of the non-linear behavior of connections between both M1s. A dynamic causal model was finally suggested.

Loading containers is like loading a subset of given three-dimensional rectangular boxes of different sizes into a three-dimensional rectangular container of fixed dimensions in order to achieve optimal space utilization. In this paper, Ant Colony Optimization (ACO) with its probabilistic decision rule is used to construct towers of boxes and to arrange them into the container. Some initial computational results on benchmark data set will be presented.

The Urban Transit Routing Problem (UTRP) involves solving a set of transit route networks, which proved to be a highly complex multi-constrained problem. In this study, a bus route network to find an efficient network to meet customer demands given information on link travel times is considered. An evolutionary optimization technique, called Genetic Algorithm is proposed to solve the UTRP. The main objective is to minimize the passenger costs where the quality of the route sets is evaluated by a set of parameters. Initial computational experiments show that the proposed algorithm performs better than the benchmark results for Mandl's problems.

In this study, a new technique is presented for choosing mate chromosomes during sexual selection in a genetic algorithm. The population is divided into groups of males and females. During the sexual selection, the female chromosome is selected by the tournament selection while the male chromosome is selected based on the hamming distance from the selected female chromosome, fitness value or active genes. Computational experiments are conducted on the proposed technique and the results are compared with some selection mechanisms commonly used for solving multidimensional 0/1 knapsack problems published in the literature.

Despite being widely used in the practical problems around the world, Gradient Descent Back-propagation algorithm comes with problems like slow convergence and convergence to local minima. Previous researchers have suggested certain modifications to improve the convergence in gradient Descent Back-propagation algorithm such as careful selection of input weights and biases, learning rate, momentum, network topology, activation function and value for 'gain' in the activation function. This research proposed an algorithm for improving the working performance of back-propagation algorithm which is 'Gradient Descent with Adaptive Momentum (GDAM)' by keeping the gain value fixed during all network trials. The performance of GDAM is compared with 'Gradient Descent with fixed Momentum (GDM)' and 'Gradient Descent Method with Adaptive Gain (GDM-AG)'. The learning rate is fixed to 0.4 and maximum epochs are set to 3000 while sigmoid activation function is used for the experimentation. The results show that GDAM is a better approach than previous methods with an accuracy ratio of 1.0 for classification problems like Wine Quality, Mushroom and Thyroid disease.

In this paper, we present the effect of network parameters to forecast temperature of a suburban area in Batu Pahat, Johor. The common ways of predicting the temperature using Neural Network has been applied for most meteorological parameters. However, researchers frequently neglected the network parameters which might affect the Neural Network's performance. Therefore, this study tends to explore the effect of network parameters by using Pi Sigma Neural Network (PSNN) with backpropagation algorithm. The network's performance is evaluated using the historical dataset of temperature in Batu Pahat for one step-ahead and benchmarked against Multilayer Perceptron (MLP) for comparison. We found out that, network parameters have significantly affected the performance of PSNN for temperature forecasting. Towards the end of this paper, we concluded the best forecasting model to predict the temperature based on the comparison of our study.

This paper presents a new method to improve back propagation algorithm from getting stuck with local minima problem and slow convergence speeds which caused by neuron saturation in the hidden layer. In this proposed algorithm, each training pattern has its own activation functions of neurons in the hidden layer that are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. The efficiency of the proposed algorithm is compared with the conventional back propagation gradient descent and the current working back propagation gradient descent with adaptive gain by means of simulation on three benchmark problems namely iris, glass and thyroid.

Recent developments in nature-inspired computation have heightened the need for research into the three main areas of scientific, engineering and industrial applications. Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. This paper investigates the abilities of Evolution Strategies (ES) to evolve feed-forward artificial neural network's internal parameters (i.e. weight and bias values) for automatically generating Ms. Pac-man controllers. The main objective of this game is to clear a maze of dots while avoiding the ghosts and to achieve the highest possible score. The experimental results show that an ES-based system can be successfully applied to automatically generate artificial intelligence for a complex, dynamic and highly stochastic video game environment.

Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability.

Medical Akzo Nobel problem (MEDAKZO) is known for its tenancy of incurring high computational cost. Originates from the penetration of radio-labeled antibodies into a tissue that has been infected by a tumor, the problem has been derived from a one dimensional partial differential equations to a two dimensional ordinary differential equations thus generates a large scale of problem to be solved. This paper presents the performance of a new 4(3) diagonally implicit Runge-Kutta (DIRK) method which is suitable to excellently solve MEDAKZO problem that is stiff in nature. The sparsity pattern designed on the method enable the functions evaluations to be computed simultaneously on two processors. The functional load balancing can be profitable especially in solving large problems.

Switching is a technique to route data and instructions between pairs of source-destination nodes or among multiple nodes for broadcast communication. We realized that the shortest path problem has a wide application in the design of networks. Therefore, in this paper, we present a mesh network as our switching mechanism for computing the shortest path between the source and destination in our simulation model, developed using C++ on the Windows environment. The Floyd-Warshall algorithm is applied in finding the shortest path in all-pairs nodes.

Routing vehicles involve the design of an optimal set of routes for a fleet of vehicles to serve a number of customers with known demands. This research develops an Ant Colony Optimization for the vehicle routing with one central depot and identical vehicles. The procedure simulates the behavior of real ants that always find the shortest path between their nest and a food source through a form of communication, pheromone trail. Finally, preliminary results on the learning of the algorithm testing on benchmark data set will be presented in this paper.

Study the heats propagation in a solid, liquid continuums is an actual problems. The liquid continuum may be considered as a biomaterial. The present investigation is devoted to the study of 1D and 2D dynamic coupled thermo elasticity problems. In case of coupled problems the motion and heat conduction equations are considered together. For numerical solution of thermo elasticity problems an explicit and implicit schemes are constructed. The explicit and implicit schemes by using recurrent formulas and the "consecutive" methods are solved. Comparison of two results shows a good coincidence.

The unsteady flow over a continuously shrinking sheet with wall mass suction in a nanofluid is numerically studied. The governing boundary layer equations are transformed into a set of nonlinear ordinary differential equations by using similarity transformation. The resulting similarity equations are then solved by the shooting method for three types of nanofluid: copper-water, alumina-water and titania-water to investigate the effect of nanoparticle volume fraction parameter ɸ to the flow in nanofluid. The skin friction coefficient and velocity profiles are presented and results show that dual solutions exist for a certain range of unsteadiness parameter A. It is also found that the nanoparticle volume fraction parameter ɸ and types of nanofluid play an important role to significantly determine the flow behaviour.

The problems of mathematical biology, as a rule, are formulated in terms of independent and depended (unknown) variables (functions), and operators (mostly differential operators). These variables belong to some spaces and operators acting in these spaces. Both, unknown variables and operators, follow the main rules of these spaces as metrics, topology and etc. In applications a solution of the problem will be constructed by approximation methods based on metrics/topology of the space. In this convergence of the constructed approximations essentially depends on compactness.

We study a differential game of one pursuer and one evader described by infinite systems of second order ordinary differential equations. Controls of players are subjected to geometric constraints. Differential game is considered in Hilbert spaces. We proved one theorem on evasion. Moreover, we constructed explicitly a control of the evader.

It is well known that Catalan Numbers are used in Mathematical Biology as Enumerating RNA secondary structures for finite points. In this paper, we present some new properties of the Catalan Numbers.

This paper deals with a class of two person zero-sum linear quadratic differential games, where the control functions for both players subject to integral constraints. Also the necessary conditions of the Maximum Principle are studied. Main objective in this work is to obtain optimal control by using method of Pontryagin's Maximum Principle. This method for a time-varying linear quadratic differential game is described. Finally, we discuss about an example.

The effect of feedback control on the onset of Bénard-Marangoni ferroconvection in a horizontal ferrofluid layer heated from below is investigated theoretically. The lower boundary is rigid and the upper free boundary is assumed to be flat and undeformable. A linear stability analysis is used and the Galerkin method is employed to find the critical stability parameters numerically. It is found that the onset of instability can be delayed through the use of feedback control.

The purpose of this paper is to present a four point direct block one-step method for solving directly the general second order nonstiff initial value problems (IVPs) of ordinary differential equations (ODEs). The mathematical problems in real world can be written in the form of differential equations and arise in the fields of science and engineering such as fluid dynamic, electric circuit, motion of rocket or satellite and other area of application. The proposed method will estimate the approximation solutions at four points simultaneously by using variable step size. Numerical results are given to show the efficiency of the proposed method.

The two point boundary value problems (BVPs) occur in a wide variety of applications especially in sciences such as chemistry and biology. In this paper, we propose two point direct method of order six for solving nonlinear two point boundary value problems directly. This method is presented in a simple form of Adams Mouton type and determines the approximate solution at two point simultaneously. The method will be implemented using constant step size via shooting technique adapted with three-step iterative method. Numerical results are given to compare the efficiency of the proposed method with the Runge-Kutta and bvp4c method.

Korteweg de Vries (KdV) equation has been used as a mathematical model of shallow water waves. In this paper, we present one-, two-, and three-soliton solution of KdV equation. By definition, soliton is a nonlinear wave that maintains its properties (shape and velocity) upon interaction with each other. In order to investigate the behavior of soliton solutions of KdV equation and the interaction process of the two- and three-solitons, computer programs have been successfully simulated. Results from these simulations confirm that the solutions of KdV equation obtained are the soliton solutions.

Hasegawa constructed the automatic quadrature scheme (AQS), of Cauchy principle value integrals for smooth functions. There is a close connection between Hadamard and Cauchy principle value integral. In this paper, we modify AQS for hypersingular integrals with second-order singularities, using hasegawa's formula and based on the relations between Hadamard finite part integral and Cauchy principle value integral. Numerical experiments are also given, to validate the modified AQS.