World Academy of Science, Engineering and Technology

Authors: Rajeev, N. K. Raigar

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In this study, one dimensional phase change problem (a Stefan problem) is considered and a numerical solution of this problem is discussed. First, we use similarity transformation to convert the governing equations into ordinary differential equations with its boundary conditions. The solutions of ordinary differential equation with the associated boundary conditions and interface condition (Stefan condition) are obtained by using a numerical approach based on operational matrix of differentiation of shifted second kind Chebyshev wavelets. The obtained results are compared with existing exact solution which is sufficiently accurate.

Keywords: operational matrix of differentiation, similarity transformation, shifted second kind chebyshev wavelets, stefan problem

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Authors: Said Ali Al-Hadhrami, Amer Ibrahim Al-Omari

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In this paper, Bayesian estimation for the mean of exponential distribution is considered using Moving Extremes Ranked Set Sampling (MERSS). Three priors are used; Jeffery, conjugate and constant using MERSS and Simple Random Sampling (SRS). Some properties of the proposed estimators are investigated. It is found that the suggested estimators using MERSS are more efficient than its counterparts based on SRS.

Keywords: Bayesian, efficiency, moving extreme ranked set sampling, ranked set sampling

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Authors: Hashem Sazegar

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In 1937, Vinograd of Russian Mathematician proved that each odd large number can be shown by three primes. In 1973, Chen Jingrun proved that each odd number can be shown by one prime plus a number that has maximum two primes. In this article, we state one proof for Goldbach’conjecture. Introduction: Bertrand’s postulate state for every positive integer n, there is always at least one prime p, such that n < p < 2n. This was first proved by Chebyshev in 1850, which is why postulate is also called the Bertrand-Chebyshev theorem. Legendre’s conjecture states that there is a prime between n2 and (n+1)2 for every positive integer n, which is one of the four Landau’s problems. The rest of these four basic problems are; (i) Twin prime conjecture: There are infinitely many primes p such that p+2 is a prime. (ii) Goldbach’s conjecture: Every even integer n > 2 can be written asthe sum of two primes. (iii) Are there infinitely many primes p such that p−1 is a perfect square? Problems (i), (ii), and (iii) are open till date.

Keywords: Bertrand-Chebyshev theorem, Landau’s problems, twin prime, Legendre’s conjecture, Oppermann’s conjecture

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Authors: Anjan Naidu

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In this paper we first discuss the minimum spanning tree, then we use the Kruskal algorithm to obtain minimum spanning tree. Based on Kruskal algorithm we propose Kruskal algorithm to apply an application to find minimum cost applying the concept of spanning tree.

Keywords: Minimum Spanning tree, algorithm, Heuxistic, application, classification of Sub 97K90

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

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Authors: Elahe Sarfi, Esmat Noroozi, Farhad Hosseinzadeh Lotfi

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One of the important issues in Data Envelopment Analysis is the ranking of Decision Making Units. In this paper, a method for ranking DMUs is presented through which the weights related to efficient units should be chosen in a way that the other units preserve a certain percentage of their efficiency with the mentioned weights. To this end, a model is presented for ranking DMUs on the base of their superefficiency by considering the mentioned restrictions related to weights. This percentage can be determined by decision Maker. If the specific percentage is unsuitable, we can find a suitable and feasible one for ranking DMUs accordingly. Furthermore, the presented model is capable of ranking all of the efficient units including nonextreme efficient ones. Finally, the presented models are utilized for two sets of data and related results are reported.

Keywords: data envelopment analysis, efficiency, ranking, weight

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Syed Afrozuddin Ahmed, Junaid Saghir Siddiqi, Sabah Quaiser

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Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan. In this study it has been investigated that spatial pattern of environment causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. The climatic or environmental structure data and the Dengue Fever (DF) data was processed by coding, editing, tabulating, recoding, restructuring in terms of re-tabulating was carried out, and finally applying different statistical methods, techniques, and procedures for the evaluation. Five climatic variables which we have studied are precipitation (P), Maximum temperature (Mx), Minimum temperature (Mn), Humidity (H) and Wind speed (W) collected from 1980-2012. The dengue cases in Karachi from 2010 to 2012 are reported on weekly basis. Principal component analysis is applied to explore the climatic variables and/or the climatic (structure) which may influence in the increase or decrease in the number of dengue fever cases in Karachi. PC1 for all the period is General atmospheric condition. PC2 for dengue period is contrast between precipitation and wind speed. PC3 is the weighted difference between maximum temperature and wind speed. PC4 for dengue period contrast between maximum and wind speed. Negative binomial and Poisson regression model are used to correlate the dengue fever incidence to climatic variable and principal component score. Relative humidity is estimated to positively influence on the chances of dengue occurrence by 1.71% times. Maximum temperature positively influence on the chances dengue occurrence by 19.48% times. Minimum temperature affects positively on the chances of dengue occurrence by 11.51% times. Wind speed is effecting negatively on the weekly occurrence of dengue fever by 7.41% times.

Keywords: principal component analysis, dengue fever, negative binomial regression model, poisson regression model

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Authors: Fatma Zehra Doğru, Olcay Arslan

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In this paper, we propose alternative robust estimators for the shape parameters of the Burr XII distribution. We provide a small simulation study and a real data example to illustrate the performance of the proposed estimators over the ML and the LS estimators.

Keywords: burr xii distribution, robust estimator, m-estimator, least squares

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Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

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The total tardiness is a widely used performance measure in the scheduling literature. This performance measure is particularly important in situations where there is a cost to complete a job beyond its due date. The cost of scheduling increases as the gap between a job's due date and its completion time increases. Such costs may also be penalty costs in contracts, loss of goodwill. This performance measure is important as the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. The problem is addressed in the literature, however, it has been assumed zero setup times. Even though this assumption may be valid for some environments, it is not valid for some other scheduling environments. When setup times are treated as separate from processing times, it is possible to increase machine utilization and to reduce total tardiness. Therefore, non-zero setup times need to be considered as separate. A dominance relation is developed and several algorithms are proposed. The developed dominance relation is utilized in the proposed algorithms. Extensive computational experiments are conducted for the evaluation of the algorithms. The experiments indicated that the developed algorithms perform much better than the existing algorithms in the literature. More specifically, one of the newly proposed algorithms reduces the error of the best existing algorithm in the literature by 40 percent.

Keywords: algorithm, assembly flowshop, dominance relation, total tardiness

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Authors: Vernie C. Convicto, Henry P. Aringa, Wilson I. Barredo

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This study presents a conformational model of the helical structures of globular protein particularly ferritin in the framework of white noise path integral formulation by using Associated Legendre functions, Bessel and convolution of Bessel and trigonometric functions as modulating functions. The model incorporates chirality features of proteins and their helix-turn-helix sequence structural motif.

Keywords: globular protein, modulating function, white noise, winding probability

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Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

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Authors: Morteza Raminnia

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In this study, dynamic analysis of functionally graded nano-composite pipe reinforced by single-walled carbon nano-tubes (SWCNTs) with simply supported boundary condition subjected to moving mechanical loads is investigated. The material properties of functionally graded carbon nano tube-reinforced composites (FG-CNTRCs) are assumed to be graded in the thickness direction and are estimated through a micro-mechanical model. In this paper polymeric matrix considered as isotropic material and for the CNTRC, uniform distribution (UD) and three types of FG distribution patterns of SWCNT reinforcements are considered. The system equation of motion is derived by using Hamilton's principle under the assumptions of first order shear deformation theory (FSDT).The thin piezoelectric layers embedded on inner and outer surfaces of FG-CNTRC layer are acted as distributed sensor and actuator to control dynamic characteristics of the FG-CNTRC laminated pipe. The modal analysis technique and Newmark's integration method are used to calculate the displacement and dynamic stress of the pipe subjected to moving loads. The effects of various material distribution and velocity of moving loads on dynamic behavior of the pipe is presented. This present approach is validated by comparing the numerical results with the published numerical results in literature. The results show that the above-mentioned effects play very important role on dynamic behavior of the pipe .This present work shows that some meaningful results that which are interest to scientific and engineering community in the field of FGM nano-structures.

Keywords: nano-composite, functionally garded material, moving load, active control, PZT layers

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: Patarawan Sangnawakij, Sa-Aat Niwitpong

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In this paper, we proposed two new confidence intervals for the difference of coefficients of variation, CIw and CIs, in two independent gamma distributions. These proposed confidence intervals using the close form method of variance estimation which was presented by Donner and Zou (2010) based on concept of Wald and Score confidence interval, respectively. Monte Carlo simulation study is used to evaluate the performance, coverage probability and expected length, of these confidence intervals. The results indicate that values of coverage probabilities of the new confidence interval based on Wald and Score are satisfied the nominal coverage and close to nominal level 0.95 in various situations, particularly, the former proposed confidence interval is better when sample sizes are small. Moreover, the expected lengths of the proposed confidence intervals are nearly difference when sample sizes are moderate to large. Therefore, in this study, the confidence interval for the difference of coefficients of variation which based on Wald is preferable than the other one confidence interval.

Keywords: confidence interval, score’s interval, wald’s interval, coefficient of variation, gamma distribution, simulation study

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Authors: Bojan Radisic, Katarina Stavlic

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The paper describes two economics terms consumer surplus and producer surplus using the definite integrals (the Riemann integral). The consumer surplus is the difference between what consumers are willing to pay and actual price. The producer surplus is the difference between what producers selling at the current price, rather than at the price they would have been are willing to accept. Using the definite integrals describe terms and mathematical formulas of the consumer surplus and the producer surplus and will be applied to the numerical examples.

Keywords: consumer surplus, producer surplus, definite integral, integration

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Authors: Ramandeep Behl, S. S. Motsa

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The main focus of this manuscript is to provide a highly efficient two-point sixth-order family of super-Halley type methods that do not require any second-order derivative evaluation for obtaining simple roots of nonlinear equations, numerically. Each member of the proposed family requires two evaluations of the given function and two evaluations of the first-order derivative per iteration. By using Mathematica-9 with its high precision compatibility, a variety of concrete numerical experiments and relevant results are extensively treated to confirm t he t heoretical d evelopment. From their basins of attraction, it has been observed that the proposed methods have better stability and robustness as compared to the other sixth-order methods available in the literature.

Keywords: basins of attraction, nonlinear equations, simple roots, super-Halley

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Mohsen Zahraei

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‎In this paper, ‎the notion of ‎rank-k numerical range of rectangular complex matrix polynomials‎ ‎are introduced. ‎Some algebraic and geometrical properties are investigated. ‎Moreover, ‎for ε>0 the notion of Birkhoff-James approximate orthogonality sets for ε-higher ‎rank numerical ranges of rectangular matrix polynomials is also introduced and studied. ‎The proposed definitions yield a natural generalization of the standard higher rank numerical ranges.

Keywords: ‎‎Rank-k numerical range‎, ‎isometry‎, ‎numerical range‎, ‎rectangular matrix polynomials

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Authors: Neil M. Mame

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We consider only finite graphs without loops nor multiple edges. Let G be a graph with E(G) = {e1, e2, …., em}. The edge space of G, denoted by ε(G), is a vector space over the field Z2. The elements of ε(G) are all the subsets of E(G). Vector addition is defined as X+Y = X Δ Y, the symmetric difference of sets X and Y, for X, Y ∈ ε(G). Scalar multiplication is defined as 1.X =X and 0.X = Ø for X ∈ ε(G). The set S ⊆ ε(G) is called a generating set if every element ε(G) is a linear combination of the elements of S. For a non-empty set X ∈ ε(G), the smallest subgraph with edge set X is called edge-induced subgraph of G, denoted by G[X]. The set EH(G) = { A ∈ ε(G) : G[A] ≅ H } denotes the uniform set of H with respect to G and εH(G) denotes the subspace of ε(G) generated by EH(G). If εH(G) is generating set, then we call H a generator subgraph of G. This paper gives the characterization for the generator subgraphs of the wheel that contain cycles and gives the necessary conditions for the acyclic generator subgraphs of the wheel.

Keywords: edge space, edge-induced subgraph, generator subgraph, wheel

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Authors: Yeonjune Kang

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A triangulation of a planar region is a partition of that region into triangles. In the finite element method, triangulations are often used as the grid underlying a computation. In order to be suitable as a finite element mesh, a triangulation must have well-shaped triangles, according to criteria that depend on the details of the particular problem. For instance, most methods require that all triangles be small and as close to the equilateral shape as possible. Stated differently, one wants to avoid having either thin or flat triangles in the triangulation. There are many triangulation procedures, a particular one being the one known as the longest edge bisection algorithm described below. Starting with a given triangle, locate the midpoint of the longest edge and join it to the opposite vertex of the triangle. Two smaller triangles are formed; apply the same bisection procedure to each of these triangles. Continuing in this manner after n steps one obtains a triangulation of the initial triangle into 2n smaller triangles. The longest edge algorithm was first considered in the late 70’s. It was shown by various authors that this triangulation has the desirable properties for the finite element method: independently of the number of iterations the angles of these triangles cannot get too small; moreover, the size of the triangles decays exponentially. In the present paper we consider a related triangulation algorithm we refer to as the largest angle bisection procedure. As the name suggests, rather than bisecting the longest edge, at each step we bisect the largest angle. We study the properties of the resulting triangulation and prove that, while the general behavior resembles the one in the longest edge bisection algorithm, there are several notable differences as well.

Keywords: angle bisectors, geometry, triangulation, applied mathematics

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Authors: Rajkumar N. Ingle

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In this paper, the existence of a solution of nonlinear functional random differential equations of the first order is proved under caratheodory condition. The study of the functional random differential equation has got importance in the random analysis of the dynamical systems of universal phenomena. Objectives: Nonlinear functional random differential equation is useful to the scientists, engineers, and mathematicians, who are engaged in N.F.R.D.E. analyzing a universal random phenomenon, govern by nonlinear random initial value problems of D.E. Applications of this in the theory of diffusion or heat conduction. Methodology: Using the concepts of probability theory, functional analysis, generally the existence theorems for the nonlinear F.R.D.E. are prove by using some tools such as fixed point theorem. The significance of the study: Our contribution will be the generalization of some well-known results in the theory of Nonlinear F.R.D.E.s. Further, it seems that our study will be useful to scientist, engineers, economists and mathematicians in their endeavors to analyses the nonlinear random problems of the universe in a better way.

Keywords: Random Fixed Point Theorem, functional random differential equation, N.F.R.D.E., universal random phenomenon

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Authors: Shahed Vahedi, Mohd Salmi Md Noorani

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This paper investigates cluster synchronization phenomena between community networks. We focus on the situation where a variety of dynamics occur in the clusters. In particular, we show that different synchronization states simultaneously occur between the networks. The controller is designed having an adaptive control gain, and theoretical results are derived via Lyapunov stability. Simulations on well-known dynamical systems are provided to elucidate our results.

Keywords: cluster synchronization, adaptive control, community network, simulation

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Hassan Al Salman, Ahmed Al Ghafli

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In this study we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed point theorem to prove existence of the approximations. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. Also, we prove an optimal error bound in time for d=1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the theoretical results.

Keywords: reaction diffusion system, finite element approximation, fixed point theorem, an optimal error bound

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Authors: Mahmoud I. Syam, Osama K. El-Hafy

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With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

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Authors: M. T. Alodat

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In this paper, we propose a mechanism for skewing any symmetric distribution. The new distribution is called the deflation-inflation distribution (DID). We discuss some statistical properties of the DID such moments, stochastic representation, log-concavity. Also we fit the distribution to real data and we compare it to normal distribution and Azzlaini's skew normal distribution. Numerical results show that the DID fits the the tree ring data better than the other two distributions.

Keywords: normal distribution, moments, Fisher information, symmetric distributions

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Authors: Ayman Baklizi

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Based on type II censored data, we consider interval estimation of the quantiles of the two-parameter exponential distribution and the difference between the quantiles of two independent two-parameter exponential distributions. We derive asymptotic intervals, Bayesian, as well as intervals based on the generalized pivot variable. We also include some bootstrap intervals in our comparisons. The performance of these intervals is investigated in terms of their coverage probabilities and expected lengths.

Keywords: asymptotic intervals, Bayes intervals, bootstrap, generalized pivot variables, two-parameter exponential distribution, quantiles

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Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani

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The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.

Keywords: estimation, bandwidth, mean square error, cumulative distribution function

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