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Real option pricing problems in investment project evaluation are mostly solved by the simulation-based methods, the lattice methods and by the finite difference method (FDM). Only a few applications of the finite element method (FEM) to these problems have been reported in the literature; although it seems to be an alternative tool for pricing real options.Unlike the existing finite element-based papers, in this paper we use residual formulation and provide a detailed scheme for practical implementations. The FEM is introduced and developed as a numerical method for real options pricing problems. First of all, a partial differential equation (pde) model is defined, then the problem’s domain is discretized by finite elements. The weak formulation of the pde is then obtained, and finally the solution to the real option pricing problem is found by solving an algebraic system. For benchmarking purposes, the FEM is applied to known investment and abandonment option problems found in the literature and the results are compared with those of some traditional methods. These results show a good performance of the FEM and its superiority over the FDM in terms of convergence, and over the simulation-based methods in terms of the optimal exercise policy.

This paper presents a new class of functions analytic in the open unit disc, and closely related to the class of starlike functions. Besides being an introduction to this field, it provides an interesting connections defined class with well known classes. The paper deals with several ideas and techniques used in geometric function theory. The order of starlikeness in the class of convex functions of negative order is also considered here.

In this paper, we establish the determinantal representations of the generalized inverses A"r"""T"""""""1""","""S"""""""1^(^2^),A"l"""T"""""""2""","""S"""""""2^(^2^) and A"""("""T"""""""1""","""T"""""""2""")""","""("""S"""""""1""","""S"""""""2""")^(^2^) over the quaternion skew field by the theory of the column and row determinants. In addition, we derive some generalized Cramer rules for the unique solution of some restricted quaternion matrix equations. The findings of this paper extend some known results in the literature.

In this paper, existence criteria for three positive solutions of p-Laplacian difference equation △[Φp(△u(t−1))]+a(t)f(u(t))=0,t∈[1,T+1],△u(0)=u(T+2)=0,oru(0)=△u(T+1)=0, are established by using the Five Functionals Fixed Point Theorem. As an application, one example is given to illustrate the main result in this paper.

This paper studies the global existence of solutions of the second order nonlinear neutral delay difference equation @D(a"[email protected](x"n+bx"n"-"@t))+f(n,x"n"-"d"""1"""n,x"n"-"d"""2"""n,...,x"n"-"d"""k"""n)=c"n,n>=n"0 with respect to all [email protected]?R. A few results on global existence of uncountably many bounded nonoscillatory solutions are established for the above difference equation. Several nontrivial examples which dwell upon the importance of the results obtained in this paper are also included.

In this paper, we develop the differential transform method (DTM) for solving a class of the system of two-dimensional linear and nonlinear Volterra integro-differential equations of the second kind. To this end, we give some preliminary results of the differential transform and describe the method of this paper. We also give some examples to demonstrate the accuracy of the presented method.

This paper is concerned with the study of necessary and sufficient optimality conditions for convex–concave fractional disjunctive programming problems for which the decision set is the union of a family of convex sets. The Lagrangian function for such problems is defined and the Kuhn–Tucker saddle and stationary points are characterized. In addition, some important theorems related to the Kuhn–Tucker problem for saddle and stationary points are established. Moreover, a general dual problem is formulated, and weak, strong and converse duality theorems are proved. Throughout the presented paper illustrative examples are given to clarify and implement the developed theory.

Learning and job deterioration co-exist in many realistic scheduling situations. This paper introduces a general scheduling model with the effects of learning and deterioration simultaneously which is a significant generalization of some existing models in the literature. By the effects of learning and deterioration, we mean that job processing times are defined by functions of their start times and positions in the sequence. This paper shows that the single-machine scheduling problems to minimize the makespan, sum of the kth power of completion times, total lateness and sum of earliness penalties (with a common due date) are polynomially solvable under the proposed model. It further shows that the problems to minimize the total weighted completion time, discounted total weighted completion time, maximum lateness, maximum tardiness, total tardiness and total weighted earliness penalties (with a common due date) are polynomially solvable under certain conditions.

Based on the Pawlak rough set theory, this paper investigates separations in covering approximation spaces, give some characterizations of these separations and some relations among these separations. As an application of these results, investigations on network security are converted into investigations on separations in covering approximation spaces by taking covering approximation spaces as mathematical models of networks. Results of this paper give further applications of the Pawlak rough set theory in pattern recognition and artificial intelligence, which makes it possible to research network security by logical methods and mathematical methods in computer science. This contributes to giving risk assessments of securities and to raise grades of securities for networks.

In the present paper we establish several differential superordinations regarding the new operator RD"@l","@a^n defined by using the generalized Salagean operator D"@l^nf(z) and Ruscheweyh derivative R^nf(z), RD"@l","@a^n:A->A, RD"@l","@a^nf(z)=(1-@a)R^nf(z)+@aD"@l^nf(z),z@?U, where n@?N, @l,@a>=0 and f@?A,A={f@?H(U):f(z)=z+@?j=2~a"jz^j,z@?U}. A number of interesting consequences of some of these superordination results are discussed. Relevant connections of some of the new results obtained in this paper with those in earlier works are also provided.

The exponential partial Bell polynomials are polynomials in an infinite number of variables x"1,x"2,..., and it is well-known that some special combinatorial sequences, e.g., Stirling numbers of both kinds, Lah numbers and idempotent numbers, can be obtained from the Bell polynomials. In this paper, we study these polynomials by making appropriate choices of the variables x"1,x"2,... which are related to associated sequences (binomial sequences) and Sheffer sequences. As a consequence, many general identities on Bell polynomials are proposed. From these general identities, we can obtain series of identities on Bell polynomials. It can also be found that many results presented before are special cases of the general identities of this paper.

This paper proposes a two-dimensional particle swarm optimization (2D-PSO) method for optimizing the weighting in extension theory for the detection of islanding in photovoltaic (PV) power generation systems. Generally, using extension theory to implement and analyze a system with a correlation function would involve constructing a weighting determined by trial and error to help judge the problem’s performance. However, the judgment accuracy can be degraded if one uses an inappropriate weighting set. Hence, this paper proposes a weighting determination method for optimizing the performance of the extension method using the 2D-PSO algorithm. Some simulation results are obtained to verify the effectiveness of the proposed islanding detection method. In addition, the simulated results obtained using the proposed 2D-PSO algorithm are also compared with those obtained using genetic algorithm (GA) and evolutionary programming (EP) algorithms in order to reveal the search performance of the proposed method.

Tato práce se zabývá využitím dvou evolučních algoritmů Samo-Organizační Migrační Algoritmus (SOMA) a Diferenciální evoluce (DE) pro optimalizaci řízení chaosu. Tato práce je zaměřena na vysvětlení, jak používat evoluční algoritmy (EA), a jak správně definovat pokročilé robustní účelové funkce (CF) zajišťující rychlé, přesné a hlavně robustní stabilizaci vybraného chaotického systému na požadovaný stav pro všechny počáteční podmínky. Role EA je zde jako mocný nástroj pro optimální vyladění vstupních parametrů řídící techniky. Jako modelu deterministického chaotického systému bylo použíto jednorozměrné diskrétní logistické rovnice. Čtyři kanonické strategie SOMA a šest kanonických strategií DE byly využity při optimalizacích. Pro každou strategii EA, byly provedeny opakované simulace jako důkaz účinnosti a robustnosti použité metody a komplexní CF zajišťující robustní řešení. Uspokojivé výsledky dosažené obou heuristických algoritmů a dvou navržených účelových funkcí jsou zde srovnány s předchozím výzkumem, daným různými návrhy účelové funkce., This paper deals with the utilization of two evolutionary algorithms Self-Organizing Migrating Algorithm (SOMA) and Differential Evolution (DE) for the optimization of the control of chaos. This paper is aimed at an explanation on how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing fast, precise and mainly robust stabilization of selected chaotic system on a desired state for any initial conditions. The role of EA here is as a powerful tool for an optimal tuning of control technique input parameters. As a model of deterministic chaotic system, the one-dimensional discrete Logistic equation was used. The four canonical strategies of SOMA and six canonical strategies of DE were utilized. For each EA strategy, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF securing robust solution. Satisfactory results obtained by both heuristic and the two proposed cost functions are compared with previous research, given by different cost function designs. (C) 2010 Elsevier Ltd. All rights reserved.

In this paper, we derive the number of binary strings which contain, for a given i"k, exactly i"k runs of 1's of length k in all possible binary strings of length n, [email protected][email protected]?n. Such a knowledge about the distribution pattern of runs of 1's in binary strings is useful in many engineering applications - for example, data compression, bus encoding techniques to reduce crosstalk in VLSI chip design, computer arithmetic using redundant binary number system and design of energy-efficient communication schemes in wireless sensor networks by transformation of runs of 1's into compressed information patterns, among others. We present, here, a generating function based approach to derive a solution to this counting problem. Our experimental results demonstrate that, for most commonly used file formats, the observed distributions of exactly i"k runs of length k, [email protected][email protected]?n, closely follow the theoretically derived distributions, for a given n. For n=8, we find that the experimentally obtained values for most file formats agree within +/-5% of the theoretically obtained values for all i"k runs of length k, [email protected][email protected]?n. Also, the root mean square (RMS) values of these deviations across all file types studied in this paper are less than 5% for n=8. In view of these facts, the results presented in this paper could be useful in various application domains, like the ones mentioned above.

A general instance of a Degree-Constrained Subgraph problem may be found in an edge-weighted or vertex-weighted graph G whereas the objective is to find an optimal weighted subgraph, subject to certain degree constraints on the vertices of the subgraph. This class of combinatorial problems has been extensively studied due to its numerous applications in network design. If the input graph is bipartite, these problems are equivalent to classical transportation and assignment problems in operational research. This paper is an illustration of a research of the NP-hard Maximum Degree-Bounded Connected Subgraph problem (MDBCS). It is a classical NP-complete problem. Moreover this paper offers a first integer linear programming formulation of the (MDBCS), and a formal proof that it is correct. A genetic algorithm for obtaining the optimal solution of (MDBCS) has also been provided. The proposed solution comprises a genetic algorithm (GA) that uses binary representation, fine-grained tournament selection, one-point crossover, simple mutation with frozen genes and caching technique.

This paper deals with the development of a mathematical model for complex socio-economical systems, where external actions play a key role. The aim of the paper is to show the emergence of collective behaviors or macroscopic trends from individual based interactions, where agents are identified by functional subsystems. The approach is based on the methods of the mathematical kinetic theory for active particles, which describes the evolution of large systems of interacting entities which are carriers of specific functions: in our specific application socio-political activities subjected to the influence of the media.

In this paper, we introduce and consider a new class of mixed variational inequalities involving four operators, which are called extended general mixed variational inequalities. Using the resolvent operator technique, we establish the equivalence between the extended general mixed variational inequalities and fixed point problems as well as resolvent equations. We use this alternative equivalent formulation to suggest and analyze some iterative methods for solving general mixed variational inequalities. We study the convergence criteria for the suggested iterative methods under suitable conditions. Our methods of proof are very simple as compared with other techniques. The results proved in this paper may be viewed as refinements and important generalizations of the previous known results.

This paper is motivated from some recent papers treating the boundary value problems for impulsive fractional differential equations. We first make a counterexample to show that the formula of solutions in cited papers are incorrect. Second, we establish a general framework to find the solutions for impulsive fractional boundary value problems, which will provide an effective way to deal with such problems. Third, some sufficient conditions for the existence of the solutions are established by applying fixed point methods. Meanwhile, data dependence is obtained by using a new generalized singular Gronwall inequality. Finally, three examples are given to illustrate the results.

It has been shown by Sharma and Tarabia [1] that a power series technique can be successfully applied to derive the transient solution for an empty M/M/1/N queueing system. In this paper, we further illustrate how this technique can be used to extend [1] solution to allow for an arbitrary number of initial customers in the system. Moreover, from this, other more commonly sought results such as the transient solution of a nonempty M/M/1/∞ queue can be computed easily. The emphasis in this paper is theoretical but numerical assessment of operational consequences is also given.

In a recent paper by Spătaru [Precise asymptotics for a series of T.L. Lai, Proc. Amer. Math. Soc. 132 (11) (2004) 3387–3395] a precise asymptotics in the law of the logarithm for sequence of i.i.d. random variables has been established. In this paper we show that there is an analogous result for strictly stationary φ-mixing sequence. To prove this result, we have to use a different method. One of our main tools is the Gaussian approximation technique.

The growing complexity and size of High Performance Computing systems (HPCs) lead to frequent job failures, which may cause significant performance degradation. In order to provide high performance and reliable computing services, an in-depth understanding of the characteristics of HPC job failures is essential. In this paper, we present an empirical study on job failures of 10 public workload data sets collected from 8 large-scale HPCs all over the world. Multiple analysis methods are applied to provide a comprehensive and in-depth understanding of job failures. In order to facilitate design, testing and management of HPCs, we study properties of job failures from the following four aspects: proportion in workload and resource consumption, submission inter-arrival time, locality, and runtime.Our analysis results show that job failure rates are significant in most HPCs, and on average, a failed job often consumes more computational resources than a successful job. We also observe that the submission inter-arrival time of failed jobs is better fit by Generalized Pareto and Lognormal distributions, and the probability of failed job submission follows a “V” shape: decreasing during the first 100 seconds right after the submission of the last failed job and increasing afterward. The majority of job failures come from a small number of users and applications, and furthermore these users are the primary factor related to job failures compared with these applications. We find evidence that failed jobs’ lifetime accuracy (runtime / request time) always follows the “bathtub curve”. Moreover, job failures exhibit strong locality properties that can support the prediction of failed jobs’ occurrence and runtime. Most of these findings are new contributions from the research community, and some findings also reveal important properties of job failures that were misunderstood or poorly understood before. The wide range of studies in this paper can directly and thoroughly facilitate fault tolerant, scheduling, workload modeling, etc. in HPCs, and lead to better system utility while reducing costs.

In this paper, we consider a class of singular nth-order nonlocal boundary value problems in Banach spaces. The existence of multiple positive solutions for the problem is obtained by using the fixed point index theory of strict set contraction operators. To demonstrate the applications of our results, two examples are also given in the paper.

The goal of top-k ranking for objects is to rank the objects so that the best k of them can be determined. In this paper we consider an object to be an entity which consists of a number of attributes whose roles in the object are determined by an aggregation function. The problem of top-ranking in this case is conceptually simple for data that are complete and certain — the aggregation value of an object represents its strength and therefore its rank. For uncertain data, the semantic basis of top-k objects becomes unclear. In this paper, we formulate a semantics of top-k ranking for objects modeled by uncertain data, where the values of an object’s attributes are expressed by probability distributions and constrained by some stated conditions. Under this setting, we present a theory of top-k ranking for objects so that their strengths can be determined in the presence of uncertain data. We present our theory in three stages. The first deals with discrete domains, which is extended to include continuous domains. We show that top-k ranking for objects in this context is closely related to high-dimensional space studied in mathematics. In particular, the computation of the volumes of a high-dimensional polyhedron represented by a system of linear inequations is a special case of top-k ranking under our theory. We further extend this theory to add weights to objects’ positions and aggregation values in determining ranking results. We show that a number of previous proposals for top-k ranking are special cases of our theory.

In this paper, using the comparison theorem, we investigate some Pachpatte type integral inequalities on time scales, which provide explicit bounds on unknown functions. Our results extend some known dynamic inequalities on time scales, unify and extend some continuous inequalities and their corresponding discrete analogues. Some applications of the main results are given in the end of this paper.

We consider a paper of Banaś and Sadarangani (2008) [11] which deals with monotonicity properties of the superposition operator and their applications. An application of the monotonicity properties is to study the solvability of a quadratic Volterra integral equation. In this paper, we prepare an efficient numerical technique based on the fixed point method and quadrature rules to approximate a solution for quadratic Volterra integral equation. Then convergence of numerical scheme is proved by some theorems and some numerical examples are given to show applicability and accuracy of the numerical method and guarantee the theoretical results.

This paper is concerned with an operator equation on ordered Banach spaces. The existence and uniqueness of its’ positive solutions is obtained by using the properties of cones and monotone iterative technique. As applications, we utilize the results obtained in this paper to study the existence and uniqueness of positive solutions for two classes of integral equations.

In this paper, we establish the existence of triple positive solutions of a two-point boundary value problem for the nonlinear singular second-order differential equations of mixed type with a p-Laplacian operator. We also demonstrate that the results obtained can be applied to study certain higher order mixed boundary value problems. Finally, an example is given to demonstrate the use of the main results of this paper.

This paper presents a class of two-stage fuzzy programming with minimum-risk criteria in the sense of Value-at-Risk (VaR). Since the proposed two-stage fuzzy minimum-risk problem (FMRP) often includes fuzzy variable coefficients defined through possibility distributions with infinite supports, it is inherently an infinite-dimensional optimization problem that can rarely be solved directly. Thus, algorithm procedures for solving such an optimization problem must rely on soft computing and approximation schemes, which result in a finite-dimensional optimization problem. In this paper, we develop an approximation method to compute the objective function of the two-stage FMRP, and discuss the convergent results about the use of the approximation method in FMRP, including the convergence of the objective value, optimal value, and the optimal solutions. To apply the convergent results about the approximation method, we consider a two-stage fuzzy facility location-allocation (FLA) problem with VaR objective, and solve the problem indirectly by solving its approximating problem. Since the approximating fuzzy FLA problem is neither linear nor convex, conventional optimization algorithms cannot be used to solve it. In this paper, we design a hybrid particle swarm optimization (PSO) algorithm to solve the approximating fuzzy FLA problem. One numerical example with five facilities and ten customers is also presented to demonstrate the effectiveness of the designed algorithm.

In this paper, we consider minimizing multiple linear objective functions under a max-t-norm fuzzy relational equation constraint. Since the feasible domain of a max–Archimedean t-norm relational equation constraint is generally nonconvex, traditional mathematical programming techniques may have difficulty in yielding efficient solutions for such problems. In this paper, we apply the two-phase approach, utilizing the min operator and the average operator to aggregate those objectives, to yield an efficient solution. A numerical example is provided to illustrate the procedure.

Singularly perturbed boundary value problems often have solutions with very thinlayers in which the solution changes rapidly. This paper concentrates on the case where theses layers occur near the boundary, although our method can be applied to problems with interior layers. One technique to deal with the increased resolution requirements in these layers is the use of domain transformations. A coordinate stretching based transform allows to move collocation points into the layer, a requirement to resolve the layer accurately. Previously, such transformations have been studied in the context of finite-difference and spectral collocation methods. In this paper, we use radial basis functions (RBFs) to solve the boundary value problem. Specifically, we present a collocation method based on multiquadric (MQ) functions with an integral formulation combined with a coordinate transformation. We find that our scheme is ultimately more accurate than a recently proposed adaptive MQ scheme. The RBF scheme is also amenable to adaptivity.

In this paper, we propose a novel scheme for simulating geometric active contours (geometric flow) of one kind, applying multiquadric (MQ) quasi-interpolation. We first represent the geometric flow in its parametric form. Then we obtain the numerical scheme by using the derivatives of the quasi-interpolation to approximate the spatial derivative of each dependent variable and a forward difference to approximate the temporal derivative of each dependent variable. The resulting scheme is simple, efficient and easy to implement. Also images with complex boundaries can be more easily proposed on the basis of the good properties of the MQ quasi-interpolation. Several biomedical and astronomical examples of applications are shown in the paper. Comparisons with other methods are included to illustrate the validity of the method.

Many simulation algorithms (chemical reaction systems, differential systems arising from the modelling of transient behaviour in the process industries etc.) contain the numerical solution of systems of differential equations. For the efficient solution of the above mentioned problems, linear multistep methods or Runge–Kutta single-step methods are used. For the simulation of chemical procedures the radial Schrödinger equation is used frequently. In the present paper we will study a class of linear multistep methods. More specifically, the purpose of this paper is to develop an efficient algorithm for the approximate solution of the radial Schrödinger equation and related problems. This algorithm belongs in the category of the multistep methods. In order to produce an efficient multistep method the phase-lag property and its derivatives are used. Hence the main result of this paper is the development of an efficient multistep method for the numerical solution of systems of ordinary differential equations with oscillating or periodical solutions. The reason of their efficiency, as the analysis proved, is that the phase-lag and its derivatives are eliminated. Another reason of the efficiency of the new obtained methods is that they have high algebraic order

This paper discusses the multinational capital budgeting problem — when there are some candidate foreign projects, which project(s) should the investor choose? In the paper, special cash flows and value sources of foreign projects are introduced. Regarding project parameters such as construction costs, annual net operating cash flows, terminal values of the projects as well as the foreign exchange rates as uncertain variables, the paper proposes one new uncertain zero–one integer model for optimal multinational project selection. To solve the problem, a hybrid intelligent algorithm integrating the 99 Methods and genetic algorithm is provided. As an illustration, an application example is also presented.

This paper improves the algorithm for the construction of explicit bounds for the solutions of second order linear differential equations of the type [p(x)y′(x)]′+q(x)y(x)=0, p(x),q(x)>0, x>x0 described in a recent paper of the authors. The main improvements come from the introduction of new functionals devised by Trevisan and from the application of an enhanced version of the mean value theorem for integrals when some functions of the integrand are monotonic.

This paper has been motivated by the need to reduce the number of live animal tests in the development of an automated live-bird transfer system (LBTS) for the poultry meat-processing industry. Simulation-based models have been developed, which carefully address key engineering issues prior to live animal tests so that physical experiments can be focused on understanding reflex issues such as fear and escape behavior. To gain insights into the effects of operational timing on the LBTS handling performance, the multibody dynamics is modeled numerically based on the method of explicit dynamic finite element analysis (FEA) using off-the-shelf FEA packages. The findings also offer information on contact forces and their locations acting on the object’s body and legs by the compliant fingers and grippers respectively for optimizing designs and avoiding damage to the object. Specifically, this paper discusses computational issues such as time-step considerations and highly damped behavior of compliant fingers when modeling using dynamic FEA methods. The FEA model has been validated by comparing simulated handling of an ellipsoidal object by a pair of robotic hands with multiple compliant fingers against published experimental data. It is expected that the FEA-based method presented here can be extended to a spectrum of applications where flexible multibody dynamics involving large deformable contacts and highly damped behaviors plays an important role.

In this paper, on the basis of the optimal sine transform based approximation we propose a new preconditioner for the interface system arising in the fast Helmholtz solver [G. Bao, W. Sun, A fast algorithm for the electromagnetic scattering from a large cavity, SIAM J. Sci. Comput. 27 (2005) 553–574 (electronic)] for the electromagnetic scattering from a large cavity with layered media. We show that the spectrum of the preconditioned matrix is clustered around 1 if the preconditioner is not nearly singular. Numerical results show that the number of iterations of an preconditioned iterative method for the interface system is independent of the mesh size and the wavenumber. The computational cost of the fast method proposed in this paper for calculating the radar cross section, which is very important in electromagnetism, by means of fast Fourier transforms, is O(N2) on an N×N uniform partition of the unit square for the source free case.

A recent article on optimal replenishment policy of imperfect EMQ model by Chiu [S.W. Chiu, Optimal replenishment policy for imperfect quality EMQ model with rework and backlogging, Applied Stochastic Models in Business and Industry 23 (2007) 165–178], used mathematical modeling and differential calculus to derive the optimal ordering policy that minimizes overall costs. This paper presents a straightforward algebraic approach to replace the use of calculus on the cost function for determining the optimal replenishment solutions as well as the long-run average production-inventory costs for such an imperfect EMQ model. The algebraic method presented in this paper may enable students or practitioners with little or no knowledge of calculus to learn or to manage with ease the real-life manufacturing systems.

WOS: 000293718900016 Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, first we correct some of the problematic cases in a previous paper by Aktas and Cagman [H. Aktas, N. Cagman, Soft sets and soft groups, Inf. Sci. 177 (2007) 2726-2735]. Moreover, we introduce the concepts of normalistic soft group and normalistic soft group homomorphism, study their several related properties, and investigate some structures that are preserved under normalistic soft group homomorphisms. (C) 2011 Elsevier Ltd. All rights reserved.

This paper presents open-loop and closed-loop attitude control strategies of miniature spacecraft using pseudowheels, which are composed of multiple bimorphs and are mounted on the three principal axes of the spacecraft. Due to the conservation of angular momentum, the vibrations of the bimorph excited by applied voltages can rotate the spacecraft. By applying a sequence of rotations along the three axes, the attitude of the spacecraft can be changed. The modeling of the spacecraft–pseudowheel system includes the inverse piezoelectric effect and the gravity gradient torques. Since one cannot guarantee that a solution will be found for every rotation sequence, this paper proposes an approach to solve this problem. In addition, the voltages applied to the bimorphs are reduced to meet the specifications of the voltage amplifiers. Furthermore, a closed-loop attitude control strategy is presented to reduce the applied voltages and to compensate the attitude error caused by the gravity gradient torques.

A paper by D.L. Reiner researched function sequences of binomial type and established many interesting theorems. But because of an oversight in a lemma, some theorems in his paper need to be revised. This paper will revise these theorems and establish some new results on sequences of binomial type.

There are verities of useful Krylov subspace methods to solve nonsymmetric linear system of equations. GMRES is one of the best Krylov solvers with several different variants to solve large sparse linear systems. Any GMRES implementation has some advantages. As the solution of ill-posed problems are important. In this paper, some GMRES variants are discussed and applied to solve these kinds of problems. Residual smoothing techniques are efficient ways to accelerate the convergence speed of some iterative methods like CG variants. At the end of this paper, some residual smoothing techniques are applied for different GMRES methods to test the influence of these techniques on GMRES implementations.

This paper reports the magnetohydrodynamic (MHD) flow and heat transfer characteristics of a second grade fluid in a channel. Analytic technique namely the homotopy analysis method (HAM) is used to solve the momentum and energy equations. The important findings in this paper are the effects of second grade parameter, Hartmann number, Reynolds number, thermal radiation parameter, Prandtl and local Eckert numbers on the velocity, temperature, skin friction coefficient and Nusselt number.

The purpose of this paper is to introduce a new iterative scheme for finding a common fixed point of a finite family of strict pseudo-contractions. The results obtained in this paper extend and improve the corresponding results of Marino, Colao, Qin and Kang [G. Marino, V. Colao, X. Qin, S. M. Kang, Strong convergence of the modified Mann iterative method for strict pseudo-contractions, Comput. Math. Appl. 57 (2009) 455–465].

This paper deals with the existence of positive solutions for the fourth-order nonlinear ordinary differential equation x⁗(t)=λg(t)f(t,x(t),x″(t)),00, and ξi∈(0,1),ηi∈[0,+∞)(i=1,2,…,m−2). By means of a fixed-point theorem due to Krasnaselskii, some new existence results of positive solutions for the above multi-point boundary value problem are obtained, which improve the main results of Graef et al. [J.R. Graef, C. Qian, B. Yang, A three-point boundary value problem for nonlinear fourth-order differential equations, J. Math. Anal. Appl. 287 (2003) 217–233]. An example is given to demonstrate the main results of this paper.

The object of this paper is to perform an analysis of the sensitivity for convex vector programs with inequality constraints by examining the quantitative behavior of a certain set of optima according to changes of right-hand side parameters included in the program. The results in the paper prove that the sensitivity of the program depends on the solution of a dual program and its sensitivity.

In this paper, we mainly discuss an optimal portfolio selection model with liability management and Markov switching which maximize the expected final surplus under constrained variance. Because linear quadratic control is a basic method for the M–V problem, in this paper we begin with the general stochastic linear quadratic model, and obtain the optimal solution of the problem. Exactly, the analytical optimal portfolio strategy is derived in this paper. Furthermore, we demonstrate that a special case is consistent with those results of Chiu and Li (2006) [3].

In an age of cloud computing, users do not access a particular system, but a service. In a more centralized and seamless environment, it becomes important to view software as a service, or “SaaS”. In particular, ubiquitous healthcare urgently needs to reflect the view of the healthcare system as a service, “HaaS”, for the purposes of health promotion, disease prevention, and general well-being. Overcoming the current limitations of medical technologies, medical practices, and business, HaaS requires a more sustainable environment, including addressing issues of interoperability, service reuse, maintenance, and integration. This paper suggests a framework for realizing a HaaS model, focusing on vital signs-oriented systems. The proposed framework consists of four distinct modules: three modules for receiving, transforming, and analyzing vital signs and the fourth module, called a service-oriented architecture (SOA) component module, enabling access to medical services. We believe that the framework promises dramatic reductions in software development costs on the one hand and lays a foundation for users to access a rich and seamless service in a more convenient way on the other. This paper describes a framework for the HaaS model and presents an example service that we implemented, a calorie-tracking service, based on it.

In this paper, existence criteria of positive solutions to a class of nonlinear first-order periodic boundary value problems of impulsive dynamic equations on time scales are obtained. The main tool used in this paper is the well-known Guo–Krasnoselskii fixed-point theorem.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy).This article has been retracted at the request of the Editor-in-Chief.This article has been retracted at the request of the editor as it duplicates significant parts of a paper that had already appeared in Appl. Math. Lett., 24 (2011) 97–102, doi:10.1016/j.aml.2010.08.025. One of the conditions of submission of a paper for publication is that authors declare explicitly that the paper is not under consideration for publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

In this paper, we introduce and consider a new class of equilibrium variational inequalities, called the mixed general equilibrium bifunction variational inequalities. We suggest and analyze some proximal methods for solving mixed general equilibrium bifunction variational inequalities using the auxiliary principle technique. Convergence of these methods is considered under some mild suitable conditions. Several cases are also discussed. Results in this paper include some new and known results as special cases.