Lötstedt, Erik; Jentschura, Ulrich D
2009-02-01
In the relativistic and the nonrelativistic theoretical treatment of moderate and high-power laser-matter interaction, the generalized Bessel function occurs naturally when a Schrödinger-Volkov and Dirac-Volkov solution is expanded into plane waves. For the evaluation of cross sections of quantum electrodynamic processes in a linearly polarized laser field, it is often necessary to evaluate large arrays of generalized Bessel functions, of arbitrary index but with fixed arguments. We show that the generalized Bessel function can be evaluated, in a numerically stable way, by utilizing a recurrence relation and a normalization condition only, without having to compute any initial value. We demonstrate the utility of the method by illustrating the quantum-classical correspondence of the Dirac-Volkov solutions via numerical calculations.
Renormgroup symmetry for solution functionals
International Nuclear Information System (INIS)
Shirkov, D.V.; Kovalev, V.F.
2004-01-01
The paper contains generalization of the renormgroup algorithm for boundary value problems of mathematical physics and related concept of the renormgroup symmetry, formulated earlier by the authors with reference to models based on differential equations. These algorithm and symmetry are formulated now for models with nonlocal (integral) equations. We discuss in detail and illustrate by examples the applications of the generalized algorithm to models with nonlocal terms which appear as linear functionals of the solution. (author)
Discrete Riccati equation solutions: Distributed algorithms
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available In this paper new distributed algorithms for the solution of the discrete Riccati equation are introduced. The algorithms are used to provide robust and computational efficient solutions to the discrete Riccati equation. The proposed distributed algorithms are theoretically interesting and computationally attractive.
Energy functions for regularization algorithms
Delingette, H.; Hebert, M.; Ikeuchi, K.
1991-01-01
Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.
Elementary functions algorithms and implementation
Muller, Jean-Michel
2016-01-01
This textbook presents the concepts and tools necessary to understand, build, and implement algorithms for computing elementary functions (e.g., logarithms, exponentials, and the trigonometric functions). Both hardware- and software-oriented algorithms are included, along with issues related to accurate floating-point implementation. This third edition has been updated and expanded to incorporate the most recent advances in the field, new elementary function algorithms, and function software. After a preliminary chapter that briefly introduces some fundamental concepts of computer arithmetic, such as floating-point arithmetic and redundant number systems, the text is divided into three main parts. Part I considers the computation of elementary functions using algorithms based on polynomial or rational approximations and using table-based methods; the final chapter in this section deals with basic principles of multiple-precision arithmetic. Part II is devoted to a presentation of “shift-and-add” algorithm...
Algorithm for programming function generators
International Nuclear Information System (INIS)
Bozoki, E.
1981-01-01
The present paper deals with a mathematical problem, encountered when driving a fully programmable μ-processor controlled function generator. An algorithm is presented to approximate a desired function by a set of straight segments in such a way that additional restrictions (hardware imposed) are also satisfied. A computer program which incorporates this algorithm and automatically generates the necessary input for the function generator for a broad class of desired functions is also described
On the multi-level solution algorithm for Markov chains
Energy Technology Data Exchange (ETDEWEB)
Horton, G. [Univ. of Erlangen, Nuernberg (Germany)
1996-12-31
We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.
An algorithm for the solution of dynamic linear programs
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
Implementation of trigonometric function using CORDIC algorithms
Mokhtar, A. S. N.; Ayub, M. I.; Ismail, N.; Daud, N. G. Nik
2018-02-01
In 1959, Jack E. Volder presents a brand new formula to the real-time solution of the equation raised in navigation system. This new algorithm was the most beneficial replacement of analog navigation system by the digital. The CORDIC (Coordinate Rotation Digital Computer) algorithm are used for the rapid calculation associated with elementary operates like trigonometric function, multiplication, division and logarithm function, and also various conversions such as conversion of rectangular to polar coordinate including the conversion between binary coded information. In this current time CORDIC formula have many applications in the field of communication, signal processing, 3-D graphics, and others. This paper would be presents the trigonometric function implementation by using CORDIC algorithm in rotation mode for circular coordinate system. The CORDIC technique is used in order to generating the output angle between range 0o to 90o and error analysis is concern. The result showed that the average percentage error is about 0.042% at angles between ranges 00 to 900. But the average percentage error rose up to 45% at angle 90o and above. So, this method is very accurate at the 1st quadrant. The mirror properties method is used to find out an angle at 2nd, 3rd and 4th quadrant.
Genetic algorithm solution for partial digest problem.
Ahrabian, Hayedeh; Ganjtabesh, Mohammad; Nowzari-Dalini, Abbas; Razaghi-Moghadam-Kashani, Zahra
2013-01-01
One of the fundamental problems in computational biology is the construction of physical maps of chromosomes from the hybridisation experiments between unique probes and clones of chromosome fragments. Before introducing the shotgun sequencing method, Partial Digest Problem (PDP) was an intractable problem used to construct the physical maps of DNA sequence in molecular biology. In this paper, we develop a novel Genetic Algorithm (GA) for solving the PDP. This algorithm is implemented and compared with well-known existing algorithms on different types of random and real instances data, and the obtained results show the efficiency of our algorithm. Also, our GA is adapted to handle the erroneous data and their efficiency is presented for the large instances of this problem.
Quantum algorithms for testing Boolean functions
Directory of Open Access Journals (Sweden)
Erika Andersson
2010-06-01
Full Text Available We discuss quantum algorithms, based on the Bernstein-Vazirani algorithm, for finding which variables a Boolean function depends on. There are 2^n possible linear Boolean functions of n variables; given a linear Boolean function, the Bernstein-Vazirani quantum algorithm can deterministically identify which one of these Boolean functions we are given using just one single function query. The same quantum algorithm can also be used to learn which input variables other types of Boolean functions depend on, with a success probability that depends on the form of the Boolean function that is tested, but does not depend on the total number of input variables. We also outline a procedure to futher amplify the success probability, based on another quantum algorithm, the Grover search.
A hybrid artificial bee colony algorithm for numerical function optimization
Alqattan, Zakaria N.; Abdullah, Rosni
2015-02-01
Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).
Critical function monitoring system algorithm development
International Nuclear Information System (INIS)
Harmon, D.L.
1984-01-01
Accurate critical function status information is a key to operator decision-making during events threatening nuclear power plant safety. The Critical Function Monitoring System provides continuous critical function status monitoring by use of algorithms which mathematically represent the processes by which an operating staff would determine critical function status. This paper discusses in detail the systematic design methodology employed to develop adequate Critical Function Monitoring System algorithms
Lyapunov Function Synthesis - Algorithm and Software
DEFF Research Database (Denmark)
Leth, Tobias; Sloth, Christoffer; Wisniewski, Rafal
2016-01-01
In this paper we introduce an algorithm for the synthesis of polynomial Lyapunov functions for polynomial vector fields. The Lyapunov function is a continuous piecewisepolynomial defined on simplices, which compose a collection of simplices. The algorithm is elaborated and crucial features are ex...
Static Load Balancing Algorithms In Cloud Computing Challenges amp Solutions
Directory of Open Access Journals (Sweden)
Nadeem Shah
2015-08-01
Full Text Available Abstract Cloud computing provides on-demand hosted computing resources and services over the Internet on a pay-per-use basis. It is currently becoming the favored method of communication and computation over scalable networks due to numerous attractive attributes such as high availability scalability fault tolerance simplicity of management and low cost of ownership. Due to the huge demand of cloud computing efficient load balancing becomes critical to ensure that computational tasks are evenly distributed across servers to prevent bottlenecks. The aim of this review paper is to understand the current challenges in cloud computing primarily in cloud load balancing using static algorithms and finding gaps to bridge for more efficient static cloud load balancing in the future. We believe the ideas suggested as new solution will allow researchers to redesign better algorithms for better functionalities and improved user experiences in simple cloud systems. This could assist small businesses that cannot afford infrastructure that supports complex amp dynamic load balancing algorithms.
Massively Parallel Algorithms for Solution of Schrodinger Equation
Fijany, Amir; Barhen, Jacob; Toomerian, Nikzad
1994-01-01
In this paper massively parallel algorithms for solution of Schrodinger equation are developed. Our results clearly indicate that the Crank-Nicolson method, in addition to its excellent numerical properties, is also highly suitable for massively parallel computation.
A discretized algorithm for the solution of a constrained, continuous ...
African Journals Online (AJOL)
A discretized algorithm for the solution of a constrained, continuous quadratic control problem. ... The results obtained show that the Discretized constrained algorithm (DCA) is much more accurate and more efficient than some of these techniques, particularly the FSA. Journal of the Nigerian Association of Mathematical ...
ALGORITHM OF SELECTION EFFECTIVE SOLUTIONS FOR REPROFILING OF INDUSTRIAL BUILDINGS
Directory of Open Access Journals (Sweden)
MENEJLJUK A. I.
2016-08-01
Full Text Available Raising of problem.Non-compliance requirements of today's industrial enterprises, which were built during the Soviet period, as well as significant technical progress, economic reform and transition to market principles of performance evaluation leading to necessity to change their target and functionality. The technical condition of many industrial buildings in Ukraine allows to exploit them for decades.Redesigning manufacturing enterprises allows not only to reduce the cost of construction, but also to obtain new facilities in the city. Despite the large number of industrial buildings that have lost their effectiveness and relevance, as well as a significant investor interest in these objects, the scope of redevelopment in the construction remains unexplored. Analysis researches on the topic. The problem of reconstruction of industrial buildings considered in Topchy D. [3], Travin V. [9], as well as in the work of other scientists. However, there are no rules in regulatory documents and system studies for improving the organization of the reconstruction of buildings at realigning. The purpose of this work is the development an algorithm of actions for selection of effective organizational decisions at the planning stage of a reprofiling project of industrial buildings. The proposed algorithm allows you to select an effective organizational and technological solution for the re-profiling of industrial buildings, taking into account features of the building, its location, its state of structures and existing restrictions. The most effective organizational solution allows realize the reprofiling project of an industrial building in the most possible short terms and with the lowest possible use of material resources, taking into account the available features and restrictions. Conclusion. Each object has a number of unique features that necessary for considering at choosing an effective reprofiling variant. The developed algorithm for selecting
International Nuclear Information System (INIS)
Chatterjee, Kausik; Roadcap, John R.; Singh, Surendra
2014-01-01
The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications
Energy Technology Data Exchange (ETDEWEB)
Chatterjee, Kausik, E-mail: kausik.chatterjee@aggiemail.usu.edu [Strategic and Military Space Division, Space Dynamics Laboratory, North Logan, UT 84341 (United States); Center for Atmospheric and Space Sciences, Utah State University, Logan, UT 84322 (United States); Roadcap, John R., E-mail: john.roadcap@us.af.mil [Air Force Research Laboratory, Kirtland AFB, NM 87117 (United States); Singh, Surendra, E-mail: surendra-singh@utulsa.edu [Department of Electrical Engineering, The University of Tulsa, Tulsa, OK 74104 (United States)
2014-11-01
The objective of this paper is the exposition of a recently-developed, novel Green's function Monte Carlo (GFMC) algorithm for the solution of nonlinear partial differential equations and its application to the modeling of the plasma sheath region around a cylindrical conducting object, carrying a potential and moving at low speeds through an otherwise neutral medium. The plasma sheath is modeled in equilibrium through the GFMC solution of the nonlinear Poisson–Boltzmann (NPB) equation. The traditional Monte Carlo based approaches for the solution of nonlinear equations are iterative in nature, involving branching stochastic processes which are used to calculate linear functionals of the solution of nonlinear integral equations. Over the last several years, one of the authors of this paper, K. Chatterjee has been developing a philosophically-different approach, where the linearization of the equation of interest is not required and hence there is no need for iteration and the simulation of branching processes. Instead, an approximate expression for the Green's function is obtained using perturbation theory, which is used to formulate the random walk equations within the problem sub-domains where the random walker makes its walks. However, as a trade-off, the dimensions of these sub-domains have to be restricted by the limitations imposed by perturbation theory. The greatest advantage of this approach is the ease and simplicity of parallelization stemming from the lack of the need for iteration, as a result of which the parallelization procedure is identical to the parallelization procedure for the GFMC solution of a linear problem. The application area of interest is in the modeling of the communication breakdown problem during a space vehicle's re-entry into the atmosphere. However, additional application areas are being explored in the modeling of electromagnetic propagation through the atmosphere/ionosphere in UHF/GPS applications.
Comparing the Robustness of Evolutionary Algorithms on the Basis of Benchmark Functions
Directory of Open Access Journals (Sweden)
DENIZ ULKER, E.
2013-05-01
Full Text Available In real-world optimization problems, even though the solution quality is of great importance, the robustness of the solution is also an important aspect. This paper investigates how the optimization algorithms are sensitive to the variations of control parameters and to the random initialization of the solution set for fixed control parameters. The comparison is performed of three well-known evolutionary algorithms which are Particle Swarm Optimization (PSO algorithm, Differential Evolution (DE algorithm and the Harmony Search (HS algorithm. Various benchmark functions with different characteristics are used for the evaluation of these algorithms. The experimental results show that the solution quality of the algorithms is not directly related to their robustness. In particular, the algorithm that is highly robust can have a low solution quality, or the algorithm that has a high quality of solution can be quite sensitive to the parameter variations.
FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS
Directory of Open Access Journals (Sweden)
Evans BAIDOO
2017-03-01
Full Text Available Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.
Algorithms for synthesizing management solutions based on OLAP-technologies
Pishchukhin, A. M.; Akhmedyanova, G. F.
2018-05-01
OLAP technologies are a convenient means of analyzing large amounts of information. An attempt was made in their work to improve the synthesis of optimal management decisions. The developed algorithms allow forecasting the needs and accepted management decisions on the main types of the enterprise resources. Their advantage is the efficiency, based on the simplicity of quadratic functions and differential equations of only the first order. At the same time, the optimal redistribution of resources between different types of products from the assortment of the enterprise is carried out, and the optimal allocation of allocated resources in time. The proposed solutions can be placed on additional specially entered coordinates of the hypercube representing the data warehouse.
Alternative solution algorithm for coupled thermal-hydraulic problems
International Nuclear Information System (INIS)
Farnsworth, D.A.; Rice, J.G.
1986-01-01
A thermal-hydraulic system involves flow of a fluid for which a combined solution of the continuity, momentum, and energy equations is required. When the solutions of the energy and momentum fields are dependent on each other, the system is said to be thermally coupled. A common problem encountered in the numerical solution of strongly coupled thermal-hydraulic problems is a very slow rate of convergence or a complete lack of convergence. Many times this degradation in convergence is due to the lack of true coupling between the energy and momentum fields during the iteration process. In the most widely used solution algorithms - such as the SIMPLE algorithm and its many variants - a sequential solution technique is required. That is, the solution process alternates between the flow and energy fields until a converged solution is obtained. This approach allows only implicit energy-momentum coupling. To improve the convergence rate for strongly coupled problems, a practical solution algorithm that can accommodate true energy-momentum coupling terms was developed. A complete simultaneous (versus sequential) solution of the governing conservation equations utilizing a line-by-line solution was developed and direct coupling terms between the momentum and energy fields were added utilizing a modified Newton-Raphson technique
A Cooperative Harmony Search Algorithm for Function Optimization
Directory of Open Access Journals (Sweden)
Gang Li
2014-01-01
Full Text Available Harmony search algorithm (HS is a new metaheuristic algorithm which is inspired by a process involving musical improvisation. HS is a stochastic optimization technique that is similar to genetic algorithms (GAs and particle swarm optimizers (PSOs. It has been widely applied in order to solve many complex optimization problems, including continuous and discrete problems, such as structure design, and function optimization. A cooperative harmony search algorithm (CHS is developed in this paper, with cooperative behavior being employed as a significant improvement to the performance of the original algorithm. Standard HS just uses one harmony memory and all the variables of the object function are improvised within the harmony memory, while the proposed algorithm CHS uses multiple harmony memories, so that each harmony memory can optimize different components of the solution vector. The CHS was then applied to function optimization problems. The results of the experiment show that CHS is capable of finding better solutions when compared to HS and a number of other algorithms, especially in high-dimensional problems.
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
Algorithm of Functional Musculoskeletal Disorders Diagnostics
Alexandra P. Eroshenko
2012-01-01
The article scientifically justifies the algorithm of complex diagnostics of functional musculoskeletal disorders during resort treatment, aimed at the optimal application of modern methods of physical rehabilitation (correction programs formation), based on diagnostic methodologies findings
Algorithm of Functional Musculoskeletal Disorders Diagnostics
Directory of Open Access Journals (Sweden)
Alexandra P. Eroshenko
2012-04-01
Full Text Available The article scientifically justifies the algorithm of complex diagnostics of functional musculoskeletal disorders during resort treatment, aimed at the optimal application of modern methods of physical rehabilitation (correction programs formation, based on diagnostic methodologies findings
Directory of Open Access Journals (Sweden)
Ion LUNGU
2012-01-01
Full Text Available In this paper, we research, analyze and develop optimization solutions for the parallel reduction function using graphics processing units (GPUs that implement the Compute Unified Device Architecture (CUDA, a modern and novel approach for improving the software performance of data processing applications and algorithms. Many of these applications and algorithms make use of the reduction function in their computational steps. After having designed the function and its algorithmic steps in CUDA, we have progressively developed and implemented optimization solutions for the reduction function. In order to confirm, test and evaluate the solutions' efficiency, we have developed a custom tailored benchmark suite. We have analyzed the obtained experimental results regarding: the comparison of the execution time and bandwidth when using graphic processing units covering the main CUDA architectures (Tesla GT200, Fermi GF100, Kepler GK104 and a central processing unit; the data type influence; the binary operator's influence.
Generalization of Risch's algorithm to special functions
International Nuclear Information System (INIS)
Raab, Clemens G.
2013-05-01
Symbolic integration deals with the evaluation of integrals in closed form. We present an overview of Risch's algorithm including recent developments. The algorithms discussed are suited for both indefinite and definite integration. They can also be used to compute linear relations among integrals and to find identities for special functions given by parameter integrals. The aim of this presentation is twofold: to introduce the reader to some basic ideas of differential algebra in the context of integration and to raise awareness in the physics community of computer algebra algorithms for indefinite and definite integration.
Directory of Open Access Journals (Sweden)
Alkın Yurtkuran
2016-01-01
Full Text Available The artificial bee colony (ABC algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.
Yurtkuran, Alkın; Emel, Erdal
2016-01-01
The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.
AUTOMATION PROGRAM FOR RECOGNITION OF ALGORITHM SOLUTION OF MATHEMATIC TASK
Directory of Open Access Journals (Sweden)
Denis N. Butorin
2014-01-01
Full Text Available In the article are been describing technology for manage of testing task in computer program. It was found for recognition of algorithm solution of mathematic task. There are been justifi ed the using hierarchical structure for a special set of testing questions. Also, there has been presented the release of the described tasks in the computer program openSEE.
AUTOMATION PROGRAM FOR RECOGNITION OF ALGORITHM SOLUTION OF MATHEMATIC TASK
Denis N. Butorin
2014-01-01
In the article are been describing technology for manage of testing task in computer program. It was found for recognition of algorithm solution of mathematic task. There are been justifi ed the using hierarchical structure for a special set of testing questions. Also, there has been presented the release of the described tasks in the computer program openSEE.
The linear ordering problem: an algorithm for the optimal solution ...
African Journals Online (AJOL)
In this paper we describe and implement an algorithm for the exact solution of the Linear Ordering problem. Linear Ordering is the problem of finding a linear order of the nodes of a graph such that the sum of the weights which are consistent with this order is as large as possible. It is an NP - Hard combinatorial optimisation ...
Voytishek, Anton V.; Shipilov, Nikolay M.
2017-11-01
In this paper, the systematization of numerical (implemented on a computer) randomized functional algorithms for approximation of a solution of Fredholm integral equation of the second kind is carried out. Wherein, three types of such algorithms are distinguished: the projection, the mesh and the projection-mesh methods. The possibilities for usage of these algorithms for solution of practically important problems is investigated in detail. The disadvantages of the mesh algorithms, related to the necessity of calculation values of the kernels of integral equations in fixed points, are identified. On practice, these kernels have integrated singularities, and calculation of their values is impossible. Thus, for applied problems, related to solving Fredholm integral equation of the second kind, it is expedient to use not mesh, but the projection and the projection-mesh randomized algorithms.
Vorozheikin, A.; Gonchar, T.; Panfilov, I.; Sopov, E.; Sopov, S.
2009-01-01
A new algorithm for the solution of complex constrained optimization problems based on the probabilistic genetic algorithm with optimal solution prediction is proposed. The efficiency investigation results in comparison with standard genetic algorithm are presented.
Naturally selecting solutions: the use of genetic algorithms in bioinformatics.
Manning, Timmy; Sleator, Roy D; Walsh, Paul
2013-01-01
For decades, computer scientists have looked to nature for biologically inspired solutions to computational problems; ranging from robotic control to scheduling optimization. Paradoxically, as we move deeper into the post-genomics era, the reverse is occurring, as biologists and bioinformaticians look to computational techniques, to solve a variety of biological problems. One of the most common biologically inspired techniques are genetic algorithms (GAs), which take the Darwinian concept of natural selection as the driving force behind systems for solving real world problems, including those in the bioinformatics domain. Herein, we provide an overview of genetic algorithms and survey some of the most recent applications of this approach to bioinformatics based problems.
Linear scaling of density functional algorithms
International Nuclear Information System (INIS)
Stechel, E.B.; Feibelman, P.J.; Williams, A.R.
1993-01-01
An efficient density functional algorithm (DFA) that scales linearly with system size will revolutionize electronic structure calculations. Density functional calculations are reliable and accurate in determining many condensed matter and molecular ground-state properties. However, because current DFA's, including methods related to that of Car and Parrinello, scale with the cube of the system size, density functional studies are not routinely applied to large systems. Linear scaling is achieved by constructing functions that are both localized and fully occupied, thereby eliminating the need to calculate global eigenfunctions. It is, however, widely believed that exponential localization requires the existence of an energy gap between the occupied and unoccupied states. Despite this, the authors demonstrate that linear scaling can still be achieved for metals. Using a linear scaling algorithm, they have explicitly constructed localized, almost fully occupied orbitals for the quintessential metallic system, jellium. The algorithm is readily generalizable to any system geometry and Hamiltonian. They will discuss the conceptual issues involved, convergence properties and scaling for their new algorithm
Evolutionary Algorithms Approach to the Solution of Damage Detection Problems
Salazar Pinto, Pedro Yoajim; Begambre, Oscar
2010-09-01
In this work is proposed a new Self-Configured Hybrid Algorithm by combining the Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA). The aim of the proposed strategy is to increase the stability and accuracy of the search. The central idea is the concept of Guide Particle, this particle (the best PSO global in each generation) transmits its information to a particle of the following PSO generation, which is controlled by the GA. Thus, the proposed hybrid has an elitism feature that improves its performance and guarantees the convergence of the procedure. In different test carried out in benchmark functions, reported in the international literature, a better performance in stability and accuracy was observed; therefore the new algorithm was used to identify damage in a simple supported beam using modal data. Finally, it is worth noting that the algorithm is independent of the initial definition of heuristic parameters.
An airport surface surveillance solution based on fusion algorithm
Liu, Jianliang; Xu, Yang; Liang, Xuelin; Yang, Yihuang
2017-01-01
In this paper, we propose an airport surface surveillance solution combined with Multilateration (MLAT) and Automatic Dependent Surveillance Broadcast (ADS-B). The moving target to be monitored is regarded as a linear stochastic hybrid system moving freely and each surveillance technology is simplified as a sensor with white Gaussian noise. The dynamic model of target and the observation model of sensor are established in this paper. The measurements of sensors are filtered properly by estimators to get the estimation results for current time. Then, we analysis the characteristics of two fusion solutions proposed, and decide to use the scheme based on sensor estimation fusion for our surveillance solution. In the proposed fusion algorithm, according to the output of estimators, the estimation error is quantified, and the fusion weight of each sensor is calculated. The two estimation results are fused with weights, and the position estimation of target is computed accurately. Finally the proposed solution and algorithm are validated by an illustrative target tracking simulation.
An algorithm for constructing Lyapunov functions
Directory of Open Access Journals (Sweden)
Sigurdur Freyr Hafstein
2007-08-01
Full Text Available In this monograph we develop an algorithm for constructing Lyapunov functions for arbitrary switched dynamical systems $dot{mathbf{x}} = mathbf{f}_sigma(t,mathbf{x}$, possessing a uniformly asymptotically stable equilibrium. Let $dot{mathbf{x}}=mathbf{f}_p(t,mathbf{x}$, $pinmathcal{P}$, be the collection of the ODEs, to which the switched system corresponds. The number of the vector fields $mathbf{f}_p$ on the right-hand side of the differential equation is assumed to be finite and we assume that their components $f_{p,i}$ are $mathcal{C}^2$ functions and that we can give some bounds, not necessarily close, on their second-order partial derivatives. The inputs of the algorithm are solely a finite number of the function values of the vector fields $mathbf{f}_p$ and these bounds. The domain of the Lyapunov function constructed by the algorithm is only limited by the size of the equilibrium's region of attraction. Note, that the concept of a Lyapunov function for the arbitrary switched system $dot{mathbf{x}} = mathbf{f}_sigma(t,mathbf{x}$ is equivalent to the concept of a common Lyapunov function for the systems $dot{mathbf{x}}=mathbf{f}_p(t,mathbf{x}$, $pinmathcal{P}$, and that if $mathcal{P}$ contains exactly one element, then the switched system is just a usual ODE $dot{mathbf{x}}=mathbf{f}(t,mathbf{x}$. We give numerous examples of Lyapunov functions constructed by our method at the end of this monograph.
Institute of Scientific and Technical Information of China (English)
2008-01-01
Using functional derivative technique in quantum field theory, the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations. The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by introducing the time translation operator. The functional partial differential evolution equations were solved by algebraic dynam-ics. The algebraic dynamics solutions are analytical in Taylor series in terms of both initial functions and time. Based on the exact analytical solutions, a new nu-merical algorithm—algebraic dynamics algorithm was proposed for partial differ-ential evolution equations. The difficulty of and the way out for the algorithm were discussed. The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.
A new algorithm for the integration of exponential and logarithmic functions
Rothstein, M.
1977-01-01
An algorithm for symbolic integration of functions built up from the rational functions by repeatedly applying either the exponential or logarithm functions is discussed. This algorithm does not require polynomial factorization nor partial fraction decomposition and requires solutions of linear systems with only a small number of unknowns. It is proven that if this algorithm is applied to rational functions over the integers, a computing time bound for the algorithm can be obtained which is a polynomial in a bound on the integer length of the coefficients, and in the degrees of the numerator and denominator of the rational function involved.
Special solutions of neutral functional differential equations
Directory of Open Access Journals (Sweden)
Győri István
2001-01-01
Full Text Available For a system of nonlinear neutral functional differential equations we prove the existence of an -parameter family of "special solutions" which characterize the asymptotic behavior of all solutions at infinity. For retarded functional differential equations the special solutions used in this paper were introduced by Ryabov.
An Algorithm for Isolating the Real Solutions of Piecewise Algebraic Curves
Directory of Open Access Journals (Sweden)
Jinming Wu
2011-01-01
to compute the real solutions of two piecewise algebraic curves. It is primarily based on the Krawczyk-Moore iterative algorithm and good initial iterative interval searching algorithm. The proposed algorithm is relatively easy to implement.
Directory of Open Access Journals (Sweden)
Arazi Idrus
2017-12-01
Full Text Available In this paper, we present our work-in-progress of a proposed framework for automated negotiation in the construction domain. The proposed framework enables software agents to conduct negotiations and autonomously make value-based decisions. The framework consists of three main components which are, solution generator algorithm, negotiation algorithm, and conflict resolution algorithm. This paper extends the discussion on the solution generator algorithm that enables software agents to generate solutions and rank them from 1st to nth solution for the negotiation stage of the operation. The solution generator algorithm consists of three steps which are, review solutions, rank solutions, and form ranked solutions. For validation purpose, we present a scenario that utilizes the proposed algorithm to rank solutions. The validation shows that the algorithm is promising, however, it also highlights the conflict between different parties that needs further negotiation action.
A Hybrid Algorithm for Optimizing Multi- Modal Functions
Institute of Scientific and Technical Information of China (English)
Li Qinghua; Yang Shida; Ruan Youlin
2006-01-01
A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed. Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.
Incorporating functional inter-relationships into protein function prediction algorithms
Directory of Open Access Journals (Sweden)
Kumar Vipin
2009-05-01
Full Text Available Abstract Background Functional classification schemes (e.g. the Gene Ontology that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches. Results We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the k-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of
Evolutionary Algorithms for Boolean Functions in Diverse Domains of Cryptography.
Picek, Stjepan; Carlet, Claude; Guilley, Sylvain; Miller, Julian F; Jakobovic, Domagoj
2016-01-01
The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.
Bodin, Jacques
2015-03-01
In this study, new multi-dimensional time-domain random walk (TDRW) algorithms are derived from approximate one-dimensional (1-D), two-dimensional (2-D), and three-dimensional (3-D) analytical solutions of the advection-dispersion equation and from exact 1-D, 2-D, and 3-D analytical solutions of the pure-diffusion equation. These algorithms enable the calculation of both the time required for a particle to travel a specified distance in a homogeneous medium and the mass recovery at the observation point, which may be incomplete due to 2-D or 3-D transverse dispersion or diffusion. The method is extended to heterogeneous media, represented as a piecewise collection of homogeneous media. The particle motion is then decomposed along a series of intermediate checkpoints located on the medium interface boundaries. The accuracy of the multi-dimensional TDRW method is verified against (i) exact analytical solutions of solute transport in homogeneous media and (ii) finite-difference simulations in a synthetic 2-D heterogeneous medium of simple geometry. The results demonstrate that the method is ideally suited to purely diffusive transport and to advection-dispersion transport problems dominated by advection. Conversely, the method is not recommended for highly dispersive transport problems because the accuracy of the advection-dispersion TDRW algorithms degrades rapidly for a low Péclet number, consistent with the accuracy limit of the approximate analytical solutions. The proposed approach provides a unified methodology for deriving multi-dimensional time-domain particle equations and may be applicable to other mathematical transport models, provided that appropriate analytical solutions are available.
Improved Solutions for the Optimal Coordination of DOCRs Using Firefly Algorithm
Directory of Open Access Journals (Sweden)
Muhammad Sulaiman
2018-01-01
Full Text Available Nature-inspired optimization techniques are useful tools in electrical engineering problems to minimize or maximize an objective function. In this paper, we use the firefly algorithm to improve the optimal solution for the problem of directional overcurrent relays (DOCRs. It is a complex and highly nonlinear constrained optimization problem. In this problem, we have two types of design variables, which are variables for plug settings (PSs and the time dial settings (TDSs for each relay in the circuit. The objective function is to minimize the total operating time of all the basic relays to avoid unnecessary delays. We have considered four models in this paper which are IEEE (3-bus, 4-bus, 6-bus, and 8-bus models. From the numerical results, it is obvious that the firefly algorithm with certain parameter settings performs better than the other state-of-the-art algorithms.
A solution to the economic dispatch using EP based SA algorithm on large scale power system
Energy Technology Data Exchange (ETDEWEB)
Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605 014 (India)
2010-07-15
This paper develops a new approach for solving the Economic Load Dispatch (ELD) using an integrated algorithm based on Evolutionary Programming (EP) and Simulated Annealing (SA) on large scale power system. Classical methods employed for solving Economic Load Dispatch are calculus-based. For generator units having quadratic fuel cost functions, the classical techniques ignore or flatten out the portions of the incremental fuel cost curves and so may be have difficulties in the determination of the global optimum solution for non-differentiable fuel cost functions. To overcome these problems, the intelligent techniques, namely, Evolutionary Programming and Simulated Annealing are employed. The above said optimization techniques are capable of determining the global or near global optimum dispatch solutions. The validity and effectiveness of the proposed integrated algorithm has been tested with 66-bus Indian utility system, IEEE 5-bus, 30-bus, 118-bus system. And the test results are compared with the results obtained from other methods. Numerical results show that the proposed integrated algorithm can provide accurate solutions within reasonable time for any type of fuel cost functions. (author)
Nakayama, Hiromasa
2006-01-01
We give an algorithm to compute the local $b$ function. In this algorithm, we use the Mora division algorithm in the ring of differential operators and an approximate division algorithm in the ring of differential operators with power series coefficient.
Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems
Van Benthem, Mark H.; Keenan, Michael R.
2008-11-11
A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.
Function-Based Algorithms for Biological Sequences
Mohanty, Pragyan Sheela P.
2015-01-01
Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…
Analytic Solutions of Special Functional Equations
Directory of Open Access Journals (Sweden)
Octav Olteanu
2013-07-01
Full Text Available We recall some of our earlier results on the construction of a mapping defined implicitly, without using the implicit function theorem. All these considerations work in the real case, for functions and operators. Then we consider the complex case, proving the analyticity of the function defined implicitly, under certain hypothesis. Some consequences are given. An approximating formula for the analytic form of the solution is also given. Finally, one illustrates the preceding results by an application to a concrete functional and operatorial equation. Some related examples are given.
a permutation encoding te algorithm solution of reso tation encoding
African Journals Online (AJOL)
eobe
Keywords: Genetic algorithm, resource constrained. 1. INTRODUCTION. 1. .... Nigerian Journal of Technology. Vol. 34, No. 1, January 2015. 128 ... 4. ENCODING OF CHROMOSOME. ENCODING OF CHROMOSOME .... International Multi conference of Engineers and ... method”, Naval Research Logistics, vol 48, issue 2,.
A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.
Hajri, S; Liouane, N; Hammadi, S; Borne, P
2000-01-01
Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.
Minimization of Linear Functionals Defined on| Solutions of Large-Scale Discrete Ill-Posed Problems
DEFF Research Database (Denmark)
Elden, Lars; Hansen, Per Christian; Rojas, Marielba
2003-01-01
The minimization of linear functionals de ned on the solutions of discrete ill-posed problems arises, e.g., in the computation of con dence intervals for these solutions. In 1990, Elden proposed an algorithm for this minimization problem based on a parametric-programming reformulation involving...... the solution of a sequence of trust-region problems, and using matrix factorizations. In this paper, we describe MLFIP, a large-scale version of this algorithm where a limited-memory trust-region solver is used on the subproblems. We illustrate the use of our algorithm in connection with an inverse heat...
A new algorithm for 3D reconstruction from support functions
DEFF Research Database (Denmark)
Gardner, Richard; Kiderlen, Markus
2009-01-01
We introduce a new algorithm for reconstructing an unknown shape from a finite number of noisy measurements of its support function. The algorithm, based on a least squares procedure, is very easy to program in standard software such as Matlab and allows, for the first time, good 3D reconstructio...
Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong
2017-11-20
A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.
An efficient algorithm for computation of solitary wave solutions to ...
Indian Academy of Sciences (India)
KAMRAN AYUB
2017-09-08
Sep 8, 2017 ... solutions has attracted lots of attention by scientists in the field of nonlinear science ... The procedure of this technique is quite simple, explicit, and can easily be extended ... divided into different sections. In the next section, we.
A new hybrid genetic algorithm for optimizing the single and multivariate objective functions
Energy Technology Data Exchange (ETDEWEB)
Tumuluru, Jaya Shankar [Idaho National Laboratory; McCulloch, Richard Chet James [Idaho National Laboratory
2015-07-01
In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the most improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.
An inductive algorithm for smooth approximation of functions
International Nuclear Information System (INIS)
Kupenova, T.N.
2011-01-01
An inductive algorithm is presented for smooth approximation of functions, based on the Tikhonov regularization method and applied to a specific kind of the Tikhonov parametric functional. The discrepancy principle is used for estimation of the regularization parameter. The principle of heuristic self-organization is applied for assessment of some parameters of the approximating function
Institute of Scientific and Technical Information of China (English)
WANG; Shunjin; ZHANG; Hua
2006-01-01
The problem of preserving fidelity in numerical computation of nonlinear ordinary differential equations is studied in terms of preserving local differential structure and approximating global integration structure of the dynamical system.The ordinary differential equations are lifted to the corresponding partial differential equations in the framework of algebraic dynamics,and a new algorithm-algebraic dynamics algorithm is proposed based on the exact analytical solutions of the ordinary differential equations by the algebraic dynamics method.In the new algorithm,the time evolution of the ordinary differential system is described locally by the time translation operator and globally by the time evolution operator.The exact analytical piece-like solution of the ordinary differential equations is expressd in terms of Taylor series with a local convergent radius,and its finite order truncation leads to the new numerical algorithm with a controllable precision better than Runge Kutta Algorithm and Symplectic Geometric Algorithm.
Integrating R and Java for Enhancing Interactivity of Algorithmic Data Analysis Software Solutions
Directory of Open Access Journals (Sweden)
Titus Felix FURTUNĂ
2016-06-01
Full Text Available Conceiving software solutions for statistical processing and algorithmic data analysis involves handling diverse data, fetched from various sources and in different formats, and presenting the results in a suggestive, tailorable manner. Our ongoing research aims to design programming technics for integrating R developing environment with Java programming language for interoperability at a source code level. The goal is to combine the intensive data processing capabilities of R programing language, along with the multitude of statistical function libraries, with the flexibility offered by Java programming language and platform, in terms of graphical user interface and mathematical function libraries. Both developing environments are multiplatform oriented, and can complement each other through interoperability. R is a comprehensive and concise programming language, benefiting from a continuously expanding and evolving set of packages for statistical analysis, developed by the open source community. While is a very efficient environment for statistical data processing, R platform lacks support for developing user friendly, interactive, graphical user interfaces (GUIs. Java on the other hand, is a high level object oriented programming language, which supports designing and developing performant and interactive frameworks for general purpose software solutions, through Java Foundation Classes, JavaFX and various graphical libraries. In this paper we treat both aspects of integration and interoperability that refer to integrating Java code into R applications, and bringing R processing sequences into Java driven software solutions. Our research has been conducted focusing on case studies concerning pattern recognition and cluster analysis.
Fast numerical solution of KKR-CPA equations: Testing new algorithms
Energy Technology Data Exchange (ETDEWEB)
Bruno, E.; Florio, G.M.; Ginatempo, B.; Giuliano, E.S. (Universita di Messina (Italy))
1994-04-01
Some numerical methods for the solution of KKR-CPA equations are discussed and tested. New, efficient, computational algorithms are proposed, allowing a remarkable reduction of computing time and a good reliability in evaluating spectral quantities. 16 refs., 7 figs.
When do evolutionary algorithms optimize separable functions in parallel?
DEFF Research Database (Denmark)
Doerr, Benjamin; Sudholt, Dirk; Witt, Carsten
2013-01-01
is that evolutionary algorithms make progress on all subfunctions in parallel, so that optimizing a separable function does not take not much longer than optimizing the hardest subfunction-subfunctions are optimized "in parallel." We show that this is only partially true, already for the simple (1+1) evolutionary...... algorithm ((1+1) EA). For separable functions composed of k Boolean functions indeed the optimization time is the maximum optimization time of these functions times a small O(log k) overhead. More generally, for sums of weighted subfunctions that each attain non-negative integer values less than r = o(log1...
Asymmetry in some common assignment algorithms: the dispersion factor solution
T de la Barra; B Pérez
1986-01-01
Many common assignment algorithms are based on Dial's original design to determine the paths that trip makers will follow from a given origin to destination centroids. The purpose of this paper is to show that the rules that have to be applied result in two unwanted properties. The first is that trips assigned from an origin centroid i to a destination j can be dramatically different to those resulting from centroid j to centroid i , even if the number of trips is the same and the network is ...
Mehdinejadiani, Behrouz
2017-08-01
This study represents the first attempt to estimate the solute transport parameters of the spatial fractional advection-dispersion equation using Bees Algorithm. The numerical studies as well as the experimental studies were performed to certify the integrity of Bees Algorithm. The experimental ones were conducted in a sandbox for homogeneous and heterogeneous soils. A detailed comparative study was carried out between the results obtained from Bees Algorithm and those from Genetic Algorithm and LSQNONLIN routines in FracFit toolbox. The results indicated that, in general, the Bees Algorithm much more accurately appraised the sFADE parameters in comparison with Genetic Algorithm and LSQNONLIN, especially in the heterogeneous soil and for α values near to 1 in the numerical study. Also, the results obtained from Bees Algorithm were more reliable than those from Genetic Algorithm. The Bees Algorithm showed the relative similar performances for all cases, while the Genetic Algorithm and the LSQNONLIN yielded different performances for various cases. The performance of LSQNONLIN strongly depends on the initial guess values so that, compared to the Genetic Algorithm, it can more accurately estimate the sFADE parameters by taking into consideration the suitable initial guess values. To sum up, the Bees Algorithm was found to be very simple, robust and accurate approach to estimate the transport parameters of the spatial fractional advection-dispersion equation. Copyright © 2017 Elsevier B.V. All rights reserved.
Mehdinejadiani, Behrouz
2017-08-01
This study represents the first attempt to estimate the solute transport parameters of the spatial fractional advection-dispersion equation using Bees Algorithm. The numerical studies as well as the experimental studies were performed to certify the integrity of Bees Algorithm. The experimental ones were conducted in a sandbox for homogeneous and heterogeneous soils. A detailed comparative study was carried out between the results obtained from Bees Algorithm and those from Genetic Algorithm and LSQNONLIN routines in FracFit toolbox. The results indicated that, in general, the Bees Algorithm much more accurately appraised the sFADE parameters in comparison with Genetic Algorithm and LSQNONLIN, especially in the heterogeneous soil and for α values near to 1 in the numerical study. Also, the results obtained from Bees Algorithm were more reliable than those from Genetic Algorithm. The Bees Algorithm showed the relative similar performances for all cases, while the Genetic Algorithm and the LSQNONLIN yielded different performances for various cases. The performance of LSQNONLIN strongly depends on the initial guess values so that, compared to the Genetic Algorithm, it can more accurately estimate the sFADE parameters by taking into consideration the suitable initial guess values. To sum up, the Bees Algorithm was found to be very simple, robust and accurate approach to estimate the transport parameters of the spatial fractional advection-dispersion equation.
Autonomous path planning solution for industrial robot manipulator using backpropagation algorithm
Directory of Open Access Journals (Sweden)
PeiJiang Yuan
2015-12-01
Full Text Available Here, we propose an autonomous path planning solution using backpropagation algorithm. The mechanism of movement used by humans in controlling their arms is analyzed and then applied to control a robot manipulator. Autonomous path planning solution is a numerical method. The model of industrial robot manipulator used in this article is a KUKA KR 210 R2700 EXTRA robot. In order to show the performance of the autonomous path planning solution, an experiment validation of path tracking is provided. Experiment validation consists of implementation of the autonomous path planning solution and the control of physical robot. The process of converging to target solution is provided. The mean absolute error of position for tool center point is also analyzed. Comparison between autonomous path planning solution and the numerical methods based on Newton–Raphson algorithm is provided to demonstrate the efficiency and accuracy of the autonomous path planning solution.
Domínguez, Luis F.
2012-06-25
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear programming subproblem and a mixed-integer nonlinear programming subproblem to provide a series of parametric upper and lower bounds. The primal subproblem is formulated by fixing the integer variables and solved through a series of multiparametric quadratic programming (mp-QP) problems based on quadratic approximations of the objective function, while the deterministic master subproblem is formulated so as to provide feasible integer solutions for the next primal subproblem. To reduce the computational effort when infeasibilities are encountered at the vertices of the critical regions (CRs) generated by the primal subproblem, a simplicial approximation approach is used to obtain CRs that are feasible at each of their vertices. The algorithm terminates when there does not exist an integer solution that is better than the one previously used by the primal problem. Through a series of examples, the proposed algorithm is compared with a multiparametric mixed-integer outer approximation (mp-MIOA) algorithm to demonstrate its computational advantages. © 2012 American Institute of Chemical Engineers (AIChE).
Algorithmic solution of arithmetic problems and operands-answer associations in long-term memory.
Thevenot, C; Barrouillet, P; Fayol, M
2001-05-01
Many developmental models of arithmetic problem solving assume that any algorithmic solution of a given problem results in an association of the two operands and the answer in memory (Logan & Klapp, 1991; Siegler, 1996). In this experiment, adults had to perform either an operation or a comparison on the same pairs of two-digit numbers and then a recognition task. It is shown that unlike comparisons, the algorithmic solution of operations impairs the recognition of operands in adults. Thus, the postulate of a necessary and automatic storage of operands-answer associations in memory when young children solve additions by algorithmic strategies needs to be qualified.
An Elementary Algorithm to Evaluate Trigonometric Functions to High Precision
Johansson, B. Tomas
2018-01-01
Evaluation of the cosine function is done via a simple Cordic-like algorithm, together with a package for handling arbitrary-precision arithmetic in the computer program Matlab. Approximations to the cosine function having hundreds of correct decimals are presented with a discussion around errors and implementation.
An Efficient Algorithm for Partitioning and Authenticating Problem-Solutions of eLeaming Contents
Dewan, Jahangir; Chowdhury, Morshed; Batten, Lynn
2013-01-01
Content authenticity and correctness is one of the important challenges in eLearning as there can be many solutions to one specific problem in cyber space. Therefore, the authors feel it is necessary to map problems to solutions using graph partition and weighted bipartite matching. This article proposes an efficient algorithm to partition…
Unsteady Solution of Non-Linear Differential Equations Using Walsh Function Series
Gnoffo, Peter A.
2015-01-01
Walsh functions form an orthonormal basis set consisting of square waves. The discontinuous nature of square waves make the system well suited for representing functions with discontinuities. The product of any two Walsh functions is another Walsh function - a feature that can radically change an algorithm for solving non-linear partial differential equations (PDEs). The solution algorithm of non-linear differential equations using Walsh function series is unique in that integrals and derivatives may be computed using simple matrix multiplication of series representations of functions. Solutions to PDEs are derived as functions of wave component amplitude. Three sample problems are presented to illustrate the Walsh function series approach to solving unsteady PDEs. These include an advection equation, a Burgers equation, and a Riemann problem. The sample problems demonstrate the use of the Walsh function solution algorithms, exploiting Fast Walsh Transforms in multi-dimensions (O(Nlog(N))). Details of a Fast Walsh Reciprocal, defined here for the first time, enable inversion of aWalsh Symmetric Matrix in O(Nlog(N)) operations. Walsh functions have been derived using a fractal recursion algorithm and these fractal patterns are observed in the progression of pairs of wave number amplitudes in the solutions. These patterns are most easily observed in a remapping defined as a fractal fingerprint (FFP). A prolongation of existing solutions to the next highest order exploits these patterns. The algorithms presented here are considered a work in progress that provide new alternatives and new insights into the solution of non-linear PDEs.
Energy Technology Data Exchange (ETDEWEB)
Thirukkanesh, S. [Eastern University, Department of Mathematics, Chenkalady (Sri Lanka); Ragel, F.C. [Eastern University, Department of Physics, Chenkalady (Sri Lanka); Sharma, Ranjan; Das, Shyam [P.D. Women' s College, Department of Physics, Jalpaiguri (India)
2018-01-15
We present an algorithm to generalize a plethora of well-known solutions to Einstein field equations describing spherically symmetric relativistic fluid spheres by relaxing the pressure isotropy condition on the system. By suitably fixing the model parameters in our formulation, we generate closed-form solutions which may be treated as an anisotropic generalization of a large class of solutions describing isotropic fluid spheres. From the resultant solutions, a particular solution is taken up to show its physical acceptability. Making use of the current estimate of mass and radius of a known pulsar, the effects of anisotropic stress on the gross physical behaviour of a relativistic compact star is also highlighted. (orig.)
Cheap contouring of costly functions: the Pilot Approximation Trajectory algorithm
International Nuclear Information System (INIS)
Huttunen, Janne M J; Stark, Philip B
2012-01-01
The Pilot Approximation Trajectory (PAT) contour algorithm can find the contour of a function accurately when it is not practical to evaluate the function on a grid dense enough to use a standard contour algorithm, for instance, when evaluating the function involves conducting a physical experiment or a computationally intensive simulation. PAT relies on an inexpensive pilot approximation to the function, such as interpolating from a sparse grid of inexact values, or solving a partial differential equation (PDE) numerically using a coarse discretization. For each level of interest, the location and ‘trajectory’ of an approximate contour of this pilot function are used to decide where to evaluate the original function to find points on its contour. Those points are joined by line segments to form the PAT approximation of the contour of the original function. Approximating a contour numerically amounts to estimating a lower level set of the function, the set of points on which the function does not exceed the contour level. The area of the symmetric difference between the true lower level set and the estimated lower level set measures the accuracy of the contour. PAT measures its own accuracy by finding an upper confidence bound for this area. In examples, PAT can estimate a contour more accurately than standard algorithms, using far fewer function evaluations than standard algorithms require. We illustrate PAT by constructing a confidence set for viscosity and thermal conductivity of a flowing gas from simulated noisy temperature measurements, a problem in which each evaluation of the function to be contoured requires solving a different set of coupled nonlinear PDEs. (paper)
Directory of Open Access Journals (Sweden)
Anulekha Saha
2017-12-01
Full Text Available A relatively new technique to solve the optimal power flow (OPF problem inspired by the evaporation (vaporization of small quantity water particles from dense surfaces is presented in this paper. IEEE 30 bus and IEEE 118 bus test systems are assessed for various objectives to determine water evaporation algorithm’s (WEA efficiency in handling the OPF problem after satisfying constraints. Comparative study with other established techniques demonstrate competitiveness of WEA in treating varied objectives. It achieved superior results for all the objectives considered. The algorithm is found to minimize its objective values by great margins even in case of large test system. Statistical analysis of all the cases using Wilcoxon’s signed rank test resulted in p-values much lower than the required value of 0.05, thereby establishing the robustness of the applied technique. Best performance of the algorithm are obtained for voltage deviation minimization and voltage stability index minimization objectives in case of IEEE 30 and IEEE 118 bus test systems respectively.
International Nuclear Information System (INIS)
Duo, J. I.; Azmy, Y. Y.
2007-01-01
A new method, the Singular Characteristics Tracking algorithm, is developed to account for potential non-smoothness across the singular characteristics in the exact solution of the discrete ordinates approximation of the transport equation. Numerical results show improved rate of convergence of the solution to the discrete ordinates equations in two spatial dimensions with isotropic scattering using the proposed methodology. Unlike the standard Weighted Diamond Difference methods, the new algorithm achieves local convergence in the case of discontinuous angular flux along the singular characteristics. The method also significantly reduces the error for problems where the angular flux presents discontinuous spatial derivatives across these lines. For purposes of verifying the results, the Method of Manufactured Solutions is used to generate analytical reference solutions that permit estimating the local error in the numerical solution. (authors)
Solution of single linear tridiagonal systems and vectorization of the ICCG algorithm on the Cray 1
International Nuclear Information System (INIS)
Kershaw, D.S.
1981-01-01
The numerical algorithms used to solve the physics equation in codes which model laser fusion are examined, it is found that a large number of subroutines require the solution of tridiagonal linear systems of equations. One dimensional radiation transport, thermal and suprathermal electron transport, ion thermal conduction, charged particle and neutron transport, all require the solution of tridiagonal systems of equations. The standard algorithm that has been used in the past on CDC 7600's will not vectorize and so cannot take advantage of the large speed increases possible on the Cray-1 through vectorization. There is however, an alternate algorithm for solving tridiagonal systems, called cyclic reduction, which allows for vectorization, and which is optimal for the Cray-1. Software based on this algorithm is now being used in LASNEX to solve tridiagonal linear systems in the subroutines mentioned above. The new algorithm runs as much as five times faster than the standard algorithm on the Cray-1. The ICCG method is being used to solve the diffusion equation with a nine-point coupling scheme on the CDC 7600. In going from the CDC 7600 to the Cray-1, a large part of the algorithm consists of solving tridiagonal linear systems on each L line of the Lagrangian mesh in a manner which is not vectorizable. An alternate ICCG algorithm for the Cray-1 was developed which utilizes a block form of the cyclic reduction algorithm. This new algorithm allows full vectorization and runs as much as five times faster than the old algorithm on the Cray-1. It is now being used in Cray LASNEX to solve the two-dimensional diffusion equation in all the physics subroutines mentioned above
Dynamic Sensor Management Algorithm Based on Improved Efficacy Function
Directory of Open Access Journals (Sweden)
TANG Shujuan
2016-01-01
Full Text Available A dynamic sensor management algorithm based on improved efficacy function is proposed to solve the multi-target and multi-sensory management problem. The tracking task precision requirements (TPR, target priority and sensor use cost were considered to establish the efficacy function by weighted sum the normalized value of the three factors. The dynamic sensor management algorithm was accomplished through control the diversities of the desired covariance matrix (DCM and the filtering covariance matrix (FCM. The DCM was preassigned in terms of TPR and the FCM was obtained by the centralized sequential Kalman filtering algorithm. The simulation results prove that the proposed method could meet the requirements of desired tracking precision and adjust sensor selection according to target priority and cost of sensor source usage. This makes sensor management scheme more reasonable and effective.
Barrett, Steven R. H.; Britter, Rex E.
Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105-8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean
Algebraic Factoring algorithm to recognise read-once functions.
Naidu, S.R.
2003-01-01
A fast polynomial-time algorithm was recently proposed to determine whether a logic function expressed as a unate DNF (disjunctive normal form) can be expressed as a read-once formula where each variable appears no more than once. The paper uses a combinatorial characterisation of read-once formulas
Protopopescu, V.; D'Helon, C.; Barhen, J.
2003-06-01
A constant-time solution of the continuous global optimization problem (GOP) is obtained by using an ensemble algorithm. We show that under certain assumptions, the solution can be guaranteed by mapping the GOP onto a discrete unsorted search problem, whereupon Brüschweiler's ensemble search algorithm is applied. For adequate sensitivities of the measurement technique, the query complexity of the ensemble search algorithm depends linearly on the size of the function's domain. Advantages and limitations of an eventual NMR implementation are discussed.
An efficient parallel algorithm for the solution of a tridiagonal linear system of equations
Stone, H. S.
1971-01-01
Tridiagonal linear systems of equations are solved on conventional serial machines in a time proportional to N, where N is the number of equations. The conventional algorithms do not lend themselves directly to parallel computations on computers of the ILLIAC IV class, in the sense that they appear to be inherently serial. An efficient parallel algorithm is presented in which computation time grows as log sub 2 N. The algorithm is based on recursive doubling solutions of linear recurrence relations, and can be used to solve recurrence relations of all orders.
Metropolis-Hastings Algorithms in Function Space for Bayesian Inverse Problems
Ernst, Oliver
2015-01-07
We consider Markov Chain Monte Carlo methods adapted to a Hilbert space setting. Such algorithms occur in Bayesian inverse problems where the solution is a probability measure on a function space according to which one would like to integrate or sample. We focus on Metropolis-Hastings algorithms and, in particular, we introduce and analyze a generalization of the existing pCN-proposal. This new proposal allows to exploit the geometry or anisotropy of the target measure which in turn might improve the statistical efficiency of the corresponding MCMC method. Numerical experiments for a real-world problem confirm the improvement.
Metropolis-Hastings Algorithms in Function Space for Bayesian Inverse Problems
Ernst, Oliver
2015-01-01
We consider Markov Chain Monte Carlo methods adapted to a Hilbert space setting. Such algorithms occur in Bayesian inverse problems where the solution is a probability measure on a function space according to which one would like to integrate or sample. We focus on Metropolis-Hastings algorithms and, in particular, we introduce and analyze a generalization of the existing pCN-proposal. This new proposal allows to exploit the geometry or anisotropy of the target measure which in turn might improve the statistical efficiency of the corresponding MCMC method. Numerical experiments for a real-world problem confirm the improvement.
Approximated Function Based Spectral Gradient Algorithm for Sparse Signal Recovery
Directory of Open Access Journals (Sweden)
Weifeng Wang
2014-02-01
Full Text Available Numerical algorithms for the l0-norm regularized non-smooth non-convex minimization problems have recently became a topic of great interest within signal processing, compressive sensing, statistics, and machine learning. Nevertheless, the l0-norm makes the problem combinatorial and generally computationally intractable. In this paper, we construct a new surrogate function to approximate l0-norm regularization, and subsequently make the discrete optimization problem continuous and smooth. Then we use the well-known spectral gradient algorithm to solve the resulting smooth optimization problem. Experiments are provided which illustrate this method is very promising.
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2012-01-01
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear
Comparison of Nonequilibrium Solution Algorithms Applied to Chemically Stiff Hypersonic Flows
Palmer, Grant; Venkatapathy, Ethiraj
1995-01-01
Three solution algorithms, explicit under-relaxation, point implicit, and lower-upper symmetric Gauss-Seidel, are used to compute nonequilibrium flow around the Apollo 4 return capsule at the 62-km altitude point in its descent trajectory. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness.The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15 and 30, the lower-upper symmetric Gauss-Seidel method produces an eight order of magnitude drop in the energy residual in one-third to one-half the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 30 and above. At Mach 40 the performance of the lower-upper symmetric Gauss-Seidel algorithm deteriorates to the point that it is out performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.
Directory of Open Access Journals (Sweden)
A. L. Lapikov
2014-01-01
Full Text Available The article is aimed at creating techniques to study multi-sectional manipulators with parallel structure. To solve this task the analysis in the field concerned was carried out to reveal both advantages and drawbacks of such executive mechanisms and main problems to be encountered in the course of research. The work shows that it is inefficient to create complete mathematical models of multisectional manipulators, which in the context of solving a direct kinematic problem are to derive a functional dependence of location and orientation of the end effector on all the generalized coordinates of the mechanism. The structure of multisectional manipulators was considered, where the sections are platform manipulators of parallel kinematics with six degrees of freedom. The paper offers an algorithm to define location and orientation of the end effector of the manipulator by means of iterative solution of analytical equation of the moving platform plane for each section. The equation for the unknown plane is derived using three points, which are attachment points of the moving platform joints. To define the values of joint coordinates a system of nine non-linear equations is completed. It is necessary to mention that for completion of the equation system are used the equations with the same type of non-linearity. The physical sense of all nine equations of the system is Euclidean distance between the points of the manipulator. The result of algorithm execution is a matrix of homogenous transformation for each section. The correlations describing transformations between adjoining sections of the manipulator are given. An example of the mechanism consisting of three sections is examined. The comparison of theoretical calculations with results obtained on a 3D-prototype is made. The next step of the work is to conduct research activities both in the field of dynamics of platform parallel kinematics manipulators with six degrees of freedom and in the
Mokeddem, Diab; Khellaf, Abdelhafid
2009-01-01
Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples. PMID:19543537
Jacobian elliptic function expansion solutions of nonlinear stochastic equations
International Nuclear Information System (INIS)
Wei Caimin; Xia Zunquan; Tian Naishuo
2005-01-01
Jacobian elliptic function expansion method is extended and applied to construct the exact solutions of the nonlinear Wick-type stochastic partial differential equations (SPDEs) and some new exact solutions are obtained via this method and Hermite transformation
Efficient quantum algorithm for computing n-time correlation functions.
Pedernales, J S; Di Candia, R; Egusquiza, I L; Casanova, J; Solano, E
2014-07-11
We propose a method for computing n-time correlation functions of arbitrary spinorial, fermionic, and bosonic operators, consisting of an efficient quantum algorithm that encodes these correlations in an initially added ancillary qubit for probe and control tasks. For spinorial and fermionic systems, the reconstruction of arbitrary n-time correlation functions requires the measurement of two ancilla observables, while for bosonic variables time derivatives of the same observables are needed. Finally, we provide examples applicable to different quantum platforms in the frame of the linear response theory.
Directory of Open Access Journals (Sweden)
Ari Muzakir
2017-05-01
Full Text Available Ease of deployment of digital image through the internet has positive and negative sides, especially for owners of the original digital image. The positive side of the ease of rapid deployment is the owner of that image deploys digital image files to various sites in the world address. While the downside is that if there is no copyright that serves as protector of the image it will be very easily recognized ownership by other parties. Watermarking is one solution to protect the copyright and know the results of the digital image. With Digital Image Watermarking, copyright resulting digital image will be protected through the insertion of additional information such as owner information and the authenticity of the digital image. The least significant bit (LSB is one of the algorithm is simple and easy to understand. The results of the simulations carried out using android smartphone shows that the LSB watermarking technique is not able to be seen by naked human eye, meaning there is no significant difference in the image of the original files with images that have been inserted watermarking. The resulting image has dimensions of 640x480 with a bit depth of 32 bits. In addition, to determine the function of the ability of the device (smartphone in processing the image using this application used black box testing.
An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem
Directory of Open Access Journals (Sweden)
Guangmin Wang
2017-12-01
Full Text Available Continuous network design problem (CNDP is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC by describing UE as a non-linear complementarity problem (NCP. To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.
International Nuclear Information System (INIS)
Mesgarani, H; Parmour, P; Aghazadeh, N
2010-01-01
In this paper, we apply Aitken extrapolation and epsilon algorithm as acceleration technique for the solution of a weakly singular nonlinear Volterra integral equation of the second kind. In this paper, based on Tao and Yong (2006 J. Math. Anal. Appl. 324 225-37.) the integral equation is solved by Navot's quadrature formula. Also, Tao and Yong (2006) for the first time applied Richardson extrapolation to accelerating convergence for the weakly singular nonlinear Volterra integral equations of the second kind. To our knowledge, this paper may be the first attempt to apply Aitken extrapolation and epsilon algorithm for the weakly singular nonlinear Volterra integral equations of the second kind.
Alfonso, Lester; Zamora, Jose; Cruz, Pedro
2015-04-01
The stochastic approach to coagulation considers the coalescence process going in a system of a finite number of particles enclosed in a finite volume. Within this approach, the full description of the system can be obtained from the solution of the multivariate master equation, which models the evolution of the probability distribution of the state vector for the number of particles of a given mass. Unfortunately, due to its complexity, only limited results were obtained for certain type of kernels and monodisperse initial conditions. In this work, a novel numerical algorithm for the solution of the multivariate master equation for stochastic coalescence that works for any type of kernels and initial conditions is introduced. The performance of the method was checked by comparing the numerically calculated particle mass spectrum with analytical solutions obtained for the constant and sum kernels, with an excellent correspondence between the analytical and numerical solutions. In order to increase the speedup of the algorithm, software parallelization techniques with OpenMP standard were used, along with an implementation in order to take advantage of new accelerator technologies. Simulations results show an important speedup of the parallelized algorithms. This study was funded by a grant from Consejo Nacional de Ciencia y Tecnologia de Mexico SEP-CONACYT CB-131879. The authors also thanks LUFAC® Computacion SA de CV for CPU time and all the support provided.
Dakin Solution Alters Macrophage Viability and Function
2014-07-18
fungi, viruses, and parasites [1]. Dakin’s solution (DS) is buffered sodium hypochlorite, which has a long history of use as a topical antiseptic in...eagle medium (DMEM) supplemented with 10% fetal bovine serum, 10 U/mL penicillin, 10 mg/mL streptomycin, and maintained at 37C in 5% CO2. DS (buffered
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Pavlov, V. M.
2017-07-01
The problem of calculating complete synthetic seismograms from a point dipole with an arbitrary seismic moment tensor in a plane parallel medium composed of homogeneous elastic isotropic layers is considered. It is established that the solutions of the system of ordinary differential equations for the motion-stress vector have a reciprocity property, which allows obtaining a compact formula for the derivative of the motion vector with respect to the source depth. The reciprocity theorem for Green's functions with respect to the interchange of the source and receiver is obtained for a medium with cylindrical boundary. The differentiation of Green's functions with respect to the coordinates of the source leads to the same calculation formulas as the algorithm developed in the previous work (Pavlov, 2013). A new algorithm appears when the derivatives with respect to the horizontal coordinates of the source is replaced by the derivatives with respect to the horizontal coordinates of the receiver (with the minus sign). This algorithm is more transparent, compact, and economic than the previous one. It requires calculating the wavenumbers associated with Bessel function's roots of order 0 and order 1, whereas the previous algorithm additionally requires the second order roots.
A Swarm Optimization Algorithm for Multimodal Functions and Its Application in Multicircle Detection
Directory of Open Access Journals (Sweden)
Erik Cuevas
2013-01-01
Full Text Available In engineering problems due to physical and cost constraints, the best results, obtained by a global optimization algorithm, cannot be realized always. Under such conditions, if multiple solutions (local and global are known, the implementation can be quickly switched to another solution without much interrupting the design process. This paper presents a new swarm multimodal optimization algorithm named as the collective animal behavior (CAB. Animal groups, such as schools of fish, flocks of birds, swarms of locusts, and herds of wildebeest, exhibit a variety of behaviors including swarming about a food source, milling around a central location, or migrating over large distances in aligned groups. These collective behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, searcher agents emulate a group of animals which interact with each other based on simple biological laws that are modeled as evolutionary operators. Numerical experiments are conducted to compare the proposed method with the state-of-the-art methods on benchmark functions. The proposed algorithm has been also applied to the engineering problem of multi-circle detection, achieving satisfactory results.
Special function solutions of the free particle Dirac equation
International Nuclear Information System (INIS)
Strange, P
2012-01-01
The Dirac equation is one of the fundamental equations in physics. Here we present and discuss two novel solutions of the free particle Dirac equation. These solutions have an exact analytical form in terms of Airy or Mathieu functions and exhibit unexpected properties including an enhanced Doppler effect, accelerating wavefronts and solutions with a degree of localization. (paper)
Investigation of ALEGRA shock hydrocode algorithms using an exact free surface jet flow solution.
Energy Technology Data Exchange (ETDEWEB)
Hanks, Bradley Wright.; Robinson, Allen C
2014-01-01
Computational testing of the arbitrary Lagrangian-Eulerian shock physics code, ALEGRA, is presented using an exact solution that is very similar to a shaped charge jet flow. The solution is a steady, isentropic, subsonic free surface flow with significant compression and release and is provided as a steady state initial condition. There should be no shocks and no entropy production throughout the problem. The purpose of this test problem is to present a detailed and challenging computation in order to provide evidence for algorithmic strengths and weaknesses in ALEGRA which should be examined further. The results of this work are intended to be used to guide future algorithmic improvements in the spirit of test-driven development processes.
Improvement of arm solutions via step width self-tuning algorithm
International Nuclear Information System (INIS)
Sasaki, Shinobu
1993-09-01
This paper is concerned with the significant numerical problems encountered in solving the manipulator inverse kinematics. That is, essential difficulties occurred in linearized calculations such as dependence on initial guess or narrow search region are improved with great success by means of a step width self-tuning algorithm. In a practical optimization model based on the reduction of dimensionality and linearized approximation, it is shown that the desired arm solutions are found out at a faster rate over a wider application range. Also, the capability of finding solutions via a traditional Newton method is enhanced to a large extent by combined application of the proposed idea and simplex method. (author)
Mining the multigroup-discrete ordinates algorithm for high quality solutions
International Nuclear Information System (INIS)
Ganapol, B.D.; Kornreich, D.E.
2005-01-01
A novel approach to the numerical solution of the neutron transport equation via the discrete ordinates (SN) method is presented. The new technique is referred to as 'mining' low order (SN) numerical solutions to obtain high order accuracy. The new numerical method, called the Multigroup Converged SN (MGCSN) algorithm, is a combination of several sequence accelerators: Romberg and Wynn-epsilon. The extreme accuracy obtained by the method is demonstrated through self consistency and comparison to the independent semi-analytical benchmark BLUE. (authors)
Solution Algorithm for a New Bi-Level Discrete Network Design Problem
Directory of Open Access Journals (Sweden)
Qun Chen
2013-12-01
Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.
Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm
Directory of Open Access Journals (Sweden)
I. Hameem Shanavas
2014-01-01
Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.
An algorithm for computing the hull of the solution set of interval linear equations
Czech Academy of Sciences Publication Activity Database
Rohn, Jiří
2011-01-01
Roč. 435, č. 2 (2011), s. 193-201 ISSN 0024-3795 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval linear equations * solution set * interval hull * algorithm * absolute value inequality Subject RIV: BA - General Mathematics Impact factor: 0.974, year: 2011
Qi, Xin; Ju, Guohao; Xu, Shuyan
2018-04-10
The phase diversity (PD) technique needs optimization algorithms to minimize the error metric and find the global minimum. Particle swarm optimization (PSO) is very suitable for PD due to its simple structure, fast convergence, and global searching ability. However, the traditional PSO algorithm for PD still suffers from the stagnation problem (premature convergence), which can result in a wrong solution. In this paper, the stagnation problem of the traditional PSO algorithm for PD is illustrated first. Then, an explicit strategy is proposed to solve this problem, based on an in-depth understanding of the inherent optimization mechanism of the PSO algorithm. Specifically, a criterion is proposed to detect premature convergence; then a redistributing mechanism is proposed to prevent premature convergence. To improve the efficiency of this redistributing mechanism, randomized Halton sequences are further introduced to ensure the uniform distribution and randomness of the redistributed particles in the search space. Simulation results show that this strategy can effectively solve the stagnation problem of the PSO algorithm for PD, especially for large-scale and high-dimension wavefront sensing and noisy conditions. This work is further verified by an experiment. This work can improve the robustness and performance of PD wavefront sensing.
Ecosystem Function: Cyanobacteria Solutions, A Missed Opportunity?
Stream and wetland riparian functions integrate the relationships between species, their habitats and fostering ecosystem resilience, which is critical to resilience – i.e., ensuring long-term sustainability. These relationships are dependent on the drivers of ecological functio...
Directory of Open Access Journals (Sweden)
Rabha W. Ibrahim
2018-01-01
Full Text Available The maximum min utility function (MMUF problem is an important representative of a large class of cloud computing systems (CCS. Having numerous applications in practice, especially in economy and industry. This paper introduces an effective solution-based search (SBS algorithm for solving the problem MMUF. First, we suggest a new formula of the utility function in term of the capacity of the cloud. We formulate the capacity in CCS, by using a fractional diffeo-integral equation. This equation usually describes the flow of CCS. The new formula of the utility function is modified recent active utility functions. The suggested technique first creates a high-quality initial solution by eliminating the less promising components, and then develops the quality of the achieved solution by the summation search solution (SSS. This method is considered by the Mittag-Leffler sum as hash functions to determine the position of the agent. Experimental results commonly utilized in the literature demonstrate that the proposed algorithm competes approvingly with the state-of-the-art algorithms both in terms of solution quality and computational efficiency.
International Nuclear Information System (INIS)
Gougam, L.A.; Taibi, H.; Chikhi, A.; Mekideche-Chafa, F.
2009-01-01
The problem of determining the analytical description for a set of data arises in numerous sciences and applications and can be referred to as data modeling or system identification. Neural networks are a convenient means of representation because they are known to be universal approximates that can learn data. The desired task is usually obtained by a learning procedure which consists in adjusting the s ynaptic weights . For this purpose, many learning algorithms have been proposed to update these weights. The convergence for these learning algorithms is a crucial criterion for neural networks to be useful in different applications. The aim of the present contribution is to use a training algorithm for feed forward wavelet networks used for function approximation. The training is based on the minimization of the least-square cost function. The minimization is performed by iterative second order gradient-based methods. We make use of the Levenberg-Marquardt algorithm to train the architecture of the chosen network and, then, the training procedure starts with a simple gradient method which is followed by a BFGS (Broyden, Fletcher, Glodfarb et Shanno) algorithm. The performances of the two algorithms are then compared. Our method is then applied to determine the energy of the ground state associated to a sextic potential. In fact, the Schrodinger equation does not always admit an exact solution and one has, generally, to solve it numerically. To this end, the sextic potential is, firstly, approximated with the above outlined wavelet network and, secondly, implemented into a numerical scheme. Our results are in good agreement with the ones found in the literature.
A sequential quadratic programming algorithm using an incomplete solution of the subproblem
Energy Technology Data Exchange (ETDEWEB)
Murray, W. [Stanford Univ., CA (United States). Systems Optimization Lab.; Prieto, F.J. [Universidad `Carlos III` de Madrid (Spain). Dept. de Estadistica y Econometria
1993-05-01
We analyze sequential quadratic programming (SQP) methods to solve nonlinear constrained optimization problems that are more flexible in their definition than standard SQP methods. The type of flexibility introduced is motivated by the necessity to deviate from the standard approach when solving large problems. Specifically we no longer require a minimizer of the QP subproblem to be determined or particular Lagrange multiplier estimates to be used. Our main focus is on an SQP algorithm that uses a particular augmented Lagrangian merit function. New results are derived for this algorithm under weaker conditions than previously assumed; in particular, it is not assumed that the iterates lie on a compact set.
Neuroprosthetics and Solutions for Restoring Sensorimotor Functions
2009-12-01
prosthetic feet. 15. SUBJECT TERMS neural interface, neural prosthesis , biocompatibility, virtual reality, amputee, sensory feedback 16. SECURITY...limbs. By providing a communication link between the prosthesis and the user’s nervous system, our goal is to integrate the prosthetic limb as a...neuroprosthetic control. This new class of prosthetic devices will literally look, feel , and function like natural limbs, but their internal
A solution algorithm for fluid-particle flows across all flow regimes
Kong, Bo; Fox, Rodney O.
2017-09-01
Many fluid-particle flows occurring in nature and in technological applications exhibit large variations in the local particle volume fraction. For example, in circulating fluidized beds there are regions where the particles are close-packed as well as very dilute regions where particle-particle collisions are rare. Thus, in order to simulate such fluid-particle systems, it is necessary to design a flow solver that can accurately treat all flow regimes occurring simultaneously in the same flow domain. In this work, a solution algorithm is proposed for this purpose. The algorithm is based on splitting the free-transport flux solver dynamically and locally in the flow. In close-packed to moderately dense regions, a hydrodynamic solver is employed, while in dilute to very dilute regions a kinetic-based finite-volume solver is used in conjunction with quadrature-based moment methods. To illustrate the accuracy and robustness of the proposed solution algorithm, it is implemented in OpenFOAM for particle velocity moments up to second order, and applied to simulate gravity-driven, gas-particle flows exhibiting cluster-induced turbulence. By varying the average particle volume fraction in the flow domain, it is demonstrated that the flow solver can handle seamlessly all flow regimes present in fluid-particle flows.
Fikri, Fariz Fahmi; Nuraini, Nuning
2018-03-01
The differential equation is one of the branches in mathematics which is closely related to human life problems. Some problems that occur in our life can be modeled into differential equations as well as systems of differential equations such as the Lotka-Volterra model and SIR model. Therefore, solving a problem of differential equations is very important. Some differential equations are difficult to solve, so numerical methods are needed to solve that problems. Some numerical methods for solving differential equations that have been widely used are Euler Method, Heun Method, Runge-Kutta and others. However, some of these methods still have some restrictions that cause the method cannot be used to solve more complex problems such as an evaluation interval that we cannot change freely. New methods are needed to improve that problems. One of the method that can be used is the artificial bees colony algorithm. This algorithm is one of metaheuristic algorithm method, which can come out from local search space and do exploration in solution search space so that will get better solution than other method.
Directory of Open Access Journals (Sweden)
Juan Carlos Figueroa García
2011-12-01
The presented approach uses an iterative algorithm which finds stable solutions to problems with fuzzy parameter sinboth sides of an FLP problem. The algorithm is based on the soft constraints method proposed by Zimmermann combined with an iterative procedure which gets a single optimal solution.
A new algorithm for DNS of turbulent polymer solutions using the FENE-P model
Vaithianathan, T.; Collins, Lance; Robert, Ashish; Brasseur, James
2004-11-01
Direct numerical simulations (DNS) of polymer solutions based on the finite extensible nonlinear elastic model with the Peterlin closure (FENE-P) solve for a conformation tensor with properties that must be maintained by the numerical algorithm. In particular, the eigenvalues of the tensor are all positive (to maintain positive definiteness) and the sum is bounded by the maximum extension length. Loss of either of these properties will give rise to unphysical instabilities. In earlier work, Vaithianathan & Collins (2003) devised an algorithm based on an eigendecomposition that allows you to update the eigenvalues of the conformation tensor directly, making it easier to maintain the necessary conditions for a stable calculation. However, simple fixes (such as ceilings and floors) yield results that violate overall conservation. The present finite-difference algorithm is inherently designed to satisfy all of the bounds on the eigenvalues, and thus restores overall conservation. New results suggest that the earlier algorithm may have exaggerated the energy exchange at high wavenumbers. In particular, feedback of the polymer elastic energy to the isotropic turbulence is now greatly reduced.
International Nuclear Information System (INIS)
Wang Qi; Chen Yong
2007-01-01
With the aid of symbolic computation, some algorithms are presented for the rational expansion methods, which lead to closed-form solutions of nonlinear partial differential equations (PDEs). The new algorithms are given to find exact rational formal polynomial solutions of PDEs in terms of Jacobi elliptic functions, solutions of the Riccati equation and solutions of the generalized Riccati equation. They can be implemented in symbolic computation system Maple. As applications of the methods, we choose some nonlinear PDEs to illustrate the methods. As a result, we not only can successfully obtain the solutions found by most existing Jacobi elliptic function methods and Tanh-methods, but also find other new and more general solutions at the same time
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
International Nuclear Information System (INIS)
Svensson, Urban
2001-04-01
A particle tracking algorithm, PARTRACK, that simulates transport and dispersion in a sparsely fractured rock is described. The main novel feature of the algorithm is the introduction of multiple particle states. It is demonstrated that the introduction of this feature allows for the simultaneous simulation of Taylor dispersion, sorption and matrix diffusion. A number of test cases are used to verify and demonstrate the features of PARTRACK. It is shown that PARTRACK can simulate the following processes, believed to be important for the problem addressed: the split up of a tracer cloud at a fracture intersection, channeling in a fracture plane, Taylor dispersion and matrix diffusion and sorption. From the results of the test cases, it is concluded that PARTRACK is an adequate framework for simulation of transport and dispersion of a solute in a sparsely fractured rock
Functional constipation in children: challenges and solutions
Directory of Open Access Journals (Sweden)
Levy EI
2017-03-01
Full Text Available Elvira Ingrid Levy,* Roel Lemmens,* Yvan Vandenplas, Thierry Devreker Kidz Health Castle, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium *These authors contributed equally to this work Abstract: This review intends to update what is known about and what is still a challenge in functional constipation (FC in children regarding epidemiology, pathophysiology, diagnosis, and management. Although FC is a common childhood problem, its global burden remains unknown as data from parts of the world are missing. Another problem is that there is a large variation in prevalence due to differences in study methods and defining age groups. The pathophysiology of FC remains unclear to date but is probably multifactorial. Withholding behavior is likely to be the most important factor in toddlers and young children. Genetics may also play a role since many patients have positive family history, but mutations in genes associated with FC have not been found. Over the past years, different diagnostic criteria for FC in infants and children have been proposed. This year, Rome IV criteria have been released. Compared to Rome III, it eliminates two diagnostic criteria in children under the age of 4 who still wear diapers. Physical examination and taking a thorough medical history are recommended, but other investigations such as abdominal radiography, transabdominal recto-ultrasonography, colonic transit time, rectal biopsies, and colon manometry are not routinely recommended. Regarding treatment, guidelines recommend disimpaction and maintenance therapy with polyethylene glycol (PEG with or without electrolytes. But experience shows that acceptability, adherence, and tolerance to PEG are still a challenge. Counseling of parents and children about causes of FC is often neglected. Recent studies suggest that behavior therapy added to laxative therapy improves the relief of symptoms. Further homogeneous studies, better-defined outcomes, and studies
Bu, Sunyoung; Huang, Jingfang; Boyer, Treavor H.; Miller, Cass T.
2010-07-01
The focus of this work is on the modeling of an ion exchange process that occurs in drinking water treatment applications. The model formulation consists of a two-scale model in which a set of microscale diffusion equations representing ion exchange resin particles that vary in size and age are coupled through a boundary condition with a macroscopic ordinary differential equation (ODE), which represents the concentration of a species in a well-mixed reactor. We introduce a new age-averaged model (AAM) that averages all ion exchange particle ages for a given size particle to avoid the expensive Monte-Carlo simulation associated with previous modeling applications. We discuss two different numerical schemes to approximate both the original Monte-Carlo algorithm and the new AAM for this two-scale problem. The first scheme is based on the finite element formulation in space coupled with an existing backward difference formula-based ODE solver in time. The second scheme uses an integral equation based Krylov deferred correction (KDC) method and a fast elliptic solver (FES) for the resulting elliptic equations. Numerical results are presented to validate the new AAM algorithm, which is also shown to be more computationally efficient than the original Monte-Carlo algorithm. We also demonstrate that the higher order KDC scheme is more efficient than the traditional finite element solution approach and this advantage becomes increasingly important as the desired accuracy of the solution increases. We also discuss issues of smoothness, which affect the efficiency of the KDC-FES approach, and outline additional algorithmic changes that would further improve the efficiency of these developing methods for a wide range of applications.
Vectorization of a penalty function algorithm for well scheduling
Absar, I.
1984-01-01
In petroleum engineering, the oil production profiles of a reservoir can be simulated by using a finite gridded model. This profile is affected by the number and choice of wells which in turn is a result of various production limits and constraints including, for example, the economic minimum well spacing, the number of drilling rigs available and the time required to drill and complete a well. After a well is available it may be shut in because of excessive water or gas productions. In order to optimize the field performance a penalty function algorithm was developed for scheduling wells. For an example with some 343 wells and 15 different constraints, the scheduling routine vectorized for the CYBER 205 averaged 560 times faster performance than the scalar version.
Algorithms: economical computation of functions of real matrices
International Nuclear Information System (INIS)
Weiss, Z.
1991-01-01
An algorithm is presented which economizes on the calculation of F(a), where A is a real matrix and F(x) a real valued function of x, using spectral analysis. Assuming the availability of the software for the calculation of the complete set of eigenvalues and eigen vectors of A, it is shown that the complex matrix arithmetics involved in subsequent operations leading from A to F(A) can be reduced to the size comparable with the analogous problem in real matrix arithmetics. Saving in CPU time and storage has been achieved by utilizing explicitly the property that complex eigenvalues of a real matrix appear in pairs of complex conjugated numbers. (author)
The functional variable method for finding exact solutions of some ...
Indian Academy of Sciences (India)
Abstract. In this paper, we implemented the functional variable method and the modified. Riemann–Liouville derivative for the exact solitary wave solutions and periodic wave solutions of the time-fractional Klein–Gordon equation, and the time-fractional Hirota–Satsuma coupled. KdV system. This method is extremely simple ...
Gunzburger, M. D.; Nicolaides, R. A.
1986-01-01
Substructuring methods are in common use in mechanics problems where typically the associated linear systems of algebraic equations are positive definite. Here these methods are extended to problems which lead to nonpositive definite, nonsymmetric matrices. The extension is based on an algorithm which carries out the block Gauss elimination procedure without the need for interchanges even when a pivot matrix is singular. Examples are provided wherein the method is used in connection with finite element solutions of the stationary Stokes equations and the Helmholtz equation, and dual methods for second-order elliptic equations.
Chemical solution deposition of functional oxide thin films
Schneller, Theodor; Kosec, Marija
2014-01-01
Chemical Solution Deposition (CSD) is a highly-flexible and inexpensive technique for the fabrication of functional oxide thin films. Featuring nearly 400 illustrations, this text covers all aspects of the technique.
Directory of Open Access Journals (Sweden)
Eman Ali Hussain
2015-01-01
Full Text Available Absract In this project A new method for solving Stochastic Differential Equations SDEs deriving by Wiener process numerically will be construct and implement using Accelerated Genetic Algorithm AGA. An SDE is a differential equation in which one or more of the terms and hence the solutions itself is a stochastic process. Solving stochastic differential equations requires going away from the recognizable deterministic setting of ordinary and partial differential equations into a world where the evolution of a quantity has an inherent random component and where the expected behavior of this quantity can be described in terms of probability distributions. We applied our method on the Ito formula which is equivalent to the SDE to find approximation solution of the SDEs. Numerical experiments illustrate the behavior of the proposed method.
Doxley, Charles A.
2016-01-01
In the current world of applications that use reconfigurable technology implemented on field programmable gate arrays (FPGAs), there is a need for flexible architectures that can grow as the systems evolve. A project has limited resources and a fixed set of requirements that development efforts are tasked to meet. Designers must develop robust solutions that practically meet the current customer demands and also have the ability to grow for future performance. This paper describes the development of a high speed serial data streaming algorithm that allows for transmission of multiple data channels over a single serial link. The technique has the ability to change to meet new applications developed for future design considerations. This approach uses the Xilinx Serial RapidIO LOGICORE Solution to implement a flexible infrastructure to meet the current project requirements with the ability to adapt future system designs.
Introduction of Parallel GPGPU Acceleration Algorithms for the Solution of Radiative Transfer
Godoy, William F.; Liu, Xu
2011-01-01
General-purpose computing on graphics processing units (GPGPU) is a recent technique that allows the parallel graphics processing unit (GPU) to accelerate calculations performed sequentially by the central processing unit (CPU). To introduce GPGPU to radiative transfer, the Gauss-Seidel solution of the well-known expressions for 1-D and 3-D homogeneous, isotropic media is selected as a test case. Different algorithms are introduced to balance memory and GPU-CPU communication, critical aspects of GPGPU. Results show that speed-ups of one to two orders of magnitude are obtained when compared to sequential solutions. The underlying value of GPGPU is its potential extension in radiative solvers (e.g., Monte Carlo, discrete ordinates) at a minimal learning curve.
Design of attitude solution algorithm for tail-sitter VTOL UAV
Directory of Open Access Journals (Sweden)
Donghui LIU
2016-02-01
Full Text Available The tail-sitter Vertical Takeoff and Landing (VTOL Unmanned Aerial Vehicle(UAV, flying in a fixed-wing model, overcomes many shortcomings of traditional fixed-wing UAVs, and inherits the advantage of high overall efficiency, which means it has great development potential and very broad application prospects. The attitude of tail-sitter VTOL UAV shows a wide change range in its takeoff and landing stages, and when the attitude sensor changes more than 90 degrees in pitch direction, the Euler angles converted by the Quaternions will have singular points, which means gimbal deadlock appears. From the solution algorithm, this paper provides a method of changing the order of rotation to avoid the appearance of singular points. The results show that this method can be well applied to the attitude solution of the VTOL UAV.
Adachi, Kohei
2013-01-01
Rubin and Thayer ("Psychometrika," 47:69-76, 1982) proposed the EM algorithm for exploratory and confirmatory maximum likelihood factor analysis. In this paper, we prove the following fact: the EM algorithm always gives a proper solution with positive unique variances and factor correlations with absolute values that do not exceed one,…
A branch and bound algorithm for the global optimization of Hessian Lipschitz continuous functions
Fowkes, Jaroslav M.
2012-06-21
We present a branch and bound algorithm for the global optimization of a twice differentiable nonconvex objective function with a Lipschitz continuous Hessian over a compact, convex set. The algorithm is based on applying cubic regularisation techniques to the objective function within an overlapping branch and bound algorithm for convex constrained global optimization. Unlike other branch and bound algorithms, lower bounds are obtained via nonconvex underestimators of the function. For a numerical example, we apply the proposed branch and bound algorithm to radial basis function approximations. © 2012 Springer Science+Business Media, LLC.
A branch and bound algorithm for the global optimization of Hessian Lipschitz continuous functions
Fowkes, Jaroslav M.; Gould, Nicholas I. M.; Farmer, Chris L.
2012-01-01
We present a branch and bound algorithm for the global optimization of a twice differentiable nonconvex objective function with a Lipschitz continuous Hessian over a compact, convex set. The algorithm is based on applying cubic regularisation
Soliton solution for nonlinear partial differential equations by cosine-function method
International Nuclear Information System (INIS)
Ali, A.H.A.; Soliman, A.A.; Raslan, K.R.
2007-01-01
In this Letter, we established a traveling wave solution by using Cosine-function algorithm for nonlinear partial differential equations. The method is used to obtain the exact solutions for five different types of nonlinear partial differential equations such as, general equal width wave equation (GEWE), general regularized long wave equation (GRLW), general Korteweg-de Vries equation (GKdV), general improved Korteweg-de Vries equation (GIKdV), and Coupled equal width wave equations (CEWE), which are the important soliton equations
Energy Technology Data Exchange (ETDEWEB)
Reddy, N.M.; Reddy, K.R. [G. Narayanamma Inst. of Technology and Science, Hyderabad (India). Dept. of Electrical Engineering; Ramana, N.V. [JNTU College of Engineering, Jagityala (India). Dept. of Electrical Engineering
2008-07-01
Thermal power plants consist of several generating units with different generating capacities, fuel cost per MWH generated, minimum up/down times, and start-up or shut-down costs. The Unit Commitment (UC) problem in power systems involves determining the start-up and shut-down schedules of thermal generating units to meet forecasted load over a future short term for a period of one to seven days. This paper presented a new approach for the most complex UC problem using agglomerative and divisive hierarchical clustering. Euclidean costs, which are a measure of differences in fuel cost and start-up costs of any two units, were first calculated. Then, depending on the value of Euclidean costs, similar type of units were placed in a cluster. The proposed methodology has 2 individual algorithms. An agglomerative cluster algorithm is used while the load is increasing, and a divisive cluster algorithm is used when the load is decreasing. A search was conducted for an optimal solution for a minimal number of clusters and cluster data points. A standard ten-unit thermal unit power system was used to test and evaluate the performance of the method for a period of 24 hours. The new approach proved to be quite effective and satisfactory. 15 refs., 9 tabs., 5 figs.
Management Of Large Scale Osmotic Dehydration Solution Using The Pearsons Square Algorithm
Directory of Open Access Journals (Sweden)
Oladejo Duduyemi
2015-01-01
Full Text Available ABSTRACT Osmotic dehydration is a widely researched and advantageous pre-treatment process in food preservation but has not enjoyed industrial acceptance because if its highly concentrated and voluminous effluent. The Pearsons square algorithm was employed to give a focussed attack to the problem by developing a user-friendly template for reconstituting effluents for recycling purposes using Java script programme. Outflow from a pilot scale plant was reactivated and introduced into a scheme of operation for continuous OD of fruits and vegetables. Screened and re-concentrated effluent were subjected to statistical analysis in comparison to initial concentrations solution at confidence limit of p0.05. The template proven to be an adequate representation of the Pearsons square algorithm it is sufficiently good in reconstituting used osmotic solutions for repetitive usage. This protocol if adopted in the industry is not only environmentally friendly but also promises significant economic improvement of OD process. Application Recycling of non-reacting media and as a template for automation in continuous OD processing.
Solute-solvent cavity and bridge functions. I. Varying size of the solute
International Nuclear Information System (INIS)
Vyalov, I.; Chuev, G.; Georgi, N.
2014-01-01
In this work we present the results of the extensive molecular simulations of solute-solvent cavity and bridge functions. The mixtures of Lennard-Jones solvent with Lennard-Jones solute at infinite dilution are considered for different solute-solvent size ratios—up to 4:1. The Percus-Yevick and hypernetted chain closures deviate substantially from simulation results in the investigated temperature and density ranges. We also find that the behavior of the indirect and cavity correlation functions is non-monotonous within the hard-core region, but the latter can be successfully approximated by mean-field theory if the solute-solvent interaction energy is divided into repulsive and attractive contribution, according to Weeks-Chandler-Andersen theory. Furthermore, in spite of the non-monotonous behavior of logarithm of the cavity function and the indirect correlation function, their difference, i.e., the bridge function remains constant within the hard-core region. Such behavior of the bridge and indirect correlation functions at small distances and for small values of indirect correlation function is well known from the Duh-Haymet plots, where the non-unique relationship results in loops of the bridge function vs. indirect correlation function graphs. We show that the same pathological behavior appears also when distance is small and indirect correlation function is large. We further show that the unique functional behavior of the bridge function can be established when bridge is represented as a function of the renormalized, repulsive indirect correlation function
Thermodynamically Consistent Algorithms for the Solution of Phase-Field Models
Vignal, Philippe
2016-02-11
Phase-field models are emerging as a promising strategy to simulate interfacial phenomena. Rather than tracking interfaces explicitly as done in sharp interface descriptions, these models use a diffuse order parameter to monitor interfaces implicitly. This implicit description, as well as solid physical and mathematical footings, allow phase-field models to overcome problems found by predecessors. Nonetheless, the method has significant drawbacks. The phase-field framework relies on the solution of high-order, nonlinear partial differential equations. Solving these equations entails a considerable computational cost, so finding efficient strategies to handle them is important. Also, standard discretization strategies can many times lead to incorrect solutions. This happens because, for numerical solutions to phase-field equations to be valid, physical conditions such as mass conservation and free energy monotonicity need to be guaranteed. In this work, we focus on the development of thermodynamically consistent algorithms for time integration of phase-field models. The first part of this thesis focuses on an energy-stable numerical strategy developed for the phase-field crystal equation. This model was put forward to model microstructure evolution. The algorithm developed conserves, guarantees energy stability and is second order accurate in time. The second part of the thesis presents two numerical schemes that generalize literature regarding energy-stable methods for conserved and non-conserved phase-field models. The time discretization strategies can conserve mass if needed, are energy-stable, and second order accurate in time. We also develop an adaptive time-stepping strategy, which can be applied to any second-order accurate scheme. This time-adaptive strategy relies on a backward approximation to give an accurate error estimator. The spatial discretization, in both parts, relies on a mixed finite element formulation and isogeometric analysis. The codes are
Directory of Open Access Journals (Sweden)
Ambarish Panda
2016-09-01
Full Text Available A new evolutionary hybrid algorithm (HA has been proposed in this work for environmental optimal power flow (EOPF problem. The EOPF problem has been formulated in a nonlinear constrained multi objective optimization framework. Considering the intermittency of available wind power a cost model of the wind and thermal generation system is developed. Suitably formed objective function considering the operational cost, cost of emission, real power loss and cost of installation of FACTS devices for maintaining a stable voltage in the system has been optimized with HA and compared with particle swarm optimization algorithm (PSOA to prove its effectiveness. All the simulations are carried out in MATLAB/SIMULINK environment taking IEEE30 bus as the test system.
Utilizing Minkowski functionals for image analysis: a marching square algorithm
International Nuclear Information System (INIS)
Mantz, Hubert; Jacobs, Karin; Mecke, Klaus
2008-01-01
Comparing noisy experimental image data with statistical models requires a quantitative analysis of grey-scale images beyond mean values and two-point correlations. A real-space image analysis technique is introduced for digitized grey-scale images, based on Minkowski functionals of thresholded patterns. A novel feature of this marching square algorithm is the use of weighted side lengths for pixels, so that boundary lengths are captured accurately. As examples to illustrate the technique we study surface topologies emerging during the dewetting process of thin films and analyse spinodal decomposition as well as turbulent patterns in chemical reaction–diffusion systems. The grey-scale value corresponds to the height of the film or to the concentration of chemicals, respectively. Comparison with analytic calculations in stochastic geometry models reveals a remarkable agreement of the examples with a Gaussian random field. Thus, a statistical test for non-Gaussian features in experimental data becomes possible with this image analysis technique—even for small image sizes. Implementations of the software used for the analysis are offered for download
A Functional Programming Approach to AI Search Algorithms
Panovics, Janos
2012-01-01
The theory and practice of search algorithms related to state-space represented problems form the major part of the introductory course of Artificial Intelligence at most of the universities and colleges offering a degree in the area of computer science. Students usually meet these algorithms only in some imperative or object-oriented language…
Energy Technology Data Exchange (ETDEWEB)
Kamph, Jerome Henri; Robinson, Darren; Wetter, Michael
2009-09-01
There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimise the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
The performance of the backpropagation algorithm with varying slope of the activation function
International Nuclear Information System (INIS)
Bai Yanping; Zhang Haixia; Hao Yilong
2009-01-01
Some adaptations are proposed to the basic BP algorithm in order to provide an efficient method to non-linear data learning and prediction. In this paper, an adopted BP algorithm with varying slope of activation function and different learning rates is put forward. The results of experiment indicated that this algorithm can get very good performance of training. We also test the prediction performance of our adopted BP algorithm on 16 instances. We compared the test results to the ones of the BP algorithm with gradient descent momentum and an adaptive learning rate. The results indicate this adopted BP algorithm gives best performance (100%) for test example, which conclude this adopted BP algorithm produces a smoothed reconstruction that learns better to new prediction function values than the BP algorithm improved with momentum.
A finite state projection algorithm for the stationary solution of the chemical master equation
Gupta, Ankit; Mikelson, Jan; Khammash, Mustafa
2017-10-01
The chemical master equation (CME) is frequently used in systems biology to quantify the effects of stochastic fluctuations that arise due to biomolecular species with low copy numbers. The CME is a system of ordinary differential equations that describes the evolution of probability density for each population vector in the state-space of the stochastic reaction dynamics. For many examples of interest, this state-space is infinite, making it difficult to obtain exact solutions of the CME. To deal with this problem, the Finite State Projection (FSP) algorithm was developed by Munsky and Khammash [J. Chem. Phys. 124(4), 044104 (2006)], to provide approximate solutions to the CME by truncating the state-space. The FSP works well for finite time-periods but it cannot be used for estimating the stationary solutions of CMEs, which are often of interest in systems biology. The aim of this paper is to develop a version of FSP which we refer to as the stationary FSP (sFSP) that allows one to obtain accurate approximations of the stationary solutions of a CME by solving a finite linear-algebraic system that yields the stationary distribution of a continuous-time Markov chain over the truncated state-space. We derive bounds for the approximation error incurred by sFSP and we establish that under certain stability conditions, these errors can be made arbitrarily small by appropriately expanding the truncated state-space. We provide several examples to illustrate our sFSP method and demonstrate its efficiency in estimating the stationary distributions. In particular, we show that using a quantized tensor-train implementation of our sFSP method, problems admitting more than 100 × 106 states can be efficiently solved.
A finite state projection algorithm for the stationary solution of the chemical master equation.
Gupta, Ankit; Mikelson, Jan; Khammash, Mustafa
2017-10-21
The chemical master equation (CME) is frequently used in systems biology to quantify the effects of stochastic fluctuations that arise due to biomolecular species with low copy numbers. The CME is a system of ordinary differential equations that describes the evolution of probability density for each population vector in the state-space of the stochastic reaction dynamics. For many examples of interest, this state-space is infinite, making it difficult to obtain exact solutions of the CME. To deal with this problem, the Finite State Projection (FSP) algorithm was developed by Munsky and Khammash [J. Chem. Phys. 124(4), 044104 (2006)], to provide approximate solutions to the CME by truncating the state-space. The FSP works well for finite time-periods but it cannot be used for estimating the stationary solutions of CMEs, which are often of interest in systems biology. The aim of this paper is to develop a version of FSP which we refer to as the stationary FSP (sFSP) that allows one to obtain accurate approximations of the stationary solutions of a CME by solving a finite linear-algebraic system that yields the stationary distribution of a continuous-time Markov chain over the truncated state-space. We derive bounds for the approximation error incurred by sFSP and we establish that under certain stability conditions, these errors can be made arbitrarily small by appropriately expanding the truncated state-space. We provide several examples to illustrate our sFSP method and demonstrate its efficiency in estimating the stationary distributions. In particular, we show that using a quantized tensor-train implementation of our sFSP method, problems admitting more than 100 × 10 6 states can be efficiently solved.
Gravity discharge vessel revisited: An explicit Lambert W function solution
Digilov, Rafael M.
2017-07-01
Based on the generalized Poiseuille equation modified by a kinetic energy correction, an explicit solution for the time evolution of a liquid column draining under gravity through an exit capillary tube is derived in terms of the Lambert W function. In contrast to the conventional exponential behavior, as implied by the Poiseuille law, a new analytical solution gives a full account for the volumetric flow rate of a fluid through a capillary of any length and improves the precision of viscosity determination. The theoretical consideration may be of interest to students as an example of how implicit equations in the field of physics can be solved analytically using the Lambert function.
Directory of Open Access Journals (Sweden)
V. P. Gribkova
2014-01-01
Full Text Available The paper offers a new method for approximate solution of one type of singular integral equations for elasticity theory which have been studied by other authors. The approximate solution is found in the form of asymptotic polynomial function of a low degree (first approximation based on the Chebyshev second order polynomial. Other authors have obtained a solution (only in separate points using a method of mechanical quadrature and though they used also the Chebyshev polynomial of the second order they applied another system of junctures which were used for the creation of the required formulas.The suggested method allows not only to find an approximate solution for the whole interval in the form of polynomial, but it also makes it possible to obtain a remainder term in the form of infinite expansion where coefficients are linear functional of the given integral equation and basis functions are the Chebyshev polynomial of the second order. Such presentation of the remainder term of the first approximation permits to find a summand of the infinite series, which will serve as a start for fulfilling the given solution accuracy. This number is a degree of the asymptotic polynomial (second approximation, which will give the approximation to the exact solution with the given accuracy. The examined polynomial functions tend asymptotically to the polynomial of the best uniform approximation in the space C, created for the given operator.The paper demonstrates a convergence of the approximate solution to the exact one and provides an error estimation. The proposed algorithm for obtaining of the approximate solution and error estimation is easily realized with the help of computing technique and does not require considerable preliminary preparation during programming.
Villalba-Morales, Jesús Daniel; Laier, José Elias
2014-01-01
Structural damage detection has become an important research topic in certain segments of the engineering community. These methodologies occasionally formulate an optimization problem by defining an objective function based on dynamic parameters, with metaheuristics used to find the solution. In this study, damage localization and quantification is performed by an Adaptive Differential Evolution algorithm, which solves the associated optimization problem. Furthermore, this paper looks at the ...
Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm
Dutta, S.; Patra, D.; Shankar, H.; Alok Verma, P.
2014-11-01
minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim's algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it's minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several
International Nuclear Information System (INIS)
Miller, I.; Roman, K.
1979-12-01
In order to perform studies of the influence of regional groundwater flow systems on the long-term performance of potential high-level nuclear waste repositories, it was determined that an adequate computer model would have to consider the full three-dimensional flow system. Golder Associates' SOLTR code, while three-dimensional, has an overly simple algorithm for simulating the passage of radionuclides from one aquifier to another above or below it. Part 1 of this report describes the algorithm developed to provide SOLTR with an improved capability for simulating interaquifer transport
Green function iterative solution of ground state wave function for Yukawa potential
International Nuclear Information System (INIS)
Zhang Zhao
2003-01-01
The newly developed single trajectory quadrature method is applied to solve central potentials. First, based on the series expansion method an exact analytic solution of the ground state for Hulthen potential and an approximate solution for Yukawa potential are obtained respectively. Second, the newly developed iterative method based on Green function defined by quadratures along the single trajectory is applied to solve Yukawa potential using the Coulomb solution and Hulthen solution as the trial functions respectively. The results show that a more proper choice of the trial function will give a better convergence. To further improve the convergence the iterative method is combined with the variational method to solve the ground state wave function for Yukawa potential, using variational solutions of the Coulomb and Hulthen potentials as the trial functions. The results give much better convergence. Finally, the obtained critical screen coefficient is applied to discuss the dissociate temperature of J/ψ in high temperature QGP
Mild Solutions of Neutral Stochastic Partial Functional Differential Equations
Directory of Open Access Journals (Sweden)
T. E. Govindan
2011-01-01
Full Text Available This paper studies the existence and uniqueness of a mild solution for a neutral stochastic partial functional differential equation using a local Lipschitz condition. When the neutral term is zero and even in the deterministic special case, the result obtained here appears to be new. An example is included to illustrate the theory.
On nonnegative solutions of second order linear functional differential equations
Czech Academy of Sciences Publication Activity Database
Lomtatidze, Alexander; Vodstrčil, Petr
2004-01-01
Roč. 32, č. 1 (2004), s. 59-88 ISSN 1512-0015 Institutional research plan: CEZ:AV0Z1019905 Keywords : second order linear functional differential equations * nonnegative solution * two-point boundary value problem Subject RIV: BA - General Mathematics
featsel: A framework for benchmarking of feature selection algorithms and cost functions
Marcelo S. Reis; Gustavo Estrela; Carlos Eduardo Ferreira; Junior Barrera
2017-01-01
In this paper, we introduce featsel, a framework for benchmarking of feature selection algorithms and cost functions. This framework allows the user to deal with the search space as a Boolean lattice and has its core coded in C++ for computational efficiency purposes. Moreover, featsel includes Perl scripts to add new algorithms and/or cost functions, generate random instances, plot graphs and organize results into tables. Besides, this framework already comes with dozens of algorithms and co...
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Swarm algorithms with chaotic jumps for optimization of multimodal functions
Krohling, Renato A.; Mendel, Eduardo; Campos, Mauro
2011-11-01
In this article, the use of some well-known versions of particle swarm optimization (PSO) namely the canonical PSO, the bare bones PSO (BBPSO) and the fully informed particle swarm (FIPS) is investigated on multimodal optimization problems. A hybrid approach which consists of swarm algorithms combined with a jump strategy in order to escape from local optima is developed and tested. The jump strategy is based on the chaotic logistic map. The hybrid algorithm was tested for all three versions of PSO and simulation results show that the addition of the jump strategy improves the performance of swarm algorithms for most of the investigated optimization problems. Comparison with the off-the-shelf PSO with local topology (l best model) has also been performed and indicates the superior performance of the standard PSO with chaotic jump over the standard both using local topology (l best model).
An Evaluation of the Sniffer Global Optimization Algorithm Using Standard Test Functions
Butler, Roger A. R.; Slaminka, Edward E.
1992-03-01
The performance of Sniffer—a new global optimization algorithm—is compared with that of Simulated Annealing. Using the number of function evaluations as a measure of efficiency, the new algorithm is shown to be significantly better at finding the global minimum of seven standard test functions. Several of the test functions used have many local minima and very steep walls surrounding the global minimum. Such functions are intended to thwart global minimization algorithms.
Implementation of digital image encryption algorithm using logistic function and DNA encoding
Suryadi, MT; Satria, Yudi; Fauzi, Muhammad
2018-03-01
Cryptography is a method to secure information that might be in form of digital image. Based on past research, in order to increase security level of chaos based encryption algorithm and DNA based encryption algorithm, encryption algorithm using logistic function and DNA encoding was proposed. Digital image encryption algorithm using logistic function and DNA encoding use DNA encoding to scramble the pixel values into DNA base and scramble it in DNA addition, DNA complement, and XOR operation. The logistic function in this algorithm used as random number generator needed in DNA complement and XOR operation. The result of the test show that the PSNR values of cipher images are 7.98-7.99 bits, the entropy values are close to 8, the histogram of cipher images are uniformly distributed and the correlation coefficient of cipher images are near 0. Thus, the cipher image can be decrypted perfectly and the encryption algorithm has good resistance to entropy attack and statistical attack.
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
On Approximate Solutions of Functional Equations in Vector Lattices
Directory of Open Access Journals (Sweden)
Bogdan Batko
2014-01-01
Full Text Available We provide a method of approximation of approximate solutions of functional equations in the class of functions acting into a Riesz space (algebra. The main aim of the paper is to provide a general theorem that can act as a tool applicable to a possibly wide class of functional equations. The idea is based on the use of the Spectral Representation Theory for Riesz spaces. The main result will be applied to prove the stability of an alternative Cauchy functional equation F(x+y+F(x+F(y≠0⇒F(x+y=F(x+F(y in Riesz spaces, the Cauchy equation with squares F(x+y2=(F(x+F(y2 in f-algebras, and the quadratic functional equation F(x+y+F(x-y=2F(x+2F(y in Riesz spaces.
Discrete Wigner Function Derivation of the Aaronson–Gottesman Tableau Algorithm
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Lucas Kocia
2017-07-01
Full Text Available The Gottesman–Knill theorem established that stabilizer states and Clifford operations can be efficiently simulated classically. For qudits with odd dimension three and greater, stabilizer states and Clifford operations have been found to correspond to positive discrete Wigner functions and dynamics. We present a discrete Wigner function-based simulation algorithm for odd-d qudits that has the same time and space complexity as the Aaronson–Gottesman algorithm for qubits. We show that the efficiency of both algorithms is due to harmonic evolution in the symplectic structure of discrete phase space. The differences between the Wigner function algorithm for odd-d and the Aaronson–Gottesman algorithm for qubits are likely due only to the fact that the Weyl–Heisenberg group is not in S U ( d for d = 2 and that qubits exhibit state-independent contextuality. This may provide a guide for extending the discrete Wigner function approach to qubits.
Palmer, Grant; Venkatapathy, Ethiraj
1993-01-01
Three solution algorithms, explicit underrelaxation, point implicit, and lower upper symmetric Gauss-Seidel (LUSGS), are used to compute nonequilibrium flow around the Apollo 4 return capsule at 62 km altitude. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness. The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15, 23, and 30, the LUSGS method produces an eight order of magnitude drop in the L2 norm of the energy residual in 1/3 to 1/2 the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 23 and above. At Mach 40 the performance of the LUSGS algorithm deteriorates to the point it is out-performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.
An algorithm for determining the K-best solutions of the one-dimensional Knapsack problem
Directory of Open Access Journals (Sweden)
Horacio Hideki Yanasse
2000-06-01
Full Text Available In this work we present an enumerative scheme for determining the K-best solutions (K > 1 of the one dimensional knapsack problem. If n is the total number of different items and b is the knapsack's capacity, the computational complexity of the proposed scheme is bounded by O(Knb with memory requirements bounded by O(nb. The algorithm was implemented in a workstation and computational tests for varying values of the parameters were performed.Neste trabalho apresenta-se um esquema enumerativo para se determinar as K-melhores (K > 1 soluções para o problema da mochila unidimensional. Se n é o número total de itens diferentes e b é a capacidade da mochila, a complexidade computacional do esquema proposto é limitado por O(Knb. O algoritmo foi implementado em uma estação de trabalho e testes computacionais foram realizados variando-se diferentes parâmetros do problema.
A genetic algorithm solution for combinatorial problems - the nuclear core reload example
Energy Technology Data Exchange (ETDEWEB)
Schirru, R.; Silva, F.C. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia; Pereira, C.M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil); Chapot, J.L.C. [FURNAS, Rio de Janeiro, RJ (Brazil)
1997-12-01
This paper presents a solution to Traveling Salesman Problem based upon genetic algorithms (GA), using the classic crossover, but avoiding the feasibility problem in offspring individuals, allowing the natural evolution of the GA without introduction of heuristics in the genetic crossover operator. The genetic model presented, that we call the List Model (LM) is based on the encoding and decoding genotype in the way to always generate a phenotype that has a valid structure, over which will be applied the fitness, represented by the total distance. The main purpose of this work was to develop the basis for a new genetic model to be used in the reload of nuclear core of a PWR. In a generic way, this problem can be interpreted as a a search of the optimal combination of N different fuel elements in N nuclear core `holes`, where each combination or load pattern, determines the neutron flux shape and its associate peak factor. The goal is to find out the load pattern that minimizes the peak factor and consequently maximize the useful life of the nuclear fuel. The GA with the List Model was applied to the Angra-1 PWR reload problem and the results are remarkably better than the ones used in the last fuel cycle. (author). 12 refs., 3 figs., 2 tabs.
Fast sweeping algorithm for accurate solution of the TTI eikonal equation using factorization
bin Waheed, Umair
2017-06-10
Traveltime computation is essential for many seismic data processing applications and velocity analysis tools. High-resolution seismic imaging requires eikonal solvers to account for anisotropy whenever it significantly affects the seismic wave kinematics. Moreover, computation of auxiliary quantities, such as amplitude and take-off angle, rely on highly accurate traveltime solutions. However, the finite-difference based eikonal solution for a point-source initial condition has an upwind source-singularity at the source position, since the wavefront curvature is large near the source point. Therefore, all finite-difference solvers, even the high-order ones, show inaccuracies since the errors due to source-singularity spread from the source point to the whole computational domain. We address the source-singularity problem for tilted transversely isotropic (TTI) eikonal solvers using factorization. We solve a sequence of factored tilted elliptically anisotropic (TEA) eikonal equations iteratively, each time by updating the right hand side function. At each iteration, we factor the unknown TEA traveltime into two factors. One of the factors is specified analytically, such that the other factor is smooth in the source neighborhood. Therefore, through the iterative procedure we obtain accurate solution to the TTI eikonal equation. Numerical tests show significant improvement in accuracy due to factorization. The idea can be easily extended to compute accurate traveltimes for models with lower anisotropic symmetries, such as orthorhombic, monoclinic or even triclinic media.
Spectral bisection algorithm for solving Schrodinger equation using upper and lower solutions
Directory of Open Access Journals (Sweden)
Qutaibeh Deeb Katatbeh
2007-10-01
Full Text Available This paper establishes a new criteria for obtaining a sequence of upper and lower bounds for the ground state eigenvalue of Schr"odinger equation $ -Deltapsi(r+V(rpsi(r=Epsi(r$ in $N$ spatial dimensions. Based on this proposed criteria, we prove a new comparison theorem in quantum mechanics for the ground state eigenfunctions of Schrodinger equation. We determine also lower and upper solutions for the exact wave function of the ground state eigenfunctions using the computed upper and lower bounds for the eigenvalues obtained by variational methods. In other words, by using this criteria, we prove that the substitution of the lower(upper bound of the eigenvalue in Schrodinger equation leads to an upper(lower solution. Finally, two proposed iteration approaches lead to an exact convergent sequence of solutions. The first one uses Raielgh-Ritz theorem. Meanwhile, the second approach uses a new numerical spectral bisection technique. We apply our results for a wide class of potentials in quantum mechanics such as sum of power-law potentials in quantum mechanics.
Partially Adaptive STAP Algorithm Approaches to functional MRI
Huang, Lejian; Thompson, Elizabeth A.; Schmithorst, Vincent; Holland, Scott K.; Talavage, Thomas M.
2008-01-01
In this work, the architectures of three partially adaptive STAP algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in construction of brain activation maps in fMRI. Computer simulations incorporating actual MRI noise and human data analysis indicate that element space partially adaptive STAP can attain close to the performance of fully adaptive STAP while significantly decreasing processing tim...
A partitioned conjugate gradient algorithm for lattice Green functions
International Nuclear Information System (INIS)
Bowler, K.C.; Kenway, R.D.; Pawley, G.S.; Wallace, D.J.
1984-01-01
Partitioning reduces by one the dimensionality of the lattice on which a propagator need be calculated using, for example, the conjugate gradient algorithm. Thus the quark propagator in lattice QCD may be determined by a computation on a single spatial hyperplane. For free fermions on a 16 3 x N lattice 2N-bit accuracy in the propagator is required to avoid rounding errors. (orig.)
Directory of Open Access Journals (Sweden)
V. Jegathesan
2017-11-01
Full Text Available This paper presents an efficient and reliable Genetic Algorithm based solution for Selective Harmonic Elimination (SHE switching pattern. This method eliminates considerable amount of lower order line voltage harmonics in Pulse Width Modulation (PWM inverter. Determination of pulse pattern for the elimination of some lower order harmonics of a PWM inverter necessitates solving a system of nonlinear transcendental equations. Genetic Algorithm is used to solve nonlinear transcendental equations for PWM-SHE. Many methods are available to eliminate the higher order harmonics and it can be easily removed. But the greatest challenge is to eliminate the lower order harmonics and this is successfully achieved using Genetic Algorithm without using Dual transformer. Simulations using MATLABTM and Powersim with experimental results are carried out to validate the solution. The experimental results show that the harmonics up to 13th were totally eliminated.
Studies of parallel algorithms for the solution of a Fokker-Planck equation
International Nuclear Information System (INIS)
Deck, D.; Samba, G.
1995-11-01
The study of laser-created plasmas often requires the use of a kinetic model rather than a hydrodynamic one. This model change occurs, for example, in the hot spot formation in an ICF experiment or during the relaxation of colliding plasmas. When the gradients scalelengths or the size of a given system are not small compared to the characteristic mean-free-path, we have to deal with non-equilibrium situations, which can be described by the distribution functions of every species in the system. We present here a numerical method in plane or spherical 1-D geometry, for the solution of a Fokker-Planck equation that describes the evolution of stich functions in the phase space. The size and the time scale of kinetic simulations require the use of Massively Parallel Computers (MPP). We have adopted a message-passing strategy using Parallel Virtual Machine (PVM)
Optimization algorithms and applications
Arora, Rajesh Kumar
2015-01-01
Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and constrained optimization problems. It discusses the conjugate gradient method, Broyden-Fletcher-Goldfarb-Shanno algorithm, Powell method, penalty function, augmented Lagrange multiplier method, sequential quadratic programming, method of feasible direc
Directory of Open Access Journals (Sweden)
Daniel J. Garcia
2015-07-01
Full Text Available The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water, and maximization of energy output per liter of water consumed (energy efficiency of water. A mixed integer, multiobjective nonlinear fractional programming (MINLFP model is formulated. A mixed integer linear programing (MILP-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline. A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers.
Hydrogen sulfide metabolism regulates endothelial solute barrier function
Directory of Open Access Journals (Sweden)
Shuai Yuan
2016-10-01
Full Text Available Hydrogen sulfide (H2S is an important gaseous signaling molecule in the cardiovascular system. In addition to free H2S, H2S can be oxidized to polysulfide which can be biologically active. Since the impact of H2S on endothelial solute barrier function is not known, we sought to determine whether H2S and its various metabolites affect endothelial permeability. In vitro permeability was evaluated using albumin flux and transendothelial electrical resistance. Different H2S donors were used to examine the effects of exogenous H2S. To evaluate the role of endogenous H2S, mouse aortic endothelial cells (MAECs were isolated from wild type mice and mice lacking cystathionine γ-lyase (CSE, a predominant source of H2S in endothelial cells. In vivo permeability was evaluated using the Miles assay. We observed that polysulfide donors induced rapid albumin flux across endothelium. Comparatively, free sulfide donors increased permeability only with higher concentrations and at later time points. Increased solute permeability was associated with disruption of endothelial junction proteins claudin 5 and VE-cadherin, along with enhanced actin stress fiber formation. Importantly, sulfide donors that increase permeability elicited a preferential increase in polysulfide levels within endothelium. Similarly, CSE deficient MAECs showed enhanced solute barrier function along with reduced endogenous bound sulfane sulfur. CSE siRNA knockdown also enhanced endothelial junction structures with increased claudin 5 protein expression. In vivo, CSE genetic deficiency significantly blunted VEGF induced hyperpermeability revealing an important role of the enzyme for barrier function. In summary, endothelial solute permeability is critically regulated via exogenous and endogenous sulfide bioavailability with a prominent role of polysulfides.
Partially Adaptive STAP Algorithm Approaches to functional MRI
Huang, Lejian; Thompson, Elizabeth A.; Schmithorst, Vincent; Holland, Scott K.; Talavage, Thomas M.
2010-01-01
In this work, the architectures of three partially adaptive STAP algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in construction of brain activation maps in fMRI. Computer simulations incorporating actual MRI noise and human data analysis indicate that element space partially adaptive STAP can attain close to the performance of fully adaptive STAP while significantly decreasing processing time and maximum memory requirements, and thus demonstrates potential in fMRI analysis. PMID:19272913
International Nuclear Information System (INIS)
Zio, E.; Bazzo, R.
2010-01-01
In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into 'families'. On the basis of the decision maker's preferences, each family is then synthetically represented by a 'head of the family' solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions
Kaur, Avneet; Bakhshi, A. K.
2010-04-01
The interest in copolymers stems from the fact that they present interesting electronic and optical properties leading to a variety of technological applications. In order to get a suitable copolymer for a specific application, genetic algorithm (GA) along with negative factor counting (NFC) method has recently been used. In this paper, we study the effect of change in the ratio of conduction band discontinuity to valence band discontinuity (Δ Ec/Δ Ev) on the optimum solution obtained from GA for model binary copolymers. The effect of varying bandwidths on the optimum GA solution is also investigated. The obtained results show that the optimum solution changes with varying parameters like band discontinuity and band width of constituent homopolymers. As the ratio Δ Ec/Δ Ev increases, band gap of optimum solution decreases. With increasing band widths of constituent homopolymers, the optimum solution tends to be dependent on the component with higher band gap.
A novel algorithm of artificial immune system for high-dimensional function numerical optimization
Institute of Scientific and Technical Information of China (English)
DU Haifeng; GONG Maoguo; JIAO Licheng; LIU Ruochen
2005-01-01
Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.
Directory of Open Access Journals (Sweden)
Zaer Abo-Hammour
2014-01-01
Full Text Available A new kind of optimization technique, namely, continuous genetic algorithm, is presented in this paper for numerically approximating the solutions of Troesch’s and Bratu’s problems. The underlying idea of the method is to convert the two differential problems into discrete versions by replacing each of the second derivatives by an appropriate difference quotient approximation. The new method has the following characteristics. First, it should not resort to more advanced mathematical tools; that is, the algorithm should be simple to understand and implement and should be thus easily accepted in the mathematical and physical application fields. Second, the algorithm is of global nature in terms of the solutions obtained as well as its ability to solve other mathematical and physical problems. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. The algorithm is tested on different versions of Troesch’s and Bratu’s problems. Experimental results show that the proposed algorithm is effective, straightforward, and simple.
Steering Angle Function Algorithm of Morphing of Residential Area
Directory of Open Access Journals (Sweden)
XIE Tian
2015-07-01
Full Text Available A residential area feature morphing method based on steering angle function is presented. To residential area with the same representation under two different scales,transforming the representation of the residential area polygon from vector coordinates to steering angle function,then using the steering angle function to match,and finding out the similarity and the differences between the residential areas under different scale to get the steering angle function of the the residential areas under any middle scale,the final,transforming the middle scale steering angle function to vector coordinates form,and get the middle shape interpolation of the the residential area polygon.Experimental results show:the residential area morphing method by using steering angle function presented can realize the continuous multi-scale representation under the premise of keeping in shape for the residential area with the rectangular boundary features.
Energy Technology Data Exchange (ETDEWEB)
Perusquia del Cueto, R.; Montes T, J. L.; Ortiz S, J. J.; Castillo M, A., E-mail: raul.perusquia@inin.gob.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2011-11-15
At present the techniques of evolution al computation receive an increasing attention in the scientific and technological areas. This situation is due to its enormous potential in the optimization applied to problems of discussed computational complexity. In the nuclear area these techniques are used in diverse problems of combinatory optimization related with designing cores of power reactors. A distinctive characteristic of the evolution al and/or meta-heuristic algorithms is that appeal in each one from their applications to an adjustment function, fitness or of quality. This function allows to discriminate or to evaluate potentials solutions of the problem to solve. The definition of this situation is very important since it allows following the search of the algorithm toward different regions of the search space. In this work the impact that has the election of this function in the quality of the found solution is shown. The optimization technique by ant colonies or Acs (ant colony system) was used applied to the radial design of fuel cells for a boiling water power reactor. The notable results of the Acs allowed to propose the adjustment method of the importance and with this to obtain adjustment functions that guide the search of solutions of collective algorithms efficiently, basic capacity to develop the proposal of emulation of the natural selection and to investigate the possibility that on order of specify goals, to obtain the corresponding decision variables. A variety of re tro-exit (re tro-out) complementary process of feedback (re tro-in) that opens extended application perspectives of be feasible. (Author)
Maximization of submodular functions : Theory and enumeration algorithms
Goldengorin, B.
2009-01-01
Submodular functions are powerful tools to model and solve either to optimality or approximately many operational research problems including problems defined on graphs. After reviewing some long-standing theoretical results about the structure of local and global maxima of submodular functions,
Vijayakumar, Ganesh; Sprague, Michael
2017-11-01
Demonstrating expected convergence rates with spatial- and temporal-grid refinement is the ``gold standard'' of code and algorithm verification. However, the lack of analytical solutions and generating manufactured solutions presents challenges for verifying codes for complex systems. The application of the method of manufactured solutions (MMS) for verification for coupled multi-physics phenomena like fluid-structure interaction (FSI) has only seen recent investigation. While many FSI algorithms for aeroelastic phenomena have focused on boundary-resolved CFD simulations, the actuator-line representation of the structure is widely used for FSI simulations in wind-energy research. In this work, we demonstrate the verification of an FSI algorithm using MMS for actuator-line CFD simulations with a simplified structural model. We use a manufactured solution for the fluid velocity field and the displacement of the SMD system. We demonstrate the convergence of both the fluid and structural solver to second-order accuracy with grid and time-step refinement. This work was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Wind Energy Technologies Office, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.
Bouallègue, Fayçal Ben; Crouzet, Jean-François; Comtat, Claude; Fourcade, Marjolaine; Mohammadi, Bijan; Mariano-Goulart, Denis
2007-07-01
This paper presents an extended 3-D exact rebinning formula in the Fourier space that leads to an iterative reprojection algorithm (iterative FOREPROJ), which enables the estimation of unmeasured oblique projection data on the basis of the whole set of measured data. In first approximation, this analytical formula also leads to an extended Fourier rebinning equation that is the basis for an approximate reprojection algorithm (extended FORE). These algorithms were evaluated on numerically simulated 3-D positron emission tomography (PET) data for the solution of the truncation problem, i.e., the estimation of the missing portions in the oblique projection data, before the application of algorithms that require complete projection data such as some rebinning methods (FOREX) or 3-D reconstruction algorithms (3DRP or direct Fourier methods). By taking advantage of all the 3-D data statistics, the iterative FOREPROJ reprojection provides a reliable alternative to the classical FOREPROJ method, which only exploits the low-statistics nonoblique data. It significantly improves the quality of the external reconstructed slices without loss of spatial resolution. As for the approximate extended FORE algorithm, it clearly exhibits limitations due to axial interpolations, but will require clinical studies with more realistic measured data in order to decide on its pertinence.
Synchrotron radiation and atom pair correlation functions in electrolyte solutions
International Nuclear Information System (INIS)
Triolo, R.; D'Aprano, A.
1978-01-01
Despite the enormous effort invested in experimental determinations of the properties of water and aqueous solutions, understanding is still rudimentary. Many of the problems are consequences of a nonrigorous definition of interparticle interactions. It is now clear that after properly ion--water interactions in terms of probability functions of position and orientation it is possible to probe these interactions at molecular levels using diffraction experiments. The role of synchrotron x-ray radiation in this context is being examined. Emphasis is given to the possibility of performing different experiments analogous to those done using the isotopic substitution method in neutron diffraction
Firefly algorithm based solution to minimize the real power loss in a power system
Directory of Open Access Journals (Sweden)
P. Balachennaiah
2018-03-01
Full Text Available This paper proposes a method to minimize the real power loss (RPL of a power system transmission network using a new meta-heuristic algorithm known as firefly algorithm (FA by optimizing the control variables such as transformer taps, UPFC location and UPFC series injected voltage magnitude and phase angle. A software program is developed in MATLAB environment for FA to minimize the RPL by optimizing (i only the transformer tap values, (ii only UPFC location and its variables with optimized tap values and (iii UPFC location and its variables along with transformer tap setting values simultaneously. Interior point successive linear programming (IPSLP technique and real coded genetic algorithm (RCGA are considered here to compare the results and to show the efficiency and superiority of the proposed FA towards the optimization of RPL. Also in this paper, bacteria foraging algorithm (BFA is adopted to validate the results of the proposed algorithm.
Automatic Curve Fitting Based on Radial Basis Functions and a Hierarchical Genetic Algorithm
Directory of Open Access Journals (Sweden)
G. Trejo-Caballero
2015-01-01
Full Text Available Curve fitting is a very challenging problem that arises in a wide variety of scientific and engineering applications. Given a set of data points, possibly noisy, the goal is to build a compact representation of the curve that corresponds to the best estimate of the unknown underlying relationship between two variables. Despite the large number of methods available to tackle this problem, it remains challenging and elusive. In this paper, a new method to tackle such problem using strictly a linear combination of radial basis functions (RBFs is proposed. To be more specific, we divide the parameter search space into linear and nonlinear parameter subspaces. We use a hierarchical genetic algorithm (HGA to minimize a model selection criterion, which allows us to automatically and simultaneously determine the nonlinear parameters and then, by the least-squares method through Singular Value Decomposition method, to compute the linear parameters. The method is fully automatic and does not require subjective parameters, for example, smooth factor or centre locations, to perform the solution. In order to validate the efficacy of our approach, we perform an experimental study with several tests on benchmarks smooth functions. A comparative analysis with two successful methods based on RBF networks has been included.
Directory of Open Access Journals (Sweden)
Delaram Houshmand Kouchi
2017-05-01
Full Text Available The successful application of hydrological models relies on careful calibration and uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms, and each could be run with different objective functions. In this paper, we highlight the fact that each combination of optimization algorithm-objective functions may lead to a different set of optimum parameters, while having the same performance; this makes the interpretation of dominant hydrological processes in a watershed highly uncertain. We used three different optimization algorithms (SUFI-2, GLUE, and PSO, and eight different objective functions (R2, bR2, NSE, MNS, RSR, SSQR, KGE, and PBIAS in a SWAT model to calibrate the monthly discharges in two watersheds in Iran. The results show that all three algorithms, using the same objective function, produced acceptable calibration results; however, with significantly different parameter ranges. Similarly, an algorithm using different objective functions also produced acceptable calibration results, but with different parameter ranges. The different calibrated parameter ranges consequently resulted in significantly different water resource estimates. Hence, the parameters and the outputs that they produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and objective function. This adds another level of non-negligible uncertainty to watershed models, calling for more attention and investigation in this area.
Quantum algorithms on Walsh transform and Hamming distance for Boolean functions
Xie, Zhengwei; Qiu, Daowen; Cai, Guangya
2018-06-01
Walsh spectrum or Walsh transform is an alternative description of Boolean functions. In this paper, we explore quantum algorithms to approximate the absolute value of Walsh transform W_f at a single point z0 (i.e., |W_f(z0)|) for n-variable Boolean functions with probability at least 8/π 2 using the number of O(1/|W_f(z_{0)|ɛ }) queries, promised that the accuracy is ɛ , while the best known classical algorithm requires O(2n) queries. The Hamming distance between Boolean functions is used to study the linearity testing and other important problems. We take advantage of Walsh transform to calculate the Hamming distance between two n-variable Boolean functions f and g using O(1) queries in some cases. Then, we exploit another quantum algorithm which converts computing Hamming distance between two Boolean functions to quantum amplitude estimation (i.e., approximate counting). If Ham(f,g)=t≠0, we can approximately compute Ham( f, g) with probability at least 2/3 by combining our algorithm and {Approx-Count(f,ɛ ) algorithm} using the expected number of Θ( √{N/(\\lfloor ɛ t\\rfloor +1)}+√{t(N-t)}/\\lfloor ɛ t\\rfloor +1) queries, promised that the accuracy is ɛ . Moreover, our algorithm is optimal, while the exact query complexity for the above problem is Θ(N) and the query complexity with the accuracy ɛ is O(1/ɛ 2N/(t+1)) in classical algorithm, where N=2n. Finally, we present three exact quantum query algorithms for two promise problems on Hamming distance using O(1) queries, while any classical deterministic algorithm solving the problem uses Ω(2n) queries.
STUDY ON ALGORITHM OF SENSOR MANAGEMENT BASED ON FUNCTIONS OF EFFICIENCY AND WASTE
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Sensor management plays an important role in data fusion system, and this paper presents an algorithm of sensor management that can be used in target detection, identification and tracking. First, the basic concept, rule, range and function of sensor management are introduced. Then, the quantifying problems of target priority and sensor (or combination)-target pairing in multisensor management are discussed and the efficiency and waste functions are established based on the functions of target priority and sensor-target pairing. On this basis, a distribution algorithm of multisensor resources is given, which is optimized by the principle of maximum synthesis efficiency in the multisensor system and constrained by sensor maximum tracking power and what target must be scanned. In addition, the waste measure of sensor resources is introduced to improve the algorithm. Finally, a tactical task that includes three sensors and ten targets is set, and the simulation results show that the algorithm is feasible and effective.
Implicit functions and solution mappings a view from variational analysis
Dontchev, Asen L
2014-01-01
The implicit function theorem is one of the most important theorems in analysis and its many variants are basic tools in partial differential equations and numerical analysis. This second edition of Implicit Functions and Solution Mappings presents an updated and more complete picture of the field by including solutions of problems that have been solved since the first edition was published, and places old and new results in a broader perspective. The purpose of this self-contained work is to provide a reference on the topic and to provide a unified collection of a number of results which are currently scattered throughout the literature. Updates to this edition include new sections in almost all chapters, new exercises and examples, updated commentaries to chapters and an enlarged index and references section. From reviews of the first edition: “The book commences with a helpful context-setting preface followed by six chapters. Each chapter starts with a useful preamble and concludes with a careful and ins...
International Nuclear Information System (INIS)
Doster, J.M.; Sills, E.D.
1986-01-01
Current efforts are under way to develop and evaluate numerical algorithms for the parallel solution of the large sparse matrix equations associated with the finite difference representation of the macroscopic Navier-Stokes equations. Previous work has shown that these equations can be cast into smaller coupled matrix equations suitable for solution utilizing multiple computer processors operating in parallel. The individual processors themselves may exhibit parallelism through the use of vector pipelines. This wor, has concentrated on the one-dimensional drift flux form of the Navier-Stokes equations. Direct and iterative algorithms that may be suitable for implementation on parallel computer architectures are evaluated in terms of accuracy and overall execution speed. This work has application to engineering and training simulations, on-line process control systems, and engineering workstations where increased computational speeds are required
Explicit symplectic algorithms based on generating functions for charged particle dynamics
Zhang, Ruili; Qin, Hong; Tang, Yifa; Liu, Jian; He, Yang; Xiao, Jianyuan
2016-07-01
Dynamics of a charged particle in the canonical coordinates is a Hamiltonian system, and the well-known symplectic algorithm has been regarded as the de facto method for numerical integration of Hamiltonian systems due to its long-term accuracy and fidelity. For long-term simulations with high efficiency, explicit symplectic algorithms are desirable. However, it is generally believed that explicit symplectic algorithms are only available for sum-separable Hamiltonians, and this restriction limits the application of explicit symplectic algorithms to charged particle dynamics. To overcome this difficulty, we combine the familiar sum-split method and a generating function method to construct second- and third-order explicit symplectic algorithms for dynamics of charged particle. The generating function method is designed to generate explicit symplectic algorithms for product-separable Hamiltonian with form of H (x ,p ) =pif (x ) or H (x ,p ) =xig (p ) . Applied to the simulations of charged particle dynamics, the explicit symplectic algorithms based on generating functions demonstrate superiorities in conservation and efficiency.
Estimating the Partition Function Zeros by Using the Wang-Landau Monte Carlo Algorithm
Energy Technology Data Exchange (ETDEWEB)
Kim, Seung-Yeon [Korea National University of Transportation, Chungju (Korea, Republic of)
2017-03-15
The concept of the partition function zeros is one of the most efficient methods for investigating the phase transitions and the critical phenomena in various physical systems. Estimating the partition function zeros requires information on the density of states Ω(E) as a function of the energy E. Currently, the Wang-Landau Monte Carlo algorithm is one of the best methods for calculating Ω(E). The partition function zeros in the complex temperature plane of the Ising model on an L × L square lattice (L = 10 ∼ 80) with a periodic boundary condition have been estimated by using the Wang-Landau Monte Carlo algorithm. The efficiency of the Wang-Landau Monte Carlo algorithm and the accuracies of the partition function zeros have been evaluated for three different, 5%, 10%, and 20%, flatness criteria for the histogram H(E).
Bakar, Sumarni Abu; Ibrahim, Milbah
2017-08-01
The shortest path problem is a popular problem in graph theory. It is about finding a path with minimum length between a specified pair of vertices. In any network the weight of each edge is usually represented in a form of crisp real number and subsequently the weight is used in the calculation of shortest path problem using deterministic algorithms. However, due to failure, uncertainty is always encountered in practice whereby the weight of edge of the network is uncertain and imprecise. In this paper, a modified algorithm which utilized heuristic shortest path method and fuzzy approach is proposed for solving a network with imprecise arc length. Here, interval number and triangular fuzzy number in representing arc length of the network are considered. The modified algorithm is then applied to a specific example of the Travelling Salesman Problem (TSP). Total shortest distance obtained from this algorithm is then compared with the total distance obtained from traditional nearest neighbour heuristic algorithm. The result shows that the modified algorithm can provide not only on the sequence of visited cities which shown to be similar with traditional approach but it also provides a good measurement of total shortest distance which is lesser as compared to the total shortest distance calculated using traditional approach. Hence, this research could contribute to the enrichment of methods used in solving TSP.
Directory of Open Access Journals (Sweden)
Vikram Kumar Kamboj
2016-04-01
Full Text Available In recent years, global warming and carbon dioxide (CO2 emission reduction have become important issues in India, as CO2 emission levels are continuing to rise in accordance with the increased volume of Indian national energy consumption under the pressure of global warming, it is crucial for Indian government to impose the effective policy to promote CO2 emission reduction. Challenge of supplying the nation with high quality and reliable electrical energy at a reasonable cost, converted government policy into deregulation and restructuring environment. This research paper presents aims to presents an effective solution for energy and environmental problems of electric power using an efficient and powerful hybrid optimization algorithm: Hybrid Harmony search-random search algorithm. The proposed algorithm is tested for standard IEEE-14 bus, -30 bus and -56 bus system. The effectiveness of proposed hybrid algorithm is compared with others well known evolutionary, heuristics and meta-heuristics search algorithms. For multi-objective unit commitment, it is found that as there are conflicting relationship between cost and emission, if the performance in cost criterion is improved, performance in the emission is seen to deteriorate.
DEFF Research Database (Denmark)
Nica, Florin Valentin Traian; Ritchie, Ewen; Leban, Krisztina Monika
2013-01-01
, genetic algorithm and particle swarm are shortly presented in this paper. These two algorithms are tested to determine their performance on five different benchmark test functions. The algorithms are tested based on three requirements: precision of the result, number of iterations and calculation time....... Both algorithms are also tested on an analytical design process of a Transverse Flux Permanent Magnet Generator to observe their performances in an electrical machine design application.......Nowadays the requirements imposed by the industry and economy ask for better quality and performance while the price must be maintained in the same range. To achieve this goal optimization must be introduced in the design process. Two of the best known optimization algorithms for machine design...
Formula over Function? From Algorithms to Values in Judicial Evaluation
Directory of Open Access Journals (Sweden)
Francesco Contini
2014-12-01
Full Text Available This paper discusses the forms and effects of the ‘invasion’ of the ‘temples of the law’ by new economic and managerial forms of performance evaluation. While traditional judicial evaluation focused on how to select and promote individual judges and on the legal quality of the single case, new quantitative methods and formulas are being introduced to assess efficiency, productivity and timeliness of judges and courts. Building on two case studies, from Spain and the Netherlands, the paper illustrates two contrasting approaches to judicial performance evaluation. On the one hand individual judges' productivity is evaluated through quantitative data and mathematical algorithms: in the extreme case considered here, judge's remuneration was adjusted accordingly. On the other hand quantitative and qualitative data, collected by a variety of methods and theoretical frameworks, are used as the basis of a multi-layered negotiation process designed to find a synthesis between competing economic, legal and social values aimed at improving overall organizational performance. Considering the flaws of unidimensional measurement and evaluation systems and considering the incommensurability of the results of the multiple evaluative frameworks (economic, legal, sociological required to overcome such flaws, the authors argue there is a need for political dialogue between relevant players in order to allocate the values appropriate to judicial evaluation. Este artículo analiza las formas y efectos de la “invasión” de los “templos de la ley” por nuevas formas económicas y de gestión como la evaluación del rendimiento. Mientras que la evaluación judicial tradicional se ha centrado en la forma de seleccionar y promocionar a jueces individuales, y en la calidad jurídica de un caso individual, hoy en día se están introduciendo nuevos métodos cuantitativos y fórmulas para determinar la eficiencia, productividad y oportunidad de jueces y
Improving the quantum cost of reversible Boolean functions using reorder algorithm
Ahmed, Taghreed; Younes, Ahmed; Elsayed, Ashraf
2018-05-01
This paper introduces a novel algorithm to synthesize a low-cost reversible circuits for any Boolean function with n inputs represented as a Positive Polarity Reed-Muller expansion. The proposed algorithm applies a predefined rules to reorder the terms in the function to minimize the multi-calculation of common parts of the Boolean function to decrease the quantum cost of the reversible circuit. The paper achieves a decrease in the quantum cost and/or the circuit length, on average, when compared with relevant work in the literature.
A deterministic algorithm for fitting a step function to a weighted point-set
Fournier, Hervé
2013-02-01
Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance to the input points. It matches the expected time bound of the best known randomized algorithm for this problem. Our approach relies on Coles improved parametric searching technique. As a direct application, our result yields the first O(nlogn)-time algorithm for computing a k-center of a set of n weighted points on the real line. © 2012 Elsevier B.V.
Directory of Open Access Journals (Sweden)
Ewiak Ireneusz
2016-12-01
Full Text Available Available on the commercial market are a number of algorithms that enable assigning to pixels of a monochrome digital image suitable colors according to a strictly defined schedule. These algorithms have been recently used by professional film studios involved in the coloring of archival productions. This article provides an overview on the functionality of coloring algorithms in terms of their use to improve the interpretation quality of historical, black - and - white aerial photographs. The analysis covered intuitive (Recolored programs, as well as more advanced (Adobe After Effect, DaVinci Resolve programs. The use of their full functionality was limited by the too large information capacity of aerial photograph images. Black - and - white historical aerial photographs, which interpretation quality in many cases does not meet the criteria posed on photogrammetric developments, require an increase of their readability. The solution in this regard may be the process of coloring images. The authors of this article conducted studies aimed to determine to what extent the tested coloring algorithms enable an automatic detection of land cover elements on historical aerial photographs and provide color close to the natural. Used in the studies were archival black - and - white aerial photographs of the western part of Warsaw district made available by the Main Centre of Geodetic and Cartographic Documentation , the selection of which was associated with the presence in this area of various elements of land cover, such as water, forests, crops, exposed soils and also anthropogenic objects. In the analysis of different algorithms are included: format and size of the image, degree of automation of the process, degree of compliance of the result and processing time. The accuracy of the coloring process was different for each class of objects mapped on the photograph. The main limitation of the coloring process created shadows of anthropogenic objects
A Data Forward Stepwise Fitting Algorithm Based on Orthogonal Function System
Directory of Open Access Journals (Sweden)
Li Han-Ju
2017-01-01
Full Text Available Data fitting is the main method of functional data analysis, and it is widely used in the fields of economy, social science, engineering technology and so on. Least square method is the main method of data fitting, but the least square method is not convergent, no memory property, big fitting error and it is easy to over fitting. Based on the orthogonal trigonometric function system, this paper presents a data forward stepwise fitting algorithm. This algorithm takes forward stepwise fitting strategy, each time using the nearest base function to fit the residual error generated by the previous base function fitting, which makes the residual mean square error minimum. In this paper, we theoretically prove the convergence, the memory property and the fitting error diminishing character for the algorithm. Experimental results show that the proposed algorithm is effective, and the fitting performance is better than that of the least square method and the forward stepwise fitting algorithm based on the non-orthogonal function system.
Model and Algorithm for Substantiating Solutions for Organization of High-Rise Construction Project
Directory of Open Access Journals (Sweden)
Anisimov Vladimir
2018-01-01
Full Text Available In the paper the models and the algorithm for the optimal plan formation for the organization of the material and logistical processes of the high-rise construction project and their financial support are developed. The model is based on the representation of the optimization procedure in the form of a non-linear problem of discrete programming, which consists in minimizing the execution time of a set of interrelated works by a limited number of partially interchangeable performers while limiting the total cost of performing the work. The proposed model and algorithm are the basis for creating specific organization management methodologies for the high-rise construction project.
Model and Algorithm for Substantiating Solutions for Organization of High-Rise Construction Project
Anisimov, Vladimir; Anisimov, Evgeniy; Chernysh, Anatoliy
2018-03-01
In the paper the models and the algorithm for the optimal plan formation for the organization of the material and logistical processes of the high-rise construction project and their financial support are developed. The model is based on the representation of the optimization procedure in the form of a non-linear problem of discrete programming, which consists in minimizing the execution time of a set of interrelated works by a limited number of partially interchangeable performers while limiting the total cost of performing the work. The proposed model and algorithm are the basis for creating specific organization management methodologies for the high-rise construction project.
Aging and response conflict solution: behavioural and functional connectivity changes.
Langner, Robert; Cieslik, Edna C; Behrwind, Simone D; Roski, Christian; Caspers, Svenja; Amunts, Katrin; Eickhoff, Simon B
2015-01-01
Healthy aging has been found associated with less efficient response conflict solution, but the cognitive and neural mechanisms have remained elusive. In a two-experiment study, we first examined the behavioural consequences of this putative age-related decline for conflicts induced by spatial stimulus-response incompatibility. We then used resting-state functional magnetic resonance imaging data from a large, independent sample of adults (n = 399; 18-85 years) to investigate age differences in functional connectivity between the nodes of a network previously found associated with incompatibility-induced response conflicts in the very same paradigm. As expected, overcoming interference from conflicting response tendencies took longer in older adults, even after accounting for potential mediator variables (general response speed and accuracy, motor speed, visuomotor coordination ability, and cognitive flexibility). Experiment 2 revealed selective age-related decreases in functional connectivity between bilateral anterior insula, pre-supplementary motor area, and right dorsolateral prefrontal cortex. Importantly, these age effects persisted after controlling for regional grey-matter atrophy assessed by voxel-based morphometry. Meta-analytic functional profiling using the BrainMap database showed these age-sensitive nodes to be more strongly linked to highly abstract cognition, as compared with the remaining network nodes, which were more strongly linked to action-related processing. These findings indicate changes in interregional coupling with age among task-relevant network nodes that are not specifically associated with conflict resolution per se. Rather, our behavioural and neural data jointly suggest that healthy aging is associated with difficulties in properly activating non-dominant but relevant task schemata necessary to exert efficient cognitive control over action.
Fast Time and Space Parallel Algorithms for Solution of Parabolic Partial Differential Equations
Fijany, Amir
1993-01-01
In this paper, fast time- and Space -Parallel agorithms for solution of linear parabolic PDEs are developed. It is shown that the seemingly strictly serial iterations of the time-stepping procedure for solution of the problem can be completed decoupled.
Composite Differential Search Algorithm
Directory of Open Access Journals (Sweden)
Bo Liu
2014-01-01
Full Text Available Differential search algorithm (DS is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.
Directory of Open Access Journals (Sweden)
Suheel Abdullah Malik
Full Text Available In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE through substitution is converted into a nonlinear ordinary differential equation (NODE. The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM, homotopy perturbation method (HPM, and optimal homotopy asymptotic method (OHAM, show that the suggested scheme is fairly accurate and viable for solving such problems.
Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul
2015-01-01
In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.
Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.
2012-01-01
, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network
Thermodynamically Consistent Algorithms for the Solution of Phase-Field Models
Vignal, Philippe
2016-01-01
of thermodynamically consistent algorithms for time integration of phase-field models. The first part of this thesis focuses on an energy-stable numerical strategy developed for the phase-field crystal equation. This model was put forward to model microstructure
1980-10-01
solving (1.3); PFAS combines the concepts of multigrid algorithms with those of projected SOR. In Section 3, we discuss the implementation of PFAS, and...numerique de la torsion elasto- plastique d’une barre cylindrique. In Approximation et Methodes Iteratives de Resolution d’Inequations Variationelles et
Developing the algorithm for assessing the competitive abilities of functional foods in marketing
Directory of Open Access Journals (Sweden)
Nilova Liudmila
2017-01-01
Full Text Available A thorough analysis of competitive factors of functional foods has made it possible to develop an algorithm for assessing the competitive factors of functional food products, with respect to their essential consumer features — quality, safety and functionality. Questionnaires filled in by experts and the published results of surveys of consumers from different countries were used to help select the essential consumer features in functional foods. A “desirability of consumer features” model triangle, based on functional bread and bakery products, was constructed with the use of the Harrington function.
Cengizci, Süleyman; Atay, Mehmet Tarık; Eryılmaz, Aytekin
2016-01-01
This paper is concerned with two-point boundary value problems for singularly perturbed nonlinear ordinary differential equations. The case when the solution only has one boundary layer is examined. An efficient method so called Successive Complementary Expansion Method (SCEM) is used to obtain uniformly valid approximations to this kind of solutions. Four test problems are considered to check the efficiency and accuracy of the proposed method. The numerical results are found in good agreement with exact and existing solutions in literature. The results confirm that SCEM has a superiority over other existing methods in terms of easy-applicability and effectiveness.
Yan, S.; Lin, H. C.; Jiang, X. Y.
2012-04-01
In this study the authors employ network flow techniques to construct a systematic model that helps ready mixed concrete carriers effectively plan production and truck dispatching schedules under stochastic travel times. The model is formulated as a mixed integer network flow problem with side constraints. Problem decomposition and relaxation techniques, coupled with the CPLEX mathematical programming solver, are employed to develop an algorithm that is capable of efficiently solving the problems. A simulation-based evaluation method is also proposed to evaluate the model, coupled with a deterministic model, and the method currently used in actual operations. Finally, a case study is performed using real operating data from a Taiwan RMC firm. The test results show that the system operating cost obtained using the stochastic model is a significant improvement over that obtained using the deterministic model or the manual approach. Consequently, the model and the solution algorithm could be useful for actual operations.
special algorithm for the numerical solution of system of initial value ...
African Journals Online (AJOL)
Nwokem et al.
Science World Journal Vol 12(No 4) 2017 ... Over the years, several researchers have considered the collocation method as a way of generating numerical solutions to ... study problems in mathematics, engineering, computer science and.
A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification
Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.
MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.
Hong, Xia
2006-07-01
In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.
Algorithm 831: modified Bessel functions of imaginary order and positive argument
A. Gil (Amparo); J. Segura (Javier); N.M. Temme (Nico)
2004-01-01
textabstract77 programs for the computation of modified Bessel functions of purely imaginary order are presented. The codes compute the functions Kia (x), Lia (x) and their derivatives for real a and positive x; these functions are independent solutions of the differential equation x2w'' + xw' + (a2
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available We define a special case for the vehicle routing problem with stochastic demands (SC-VRPSD where customer demands are normally distributed. We propose a new linear model for computing the expected length of a tour in SC-VRPSD. The proposed model is based on the integration of the “Traveling Salesman Problem” (TSP and the Assignment Problem. For large-scale problems, we also use an Iterated Local Search (ILS algorithm in order to reach an effective solution.
Directory of Open Access Journals (Sweden)
J. Moeys
2012-07-01
Full Text Available Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedotransfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved.
Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42. Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = −0.26 due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72. Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is
Moeys, J.; Larsbo, M.; Bergström, L.; Brown, C. D.; Coquet, Y.; Jarvis, N. J.
2012-07-01
Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the
International Nuclear Information System (INIS)
Shang Yadong
2008-01-01
The extended hyperbolic functions method for nonlinear wave equations is presented. Based on this method, we obtain a multiple exact explicit solutions for the nonlinear evolution equations which describe the resonance interaction between the long wave and the short wave. The solutions obtained in this paper include (a) the solitary wave solutions of bell-type for S and L, (b) the solitary wave solutions of kink-type for S and bell-type for L, (c) the solitary wave solutions of a compound of the bell-type and the kink-type for S and L, (d) the singular travelling wave solutions, (e) periodic travelling wave solutions of triangle function types, and solitary wave solutions of rational function types. The variety of structure to the exact solutions of the long-short wave equation is illustrated. The methods presented here can also be used to obtain exact solutions of nonlinear wave equations in n dimensions
Energy Technology Data Exchange (ETDEWEB)
Rowbottom, Carl Graham [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom); Webb, Steve [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom)
2002-01-07
The successful implementation of downhill search engines in radiotherapy optimization algorithms depends on the absence of local minima in the search space. Such techniques are much faster than stochastic optimization methods but may become trapped in local minima if they exist. A technique known as 'configuration space analysis' was applied to examine the search space of cost functions used in radiotherapy beam-weight optimization algorithms. A downhill-simplex beam-weight optimization algorithm was run repeatedly to produce a frequency distribution of final cost values. By plotting the frequency distribution as a function of final cost, the existence of local minima can be determined. Common cost functions such as the quadratic deviation of dose to the planning target volume (PTV), integral dose to organs-at-risk (OARs), dose-threshold and dose-volume constraints for OARs were studied. Combinations of the cost functions were also considered. The simple cost function terms such as the quadratic PTV dose and integral dose to OAR cost function terms are not susceptible to local minima. In contrast, dose-threshold and dose-volume OAR constraint cost function terms are able to produce local minima in the example case studied. (author)
Ghazzai, Hakim
2012-01-01
The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.
A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization
Directory of Open Access Journals (Sweden)
Daqing Wu
2012-01-01
Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.
A deterministic algorithm for fitting a step function to a weighted point-set
Fournier, Hervé
2013-01-01
Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance
A solution algorithm for calculating photon radiation fields with the aid of the Monte Carlo method
International Nuclear Information System (INIS)
Zappe, D.
1978-04-01
The MCTEST program and its subroutines for the solution of the Boltzmann transport equation is presented. The program renders possible to calculate photon radiation fields of point or plane gamma sources. After changing two subroutines the calculation can also be carried out for the case of directed incidence of radiation on plane shields of iron or concrete. (author)
Goldengorin, B.; Ghosh, D.
Maximization of submodular functions on a ground set is a NP-hard combinatorial optimization problem. Data correcting algorithms are among the several algorithms suggested for solving this problem exactly and approximately. From the point of view of Hasse diagrams data correcting algorithms use
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Existence of global solutions to reaction-diffusion systems via a Lyapunov functional
Directory of Open Access Journals (Sweden)
Said Kouachi
2001-10-01
Full Text Available The purpose of this paper is to construct polynomial functionals (according to solutions of the coupled reaction-diffusion equations which give $L^{p}$-bounds for solutions. When the reaction terms are sufficiently regular, using the well known regularizing effect, we deduce the existence of global solutions. These functionals are obtained independently of work done by Malham and Xin [11].
Viscosity solutions of fully nonlinear functional parabolic PDE
Directory of Open Access Journals (Sweden)
Liu Wei-an
2005-01-01
Full Text Available By the technique of coupled solutions, the notion of viscosity solutions is extended to fully nonlinear retarded parabolic equations. Such equations involve many models arising from optimal control theory, economy and finance, biology, and so forth. The comparison principle is shown. Then the existence and uniqueness are established by the fixed point theory.
International Nuclear Information System (INIS)
Zhang Liang; Zhang Lifeng; Li Chongyin
2008-01-01
By using the modified mapping method, we find some new exact solutions of the generalized Boussinesq equation and the Boussinesq-Burgers equation. The solutions obtained in this paper include Jacobian elliptic function solutions, combined Jacobian elliptic function solutions, soliton solutions, triangular function solutions
Solution for the multigroup neutron space kinetics equations by the modified Picard algorithm
Energy Technology Data Exchange (ETDEWEB)
Tavares, Matheus G.; Petersen, Claudio Z., E-mail: matheus.gulartetavares@gmail.com [Universidade Federal de Pelotas (UFPEL), Capao do Leao, RS (Brazil). Departamento de Matematica e Estatistica; Schramm, Marcelo, E-mail: schrammmarcelo@gmail.com [Universidade Federal de Pelotas (UFPEL), RS (Brazil). Centro de Engenharias; Zanette, Rodrigo, E-mail: rodrigozanette@hotmail.com [Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil). Instituto de Matematica e Estatistica
2017-07-01
In this work, we used a modified Picards method to solve the Multigroup Neutron Space Kinetics Equations (MNSKE) in Cartesian geometry. The method consists in assuming an initial guess for the neutron flux and using it to calculate a fictitious source term in the MNSKE. A new source term is calculated applying its solution, and so on, iteratively, until a stop criterion is satisfied. For the solution of the fast and thermal neutron fluxes equations, the Laplace Transform technique is used in time variable resulting in a rst order linear differential matrix equation, which are solved by classical methods in the literature. After each iteration, the scalar neutron flux and the delayed neutron precursors are reconstructed by polynomial interpolation. We obtain the fluxes and precursors through Numerical Inverse Laplace Transform using the Stehfest method. We present numerical simulations and comparisons with available results in literature. (author)
Solution for the multigroup neutron space kinetics equations by the modified Picard algorithm
International Nuclear Information System (INIS)
Tavares, Matheus G.; Petersen, Claudio Z.; Schramm, Marcelo; Zanette, Rodrigo
2017-01-01
In this work, we used a modified Picards method to solve the Multigroup Neutron Space Kinetics Equations (MNSKE) in Cartesian geometry. The method consists in assuming an initial guess for the neutron flux and using it to calculate a fictitious source term in the MNSKE. A new source term is calculated applying its solution, and so on, iteratively, until a stop criterion is satisfied. For the solution of the fast and thermal neutron fluxes equations, the Laplace Transform technique is used in time variable resulting in a rst order linear differential matrix equation, which are solved by classical methods in the literature. After each iteration, the scalar neutron flux and the delayed neutron precursors are reconstructed by polynomial interpolation. We obtain the fluxes and precursors through Numerical Inverse Laplace Transform using the Stehfest method. We present numerical simulations and comparisons with available results in literature. (author)
Penkov, V. B.; Levina, L. V.; Novikova, O. S.; Shulmin, A. S.
2018-03-01
Herein we propose a methodology for structuring a full parametric analytical solution to problems featuring elastostatic media based on state-of-the-art computing facilities that support computerized algebra. The methodology includes: direct and reverse application of P-Theorem; methods of accounting for physical properties of media; accounting for variable geometrical parameters of bodies, parameters of boundary states, independent parameters of volume forces, and remote stress factors. An efficient tool to address the task is the sustainable method of boundary states originally designed for the purposes of computerized algebra and based on the isomorphism of Hilbertian spaces of internal states and boundary states of bodies. We performed full parametric solutions of basic problems featuring a ball with a nonconcentric spherical cavity, a ball with a near-surface flaw, and an unlimited medium with two spherical cavities.
Development of Web-Based Menu Planning Support System and its Solution Using Genetic Algorithm
Kashima, Tomoko; Matsumoto, Shimpei; Ishii, Hiroaki
2009-10-01
Recently lifestyle-related diseases have become an object of public concern, while at the same time people are being more health conscious. As an essential factor for causing the lifestyle-related diseases, we assume that the knowledge circulation on dietary habits is still insufficient. This paper focuses on everyday meals close to our life and proposes a well-balanced menu planning system as a preventive measure of lifestyle-related diseases. The system is developed by using a Web-based frontend and it provides multi-user services and menu information sharing capabilities like social networking services (SNS). The system is implemented on a Web server running Apache (HTTP server software), MySQL (database management system), and PHP (scripting language for dynamic Web pages). For the menu planning, a genetic algorithm is applied by understanding this problem as multidimensional 0-1 integer programming.
A genetic algorithm solution for a nuclear power plant risk-cost maintenance model
International Nuclear Information System (INIS)
Tong Jiejuan; Mao Dingyuan; Xue Dazhi
2004-01-01
Reliability Centered Maintenance (RCM) is one of the popular maintenance optimization methods according to certain kinds of priorities. Traditional RCM usually analyzes and optimizes the maintenance strategy from the viewpoint of component instead of the whole maintenance program impact. Research presented in this paper is a pilot study using PSA techniques in RCM. How to reflect the effect on component unavailability by the maintenance activities such as surveillance testing and preventive maintenance in PSA model is discussed firstly. Based on the discussion, a maintenance risk-cost model is established for global maintenance optimization in a nuclear power plant, and a genetic algorithm (GA) is applied to solve such a model to get the global optimized maintenance strategy. Finally, the result got from a simple test case based on a risk-cost model consisting of 10 components is presented
International Nuclear Information System (INIS)
Molchanov, I.N.; Khimich, A.N.
1984-01-01
This article shows how a reflection method can be used to find the eigenvalues of a matrix by transforming the matrix to tridiagonal form. The method of conjugate gradients is used to find the smallest eigenvalue and the corresponding eigenvector of symmetric positive-definite band matrices. Topics considered include the computational scheme of the reflection method, the organization of parallel calculations by the reflection method, the computational scheme of the conjugate gradient method, the organization of parallel calculations by the conjugate gradient method, and the effectiveness of parallel algorithms. It is concluded that it is possible to increase the overall effectiveness of the multiprocessor electronic computers by either letting the newly available processors of a new problem operate in the multiprocessor mode, or by improving the coefficient of uniform partition of the original information
Hong, X; Harris, C J
2000-01-01
This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.
Development of fuzzy algorithm with learning function for nuclear steam generator level control
International Nuclear Information System (INIS)
Park, Gee Yong; Seong, Poong Hyun
1993-01-01
A fuzzy algorithm with learning function is applied to the steam generator level control of nuclear power plant. This algorithm can make its rule base and membership functions suited for steam generator level control by use of the data obtained from the control actions of a skilled operator or of other controllers (i.e., PID controller). The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0 % - 30 % of full power) and the other to level control at high power level (30 % - 100 % of full power). Response time of steam generator level control at low power range with this rule base is shown to be shorter than that of fuzzy controller with direct inference. (Author)
Simulation of 4-turn algorithms for reconstructing lattice optic functions from orbit measurements
International Nuclear Information System (INIS)
Koscielniak, S.; Iliev, A.
1994-06-01
We describe algorithms for reconstructing tune, closed-orbit, beta-function and phase advance from four individual turns of beam orbit acquisition data, under the assumption of coherent, almost linear and uncoupled betatron oscillations. To estimate the beta-function at, and phase advance between, position monitors, we require at least one anchor location consisting of two monitors separated by a drift. The algorithms were submitted to a Monte Carlo analysis to find the likely measurement accuracy of the optics functions in the KAON Factory Booster ring racetrack lattice, assuming beam position monitors with surveying and reading errors, and assuming an imperfect lattice with gradient and surveying errors. Some of the results of this study are reported. (author)
High-frequency asymptotics of the local vertex function. Algorithmic implementations
Energy Technology Data Exchange (ETDEWEB)
Tagliavini, Agnese; Wentzell, Nils [Institut fuer Theoretische Physik, Eberhard Karls Universitaet, 72076 Tuebingen (Germany); Institute for Solid State Physics, Vienna University of Technology, 1040 Vienna (Austria); Li, Gang; Rohringer, Georg; Held, Karsten; Toschi, Alessandro [Institute for Solid State Physics, Vienna University of Technology, 1040 Vienna (Austria); Taranto, Ciro [Institute for Solid State Physics, Vienna University of Technology, 1040 Vienna (Austria); Max Planck Institute for Solid State Research, D-70569 Stuttgart (Germany); Andergassen, Sabine [Institut fuer Theoretische Physik, Eberhard Karls Universitaet, 72076 Tuebingen (Germany)
2016-07-01
Local vertex functions are a crucial ingredient of several forefront many-body algorithms in condensed matter physics. However, the full treatment of their frequency dependence poses a huge limitation to the numerical performance. A significant advancement requires an efficient treatment of the high-frequency asymptotic behavior of the vertex functions. We here provide a detailed diagrammatic analysis of the high-frequency asymptotic structures and their physical interpretation. Based on these insights, we propose a frequency parametrization, which captures the whole high-frequency asymptotics for arbitrary values of the local Coulomb interaction and electronic density. We present its algorithmic implementation in many-body solvers based on parquet-equations as well as functional renormalization group schemes and assess its validity by comparing our results for the single impurity Anderson model with exact diagonalization calculations.
DEFF Research Database (Denmark)
Caerts, Chris; Rikos, Evangelos; Syed, Mazheruddin
2017-01-01
This D4.2 document provides the description of the detailed functional architecture of the selected solutions that will be implemented and tested. This is documented by combining a function-based IEC 62559 Use Case description with an SGAM mapping of these functions and the interactions among...... these functions on the Function and Information layer....
Energy Technology Data Exchange (ETDEWEB)
Fischer, P.F. [Brown Univ., Providence, RI (United States)
1996-12-31
Efficient solution of the Navier-Stokes equations in complex domains is dependent upon the availability of fast solvers for sparse linear systems. For unsteady incompressible flows, the pressure operator is the leading contributor to stiffness, as the characteristic propagation speed is infinite. In the context of operator splitting formulations, it is the pressure solve which is the most computationally challenging, despite its elliptic origins. We seek to improve existing spectral element iterative methods for the pressure solve in order to overcome the slow convergence frequently observed in the presence of highly refined grids or high-aspect ratio elements.
Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T
2017-01-01
Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.
Energy Technology Data Exchange (ETDEWEB)
Barbosa, Diego R.; Silva, Alessandro L. da; Luciano, Edson Jose Rezende; Nepomuceno, Leonardo [Universidade Estadual Paulista (UNESP), Bauru, SP (Brazil). Dept. de Engenharia Eletrica], Emails: diego_eng.eletricista@hotmail.com, alessandrolopessilva@uol.com.br, edson.joserl@uol.com.br, leo@feb.unesp.br
2009-07-01
Problems of DC Optimal Power Flow (OPF) have been solved by various conventional optimization methods. When the modeling of DC OPF involves discontinuous functions or not differentiable, the use of solution methods based on conventional optimization is often not possible because of the difficulty in calculating the gradient vectors at points of discontinuity/non-differentiability of these functions. This paper proposes a method for solving the DC OPF based on Genetic Algorithms (GA) with real coding. The proposed GA has specific genetic operators to improve the quality and viability of the solution. The results are analyzed for an IEEE test system, and its solutions are compared, when possible, with those obtained by a method of interior point primal-dual logarithmic barrier. The results highlight the robustness of the method and feasibility of obtaining the solution to real systems.
Hyperbolic white noise functional solutions of Wick-type stochastic compound KdV-Burgers equations
International Nuclear Information System (INIS)
Han Xiu; Xie Yingchao
2009-01-01
Variable coefficient and Wick-type stochastic compound KdV-Burgers equations are investigated. By using white noise analysis, Hermite transform and the hyperbolic function method, we obtain a number of Wick versions of hyperbolic white noise functional solutions and hyperbolic function solutions for Wick-type stochastic and variable coefficient compound KdV-Burgers equations, respectively.
Benchmarking algorithms for the solution of Collisional Radiative Model (CRM) equations.
Klapisch, Marcel; Busquet, Michel
2007-11-01
Elements used in ICF target designs can have many charge states in the same plasma conditions, each charge state having numerous energy levels. When LTE conditions are not met, one has to solve CRM equations for the populations of energy levels, which are necessary for opacities/emissivities, Z* etc. In case of sparse spectra, or when configuration interaction is important (open d or f shells), statistical methods[1] are insufficient. For these cases one must resort to a detailed level CRM rate generator[2]. The equations to be solved may involve tens of thousands of levels. The system is by nature ill conditioned. We show that some classical methods do not converge. Improvements of the latter will be compared with new algorithms[3] with respect to performance, robustness, and accuracy. [1] A Bar-Shalom, J Oreg, and M Klapisch, J. Q. S. R. T.,65, 43 (2000). [2] M Klapisch, M Busquet and A. Bar-Shalom, Proceedings of APIP'07, AIP series (to be published). [3] M Klapisch and M Busquet, High Ener. Density Phys. 3,143 (2007)
Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao
2015-01-01
Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383
Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution, and Inversion
DEFF Research Database (Denmark)
Gustavson, Fred G.; Wasniewski, Jerzy; Dongarra, Jack J
2010-01-01
of the storage space but provide high performance via the use of Level 3 BLAS. Standard packed format arrays fully utilize storage (array space) but provide low performance as there is no Level 3 packed BLAS. We combine the good features of packed and full storage using RFPF to obtain high performance via using...... Level 3 BLAS as RFPF is a standard full-format representation. Also, RFPF requires exactly the same minimal storage as packed the format. Each LAPACK full and/or packed triangular, symmetric, and Hermitian routine becomes a single new RFPF routine based on eight possible data layouts of RFPF. This new...... RFPF routine usually consists of two calls to the corresponding LAPACK full-format routine and two calls to Level 3 BLAS routines. This means no new software is required. As examples, we present LAPACK routines for Cholesky factorization, Cholesky solution, and Cholesky inverse computation in RFPF...
Integrated algorithms for RFID-based multi-sensor indoor/outdoor positioning solutions
Zhu, Mi.; Retscher, G.; Zhang, K.
2011-12-01
Position information is very important as people need it almost everywhere all the time. However, it is a challenging task to provide precise positions indoor/outdoor seamlessly. Outdoor positioning has been widely studied and accurate positions can usually be achieved by well developed GPS techniques but these techniques are difficult to be used indoors since GPS signal reception is limited. The alternative techniques that can be used for indoor positioning include, to name a few, Wireless Local Area Network (WLAN), bluetooth and Ultra Wideband (UWB) etc.. However, all of these have limitations. The main objectives of this paper are to investigate and develop algorithms for a low-cost and portable indoor personal positioning system using Radio Frequency Identification (RFID) and its integration with other positioning systems. An RFID system consists of three components, namely a control unit, an interrogator and a transponder that transmits data and communicates with the reader. An RFID tag can be incorporated into a product, animal or person for the purpose of identification and tracking using radio waves. In general, for RFID positioning in urban and indoor environments three different methods can be used, including cellular positioning, trilateration and location fingerprinting. In addition, the integration of RFID with other technologies is also discussed in this paper. A typical combination is to integrate RFID with relative positioning technologies such as MEMS INS to bridge the gaps between RFID tags for continuous positioning applications. Experiments are shown to demonstrate the improvements of integrating multiple sensors with RFID which can be employed successfully for personal positioning.
On the existence of solutions for functional differential equations
International Nuclear Information System (INIS)
Walo Omana, R.
1994-12-01
The aim of the paper is to extend the Granas Topological Transversality Method used in boundary value problems for functional differential equations for first and second order, to the case of n-th order functional differential equations. 15 refs
International Nuclear Information System (INIS)
Cunha Furtado, F. da; Galeao, A.C.N.R.
1984-01-01
A numerical procedure for the integration of the incompressible Navier-Stokes equations, when expressed in terms of a stream function equation and a vorticity transport equation, is presented. This procedure comprises: the variational formulation of the equations, the construction of the approximation spaces by the finite element method and the discretization via the Galerkin method. For the stationary problems, the system of non-linear algebraic equations resulting from the discretization is solved by the Newton-Raphson algorithm. Finally, for the transient problems, the solution of the non-linear ordinary differential equations resulting from the spatial discretization is accomplished through a Crank-Nicolson scheme. (Author) [pt
International Nuclear Information System (INIS)
Niknam, Taher; Sharifinia, Sajjad; Azizipanah-Abarghooee, Rasoul
2013-01-01
Highlights: • Present optimal bidding strategies of Generating Companies (GENCOs) in a network-constrained electricity market. • Present new enhanced bat-inspired algorithm. • Consider the bi level optimization problem. • Present a linear supply function model. - Abstract: This paper proposes a new enhanced bat-inspired algorithm to find out linear supply function equilibrium of Generating Companies (GENCOs) in a network-constrained electricity market where they have incomplete information about other rivals. The model enables a GENCO to link its bidding price with the bidding quantity of its product. In this regard, the social welfare maximization is applied to clearing the market and nodal pricing mechanism is utilized to calculate the GENCO’s profit. It is formulated as a bi level optimization problem, where the higher level problem maximizes GENCO’s payoff and the lower level problem solves the independent system operator’s market clearing problem based on the maximization of social welfare. Due to non-convexity nature of the proposed bi level optimization problem, the mathematical-based optimization approach is incapable to solve the problem and obtain the nearly global optima. In order to overcome the obstacle of the conventional approaches, this study suggests a new meta-heuristic Bat-inspired Algorithm (BA) to achieve the nearly global solution of the bi level optimization problem. In addition a novel self-adaptive learning mechanism is utilized on the original BA to improve the population diversity and global searching capability. Numerical examples are applied to three test systems in order to evaluate the performances of the presented framework
Kutsanedzie, Felix Y H; Chen, Quansheng; Hassan, Md Mehedi; Yang, Mingxiu; Sun, Hao; Rahman, Md Hafizur
2018-02-01
Total fungi count (TFC) is a quality indicator of cocoa beans when unmonitored leads to quality and safety problems. Fourier transform near infrared spectroscopy (FT-NIRS) combined with chemometric algorithms like partial least square (PLS); synergy interval-PLS (Si-PLS); synergy interval-genetic algorithm-PLS (Si-GAPLS); Ant colony optimization - PLS (ACO-PLS) and competitive-adaptive reweighted sampling-PLS (CARS-PLS) was employed to predict TFC in cocoa beans neat solution. Model results were evaluated using the correlation coefficients of the prediction (Rp) and calibration (Rc); root mean square error of prediction (RMSEP), and the ratio of sample standard deviation to RMSEP (RPD). The developed models performance yielded 0.951≤Rp≤0.975; and 3.15≤RPD≤4.32. The models' prediction stability improved in the order of PLS
Weierstrass Elliptic Function Solutions to Nonlinear Evolution Equations
International Nuclear Information System (INIS)
Yu Jianping; Sun Yongli
2008-01-01
This paper is based on the relations between projection Riccati equations and Weierstrass elliptic equation, combined with the Groebner bases in the symbolic computation. Then the novel method for constructing the Weierstrass elliptic solutions to the nonlinear evolution equations is given by using the above relations
SOLA-VOF: a solution algorithm for transient fluid flow with multiple free boundaries
International Nuclear Information System (INIS)
Nichols, B.D.; Hirt, C.W.; Hotchkiss, R.S.
1980-08-01
In this report a simple, but powerful, computer program is presented for the solution of two-dimensional transient fluid flow with free boundaries. The SOLA-VOF program, which is based on the concept of a fractional volume of fluid (VOF), is more flexible and efficient than other methods for treating arbitrary free boundaries. SOLA-VOF has a variety of user options that provide capabilities for a wide range of applications. Its basic mode of operation is for single fluid calculations having multiple free surfaces. However, SOLA-VOF can also be used for calculations involving two fluids separated by a sharp interface. In either case, the fluids may be treated as incompressible or as having limited compressibility. Surface tension forces with wall adhesion are permitted in both cases. Internal obstacles may be defined by blocking out any desired combination of cells in the mesh, which is composed of rectangular cells of variable size. SOLA-VOF is an easy-to-use program. Its logical parts are isolated in separate subroutines, and numerous special features have been included to simplify its operation, such as an automatic time-step control, a flexible mesh generator, extensive output capabilities, a variety of optional boundary conditions, and instructive internal documentation
International Nuclear Information System (INIS)
Wilde, Juray de; Vierendeels, Jan; Heynderickx, Geraldine J.; Marin, Guy B.
2005-01-01
Simultaneous solution algorithms for Eulerian-Eulerian gas-solid flow models are presented and their stability analyzed. The integration algorithms are based on dual-time stepping with fourth-order Runge-Kutta in pseudo-time. The domain is solved point or plane wise. The discretization of the inviscid terms is based on a low-Mach limit of the multi-phase preconditioned advection upstream splitting method (MP-AUSMP). The numerical stability of the simultaneous solution algorithms is analyzed in 2D with the Fourier method. Stability results are compared with the convergence behaviour of 3D riser simulations. The impact of the grid aspect ratio, preconditioning, artificial dissipation, and the treatment of the source terms is investigated. A particular advantage of the simultaneous solution algorithms is that they allow a fully implicit treatment of the source terms which are of crucial importance for the Eulerian-Eulerian gas-solid flow models and their solution. The numerical stability of the optimal simultaneous solution algorithm is analyzed for different solids volume fractions and gas-solid slip velocities. Furthermore, the effect of the grid resolution on the convergence behaviour and the simulation results is investigated. Finally, simulations of the bottom zone of a pilot-scale riser with a side solids inlet are experimentally validated
An Allometric Algorithm for Fractal-Based Cobb-Douglas Function of Geographical Systems
Directory of Open Access Journals (Sweden)
Hongyu Luo
2014-01-01
Full Text Available The generalized Cobb-Douglas production function has been derived from a general input-output relation based on fractality assumptions. It was proved to be a useful self-affine model for geographical analysis. However, the ordinary least square calculation is always an ineffectual method for the Cobb-Douglas modeling because of the multicollinearity in the logarithmic linear regression. In this paper, a novel approach is proposed to build the geographical Cobb-Douglas models. Combining the concept of allometric scaling with the linear regression technique, we obtain a simple algorithm that can be employed to estimate the parameters of the Cobb-Douglas function. As a case, the algorithm and models are applied to the public transportation of China’s cities, and the results validate the allometric algorithm. A conclusion can be drawn that the allometric analysis is an effective way of modeling geographical systems with the general Cobb-Douglas function. This study is significant for integrating the notions of allometry, fractals, and scaling into a new framework to form a quantitative methodology of spatial analysis.
International Nuclear Information System (INIS)
Zhong, Z.
1985-01-01
A new approach to the solution of certain differential equations, the double complex function method, is developed, combining ordinary complex numbers and hyperbolic complex numbers. This method is applied to the theory of stationary axisymmetric Einstein equations in general relativity. A family of exact double solutions, double transformation groups, and n-soliton double solutions are obtained
International Nuclear Information System (INIS)
Bathke, C.
1978-03-01
A description is presented of a general algorithm for locating the extremum of a multi-dimensional constrained function. The algorithm employs a series of techniques dominated by random shrinkage, steepest descent, and adaptive creeping. A discussion follows of the algorithm's application to a ''real world'' problem, namely the optimization of the price of electricity, P/sub eh/, from a hybrid fusion-fission reactor. Upon the basis of comparisons with other optimization schemes of a survey nature, the algorithm is concluded to yield a good approximation to the location of a function's optimum
Paul, M.; Negahban-Azar, M.
2017-12-01
The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination
Directory of Open Access Journals (Sweden)
Yusuf Pandir
2013-01-01
Full Text Available We firstly give some new functions called generalized hyperbolic functions. By the using of the generalized hyperbolic functions, new kinds of transformations are defined to discover the exact approximate solutions of nonlinear partial differential equations. Based on the generalized hyperbolic function transformation of the generalized KdV equation and the coupled equal width wave equations (CEWE, we find new exact solutions of two equations and analyze the properties of them by taking different parameter values of the generalized hyperbolic functions. We think that these solutions are very important to explain some physical phenomena.
Tables of generalized Airy functions for the asymptotic solution of the differential equation
Nosova, L N
1965-01-01
Tables of Generalized Airy Functions for the Asymptotic Solution of the Differential Equations contains tables of the special functions, namely, the generalized Airy functions, and their first derivatives, for real and pure imaginary values. The tables are useful for calculations on toroidal shells, laminae, rode, and for the solution of certain other problems of mathematical physics. The values of the functions were computed on the ""Strela"" highspeed electronic computer.This book will be of great value to mathematicians, researchers, and students.
Institute of Scientific and Technical Information of China (English)
Wan-sheng WANG; Shou-fu LI; Run-sheng YANG
2012-01-01
A series of contractivity and exponential stability results for the solutions to nonlinear neutral functional differential equations (NFDEs) in Banach spaces are obtained,which provide unified theoretical foundation for the contractivity analysis of solutions to nonlinear problems in functional differential equations (FDEs),neutral delay differential equations (NDDEs) and NFDEs of other types which appear in practice.
Finite-gap solutions of Abelian Toda chain of genus 4 and 5 in elliptic functions
International Nuclear Information System (INIS)
Smirnov, A.O.
1989-01-01
A reduction theorem is formulated and proved. Smooth real solutions of the Abelian Toda chain of genus 4 and 5 are obtained in elliptic functions. Solutions of genus 2g and 2g + 1 of the discrete Peierls-Froehlich model in the absence of intramolecular deformation are constructed in terms of g-dimensional theta functions
Chae, Kum Ju; Goo, Jin Mo; Ahn, Su Yeon; Yoo, Jin Young; Yoon, Soon Ho
2018-01-01
To evaluate the preference of observers for image quality of chest radiography using the deconvolution algorithm of point spread function (PSF) (TRUVIEW ART algorithm, DRTECH Corp.) compared with that of original chest radiography for visualization of anatomic regions of the chest. Prospectively enrolled 50 pairs of posteroanterior chest radiographs collected with standard protocol and with additional TRUVIEW ART algorithm were compared by four chest radiologists. This algorithm corrects scattered signals generated by a scintillator. Readers independently evaluated the visibility of 10 anatomical regions and overall image quality with a 5-point scale of preference. The significance of the differences in reader's preference was tested with a Wilcoxon's signed rank test. All four readers preferred the images applied with the algorithm to those without algorithm for all 10 anatomical regions (mean, 3.6; range, 3.2-4.0; p chest anatomical structures applied with the deconvolution algorithm of PSF was superior to the original chest radiography.
Energy Technology Data Exchange (ETDEWEB)
Fernandes, D.H.; Medeiros, A.R. [Subsea7, Niteroi, RJ (Brazil); Jacob, B.P.; Lima, B.S.L.P.; Albrecht, C.H. [Universidade Federaldo Rio de Janeiro (COPPE/UFRJ), RJ (Brazil). Coordenacao de Programas de Pos-graduacao em Engenharia
2009-07-01
This work presents studies regarding the determination of optimal pipeline routes for offshore applications. The assembly of an objective function is presented; this function can be later associated with Evolutionary Algorithm to implement a computational tool for the automatic determination of the most advantageous pipeline route for a given scenario. This tool may reduce computational overheads, avoid mistakes with route interpretation, and minimize costs with respect to submarine pipeline design and installation. The following aspects can be considered in the assembly of the objective function: Geophysical and geotechnical data obtained from the bathymetry and sonography; the influence of the installation method, total pipeline length and number of free spans to be mitigated along the routes as well as vessel time for both cases. Case studies are presented to illustrate the use of the proposed objective function, including a sensitivity analysis intended to identify the relative influence of selected parameters in the evaluation of different routes. (author)
A Particle Swarm Optimization Algorithm with Variable Random Functions and Mutation
Institute of Scientific and Technical Information of China (English)
ZHOU Xiao-Jun; YANG Chun-Hua; GUI Wei-Hua; DONG Tian-Xue
2014-01-01
The convergence analysis of the standard particle swarm optimization (PSO) has shown that the changing of random functions, personal best and group best has the potential to improve the performance of the PSO. In this paper, a novel strategy with variable random functions and polynomial mutation is introduced into the PSO, which is called particle swarm optimization algorithm with variable random functions and mutation (PSO-RM). Random functions are adjusted with the density of the population so as to manipulate the weight of cognition part and social part. Mutation is executed on both personal best particle and group best particle to explore new areas. Experiment results have demonstrated the effectiveness of the strategy.
Vector Green's function algorithm for radiative transfer in plane-parallel atmosphere
Energy Technology Data Exchange (ETDEWEB)
Qin Yi [School of Physics, University of New South Wales (Australia)]. E-mail: yi.qin@csiro.au; Box, Michael A. [School of Physics, University of New South Wales (Australia)
2006-01-15
Green's function is a widely used approach for boundary value problems. In problems related to radiative transfer, Green's function has been found to be useful in land, ocean and atmosphere remote sensing. It is also a key element in higher order perturbation theory. This paper presents an explicit expression of the Green's function, in terms of the source and radiation field variables, for a plane-parallel atmosphere with either vacuum boundaries or a reflecting (BRDF) surface. Full polarization state is considered but the algorithm has been developed in such way that it can be easily reduced to solve scalar radiative transfer problems, which makes it possible to implement a single set of code for computing both the scalar and the vector Green's function.
Vector Green's function algorithm for radiative transfer in plane-parallel atmosphere
International Nuclear Information System (INIS)
Qin Yi; Box, Michael A.
2006-01-01
Green's function is a widely used approach for boundary value problems. In problems related to radiative transfer, Green's function has been found to be useful in land, ocean and atmosphere remote sensing. It is also a key element in higher order perturbation theory. This paper presents an explicit expression of the Green's function, in terms of the source and radiation field variables, for a plane-parallel atmosphere with either vacuum boundaries or a reflecting (BRDF) surface. Full polarization state is considered but the algorithm has been developed in such way that it can be easily reduced to solve scalar radiative transfer problems, which makes it possible to implement a single set of code for computing both the scalar and the vector Green's function
Directory of Open Access Journals (Sweden)
Huaiqing Zhang
2014-01-01
Full Text Available The spectral leakage has a harmful effect on the accuracy of harmonic analysis for asynchronous sampling. This paper proposed a time quasi-synchronous sampling algorithm which is based on radial basis function (RBF interpolation. Firstly, a fundamental period is evaluated by a zero-crossing technique with fourth-order Newton’s interpolation, and then, the sampling sequence is reproduced by the RBF interpolation. Finally, the harmonic parameters can be calculated by FFT on the synchronization of sampling data. Simulation results showed that the proposed algorithm has high accuracy in measuring distorted and noisy signals. Compared to the local approximation schemes as linear, quadric, and fourth-order Newton interpolations, the RBF is a global approximation method which can acquire more accurate results while the time-consuming is about the same as Newton’s.
International Nuclear Information System (INIS)
Park, H.; De Oliveira, C. R. E.
2007-01-01
This paper describes the verification of the recently developed space-angle self-adaptive algorithm for the finite element-spherical harmonics method via the Method of Manufactured Solutions. This method provides a simple, yet robust way for verifying the theoretical properties of the adaptive algorithm and interfaces very well with the underlying second-order, even-parity transport formulation. Simple analytic solutions in both spatial and angular variables are manufactured to assess the theoretical performance of the a posteriori error estimates. The numerical results confirm reliability of the developed space-angle error indicators. (authors)
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Directory of Open Access Journals (Sweden)
Ruzzo Walter L
2006-03-01
Full Text Available Abstract Background As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. Methods In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. Results We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly. Conclusion Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.
Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng
2015-01-01
The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.
COULCC: A continued-fraction algorithm for Coulomb functions of complex order with complex arguments
International Nuclear Information System (INIS)
Thompson, I.J.; Barnett, A.R.
1985-01-01
The routine COULCC calculates both the oscillating and the exponentially varying Coulomb wave functions, and their radial derivations, for complex eta(Sommerfeld parameter), complex energies and complex angular momenta. The functions for uncharged scattering (spherical Bessels) and cylindrical Bessel functions are special cases which are more easily solved. Two linearly independent solutions are found, in general, to the differential equation f''(x)+g(x)f(x)=0, where g(x) has x 0 , x -1 and x -2 terms, with coefficients 1, -2eta and -lambda(lambda+1), respectively. (orig.)
Approximation solutions for indifference pricing under general utility functions
Chen, An; Pelsser, Antoon; Vellekoop, M.H.
2008-01-01
With the aid of Taylor-based approximations, this paper presents results for pricing insurance contracts by using indifference pricing under general utility functions. We discuss the connection between the resulting "theoretical" indifference prices and the pricing rule-of-thumb that practitioners
Approximate Solutions for Indifference Pricing under General Utility Functions
Chen, A.; Pelsser, A.; Vellekoop, M.
2007-01-01
With the aid of Taylor-based approximations, this paper presents results for pricing insurance contracts by using indifference pricing under general utility functions. We discuss the connection between the resulting "theoretical" indifference prices and the pricing rule-of-thumb that practitioners
Some functional solutions of the Yang-Baxter equation
International Nuclear Information System (INIS)
Stoyanov, D.Ts.
1994-09-01
A general functional definition of the infinite dimensional quantum R-matrix satisfying the Yang-Baxter equation is given. A procedure for extracting a finite dimensional R-matrix from the general definition is demonstrated in a particular case when the group SU(2) takes place. (author). 6 refs
Efficient fractal-based mutation in evolutionary algorithms from iterated function systems
Salcedo-Sanz, S.; Aybar-Ruíz, A.; Camacho-Gómez, C.; Pereira, E.
2018-03-01
In this paper we present a new mutation procedure for Evolutionary Programming (EP) approaches, based on Iterated Function Systems (IFSs). The new mutation procedure proposed consists of considering a set of IFS which are able to generate fractal structures in a two-dimensional phase space, and use them to modify a current individual of the EP algorithm, instead of using random numbers from different probability density functions. We test this new proposal in a set of benchmark functions for continuous optimization problems. In this case, we compare the proposed mutation against classical Evolutionary Programming approaches, with mutations based on Gaussian, Cauchy and chaotic maps. We also include a discussion on the IFS-based mutation in a real application of Tuned Mass Dumper (TMD) location and optimization for vibration cancellation in buildings. In both practical cases, the proposed EP with the IFS-based mutation obtained extremely competitive results compared to alternative classical mutation operators.
Solution of the Doppler broadening function based on the fourier cosine transform
Energy Technology Data Exchange (ETDEWEB)
Goncalves, Alessandro da C [COPPE/UFRJ - Programa de Engenharia Nuclear, Universidade Federal do Rio de Janeiro, P.O. Box 68509, 21941-914 Rio de Janeiro, RJ (Brazil)], E-mail: agoncalves@con.ufrj.br; Martinez, Aquilino S.; Silva, Fernando C. da [COPPE/UFRJ - Programa de Engenharia Nuclear, Universidade Federal do Rio de Janeiro, P.O. Box 68509, 21941-914 Rio de Janeiro, RJ (Brazil)
2008-10-15
This paper provides a new integral representation for the Doppler broadening function {psi}({xi}, x), which is interpreted as being a Fourier cosine transform. This integral form allows the obtaining of an analytical solution in a simple and accurate functional manner as regards the elementary functions. The solution obtained through the new integral representation can be widely used in several applications such as the calculation of self-shielding factors and measurement corrections for the microscopic cross section through the activation technique.
Solution of the Doppler broadening function based on the fourier cosine transform
International Nuclear Information System (INIS)
Goncalves, Alessandro da C; Martinez, Aquilino S.; Silva, Fernando C. da
2008-01-01
This paper provides a new integral representation for the Doppler broadening function ψ(ξ, x), which is interpreted as being a Fourier cosine transform. This integral form allows the obtaining of an analytical solution in a simple and accurate functional manner as regards the elementary functions. The solution obtained through the new integral representation can be widely used in several applications such as the calculation of self-shielding factors and measurement corrections for the microscopic cross section through the activation technique
The relation among the hyperbolic-function-type exact solutions of nonlinear evolution equations
International Nuclear Information System (INIS)
Liu Chunping; Liu Xiaoping
2004-01-01
First, we investigate the solitary wave solutions of the Burgers equation and the KdV equation, which are obtained by using the hyperbolic function method. Then we present a theorem which will not only give us a clear relation among the hyperbolic-function-type exact solutions of nonlinear evolution equations, but also provide us an approach to construct new exact solutions in complex scalar field. Finally, we apply the theorem to the KdV-Burgers equation and obtain its new exact solutions
Soft functions for generic jet algorithms and observables at hadron colliders
Energy Technology Data Exchange (ETDEWEB)
Bertolini, Daniele [Lawrence Berkeley National Laboratory, Berkeley, CA (United States). Theoretical Physics Group; California Univ., Berkeley, CA (United States). Berkeley Center for Theoretical Physics; Kolodrubetz, Daniel; Stewart, Iain W. [Massachusetts Institute of Technology, Cambridge, MA (United States). Center for Theoretical Physics; Duff, Neill [Los Alamos National Laboratory, NM (United States). Theoretical Div.; Massachusetts Institute of Technology, Cambridge, MA (United States). Center for Theoretical Physics; Pietrulewicz, Piotr; Tackmann, Frank J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Theory Group; Waalewijn, Wouter J. [NIKHEF, Amsterdam (Netherlands). Theory Group; Amsterdam Univ. (Netherlands). Inst. for Theoretical Physics Amsterdam and Delta Inst. for Theoretical Physics
2017-07-15
We introduce a method to compute one-loop soft functions for exclusive N-jet processes at hadron colliders, allowing for different definitions of the algorithm that determines the jet regions and of the measurements in those regions. In particular, we generalize the N-jettiness hemisphere decomposition of T. T. Joutennus et al. (2011) in a manner that separates the dependence on the jet boundary from the observables measured inside the jet and beam regions. Results are given for several factorizable jet definitions, including anti-k{sub T}, XCone, and other geometric partitionings. We calculate explicitly the soft functions for angularity measurements, including jet mass and jet broadening, in pp→L+1 jet and explore the differences for various jet vetoes and algorithms. This includes a consistent treatment of rapidity divergences when applicable. We also compute analytic results for these soft functions in an expansion for a small jet radius R. We find that the small-R results, including corrections up to O(R{sup 2}), accurately capture the full behavior over a large range of R.
INNOVATIVE TECHNOLOGICAL SOLUTIONS IN CREATING FUNCTIONAL PRODUCTS POWER
I. V. Sergienko; A. E. Kutsova; S. V. Kutsov
2015-01-01
The article deals with a problem of functional products creation for consumers feeling need in proteins, irreplaceable amino acids, vitamins, mineral substances, food fibers, polynonsaturated fat acids. One of the possible ways to improve human nutrition is using non-traditional cultures for bread making technology containing significant amounts of fibrous substances, easily digestible protein, vitamins, unsaturated fatty acids and minerals. Taking into account the Nutrition Science requireme...
International Nuclear Information System (INIS)
Faulin, Javier; Juan, Angel A.; Serrat, Carles; Bargueno, Vicente
2008-01-01
In this paper, we propose the use of discrete-event simulation (DES) as an efficient methodology to obtain estimates of both survival and availability functions in time-dependent real systems-such as telecommunication networks or distributed computer systems. We discuss the use of DES in reliability and availability studies, not only as an alternative to the use of analytical and probabilistic methods, but also as a complementary way to: (i) achieve a better understanding of the system internal behavior and (ii) find out the relevance of each component under reliability/availability considerations. Specifically, this paper describes a general methodology and two DES algorithms, called SAEDES, which can be used to analyze a wide range of time-dependent complex systems, including those presenting multiple states, dependencies among failure/repair times or non-perfect maintenance policies. These algorithms can provide valuable information, specially during the design stages, where different scenarios can be compared in order to select a system design offering adequate reliability and availability levels. Two case studies are discussed, using a C/C++ implementation of the SAEDES algorithms, to show some potential applications of our approach
Energy Technology Data Exchange (ETDEWEB)
Faulin, Javier [Department of Statistics and Operations Research, Los Magnolios Building, First Floor, Campus Arrosadia, Public University of Navarre, 31006 Pamplona, Navarre (Spain)], E-mail: javier.faulin@unavarra.es; Juan, Angel A. [Department of Applied Mathematics I, Av. Doctor Maranon 44-50, Technical University of Catalonia, 08028 Barcelona (Spain)], E-mail: angel.alejandro.juan@upc.edu; Serrat, Carles [Department of Applied Mathematics I, Av. Doctor Maranon 44-50, Technical University of Catalonia, 08028 Barcelona (Spain)], E-mail: carles.serrat@upc.edu; Bargueno, Vicente [Department of Applied Mathematics I, ETS Ingenieros Industriales, Universidad Nacional de Educacion a Distancia, 28080 Madrid (Spain)], E-mail: vbargueno@ind.uned.es
2008-11-15
In this paper, we propose the use of discrete-event simulation (DES) as an efficient methodology to obtain estimates of both survival and availability functions in time-dependent real systems-such as telecommunication networks or distributed computer systems. We discuss the use of DES in reliability and availability studies, not only as an alternative to the use of analytical and probabilistic methods, but also as a complementary way to: (i) achieve a better understanding of the system internal behavior and (ii) find out the relevance of each component under reliability/availability considerations. Specifically, this paper describes a general methodology and two DES algorithms, called SAEDES, which can be used to analyze a wide range of time-dependent complex systems, including those presenting multiple states, dependencies among failure/repair times or non-perfect maintenance policies. These algorithms can provide valuable information, specially during the design stages, where different scenarios can be compared in order to select a system design offering adequate reliability and availability levels. Two case studies are discussed, using a C/C++ implementation of the SAEDES algorithms, to show some potential applications of our approach.
Kiguchi, Masashi; Funane, Tsukasa
2014-11-01
A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.
Zheng, H. W.; Shu, C.; Chew, Y. T.
2008-07-01
In this paper, an object-oriented and quadrilateral-mesh based solution adaptive algorithm for the simulation of compressible multi-fluid flows is presented. The HLLC scheme (Harten, Lax and van Leer approximate Riemann solver with the Contact wave restored) is extended to adaptively solve the compressible multi-fluid flows under complex geometry on unstructured mesh. It is also extended to the second-order of accuracy by using MUSCL extrapolation. The node, edge and cell are arranged in such an object-oriented manner that each of them inherits from a basic object. A home-made double link list is designed to manage these objects so that the inserting of new objects and removing of the existing objects (nodes, edges and cells) are independent of the number of objects and only of the complexity of O( 1). In addition, the cells with different levels are further stored in different lists. This avoids the recursive calculation of solution of mother (non-leaf) cells. Thus, high efficiency is obtained due to these features. Besides, as compared to other cell-edge adaptive methods, the separation of nodes would reduce the memory requirement of redundant nodes, especially in the cases where the level number is large or the space dimension is three. Five two-dimensional examples are used to examine its performance. These examples include vortex evolution problem, interface only problem under structured mesh and unstructured mesh, bubble explosion under the water, bubble-shock interaction, and shock-interface interaction inside the cylindrical vessel. Numerical results indicate that there is no oscillation of pressure and velocity across the interface and it is feasible to apply it to solve compressible multi-fluid flows with large density ratio (1000) and strong shock wave (the pressure ratio is 10,000) interaction with the interface.
Liu, Z.; Kar, J.; Zeng, S.; Tackett, J. L.; Vaughan, M.; Trepte, C. R.; Omar, A. H.; Hu, Y.; Winker, D. M.
2017-12-01
In the CALIPSO retrieval algorithm, detection layers in the lidar measurements is followed by their classification as a "cloud" or "aerosol" using 5-dimensional probability density functions (PDFs). The five dimensions are the mean attenuated backscatter at 532 nm, the layer integrated total attenuated color ratio, the mid-layer altitude, integrated volume depolarization ratio and latitude. The new version 4 (V4) level 2 (L2) data products, released in November 2016, are the first major revision to the L2 product suite since May 2010. Significant calibration changes in the V4 level 1 data necessitated substantial revisions to the V4 L2 CAD algorithm. Accordingly, a new set of PDFs was generated to derive the V4 L2 data products. The V4 CAD algorithm is now applied to layers detected in the stratosphere, where volcanic layers and occasional cloud and smoke layers are observed. Previously, these layers were designated as `stratospheric', and not further classified. The V4 CAD algorithm is also applied to all layers detected at single shot (333 m) resolution. In prior data releases, single shot detections were uniformly classified as clouds. The CAD PDFs used in the earlier releases were generated using a full year (2008) of CALIPSO measurements. Because the CAD algorithm was not applied to stratospheric features, the properties of these layers were not incorporated into the PDFs. When building the V4 PDFs, the 2008 data were augmented with additional data from June 2011, and all stratospheric features were included. The Nabro and Puyehue-Cordon volcanos erupted in June 2011, and volcanic aerosol layers were observed in the upper troposphere and lower stratosphere in both the northern and southern hemispheres. The June 2011 data thus provides the stratospheric aerosol properties needed for comprehensive PDF generation. In contrast to earlier versions of the PDFs, which were generated based solely on observed distributions, construction of the V4 PDFs considered the
An compression algorithm for medical images and a display with the decoding function
International Nuclear Information System (INIS)
Gotoh, Toshiyuki; Nakagawa, Yukihiro; Shiohara, Morito; Yoshida, Masumi
1990-01-01
This paper describes and efficient image compression method for medical images, a high-speed display with the decoding function. In our method, an input image is divided into blocks, and either of Discrete Cosine Transform coding (DCT) or Block Truncation Coding (BTC) is adaptively applied on each block to improve image quality. The display, we developed, receives the compressed data from the host computer and reconstruct images of good quality at high speed using four decoding microprocessors on which our algorithm is implemented in pipeline. By the experiments, our method and display were verified to be effective. (author)
Progressive geometric algorithms
Alewijnse, S.P.A.; Bagautdinov, T.M.; de Berg, M.T.; Bouts, Q.W.; ten Brink, Alex P.; Buchin, K.A.; Westenberg, M.A.
2015-01-01
Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms
Progressive geometric algorithms
Alewijnse, S.P.A.; Bagautdinov, T.M.; Berg, de M.T.; Bouts, Q.W.; Brink, ten A.P.; Buchin, K.; Westenberg, M.A.
2014-01-01
Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms
INNOVATIVE TECHNOLOGICAL SOLUTIONS IN CREATING FUNCTIONAL PRODUCTS POWER
Directory of Open Access Journals (Sweden)
I. V. Sergienko
2015-01-01
Full Text Available The article deals with a problem of functional products creation for consumers feeling need in proteins, irreplaceable amino acids, vitamins, mineral substances, food fibers, polynonsaturated fat acids. One of the possible ways to improve human nutrition is using non-traditional cultures for bread making technology containing significant amounts of fibrous substances, easily digestible protein, vitamins, unsaturated fatty acids and minerals. Taking into account the Nutrition Science requirements an expediency of the most full functional ingredients complex entering into bakery products prescription structure is proved. Replacement of the first grade wheat flour by the offered prescription composition allows to slow down a bread aging, to increase periods of products storage and to improve their physical and chemical indicators on the specific volume and porosity. The bakery products "Svyatogor" at the use of 100 g of a product allow to cover daily need in protein for 38,9%, in carbohydrates – for 3,4%, fat – for 9,2%. The power value of "Svyatogor" is 897 kJ, in control 959. Biological value, % 82,7 against 53,1 in control. Thanks to it the digestibility of bread protein (in vitro method of “Svyatogor” is higher. Thanks to unique properties of the compounding components “Svyatogor” gets functional properties by full-fledged protein increasing and its best comprehensibility (in vitro, advanced structure according to the content of vitamins, mineral substances, their balanced structure and can be recommended for mass consumption and prevention of osteoporosis, atherosclerosis, anemia, for children food, pregnant women and the feeding women.
Directory of Open Access Journals (Sweden)
Sara Nakhjirkan
2017-09-01
in green supply chain. Vehicle routing between distribution centres and customers has been considered in the model. Establishment place of distribution centres among potential places is determined by the model. The distributors use continuous review policy (r, Q to control the inventory. The proposed model object is to find an optimal supply chain with minimum costs. To validate the proposed model and measure its compliance with real world problems, GAMS IDE/Cplex has been used. In order to measure the efficiency of the proposed model in large scale problems, a genetic algorithm has been used. The results confirm the efficiency of the proposed model as a practical tool for decision makers to solve location-inventory-routing problems in green supply chain. The proposed GA could reduce the solving time by 85% while reaching on the average 97% of optimal solution compared with exact method.
International Nuclear Information System (INIS)
Warsa, J. S.; Morel, J. E.
2007-01-01
Angular discretizations of the S N transport equation in curvilinear coordinate systems may result in a streaming-plus-removal operator that is dense in the angular variable or that is not lower-triangular. We investigate numerical solution algorithms for such angular discretizations using relationships given by Chandrasekhar to compute the angular derivatives in the one-dimensional S N transport equation in spherical coordinates with Gauss quadrature. This discretization makes the S N transport equation P N-1 - equivalent, but it also makes the sweep operator dense at every spatial point because the N angular derivatives are expressed in terms of the N angular fluxes. To avoid having to invert the sweep operator directly, we must work with the angular fluxes to solve the equations iteratively. We show how we can use approximations to the sweep operator to precondition the full P N-1 equivalent S N equations. We show that these pre-conditioners affect the operator enough such that convergence of a Krylov iterative method improves. (authors)
Rusyaman, E.; Parmikanti, K.; Chaerani, D.; Asefan; Irianingsih, I.
2018-03-01
One of the application of fractional ordinary differential equation is related to the viscoelasticity, i.e., a correlation between the viscosity of fluids and the elasticity of solids. If the solution function develops into function with two or more variables, then its differential equation must be changed into fractional partial differential equation. As the preliminary study for two variables viscoelasticity problem, this paper discusses about convergence analysis of function sequence which is the solution of the homogenous fractional partial differential equation. The method used to solve the problem is Homotopy Analysis Method. The results show that if given two real number sequences (αn) and (βn) which converge to α and β respectively, then the solution function sequences of fractional partial differential equation with order (αn, βn) will also converge to the solution function of fractional partial differential equation with order (α, β).
Opposition-Based Adaptive Fireworks Algorithm
Directory of Open Access Journals (Sweden)
Chibing Gong
2016-07-01
Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.
Numerical solution of Euler's equation by perturbed functionals
Dey, S. K.
1985-01-01
A perturbed functional iteration has been developed to solve nonlinear systems. It adds at each iteration level, unique perturbation parameters to nonlinear Gauss-Seidel iterates which enhances its convergence properties. As convergence is approached these parameters are damped out. Local linearization along the diagonal has been used to compute these parameters. The method requires no computation of Jacobian or factorization of matrices. Analysis of convergence depends on properties of certain contraction-type mappings, known as D-mappings. In this article, application of this method to solve an implicit finite difference approximation of Euler's equation is studied. Some representative results for the well known shock tube problem and compressible flows in a nozzle are given.
Global convergence of periodic solution of neural networks with discontinuous activation functions
International Nuclear Information System (INIS)
Huang Lihong; Guo Zhenyuan
2009-01-01
In this paper, without assuming boundedness and monotonicity of the activation functions, we establish some sufficient conditions ensuring the existence and global asymptotic stability of periodic solution of neural networks with discontinuous activation functions by using the Yoshizawa-like theorem and constructing proper Lyapunov function. The obtained results improve and extend previous works.
Classical Solutions of Path-Dependent PDEs and Functional Forward-Backward Stochastic Systems
Directory of Open Access Journals (Sweden)
Shaolin Ji
2013-01-01
Full Text Available In this paper we study the relationship between functional forward-backward stochastic systems and path-dependent PDEs. In the framework of functional Itô calculus, we introduce a path-dependent PDE and prove that its solution is uniquely determined by a functional forward-backward stochastic system.
Density functional theory and evolution algorithm calculations of elastic properties of AlON
Energy Technology Data Exchange (ETDEWEB)
Batyrev, I. G.; Taylor, D. E.; Gazonas, G. A.; McCauley, J. W. [U.S. Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005 (United States)
2014-01-14
Different models for aluminum oxynitride (AlON) were calculated using density functional theory and optimized using an evolutionary algorithm. Evolutionary algorithm and density functional theory (DFT) calculations starting from several models of AlON with different Al or O vacancy locations and different positions for the N atoms relative to the vacancy were carried out. The results show that the constant anion model [McCauley et al., J. Eur. Ceram. Soc. 29(2), 223 (2009)] with a random distribution of N atoms not adjacent to the Al vacancy has the lowest energy configuration. The lowest energy structure is in a reasonable agreement with experimental X-ray diffraction spectra. The optimized structure of a 55 atom unit cell was used to construct 220 and 440 atom models for simulation cells using DFT with a Gaussian basis set. Cubic elastic constant predictions were found to approach the experimentally determined AlON single crystal elastic constants as the model size increased from 55 to 440 atoms. The pressure dependence of the elastic constants found from simulated stress-strain relations were in overall agreement with experimental measurements of polycrystalline and single crystal AlON. Calculated IR intensity and Raman spectra are compared with available experimental data.
O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin
2017-12-06
Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.
International Nuclear Information System (INIS)
Frink, L.J.D.; Salinger, A.G.
2000-01-01
Fluids adsorbed near surfaces, near macromolecules, and in porous materials are inhomogeneous, exhibiting spatially varying density distributions. This inhomogeneity in the fluid plays an important role in controlling a wide variety of complex physical phenomena including wetting, self-assembly, corrosion, and molecular recognition. One of the key methods for studying the properties of inhomogeneous fluids in simple geometries has been density functional theory (DFT). However, there has been a conspicuous lack of calculations in complex two- and three-dimensional geometries. The computational difficulty arises from the need to perform nested integrals that are due to nonlocal terms in the free energy functional. These integral equations are expensive both in evaluation time and in memory requirements; however, the expense can be mitigated by intelligent algorithms and the use of parallel computers. This paper details the efforts to develop efficient numerical algorithms so that nonlocal DFT calculations in complex geometries that require two or three dimensions can be performed. The success of this implementation will enable the study of solvation effects at heterogeneous surfaces, in zeolites, in solvated (bio)polymers, and in colloidal suspensions
A new algorithm to compute conjectured supply function equilibrium in electricity markets
International Nuclear Information System (INIS)
Diaz, Cristian A.; Villar, Jose; Campos, Fco Alberto; Rodriguez, M. Angel
2011-01-01
Several types of market equilibria approaches, such as Cournot, Conjectural Variation (CVE), Supply Function (SFE) or Conjectured Supply Function (CSFE) have been used to model electricity markets for the medium and long term. Among them, CSFE has been proposed as a generalization of the classic Cournot. It computes the equilibrium considering the reaction of the competitors against changes in their strategy, combining several characteristics of both CVE and SFE. Unlike linear SFE approaches, strategies are linearized only at the equilibrium point, using their first-order Taylor approximation. But to solve CSFE, the slope or the intercept of the linear approximations must be given, which has been proved to be very restrictive. This paper proposes a new algorithm to compute CSFE. Unlike previous approaches, the main contribution is that the competitors' strategies for each generator are initially unknown (both slope and intercept) and endogenously computed by this new iterative algorithm. To show the applicability of the proposed approach, it has been applied to several case examples where its qualitative behavior has been analyzed in detail. (author)
The fractional coupled KdV equations: Exact solutions and white noise functional approach
International Nuclear Information System (INIS)
Ghany, Hossam A.; El Bab, A. S. Okb; Zabel, A. M.; Hyder, Abd-Allah
2013-01-01
Variable coefficients and Wick-type stochastic fractional coupled KdV equations are investigated. By using the modified fractional sub-equation method, Hermite transform, and white noise theory the exact travelling wave solutions and white noise functional solutions are obtained, including the generalized exponential, hyperbolic, and trigonometric types. (general)
Nonlinear differential equations with exact solutions expressed via the Weierstrass function
Kudryashov, NA
2004-01-01
A new problem is studied, that is to find nonlinear differential equations with special solutions expressed via the Weierstrass function. A method is discussed to construct nonlinear ordinary differential equations with exact solutions. The main step of our method is the assumption that nonlinear
Explicit appropriate basis function method for numerical solution of stiff systems
International Nuclear Information System (INIS)
Chen, Wenzhen; Xiao, Hongguang; Li, Haofeng; Chen, Ling
2015-01-01
Highlights: • An explicit numerical method called the appropriate basis function method is presented. • The method differs from the power series method for obtaining approximate numerical solutions. • Two cases show the method is fit for linear and nonlinear stiff systems. • The method is very simple and effective for most of differential equation systems. - Abstract: In this paper, an explicit numerical method, called the appropriate basis function method, is presented. The explicit appropriate basis function method differs from the power series method because it employs an appropriate basis function such as the exponential function, or periodic function, other than a polynomial, to obtain approximate numerical solutions. The method is successful and effective for the numerical solution of the first order ordinary differential equations. Two examples are presented to show the ability of the method for dealing with linear and nonlinear systems of differential equations
Covariant two-particle wave functions for model quasipotentials admitting exact solutions
International Nuclear Information System (INIS)
Kapshaj, V.N.; Skachkov, N.B.
1983-01-01
Two formulations of quasipotential equations in the relativistic configurational representation are considered for the wave function of the internal motion of the bound system of two relativistic particles. Exact solutions of these equations are found for some model quasipotentials
Covariant two-particle wave functions for model quasipotential allowing exact solutions
International Nuclear Information System (INIS)
Kapshaj, V.N.; Skachkov, N.B.
1982-01-01
Two formulations of quasipotential equations in the relativistic configurational representation are considered for the wave function of relative motion of a bound state of two relativistic particles. Exact solutions of these equations are found for some model quasipotentials
OSCILLATION BEHAVIOR OF SOLUTIONS FOR EVEN ORDER NEUTRAL FUNCTIONAL DIFFERENTIAL EQUATIONS
Institute of Scientific and Technical Information of China (English)
T.Candan
2006-01-01
Even order neutral functional differential equations are considered. Sufficient conditions for the oscillation behavior of solutions for this differential equation are presented. The new results are presented and some examples are also given.
TWIN POSITIVE PERIODIC SOLUTIONS OF FUNCTIONAL DIFFERENTIAL EQUATIONS WITH INFINITE DELAY
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In this paper, the author studies a class of nonlinear functional differential equation. By using a fixed point theorem in cones, sufficient conditions are established for the existence of twin positive periodic solutions.
Directory of Open Access Journals (Sweden)
Dhakne Machindra B.
2017-04-01
Full Text Available In this paper we discuss the existence of mild and strong solutions of abstract nonlinear mixed functional integrodifferential equation with nonlocal condition by using Sadovskii’s fixed point theorem and theory of fractional power of operators.
Exact Travelling Solutions of Discrete sine-Gordon Equation via Extended Tanh-Function Approach
International Nuclear Information System (INIS)
Dai Chaoqing; Zhang Jiefang
2006-01-01
In this paper, we generalize the extended tanh-function approach, which was used to find new exact travelling wave solutions of nonlinear partial differential equations or coupled nonlinear partial differential equations, to nonlinear differential-difference equations. As illustration, two series of exact travelling wave solutions of the discrete sine-Gordon equation are obtained by means of the extended tanh-function approach.
DEFF Research Database (Denmark)
Andersen, Kurt Munk; Sandqvist, Allan
1997-01-01
We investigate the domain of definition and the domain of values for the successor function of a cooperative differential system x'=f(t,x), where the coordinate functions are concave in x for any fixed value of t. Moreover, we give a characterization of a weakly Pareto optimal solution.......We investigate the domain of definition and the domain of values for the successor function of a cooperative differential system x'=f(t,x), where the coordinate functions are concave in x for any fixed value of t. Moreover, we give a characterization of a weakly Pareto optimal solution....
Special function solutions of a spectral problem for a nonlinear quantum oscillator
International Nuclear Information System (INIS)
Schulze-Halberg, A; Morris, J R
2012-01-01
We construct exact solutions of a spectral problem involving the Schrödinger equation for a nonlinear, one-parameter oscillator potential. In contrast to a previous analysis of the problem (Carinena et al 2007 Ann. Phys. 322 434–59), where solutions were given through a Rodrigues-type formula, our approach leads to closed-form representations of the solutions in terms of special functions, not containing any derivative operators. We show normalizability and orthogonality of our solutions, as well as correct reduction of the problem to the harmonic oscillator model, if the parameter in the potential gets close to zero. (paper)
Shojaeefard, Mohammad Hassan; Khalkhali, Abolfazl; Faghihian, Hamed; Dahmardeh, Masoud
2018-03-01
Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.
DEFF Research Database (Denmark)
Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter
2004-01-01
An efficient higher-order method of moments (MoM) solution of volume integral equations is presented. The higher-order MoM solution is based on higher-order hierarchical Legendre basis functions and higher-order geometry modeling. An unstructured mesh composed of 8-node trilinear and/or curved 27...... of magnitude in comparison to existing higher-order hierarchical basis functions. Consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement with the analytical Mie series solution for a dielectric sphere as well as with results obtained...
Directory of Open Access Journals (Sweden)
Elmira Ashpazzadeh
2018-04-01
Full Text Available A numerical technique based on the Hermite interpolant multiscaling functions is presented for the solution of Convection-diusion equations. The operational matrices of derivative, integration and product are presented for multiscaling functions and are utilized to reduce the solution of linear Convection-diusion equation to the solution of algebraic equations. Because of sparsity of these matrices, this method is computationally very attractive and reduces the CPU time and computer memory. Illustrative examples are included to demonstrate the validity and applicability of the new technique.
Ghaedi, M; Zeinali, N; Ghaedi, A M; Teimuori, M; Tashkhourian, J
2014-05-05
In this study, graphite oxide (GO) nano according to Hummers method was synthesized and subsequently was used for the removal of methylene blue (MB) and brilliant green (BG). The detail information about the structure and physicochemical properties of GO are investigated by different techniques such as XRD and FTIR analysis. The influence of solution pH, initial dye concentration, contact time and adsorbent dosage was examined in batch mode and optimum conditions was set as pH=7.0, 2 mg of GO and 10 min contact time. Employment of equilibrium isotherm models for description of adsorption capacities of GO explore the good efficiency of Langmuir model for the best presentation of experimental data with maximum adsorption capacity of 476.19 and 416.67 for MB and BG dyes in single solution. The analysis of adsorption rate at various stirring times shows that both dyes adsorption followed a pseudo second-order kinetic model with cooperation with interparticle diffusion model. Subsequently, the adsorption data as new combination of artificial neural network was modeled to evaluate and obtain the real conditions for fast and efficient removal of dyes. A three-layer artificial neural network (ANN) model is applicable for accurate prediction of dyes removal percentage from aqueous solution by GO following conduction of 336 experimental data. The network was trained using the obtained experimental data at optimum pH with different GO amount (0.002-0.008 g) and 5-40 mg/L of both dyes over contact time of 0.5-30 min. The ANN model was able to predict the removal efficiency with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) at hidden layer with 10 and 11 neurons for MB and BG dyes, respectively. The minimum mean squared error (MSE) of 0.0012 and coefficient of determination (R(2)) of 0.982 were found for prediction and modeling of MB removal, while the respective value for BG was the
International Nuclear Information System (INIS)
Ji Zhilong; Ma Yuanwei; Wang Dezhong
2014-01-01
Background: In radioactive nuclides atmospheric diffusion models, the empirical dispersion coefficients were deduced under certain experiment conditions, whose difference with nuclear accident conditions is a source of deviation. A better estimation of the radioactive nuclide's actual dispersion process could be done by correcting dispersion coefficients with observation data, and Genetic Algorithm (GA) is an appropriate method for this correction procedure. Purpose: This study is to analyze the fitness functions' influence on the correction procedure and the forecast ability of diffusion model. Methods: GA, coupled with Lagrange dispersion model, was used in a numerical simulation to compare 4 fitness functions' impact on the correction result. Results: In the numerical simulation, the fitness function with observation deviation taken into consideration stands out when significant deviation exists in the observed data. After performing the correction procedure on the Kincaid experiment data, a significant boost was observed in the diffusion model's forecast ability. Conclusion: As the result shows, in order to improve dispersion models' forecast ability using GA, observation data should be given different weight in the fitness function corresponding to their error. (authors)
International Nuclear Information System (INIS)
Snyder, Abigail C.; Jiao, Yu
2010-01-01
Neutron experiments at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) frequently generate large amounts of data (on the order of 106-1012 data points). Hence, traditional data analysis tools run on a single CPU take too long to be practical and scientists are unable to efficiently analyze all data generated by experiments. Our goal is to develop a scalable algorithm to efficiently compute high-dimensional integrals of arbitrary functions. This algorithm can then be used to integrate the four-dimensional integrals that arise as part of modeling intensity from the experiments at the SNS. Here, three different one-dimensional numerical integration solvers from the GNU Scientific Library were modified and implemented to solve four-dimensional integrals. The results of these solvers on a final integrand provided by scientists at the SNS can be compared to the results of other methods, such as quasi-Monte Carlo methods, computing the same integral. A parallelized version of the most efficient method can allow scientists the opportunity to more effectively analyze all experimental data.
Morphology Development in Solution-Processed Functional Organic Blend Films: An In Situ Viewpoint.
Richter, Lee J; DeLongchamp, Dean M; Amassian, Aram
2017-05-10
Solution-processed organic films are a facile route to high-speed, low cost, large-area deposition of electrically functional components (transistors, solar cells, emitters, etc.) that can enable a diversity of emerging technologies, from Industry 4.0, to the Internet of things, to point-of-use heath care and elder care. The extreme sensitivity of the functional performance of organic films to structure and the general nonequilibrium nature of solution drying result in extreme processing-performance correlations. In this Review, we highlight insights into the fundamentals of solution-based film deposition afforded by recent state-of-the-art in situ measurements of functional film drying. Emphasis is placed on multimodal studies that combine surface-sensitive X-ray scattering (GIWAXS or GISAXS) with optical characterization to clearly define the evolution of solute structure (aggregation, crystallinity, and morphology) with film thickness.
Morphology Development in Solution-Processed Functional Organic Blend Films: An In Situ Viewpoint
Richter, Lee J.
2017-04-17
Solution-processed organic films are a facile route to high-speed, low cost, large-area deposition of electrically functional components (transistors, solar cells, emitters, etc.) that can enable a diversity of emerging technologies, from Industry 4.0, to the Internet of things, to point-of-use heath care and elder care. The extreme sensitivity of the functional performance of organic films to structure and the general nonequilibrium nature of solution drying result in extreme processing-performance correlations. In this Review, we highlight insights into the fundamentals of solution-based film deposition afforded by recent state-of-the-art in situ measurements of functional film drying. Emphasis is placed on multimodal studies that combine surface-sensitive X-ray scattering (GIWAXS or GISAXS) with optical characterization to clearly define the evolution of solute structure (aggregation, crystallinity, and morphology) with film thickness.
International Nuclear Information System (INIS)
Xiao, Tiejun
2015-01-01
In this paper, the longitudinal dielectric function ϵ_l(k) of primitive electrolyte solutions is discussed. Starting from a modified mean spherical approximation, an analytical dielectric function in terms of two parameters is established. These two parameters can be related to the first two decay parameters k_1_,_2 of the dielectric response modes of the bulk system, and can be determined using constraints of k_1_,_2 from statistical theories. Furthermore, a combination of this dielectric function and the molecular Debye-Hückel theory[J. Chem. Phys. 135(2011)104104] leads to a self-consistent mean filed description of electrolyte solutions. Our theory reveals a relationship between the microscopic structure parameters of electrolyte solutions and the macroscopic thermodynamic properties, which is applied to concentrated electrolyte solutions.
Zeng, Xiang-Yang; Wang, Shu-Guang; Gao, Li-Ping
2010-09-01
As the basic data for virtual auditory technology, head-related transfer function (HRTF) has many applications in the areas of room acoustic modeling, spatial hearing and multimedia. How to individualize HRTF fast and effectively has become an opening problem at present. Based on the similarity and relativity of anthropometric structures, a hybrid HRTF customization algorithm, which has combined the method of principal component analysis (PCA), multiple linear regression (MLR) and database matching (DM), has been presented in this paper. The HRTFs selected by both the best match and the worst match have been applied into obtaining binaurally auralized sounds, which are then used for subjective listening experiments and the results are compared. For the area in the horizontal plane, the localization results have shown that the selection of HRTFs can enhance the localization accuracy and can also abate the problem of front-back confusion.
Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.
2017-11-01
Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.
International Nuclear Information System (INIS)
Tamura, Hiroyuki; Hikita, Shiro
1985-01-01
In this paper, we develop an interactive algorithm for identifying multiattribute measurable value functions based on the concept of finite-order independence of structural difference. This concept includes Dyer and Sarin's weak difference independence as special cases. The algorithm developed is composed of four major parts: 1) formulation of the problem 2) assessment of normalized conditional value functions and structural difference functions 3) assessment of corner values 4) assessment of the order of independence of structural difference and selection of the model. A hypothetical numerical example of a trade-off analysis for siting a nuclear power plant is included. (author)
Directory of Open Access Journals (Sweden)
Jian-feng Zhao
2017-01-01
Full Text Available This paper presents a three-dimensional autonomous chaotic system with high fraction dimension. It is noted that the nonlinear characteristic of the improper fractional-order chaos is interesting. Based on the continuous chaos and the discrete wavelet function map, an image encryption algorithm is put forward. The key space is formed by the initial state variables, parameters, and orders of the system. Every pixel value is included in secret key, so as to improve antiattack capability of the algorithm. The obtained simulation results and extensive security analyses demonstrate the high level of security of the algorithm and show its robustness against various types of attacks.
Scale-up of nature’s tissue weaving algorithms to engineer advanced functional materials
Ng, Joanna L.; Knothe, Lillian E.; Whan, Renee M.; Knothe, Ulf; Tate, Melissa L. Knothe
2017-01-01
We are literally the stuff from which our tissue fabrics and their fibers are woven and spun. The arrangement of collagen, elastin and other structural proteins in space and time embodies our tissues and organs with amazing resilience and multifunctional smart properties. For example, the periosteum, a soft tissue sleeve that envelops all nonarticular bony surfaces of the body, comprises an inherently “smart” material that gives hard bones added strength under high impact loads. Yet a paucity of scalable bottom-up approaches stymies the harnessing of smart tissues’ biological, mechanical and organizational detail to create advanced functional materials. Here, a novel approach is established to scale up the multidimensional fiber patterns of natural soft tissue weaves for rapid prototyping of advanced functional materials. First second harmonic generation and two-photon excitation microscopy is used to map the microscopic three-dimensional (3D) alignment, composition and distribution of the collagen and elastin fibers of periosteum, the soft tissue sheath bounding all nonarticular bone surfaces in our bodies. Then, using engineering rendering software to scale up this natural tissue fabric, as well as multidimensional weaving algorithms, macroscopic tissue prototypes are created using a computer-controlled jacquard loom. The capacity to prototype scaled up architectures of natural fabrics provides a new avenue to create advanced functional materials.
International Nuclear Information System (INIS)
Sundararaman, Ravishankar; Goddard, William A. III; Arias, Tomas A.
2017-01-01
First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solve the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Lastly, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.
Sundararaman, Ravishankar; Goddard, William A.; Arias, Tomas A.
2017-03-01
First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solve the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Finally, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.
Objective Function and Learning Algorithm for the General Node Fault Situation.
Xiao, Yi; Feng, Rui-Bin; Leung, Chi-Sing; Sum, John
2016-04-01
Fault tolerance is one interesting property of artificial neural networks. However, the existing fault models are able to describe limited node fault situations only, such as stuck-at-zero and stuck-at-one. There is no general model that is able to describe a large class of node fault situations. This paper studies the performance of faulty radial basis function (RBF) networks for the general node fault situation. We first propose a general node fault model that is able to describe a large class of node fault situations, such as stuck-at-zero, stuck-at-one, and the stuck-at level being with arbitrary distribution. Afterward, we derive an expression to describe the performance of faulty RBF networks. An objective function is then identified from the formula. With the objective function, a training algorithm for the general node situation is developed. Finally, a mean prediction error (MPE) formula that is able to estimate the test set error of faulty networks is derived. The application of the MPE formula in the selection of basis width is elucidated. Simulation experiments are then performed to demonstrate the effectiveness of the proposed method.
A note on monotone solutions for a nonconvex second-order functional differential inclusion
Directory of Open Access Journals (Sweden)
Aurelian Cernea
2011-12-01
Full Text Available The existence of monotone solutions for a second-order functional differential inclusion with Carath\\'{e}odory perturbation is obtained in the case when the multifunction that define the inclusion is upper semicontinuous compact valued and contained in the Fr\\'{e}chet subdifferential of a $\\phi $-convex function of order two.
Functional porous composites by blending with solution-processable molecular pores.
Jiang, S; Chen, L; Briggs, M E; Hasell, T; Cooper, A I
2016-05-25
We present a simple method for rendering non-porous materials porous by solution co-processing with organic cage molecules. This method can be used both for small functional molecules and for polymers, thus creating porous composites by molecular blending, rather than the more traditional approach of supporting functional molecules on pre-frabricated porous supports.
Directory of Open Access Journals (Sweden)
Surafel Luleseged Tilahun
2012-01-01
Full Text Available Firefly algorithm is one of the new metaheuristic algorithms for optimization problems. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. One of the rules used to construct the algorithm is, a firefly will be attracted to a brighter firefly, and if there is no brighter firefly, it will move randomly. In this paper we modify this random movement of the brighter firefly by generating random directions in order to determine the best direction in which the brightness increases. If such a direction is not generated, it will remain in its current position. Furthermore the assignment of attractiveness is modified in such a way that the effect of the objective function is magnified. From the simulation result it is shown that the modified firefly algorithm performs better than the standard one in finding the best solution with smaller CPU time.
Solutions to an advanced functional partial differential equation of the pantograph type.
Zaidi, Ali A; Van Brunt, B; Wake, G C
2015-07-08
A model for cells structured by size undergoing growth and division leads to an initial boundary value problem that involves a first-order linear partial differential equation with a functional term. Here, size can be interpreted as DNA content or mass. It has been observed experimentally and shown analytically that solutions for arbitrary initial cell distributions are asymptotic as time goes to infinity to a certain solution called the steady size distribution. The full solution to the problem for arbitrary initial distributions, however, is elusive owing to the presence of the functional term and the paucity of solution techniques for such problems. In this paper, we derive a solution to the problem for arbitrary initial cell distributions. The method employed exploits the hyperbolic character of the underlying differential operator, and the advanced nature of the functional argument to reduce the problem to a sequence of simple Cauchy problems. The existence of solutions for arbitrary initial distributions is established along with uniqueness. The asymptotic relationship with the steady size distribution is established, and because the solution is known explicitly, higher-order terms in the asymptotics can be readily obtained.
The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models
GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.
2008-01-01
In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.
Directory of Open Access Journals (Sweden)
Young-Bo Sim
2017-11-01
Full Text Available In this paper, we proposed and developed Function-Oriented Networking (FON, a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV, which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.
Solution of the generalized Emden-Fowler equations by the hybrid functions method
International Nuclear Information System (INIS)
Tabrizidooz, H R; Marzban, H R; Razzaghi, M
2009-01-01
In this paper, we present a numerical algorithm for solving the generalized Emden-Fowler equations, which have many applications in mathematical physics and astrophysics. The method is based on hybrid functions approximations. The properties of hybrid functions, which consist of block-pulse functions and Lagrange interpolating polynomials, are presented. These properties are then utilized to reduce the computation of the generalized Emden-Fowler equations to a system of nonlinear equations. The method is easy to implement and yields very accurate results.
Directory of Open Access Journals (Sweden)
Hui-Sheng Ding
2013-04-01
Full Text Available In this paper, we first introduce a new class of pseudo almost periodic type functions and investigate some properties of pseudo almost periodic type functions; and then we discuss the existence of pseudo almost periodic solutions to the class of abstract partial functional differential equations $x'(t=Ax(t+f(t,x_t$ with finite delay in a Banach space X.
Institute of Scientific and Technical Information of China (English)
LI Shoufu
2005-01-01
A series of stability, contractivity and asymptotic stability results of the solutions to nonlinear stiff Volterra functional differential equations (VFDEs) in Banach spaces is obtained, which provides the unified theoretical foundation for the stability analysis of solutions to nonlinear stiff problems in ordinary differential equations(ODEs), delay differential equations(DDEs), integro-differential equations(IDEs) and VFDEs of other type which appear in practice.
Directory of Open Access Journals (Sweden)
A. K. CHOWDHURY
2016-02-01
Full Text Available In this paper an evolutionary technique for synthesizing Multi-Valued Logic (MVL functions using Neural Network Deployment Algorithm (NNDA is presented. The algorithm is combined with back-propagation learning capability and neural MVL operators. This research article is done to observe the anomalistic characteristics of MVL neural operators and their role in synthesis. The advantages of NNDA-MVL algorithm is demonstrated with realization of synthesized many valued functions with lesser MVL operators. The characteristic feature set consists of MVL gate count, network link count, network propagation delay and accuracy achieved in training. In brief, this paper depicts an effort of reduced network size for synthesized MVL functions. Trained MVL operators improve the basic architecture by reducing MIN gate and interlink connection by 52.94% and 23.38% respectively.
Directory of Open Access Journals (Sweden)
Motasem Aldiab
2008-01-01
Full Text Available Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.
Energy Technology Data Exchange (ETDEWEB)
Etim, E; Basili, C [Rome Univ. (Italy). Ist. di Matematica
1978-08-21
The lagrangian in the path integral solution of the master equation of a stationary Markov process is derived by application of the Ehrenfest-type theorem of quantum mechanics and the Cauchy method of finding inverse functions. Applied to the non-linear Fokker-Planck equation the authors reproduce the result obtained by integrating over Fourier series coefficients and by other methods.
Jensen, Peter Bjerre; Lysgaard, Steen; Quaade, Ulrich J; Vegge, Tejs
2014-09-28
Metal halide ammines have great potential as a future, high-density energy carrier in vehicles. So far known materials, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, are not suitable for automotive, fuel cell applications, because the release of ammonia is a multi-step reaction, requiring too much heat to be supplied, making the total efficiency lower. Here, we apply density functional theory (DFT) calculations to predict new mixed metal halide ammines with improved storage capacities and the ability to release the stored ammonia in one step, at temperatures suitable for system integration with polymer electrolyte membrane fuel cells (PEMFC). We use genetic algorithms (GAs) to search for materials containing up to three different metals (alkaline-earth, 3d and 4d) and two different halides (Cl, Br and I) - almost 27,000 combinations, and have identified novel mixtures, with significantly improved storage capacities. The size of the search space and the chosen fitness function make it possible to verify that the found candidates are the best possible candidates in the search space, proving that the GA implementation is ideal for this kind of computational materials design, requiring calculations on less than two percent of the candidates to identify the global optimum.
International Nuclear Information System (INIS)
Piskunov, N.E.
1985-01-01
Mathematical formulation of the inverse problem of determination of magnetic field geometry from the polarization profiles of spectral lines is gven. The solving algorithm is proposed. A set of model calculations has shown the effectiveness of the algorithm, the high precision of magnetic star model parameters obtained and also the advantages of the inverse problem method over the commonly used method of interpretation of effective field curves
Fall with linear drag and Wien's displacement law: approximate solution and Lambert function
International Nuclear Information System (INIS)
Vial, Alexandre
2012-01-01
We present an approximate solution for the downward time of travel in the case of a mass falling with a linear drag force. We show how a quasi-analytical solution implying the Lambert function can be found. We also show that solving the previous problem is equivalent to the search for Wien's displacement law. These results can be of interest for undergraduate students, as they show that some transcendental equations found in physics may be solved without purely numerical methods. Moreover, as will be seen in the case of Wien's displacement law, solutions based on series expansion can be very accurate even with few terms. (paper)
Yang, Hee-Man; Choi, Hye Min; Jang, Sung-Chan; Han, Myeong Jin; Seo, Bum-Kyoung; Moon, Jei-Kwon; Lee, Kune-Woo
2015-10-01
Hyperbranched polyglycerol-coated magnetic nanoparticles (SHPG-MNPs) were functionalized with succinate groups to form a draw solute for use in a forward osmosis (FO). After the one-step synthesis of hyperbranched polyglycerol-coated magnetic nanoparticles (HPG-MNPs), the polyglycerol groups on the surfaces of the HPG-MNPs were functionalized with succinic anhydride moieties. The resulting SHPG-MNPs showed no change of size and magnetic property compared with HPG-MNPs and displayed excellent dispersibility in water up to the concentration of 400 g/L. SHPG-MNPs solution showed higher osmotic pressure than that of HPG-MNPs solution due to the presence of surface carboxyl groups in SHPG-MNPs and could draw water from a feed solution across an FO membrane without any reverse draw solute leakage during FO process. Moreover, the water flux remained nearly constant over several SHPG-MNP darw solute regeneration cycles applied to the ultrafiltration (UF) process. The SHPG-MNPs demonstrate strong potential for use as a draw solute in FO processes.
Directory of Open Access Journals (Sweden)
Chunhua Ju
2012-01-01
Full Text Available Managing multiple project is a complex task involving the unrelenting pressures of time and cost. Many studies have proposed various tools and techniques for single-project scheduling; however, the literature further considering multimode or multiproject issues occurring in the real world is rather scarce. In this paper, design structure matrix (DSM and an improved artificial immune network algorithm (aiNet are developed to solve a multi-mode resource-constrained scheduling problem. Firstly, the DSM is used to simplify the mathematic model of multi-project scheduling problem. Subsequently, aiNet algorithm comprised of clonal selection, negative selection, and network suppression is adopted to realize the local searching and global searching, which will assure that it has a powerful searching ability and also avoids the possible combinatorial explosion. Finally, the approach is tested on a set of randomly cases generated from ProGen. The computational results validate the effectiveness of the proposed algorithm comparing with other famous metaheuristic algorithms such as genetic algorithm (GA, simulated annealing algorithm (SA, and ant colony optimization (ACO.
Extension and optimization of the FIND algorithm: Computing Green’s and less-than Green’s functions
International Nuclear Information System (INIS)
Li, S.; Darve, E.
2012-01-01
Highlights: ► FIND is an algorithm for calculating entries of the inverse of a sparse matrix. ► We extend the algorithm to other matrix inverse related calculations. ► We exploit sparsity and symmetry to improve performance. - Abstract: The FIND algorithm is a fast algorithm designed to calculate certain entries of the inverse of a sparse matrix. Such calculation is critical in many applications, e.g., quantum transport in nano-devices. We extended the algorithm to other matrix inverse related calculations. Those are required for example to calculate the less-than Green’s function and the current density through the device. For a 2D device discretized as an N x × N y mesh, the best known algorithms have a running time of O(N x 3 N y ), whereas FIND only requires O(N x 2 N y ). Even though this complexity has been reduced by an order of magnitude, the matrix inverse calculation is still the most time consuming part in the simulation of transport problems. We could not reduce the order of complexity, but we were able to significantly reduce the constant factor involved in the computation cost. By exploiting the sparsity and symmetry, the size of the problem beyond which FIND is faster than other methods typically decreases from a 130 × 130 2D mesh down to a 40 × 40 mesh. These improvements make the optimized FIND algorithm even more competitive for real-life applications.
International Nuclear Information System (INIS)
Zhang Jiefang; Dai Chaoqing; Zong Fengde
2007-01-01
In this paper, with the variable separation approach and based on the general reduction theory, we successfully generalize this extended tanh-function method to obtain new types of variable separation solutions for the following Nizhnik-Novikov-Veselov (NNV) equation. Among the solutions, two solutions are new types of variable separation solutions, while the last solution is similar to the solution given by Darboux transformation in Hu et al 2003 Chin. Phys. Lett. 20 1413
On extension of solutions of a simultaneous system of iterative functional equations
Directory of Open Access Journals (Sweden)
Janusz Matkowski
2009-01-01
Full Text Available Some sufficient conditions which allow to extend every local solution of a simultaneous system of equations in a single variable of the form \\[ \\varphi(x = h (x, \\varphi[f_1(x],\\ldots,\\varphi[f_m(x],\\] \\[\\varphi(x = H (x, \\varphi[F_1(x],\\ldots,\\varphi[F_m(x],\\] to a global one are presented. Extensions of solutions of functional equations, both in single and in several variables, play important role (cf. for instance [M. Kuczma, Functional equations in a single variable, Monografie Mat. 46, Polish Scientific Publishers, Warsaw, 1968, M. Kuczma, B. Choczewski, R. Ger, Iterative functional equations, Encyclopedia of Mathematics and Its Applications v. 32, Cambridge, 1990, J. Matkowski, Iteration groups, commuting functions and simultaneous systems of linear functional equations, Opuscula Math. 28 (2008 4, 531-541].
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Emer Bernal
2017-01-01
Full Text Available In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation.
Zhang, Ruili; Wang, Yulei; He, Yang; Xiao, Jianyuan; Liu, Jian; Qin, Hong; Tang, Yifa
2018-02-01
Relativistic dynamics of a charged particle in time-dependent electromagnetic fields has theoretical significance and a wide range of applications. The numerical simulation of relativistic dynamics is often multi-scale and requires accurate long-term numerical simulations. Therefore, explicit symplectic algorithms are much more preferable than non-symplectic methods and implicit symplectic algorithms. In this paper, we employ the proper time and express the Hamiltonian as the sum of exactly solvable terms and product-separable terms in space-time coordinates. Then, we give the explicit symplectic algorithms based on the generating functions of orders 2 and 3 for relativistic dynamics of a charged particle. The methodology is not new, which has been applied to non-relativistic dynamics of charged particles, but the algorithm for relativistic dynamics has much significance in practical simulations, such as the secular simulation of runaway electrons in tokamaks.
International Nuclear Information System (INIS)
Liu Qing; Wang Zihua
2010-01-01
According to two dependent rational solutions to a generalized Riccati equation together with the equation itself, a rational-exponent solution to a nonlinear partial differential equation can be constructed. By selecting different parameter values in the rational-exponent solution, many families of combinatorial solutions combined with a rational function such as hyperbolic functions or trigonometric functions, are rapidly derived. This method is applied to the Whitham-Broer-Kaup equation and a series of combinatorial solutions are obtained, showing that this method is a more concise and efficient approach and can uniformly construct many types of combined solutions to nonlinear partial differential equations.
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Georgii N. Lebedev
2017-01-01
Full Text Available The improvement in the effectiveness of airfield operation largely depends on the problem solving quality on the interaction boundaries of different technological sections. One of such hotspots is the use of the same runway by inbound and outbound aircraft. At certain intensity of outbound and inbound air traffic flow the conflict of aircraft interests appears, where it may be quite difficult to sort out priorities even for experienced controllers, in consequence of which mistakes in decision-making unavoidably appear.In this work the task of response correction of landing and takeoff time of the aircraft using the same RW, in condition of the conflict of interests “arrival – departure” at the increased operating intensity is formulated. The choice of optimal solution is made taking into account mutual interests without the complete sorting and the evaluation of all solutions.Accordingly, the genetic algorithm, which offers a simple and effective approach to optimal control problem solution by providing flight safety at an acceptably high level, is proposed. The estimation of additional aviation fuel consumption is used as optimal choice evaluation criterion.The advantages of the genetic algorithm application at decision-making in comparison with today’s “team” solution of the conflict “departure – arrival” in the airfield area are shown.
DEFF Research Database (Denmark)
2008-01-01
Method and apparatus for determining dielectric function of liquid solutions and thereby concentrations of substances in aqueous solution or the volatile/non-volatile nature of the liquid by self-referenced reflection THz spectroscopy. Having the aqueous solution in any container with a window al....... The invention is particularly useful for determining alcohol (ethanol) content in aqueous solution containing other substances and particles....
Exponential Convergence for Numerical Solution of Integral Equations Using Radial Basis Functions
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Zakieh Avazzadeh
2014-01-01
Full Text Available We solve some different type of Urysohn integral equations by using the radial basis functions. These types include the linear and nonlinear Fredholm, Volterra, and mixed Volterra-Fredholm integral equations. Our main aim is to investigate the rate of convergence to solve these equations using the radial basis functions which have normic structure that utilize approximation in higher dimensions. Of course, the use of this method often leads to ill-posed systems. Thus we propose an algorithm to improve the results. Numerical results show that this method leads to the exponential convergence for solving integral equations as it was already confirmed for partial and ordinary differential equations.
On benchmarking Stochastic Global Optimization Algorithms
Hendrix, E.M.T.; Lancinskas, A.
2015-01-01
A multitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which
The General Analytic Solution of a Functional Equation of Addition Type
Braden, H. W.; Buchstaber, V. M.
1995-01-01
The general analytic solution to the functional equation $$ \\phi_1(x+y)= { { \\biggl|\\matrix{\\phi_2(x)&\\phi_2(y)\\cr\\phi_3(x)&\\phi_3(y)\\cr}\\biggr|} \\over { \\biggl|\\matrix{\\phi_4(x)&\\phi_4(y)\\cr\\phi_5(x)&\\phi_5(y)\\cr}\\biggr|} } $$ is characterised. Up to the action of the symmetry group, this is described in terms of Weierstrass elliptic functions. We illustrate our theory by applying it to the classical addition theorems of the Jacobi elliptic functions and the functional equations $$ \\phi_1(x+...
THE ALGORITHM OF MESHFREE METHOD OF RADIAL BASIS FUNCTIONS IN TASKS OF UNDERGROUND HYDROMECHANICS
Directory of Open Access Journals (Sweden)
N. V. Medvid
2016-01-01
Full Text Available A Mathematical model of filtering consolidation in the body of soil dam with conduit andwashout zone in two-dimensional case is considered. The impact of such technogenic factors as temperature, salt concentration, subsidence of upper boundary and interior points of the dam with time is taken into account. The software to automate the calculation of numerical solution of the boundary problem by radial basis functions has been created, which enables to conduct numerical experiments by varying the input parameters and shape. The influence of the presence of conduit and washout zone on the pressure, temperature and concentration of salts in the dam body at different time intervals isinvestigated. A number of numerical experiments is conducted and the analysis of dam accidents is performed.
Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.
1991-01-01
A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.
Directory of Open Access Journals (Sweden)
C. Avramescu
2003-07-01
Full Text Available Let $f:\\mathbb{R}\\times \\mathbb{R}^{N}\\rightarrow \\mathbb{R}^{N}$ be a continuous function and let $h:\\mathbb{R}\\rightarrow \\mathbb{R}$ be a continuous and strictly positive function. A sufficient condition such that the equation $\\dot{x}=f\\left( t,x\\right $ admits solutions $x:\\mathbb{R}\\rightarrow \\mathbb{R}^{N}$ satisfying the inequality $\\left| x\\left( t\\right \\right| \\leq k\\cdot h\\left( t\\right ,$ $t\\in \\mathbb{R},$ $k>0$, where $\\left| \\cdot \\right| $ is the euclidean norm in $\\mathbb{R}^{N},$ is given. The proof of this result is based on the use of a special function of Lyapunov type, which is often called guiding function. In the particular case $h\\equiv 1$, one obtains known results regarding the existence of bounded solutions.
Exact solutions for nonlinear evolution equations using Exp-function method
International Nuclear Information System (INIS)
Bekir, Ahmet; Boz, Ahmet
2008-01-01
In this Letter, the Exp-function method is used to construct solitary and soliton solutions of nonlinear evolution equations. The Klein-Gordon, Burger-Fisher and Sharma-Tasso-Olver equations are chosen to illustrate the effectiveness of the method. The method is straightforward and concise, and its applications are promising. The Exp-function method presents a wider applicability for handling nonlinear wave equations
Existence of solutions to differential inclusions with primal lower nice functions
Directory of Open Access Journals (Sweden)
Nora Fetouci
2016-02-01
Full Text Available We prove the existence of absolutely continuous solutions to the differential inclusion $$ \\dot{x}(t\\in F(x(t+h(t,x(t, $$ where F is an upper semi-continuous set-valued function with compact values such that $F(x(t\\subset \\partial f(x(t$ on [0,T], where f is a primal lower nice function, and h a single valued Caratheodory perturbation.
Exp-function method for constructing exact solutions of Sharma-Tasso-Olver equation
International Nuclear Information System (INIS)
Erbas, Baris; Yusufoglu, Elcin
2009-01-01
In this paper we use the Exp-function method for the analytic treatment of Sharma-Tasso-Olver equation. New solitonary solutions are formally derived. Change of parameters, which drastically changes the characteristics of the equations, is examined. It is shown that the Exp-function method provides a powerful mathematical tool for solving high-dimensional nonlinear evolutions in mathematical physics. The proposed schemes are reliable and manageable.
Periodic solutions of first-order functional differential equations in population dynamics
Padhi, Seshadev; Srinivasu, P D N
2014-01-01
This book provides cutting-edge results on the existence of multiple positive periodic solutions of first-order functional differential equations. It demonstrates how the Leggett-Williams fixed-point theorem can be applied to study the existence of two or three positive periodic solutions of functional differential equations with real-world applications, particularly with regard to the Lasota-Wazewska model, the Hematopoiesis model, the Nicholsons Blowflies model, and some models with Allee effects. Many interesting sufficient conditions are given for the dynamics that include nonlinear characteristics exhibited by population models. The last chapter provides results related to the global appeal of solutions to the models considered in the earlier chapters. The techniques used in this book can be easily understood by anyone with a basic knowledge of analysis. This book offers a valuable reference guide for students and researchers in the field of differential equations with applications to biology, ecology, a...
Numerical solution of the potential problem by integral equations without Green's functions
International Nuclear Information System (INIS)
De Mey, G.
1977-01-01
An integral equation technique will be presented to solve Laplace's equation in a two-dimensional area S. The Green's function has been replaced by a particular solution of Laplace equation in order to establish the integral equation. It is shown that accurate results can be obtained provided the pivotal elimination method is used to solve the linear algebraic set
C. Yao; F. Wang; Z. Cai; X. Wang
2016-01-01
Nanoscale sorption is a promising strategy for catalyst and purification system design. In this paper, cellulose nanofibrils (CNFs) were densely attached with aldehyde functional groups on the surface via a mild periodate oxidation process, and then applied as mesoporous sorbents to remove Cu(II) and Pb(II) from aqueous solutions. In the studied concentration range (0....
Morphology and function of dog arterial grafts preserved in UW-solution
Vischjager, M.; van Gulik, T. M.; Pfaffendorf, M.; van Zwieten, P. A.; van Marle, J.; Kromhout, J. G.; Klopper, P. J.; Jacobs, M. J.
1995-01-01
To assess the function of arterial grafts after prolonged preservation in the University of Wisconsin solution (UW), in vitro and in vivo. Carotid arteries were harvested from dogs and stored for 1-21 days at 4 degrees C in UW (n = 10) or in PBS (0.9% NaCl, pH 7.4), (PBS) (n = 10). Slices were
DEFF Research Database (Denmark)
Brudler, Sarah; Arnbjerg-Nielsen, Karsten; Rygaard, Martin
The wide range of approaches to handle storm water runoff have varying effects on the environment. Local stormwater control measures for retention and treatment are increasingly used components in urban climate adaptation plans. Often, these solutions modify the multiple functions of urban...
Some properties of solutions of a functional-differential equation of second order with delay.
Ilea, Veronica Ana; Otrocol, Diana
2014-01-01
Existence, uniqueness, data dependence (monotony, continuity, and differentiability with respect to parameter), and Ulam-Hyers stability results for the solutions of a system of functional-differential equations with delays are proved. The techniques used are Perov's fixed point theorem and weakly Picard operator theory.
Periodic solutions of delayed predator-prey model with the Beddington-DeAngelis functional response
Energy Technology Data Exchange (ETDEWEB)
Huo Haifeng [Institute of Applied Mathematics, Lanzhou University of Technology, Lanzhou, Gansu 730050 (China)]. E-mail: hfhuo@lut.cn; Li Wantong [Department of Mathematics, Lanzhou University Lanzhou, Gansu 730000 (China)]. E-mail: wtli@lzu.edu.cn; Nieto, Juan J. [Departamento de Analisis Matematico, Facultad de Matematicas, Universidad de Santiago de Compostela 15782 (Spain)]. E-mail: amnieto@usc.es
2007-07-15
By using the continuation theorem based on Gaines and Mawhin's coincidence degree, sufficient and realistic conditions are obtained for the global existence of positive periodic solutions for a delayed predator-prey model with the Beddington-DeAngelis functional response. Our results are applicable to state dependent and distributed delays.
Exact solitary wave solutions for some nonlinear evolution equations via Exp-function method
International Nuclear Information System (INIS)
Ebaid, A.
2007-01-01
Based on the Exp-function method, exact solutions for some nonlinear evolution equations are obtained. The KdV equation, Burgers' equation and the combined KdV-mKdV equation are chosen to illustrate the effectiveness of the method
Czech Academy of Sciences Publication Activity Database
Lomtatidze, Alexander; Vodstrčil, Petr
2005-01-01
Roč. 84, č. 2 (2005), s. 197-209 ISSN 0003-6811 Institutional research plan: CEZ:AV0Z10190503 Keywords : second order linear functional differential equations * nonnegative solution * two-point boundary value problem Subject RIV: BA - General Mathematics http://www.tandfonline.com/doi/full/10.1080/00036810410001724427
International Nuclear Information System (INIS)
Sato, M.
1991-01-01
The Saha equation for a plasma in thermodynamic equilibrium (TE) is approximately solved to give the temperature as an explicit function of population densities. It is shown that the derived expressions for the Saha temperature are valid approximations to the exact solution. An application of the approximate temperature to the calculation of TE plasma parameters is also described. (orig.)
Some Properties of Solutions of a Functional-Differential Equation of Second Order with Delay
Directory of Open Access Journals (Sweden)
Veronica Ana Ilea
2014-01-01
Full Text Available Existence, uniqueness, data dependence (monotony, continuity, and differentiability with respect to parameter, and Ulam-Hyers stability results for the solutions of a system of functional-differential equations with delays are proved. The techniques used are Perov’s fixed point theorem and weakly Picard operator theory.
Morphology Development in Solution-Processed Functional Organic Blend Films: An In Situ Viewpoint
Richter, Lee J.; DeLongchamp, Dean M.; Amassian, Aram
2017-01-01
.0, to the Internet of things, to point-of-use heath care and elder care. The extreme sensitivity of the functional performance of organic films to structure and the general nonequilibrium nature of solution drying result in extreme processing-performance correlations
Measuring Functional Creativity: Non-Expert Raters and the Creative Solution Diagnosis Scale
Cropley, David H.; Kaufman, James C.
2012-01-01
The Creative Solution Diagnosis Scale (CSDS) is a 30-item scale based on a core of four criteria: Relevance & Effectiveness, Novelty, Elegance, and Genesis. The CSDS offers potential for the consensual assessment of functional product creativity. This article describes an empirical study in which non-expert judges rated a series of mousetrap…
Directory of Open Access Journals (Sweden)
Nasri Abdelfatah
2011-01-01
Full Text Available The Reactive power flow’s is one of the most electrical distribution systems problem wich have great of interset of the electrical network researchers, it’s cause’s active power transmission reduction, power losses decreasing, and the drop voltage’s increase. In this research we described the efficiency of the FLC-GAO approach to solve the optimal power flow (OPF combinatorial problem. The proposed approach employ tow algorithms, Fuzzy logic controller (FLC algorithm for critical nodal detection and gentic algorithm optimization (GAO algorithm for optimal seizing capacitor.GAO method is more efficient in combinatory problem solutions. The proposed approach has been examined and tested on the standard IEEE 57-bus the resulats show the power loss minimization denhancement, voltage profile, and stability improvement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach.
Removal of patulin from aqueous solutions by propylthiol functionalized SBA-15
International Nuclear Information System (INIS)
Appell, Michael; Jackson, Michael A.; Dombrink-Kurtzman, Mary Ann
2011-01-01
Propylthiol functionalized SBA-15 silica was investigated to detoxify aqueous solutions contaminated with the regulated mycotoxin patulin. Micelle templated silicas with a specific pore size were synthetically modified to possess propylthiol groups, a functional group known to form Michael reaction products with the conjugated double bond system of patulin. BET surface area analysis indicated the propylthiol functionalized SBA-15 possesses channels with the pore size of 5.4 nm and a surface area of 345 m 2 g -1 . Elemental analysis indicates the silicon/sulfur ratio to be 10:1, inferring one propylthiol substituent for every ten silica residues. The propylthiol modified SBA-15 was effective at significantly reducing high levels of patulin from aqueous solutions (pH 7.0) in batch sorption assays at room temperature. The material was less effective at lower pH; however heating low pH solutions and apple juice to 60 deg, C in the presence of propylthiol functionalized SBA-15 significantly reduced the levels of patulin in contaminated samples. Composite molecular models developed by semi-empirical PM3 and empirical force field methods support patulin permeation through the mesoporous channels of propylthiol functionalized SBA-15. Density functional study at the B3LYP/6-31G(d,p) level predicts the proposed patulin adducts formed by reaction with the thiol residues exhibit less electrophilic properties than patulin. It is demonstrated the use of propylthiol functionalized SBA-15 is a viable approach to reduce patulin levels in aqueous solutions, including contaminated apple juice.
Removal of patulin from aqueous solutions by propylthiol functionalized SBA-15
Energy Technology Data Exchange (ETDEWEB)
Appell, Michael, E-mail: michael.appell@ars.usda.gov [Bacterial Foodborne Pathogens and Mycology Research Unit, United States Department of Agriculture, Agricultural Research Service, National Center for Agricultural Utilization Research, 1815 N. University St., Peoria, IL 61604 (United States); Jackson, Michael A.; Dombrink-Kurtzman, Mary Ann [Renewable Product Technology Research Unit, United States Department of Agriculture, Agricultural Research Service, National Center for Agricultural Utilization Research, 1815 N. University St., Peoria, IL 61604 (United States)
2011-03-15
Propylthiol functionalized SBA-15 silica was investigated to detoxify aqueous solutions contaminated with the regulated mycotoxin patulin. Micelle templated silicas with a specific pore size were synthetically modified to possess propylthiol groups, a functional group known to form Michael reaction products with the conjugated double bond system of patulin. BET surface area analysis indicated the propylthiol functionalized SBA-15 possesses channels with the pore size of 5.4 nm and a surface area of 345 m{sup 2} g{sup -1}. Elemental analysis indicates the silicon/sulfur ratio to be 10:1, inferring one propylthiol substituent for every ten silica residues. The propylthiol modified SBA-15 was effective at significantly reducing high levels of patulin from aqueous solutions (pH 7.0) in batch sorption assays at room temperature. The material was less effective at lower pH; however heating low pH solutions and apple juice to 60 deg, C in the presence of propylthiol functionalized SBA-15 significantly reduced the levels of patulin in contaminated samples. Composite molecular models developed by semi-empirical PM3 and empirical force field methods support patulin permeation through the mesoporous channels of propylthiol functionalized SBA-15. Density functional study at the B3LYP/6-31G(d,p) level predicts the proposed patulin adducts formed by reaction with the thiol residues exhibit less electrophilic properties than patulin. It is demonstrated the use of propylthiol functionalized SBA-15 is a viable approach to reduce patulin levels in aqueous solutions, including contaminated apple juice.
Directory of Open Access Journals (Sweden)
Raycon Roberto Freitas Garcia
Full Text Available Cryoprotectant solutions are used to protect the sperm from alterations caused by the low temperature in the cryopreservation process. We evaluated the quality of Colossoma macropomum semen after freezing, using dimethyl sulfoxide (DMSO as a cryoprotectant, combined with two extender solutions (T1 - Solution 1: Glucose 90.0 g/L, Sodium Citrate 6.0 g/L, EDTA 1.5 g/L, Sodium Bicarbonate 1.5 g/L, Potassium Chloride 0.8 g/L, Gentamycin Sulphate 0.2 g/L, and T2 - Solution 2: Glucose 90.0 g/L, ACP(r-104 10.0 g/L. Motility rate and motility time did not differ between T1 and T2 and were lower than fresh semen. The number of normal sperm was significantly different in treatments T1 (15.1% and T2 (21.9%, and both showed a reduction in the percentage of normal sperm compared to fresh semen (57.4%. The values found for the rates of fertilization and hatching, mitochondrial functionality and sperm DNA, did not differ between the treatments (T1 and T2. Regarding membrane integrity, there was a higher percentage of spermatozoa with intact membranes in T1 (53.4% than T2 (43.7%. The extender solutions, combined with 10% DMSO, maintained the sperm DNA intact in almost all the C. macropomum sperm cells, however there was a loss in their functionality.
McCollom, Brittany A; Collis, Jon M
2014-09-01
A normal mode solution to the ocean acoustic problem of the Pekeris waveguide with an elastic bottom using a Green's function formulation for a compressional wave point source is considered. Analytic solutions to these types of waveguide propagation problems are strongly dependent on the eigenvalues of the problem; these eigenvalues represent horizontal wavenumbers, corresponding to propagating modes of energy. The eigenvalues arise as singularities in the inverse Hankel transform integral and are specified by roots to a characteristic equation. These roots manifest themselves as poles in the inverse transform integral and can be both subtle and difficult to determine. Following methods previously developed [S. Ivansson et al., J. Sound Vib. 161 (1993)], a root finding routine has been implemented using the argument principle. Using the roots to the characteristic equation in the Green's function formulation, full-field solutions are calculated for scenarios where an acoustic source lies in either the water column or elastic half space. Solutions are benchmarked against laboratory data and existing numerical solutions.
A three-dimensional elasticity solution of functionally graded piezoelectric cylindrical panels
International Nuclear Information System (INIS)
Sedighi, M R; Shakeri, M
2009-01-01
This research presents an exact solution of finitely long, simply supported, orthotropic, functionally graded piezoelectric (FGP), cylindrical shell panels under pressure and electrostatic excitation. The FGP cylindrical panel is first divided into linearly inhomogeneous elements (LIEs). The general solution of governing partial differential equations of the LIEs is obtained by separation of variables. The highly coupled partial differential equations are reduced to ordinary differential equations with variable coefficients by means of appropriate trigonometric expansion of displacements and electric potential in circumferential and axial directions. The resulting governing ordinary differential equations are solved by the Galerkin finite element method. In this procedure the quadratic shape function is used in each element. The present method is applied to several benchmark problems. The coupled electromechanical effect on the structural behavior of functionally graded piezoelectric cylindrical shell panels is evaluated. The influence of the material property gradient index on the variables of electric and mechanical fields is studied. Finally some results are compared with published results
Deb, Kalyanmoy; Sinha, Ankur
2010-01-01
Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.
Use of Green's functions in the numerical solution of two-point boundary value problems
Gallaher, L. J.; Perlin, I. E.
1974-01-01
This study investigates the use of Green's functions in the numerical solution of the two-point boundary value problem. The first part deals with the role of the Green's function in solving both linear and nonlinear second order ordinary differential equations with boundary conditions and systems of such equations. The second part describes procedures for numerical construction of Green's functions and considers briefly the conditions for their existence. Finally, there is a description of some numerical experiments using nonlinear problems for which the known existence, uniqueness or convergence theorems do not apply. Examples here include some problems in finding rendezvous orbits of the restricted three body system.
Effect of timolol 0.5% gel and solution on pulmonary function in older glaucoma patients.
Stewart, W C; Day, D G; Holmes, K T; Stewart, J A
2001-06-01
To evaluate the effect of timolol maleate solution or gel forming solution versus placebo on pulmonary function in patients with primary open-angle glaucoma or ocular hypertension without reactive airway disease. After a screening visit, each patient was randomized by a Latin square technique to receive placebo twice daily, 0.5% timolol solution twice daily, or 0.5% timolol gel once a day (placebo given as second dose) to each eye for 2 weeks. Subjects then were crossed over to the two other treatments for 2-week treatment intervals. At each visit, patients were received a dose 15 minutes before pulmonary function testing. This study began with 25 patients, and 20 finished the trial. There was no difference between treatment groups for the forced expiratory volume at one second (FEV1), forced vital capacity (FVC), FEV1/FVC ratio (P > 0.1). The mean FEV1 for timolol solution, timolol gel, and placebo was 2.42 L, 2.45 L, and 2.50 L, respectively. The mean FVC for timolol solution, timolol gel, and placebo was 3.33 L, 3.38 L, and 3.44 L, respectively. No difference in intraocular pressure was observed between the timolol solution (17.1 +/- 3.3 mm Hg) and timolol gel (17.1 +/- 3.6 mm Hg) between the treatment periods (P > 0.1). No difference in side effects was observed between treatment groups (P > 0.05). In older patients with primary open-angle glaucoma or ocular hypertension without reactive airway disease, nonselective beta-blockers should not worsen pulmonary function.
In vitro function of random donor platelets stored for 7 days in composol platelet additive solution
Directory of Open Access Journals (Sweden)
Gupta Ashish
2011-01-01
Full Text Available Background and Aim: Platelets are routinely isolated from whole blood and stored in plasma for 5 days. The present study was done to assess the in vitro function of random donor platelets stored for 7 days in composol platelet additive solution at 22°C. Materials and Methods: The study sample included 30 blood donors of both sex in State Blood Bank, CSM Medical University, Lucknow. Random donor platelets were prepared by platelet rich plasma method. Whole blood (350 ml was collected in anticoagulant Citrate Phosphate Dextrose Adenine triple blood bags. Random donor platelets were stored for 7 days at 22°C in platelet incubators and agitators, with and without additive solution. Results: Platelet swirling was present in all the units at 22°C on day 7, with no evidence of bacterial contamination. Comparison of the mean values of platelet count, platelet factor 3, lactate dehydrogenase, pH, glucose and platelet aggregation showed no significant difference in additive solution, whereas platelet factor 3, glucose and platelet aggregation showed significant difference (P < 0.001 on day 7 without additive solution at 22°C. Conclusion: Our study infers that platelet viability and aggregation were best maintained within normal levels on day 7 of storage in platelet additive solution at 22°C. Thus, we may conclude that in vitro storage of random donor platelets with an extended shelf life of 7 days using platelet additive solution may be advocated to improve the inventory of platelets.
Superposition of elliptic functions as solutions for a large number of nonlinear equations
International Nuclear Information System (INIS)
Khare, Avinash; Saxena, Avadh
2014-01-01
For a large number of nonlinear equations, both discrete and continuum, we demonstrate a kind of linear superposition. We show that whenever a nonlinear equation admits solutions in terms of both Jacobi elliptic functions cn(x, m) and dn(x, m) with modulus m, then it also admits solutions in terms of their sum as well as difference. We have checked this in the case of several nonlinear equations such as the nonlinear Schrödinger equation, MKdV, a mixed KdV-MKdV system, a mixed quadratic-cubic nonlinear Schrödinger equation, the Ablowitz-Ladik equation, the saturable nonlinear Schrödinger equation, λϕ 4 , the discrete MKdV as well as for several coupled field equations. Further, for a large number of nonlinear equations, we show that whenever a nonlinear equation admits a periodic solution in terms of dn 2 (x, m), it also admits solutions in terms of dn 2 (x,m)±√(m) cn (x,m) dn (x,m), even though cn(x, m)dn(x, m) is not a solution of these nonlinear equations. Finally, we also obtain superposed solutions of various forms for several coupled nonlinear equations
International Nuclear Information System (INIS)
Ball, G.
1990-01-01
The development and analysis of methods for generating first-flight collision probabilities in two-dimensional geometries consistent with Light Water Moderated (LWR) fuel assemblies are examined. A new ray-tracing algorithm is discussed. A number of numerical results are given demonstrating the feasibility of this algorithm and the effects of the moderator (and fuel) sectorizations on the resulting flux distributions. The collision probabilties have been introduced and their subsequent utilization in the flux calculation procedures illustrated. A brief description of the Coxy-1 and Coxy-2 programs (which were developed in the Reactor Theory Division of the Atomic Energy Agency of South Africa Ltd) has also been added. 41 figs., 9 tabs., 18 refs
Large-area graphene films by simple solution casting of edge-selectively functionalized graphite.
Bae, Seo-Yoon; Jeon, In-Yup; Yang, Jieun; Park, Noejung; Shin, Hyeon Suk; Park, Sungjin; Ruoff, Rodney S; Dai, Liming; Baek, Jong-Beom
2011-06-28
We report edge-selective functionalization of graphite (EFG) for the production of large-area uniform graphene films by simply solution-casting EFG dispersions in dichloromethane on silicon oxide substrates, followed by annealing. The resultant graphene films show ambipolar transport properties with sheet resistances of 0.52-3.11 kΩ/sq at 63-90% optical transmittance. EFG allows solution processing methods for the scalable production of electrically conductive, optically transparent, and mechanically robust flexible graphene films for use in practice.
A Green's function solution for a rectangular heat source on an infinite plate
International Nuclear Information System (INIS)
Bainbridge, B.L.
1989-01-01
The applications associated with a rectangular heat source on an infinite plate range from integrated circuits to thin film heat flux sensors on thin substrates. The particular problem from which the solution is developed concerns the use of a resistive strip for monitoring currents generated in circuits exposed to electromagnetic fields. The Green's function formulation is solved by using early and late time approximations for which analytical solutions can be derived. In this paper expressions are developed for three sets of boundary conditions and compared to the experimental performance of a physical device
New exact solutions of coupled Boussinesq–Burgers equations by Exp-function method
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L.K. Ravi
2017-03-01
Full Text Available In the present paper, we build the new analytical exact solutions of a nonlinear differential equation, specifically, coupled Boussinesq–Burgers equations by means of Exp-function method. Then, we analyze the results by plotting the three dimensional soliton graphs for each case, which exhibit the simplicity and effectiveness of the proposed method. The primary purpose of this paper is to employ a new approach, which allows us victorious and efficient derivation of the new analytical exact solutions for the coupled Boussinesq–Burgers equations.
International Nuclear Information System (INIS)
Zajic, T.; Fischer, R.; Brink, I.; Moser, E.; Krause, T.; Saurbier, B.
2001-01-01
Aim: Left ventricular volume and function can be computed from gated SPECT myocardial perfusion imaging using emory cardiac toolbox (ECT) or gated SPECT quantification (GS-Quant). The aim of this study was to compare both programs with respect to their practical application, stability and precision on heart-models as well as in clinical use. Methods: The volumes of five cardiac models were calculated by ECT and GS-Quant. 48 patients (13 female, 35 male) underwent a one day stress-rest protocol and gated SPECT. From these 96 gated SPECT images, left ventricular ejection fraction (LVEF), end-diastolic volume (EDV) and end-systolic volume (ESV) were estimated by ECT and GS-Quant. For 42 patients LVEF was also determined by echocardiography. Results: For the cardiac models the computed volumes showed high correlation with the model-volumes as well as high correlation between ECT and GS-Quant (r ≥0.99). Both programs underestimated the volume by approximately 20-30% independent of the ventricle-size. Calculating LVEF, EDV and ESV, GS-Quant and ECT correlated well to each other and to the LVEF estimated by echocardiography (r ≥0.86). LVEF values determined with ECT were about 10% higher than values determined with GS-Quant or echocardiography. The incorrect surfaces calculated by the automatic algorithm of GS-Quant for three examinations could not be corrected manually. 34 of the ECT studies were optimized by the operator. Conclusion: GS-Quant and ECT are two reliable programs in estimating LVEF. Both seem to underestimate the cardiac volume. In practical application GS-Quant was faster and easier to use. ECT allows the user to define the contour of the ventricle and thus is less susceptible to artifacts. (orig.) [de
Directory of Open Access Journals (Sweden)
BARSUK R. V.
2016-08-01
Full Text Available Annotation. Problems formulation. The article deals with choice functions building of preferred solutions by experimental information for tubular gas heater working on fuel granules - pellets.Further choice functions using for making technical solutions by tubular gas heaters construction and designing. Recently research analysis. There are works about choice functions construction by separate presents are examined. But full chose functions building by separate presents are not examined. Aims and tasks. There are setting aim to develop full choice functions mathematical model on separate presents by authors. The expert are connect to primary experimental data’s evaluation that estimates separate results by output functions (criteria. Its evaluations issue in experimental points paired comparison’s table form. Thus, there are necessary construct binary choice relations presents on experimental “points” set by expert that then using for full choice function’s constructing. Conclusions. There are choice function’s construction’s sequence are sets. There are posed point comparison results that characterized tubular gas heater’s condition with expert’s evaluation using. Also posed output functions comparisons by which can be characterized improving tubular gas heater’s performance or vice versa.
Energy Technology Data Exchange (ETDEWEB)
Hurtado, S. [Servicio de Radioisotopos, Centro de Investigacion, Tecnologia e Innovacion (CITIUS), Universidad de Sevilla, Avda. Reina Mercedes s/n, 41012 Sevilla (Spain)], E-mail: shurtado@us.es; Garcia-Leon, M. [Departamento de Fisica Atomica, Molecular y Nuclear, Facultad de Fisica, Universidad de Sevilla, Aptd. 1065, 41080 Sevilla (Spain); Garcia-Tenorio, R. [Departamento de Fisica Aplicada II, E.T.S.A. Universidad de Sevilla, Avda, Reina Mercedes 2, 41012 Sevilla (Spain)
2008-09-11
In this work several mathematical functions are compared in order to perform the full-energy peak efficiency calibration of HPGe detectors using a 126cm{sup 3} HPGe coaxial detector and gamma-ray energies ranging from 36 to 1460 keV. Statistical tests and Monte Carlo simulations were used to study the performance of the fitting curve equations. Furthermore the fitting procedure of these complex functional forms to experimental data is a non-linear multi-parameter minimization problem. In gamma-ray spectrometry usually non-linear least-squares fitting algorithms (Levenberg-Marquardt method) provide a fast convergence while minimizing {chi}{sub R}{sup 2}, however, sometimes reaching only local minima. In order to overcome that shortcoming a hybrid algorithm based on simulated annealing (HSA) techniques is proposed. Additionally a new function is suggested that models the efficiency curve of germanium detectors in gamma-ray spectrometry.
Chhettry; Wang; Hsu; Fox; Baig; Barry; Zhuang; Otsuka; Higuchi
1999-10-01
Previous studies have shown that carbonated apatites (CAPs) exhibit the phenomenon of metastable equilibrium solubility (MES) in weak acid media. The purpose of the present investigation was to examine two questions: first, whether the MES concept is applicable to a broader range of solution conditions and, second, whether a driving force function associated with a surface complex having a constant stoichiometry governs the dissolution of CAP and, if so, what is this stoichiometry. CAP preparations with carbonate contents of 1.8-5.7 wt% (synthesized by hydrolysis of dicalcium phosphate anhydrate in solutions of varying bicarbonate levels or by direct precipitation from supersaturated calcium/phosphate/carbonate solutions) were studied as follows. MES distributions for each of the CAP preparations were determined by equilibrating the CAP under stirred conditions in a series of acetate buffers (0.10 M) containing various levels of calcium and phosphate in the pH range 4.5-6.5 and a solution calcium/phosphate ratio in the range 0.1-10. The amount dissolved in each instance was regarded as the fraction of the CAP possessing an MES value greater than that corresponding to the ion activity product (IAP) of the equilibrating solution. The solution IAPs were calculated from the solution compositions using plausible calcium phosphate stoichiometries, viz., dicalcium phosphate dihydrate, octacalcium phosphate, tricalcium phosphate, hydroxyapatite, carbonated apatite (based on the bulk composition of the particular CAP involved in the experiment), and tetracalcium phosphate. The fraction of CAP dissolved was plotted against the solution IAPs for each experimental set using each of the six assumed stoichiometries for the surface complex. The results demonstrated that the MES concept was applicable to all of the CAP preparations in media of various solution compositions and different pH levels. The most important new outcome of this study was that MES profiles for each of the
Pseudo-deterministic Algorithms
Goldwasser , Shafi
2012-01-01
International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...
International Nuclear Information System (INIS)
Appleby, J A D; Wu, H
2008-01-01
In this paper we consider functional differential equations subjected to either instantaneous state-dependent noise, or to a white noise perturbation. The drift of the equations depend linearly on the current value and on the maximum of the solution. The functional term always provides positive feedback, while the instantaneous term can be mean-reverting or can exhibit positive feedback. We show in the white noise case that if the instantaneous term is mean reverting and dominates the history term, then solutions are recurrent, and upper bounds on the a.s. growth rate of the partial maxima of the solution can be found. When the instantaneous term is weaker, or is of positive feedback type, we determine necessary and sufficient conditions on the diffusion coefficient which ensure the exact exponential growth of solutions. An application of these results to an inefficient financial market populated by reference traders and speculators is given, in which the difference between the current instantaneous returns and maximum of the returns over the last few time units is used to determine trading strategies.
Scemama, Anthony; Renon, Nicolas; Rapacioli, Mathias
2014-06-10
We present an algorithm and its parallel implementation for solving a self-consistent problem as encountered in Hartree-Fock or density functional theory. The algorithm takes advantage of the sparsity of matrices through the use of local molecular orbitals. The implementation allows one to exploit efficiently modern symmetric multiprocessing (SMP) computer architectures. As a first application, the algorithm is used within the density-functional-based tight binding method, for which most of the computational time is spent in the linear algebra routines (diagonalization of the Fock/Kohn-Sham matrix). We show that with this algorithm (i) single point calculations on very large systems (millions of atoms) can be performed on large SMP machines, (ii) calculations involving intermediate size systems (1000-100 000 atoms) are also strongly accelerated and can run efficiently on standard servers, and (iii) the error on the total energy due to the use of a cutoff in the molecular orbital coefficients can be controlled such that it remains smaller than the SCF convergence criterion.
Directory of Open Access Journals (Sweden)
Lars H. Wegner
2017-03-01
Full Text Available Current concepts of plant membrane transport are based on the assumption that water and solutes move across membranes via separate pathways. According to this view, coupling between the fluxes is more or less exclusively constituted via the osmotic force that solutes exert on water transport. This view is questioned here, and experimental evidence for a cotransport of water and solutes is reviewed. The overview starts with ion channels that provide pathways for both ion and water transport, as exemplified for maxi K+ channels from cytoplasmic droplets of Chara corallina. Aquaporins are usually considered to be selective for water (just allowing for slippage of some other small, neutral molecules. Recently, however, a “dual function” aquaporin has been characterized from Arabidopsis thaliana (AtPIP2.1 that translocates water and at the same time conducts cations, preferentially Na+. By analogy with mammalian physiology, other candidates for solute-water flux coupling are cation-chloride cotransporters of the CCC type, and transporters of sugars and amino acids. The last part is dedicated to possible physiological functions that could rely on solute-water cotransport. Among these are the generation of root pressure, refilling of embolized xylem vessels, fast turgor-driven movements of leaves, cell elongation (growth, osmoregulation and adjustment of buoyancy in marine algae. This review will hopefully initiate further research in the field.
Solutions of the two-level problem in terms of biconfluent Heun functions
Energy Technology Data Exchange (ETDEWEB)
Ishkhanyan, Artur [Engineering Center of Armenian National Academy of Sciences, Ashtarak (Armenia)]. E-mail: artur@ec.sci.am; Suominen, Kalle-Antti [Helsinki Institute of Physics, Helsinki (Finland); Department of Applied Physics, University of Turku, Turku (Finland)
2001-08-17
Five four-parametric classes of quantum mechanical two-level models permitting solutions in terms of the biconfluent Heun function are derived. Three of these classes are generalizations of the well known classes of Landau-Zener, Nikitin and Crothers. It is shown that two other classes describe super- and sublinear and essentially nonlinear level crossings, as well as processes with three crossing points. In particular, these classes include two-level models where the field amplitude is constant and the detuning varies as {delta}{sub 0}t+{delta}{sub 2}t{sup 3} or {approx}t{sup 1/3}. For the essentially nonlinear cubic-crossing model, {delta}{sub t}{approx}{delta}{sub 2}t{sup 3}, the general solution of the two-level problem is shown to be expressed as series of confluent hypergeometric functions. (author)
Plane strain analytical solutions for a functionally graded elastic-plastic pressurized tube
International Nuclear Information System (INIS)
Eraslan, Ahmet N.; Akis, Tolga
2006-01-01
Plane strain analytical solutions to functionally graded elastic and elastic-plastic pressurized tube problems are obtained in the framework of small deformation theory. The modulus of elasticity and the uniaxial yield limit of the tube material are assumed to vary radially according to two parametric parabolic forms. The analytical plastic model is based on Tresca's yield criterion, its associated flow rule and ideally plastic material behaviour. Elastic, partially plastic and fully plastic stress states are investigated. It is shown that the elastoplastic response of the functionally graded pressurized tube is affected significantly by the material nonhomogeneity. Different modes of plasticization may take place unlike the homogeneous case. It is also shown mathematically that the nonhomogeneous elastoplastic solution presented here reduces to that of a homogeneous one by appropriate choice of the material parameters
DEFF Research Database (Denmark)
Kim, Oleksiy S.; Meincke, Peter; Breinbjerg, Olav
2007-01-01
The problem of electromagnetic scattering by composite metallic and dielectric objects is solved using the coupled volume-surface integral equation (VSIE). The method of moments (MoM) based on higher-order hierarchical Legendre basis functions and higher-order curvilinear geometrical elements...... with the analytical Mie series solution. Scattering by more complex metal-dielectric objects are also considered to compare the presented technique with other numerical methods....
Size-dependent error of the density functional theory ionization potential in vacuum and solution.
Sosa Vazquez, Xochitl A; Isborn, Christine M
2015-12-28
Density functional theory is often the method of choice for modeling the energetics of large molecules and including explicit solvation effects. It is preferable to use a method that treats systems of different sizes and with different amounts of explicit solvent on equal footing. However, recent work suggests that approximate density functional theory has a size-dependent error in the computation of the ionization potential. We here investigate the lack of size-intensivity of the ionization potential computed with approximate density functionals in vacuum and solution. We show that local and semi-local approximations to exchange do not yield a constant ionization potential for an increasing number of identical isolated molecules in vacuum. Instead, as the number of molecules increases, the total energy required to ionize the system decreases. Rather surprisingly, we find that this is still the case in solution, whether using a polarizable continuum model or with explicit solvent that breaks the degeneracy of each solute, and we find that explicit solvent in the calculation can exacerbate the size-dependent delocalization error. We demonstrate that increasing the amount of exact exchange changes the character of the polarization of the solvent molecules; for small amounts of exact exchange the solvent molecules contribute a fraction of their electron density to the ionized electron, but for larger amounts of exact exchange they properly polarize in response to the cationic solute. In vacuum and explicit solvent, the ionization potential can be made size-intensive by optimally tuning a long-range corrected hybrid functional.
Shape functions for separable solutions to cross-field diffusion problems
International Nuclear Information System (INIS)
Luning, C.D.; Perry, W.L.
1984-01-01
The shape function S(x), which arises in the study of nonlinear diffusion for cross-field diffusion in plasmas, satisfies the equation S''(x)+lambdaa(x)S/sup α/(x) = 0, 0 0. In the cases of physical interest a(x) possesses an integrable singularity at some point in (0,1) but is otherwise continuous. Existence of a positive solution to this problem is established
International Nuclear Information System (INIS)
Cemal Oezeroglu; Niluefer Metin
2012-01-01
In this paper, the crosslinked polyester resin containing acrylic acid functional groups was used for the adsorption of uranium ions from aqueous solutions. For this purpose, the crosslinked polyester resin of unsaturated polyester in styrene monomer (Polipol 353, Poliya) and acrylic acid as weight percentage at 80 and 20%, respectively was synthesized by using methyl ethyl ketone peroxide (MEKp, Butanox M60, Azo Nobel)-cobalt octoate initiator system. The adsorption of uranium ions on the sample (0.05 g copolymer and 5 mL of U(VI) solution were mixed) of the crosslinked polyester resin functionalized with acrylic acid was carried out in a batch reactor. The effects of adsorption parameters of the contact time, temperature, pH of solution and initial uranium(VI) concentration for U(VI) adsorption on the crosslinked polyester resin functionalized with acrylic acid were investigated. The adsorption data obtained from experimental results depending on the initial U(VI) concentration were analyzed by the Freundlich, Langmuir and Dubinin-Radushkevich (D-R) adsorption isotherms. The adsorption capacity and free energy change were determined by using D-R isotherm. The obtained experimental adsorption data depending on temperature were evaluated to calculate the thermodynamic parameters of enthalpy (ΔH o ), entropy (ΔS o ) and free energy change (ΔG o ) for the U(VI) adsorption on the crosslinked polyester resin functionalized with acrylic acid from aqueous solutions. The obtained adsorption data depending on contact time were analyzed by using adsorption models such as the modified Freundlich, Elovich, pseudo-first order and pseudo-second-order kinetic models. (author)
Chen, Tinggui; Xiao, Renbin
2014-01-01
Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.
Directory of Open Access Journals (Sweden)
DAHIYA, P.
2015-05-01
Full Text Available This paper presents the application of hybrid opposition based disruption operator in gravitational search algorithm (DOGSA to solve automatic generation control (AGC problem of four area hydro-thermal-gas interconnected power system. The proposed DOGSA approach combines the advantages of opposition based learning which enhances the speed of convergence and disruption operator which has the ability to further explore and exploit the search space of standard gravitational search algorithm (GSA. The addition of these two concepts to GSA increases its flexibility for solving the complex optimization problems. This paper addresses the design and performance analysis of DOGSA based proportional integral derivative (PID and fractional order proportional integral derivative (FOPID controllers for automatic generation control problem. The proposed approaches are demonstrated by comparing the results with the standard GSA, opposition learning based GSA (OGSA and disruption based GSA (DGSA. The sensitivity analysis is also carried out to study the robustness of DOGSA tuned controllers in order to accommodate variations in operating load conditions, tie-line synchronizing coefficient, time constants of governor and turbine. Further, the approaches are extended to a more realistic power system model by considering the physical constraints such as thermal turbine generation rate constraint, speed governor dead band and time delay.
Removal of Cu(II) metal ions from aqueous solution by amine functionalized magnetic nanoparticles
Kothavale, V. P.; Karade, V. C.; Waifalkar, P. P.; Sahoo, Subasa C.; Patil, P. S.; Patil, P. B.
2018-04-01
The adsorption behavior of Cu(II) metal cations was investigated on the amine functionalized magnetic nanoparticles (MNPs). TheMNPs were synthesized by thesolvothermal method and functionalized with (3-Aminopropyl)triethoxysilane (APTES). MNPs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and vibrating sample magnetometer (VSM). The MNPs have pure magnetite phase with particle size around 10-12 nm. MNPs exhibits superparamagnetic behavior with asaturation magnetization of 68 emu/g. The maximum 38 % removal efficiency was obtained for Cu(II) metal ions from the aqueous solution.
A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.
Daeyaert, Frits; Deem, Micheal W
2017-01-01
We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Exact solutions for fermionic Green's functions in the Bloch-Nordsieck approximation of QED
International Nuclear Information System (INIS)
Kernemann, A.; Stefanis, N.G.
1989-01-01
A set of new closed-form solutions for fermionic Green's functions in the Bloch-Nordsieck approximation of QED is presented. A manifestly covariant phase-space path-integral method is applied for calculating the n-fermion Green's function in a classical external field. In the case of one and two fermions, explicit expressions for the full Green's functions are analytically obtained, with renormalization carried out in the modified minimal subtraction scheme. The renormalization constants and the corresponding anomalous dimensions are determined. The mass-shell behavior of the two-fermion Green's function is investigated in detail. No assumptions are made concerning the structure of asymptotic states and no IR cutoff is used in the calculations
Hamiltonian Algorithm Sound Synthesis
大矢, 健一
2013-01-01
Hamiltonian Algorithm (HA) is an algorithm for searching solutions is optimization problems. This paper introduces a sound synthesis technique using Hamiltonian Algorithm and shows a simple example. "Hamiltonian Algorithm Sound Synthesis" uses phase transition effect in HA. Because of this transition effect, totally new waveforms are produced.
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Rahmatullah
2018-03-01
Full Text Available We have computed new exact traveling wave solutions, including complex solutions of fractional order Boussinesq-Like equations, occurring in physical sciences and engineering, by applying Exp-function method. The method is blended with fractional complex transformation and modified Riemann-Liouville fractional order operator. Our obtained solutions are verified by substituting back into their corresponding equations. To the best of our knowledge, no other technique has been reported to cope with the said fractional order nonlinear problems combined with variety of exact solutions. Graphically, fractional order solution curves are shown to be strongly related to each other and most importantly, tend to fixate on their integer order solution curve. Our solutions comprise high frequencies and very small amplitude of the wave responses. Keywords: Exp-function method, New exact traveling wave solutions, Modified Riemann-Liouville derivative, Fractional complex transformation, Fractional order Boussinesq-like equations, Symbolic computation
Handbook of Memetic Algorithms
Cotta, Carlos; Moscato, Pablo
2012-01-01
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, ...
Salama, Amgad; Sun, Shuyu; Amin, Mohamed F. El
2015-01-01
In this work, the experimenting fields approach is applied to the numerical solution of the Navier-Stokes equation for incompressible viscous flow. In this work, the solution is sought for both the pressure and velocity fields in the same time. Apparently, the correct velocity and pressure fields satisfy the governing equations and the boundary conditions. In this technique a set of predefined fields are introduced to the governing equations and the residues are calculated. The flow according to these fields will not satisfy the governing equations and the boundary conditions. However, the residues are used to construct the matrix of coefficients. Although, in this setup it seems trivial constructing the global matrix of coefficients, in other setups it can be quite involved. This technique separates the solver routine from the physics routines and therefore makes easy the coding and debugging procedures. We compare with few examples that demonstrate the capability of this technique.
Salama, Amgad
2015-06-01
In this work, the experimenting fields approach is applied to the numerical solution of the Navier-Stokes equation for incompressible viscous flow. In this work, the solution is sought for both the pressure and velocity fields in the same time. Apparently, the correct velocity and pressure fields satisfy the governing equations and the boundary conditions. In this technique a set of predefined fields are introduced to the governing equations and the residues are calculated. The flow according to these fields will not satisfy the governing equations and the boundary conditions. However, the residues are used to construct the matrix of coefficients. Although, in this setup it seems trivial constructing the global matrix of coefficients, in other setups it can be quite involved. This technique separates the solver routine from the physics routines and therefore makes easy the coding and debugging procedures. We compare with few examples that demonstrate the capability of this technique.
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.
2015-07-01
This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the control of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.
International Nuclear Information System (INIS)
Ma Wenxiu; Lee, J.-H.
2009-01-01
A direct approach to exact solutions of nonlinear partial differential equations is proposed, by using rational function transformations. The new method provides a more systematical and convenient handling of the solution process of nonlinear equations, unifying the tanh-function type methods, the homogeneous balance method, the exp-function method, the mapping method, and the F-expansion type methods. Its key point is to search for rational solutions to variable-coefficient ordinary differential equations transformed from given partial differential equations. As an application, the construction problem of exact solutions to the 3+1 dimensional Jimbo-Miwa equation is treated, together with a Baecklund transformation.
International Nuclear Information System (INIS)
Nitej, N.V.; Sharovarov, G.A.
1982-01-01
The method of estimation of counterflow heat exchanger characteristics is presented. Mathematical description of the processes is presented by the mass, energy and pulse conservation equations for both coolants and energy conservation equation for the wall which devides them. In the presence of chemical reactions the system is supplemented by equations, characterizing the kinetics of their progress. The methods of numerical solution of static and dynamic problems have been chosen, and the computer programs on the Fortran language have been developed. The schemes of solution of both problems are so constructed, that the conservation equations are placed in the main program, and such characteristics of the coolants as properties, heat transfer and friction coefficients, the mechanism of chemical reaction are concentrated in the subprogram unit. This allows to create the single method of solution with the flow of single-phase and two-phase coolants of abovecritical and supercritical paramters. The evaluation results of three heat exchangers are given: with heating of N 2 O 4 gas phase by heat of flue gas; with cooling of N 2 O 4 supercritical parameters by water; regenerator on N 2 O 4
In vitro function of random donor platelets stored for 7 days in composol platelet additive solution
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Gupta Ashish
2011-01-01
Full Text Available Background and Aim: Platelets are routinely isolated from whole blood and stored in plasma for 5 days. This study was done to assess the in vitro function of random donor platelets stored for 7 days in composol platelet additive solution at 22°C. Materials and Methods: The study sample included 30 blood donors of both sex in State Blood Bank, C S M Medical University, Lucknow. Random donor platelets were prepared by the platelet-rich plasma method. Whole blood (350 ml was collected in anticoagulant Citrate Phosphate Dextrose Adenine triple blood bags. Random donor platelets were stored for 7 days at 22°C in platelet incubators and agitators with and without additive solution. Results: Platelet swirling was present in all the units at 22°C on day 7 with no evidence of bacterial contamination. Comparison of the mean values of platelet count, platelet factor 3, lactate dehydrogenase, pH, glucose and platelet aggregation showed no significant difference in additive solution while platelet factor 3, glucose and platelet aggregation showed significant difference (P < 0.001 on day 7 without additive solution at 22°C. Conclusion: Our study infers that the platelet viability and aggregation were the best maintained within normal levels on day 7 of storage in platelet additive solution at 22°C. Thus, we may conclude that in vitro storage of random donor platelets with an extended shelf life of 7 days using platelet additive solution may be advocated to improve the inventory of platelets.
Gabor, A.F.; Ommeren, van J.C.W.
2006-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present three facility location problems with stochastic demand and exponential servers, respectively inventory. We present a (1+e,1)-reduction of the facility
Gabor, Adriana F.; van Ommeren, Jan C.W.
2006-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present three facility location problems with stochastic demand and exponential servers, respectively inventory. We present a $(1+\\varepsilon, 1)$-reduction of
Approximation algorithms for facility location problems with discrete subadditive cost functions
Gabor, A.F.; van Ommeren, Jan C.W.
2005-01-01
In this article we focus on approximation algorithms for facility location problems with subadditive costs. As examples of such problems, we present two facility location problems with stochastic demand and exponential servers, respectively inventory. We present a $(1+\\epsilon,1)$- reduction of the
The development of a new algorithm to calculate a survival function in non-parametric ways
International Nuclear Information System (INIS)
Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo
2001-01-01
In this study, a generalized formula of the Kaplan-Meier method is developed. The idea of this algorithm is that the result of the Kaplan-Meier estimator is the same as that of the redistribute-to-the right algorithm. Hence, the result of the Kaplan-Meier estimator is used when we redistribute to the right. This can be explained as the following steps, at first, the same mass is distributed to all the points. At second, when you reach the censored points, you must redistribute the mass of that point to the right according to the following rule; to normalize the masses, which are located to the right of the censored point, and redistribute the mass of the censored point to the right according to the ratio of the normalized mass. Until now, we illustrate the main idea of this algorithm.The meaning of that idea is more efficient than PL-estimator in the sense that it decreases the mass of after that area. Just like a redistribute to the right algorithm, this method is enough for the probability theory
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Hasibun Naher
2012-01-01
Full Text Available We construct new analytical solutions of the (3+1-dimensional modified KdV-Zakharov-Kuznetsev equation by the Exp-function method. Plentiful exact traveling wave solutions with arbitrary parameters are effectively obtained by the method. The obtained results show that the Exp-function method is effective and straightforward mathematical tool for searching analytical solutions with arbitrary parameters of higher-dimensional nonlinear partial differential equation.
Joint density-functional theory and its application to systems in solution
Petrosyan, Sahak A.
The physics of solvation, the interaction of water with solutes, plays a central role in chemistry and biochemistry, and it is essential for the very existence of life. Despite the central importance of water and the advent of the quantum theory early in the twentieth century, the link between the fundamental laws of physics and the observable properties of water remain poorly understood to this day. The central goal of this thesis is to develop a new formalism and framework to make the study of systems (solutes or surfaces) in contact with liquid water as practical and accurate as standard electronic structure calculations without the need for explicit averaging over large ensembles of configurations of water molecules. The thesis introduces a new form of density functional theory for the ab initio description of electronic systems in contact with a molecular liquid environment. This theory rigorously joins an electron density-functional for the electrons of a solute with a classical density-functional theory for the liquid into a single variational principle for the free energy of the combined system. Using the new form of density-functional theory for the ab initio description of electronic systems in contact with a molecular liquid environment, the thesis then presents the first detailed study of the impact of a solvent on the surface chemistry of Cr2O3, the passivating layer of stainless steel alloys. In comparison to a vacuum, we predict that the presence of water has little impact on the adsorption of chloride ions to the oxygen-terminated surface but has a dramatic effect on the binding of hydrogen to that surface. A key ingredient of a successful joint density functional theory is a good approximate functional for describing the solvent. We explore how the simplest examples of the best known class of approximate forms for the classical density functional fail when applied directly to water. The thesis then presents a computationally efficient density-functional
Rapisarda, E; Bettinardi, V; Thielemans, K; Gilardi, M C
2010-07-21
The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.
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Qiang Zhang
2017-09-01
Full Text Available Course keeping is hard to implement under the condition of the propeller stopping or reversing at slow speed for berthing due to the ship's dynamic motion becoming highly nonlinear. To solve this problem, a practical Maneuvering Modeling Group (MMG ship mathematic model with propeller reversing transverse forces and low speed correction is first discussed to be applied for the right-handed single-screw ship. Secondly, a novel PID-based nonlinear feedback algorithm driven by bipolar sigmoid function is proposed. The PID parameters are determined by a closed-loop gain shaping algorithm directly, while the closed-loop gain shaping theory was employed for effects analysis of this algorithm. Finally, simulation experiments were carried out on an LPG ship. It is shown that the energy consumption and the smoothness performance of the nonlinear feedback control are reduced by 4.2% and 14.6% with satisfactory control effects; the proposed algorithm has the advantages of robustness, energy saving and safety in berthing practice.
Feng, Fei; Li, Xianglan; Yao, Yunjun; Liang, Shunlin; Chen, Jiquan; Zhao, Xiang; Jia, Kun; Pintér, Krisztina; McCaughey, J Harry
2016-01-01
Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.
Mateos-Pérez, José María; Soto-Montenegro, María Luisa; Peña-Zalbidea, Santiago; Desco, Manuel; Vaquero, Juan José
2016-02-01
We present a novel segmentation algorithm for dynamic PET studies that groups pixels according to the similarity of their time-activity curves. Sixteen mice bearing a human tumor cell line xenograft (CH-157MN) were imaged with three different (68)Ga-DOTA-peptides (DOTANOC, DOTATATE, DOTATOC) using a small animal PET-CT scanner. Regional activities (input function and tumor) were obtained after manual delineation of regions of interest over the image. The algorithm was implemented under the jClustering framework and used to extract the same regional activities as in the manual approach. The volume of distribution in the tumor was computed using the Logan linear method. A Kruskal-Wallis test was used to investigate significant differences between the manually and automatically obtained volumes of distribution. The algorithm successfully segmented all the studies. No significant differences were found for the same tracer across different segmentation methods. Manual delineation revealed significant differences between DOTANOC and the other two tracers (DOTANOC - DOTATATE, p=0.020; DOTANOC - DOTATOC, p=0.033). Similar differences were found using the leader-follower algorithm. An open implementation of a novel segmentation method for dynamic PET studies is presented and validated in rodent studies. It successfully replicated the manual results obtained in small-animal studies, thus making it a reliable substitute for this task and, potentially, for other dynamic segmentation procedures. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Eyad K Almaita
2017-03-01
Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application. International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17
Akiel, R D; Stepanov, V; Takahashi, S
2017-06-01
Nanodiamond (ND) is an attractive class of nanomaterial for fluorescent labeling, magnetic sensing of biological molecules, and targeted drug delivery. Many of those applications require tethering of target biological molecules on the ND surface. Even though many approaches have been developed to attach macromolecules to the ND surface, it remains challenging to characterize dynamics of tethered molecule. Here, we show high-frequency electron paramagnetic resonance (HF EPR) spectroscopy of nitroxide-functionalized NDs. Nitroxide radical is a commonly used spin label to investigate dynamics of biological molecules. In the investigation, we developed a sample holder to overcome water absorption of HF microwave. Then, we demonstrated HF EPR spectroscopy of nitroxide-functionalized NDs in aqueous solution and showed clear spectral distinction of ND and nitroxide EPR signals. Moreover, through EPR spectral analysis, we investigate dynamics of nitroxide radicals on the ND surface. The demonstration sheds light on the use of HF EPR spectroscopy to investigate biological molecule-functionalized nanoparticles.
Properties of healthcare teaming networks as a function of network construction algorithms.
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Martin S Zand
Full Text Available Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106-108 individual claims per year, making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast
Mohebbi, Akbar
2018-02-01
In this paper we propose two fast and accurate numerical methods for the solution of multidimensional space fractional Ginzburg-Landau equation (FGLE). In the presented methods, to avoid solving a nonlinear system of algebraic equations and to increase the accuracy and efficiency of method, we split the complex problem into simpler sub-problems using the split-step idea. For a homogeneous FGLE, we propose a method which has fourth-order of accuracy in time component and spectral accuracy in space variable and for nonhomogeneous one, we introduce another scheme based on the Crank-Nicolson approach which has second-order of accuracy in time variable. Due to using the Fourier spectral method for fractional Laplacian operator, the resulting schemes are fully diagonal and easy to code. Numerical results are reported in terms of accuracy, computational order and CPU time to demonstrate the accuracy and efficiency of the proposed methods and to compare the results with the analytical solutions. The results show that the present methods are accurate and require low CPU time. It is illustrated that the numerical results are in good agreement with the theoretical ones.
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Eusebio Eduardo Hernández Martinez
2013-01-01
Full Text Available In robotics, solving the direct kinematics problem (DKP for parallel robots is very often more difficult and time consuming than for their serial counterparts. The problem is stated as follows: given the joint variables, the Cartesian variables should be computed, namely the pose of the mobile platform. Most of the time, the DKP requires solving a non-linear system of equations. In addition, given that the system could be non-convex, Newton or Quasi-Newton (Dogleg based solvers get trapped on local minima. The capacity of such kinds of solvers to find an adequate solution strongly depends on the starting point. A well-known problem is the selection of such a starting point, which requires a priori information about the neighbouring region of the solution. In order to circumvent this issue, this article proposes an efficient method to select and to generate the starting point based on probabilistic learning. Experiments and discussion are presented to show the method performance. The method successfully avoids getting trapped on local minima without the need for human intervention, which increases its robustness when compared with a single Dogleg approach. This proposal can be extended to other structures, to any non-linear system of equations, and of course, to non-linear optimization problems.
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Hassan Abdullah Kubba
2015-05-01
Full Text Available The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA with system reduction and restoration. The proposed method (RCGA is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms of the calculated voltages of the generator buses, after a derivation of equations for calculating the voltages of the load busbars. The proposed method was demonstrated on 14-bus IEEE test systems and the practical system 362-busbar IRAQI NATIONAL GRID (ING. The proposed method has reliable convergence, a highly accurate solution and less computing time for on-line applications. The method can conveniently be applied for on-line analysis and planning studies of large power systems.
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Marina Popolizio
2018-01-01
Full Text Available Multiterm fractional differential equations (MTFDEs nowadays represent a widely used tool to model many important processes, particularly for multirate systems. Their numerical solution is then a compelling subject that deserves great attention, not least because of the difficulties to apply general purpose methods for fractional differential equations (FDEs to this case. In this paper, we first transform the MTFDEs into equivalent systems of FDEs, as done by Diethelm and Ford; in this way, the solution can be expressed in terms of Mittag–Leffler (ML functions evaluated at matrix arguments. We then propose to compute it by resorting to the matrix approach proposed by Garrappa and Popolizio. Several numerical tests are presented that clearly show that this matrix approach is very accurate and fast, also in comparison with other numerical methods.
Noniterative accurate algorithm for the exact exchange potential of density-functional theory
International Nuclear Information System (INIS)
Cinal, M.; Holas, A.
2007-01-01
An algorithm for determination of the exchange potential is constructed and tested. It represents a one-step procedure based on the equations derived by Krieger, Li, and Iafrate (KLI) [Phys. Rev. A 46, 5453 (1992)], implemented already as an iterative procedure by Kuemmel and Perdew [Phys. Rev. Lett. 90, 043004 (2003)]. Due to suitable transformation of the KLI equations, we can solve them avoiding iterations. Our algorithm is applied to the closed-shell atoms, from Be up to Kr, within the DFT exchange-only approximation. Using pseudospectral techniques for representing orbitals, we obtain extremely accurate values of total and orbital energies with errors at least four orders of magnitude smaller than known in the literature
International Nuclear Information System (INIS)
Durrans, R.F.
1978-12-01
In order to design reactor structures to withstand the large flow and acoustic forces present it is necessary to know something of their dynamic properties. In many cases these properties cannot be predicted theoretically and it is necessary to determine them experimentally. The algorithm MIDAS (Modal Identification for the Dynamic Analysis of Structures) which has been developed at B.N.L. for extracting these structural properties from experimental data is described. (author)
Lee, Y. C.; Thompson, H. M.; Gaskell, P. H.
2009-12-01
FILMPAR is a highly efficient and portable parallel multigrid algorithm for solving a discretised form of the lubrication approximation to three-dimensional, gravity-driven, continuous thin film free-surface flow over substrates containing micro-scale topography. While generally applicable to problems involving heterogeneous and distributed features, for illustrative purposes the algorithm is benchmarked on a distributed memory IBM BlueGene/P computing platform for the case of flow over a single trench topography, enabling direct comparison with complementary experimental data and existing serial multigrid solutions. Parallel performance is assessed as a function of the number of processors employed and shown to lead to super-linear behaviour for the production of mesh-independent solutions. In addition, the approach is used to solve for the case of flow over a complex inter-connected topographical feature and a description provided of how FILMPAR could be adapted relatively simply to solve for a wider class of related thin film flow problems. Program summaryProgram title: FILMPAR Catalogue identifier: AEEL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 530 421 No. of bytes in distributed program, including test data, etc.: 1 960 313 Distribution format: tar.gz Programming language: C++ and MPI Computer: Desktop, server Operating system: Unix/Linux Mac OS X Has the code been vectorised or parallelised?: Yes. Tested with up to 128 processors RAM: 512 MBytes Classification: 12 External routines: GNU C/C++, MPI Nature of problem: Thin film flows over functional substrates containing well-defined single and complex topographical features are of enormous significance, having a wide variety of engineering
International Nuclear Information System (INIS)
Muehlenbruch, Georg; Das, Marco; Hohl, Christian; Wildberger, Joachim E.; Guenther, Rolf W.; Mahnken, Andreas H.; Rinck, Daniel; Flohr, Thomas G.; Koos, Ralf; Knackstedt, Christian
2006-01-01
The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16 x 0.75 mm; 120 kV; 550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2±1.0 vs. 2.6±0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all P≤0.0001); the limits of agreement for the ejection fraction were 2.3±8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective. (orig.)
Evidence of three-body correlation functions in Rb+ and Sr2+ acetonitrile solutions
D'Angelo, P.; Pavel, N. V.
1999-09-01
The local structure of Sr2+ and Rb+ ions in acetonitrile has been investigated by x-ray absorption spectroscopy (XAS) and molecular dynamics simulations. The extended x-ray absorption fine structure above the Sr and Rb K edges has been interpreted in the framework of multiple scattering (MS) formalism and, for the first time, clear evidence of MS contributions has been found in noncomplexing ion solutions. Molecular dynamics has been used to generate the partial pair and triangular distribution functions from which model χ(k) signals have been constructed. The Sr2+ and Rb+ acetonitrile pair distribution functions show very sharp and well-defined first peaks indicating the presence of a well organized first solvation shell. Most of the linear acetonitrile molecules have been found to be distributed like hedgehog spines around the Sr2+ and Rb+ ions. The presence of three-body correlations has been singled out by the existence of well-defined peaks in the triangular configurations. Excellent agreement has been found between the theoretical and experimental data enforcing the reliability of the interatomic potentials used in the simulations. These results demonstrate the ability of the XAS technique in probing the higher-order correlation functions in solution.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1991-01-01
In recent complicated nuclear systems, there are increasing demands for developing highly advanced procedures for various problems-solvings. Among them keen interests have been paid on man-machine communications to improve both safety and economy factors. Many optimization methods have been good enough to elaborate on these points. In this preliminary note, we will concern with application of linear programming (LP) for this purpose. First we will present a new superior version of the generalized PAPA method (GEPAPA) to solve LP problems. We will then examine its effectiveness when applied to derive dynamic matrix control (DMC) as the LP solution. The approach is to aim at the above goal through a quality control of process that will appear in the system. (author)
Giacometti, Paolo; Perdue, Katherine L; Diamond, Solomon G
2014-05-30
Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest. Copyright © 2014 Elsevier B.V. All rights reserved.
Fisicaro, E; Braibanti, A; Lamb, J D; Oscarson, J L
1990-05-01
The relationships between the chemical properties of a system and the partition function algorithm as applied to the description of multiple equilibria in solution are explained. The partition functions ZM, ZA, and ZH are obtained from powers of the binary generating functions Jj = (1 + kappa j gamma j,i[Y])i tau j, where i tau j = p tau j, q tau j, or r tau j represent the maximum number of sites in sites in class j, for Y = M, A, or H, respectively. Each term of the generating function can be considered an element (ij) of a vector Jj and each power of the cooperativity factor gamma ij,i can be considered an element of a diagonal cooperativity matrix gamma j. The vectors Jj are combined in tensor product matrices L tau = (J1) [J2]...[Jj]..., thus representing different receptor-ligand combinations. The partition functions are obtained by summing elements of the tensor matrices. The relationship of the partition functions with the total chemical amounts TM, TA, and TH has been found. The aim is to describe the total chemical amounts TM, TA, and TH as functions of the site affinity constants kappa j and cooperativity coefficients bj. The total amounts are calculated from the sum of elements of tensor matrices Ll. Each set of indices (pj..., qj..., rj...) represents one element of a tensor matrix L tau and defines each term of the summation. Each term corresponds to the concentration of a chemical microspecies. The distinction between microspecies MpjAqjHrj with ligands bound on specific sites and macrospecies MpAqHR corresponding to a chemical stoichiometric composition is shown. The translation of the properties of chemical model schemes into the algorithms for the generation of partition functions is illustrated with reference to a series of examples of gradually increasing complexity. The equilibria examined concern: (1) a unique class of sites; (2) the protonation of a base with two classes of sites; (3) the simultaneous binding of ligand A and proton H to a
Asiri, Sharefa M.; Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem
2017-01-01
In this paper, an on-line estimation algorithm of the source term in a first order hyperbolic PDE is proposed. This equation describes heat transport dynamics in concentrated solar collectors where the source term represents the received energy. This energy depends on the solar irradiance intensity and the collector characteristics affected by the environmental changes. Control strategies are usually used to enhance the efficiency of heat production; however, these strategies often depend on the source term which is highly affected by the external working conditions. Hence, efficient source estimation methods are required. The proposed algorithm is based on modulating functions method where a moving horizon strategy is introduced. Numerical results are provided to illustrate the performance of the proposed estimator in open and closed loops.
Asiri, Sharefa M.
2017-08-22
In this paper, an on-line estimation algorithm of the source term in a first order hyperbolic PDE is proposed. This equation describes heat transport dynamics in concentrated solar collectors where the source term represents the received energy. This energy depends on the solar irradiance intensity and the collector characteristics affected by the environmental changes. Control strategies are usually used to enhance the efficiency of heat production; however, these strategies often depend on the source term which is highly affected by the external working conditions. Hence, efficient source estimation methods are required. The proposed algorithm is based on modulating functions method where a moving horizon strategy is introduced. Numerical results are provided to illustrate the performance of the proposed estimator in open and closed loops.
DeJong, Jason T; Soga, Kenichi; Banwart, Steven A; Whalley, W Richard; Ginn, Timothy R; Nelson, Douglas C; Mortensen, Brina M; Martinez, Brian C; Barkouki, Tammer
2011-01-06
Carbon sequestration, infrastructure rehabilitation, brownfields clean-up, hazardous waste disposal, water resources protection and global warming-these twenty-first century challenges can neither be solved by the high-energy consumptive practices that hallmark industry today, nor by minor tweaking or optimization of these processes. A more radical, holistic approach is required to develop the sustainable solutions society needs. Most of the above challenges occur within, are supported on, are enabled by or grown from soil. Soil, contrary to conventional civil engineering thought, is a living system host to multiple simultaneous processes. It is proposed herein that 'soil engineering in vivo', wherein the natural capacity of soil as a living ecosystem is used to provide multiple solutions simultaneously, may provide new, innovative, sustainable solutions to some of these great challenges of the twenty-first century. This requires a multi-disciplinary perspective that embraces the science of biology, chemistry and physics and applies this knowledge to provide multi-functional civil and environmental engineering designs for the soil environment. For example, can native soil bacterial species moderate the carbonate cycle in soils to simultaneously solidify liquefiable soil, immobilize reactive heavy metals and sequester carbon-effectively providing civil engineering functionality while clarifying the ground water and removing carbon from the atmosphere? Exploration of these ideas has begun in earnest in recent years. This paper explores the potential, challenges and opportunities of this new field, and highlights one biogeochemical function of soil that has shown promise and is developing rapidly as a new technology. The example is used to propose a generalized approach in which the potential of this new field can be fully realized.
DeJong, Jason T.; Soga, Kenichi; Banwart, Steven A.; Whalley, W. Richard; Ginn, Timothy R.; Nelson, Douglas C.; Mortensen, Brina M.; Martinez, Brian C.; Barkouki, Tammer
2011-01-01
Carbon sequestration, infrastructure rehabilitation, brownfields clean-up, hazardous waste disposal, water resources protection and global warming—these twenty-first century challenges can neither be solved by the high-energy consumptive practices that hallmark industry today, nor by minor tweaking or optimization of these processes. A more radical, holistic approach is required to develop the sustainable solutions society needs. Most of the above challenges occur within, are supported on, are enabled by or grown from soil. Soil, contrary to conventional civil engineering thought, is a living system host to multiple simultaneous processes. It is proposed herein that ‘soil engineering in vivo’, wherein the natural capacity of soil as a living ecosystem is used to provide multiple solutions simultaneously, may provide new, innovative, sustainable solutions to some of these great challenges of the twenty-first century. This requires a multi-disciplinary perspective that embraces the science of biology, chemistry and physics and applies this knowledge to provide multi-functional civil and environmental engineering designs for the soil environment. For example, can native soil bacterial species moderate the carbonate cycle in soils to simultaneously solidify liquefiable soil, immobilize reactive heavy metals and sequester carbon—effectively providing civil engineering functionality while clarifying the ground water and removing carbon from the atmosphere? Exploration of these ideas has begun in earnest in recent years. This paper explores the potential, challenges and opportunities of this new field, and highlights one biogeochemical function of soil that has shown promise and is developing rapidly as a new technology. The example is used to propose a generalized approach in which the potential of this new field can be fully realized. PMID:20829246
Energy Technology Data Exchange (ETDEWEB)
Guais, J C [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1967-07-01
After a brief survey of classical techniques for static optimization, we present a Random seeking method for any function, of an arbitrary number of variables, with constraints. The resulting program is shown and illustrated by some examples. The comparison with classical methods points out the advantages of Random in some cases where analytic procedures fail or require too much calculation time. (author) [French] Apres une rapide revue des differents procedes actuels d'optimisation statique, on expose une methode de recherche aleatoire du minimum (ou du maximum) d'une fonction quelconque, definie sur un nombre theoriquement illimite de parametres independants, avec contraintes. Le programme resultant est presente. Il est illustre par quelques exemples simples et compare a des methodes d'optimisation classiques; Ceci montre en particulier que le programme RANDOM permet une recherche aisee d'extrema dans certains cas ou d'autres programmes ne conduisent pas a des solutions satisfaisantes ou bien demandent un temps calcul prohibitif. (auteur)
Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.
2013-01-01
There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in
Directory of Open Access Journals (Sweden)
Chuanzhi Bai
2010-06-01
Full Text Available This paper deals with the existence of positive solutions for a boundary value problem involving a nonlinear functional differential equation of fractional order $\\alpha$ given by $ D^{\\alpha} u(t + f(t, u_t = 0$, $t \\in (0, 1$, $2 < \\alpha \\le 3$, $ u^{\\prime}(0 = 0$, $u^{\\prime}(1 = b u^{\\prime}(\\eta$, $u_0 = \\phi$. Our results are based on the nonlinear alternative of Leray-Schauder type and Krasnosel'skii fixed point theorem.
International Nuclear Information System (INIS)
Dehghan, Mehdi; Shakourifar, Mohammad; Hamidi, Asgar
2009-01-01
The purpose of this study is to implement Adomian-Pade (Modified Adomian-Pade) technique, which is a combination of Adomian decomposition method (Modified Adomian decomposition method) and Pade approximation, for solving linear and nonlinear systems of Volterra functional equations. The results obtained by using Adomian-Pade (Modified Adomian-Pade) technique, are compared to those obtained by using Adomian decomposition method (Modified Adomian decomposition method) alone. The numerical results, demonstrate that ADM-PADE (MADM-PADE) technique, gives the approximate solution with faster convergence rate and higher accuracy than using the standard ADM (MADM).
Functions of chalcogenide electrodes in solutions of complexing reagents and interfering ions
International Nuclear Information System (INIS)
Kiyanskij, V.V.
1990-01-01
The possibility to modify chalcogenide electrodes and their behaviour in solutions of complexing reagents for the development of new methods of potentiometric titration has been studied. It is shown that complexing reagents (EDTA, cupferron, 8-hydroxyquinoline, sodium dithiocarbaminate) and Cu(2), Hg(2) produce a strong effect on the functions of Ag, Cu, Cd, Pb - selective electrodes, which is used for titration of potential-determining and non-potential-determining ions ions (Sr 2+ , La 3+ etc.) and also for modification of sulfide-selecting electrode. A method of potentiometric titration of sulfates and chlorides with modified Cd- and Ag-selective electrodes is suggested
Directory of Open Access Journals (Sweden)
Supriya Aggarwal
2012-01-01
Full Text Available One of the most important steps in spectral analysis is filtering, where window functions are generally used to design filters. In this paper, we modify the existing architecture for realizing the window functions using CORDIC processor. Firstly, we modify the conventional CORDIC algorithm to reduce its latency and area. The proposed CORDIC algorithm is completely scale-free for the range of convergence that spans the entire coordinate space. Secondly, we realize the window functions using a single CORDIC processor as against two serially connected CORDIC processors in existing technique, thus optimizing it for area and latency. The linear CORDIC processor is replaced by a shift-add network which drastically reduces the number of pipelining stages required in the existing design. The proposed design on an average requires approximately 64% less pipeline stages and saves up to 44.2% area. Currently, the processor is designed to implement Blackman windowing architecture, which with slight modifications can be extended to other widow functions as well. The details of the proposed architecture are discussed in the paper.
Directory of Open Access Journals (Sweden)
Cristinel Mortici
2015-01-01
Full Text Available In this survey we present our recent results on analysis of gamma function and related functions. The results obtained are in the theory of asymptotic analysis, approximation of gamma and polygamma functions, or in the theory of completely monotonic functions. The motivation of this first part is the work of C. Mortici [Product Approximations via Asymptotic Integration Amer. Math. Monthly 117 (2010 434-441] where a simple strategy for constructing asymptotic series is presented. The classical asymptotic series associated to Stirling, Wallis, Glaisher-Kinkelin are rediscovered. In the second section we discuss some new inequalities related to Landau constants and we establish some asymptotic formulas.
Mahalakshmi; Murugesan, R.
2018-04-01
This paper regards with the minimization of total cost of Greenhouse Gas (GHG) efficiency in Automated Storage and Retrieval System (AS/RS). A mathematical model is constructed based on tax cost, penalty cost and discount cost of GHG emission of AS/RS. A two stage algorithm namely positive selection based clonal selection principle (PSBCSP) is used to find the optimal solution of the constructed model. In the first stage positive selection principle is used to reduce the search space of the optimal solution by fixing a threshold value. In the later stage clonal selection principle is used to generate best solutions. The obtained results are compared with other existing algorithms in the literature, which shows that the proposed algorithm yields a better result compared to others.
Work function tuning of tin-doped indium oxide electrodes with solution-processed lithium fluoride
Energy Technology Data Exchange (ETDEWEB)
Ow-Yang, C.W., E-mail: cleva@sabanciuniv.edu [Materials Science and Engineering Program, Sabanci University, Orhanli, Tuzla, 34956 Istanbul (Turkey); Nanotechnology Application Center, Sabanci University, Orhanli, Tuzla, 34956 Istanbul (Turkey); Jia, J. [Graduate School of Science and Engineering, Aoyama Gakuin University, 5-10-1 Fuchinobe, Chuo, Sagamihara, Kanagawa 252-5258 (Japan); Aytun, T. [Materials Science and Engineering Program, Sabanci University, Orhanli, Tuzla, 34956 Istanbul (Turkey); Zamboni, M.; Turak, A. [Department of Engineering Physics, McMaster University, Hamilton, Ontario L8S 4L8 (Canada); Saritas, K. [Materials Science and Engineering Program, Sabanci University, Orhanli, Tuzla, 34956 Istanbul (Turkey); Shigesato, Y. [Graduate School of Science and Engineering, Aoyama Gakuin University, 5-10-1 Fuchinobe, Chuo, Sagamihara, Kanagawa 252-5258 (Japan)
2014-05-30
Solution-processed lithium fluoride (sol-LiF) nanoparticles synthesized in polymeric micelle nanoreactors enabled tuning of the surface work function of tin-doped indium oxide (ITO) films. The micelle reactors provided the means for controlling surface coverage by progressively building up the interlayer through alternating deposition and plasma etch removal of the polymer. In order to determine the surface coverage and average interparticle distance, spatial point pattern analysis was applied to scanning electron microscope images of the nanoparticle dispersions. The work function of the sol-LiF modified ITO, obtained from photoelectron emission yield spectroscopy analysis, was shown to increase with surface coverage of the sol-LiF particles, suggesting a lateral depolarization effect. Analysis of the photoelectron emission energy distribution in the near threshold region revealed the contribution of surface states for surface coverage in excess of 14.1%. Optimization of the interfacial barrier was achieved through contributions from both work function modification and surface states. - Highlights: • Work function of indium tin oxide increased with LiF nanoparticle coverage. • Work function was analyzed via photoelectron emission yield (PEYS). • At higher surface coverage, the energy distribution of PEYS increased. • Pre-threshold increase in PEYS consistent with emission from surface states.
Narula, Sukrit; Shameer, Khader; Salem Omar, Alaa Mabrouk; Dudley, Joel T; Sengupta, Partho P
2016-11-29
Machine-learning models may aid cardiac phenotypic recognition by using features of cardiac tissue deformation. This study investigated the diagnostic value of a machine-learning framework that incorporates speckle-tracking echocardiographic data for automated discrimination of hypertrophic cardiomyopathy (HCM) from physiological hypertrophy seen in athletes (ATH). Expert-annotated speckle-tracking echocardiographic datasets obtained from 77 ATH and 62 HCM patients were used for developing an automated system. An ensemble machine-learning model with 3 different machine-learning algorithms (support vector machines, random forests, and artificial neural networks) was developed and a majority voting method was used for conclusive predictions with further K-fold cross-validation. Feature selection using an information gain (IG) algorithm revealed that volume was the best predictor for differentiating between HCM ands. ATH (IG = 0.24) followed by mid-left ventricular segmental (IG = 0.134) and average longitudinal strain (IG = 0.131). The ensemble machine-learning model showed increased sensitivity and specificity compared with early-to-late diastolic transmitral velocity ratio (p 13 mm. In this subgroup analysis, the automated model continued to show equal sensitivity, but increased specificity relative to early-to-late diastolic transmitral velocity ratio, e', and strain. Our results suggested that machine-learning algorithms can assist in the discrimination of physiological versus pathological patterns of hypertrophic remodeling. This effort represents a step toward the development of a real-time, machine-learning-based system for automated interpretation of echocardiographic images, which may help novice readers with limited experience. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
DEFF Research Database (Denmark)
Jensen, Peter Bjerre; Lysgaard, Steen; Quaade, Ulrich J.
2014-01-01
electrolyte membrane fuel cells (PEMFC). We use genetic algorithms (GAs) to search for materials containing up to three different metals (alkaline-earth, 3d and 4d) and two different halides (Cl, Br and I) – almost 27000 combinations, and have identified novel mixtures, with significantly improved storage......Metal halide ammines have great potential as a future, high-density energy carrier in vehicles. So far known materials, e.g. Mg(NH3)6Cl2 and Sr(NH3)8Cl2, are not suitable for automotive, fuel cell applications, because the release of ammonia is a multi-step reaction, requiring too much heat...
Energy Technology Data Exchange (ETDEWEB)
Berkolaiko, G. [Department of Mathematics, Texas A and M University, College Station, Texas 77843-3368 (United States); Kuipers, J. [Institut für Theoretische Physik, Universität Regensburg, D-93040 Regensburg (Germany)
2013-12-15
Electronic transport through chaotic quantum dots exhibits universal behaviour which can be understood through the semiclassical approximation. Within the approximation, calculation of transport moments reduces to codifying classical correlations between scattering trajectories. These can be represented as ribbon graphs and we develop an algorithmic combinatorial method to generate all such graphs with a given genus. This provides an expansion of the linear transport moments for systems both with and without time reversal symmetry. The computational implementation is then able to progress several orders further than previous semiclassical formulae as well as those derived from an asymptotic expansion of random matrix results. The patterns observed also suggest a general form for the higher orders.
Xu, Xiaonong; Lu, Dingwei; Xu, Xibin; Yu, Yang; Gu, Min
2017-09-01
The Halbach type hollow cylindrical permanent magnet array (HCPMA) is a volume compact and energy conserved field source, which have attracted intense interests in many practical applications. Here, using the complex variable integration method based on the Biot-Savart Law (including current distributions inside the body and on the surfaces of magnet), we derive analytical field solutions to an ideal multipole HCPMA in entire space including the interior of magnet. The analytic field expression inside the array material is used to construct an analytic demagnetization function, with which we can explain the origin of demagnetization phenomena in HCPMA by taking into account an ideal magnetic hysteresis loop with finite coercivity. These analytical field expressions and demagnetization functions provide deeper insight into the nature of such permanent magnet array systems and offer guidance in designing optimized array system.
International Nuclear Information System (INIS)
Kim, M; Hyun, W J; Mun, S C; Park, O O
2015-01-01
Chemically derived graphenes were assembled into functional composite materials using solution process from stable solvent dispersion. We have developed foldable electronic circuits on paper substrates using vacuum filtration of graphene nanoplates dispersion and a selective transfer process without need for special equipment. The electronic circuits on paper substrates revealed only a small change in conductance under various folding angles and maintained an electronic path after repetitive folding and unfolding. We also prepared flexible. binder-free graphene paper-like materials by addition of graphene oxide as a film stabilizer. This graphene papers showed outstanding electrical conductivity up to 26,000 S/m and high charge capacity as an anode in lithium-ion battery without any post-treatments. For last case, multi-functional thin film structures of graphene nanoplates were fabricated by using layer-by-layer assembly technique, showing optical transparency, electrical conductivity and enhanced gas barrier property. (paper)
Konishi, Kana; Kimura, Tetsuya; Yuhaku, Atsushi; Kurihara, Toshiyuki; Fujimoto, Masahiro; Hamaoka, Takafumi; Sanada, Kiyoshi
2017-01-01
A decline in executive function could have a negative influence on the control of actions in dynamic situations, such as sports activities. Mouth rinsing with a carbohydrate solution could serve as an effective treatment for preserving the executive function in exercise. The purpose of this study was to examine the effects of mouth rinsing with a carbohydrate solution on executive function after sustained moderately high-intensity exercise. Eight young healthy participants completed 65 min of running at 75% V̇O 2 max with two mouth-rinsing conditions: with a carbohydrate solution (CHO) or with water (CON). Executive function was assessed before and after exercise by using the incongruent task of the Stroop Color and Word Test. The levels of blood glucose; and plasma adrenocorticotropic hormone (ACTH), epinephrine, and norepinephrine (NE) were evaluated. A two-way repeated-measures ANOVA, with condition (CHO and CON) and time (pre-exercise and post-exercise) as factors, was used to examine the main and interaction effects on the outcome measures. The reaction time in the incongruent condition of the Stroop test significantly increased after exercise in CON (pre-exercise 529 ± 45 ms vs. post-exercise 547 ± 60 ms, P = 0.029) but not in CHO (pre-exercise 531 ± 54 ms vs. post-exercise 522 ± 80 ms), which resulted in a significant interaction (condition × time) on the reaction time ( P = 0.028). The increased reaction time in CON indicates a decline in the executive function, which was attenuated in CHO. Increases in plasma epinephrine and NE levels demonstrated a trend toward attenuation accompanying CHO ( P exercise, and that such attenuation seems to be unrelated to carbohydrate metabolic pathway but rather attributed, in part, to the inhibition of the excessive release of stress hormones.
International Nuclear Information System (INIS)
Cao Rui; Zhang Jian
2013-01-01
In this paper, the trial function method is extended to study the generalized nonlinear Schrödinger equation with time-dependent coefficients. On the basis of a generalized traveling wave transformation and a trial function, we investigate the exact envelope traveling wave solutions of the generalized nonlinear Schrödinger equation with time-dependent coefficients. Taking advantage of solutions to trial function, we successfully obtain exact solutions for the generalized nonlinear Schrödinger equation with time-dependent coefficients under constraint conditions. (general)
Fazayel, A. S.; Khorasani, M.; Sarabi, A. A.
2018-05-01
In this study, the effects of polycarboxylate derivatives with different comonomers and functional groups on the control or reduction of corrosion in steel specimens were evaluated through electrochemical impedance spectroscopy (EIS) and potentiodynamic analysis. A highly alkaline contaminated concrete pore solution (CPS) containing chlorides was used to simulate the pitting corrosion, and according to the results, the mechanism of inhibitive action was determined. Both the inhibition efficiency and pitting corrosion inhibition of methacrylate-copolymers were in the order of poly methacrylate-co acrylamide > poly methacrylate-co-2-acrylamido-2 methylpropane sulfonic acid > poly methacrylate-co-hydroxyethyl methacrylate. In addition, the corrosion potential of steel specimens in all studied concentrations of NaCl with different concentrations of polymethacrylate-co acrylamide (as the best inhibitor in this study) in saturated Ca(OH)2 solution showed almost an identical trend. Polymethacrylic acid-co-acrylamide showed a 92.35% inhibitor efficiency in the saturated Ca(OH)2 solution containing 1.8 wt.% chlorides and could effectively reduce the corrosion rate. Even at 3.5 wt.% of NaCl, this inhibitor could remarkably reduce the destructive effect of chloride ion attacks on the steel surface and passive film. The inhibition effect of these polymeric inhibitors seemed to be due to the formation of a barrier layer on the metal surface, approved by the well-known adsorption mechanism of organic molecules at the metal/solution interface. The results of SEM, EDS and AFM investigations were also in agreement with the outcomes of electrochemical studies.
Finite medium Green's function solutions to nuclide transport in porous media
International Nuclear Information System (INIS)
Oston, S.G.
1979-01-01
Current analytical techniques for predicting the transport of nuclides in porous materials center on the Green's function approach - i.e., determining the response characteristics of a geologic pathway to an impulse function input. To data, the analyses all have set the boundary conditions needed to solve the 1-D transport equation as though each pathway were infinite in length. The purpose of this work is to critically examine the effect that this infinite pathway assumption has on Green's function models of nuclide transport in porous media. The work described herein has directly attacked the more difficult problem of obtaining suitable Green's functions for finite pathways whose dimensions, in fact, may not be much greater than the diffusion length. Two different finite media Green's functions describing the nuclide mass flux have been determined, depending on whether the pathway is terminated by a high or a low flow resistance at the outlet end. Pulse shapes and peak amplitudes have been computed for each Green's function over a wide range of geohydrologic parameters. These results have been compared to both infinite and semi-infinite medium solutions. It was found that predicted pulse shapes are quite sensitive to selection of a Green's function model for short pathways only. For long pathways all models tend toward a symmetric Gaussian flux-time history at the outlet. Thus, the results of our previous waste transport studies using the infinite pathway assumption are still generally valid because they always included at least one long pathway. It was also found that finite medium models offer some unique computational advantages for evaluating nuclide transport in a series of connecting pathways
Energy Technology Data Exchange (ETDEWEB)
Ray, Rupashree Shyama
2009-02-10
In this work, the complexation of uranium in its most stable oxidation state VI in aqueous solution was studied computationally, within the framework of density functional (DF) theory. The thesis is divided into the following parts: Chapter 2 briefly summarizes the relevant general aspects of actinide chemistry and then focuses on actinide environmental chemistry. Experimental results on hydrolysis, actinide complexation by carboxylic acids, and humic substances are presented to establish a background for the subsequent discussion. Chapter 3 describes the computational method used in this work and the relevant features of the parallel quantum chemistry code PARAGAUSS employed. First, the most relevant basics of the applied density functional approach are presented focusing on relativistic effects. Then, the treatment of solvent effects, essential for an adequate modeling of actinide species in aqueous solution, will be introduced. At the end of this chapter, computational parameters and procedures will be summarized. Chapter 4 presents the computational results including a comparison to available experimental data. In the beginning, the mononuclear hydrolysis product of UO{sub 2}{sup 2+}, [UO{sub 2}OH]{sup +}, will be discussed. The second part deals with actinide complexation by carboxylate ligands. First of all the coordination number for uranylacetate will be discussed with respect to implications for the complexation of actinides by humic substances followed by the uranyl complexation of aromatic carboxylic acids in comparison to earlier results for aliphatic ones. In the end, the ternary uranyl-hydroxo-acetate are discussed, as models of uranyl humate complexation at ambient condition.
International Nuclear Information System (INIS)
Ray, Rupashree Shyama
2009-01-01
In this work, the complexation of uranium in its most stable oxidation state VI in aqueous solution was studied computationally, within the framework of density functional (DF) theory. The thesis is divided into the following parts: Chapter 2 briefly summarizes the relevant general aspects of actinide chemistry and then focuses on actinide environmental chemistry. Experimental results on hydrolysis, actinide complexation by carboxylic acids, and humic substances are presented to establish a background for the subsequent discussion. Chapter 3 describes the computational method used in this work and the relevant features of the parallel quantum chemistry code PARAGAUSS employed. First, the most relevant basics of the applied density functional approach are presented focusing on relativistic effects. Then, the treatment of solvent effects, essential for an adequate modeling of actinide species in aqueous solution, will be introduced. At the end of this chapter, computational parameters and procedures will be summarized. Chapter 4 presents the computational results including a comparison to available experimental data. In the beginning, the mononuclear hydrolysis product of UO_2"2"+, [UO_2OH]"+, will be discussed. The second part deals with actinide complexation by carboxylate ligands. First of all the coordination number for uranylacetate will be discussed with respect to implications for the complexation of actinides by humic substances followed by the uranyl complexation of aromatic carboxylic acids in comparison to earlier results for aliphatic ones. In the end, the ternary uranyl-hydroxo-acetate are discussed, as models of uranyl humate complexation at ambient condition.
Energy Technology Data Exchange (ETDEWEB)
Malhotra, M. [Stanford Univ., CA (United States)
1996-12-31
Finite-element discretizations of time-harmonic acoustic wave problems in exterior domains result in large sparse systems of linear equations with complex symmetric coefficient matrices. In many situations, these matrix problems need to be solved repeatedly for different right-hand sides, but with the same coefficient matrix. For instance, multiple right-hand sides arise in radiation problems due to multiple load cases, and also in scattering problems when multiple angles of incidence of an incoming plane wave need to be considered. In this talk, we discuss the iterative solution of multiple linear systems arising in radiation and scattering problems in structural acoustics by means of a complex symmetric variant of the BL-QMR method. First, we summarize the governing partial differential equations for time-harmonic structural acoustics, the finite-element discretization of these equations, and the resulting complex symmetric matrix problem. Next, we sketch the special version of BL-QMR method that exploits complex symmetry, and we describe the preconditioners we have used in conjunction with BL-QMR. Finally, we report some typical results of our extensive numerical tests to illustrate the typical convergence behavior of BL-QMR method for multiple radiation and scattering problems in structural acoustics, to identify appropriate preconditioners for these problems, and to demonstrate the importance of deflation in block Krylov-subspace methods. Our numerical results show that the multiple systems arising in structural acoustics can be solved very efficiently with the preconditioned BL-QMR method. In fact, for multiple systems with up to 40 and more different right-hand sides we get consistent and significant speed-ups over solving the systems individually.
Directory of Open Access Journals (Sweden)
Okiljević Z.
2014-01-01
Full Text Available The assessment of functional work capacity based on the biological function of the body and a specific job demands and job characteristics, determine whether a person is capable to do the job or group of jobs. Evaluation of work capacity (EWC railway workers is conducted according to the program of Regulations for the former and periodic examinations of employees in workplaces with high risk published in the Official Gazette of RS no. 120/ 07 and 655. Regulations on health conditions to be met by railway workers, who are directly involved in railway transport. One of the most common chronic diseases during EWC is chronic obstructive pulmonary disease (COPD. The definition of contraindications for use of railway employees with COPD given by Ordinance 655 is in very general terms, trying to make it easier and improve the quality of assessment of work capacity, we have developed an algorithm for the assessment of work ability among these workers. When doubt the existence of COPD should first prove that the disease exists, according to GOLD (Global Initiative for Chronic Obstructive Lung Disease guidelines, and for occupational medicine we considered important to clarify and standardize the assessment criteria for EWC, which resulting in a diagnostic algorithm for EWC. It is also important to know which type of job will worker to do. Application of a diagnostic algorithm in EWC will allow optimal assessment of disease severity in railway and other workers suffering of COPD working at the workplace with an increased risk efficacy treatment evaluation; assess compensation of functional defects and determine schedule of periodical examination.
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R. Ghiasi
2017-09-01
Full Text Available Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW is proposed for Extreme Learning Machine (ELM algorithm to improve the accuracy of detecting multiple damages in structural systems. ELM is used as metamodel (surrogate model of exact finite element analysis of structures in order to efficiently reduce the computational cost through updating process. In the proposed two-step method, first a damage index, based on Frequency Response Function (FRF of the structure, is used to identify the location of damages. In the second step, the severity of damages in identified elements is detected using ELM. In order to evaluate the efficacy of ELM, the results obtained from the proposed kernel were compared with other kernels proposed for ELM as well as Least Square Support Vector Machine algorithm. The solved numerical problems indicated that ELM algorithm accuracy in detecting structural damages is increased drastically in case of using LPW kernel.
Forsström, J
1992-01-01
The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.
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Gh. Assadipour
2012-01-01
Full Text Available
ENGLISH ABSTRACT:The trade-off between time, cost, and quality is one of the important problems of project management. This problem assumes that all project activities can be executed in different modes of cost, time, and quality. Thus a manager should select each activity’s mode such that the project can meet the deadline with the minimum possible cost and the maximum achievable quality. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimisation method. The proposed algorithm provides project managers with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Three metrics are employed for evaluating the performance of the algorithm, appraising the diversity and convergence of the achieved Pareto fronts. Finally a comparison is made between CellDE and another meta-heuristic available in the literature. The results show the superiority of CellDE.
AFRIKAANSE OPSOMMING: ‘n Balans tussen tyd, koste en gehalte is een van die belangrike probleme van projekbestuur. Die vraagstuk maak gewoonlik die aanname dat alle projekaktiwiteite uitgevoer kan word op uiteenlopende wyses wat verband hou met koste, tyd en gehalte. ‘n Projekbestuurder selekteer gewoonlik die uitvoeringsmetodes sodanig per aktiwiteit dat gehoor gegegee word aan minimum koste en maksimum gehalte teen die voorwaarde van voltooiingsdatum wat bereik moet word.
Aangesien die beskrewe problem NP-hard is, word dit behandel ten opsigte van konflikterende doelwitte met ‘n multidoelwit metaheuristiese metode (CellDE. Die metode is ‘n hibride-sellulêre genetiese algoritme. Die algoritme lewer aan die besluitvormer ‘n versameling van ongedomineerde of Pareto
Rahmatullah; Ellahi, Rahmat; Mohyud-Din, Syed Tauseef; Khan, Umar
2018-03-01
We have computed new exact traveling wave solutions, including complex solutions of fractional order Boussinesq-Like equations, occurring in physical sciences and engineering, by applying Exp-function method. The method is blended with fractional complex transformation and modified Riemann-Liouville fractional order operator. Our obtained solutions are verified by substituting back into their corresponding equations. To the best of our knowledge, no other technique has been reported to cope with the said fractional order nonlinear problems combined with variety of exact solutions. Graphically, fractional order solution curves are shown to be strongly related to each other and most importantly, tend to fixate on their integer order solution curve. Our solutions comprise high frequencies and very small amplitude of the wave responses.
Golden Sine Algorithm: A Novel Math-Inspired Algorithm
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TANYILDIZI, E.
2017-05-01
Full Text Available In this study, Golden Sine Algorithm (Gold-SA is presented as a new metaheuristic method for solving optimization problems. Gold-SA has been developed as a new search algorithm based on population. This math-based algorithm is inspired by sine that is a trigonometric function. In the algorithm, random individuals are created as many as the number of search agents with uniform distribution for each dimension. The Gold-SA operator searches to achieve a better solution in each iteration by trying to bring the current situation closer to the target value. The solution space is narrowed by the golden section so that the areas that are supposed to give only good results are scanned instead of the whole solution space scan. In the tests performed, it is seen that Gold-SA has better results than other population based methods. In addition, Gold-SA has fewer algorithm-dependent parameters and operators than other metaheuristic methods, increasing the importance of this method by providing faster convergence of this new method.
J(l)-unitary factorization and the Schur algorithm for Nevanlinna functions in an indefinite setting
Alpay, D.; Dijksma, A.; Langer, H.
2006-01-01
We introduce a Schur transformation for generalized Nevanlinna functions and show that it can be used in obtaining the unique minimal factorization of a class of rational J(l)-unitary 2 x 2 matrix functions into elementary factors from the same class. (c) 2006 Elsevier Inc. All rights reserved.
A Multilevel Search Algorithm for the Maximization of Submodular Functions
Goldengorin, Boris; Ghosh, Diptesh
2004-01-01
We consider the objective function of a simple recourse problem with fixed technology matrix and integer second-stage variables. Separability due to the simple recourse structure allows to study a one-dimensional version instead. Based on an explicit formula for the objective function, we derive a
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Mohamed Abdalla Darwish
2014-01-01
Full Text Available We study a generalized fractional quadratic functional-integral equation of Erdélyi-Kober type in the Banach space BC(ℝ+. We show that this equation has at least one asymptotically stable solution.
Ahmed M. A. El-Sayed; Ebtisam O. Bin-Taher
2011-01-01
In this article, we prove the existence of positive nondecreasing solutions for a multi-term fractional-order functional differential equations. We consider Cauchy boundary problems with: nonlocal conditions, two-point boundary conditions, integral conditions, and deviated arguments.
Optimally stopped variational quantum algorithms
Vinci, Walter; Shabani, Alireza
2018-04-01
Quantum processors promise a paradigm shift in high-performance computing which needs to be assessed by accurate benchmarking measures. In this article, we introduce a benchmark for the variational quantum algorithm (VQA), recently proposed as a heuristic algorithm for small-scale quantum processors. In VQA, a classical optimization algorithm guides the processor's quantum dynamics to yield the best solution for a given problem. A complete assessment of the scalability and competitiveness of VQA should take into account both the quality and the time of dynamics optimization. The method of optimal stopping, employed here, provides such an assessment by explicitly including time as a cost factor. Here, we showcase this measure for benchmarking VQA as a solver for some quadratic unconstrained binary optimization. Moreover, we show that a better choice for the cost function of the classical routine can significantly improve the performance of the VQA algorithm and even improve its scaling properties.
Xia, Ya-Rong; Zhang, Shun-Li; Xin, Xiang-Peng
2018-03-01
In this paper, we propose the concept of the perturbed invariant subspaces (PISs), and study the approximate generalized functional variable separation solution for the nonlinear diffusion-convection equation with weak source by the approximate generalized conditional symmetries (AGCSs) related to the PISs. Complete classification of the perturbed equations which admit the approximate generalized functional separable solutions (AGFSSs) is obtained. As a consequence, some AGFSSs to the resulting equations are explicitly constructed by way of examples.
International Nuclear Information System (INIS)
Chen Jinlong; Gao Yingchun; Xu, ZhiBing; Wu, GenHua; Chen, YouCun; Zhu, ChangQing
2006-01-01
Mono-disperse CdSe nanoclusters have been prepared facilely and functionalized with L-cysteine through two steps by using safe and low cost substances. They are water-soluble and biocompatible. Especially these functionalized quantum dots can be stably soluble in water more than for 30 days, and the intensity of fluorescence and absorbance was decreased less than 15% of fresh prepared CdSe colloids. These functionalized CdSe QDs exhibited strong specific affinity for mercury (II) through QDs interface functional groups. Based on the quenching of fluorescence signals of functionalized CdSe QDs at 530 nm and no obvious wavelength shift or no new emission band in present of Hg (II) at pH 7.75 of phosphate buffer solution, a simple, rapid and specific array for Hg (II) was proposed. In comparison with conventional organic fluorophores, these nanoparticles are brighter, more stable against photobleaching, and do not suffer from blinking. Under optimum conditions, the response of linearly proportional to the concentration of Hg (II) between 0 and 2.0 x 10 -6 mol L -1 , and the limit of detection is 6.0 x 10 -9 mol L -1 . The relative standard deviation of six replicate measurements is 1.8% for 1.0 x 10 -7 mol L -1 Hg (II). The mechanism of reaction is also discussed. The proposed method was successfully applied for Hg (II) detection in four real samples with a satisfactory result that was obtained by cold vapor atomic fluorescence spectrometry (CV-AFS)
Yu, Jiyang; Silva, Jose; Califano, Andrea
2016-01-15
Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives. Indeed, rigorous statistical analysis of high-throughput FG screening data remains challenging, particularly when integrative analyses are used to combine multiple sh/sgRNAs targeting the same gene in the library. We use large RNAi and CRISPR repositories that are publicly available to evaluate a novel meta-analysis approach for FG screens via Bayesian hierarchical modeling, Screening Bayesian Evaluation and Analysis Method (ScreenBEAM). Results from our analysis show that the proposed strategy, which seamlessly combines all available data, robustly outperforms classical algorithms developed for microarray data sets as well as recent approaches designed for next generation sequencing technologies. Remarkably, the ScreenBEAM algorithm works well even when the quality of FG screens is relatively low, which accounts for about 80-95% of the public datasets. R package and source code are available at: https://github.com/jyyu/ScreenBEAM. ac2248@columbia.edu, jose.silva@mssm.edu, yujiyang@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Removal of anionic azo dyes from aqueous solution by functional ionic liquid cross-linked polymer
International Nuclear Information System (INIS)
Gao, Hejun; Kan, Taotao; Zhao, Siyuan; Qian, Yixia; Cheng, Xiyuan; Wu, Wenli; Wang, Xiaodong; Zheng, Liqiang
2013-01-01
Highlights: • Equilibrium, kinetic and thermodynamic of adsorption of dyes onto PDVB-IL was investigated. • PDVB-IL has a high adsorption capacity to treat dyes solution. • Higher adsorption capacity is due to the functional groups of PDVB-IL. • Molecular structure of dyes influences the adsorption capacity. -- Abstract: A novel functional ionic liquid based cross-linked polymer (PDVB-IL) was synthesized from 1-aminoethyl-3-vinylimidazolium chloride and divinylbenzene for use as an adsorbent. The physicochemical properties of PDVB-IL were investigated by Fourier transform infrared spectroscopy, scanning electron microscopy and thermogravimetric analysis. The adsorptive capacity was investigated using anionic azo dyes of orange II, sunset yellow FCF, and amaranth as adsorbates. The maximum adsorption capacity could reach 925.09, 734.62, and 547.17 mg/g for orange II, sunset yellow FCF and amaranth at 25 °C, respectively, which are much better than most of the other adsorbents reported earlier. The effect of pH value was investigated in the range of 1–8. The result shows that a low pH value is found to favor the adsorption of those anionic azo dyes. The adsorption kinetics and isotherms are well fitted by a pseudo second-order model and Langmuir model, respectively. The adsorption process is found to be dominated by physisorption. The introduction of functional ionic liquid moieties into cross-linked poly(divinylbenzene) polymer constitutes a new and efficient kind of adsorbent
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Mohammad Norisepehr
2013-12-01
Full Text Available Background & Objectives: Nitrate and nitrite compounds pollution of groundwater resources in recent years which recently their mean concentration due to enhancement of different kind of municipal, industrial and agriculture waste water, were increased. The most common source of nitrates entering the water include chemical fertilizers and animal manure in agriculture, septic tank effluent, wastewater, wastewater treatment plants, animal and plant residue analysis on the ground of non-sanitary disposal of solid waste and the use of absorbing wells for sewage disposal. Materials and methods: This experimental study is applied to the nitrate removal using chitosan in laboratory scale at ambient temperature and the design of the system was Batch. Effects of parameters such as pH, contact time, initial concentration and adsorbent concentration of nitrate on nitrate removal from aqueous solution was studied. Results: Function of chitosan in synthetic aqueous solution and drinking water according to the slurry system results, the optimum condition was obtained at pH=4, 20 min contact time and increasing the initial concentration of nitrate enhance the adsorption capacity of chitosan. Also optimum dosage of adsorbent was obtained at 0.5 g/l. The data obtained from the experiments of adsorbent isotherm were analyzed using Langmuir and Freundlich isotherm models. The Langmuir equation was found to be the best fitness with the experimental data (R2>0.93. Conclusion: Although efficiency of Nitrate removal in synthetic aqueous solution was better than drinking water, adsorption process using chitosan as an option for the design and selection nitrate removal should be considered in order to achieve environmental standards.
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Xiangrong Li
Full Text Available It is generally acknowledged that the conjugate gradient (CG method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang
2015-01-01
It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
International Nuclear Information System (INIS)
Ignat'yev, A O
2003-01-01
A system of ordinary differential equations with impulse action at fixed moments of time is considered. The system is assumed to have the zero solution. It is shown that the existence of a corresponding Lyapunov function is a necessary and sufficient condition for the uniform asymptotic stability of the zero solution. Restrictions on perturbations of the right-hand sides of differential equations and impulse actions are obtained under which the uniform asymptotic stability of the zero solution of the 'unperturbed' system implies the uniform asymptotic stability of the zero solution of the 'perturbed' system
Sugisaki, Kenji; Yamamoto, Satoru; Nakazawa, Shigeaki; Toyota, Kazuo; Sato, Kazunobu; Shiomi, Daisuke; Takui, Takeji
2016-08-18
Quantum computers are capable to efficiently perform full configuration interaction (FCI) calculations of atoms and molecules by using the quantum phase estimation (QPE) algorithm. Because the success probability of the QPE depends on the overlap between approximate and exact wave functions, efficient methods to prepare accurate initial guess wave functions enough to have sufficiently large overlap with the exact ones are highly desired. Here, we propose a quantum algorithm to construct the wave function consisting of one configuration state function, which is suitable for the initial guess wave function in QPE-based FCI calculations of open-shell molecules, based on the addition theorem of angular momentum. The proposed quantum algorithm enables us to prepare the wave function consisting of an exponential number of Slater determinants only by a polynomial number of quantum operations.