ON NONDETERMINISTIC DYNAMIC PROGRAMMING
2008-01-01
R. Bellman left a lot of research problems in his work “Dynamic Programming" (1957). Having received ideas from Bellman, S. Iwamoto has extracted, out of his problems, a problem on nondeterministic dynamic programming (NDP). Instead of stochastic dynamic programming which has been well studied, Iwamoto has opened a gate to NDP. This report presents speci_c optimal solutions for NDPs on continuous state and decision spaces.
Introduction to dynamic programming
Cooper, Leon; Rodin, E Y
1981-01-01
Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark
A HYBRID DYNAMIC PROGRAM SLICING
Institute of Scientific and Technical Information of China (English)
Yi Tong; Wu Fangjun
2005-01-01
This letter proposes a hybrid method for computing dynamic program slicing. The key element is to construct a Coverage-Testing-based Dynamic Dependence Graph (CTDDG),which makes use of both dynamic and static information to get execution status. The approach overcomes the limitations of previous dynamic slicing methods, which have to redo slicing if slice criterion changes.
Software Acquisition Program Dynamics
2011-10-24
techniques to avoid these problems The Objective • Improve acquisition program staff decision-making, and thus improve acquisition program outcomes...classroom training, eLearning , certification, and more—to serve the needs of customers and partners worldwide.
Dynamic Programming Foundations and Principles
Sniedovich, Moshe
2010-01-01
Focusing on the modeling and solution of deterministic multistage decision problems, this book looks at dynamic programming as a problem-solving optimization method. With over 400 useful references, this edition discusses the dynamic programming analysis of a problem, illustrates the rationale behind this analysis, and clarifies the theoretical grounds that justify the rationale. It also explains the meaning and role of the concept of state in dynamic programming, examines the purpose and function of the principle of optimality, and outlines solution strategies for problems defiant of conventi
Introduction to stochastic dynamic programming
Ross, Sheldon M; Lukacs, E
1983-01-01
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
Programming an Interpreter Using Molecular Dynamics
Directory of Open Access Journals (Sweden)
C.A. Middelburg
2007-01-01
Full Text Available PGA (ProGram Algebra is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of PGA, which bears on the use of dynamic data structures in programming.We consider the programming of an interpreter for a program notation that is close to existing assembly languages using PGA with the primitives of molecular dynamics as basic instructions. It happens that, although primarily meant for explaining programming language features relating to the use of dynamic data structures, the collection of primitives of molecular dynamics in itself is suited to our programming wants.
Dynamical genetic programming in XCSF.
Preen, Richard J; Bull, Larry
2013-01-01
A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to artificial neural networks. This paper presents results from an investigation into using a temporally dynamic symbolic representation within the XCSF learning classifier system. In particular, dynamical arithmetic networks are used to represent the traditional condition-action production system rules to solve continuous-valued reinforcement learning problems and to perform symbolic regression, finding competitive performance with traditional genetic programming on a number of composite polynomial tasks. In addition, the network outputs are later repeatedly sampled at varying temporal intervals to perform multistep-ahead predictions of a financial time series.
Programming an interpreter using molecular dynamics
2008-01-01
PGA (ProGram Algebra) is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of \\PGA, which bears on the use of dynamic data structures in programming. We consider the programming of an interpreter for a program notation that is close to existing assembly languages using PGA with the primitives of molecular dynamics as basic instructions. It happens that, although primari...
Programming an Interpreter Using Molecular Dynamics
2007-01-01
PGA (ProGram Algebra) is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of PGA, which bears on the use of dynamic data structures in programming.We consider the programming of an interpreter for a program notation that is close to existing assembly languages using PGA with the primitives of molecular dynamics as basic instructions. It happens that, although primarily...
Gate complexity using Dynamic Programming
Sridharan, Srinivas; Gu, Mile; James, Matthew R.
2008-01-01
The relationship between efficient quantum gate synthesis and control theory has been a topic of interest in the quantum control literature. Motivated by this work, we describe in the present article how the dynamic programming technique from optimal control may be used for the optimal synthesis of quantum circuits. We demonstrate simulation results on an example system on SU(2), to obtain plots related to the gate complexity and sample paths for different logic gates.
Programming an interpreter using molecular dynamics
Bergstra, J.A.; Middelburg, C.A.
2007-01-01
PGA (ProGram Algebra) is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of \\PGA, which bears on the use of dynamic data structures in programming. We consider the programmi
Programming an interpreter using molecular dynamics
Bergstra, J.A.; Middelburg, C.A.
2007-01-01
PGA (ProGram Algebra) is an algebra of programs which concerns programs in their simplest form: sequences of instructions. Molecular dynamics is a simple model of computation developed in the setting of \\PGA, which bears on the use of dynamic data structures in programming. We consider the
BUILDING MATHEMATICAL MODELS IN DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
LIANA RODICA PATER
2012-05-01
Full Text Available In short, we can say that dynamic programming is a method of optimization of systems, using their mathematical representation in phases or sequences or as we say, periods. Such systems are common in economic studies at the implementation of programs on the most advanced techniques, such as for example that involving cosmic navigation. Another concept that is involved in the study of dynamic programs is the economic horizon (number of periods or phases that a dynamic program needs. This concept often leads to the examination of the convergence of certain variables on infinite horizon. In many cases from the real economy by introducing updating, dynamic programs can be made convergent.
Dynamic Slicing of Object-Oriented Programs
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Program slice has many applications such as program debugging,testing, maintena n ce, and complexity measurement. A static slice consists of all statements in pro gram P that may effect the value of variable v at some point p, and a dynamic s lice consists only of statements that influence the value of variable occurrence for specific program inputs. In this paper, we concern the problem of dynamic s licing of object-oriented programs which, to our knowledge, has not been addres s ed in the literatures. To solve this problem, we present the dynamic object-ori e nted dependence graph (DODG)which is an arc-classified digraph to explicitly re p resent various dynamic dependence between statement instances for a particular e xecution of an object-oriented program. Based on the DODG, we present a two-ph as e backward algorithm for computing a dynamic slice of an object-oriented program.
Genomic Signal Search by Dynamic Programming
Institute of Scientific and Technical Information of China (English)
ZHENG Wei-Mou
2003-01-01
A general and flexible multi-motif model is proposed based on dynamic programming. By extending theGibbs sampler to the dynamic programming and introducing temperature, an efficient algorithm is developed. Branchpoint signalsequences and translation initiation sequences extracted from the rice genome are then examined.
Integrating Pareto Optimization into Dynamic Programming
Directory of Open Access Journals (Sweden)
Thomas Gatter
2016-01-01
Full Text Available Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so can Pareto optimization with respect to A and B. However, the integration of Pareto optimization into dynamic programming opens a wide range of algorithmic alternatives, which we study in substantial detail in this article, using real-world applications in biosequence analysis, a field where dynamic programming is ubiquitous. Our results are two-fold: (1 We introduce the operation of a “Pareto algebra product” in the dynamic programming framework of Bellman’s GAP. Users of this framework can now ask for Pareto optimization with a single keystroke. Careful evaluation of the implementation alternatives by means of an extended Bellman’s GAP compiler demonstrates the dependence of the best implementation choice on the application at hand. (2 We extract from our experiments several pieces of advice to programmers who do not use a system such as Bellman’s GAP, but who choose to hand-craft their dynamic programming recurrences, incorporating Pareto optimization from scratch.
Dynamic Programming: An Introduction by Example
Zietz, Joachim
2007-01-01
The author introduces some basic dynamic programming techniques, using examples, with the help of the computer algebra system "Maple". The emphasis is on building confidence and intuition for the solution of dynamic problems in economics. To integrate the material better, the same examples are used to introduce different techniques. One covers the…
Solution Methods for Stochastic Dynamic Linear Programs.
1980-12-01
Linear Programming, IIASA , Laxenburg, Austria, June 2-6, 1980. [2] Aghili, P., R.H., Cramer and H.W. Thompson, "On the applicability of two- stage...Laxenburg, Austria, May, 1978. [52] Propoi, A. and V. Krivonozhko, ’The simplex method for dynamic linear programs", RR-78-14, IIASA , Vienna, Austria
Hybrid Differential Dynamic Programming with Stochastic Search
Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob
2016-01-01
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Dynamic programming for QFD in PES optimization
Energy Technology Data Exchange (ETDEWEB)
Sorrentino, R. [Mediterranean Univ. of Reggio Calabria, Reggio Calabria (Italy). Dept. of Computer Science and Electrical Technology
2008-07-01
Quality function deployment (QFD) is a method for linking the needs of the customer with design, development, engineering, manufacturing, and service functions. In the electric power industry, QFD is used to help designers concentrate on the most important technical attributes to develop better electrical services. Most optimization approaches used in QFD analysis have been based on integer or linear programming. These approaches perform well in certain circumstances, but there are problems that hinder their practical use. This paper proposed an approach to optimize Power and Energy Systems (PES). A dynamic programming approach was used along with an extended House of Quality to gather information. Dynamic programming was used to allocate the limited resources to the technical attributes. The approach integrated dynamic programming into the electrical service design process. The dynamic programming approach did not require the full relationship curve between technical attributes and customer satisfaction, or the relationship between technical attributes and cost. It only used a group of discrete points containing information about customer satisfaction, technical attributes, and the cost to find the optimal product design. Therefore, it required less time and resources than other approaches. At the end of the optimization process, the value of each technical attribute, the related cost, and the overall customer satisfaction were obtained at the same time. It was concluded that compared with other optimization methods, the dynamic programming method requires less information and the optimal results are more relevant. 21 refs., 2 tabs., 2 figs.
Planar multibody dynamics formulation, programming and applications
Nikravesh, Parviz E
2007-01-01
Introduction Multibody Mechanical Systems Types of Analyses Methods of Formulation Computer Programming Application Examples Unit System Remarks Preliminaries Reference Axes Scalars and Vectors Matrices Vector, Array, and Matrix Differentiation Equations and Expressions Remarks Problems Fundamentals of Kinematics A Particle Kinematics of a Rigid Body Definitions Remarks Problems Fundamentals of Dynamics Newton's Laws of Motion Dynamics of a Body Force Elements Applied Forces Reaction Force Remarks Problems Point-Coordinates: Kinematics Multipoint
Configuring Airspace Sectors with Approximate Dynamic Programming
Bloem, Michael; Gupta, Pramod
2010-01-01
In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.
Microsoft Dynamics NAV 7 programming cookbook
Raul, Rakesh
2013-01-01
Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.
Comparison of two approaches to dynamic programming
Broek, van den Pim; Noppen, Joost
2004-01-01
Both in mathematics and in computer science Dynamic Programming is a well known concept. It is an algorithmic technique, which can be used to write efficient algorithms, based on the avoidance of multiple executions of identical subcomputations. Its definition in both disciplines is however quite di
Two stage gear tooth dynamics program
Boyd, Linda S.
1989-01-01
The epicyclic gear dynamics program was expanded to add the option of evaluating the tooth pair dynamics for two epicyclic gear stages with peripheral components. This was a practical extension to the program as multiple gear stages are often used for speed reduction, space, weight, and/or auxiliary units. The option was developed for either stage to be a basic planetary, star, single external-external mesh, or single external-internal mesh. The two stage system allows for modeling of the peripherals with an input mass and shaft, an output mass and shaft, and a connecting shaft. Execution of the initial test case indicated an instability in the solution with the tooth paid loads growing to excessive magnitudes. A procedure to trace the instability is recommended as well as a method of reducing the program's computation time by reducing the number of boundary condition iterations.
Expansion of epicyclic gear dynamic analysis program
Boyd, Linda Smith; Pike, James A.
1987-01-01
The multiple mesh/single stage dynamics program is a gear tooth analysis program which determines detailed geometry, dynamic loads, stresses, and surface damage factors. The program can analyze a variety of both epicyclic and single mesh systems with spur or helical gear teeth including internal, external, and buttress tooth forms. The modifications refine the options for the flexible carrier and flexible ring gear rim and adds three options: a floating Sun gear option; a natural frequency option; and a finite element compliance formulation for helical gear teeth. The option for a floating Sun incorporates two additional degrees of freedom at the Sun center. The natural frequency option evaluates the frequencies of planetary, star, or differential systems as well as the effect of additional springs at the Sun center and those due to a flexible carrier and/or ring gear rim. The helical tooth pair finite element calculated compliance is obtained from an automated element breakup of the helical teeth and then is used with the basic gear dynamic solution and stress postprocessing routines. The flexible carrier or ring gear rim option for planetary and star spur gear systems allows the output torque per carrier and ring gear rim segment to vary based on the dynamic response of the entire system, while the total output torque remains constant.
Protein Secondary Structure Prediction Using Dynamic Programming
Institute of Scientific and Technical Information of China (English)
Jing ZHAO; Pei-Ming SONG; Qing FANG; Jian-Hua LUO
2005-01-01
In the present paper, we describe how a directed graph was constructed and then searched for the optimum path using a dynamic programming approach, based on the secondary structure propensity of the protein short sequence derived from a training data set. The protein secondary structure was thus predicted in this way. The average three-state accuracy of the algorithm used was 76.70%.
Eradication of Ebola Based on Dynamic Programming
Zhu, Jia-Ming; Wang, Lu; Liu, Jia-Bao
2016-01-01
This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. PMID:27313655
Joint Chance-Constrained Dynamic Programming
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
Joint Chance-Constrained Dynamic Programming
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
On a Natural Dynamics for Linear Programming
Straszak, Damian
2015-01-01
In this paper we study dynamics inspired by Physarum polycephalum (a slime mold) for solving linear programs [NTY00, IJNT11, JZ12]. These dynamics are arrived at by a local and mechanistic interpretation of the inner workings of the slime mold and a global optimization perspective has been lacking even in the simplest of instances. Our first result is an interpretation of the dynamics as an optimization process. We show that Physarum dynamics can be seen as a steepest-descent type algorithm on a certain Riemannian manifold. Moreover, we prove that the trajectories of Physarum are in fact paths of optimizers to a parametrized family of convex programs, in which the objective is a linear cost function regularized by an entropy barrier. Subsequently, we rigorously establish several important properties of solution curves of Physarum. We prove global existence of such solutions and show that they have limits, being optimal solutions of the underlying LP. Finally, we show that the discretization of the Physarum dy...
Sandia Dynamic Materials Program Strategic Plan.
Energy Technology Data Exchange (ETDEWEB)
Flicker, Dawn Gustine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benage, John F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Desjarlais, Michael P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knudson, Marcus D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Leifeste, Gordon T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lemke, Raymond W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mattsson, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wise, Jack L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-05-01
Materials in nuclear and conventional weapons can reach multi-megabar pressures and 1000s of degree temperatures on timescales ranging from microseconds to nanoseconds. Understanding the response of complex materials under these conditions is important for designing and assessing changes to nuclear weapons. In the next few decades, a major concern will be evaluating the behavior of aging materials and remanufactured components. The science to enable the program to underwrite decisions quickly and confidently on use, remanufacturing, and replacement of these materials will be critical to NNSA’s new Stockpile Responsiveness Program. Material response is also important for assessing the risks posed by adversaries or proliferants. Dynamic materials research, which refers to the use of high-speed experiments to produce extreme conditions in matter, is an important part of NNSA’s Stockpile Stewardship Program.
Dynamic programming algorithms for biological sequence comparison.
Pearson, W R; Miller, W
1992-01-01
Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.
Approximate Dynamic Programming for Self-Learning Control
Institute of Scientific and Technical Information of China (English)
Derong Liu
2005-01-01
This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.
A Dynamic Programming Approach to Constrained Portfolios
DEFF Research Database (Denmark)
Kraft, Holger; Steffensen, Mogens
2013-01-01
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies...... the martingale method. More precisely, we construct the non-separable value function by formalizing the optimal constrained terminal wealth to be a (conjectured) contingent claim on the optimal non-constrained terminal wealth. This is relevant by itself, but also opens up the opportunity to derive new solutions...
Automated Flight Routing Using Stochastic Dynamic Programming
Ng, Hok K.; Morando, Alex; Grabbe, Shon
2010-01-01
Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.
Runway Scheduling Using Generalized Dynamic Programming
Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar
2011-01-01
A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.
Versatile and declarative dynamic programming using pair algebras
Directory of Open Access Journals (Sweden)
Giegerich Robert
2005-09-01
Full Text Available Abstract Background Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes. Results Based on this programming style, we introduce a generic product operation of scoring schemes. This leads to a remarkable variety of applications, allowing us to achieve optimizations under multiple objective functions, alternative solutions and backtracing, holistic search space analysis, ambiguity checking, and more, without additional programming effort. We demonstrate the method on several applications for RNA secondary structure prediction. Conclusion The product operation as introduced here adds a significant amount of flexibility to dynamic programming. It provides a versatile testbed for the development of new algorithmic ideas, which can immediately be put to practice.
Robot trajectory planning via dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Dohrmann, C.R.; Robinett, R.D.
1994-03-01
The method of dynamic programming is applied to three example problems dealing with robot trajectory planning. The first two examples involve end-effector tracking of a straight line with rest-to-rest motions of planar two-link and three-link rigid robots. These examples illustrate the usefulness of the method for producing smooth trajectories either in the presence or absence of joint redundancies. The last example demonstrates the use of the method for rest-to-rest maneuvers of a single-link manipulator with a flexible payload. Simulation results for this example display interesting symmetries that are characteristic of such maneuvers. Details concerning the implementation and computational aspects of the method are discussed.
Pareto optimization in algebraic dynamic programming.
Saule, Cédric; Giegerich, Robert
2015-01-01
Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.
A Simulation Program for Dynamic Infrared (IR) Spectra
Zoerb, Matthew C.; Harris, Charles B.
2013-01-01
A free program for the simulation of dynamic infrared (IR) spectra is presented. The program simulates the spectrum of two exchanging IR peaks based on simple input parameters. Larger systems can be simulated with minor modifications. The program is available as an executable program for PCs or can be run in MATLAB on any operating system. Source…
Spatial cluster detection using dynamic programming
Directory of Open Access Journals (Sweden)
Sverchkov Yuriy
2012-03-01
Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic
Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)
Energy Technology Data Exchange (ETDEWEB)
2012-05-31
The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.
Application of a Dynamic Programming Algorithm for Weapon Target Assignment
2016-02-01
UNCLASSIFIED UNCLASSIFIED Application of a Dynamic Programming Algorithm for Weapon Target Assignment Lloyd Hammond Weapons and...Combat Systems Division Defence Science and Technology Group DST Group-TR-3221 ABSTRACT Threat evaluation and weapon assignment...dynamic programming algorithm for Weapon Target Assignment which, after more rigorous testing, could be used as a concept demonstrator and as an auxiliary
Lower Bounds for Tropical Circuits and Dynamic Programs
Jukna, Stasys
2014-01-01
Tropical circuits are circuits with Min and Plus, or Max and Plus operations as gates. Their importance stems from their intimate relation to dynamic programming algorithms. The power of tropical circuits lies somewhere between that of monotone boolean circuits and monotone arithmetic circuits. In this paper we present some lower bounds arguments for tropical circuits, and hence, for dynamic programs.
A Dynamic Programming Approach to Adaptive Fractionation
Ramakrishnan, Jagdish; Bortfeld, Thomas; Tsitsiklis, John
2011-01-01
We formulate a previously introduced adaptive fractionation problem in a dynamic programming (DP) framework and explore various solution techniques. The two messages of this paper are: (i) the DP model is a useful framework for studying adaptive radiation therapy, particularly adaptive fractionation, and (ii) there is a potential for substantial decrease in dose to the primary organ-at-risk (OAR), or equivalently increase in tumor escalation, when using an adaptive fraction size. The essence of adaptive fractionation is to increase the fraction size when observing a "favorable" anatomy or when the tumor and OAR are far apart and to decrease the fraction size when they are close together. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to the OAR when compared to that resulting from standard fractionation. We first establish a benchmark by using the DP algorithm to solve the problem exactly. In this case, we...
ALPprolog --- A New Logic Programming Method for Dynamic Domains
Drescher, Conrad
2011-01-01
Logic programming is a powerful paradigm for programming autonomous agents in dynamic domains, as witnessed by languages such as Golog and Flux. In this work we present ALPprolog, an expressive, yet efficient, logic programming language for the online control of agents that have to reason about incomplete information and sensing actions.
An Improved Dynamic Programming Method for Automatic Stratigraphic Correlation
Institute of Scientific and Technical Information of China (English)
Yan Hanjie; Yan Hong; Xiang Zhucong; Wang Yanjiang
2003-01-01
An improved dynamic programming algorithm is proposed for reducing the possible mismatching of layer in multi-well correlation. Compared with the standard dynamic programming algorithm, this method restricts the searching range during layer matching. It can not only avoid possible mismatching between sample and target layer, but also reduce the time spent on layer correlation. The result of applying the improved methods on the data processed by standard method before indicates that the improved one is more effective and timesaving for the multi-well correlation system than conventional dynamic programming algorithm.
Approximate Dynamic Programming Solving the Curses of Dimensionality
Powell, Warren B
2011-01-01
Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners."-Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of unce
Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator
Marcin Szuster; Piotr Gierlak
2016-01-01
This article focuses on the implementation of an approximate dynamic programming algorithm in the discrete tracking control system of the three-degrees of freedom Scorbot-ER 4pc robotic manipulator. The controlled system is included in an articulated robots group which uses rotary joints to access their work space. The main part of the control system is a dual heuristic dynamic programming algorithm that consists of two structures designed in the form of neural networks: an actor and a critic...
Incremental approximate dynamic programming for nonlinear flight control design
Zhou, Y.; Van Kampen, E.J.; Chu, Q.P.
2015-01-01
A self-learning adaptive flight control design for non-linear systems allows reliable and effective operation of flight vehicles in a dynamic environment. Approximate dynamic programming (ADP) provides a model-free and computationally effective process for designing adaptive linear optimal
Program Partitioning using Dynamic Trust Models
DEFF Research Database (Denmark)
Søndergaard, Dan; Probst, Christian W.; Jensen, Christian D.;
2006-01-01
-based scenarios. Language-based technologies have been suggested to support developers of those applications---the \\$\\backslash\\$emph{Decentralized Label Model} and \\$\\backslash\\$emph{Secure Program Partitioning} allow to annotate programs with security specifications, and to partition the annotated program...... across a set of hosts, obeying both the annotations and the trust relation between the principals. The resulting applications guarantee \\$\\backslash\\$emph{by construction} that safety and confidentiality of both data and computations are ensured. In this work, we develop a generalised version...
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Dynamic Performance Tuning Supported by Program Specification
Directory of Open Access Journals (Sweden)
Eduardo César
2002-01-01
Full Text Available Performance analysis and tuning of parallel/distributed applications are very difficult tasks for non-expert programmers. It is necessary to provide tools that automatically carry out these tasks. These can be static tools that carry out the analysis on a post-mortem phase or can tune the application on the fly. Both kind of tools have their target applications. Static automatic analysis tools are suitable for stable application while dynamic tuning tools are more appropriate to applications with dynamic behaviour. In this paper, we describe KappaPi as an example of a static automatic performance analysis tool, and also a general environment based on parallel patterns for developing and dynamically tuning parallel/distributed applications.
Dynamic Learning Objects to Teach Java Programming Language
Narasimhamurthy, Uma; Al Shawkani, Khuloud
2010-01-01
This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…
Dynamic Learning Objects to Teach Java Programming Language
Narasimhamurthy, Uma; Al Shawkani, Khuloud
2010-01-01
This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…
A dynamic inequality generation scheme for polynomial programming
Ghaddar, B.; Vera Lizcano, J.C.; Anjos, M.F.
2016-01-01
Hierarchies of semidefinite programs have been used to approximate or even solve polynomial programs. This approach rapidly becomes computationally expensive and is often tractable only for problems of small size. In this paper, we propose a dynamic inequality generation scheme to generate valid pol
A Systematic Survey of Program Comprehension through Dynamic Analysis
Cornelissen, B.; Zaidman, A.; Van Deursen, A.; Moonen, L.; Koschke, R.
2009-01-01
Program comprehension is an important activity in software maintenance, as software must be sufficiently understood before it can be properly modified. The study of a program's execution, known as dynamic analysis, has become a common technique in this respect and has received substantial attention
Programming the dynamics of biochemical reaction networks.
Simmel, Friedrich C
2013-01-22
The development of complex self-organizing molecular systems for future nanotechnology requires not only robust formation of molecular structures by self-assembly but also precise control over their temporal dynamics. As an exquisite example of such control, in this issue of ACS Nano, Fujii and Rondelez demonstrate a particularly compact realization of a molecular "predator-prey" ecosystem consisting of only three DNA species and three enzymes. The system displays pronounced oscillatory dynamics, in good agreement with the predictions of a simple theoretical model. Moreover, its considerable modularity also allows for ecological studies of competition and cooperation within molecular networks.
Dynamic Programming Method for Impulsive Control Problems
Balkew, Teshome Mogessie
2015-01-01
In many control systems changes in the dynamics occur unexpectedly or are applied by a controller as needed. The time at which a controller implements changes is not necessarily known a priori. For example, many manufacturing systems and flight operations have complicated control systems, and changes in the control systems may be automatically…
Attack diagnosis on binary executables using dynamic program slicing
Huang, Shan; Zheng, Yudi; Zhang, Ruoyu
2011-12-01
Nowadays, the level of the practically used programs is often complex and of such a large scale so that it is not as easy to analyze and debug them as one might expect. And it is quite difficult to diagnose attacks and find vulnerabilities in such large-scale programs. Thus, dynamic program slicing becomes a popular and effective method for program comprehension and debugging since it can reduce the analysis scope greatly and drop useless data that do not influence the final result. Besides, most of existing dynamic slicing tools perform dynamic slicing in the source code level, but the source code is not easy to obtain in practice. We believe that we do need some kinds of systems to help the users understand binary programs. In this paper, we present an approach of diagnosing attacks using dynamic backward program slicing based on binary executables, and provide a dynamic binary slicing tool named DBS to analyze binary executables precisely and efficiently. It computes the set of instructions that may have affected or been affected by slicing criterion set in certain location of the binary execution stream. This tool also can organize the slicing results by function call graphs and control flow graphs clearly and hierarchically.
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
. It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model...... with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator rotor......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively...
Granular contact dynamics using mathematical programming methods
DEFF Research Database (Denmark)
Krabbenhoft, K.; Lyamin, A. V.; Huang, J.
2012-01-01
A class of variational formulations for discrete element analysis of granular media is presented. These formulations lead naturally to convex mathematical programs that can be solved using standard and readily available tools. In contrast to traditional discrete element analysis, the present...
Approximate Dynamic Programming for Military Resource Allocation
2014-12-26
combinatorial optimization, the DWTA prob- lem suffers from the curses of dimensionality and optimality is often computationally intractability. As such...exponentially. These are known as dynamic programming’s curses of dimensionality [82]. Much of the existing research focuses on solution techniques for...simultaneously. • The outcomes of each stage are observed prior to the following stage (this can either be perfect knowledge or stochastic, though Hosein [47
Dynamic Pricing Criteria in Linear Programming
1988-07-01
Dantzig, M.A.H. Dempster and M. Kallio, eds.), pp. 631- 662, IIASA , Laxenburg, Austria. [23] Karmarkar, N. (1984). A new polynomial-time algorithm for...simplex method, in Large Scale Linear Programming (G.B. Dantzig, M.A.H. Dempster and M. Kallio, eds.), pp. 55-66, IIASA , Laxenburg, Austria. [39] Perold...M.J. Kallio, eds.), pp. 67-96, IIASA , Laxenburg, Austria. [40] Pyle, L.D. (1987). Generalizations of the simplex algorithm, Department of Compvter
The application of dynamic programming in production planning
Wu, Run
2017-05-01
Nowadays, with the popularity of the computers, various industries and fields are widely applying computer information technology, which brings about huge demand for a variety of application software. In order to develop software meeting various needs with most economical cost and best quality, programmers must design efficient algorithms. A superior algorithm can not only soul up one thing, but also maximize the benefits and generate the smallest overhead. As one of the common algorithms, dynamic programming algorithms are used to solving problems with some sort of optimal properties. When solving problems with a large amount of sub-problems that needs repetitive calculations, the ordinary sub-recursive method requires to consume exponential time, and dynamic programming algorithm can reduce the time complexity of the algorithm to the polynomial level, according to which we can conclude that dynamic programming algorithm is a very efficient compared to other algorithms reducing the computational complexity and enriching the computational results. In this paper, we expound the concept, basic elements, properties, core, solving steps and difficulties of the dynamic programming algorithm besides, establish the dynamic programming model of the production planning problem.
Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.
Jiang, Yu; Jiang, Zhong-Ping
2014-05-01
This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system.
Dynamic structural correlation via nonlinear programming techniques
Ting, T.; Ojalvo, I. U.
1988-01-01
A solution to the correlation between structural dynamic test results and finite element analyses of the same components is presented in this paper. Basically, the method can be categorized as a Levenberg-Marquardt type Gauss-Newton method which requires only the differences between FE modal analyses and test results and their first derivatives with respect to preassigned design variables. With proper variable normalization and equation scaling, the method has been made numerically better-conditioned and the inclusion of the Levenberg-Marquardt technique overcomes any remaining difficulty encountered in inverting singular or near-singular matrices. An important feature is that each iteration requires only one function evaluation along with the associated design sensitivity analysis and so the procedure is computationally efficient.
Spacecraft Dynamics and Control Program at AFRPL
Das, A.; Slimak, L. K. S.; Schloegel, W. T.
1986-01-01
A number of future DOD and NASA spacecraft such as the space based radar will be not only an order of magnitude larger in dimension than the current spacecraft, but will exhibit extreme structural flexibility with very low structural vibration frequencies. Another class of spacecraft (such as the space defense platforms) will combine large physical size with extremely precise pointing requirement. Such problems require a total departure from the traditional methods of modeling and control system design of spacecraft where structural flexibility is treated as a secondary effect. With these problems in mind, the Air Force Rocket Propulsion Laboratory (AFRPL) initiated research to develop dynamics and control technology so as to enable the future large space structures (LSS). AFRPL's effort in this area can be subdivided into the following three overlapping areas: (1) ground experiments, (2) spacecraft modeling and control, and (3) sensors and actuators. Both the in-house and contractual efforts of the AFRPL in LSS are summarized.
Eucb: A C++ program for molecular dynamics trajectory analysis
Tsoulos, Ioannis G.; Stavrakoudis, Athanassios
2011-03-01
Eucb is a standalone program for geometrical analysis of molecular dynamics trajectories of protein systems. The program is written in GNU C++ and it can be installed in any operating system running a C++ compiler. The program performs its analytical tasks based on user supplied keywords. The source code is freely available from http://stavrakoudis.econ.uoi.gr/eucb under LGPL 3 license. Program summaryProgram title:Eucb Catalogue identifier: AEIC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIC_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.: 31 169 No. of bytes in distributed program, including test data, etc.: 297 364 Distribution format: tar.gz Programming language: GNU C++ Computer: The tool is designed and tested on GNU/Linux systems Operating system: Unix/Linux systems RAM: 2 MB Supplementary material: Sample data files are available Classification: 3 Nature of problem: Analysis of molecular dynamics trajectories. Solution method: The program finds all possible interactions according to input files and the user instructions. Then it reads all the trajectory frames and finds those frames in which these interactions occur, under certain geometrical criteria. This is a blind search, without a priori knowledge if a certain interaction occurs or not. The program exports time series of these quantities (distance, angles, etc.) and appropriate descriptive statistics. Running time: Depends on the input data and the required options.
Approximate dynamic programming solving the curses of dimensionality
Powell, Warren B
2007-01-01
Warren B. Powell, PhD, is Professor of Operations Research and Financial Engineering at Princeton University, where he is founder and Director of CASTLE Laboratory, a research unit that works with industrial partners to test new ideas found in operations research. The recipient of the 2004 INFORMS Fellow Award, Dr. Powell has authored over 100 refereed publications on stochastic optimization, approximate dynamic programming, and dynamic resource management.
Fast and Cache-Oblivious Dynamic Programming with Local Dependencies
DEFF Research Database (Denmark)
Bille, Philip; Stöckel, Morten
2012-01-01
are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm...
Fast and Cache-Oblivious Dynamic Programming with Local Dependencies
DEFF Research Database (Denmark)
Bille, Philip; Stöckel, Morten
2012-01-01
are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm....... Additionally, our new algorithm generalizes the best known theoretical complexity trade-offs for the problem....
Application of dynamic programming to the correlation of paleoclimate records
Lisiecki, Lorraine E.; Lisiecki, Philip A.
2002-12-01
Signal matching is a powerful tool frequently used in paleoclimate research, but it is enormously time-consuming when performed by hand. Previously proposed automatic correlation techniques require very good initial fits to find the correct alignment of two records. A new technique presented in this paper utilizes dynamic programming to find the globally optimal alignment of two records. Geological realism is instilled in the solution through the definition of penalty functions for undesirable behavior such as unlikely changes in accumulation rate. Examples with synthetic and real data demonstrate that the dynamic programming technique produces accurate, high-resolution results with much less effort than hand tuning or preexisting automated correlation techniques.
Multi-view video color correction using dynamic programming
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.
Path planning for complex terrain navigation via dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Kwok, K.S.; Driessen, B.J.
1998-12-31
This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains.
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
Approximate group context tree: applications to dynamic programming and dynamic choice models
Belloni, Alexandre
2011-01-01
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities. We propose a new model selection and estimation method, develop oracle inequalities and model selection properties for the estimator. These results also provide conditions under which the use of the group structure can lead to improvements in the overall estimation. Our work is also motivated by two methodological applications: discrete stochastic dynamic programming and dynamic discrete choice models. We analyze the uniform estimation of the value function for dynamic programming and the uniform estimation of average dynamic marginal effects for dynamic discrete choice models accounting for possible imperfect model selection. We also derive the typical behavior of our estimator when applied to polynomially $\\beta$-mixing stochastic processes. For parametric models, we derive uniform rate of convergence for the estimation...
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.
Dynamic Frames Based Verification Method for Concurrent Java Programs
Mostowski, Wojciech
2016-01-01
In this paper we discuss a verification method for concurrent Java programs based on the concept of dynamic frames. We build on our earlier work that proposes a new, symbolic permission system for concurrent reasoning and we provide the following new contributions. First, we describe our approach
"Intensive Research Program on Advances in Nonsmooth Dynamics 2016
Jeffrey, Mike; Lázaro, J; Olm, Josep
2017-01-01
This volume contains extended abstracts outlining selected talks and other selected presentations given by participants throughout the "Intensive Research Program on Advances in Nonsmooth Dynamics 2016", held at the Centre de Recerca Matemàtica (CRM) in Barcelona from February 1st to April 29th, 2016. They include brief research articles reporting new results, descriptions of preliminary work or open problems, and outlines of prominent discussion sessions. The articles are all the result of direct collaborations initiated during the research program. The topic is the theory and applications of Nonsmooth Dynamics. This includes systems involving elements of: impacting, switching, on/off control, hybrid discrete-continuous dynamics, jumps in physical properties, and many others. Applications include: electronics, climate modeling, life sciences, mechanics, ecology, and more. Numerous new results are reported concerning the dimensionality and robustness of nonsmooth models, shadowing variables, numbers of limit...
Dynamic analysis of spur gears using computer program DANST
Oswald, Fred B.; Lin, Hsiang H.; Liou, Chuen-Huei; Valco, Mark J.
1993-06-01
DANST is a computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the effect on dynamic load and tooth bending stress of spur gears due to operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratio ranging from one to three. It was designed to be easy to use, and it is extensively documented by comments in the source code. This report describes the installation and use of DANST. It covers input data requirements and presents examples. The report also compares DANST predictions for gear tooth loads and bending stress to experimental and finite element results.
A Hybrid Dynamic Programming Method for Concave Resource Allocation Problems
Institute of Scientific and Technical Information of China (English)
姜计荣; 孙小玲
2005-01-01
Concave resource allocation problem is an integer programming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the revised domain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
Directory of Open Access Journals (Sweden)
Wenjie Bi
2014-01-01
Full Text Available Dynamic portfolio choice is an important problem in finance, but the optimal strategy analysis is difficult when considering multiple stochastic volatility variables such as the stock price, interest rate, and income. Besides, recent research in experimental economics indicates that the agent shows limited attention, considering only the variables with high fluctuations but ignoring those with small ones. By extending the sparse max method, we propose an approach to solve dynamic programming problem with small stochastic volatility and the agent’s bounded rationality. This approach considers the agent’s behavioral factors and avoids effectively the “Curse of Dimensionality” in a dynamic programming problem with more than a few state variables. We then apply it to Merton dynamic portfolio choice model with stochastic volatility and get a tractable solution. Finally, the numerical analysis shows that the bounded rational agent may pay no attention to the varying equity premium and interest rate with small variance.
Overview of the solar dynamic ground test demonstration program
Shaltens, Richard K.; Boyle, Robert V.
1993-01-01
The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the availability of SD technologies in a simulated space environment at the NASA Lewis Research Center (LeRC) vacuum facility. An aerospace industry/ government team is working together to design, fabricate, build, and test a complete SD system. This paper reviews the goals and status of the SD GTD program. A description of the SD system includes key design features of the system, subsystems, and components as reported at the Critical Design Review (CDR).
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Hydrothermal scheduling via extended differential dynamic programming and mixed coordination
Energy Technology Data Exchange (ETDEWEB)
Tang, J. [Alfred Univ., NY (United States). Div. of Electrical Engineering; Luh, P.B. [Univ. of Connecticut, Storrs, CT (United States). Dept. of Electrical and Systems Engineering
1995-11-01
This paper addresses short-term scheduling of hydrothermal systems by using extended differential dynamic programming and mixed coordination. The problem is first decomposed into a thermal subproblem and a hydro subproblem by relaxing the supply-demand constraints. The thermal subproblem is solved analytically. The hydro subproblem is further decomposed into a set of smaller problems that can be solved in parallel. Extended differential dynamic programming and mixed coordination are used to solve the hydro subproblem. Two problems are tested and the results show that the new approach performs well under a simulated parallel processing environment, and high speedup is obtained. The method is then extended to handle unpredictable changes in natural inflow by utilizing the variational feedback nature of the control strategy. A quick estimate on the impact of an unpredictable change on total cost is also obtained. Numerical results show that estimates are accurate, and unpredictable change in natural inflow can be quickly and effectively handled.
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-03
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
Viorel MINZU
2015-12-01
Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.
Dynamic Programming Approach for Construction of Association Rule Systems
Alsolami, Fawaz
2016-11-18
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
Dynamics of a wellness program: a conservation of resources perspective.
Kim, Sung Doo; Hollensbe, Elaine C; Schwoerer, Catherine E; Halbesleben, Jonathon R B
2015-01-01
We leverage conservation of resources theory to explain possible dynamics through which a holistic wellness program results in positive longer-term outcomes. Specifically, we hypothesize that wellness self-efficacy at the end of a wellness program will create a positive resource gain spiral, increasing psychological availability (a sense of having cognitive, physical, and emotional resources to engage oneself) 6 months later, and career satisfaction, 1 year later. To test these hypotheses, using a time-lagged with control group design, we gathered questionnaire data from 160 Episcopal priests who participated in a 10-day off-site wellness program. We developed a scale measuring self-efficacy in the 4 wellness areas the program was designed to improve: physical, spiritual, financial, and vocational. Our findings provide evidence from a field setting of a relatively untested tenet of conservation of resources theory, resource gain spirals. The wellness program that we studied served as an opportunity for participants to gain new resources in the form of wellness self-efficacy, which in turn helped participants experience positive outcomes over time. We discuss theoretical and practical implications of the findings.
Modelling dynamic programming problems by generalized d-graphs
Kátai, Zoltán
2010-01-01
In this paper we introduce the concept of generalized d-graph (admitting cycles) as special dependency-graphs for modelling dynamic programming (DP) problems. We describe the d-graph versions of three famous single-source shortest algorithms (The algorithm based on the topological order of the vertices, Dijkstra algorithm and Bellman-Ford algorithm), which can be viewed as general DP strategies in the case of three different class of optimization problems. The new modelling method also makes possible to classify DP problems and the corresponding DP strategies in term of graph theory.
Editorial Special issue on approximate dynamic programming and reinforcement learning
Institute of Scientific and Technical Information of China (English)
Silvia Ferrari; Jagannathan Sarangapani; Frank L. Lewis
2011-01-01
We are extremely pleased to present this special issue of the Journal of Control Theory and Applications.Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over time.ADP optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.
Performance Potential-based Neuro-dynamic Programming for SMDPs
Institute of Scientific and Technical Information of China (English)
TANGHao; YUANJi-Bin; LUYang; CHENGWen-Juan
2005-01-01
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimal generator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimization of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamic programming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performance error bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, a numerical example is provided.
Automatic cone photoreceptor segmentation using graph theory and dynamic programming.
Chiu, Stephanie J; Lokhnygina, Yuliya; Dubis, Adam M; Dubra, Alfredo; Carroll, Joseph; Izatt, Joseph A; Farsiu, Sina
2013-06-01
Geometrical analysis of the photoreceptor mosaic can reveal subclinical ocular pathologies. In this paper, we describe a fully automatic algorithm to identify and segment photoreceptors in adaptive optics ophthalmoscope images of the photoreceptor mosaic. This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP). We validated the performance of the proposed algorithm by comparing it to the state-of-the-art technique on a large data set consisting of over 200,000 cones and posted the results online. We found that the GTDP method achieved a higher detection rate, decreasing the cone miss rate by over a factor of five.
Dynamic programming and graph algorithms in computer vision.
Felzenszwalb, Pedro F; Zabih, Ramin
2011-04-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.
Dynamic programming in in uence diagrams with decision circuits
Shachter, Ross D
2012-01-01
Decision circuits perform efficient evaluation of influence diagrams, building on the ad- vances in arithmetic circuits for belief net- work inference [Darwiche, 2003; Bhattachar- jya and Shachter, 2007]. We show how even more compact decision circuits can be con- structed for dynamic programming in influ- ence diagrams with separable value functions and conditionally independent subproblems. Once a decision circuit has been constructed based on the diagram's "global" graphical structure, it can be compiled to exploit "lo- cal" structure for efficient evaluation and sen- sitivity analysis.
Dynamic Programming and Graph Algorithms in Computer Vision*
Felzenszwalb, Pedro F.; Zabih, Ramin
2013-01-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-04-09
We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth
BRANECODE: A Program for Simulations of Braneworld Dynamics
Martin, Johannes; Frolov, Andrei V; Kofman, Lev; Peloso, Marco; Martin, Johannes; Felder, Gary N.; Frolov, Andrei V.; Kofman, Lev; Peloso, Marco
2004-01-01
We describe an algorithm and a C++ implementation that we have written and made available for calculating the fully nonlinear evolution of 5D braneworld models with scalar fields. Bulk fields allow for the stabilization of the extra space. However, they complicate the dynamics of the system, so that analytic calculations (performed within an effective 4D theory) are typically only reliable close to stabilized configurations or when the evolution of the extra space is negligible. In the general case, a numerical study of the 5D equations is necessary, and the algorithm and code we describe are the first ones designed for this task. The program and its full documentation are available on the Web at http://www.cita.utoronto.ca/~jmartin/BRANECODE/. In this paper we provide a brief overview of what the program does and how to use it.
Dynamics of the public concern and risk communication program implementation.
Zaryabova, Victoria; Israel, Michel
2015-09-01
The public concern about electromagnetic field (EMF) exposure varies due to different reasons. A part of them are connected with the better and higher quality of information that people receive from science, media, Internet, social networks, industry, but others are based on good communication programs performed by the responsible institutions, administration and persons. Especially, in Bulgaria, public concern follows interesting changes, some of them in correlation with the European processes of concern, but others following the economic and political processes in the country. Here, we analyze the dynamics of the public concern over the last 10 years. Our explanation of the decrease of the people's complaints against EMF exposure from base stations for mobile communication is as a result of our risk communication program that is in implementation for >10 years.
A mathematical programming approach for sequential clustering of dynamic networks
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming
Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji
In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.
Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator
Directory of Open Access Journals (Sweden)
Marcin Szuster
2016-02-01
Full Text Available This article focuses on the implementation of an approximate dynamic programming algorithm in the discrete tracking control system of the three-degrees of freedom Scorbot-ER 4pc robotic manipulator. The controlled system is included in an articulated robots group which uses rotary joints to access their work space. The main part of the control system is a dual heuristic dynamic programming algorithm that consists of two structures designed in the form of neural networks: an actor and a critic. The actor generates the suboptimal control law while the critic approximates the difference of the value function from Bellman’s equation with respect to the state. The residual elements of the control system are the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis performed using the Lyapunov stability theorem. The control system works online, the neural networks’ weights-adaptation procedure is performed in every iteration step, and the neural networks’ preliminary learning process is not required. The performance of the control system was verified by a series of computer simulations and experiments performed using the Scorbot-ER 4pc robotic manipulator.
Dynamic Analysis of a Helicopter Rotor by Dymore Program
Doğan, Vedat; Kırca, Mesut
The dynamic behavior of hingeless and bearingless blades of a light commercial helicopter which has been under design process at ITU (İstanbul Technical University, Rotorcraft Research and Development Centre) is investigated. Since the helicopter rotor consists of several parts connected to each other by joints and hinges; rotors in general can be considered as an assembly of the rigid and elastic parts. Dynamics of rotor system in rotation is complicated due to coupling of elastic forces (bending, torsion and tension), inertial forces, control and aerodynamic forces on the rotor blades. In this study, the dynamic behavior of the rotor for a real helicopter design project is analyzed by using DYMORE. Blades are modeled as elastic beams, hub as a rigid body, torque tubes as rigid bodies, control links as rigid bodies plus springs and several joints. Geometric and material cross-sectional properties of blades (Stiffness-Matrix and Mass-Matrix) are calculated by using VABS programs on a CATIA model. Natural frequencies and natural modes of the rotating (and non-rotating) blades are obtained by using DYMORE. Fan-Plots which show the variation of the natural frequencies for different modes (Lead-Lag, Flapping, Feathering, etc.) vs. rotor RPM are presented.
NEW METHOD FOR SHAPE RECOGNITION BASED ON DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
NOREDINNE GHERABI
2011-02-01
Full Text Available In this paper we present a new method for shape recognition based on dynamic programming. First, each contour of shape is represented by a set of points. After alignment and matching between two shapes, the outline of the shape is divided into parts according to N angular and M radial sectors , Each Sector contains a portion of the contour; thisportion is divided at the inflexion points into convex and concave sections, and the information about sections are extracted in order to provide a semantic content to the outline shape, then this information are coded and transformed into a string of symbols. Finally we find the best alignment of two complete strings and compute the optimal cost of similarity. The algorithm has been tested on a large set of shape databases and real images (MPEG-7, natural silhouette database.
Optimal Charging of Electric Drive Vehicles: A Dynamic Programming Approach
DEFF Research Database (Denmark)
Delikaraoglou, Stefanos; Capion, Karsten Emil; Juul, Nina
2013-01-01
of electric vehicles in a market environment. From the perspective of vehicle operators participating in the electricity spot market, the problem is to optimally charge and discharge the vehicles in response to spot market prices. We consider the case of a vehicle owner who is a price......With the integration of fluctuating renewable production into the electricity system, electric-drive vehicles may contribute to the resulting need for flexibility, given that the market conditions provide sufficient economic incentive. To investigate this, we consider the short-term management......-taker and that of a fleet operator who can influence prices. In both cases, we show how the problem is amenable to dynamic programming with respectively linear and quadratic costs. With discretization of the state space, however, the problem of fleet operation is prone to suffer from the curse of dimensionality and...
Estimating Arrhenius parameters using temperature programmed molecular dynamics
Imandi, Venkataramana; Chatterjee, Abhijit
2016-07-01
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Novel algorithm for distributed replicas management based on dynamic programming
Institute of Scientific and Technical Information of China (English)
Wang Tao; Lu Xianliang; Hou Mengshu
2006-01-01
Replicas can improve the data reliability in distributed system. However, the traditional algorithms for replica management are based on the assumption that all replicas have the uniform reliability, which is inaccurate in some actual systems. To address such problem, a novel algorithm is proposed based on dynamic programming to manage the number and distribution of replicas in different nodes. By using Markov model, replicas management is organized as a multi-phase process, and the recursion equations are provided. In this algorithm, the heterogeneity of nodes, the expense for maintaining replicas and the engaged space have been considered. Under these restricted conditions, this algorithm realizes high data reliability in a distributed system. The results of case analysis prove the feasibility of the algorithm.
Condition-dependent mate choice: A stochastic dynamic programming approach.
Frame, Alicia M; Mills, Alex F
2014-09-01
We study how changing female condition during the mating season and condition-dependent search costs impact female mate choice, and what strategies a female could employ in choosing mates to maximize her own fitness. We address this problem via a stochastic dynamic programming model of mate choice. In the model, a female encounters males sequentially and must choose whether to mate or continue searching. As the female searches, her own condition changes stochastically, and she incurs condition-dependent search costs. The female attempts to maximize the quality of the offspring, which is a function of the female's condition at mating and the quality of the male with whom she mates. The mating strategy that maximizes the female's net expected reward is a quality threshold. We compare the optimal policy with other well-known mate choice strategies, and we use simulations to examine how well the optimal policy fares under imperfect information.
Dynamic programming algorithm for detecting dim infrared moving targets
He, Lisha; Mao, Liangjing; Xie, Lijun
2009-10-01
Infrared (IR) target detection is a key part of airborne infrared weapon system, especially the detection of poor dim moving IR target embedded in complex context. This paper presents an improved Dynamic Programming (DP) algorithm in allusion to low Signal to Noise Ratio (SNR) infrared dim moving targets under cluttered context. The algorithm brings the dim target to prominence by accumulating the energy of pixels in the image sequence, after suppressing the background noise with a mathematical morphology preprocessor. As considering the continuity and stabilization of target's energy and forward direction, this algorithm has well solved the energy scattering problem that exists in the original DP algorithm. An effective energy segmentation threshold is given by a Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter with a regional peak extraction algorithm. Simulation results show that the improved DP tracking algorithm performs well in detecting poor dim targets.
Optimization of decision rules based on dynamic programming approach
Zielosko, Beata
2014-01-14
This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.
Dispersion analysis techniques within the space vehicle dynamics simulation program
Snow, L. S.; Kuhn, A. E.
1975-01-01
The Space Vehicle Dynamics Simulation (SVDS) program was evaluated as a dispersion analysis tool. The Linear Error Analysis (LEA) post processor was examined in detail and simulation techniques relative to conducting a dispersion analysis using the SVDS were considered. The LEA processor is a tool for correlating trajectory dispersion data developed by simulating 3 sigma uncertainties as single error source cases. The processor combines trajectory and performance deviations by a root-sum-square (RSS process) and develops a covariance matrix for the deviations. Results are used in dispersion analyses for the baseline reference and orbiter flight test missions. As a part of this study, LEA results were verified as follows: (A) Hand calculating the RSS data and the elements of the covariance matrix for comparison with the LEA processor computed data. (B) Comparing results with previous error analyses. The LEA comparisons and verification are made at main engine cutoff (MECO).
Chimeric alignment by dynamic programming: Algorithm and biological uses
Energy Technology Data Exchange (ETDEWEB)
Komatsoulis, G.A.; Waterman, M.S. [Univ. of Southern California, Los Angeles, CA (United States)
1997-12-01
A new nearest-neighbor method for detecting chimeric 16S rRNA artifacts generated during PCR amplification from mixed populations has been developed. The method uses dynamic programming to generate an optimal chimeric alignment, defined as the highest scoring alignment between a query and a concatenation of a 5{prime} and a 3{prime} segment from two separate entries from a database of related sequences. Chimeras are detected by studying the scores and form of the chimeric and global sequence alignments. The chimeric alignment method was found to be marginally more effective than k-tuple based nearest-neighbor methods in simulation studies, but its most effective use is in concert with k-tuple methods. 15 refs., 3 figs., 1 tab.
A Dynamic Programming Approach To Length-Limited Huffman Coding
Golin, Mordecai
2008-01-01
The ``state-of-the-art'' in Length Limited Huffman Coding algorithms is the $\\Theta(ND)$-time, $\\Theta(N)$-space one of Hirschberg and Larmore, where $D\\le N$ is the length restriction on the code. This is a very clever, very problem specific, technique. In this note we show that there is a simple Dynamic-Programming (DP) method that solves the problem with the same time and space bounds. The fact that there was an $\\Theta(ND)$ time DP algorithm was previously known; it is a straightforward DP with the Monge property (which permits an order of magnitude speedup). It was not interesting, though, because it also required $\\Theta(ND)$ space. The main result of this paper is the technique developed for reducing the space. It is quite simple and applicable to many other problems modeled by DPs with the Monge property. We illustrate this with examples from web-proxy design and wireless mobile paging.
Application of dynamic programming to structural repairing strategies
Institute of Scientific and Technical Information of China (English)
陈朝晖; LIU; Xila; 等
2002-01-01
A model of dynamic programming for repairing strategies of concrete structures during a projected service period is proposed,which takes into account the degradation in strength of components and the probability of accidental load.This model takes the safety grade of a structural system as the state variable of repairing strategies,and incorporates economic factors including expected repair cost,property loss due to structure failure,goods and material loss due to structure failure,loss of production interrupt due to structure failure,and inspection cost in decision making.It is found that the optimal repairing strategies are sensitive to the probability of accidental loads as well as the failure costs.The practicality of the model is demonstrated by an example.
Reversible circuit synthesis by genetic programming using dynamic gate libraries
Abubakar, Mustapha Y.; Jung, Low Tang; Zakaria, Nordin; Younes, Ahmed; Abdel-Aty, Abdel-Haleem
2017-06-01
We have defined a new method for automatic construction of reversible logic circuits by using the genetic programming approach. The choice of the gate library is 100% dynamic. The algorithm is capable of accepting all possible combinations of the following gate types: NOT TOFFOLI, NOT PERES, NOT CNOT TOFFOLI, NOT CNOT SWAP FREDKIN, NOT CNOT TOFFOLI SWAP FREDKIN, NOT CNOT PERES, NOT CNOT SWAP FREDKIN PERES, NOT CNOT TOFFOLI PERES and NOT CNOT TOFFOLI SWAP FREDKIN PERES. Our method produced near optimum circuits in some cases when a particular subset of gate types was used in the library. Meanwhile, in some cases, optimal circuits were produced due to the heuristic nature of the algorithm. We compared the outcomes of our method with several existing synthesis methods, and it was shown that our algorithm performed relatively well compared to the previous synthesis methods in terms of the output efficiency of the algorithm and execution time as well.
Estimating Arrhenius parameters using temperature programmed molecular dynamics.
Imandi, Venkataramana; Chatterjee, Abhijit
2016-07-21
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Dynamic programming on a tree for ultrasound elastography
Shams, Roozbeh; Boily, Mathieu; Martineau, Paul A.; Rivaz, Hassan
2016-04-01
Ultrasound Elastography is an emerging imaging technique that allows estimation of the mechanical characteristics of tissue. Two issues that need to be addressed before widespread use of elastography in clinical environments are real time constraints and deteriorating effects of signal decorrelation between pre- and post-compression images. Previous work has used Dynamic Programming (DP) to estimate tissue deformation. However, in case of large signal decorrelation, DP can fail. In this paper we, have proposed a novel solution to this problem by solving DP on a tree instead of a single Radio-Frequency line. Formulation of DP on a tree allows exploiting significantly more information, and as such, is more robust and accurate. Our results on phantom and in-vivo human data show that DP on tree significantly outperforms traditional DP in ultrasound elastography.
Design and Analysis of Decision Rules via Dynamic Programming
Amin, Talha M.
2017-04-24
The areas of machine learning, data mining, and knowledge representation have many different formats used to represent information. Decision rules, amongst these formats, are the most expressive and easily-understood by humans. In this thesis, we use dynamic programming to design decision rules and analyze them. The use of dynamic programming allows us to work with decision rules in ways that were previously only possible for brute force methods. Our algorithms allow us to describe the set of all rules for a given decision table. Further, we can perform multi-stage optimization by repeatedly reducing this set to only contain rules that are optimal with respect to selected criteria. One way that we apply this study is to generate small systems with short rules by simulating a greedy algorithm for the set cover problem. We also compare maximum path lengths (depth) of deterministic and non-deterministic decision trees (a non-deterministic decision tree is effectively a complete system of decision rules) with regards to Boolean functions. Another area of advancement is the presentation of algorithms for constructing Pareto optimal points for rules and rule systems. This allows us to study the existence of “totally optimal” decision rules (rules that are simultaneously optimal with regards to multiple criteria). We also utilize Pareto optimal points to compare and rate greedy heuristics with regards to two criteria at once. Another application of Pareto optimal points is the study of trade-offs between cost and uncertainty which allows us to find reasonable systems of decision rules that strike a balance between length and accuracy.
Directory of Open Access Journals (Sweden)
Jooyoung Park
2015-05-01
Full Text Available Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP. ADP methods are important tools in the fields of stochastic control and machine learning, and the utilization of these tools for practical engineering problems is now an active and promising research field. We propose an ADP-based procedure based on optimization under constraints including the iterated Bellman inequalities, which can be solved by convex optimization carried out offline, to find the optimal power management rules for portable HPSSs. The effectiveness of the proposed procedure is tested through dynamic simulations for smartphone workload scenarios, and simulation results show that the proposed strategy can successfully cope with uncertain workload demands.
Lewis, F L; Vamvoudakis, Kyriakos G
2011-02-01
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.
Optimal power system management via mixed integer dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Kwatny, H.G.; Mensah, E. [Drexel Univ., Philadelphia, PA (United States). Dept. of Mechanical Engineering and Mechanics; Niebur, D. [Drexel Univ., Philadelphia, PA (United States). Dept. of Electrical and Computer Engineering; Teolis, C. [Techno-Sciences Inc., Lanham, MD (United States)
2006-07-01
Power systems are comprised of continuous and discrete acting components and subsystems. This paper discussed a logical specification that was used to define the transition dynamics of the discrete subsystem. It also presented a computational tool that reduced the logical specification to a set of inequalities as well as the use of the transformed model in a dynamic programming approach to the design of the optimal feedback controls. An example of optimal load shedding within a power system with an aggregate induction motor and constant admittance loads was presented. Specifically, the paper outlined the problem and discussed the modeling of hybrid systems and the control problem. A solution to the optimal control problem was presented. The essential feature of the model was the characterization of the discrete subsystem in terms of a set of mixed-integer formulas. The case example showed how logical constraints involving system real variables, such as case excitation voltage, could be incorporated in the problem via transformation to mixed-integer formulas. 10 refs., 4 figs.
Stochastic dynamic programming applied to planning of robot grinding tasks
Energy Technology Data Exchange (ETDEWEB)
Brown, M.L. (Digital Equipment Corp., Shrewsbury, MA (United States)); Whitney, D.E. (Massachusetts Inst. of Technology, Cambridge, MA (United States))
1994-10-01
This paper proposes an intelligent manufacturing system that can make decisions about the process in light of the uncertain outcome of these decisions and attempts to minimize the expected economic penalty resulting from those decisions. It uses robot weld bead grinding as an example of a process with significant process variations. The need for multiple grinding passes, the poor predictability of those passes, the task requirements, and the process constraints conspire to make planning and controlling weld bead grinding a formidable probe. A three tier hierarchical control system is proposed to plan an optimal sequence of grinding passes, dynamically simulate each pass, execute the planned sequence of controlled grinding passes, and modify the pass sequence as grinding continues. The top tier, described in this paper, plans the grinding sequence for each weld bead, and is implemented using Stochastic Dynamic Programming, selecting the volumetric removal and feedspeed for each pass in order to optimize the satisfaction of the task requirements by the entire grinding sequence within the equipment, task, and process constraints. The resulting optimal policies have quite complex structures, showing foresight, anxiety, indifference, and aggressiveness, depending upon the situation.
Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems.
Yang, Yongliang; Wunsch, Donald; Yin, Yixin
2017-02-01
This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.
Dynamic Line Rating Oncor Electric Delivery Smart Grid Program
Energy Technology Data Exchange (ETDEWEB)
Johnson, Justin; Smith, Cale; Young, Mike; Donohoo, Ken; Owen, Ross; Clark, Eddit; Espejo, Raul; Aivaliotis, Sandy; Stelmak, Ron; Mohr, Ron; Barba, Cristian; Gonzalez, Guillermo; Malkin, Stuart; Dimitrova, Vessela; Ragsdale, Gary; Mitchem, Sean; Jeirath, Nakul; Loomis, Joe; Trevino, Gerardo; Syracuse, Steve; Hurst, Neil; Mereness, Matt; Johnson, Chad; Bivens, Carrie
2013-05-04
Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar
Knowledge representation and rule-based solution system for dynamic programming model
Institute of Scientific and Technical Information of China (English)
胡祥培; 王旭茵
2003-01-01
A knowledge representation has been proposed using the state-space theory of Artificial Intelligencefor Dynamic Programming Model, in which a model can be defined as a six-tuple M = (I,G,O,T,D,S). Abuilding block modeling method uses the modules of a six-tuple to form a rule-based solution model. Moreover,a rule-based system has been designed and set up to solve the Dynamic Programming Model. This knowledge-based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynam-ic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Program-ming Model can also be conveniently realized in computer.
A Rapid Grid Search Method for Solving Dynamic Programming Problems in Economics
Hui He; Hao Zhang
2013-01-01
We introduce a rapid grid search method in solving dynamic programming problems in economics. Compared to mainstream grid search methods, by using local information of the Bellman equation, this method can significantly increase the efficiency in solving dynamic programming problems by reducing the grid points searched in the control space.
A Note on a Rapid Grid Search Method for Solving Dynamic Programming Problems in Economics
Hui He; Hao Zhang
2010-01-01
We introduce a rapid grid search method in solving the dynamic programming problems in economics. Compared to mainstream grid search methods, by using local information of the Bellman equation, this method can significantly increase the efficiency in solving dynamic programming problems by reducing the grid points searched in the control space.
F -Discrepancy for Efficient Sampling in Approximate Dynamic Programming.
Cervellera, Cristiano; Maccio, Danilo
2016-07-01
In this paper, we address the problem of generating efficient state sample points for the solution of continuous-state finite-horizon Markovian decision problems through approximate dynamic programming. It is known that the selection of sampling points at which the value function is observed is a key factor when such function is approximated by a model based on a finite number of evaluations. A standard approach consists in generating these points through a random or deterministic procedure, aiming at a balanced covering of the state space. Yet, this solution may not be efficient if the state trajectories are not uniformly distributed. Here, we propose to exploit F -discrepancy, a quantity that measures how closely a set of random points represents a probability distribution, and introduce an example of an algorithm based on such concept to automatically select point sets that are efficient with respect to the underlying Markovian process. An error analysis of the approximate solution is provided, showing how the proposed algorithm enables convergence under suitable regularity hypotheses. Then, simulation results are provided concerning an inventory forecasting test problem. The tests confirm in general the important role of F -discrepancy, and show how the proposed algorithm is able to yield better results than uniform sampling, using sets even 50 times smaller.
A stochastic dynamic programming model for stream water quality management
Indian Academy of Sciences (India)
P P Mujumdar; Pavan Saxena
2004-10-01
This paper deals with development of a seasonal fraction-removal policy model for waste load allocation in streams addressing uncertainties due to randomness and fuzziness. A stochastic dynamic programming (SDP) model is developed to arrive at the steady-state seasonal fraction-removal policy. A fuzzy decision model (FDM) developed by us in an earlier study is used to compute the system performance measure required in the SDP model. The state of the system in a season is deﬁned by streamﬂows at the headwaters during the season and the initial DO deﬁcit at some pre-speciﬁed checkpoints. The random variation of streamﬂows is included in the SDP model through seasonal transitional probabilities. The decision vector consists of seasonal fraction-removal levels for the efﬂuent dischargers. Uncertainty due to imprecision (fuzziness) associated with water quality goals is addressed using the concept of fuzzy decision. Responses of pollution control agencies to the resulting end-of-season DO deﬁcit vector and that of dischargers to the fraction-removal levels are treated as fuzzy, and modelled with appropriate membership functions. Application of the model is illustrated with a case study of the Tungabhadra river in India.
Cursive script segmentation and recognition by dynamic programming
Man, Gary M. T.; Poon, Joe C. H.
1993-04-01
Traditionally, the problem of cursive script recognition has been handled in two fundamental ways: one based on the global approach and the other on the segmentation approach. In this paper, we present an inexact segmentation approach to segment the word into letters or even strokes. Our algorithm searches for high curvature points along the lower contour of the image profile. These points are then treated as segment points and marked as potential letter boundaries. Using the histogram profile, an initial estimation of the word length is made. Yet, this estimated word length may be adjusted later. In the process, dynamic programming is used as a general optimization technique to produce a list of possible candidates of the same word length. If the score of these candidates cannot meet some recognition criteria, the word length is re-estimated and another set of candidates are generated. Eventually, an entropy- based measure is provided for comparison among candidates of different word length. In our system, a contextual postprocessor can easily be added to further improve the recognition rate. But in this instance, we have an additional advantage in that a large number of candidates of variable word length are available for selection and even some words with unrecognized letters may also be taken into consideration. In this paper, some experiments are also carried out to evaluate the performance of our novel algorithm.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha
2013-02-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.
Dynamic programming approach for partial decision rule optimization
Amin, Talha
2012-10-04
This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.
Dynamic Programming Using Polar Variance for Image Segmentation.
Rosado-Toro, Jose A; Altbach, Maria I; Rodriguez, Jeffrey J
2016-10-06
When using polar dynamic programming (PDP) for image segmentation, the object size is one of the main features used. This is because if size is left unconstrained the final segmentation may include high-gradient regions that are not associated with the object. In this paper, we propose a new feature, polar variance, which allows the algorithm to segment objects of different sizes without the need for training data. The polar variance is the variance in a polar region between a user-selected origin and a pixel we want to analyze. We also incorporate a new technique that allows PDP to segment complex shapes by finding low-gradient regions and growing them. The experimental analysis consisted on comparing our technique with different active contour segmentation techniques on a series of tests. The tests consisted on robustness to additive Gaussian noise, segmentation accuracy with different grayscale images and finally robustness to algorithm-specific parameters. Experimental results show that our technique performs favorably when compared to other segmentation techniques.
Optimization of conventional water treatment plant using dynamic programming.
Mostafa, Khezri Seyed; Bahareh, Ghafari; Elahe, Dadvar; Pegah, Dadras
2015-12-01
In this research, the mathematical models, indicating the capability of various units, such as rapid mixing, coagulation and flocculation, sedimentation, and the rapid sand filtration are used. Moreover, cost functions were used for the formulation of conventional water and wastewater treatment plant by applying Clark's formula (Clark, 1982). Also, by applying dynamic programming algorithm, it is easy to design a conventional treatment system with minimal cost. The application of the model for a case reduced the annual cost. This reduction was approximately in the range of 4.5-9.5% considering variable limitations. Sensitivity analysis and prediction of system's feedbacks were performed for different alterations in proportion from parameters optimized amounts. The results indicated (1) that the objective function is more sensitive to design flow rate (Q), (2) the variations in the alum dosage (A), and (3) the sand filter head loss (H). Increasing the inflow by 20%, the total annual cost would increase to about 12.6%, while 20% reduction in inflow leads to 15.2% decrease in the total annual cost. Similarly, 20% increase in alum dosage causes 7.1% increase in the total annual cost, while 20% decrease results in 7.9% decrease in the total annual cost. Furthermore, the pressure decrease causes 2.95 and 3.39% increase and decrease in total annual cost of treatment plants.
Dynamic programming approach for newborn's incubator humidity control.
Bouattoura, D; Villon, P; Farges, G
1998-01-01
The anatomy, physiology, and biochemistry of the human skin have been studied for a long time. A special interest has been shown in the water permeability of the premature infant's skin, which is known to be an important factor in the maintenance of a controlled water and heat balance. The rate of evaporative heat exchange between the skin surface of a very premature infant and the surrounding incubator air may be so high that evaporative heat loss alone may exceed the infant's total metabolic heat production. However, it has been demonstrated in several investigations published in recent years that basal evaporative water loss can be consistently reduced by increasing the ambient humidity. Nevertheless, the passive humidification system (water reservoir) used in most incubators cannot achieve high and steady humidity levels. In this paper, we propose an active humidification system. The algorithm is based on a combination of optimal control theory and dynamic programming approach. The relative-humidity (R.H.) regulation is performed in range of 35-90% at 33 degrees C with small oscillations (+/- 0.5% R.H.) around the reference value (i.e., prescribed R.H.).
Dynamic Programming and Genetic Algorithm for Business Processes Optimisation
Directory of Open Access Journals (Sweden)
Mateusz Wibig
2012-12-01
Full Text Available There are many business process modelling techniques, which allow to capture features of those processes, but graphical, diagrammatic models seems to be used most in companies and organizations. Although the modelling notations are more and more mature and can be used not only to visualise the process idea but also to implement it in the workflow solution and although modern software allows us to gather a lot of data for analysis purposes, there is still not much commercial used business process optimisation methods. In this paper the scheduling / optimisation method for automatic task scheduling in business processes models is described. The Petri Net model is used, but it can be easily applied to any other modelling notation, where the process is presented as a set of tasks, i.e. BPMN (Business Process Modelling Notation. The method uses Petri Nets’, business processes’ scalability and dynamic programming concept to reduce the necessary computations, by revising only those parts of the model, to which the change was applied.
Replacement model of city bus: A dynamic programming approach
Arifin, Dadang; Yusuf, Edhi
2017-06-01
This paper aims to develop a replacement model of city bus vehicles operated in Bandung City. This study is driven from real cases encountered by the Damri Company in the efforts to improve services to the public. The replacement model propounds two policy alternatives: First, to maintain or keep the vehicles, and second is to replace them with new ones taking into account operating costs, revenue, salvage value, and acquisition cost of a new vehicle. A deterministic dynamic programming approach is used to solve the model. The optimization process was heuristically executed using empirical data of Perum Damri. The output of the model is to determine the replacement schedule and the best policy if the vehicle has passed the economic life. Based on the results, the technical life of the bus is approximately 20 years old, while the economic life is an average of 9 (nine) years. It means that after the bus is operated for 9 (nine) years, managers should consider the policy of rejuvenation.
Munneke, M.; Jong, Z. de; Zwinderman, A.H.; Jansen, A.; Ronday, H.K.; Peter, W.F.H.; Boonman, D.C.G.; Ende, C.H.M. van den; Vliet Vlieland, T.P.M.; Hazes, J.M.W.
2003-01-01
OBJECTIVE: To evaluate adherence and satisfaction of patients with rheumatoid arthritis (RA) in a long-term intensive dynamic exercise program. METHODS: A total of 146 RA patients started an intensive (strength and endurance training for 75 minutes, twice a week, for 2 years) exercise program (Rheum
Schmid, Verena
2012-06-16
Emergency service providers are supposed to locate ambulances such that in case of emergency patients can be reached in a time-efficient manner. Two fundamental decisions and choices need to be made real-time. First of all immediately after a request emerges an appropriate vehicle needs to be dispatched and send to the requests' site. After having served a request the vehicle needs to be relocated to its next waiting location. We are going to propose a model and solve the underlying optimization problem using approximate dynamic programming (ADP), an emerging and powerful tool for solving stochastic and dynamic problems typically arising in the field of operations research. Empirical tests based on real data from the city of Vienna indicate that by deviating from the classical dispatching rules the average response time can be decreased from 4.60 to 4.01 minutes, which corresponds to an improvement of 12.89%. Furthermore we are going to show that it is essential to consider time-dependent information such as travel times and changes with respect to the request volume explicitly. Ignoring the current time and its consequences thereafter during the stage of modeling and optimization leads to suboptimal decisions.
A user's guide to the Flexible Spacecraft Dynamics and Control Program
Fedor, J. V.
1984-01-01
A guide to the use of the Flexible Spacecraft Dynamics Program (FSD) is presented covering input requirements, control words, orbit generation, spacecraft description and simulation options, and output definition. The program can be used in dynamics and control analysis as well as in orbit support of deployment and control of spacecraft. The program is applicable to inertially oriented spinning, Earth oriented or gravity gradient stabilized spacecraft. Internal and external environmental effects can be simulated.
Energy Technology Data Exchange (ETDEWEB)
Tinianow, M.A.; Rotelli, R.L. Jr.; Baird, J.A.
1984-06-01
User instructions for the GEODYN Interactive Finite Element Computer Program are presented. The program is capable of performing the analysis of the three-dimensional transient dynamic response of a Polycrystalline Diamond Compact Bit - Bit Sub arising from the intermittent contact of the bit with the downhole rock formations. The program accommodates non-linear, time dependent, loading and boundary conditions.
Evolutionary programming for goal-driven dynamic planning
Vaccaro, James M.; Guest, Clark C.; Ross, David O.
2002-03-01
Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move
Developing molecular dynamics simulation codes using mixed language programming
Energy Technology Data Exchange (ETDEWEB)
DeBoni, T.; Feo, J.T. [Lawrence Livermore National Lab., CA (United States); Caffey, H.; Hausheer, F. [BioNumerik Pharmaceuticals, Inc., San Antonio, TX (United States)
1994-05-01
We describe our experiences parallelizing a large-scale scientific application to model systems of discrete particles. We describe the approach and tasks undertaken to parallelize this application using two different programming paradigms: imperative and functional. The objectives of both exercises were to maximize performance, parallelism and portability, and to minimize program development costs. We believe this study reveals an important relationship between conventional and novel parallel programming paradigms, and identifies important attributes that novel paradigms must have to gain wide acceptance.
Bellman's GAP : a 2nd generation language and system for algebraic dynamic programming
Sauthoff, Georg
2010-01-01
The dissertation describes the new Bellmans GAP which is a programming system for writing dynamic programming algorithms over sequential data. It is the second generation implementation of the algebraic dynamic programming framework (ADP). The system includes the multi-paradigm language (GAP-L), its compiler (GAP-C), functional modules (GAP-M) and a web site (GAP Pages) to experiment with GAP-L programs. GAP-L includes declarative constructs, e.g. tree grammars to model the search space, and...
Fixed point theorems for compatible mappings of type (P and applications to dynamic programming
Directory of Open Access Journals (Sweden)
H. K. Pathak
1995-11-01
Full Text Available In this paper, we prove some common fixed point theorems for compatible mappings of type (P. As applications, the existence and uniqueness of common solutions for a class of the functional equations in dynamic programming are discussed.
Program participation, labor force dynamics, and accepted wage rates
DEFF Research Database (Denmark)
Munch, Jakob Roland; Skipper, Lars
2008-01-01
We apply a recently suggested econometric approach to measure the effects of active labor market programs on employment, unemployment, and wage histories among participants. We find that participation in most of these training programs produces an initial locking-in effect and for some even a lower...... subpopulations. These longer spells of employment come at a cost of lower accepted hourly wage rates...
Institute of Scientific and Technical Information of China (English)
陈志平
2003-01-01
A new deterministic formulation,called the conditional expectation formulation,is proposed for dynamic stochastic programming problems in order to overcome some disadvantages of existing deterministic formulations.We then check the impact of the new deterministic formulation and other two deterministic formulations on the corresponding problem size,nonzero elements and solution time by solving some typical dynamic stochastic programming problems with different interior point algorithms.Numerical results show the advantage and application of the new deterministic formulation.
Directory of Open Access Journals (Sweden)
Anders Gjelsvik
1982-07-01
Full Text Available A first-order differential dynamic programming (DDP algorithm is used for computing optimal control for a five-reservoir system, where the stochastic inflow process has been approximated by a few discrete disturbance values in each time step. The method is found to be faster than linear programming, previously tried on the same system model.
Program for quantum wave-packet dynamics with time-dependent potentials
Dion, C M; Rahali, G
2014-01-01
We present a program to simulate the dynamics of a wave packet interacting with a time-dependent potential. The time-dependent Schr\\"odinger equation is solved on a one-, two-, or three-dimensional spatial grid using the split operator method. The program can be compiled for execution either on a single processor or on a distributed-memory parallel computer.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1991-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All the calculati...
DYNAMIC PROGRAMMING AND ADAPTIVE PROCESSES--1: MATHEMATICAL FOUNDATION
engulf the field of operations research, and play a paramount role in the current theory of stochastic control processes of ejectronic and mechanical ...origin. All three of these domains merge in the consideration of the problems of communication theory. The functional equation approach of dynamic
DISCRETE DYNAMIC MODEL OF BEVEL GEAR – VERIFICATION THE PROGRAM SOURCE CODE FOR NUMERICAL SIMULATION
Directory of Open Access Journals (Sweden)
Krzysztof TWARDOCH
2014-06-01
Full Text Available In the article presented a new model of physical and mathematical bevel gear to study the influence of design parameters and operating factors on the dynamic state of the gear transmission. Discusses the process of verifying proper operation of copyright calculation program used to determine the solutions of the dynamic model of bevel gear. Presents the block diagram of a computing algorithm that was used to create a program for the numerical simulation. The program source code is written in an interactive environment to perform scientific and engineering calculations, MATLAB
Snow, L. S.; Kuhn, A. E.
1975-01-01
Previous error analyses conducted by the Guidance and Dynamics Branch of NASA have used the Guidance Analysis Program (GAP) as the trajectory simulation tool. Plans are made to conduct all future error analyses using the Space Vehicle Dynamics Simulation (SVDS) program. A study was conducted to compare the inertial measurement unit (IMU) error simulations of the two programs. Results of the GAP/SVDS comparison are presented and problem areas encountered while attempting to simulate IMU errors, vehicle performance uncertainties and environmental uncertainties using SVDS are defined. An evaluation of the SVDS linear error analysis capability is also included.
Program participation, labor force dynamics, and accepted wage rates
DEFF Research Database (Denmark)
Munch, Jakob Roland; Skipper, Lars
2008-01-01
transition rate from unemployment to employment upon completion. Most programs, therefore, increase the expected duration of unemployment spells. However, we find that the training undertaken while unemployed successfully increases the expected duration of subsequent spells of employment for many...... subpopulations. These longer spells of employment come at a cost of lower accepted hourly wage rates...
SPOT: an optimization software for dynamic observation programming
Lagrange, Anne-Marie; Rubini, Pascal; Brauner-Vettier, Nadia; Cambazard, Hadrien; Catusse, Nicolas; Lemaire, Pierre; Baude, Laurence
2016-07-01
The surveys dedicated to the search for extrasolar planets with the recently installed extreme-AO, high contrast Planet Imagers generally include hundreds of targets, to be observed sometimes repeatedly, generally in Angular Differential Imaging Mode. Each observation has to fulfill several time-dependent constraints, which makes a manual elaboration of an optimized planning impossible. We have developed a software (SPOT), an easy to use tool with graphical interface that allows both long term (months, years) and dynamic (nights) optimized scheduling of such surveys, taking into account all relevant constraints. Tests show that excellent schedules and high filling efficiencies can be obtained with execution times compatible with real-time scheduling, making possible to take in account complex constraints and to dynamically adapt planning to unexpected circumstances even during their execution. Moreover, such a tool is very valuable during survey preparations to build target lists and calendars. SPOT could be easily adapted for scheduling observations other instruments or telescopes.
Grammatikopoulos, Vasilis
2012-01-01
The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic…
Grammatikopoulos, Vasilis
2012-01-01
The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic…
Grammatikopoulos, Vasilis
2012-01-01
The current study attempts to integrate parts of program theory and systems-based procedures in educational program evaluation. The educational program that was implemented, called the "Early Steps" project, proposed that physical education can contribute to various educational goals apart from the usual motor skills improvement. Basic elements of…
A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
Directory of Open Access Journals (Sweden)
Jooyong Yi
2013-09-01
Full Text Available Backtracking (i.e., reverse execution helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug. So far backtracking has been implemented mostly by state saving or by checkpointing. These implementations, however, inherently do not scale. Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving. In the literature, there can be found two methods that generate reverse code: (a static reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session. In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g., multi-threading. To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours. We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program. In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms the existing backtracking methods in terms of memory efficiency.
A multi-objective dynamic programming approach to constrained discrete-time optimal control
Energy Technology Data Exchange (ETDEWEB)
Driessen, B.J.; Kwok, K.S.
1997-09-01
This work presents a multi-objective differential dynamic programming approach to constrained discrete-time optimal control. In the backward sweep of the dynamic programming in the quadratic sub problem, the sub problem input at a stage or time step is solved for in terms of the sub problem state entering that stage so as to minimize the summed immediate and future cost subject to minimizing the summed immediate and future constraint violations, for all such entering states. The method differs from previous dynamic programming methods, which used penalty methods, in that the constraints of the sub problem, which may include terminal constraints and path constraints, are solved exactly if they are solvable; otherwise, their total violation is minimized. Again, the resulting solution of the sub problem is an input history that minimizes the quadratic cost function subject to being a minimizer of the total constraint violation. The expected quadratic convergence of the proposed algorithm is demonstrated on a numerical example.
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2009-01-01
This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost...... efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce...... the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained....
1991-01-01
Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper develops a straightforward but effective algorithm for molecular dynamics simulations using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a netw...
Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism
DEFF Research Database (Denmark)
Achenbach, Michael; Ostermann, Klaus
2010-01-01
without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines.......The implementation of unit tests with mock objects and stubs often involves substantial manual work. Stubbed methods return simple default values, therefore variations of these values require separate test cases. The integration of mock objects often requires more infrastructure code and design...
Watermarking Java Programs using Dummy Methods with Dynamically Opaque Predicates
Akbar, Zaenal
2010-01-01
Software piracy, the illegal using, copying, and resale of applications is a major concern for anyone develops software. Software developers also worry about their applications being reverse engineered by extracting data structures and algorithms from an application and incorporated into competitor's code. A defense against software piracy is watermarking, a process that embeds a secret message in a cover software. Watermarking is a method that does not aim to stop piracy copying, but to prove ownership of the software and possibly even the data structures and algorithms used in the software. The language Java was designed to be compiled into a platform independent bytecode format. Much of the information contained in the source code remains in the bytecode, which means that decompilation is easier than with traditional native codes. In this thesis, we present a technique for watermarking Java programs by using a never-executed dummy method (Monden et.al., 2000) combined with opaque predicates (Collberg et.al...
Repetitive elements dynamics in cell identity programming, maintenance and disease
Bodega, Beatrice
2014-12-01
The days of \\'junk DNA\\' seem to be over. The rapid progress of genomics technologies has been unveiling unexpected mechanisms by which repetitive DNA and in particular transposable elements (TEs) have evolved, becoming key issues in understanding genome structure and function. Indeed, rather than \\'parasites\\', recent findings strongly suggest that TEs may have a positive function by contributing to tissue specific transcriptional programs, in particular as enhancer-like elements and/or modules for regulation of higher order chromatin structure. Further, it appears that during development and aging genomes experience several waves of TEs activation, and this contributes to individual genome shaping during lifetime. Interestingly, TEs activity is major target of epigenomic regulation. These findings are shedding new light on the genome-phenotype relationship and set the premises to help to explain complex disease manifestation, as consequence of TEs activity deregulation.
Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R
2013-01-01
This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.
Karachanskaya, Elena
2012-01-01
Investigate the stochastic dynamic non-linear system with the Wiener and the Poisson perturbations. For such systems we construct the program control with probability one, which allows this system to move on the given trajectory. In this case the control program is solution of the algebraic system of linear equations. Considered algorithm is based on the first integral theory for stochastic differential equations system.
A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon
Energy Technology Data Exchange (ETDEWEB)
D`Azevedo, E.F.; Romine, C.H.
1994-12-01
This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON-PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing.
A New Shared-Memory Programming Paradigm for Molecular Dynamics Simulations on the Intel Paragon
Energy Technology Data Exchange (ETDEWEB)
D' Azevedo, E.F.
1995-01-01
This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing.
A novel neural dynamical approach to convex quadratic program and its efficient applications.
Xia, Youshen; Sun, Changyin
2009-12-01
This paper proposes a novel neural dynamical approach to a class of convex quadratic programming problems where the number of variables is larger than the number of equality constraints. The proposed continuous-time and proposed discrete-time neural dynamical approach are guaranteed to be globally convergent to an optimal solution. Moreover, the number of its neurons is equal to the number of equality constraints. In contrast, the number of neurons in existing neural dynamical methods is at least the number of the variables. Therefore, the proposed neural dynamical approach has a low computational complexity. Compared with conventional numerical optimization methods, the proposed discrete-time neural dynamical approach reduces multiplication operation per iteration and has a large computational step length. Computational examples and two efficient applications to signal processing and robot control further confirm the good performance of the proposed approach.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge an...... in a simply supported plane, vibrating beam model. Results show optimal number of sensors and their locations....... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...
Institute of Scientific and Technical Information of China (English)
Ze-qing Liu; Shin Min Kang
2007-01-01
In this paper we establish the existence,uniqueness and iterative approxinlation of solutions for two classes of functional equations arising in dynamic programming of multistage decision Processes.The resultspresented here extend,and unify the corresponding results due to Bellman,Bhakta and Choudhury,Bhakta and Mitra,Liu and others.
The Repeated School-to-Work Transition: Evidence from a Dynamic Programming Model
DEFF Research Database (Denmark)
Nielsen, Helena Skyt
by youths after high school graduation. It is assumed that the decision is taken year by year, and it is analyzed in a discrete choice dynamic programming model. In this forward-looking behavioral model, it is shown that a small bonus would remove interruptions of the educational careers just after high...
ℋ-Operator Pairs with Application to Functional Equations Arising in Dynamic Programming
Directory of Open Access Journals (Sweden)
A. Razani
2014-01-01
Full Text Available Some common fixed point theorems for ℋ-operator pairs are proved. As an application, the existence and uniqueness of the common solution for systems of functional equations arising in dynamic programming are discussed. Also, an example to validate all the conditions of the main result is presented.
A dynamic programming approach to missing data estimation using neural networks
CSIR Research Space (South Africa)
Nelwamondo, FV
2013-01-01
Full Text Available This paper develops and presents a novel technique for missing data estimation using a combination of dynamic programming, neural networks and genetic algorithms (GA) on suitable subsets of the input data. The method proposed here is well suited...
Modeling Dynamic Programming Problems over Sequences and Trees with Inverse Coupled Rewrite Systems
Directory of Open Access Journals (Sweden)
Robert Giegerich
2014-03-01
Full Text Available Dynamic programming is a classical algorithmic paradigm, which often allows the evaluation of a search space of exponential size in polynomial time. Recursive problem decomposition, tabulation of intermediate results for re-use, and Bellman’s Principle of Optimality are its well-understood ingredients. However, algorithms often lack abstraction and are difficult to implement, tedious to debug, and delicate to modify. The present article proposes a generic framework for specifying dynamic programming problems. This framework can handle all kinds of sequential inputs, as well as tree-structured data. Biosequence analysis, document processing, molecular structure analysis, comparison of objects assembled in a hierarchic fashion, and generally, all domains come under consideration where strings and ordered, rooted trees serve as natural data representations. The new approach introduces inverse coupled rewrite systems. They describe the solutions of combinatorial optimization problems as the inverse image of a term rewrite relation that reduces problem solutions to problem inputs. This specification leads to concise yet translucent specifications of dynamic programming algorithms. Their actual implementation may be challenging, but eventually, as we hope, it can be produced automatically. The present article demonstrates the scope of this new approach by describing a diverse set of dynamic programming problems which arise in the domain of computational biology, with examples in biosequence and molecular structure analysis.
Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ
2000-01-01
Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general practitioner-b
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ
2000-01-01
Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general
An Optimal Algorithm towards Successive Location Privacy in Sensor Networks with Dynamic Programming
Zhao, Baokang; Wang, Dan; Shao, Zili; Cao, Jiannong; Chan, Keith C. C.; Su, Jinshu
In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a dynamic programming based algorithm and prove it is optimal in special cases where the correlation only exists between p immediate adjacent observations.
Optimizing Gear Shifting Strategy for Off-Road Vehicle with Dynamic Programming
Directory of Open Access Journals (Sweden)
Xinxin Zhao
2014-01-01
Full Text Available Gear shifting strategy of vehicle is important aid for the acquisition of dynamic performance and high economy. A dynamic programming (DP algorithm is used to optimize the gear shifting schedule for off-road vehicle by using an objective function that weighs fuel use and trip time. The optimization is accomplished through discrete dynamic programming and a trade-off between trip time and fuel consumption is analyzed. By using concave and convex surface road as road profile, an optimal gear shifting strategy is used to control the longitudinal behavior of the vehicle. Simulation results show that the trip time can be reduced by powerful gear shifting strategy and fuel consumption can achieve high economy with economical gear shifting strategy in different initial conditions and route cases.
Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo
2016-04-08
This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.
Nie, Xianghui; Huang, Guo H; Li, Yongping
2009-11-01
This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
Harper, William B.; Shaltens, Richard K.
1993-01-01
Closed Brayton cycle power conversion systems are readily adaptable to any heat source contemplated for space application. The inert gas working fluid can be used directly in gas-cooled reactors and coupled to a variety of heat sources (reactor, isotope or solar) by a heat exchanger. This point is demonstrated by the incorporation in the NASA 2 kWe Solar Dynamic (SD) Space Power Ground Test Demonstration (GTD) Program of the turboalternator-compressor and recuperator from the Brayton Isotope Power System (BIPS) program. This paper will review the goals and status of the SD GTD Program, initiated in April 1992. The performance of the BIPS isotope-heated system will be compared to the solar-heated GTD system incorporating the BIPS components and the applicability of the GTD test bed to dynamics space nuclear power R&D will be discussed.
Sutrisno; Widowati; Solikhin
2016-06-01
In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.
An Approach for Dynamic Optimization of Prevention Program Implementation in Stochastic Environments
Kang, Yuncheol; Prabhu, Vittal
The science of preventing youth problems has significantly advanced in developing evidence-based prevention program (EBP) by using randomized clinical trials. Effective EBP can reduce delinquency, aggression, violence, bullying and substance abuse among youth. Unfortunately the outcomes of EBP implemented in natural settings usually tend to be lower than in clinical trials, which has motivated the need to study EBP implementations. In this paper we propose to model EBP implementations in natural settings as stochastic dynamic processes. Specifically, we propose Markov Decision Process (MDP) for modeling and dynamic optimization of such EBP implementations. We illustrate these concepts using simple numerical examples and discuss potential challenges in using such approaches in practice.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Institute of Scientific and Technical Information of China (English)
LIU Xiao; WANG Cheng-en
2005-01-01
This paper addresses a single item dynamic lot-sizing model with inventory capacity and out-sourcing. The goal is to minimize the total costs of production, setup, inventory holding and out-sourcing. Two versions of an out-sourcing model with time-varying costs are considered: stock out case and conservation case. Zero Inventory Order property has been found and some new properties are obtained in an optimal solution. Dynamic programming algorithms are developed to solve the problem in strongly polynomial time respectively. Furthermore, some numerical results demonstrate that the approach proposed is efficient and applicable.
Bellman, Richard
2003-01-01
An introduction to the mathematical theory of multistage decision processes, this text takes a ""functional equation"" approach to the discovery of optimum policies. Written by a leading developer of such policies, it presents a series of methods, uniqueness and existence theorems, and examples for solving the relevant equations. The text examines existence and uniqueness theorems, the optimal inventory equation, bottleneck problems in multistage production processes, a new formalism in the calculus of variation, strategies behind multistage games, and Markovian decision processes. Each chapte
Update of the 2 Kw Solar Dynamic Ground Test Demonstration Program
Shaltens, Richard K.; Boyle, Robert V.
1994-01-01
The Solar Dynamic (SD) Ground Test Demonstration (GTD) program demonstrates the operation of a complete 2 kW, SD system in a simulated space environment at a NASA Lewis Research Center (LeRC) thermal-vacuum facility. This paper reviews the goals and status of the SD GTD program. A brief description of the SD system identifying key design features of the system, subsystems, and components is included. An aerospace industry/government team is working together to design, fabricate, assemble, and test a complete SD system.
A 4-cylinder Stirling engine computer program with dynamic energy equations
Daniele, C. J.; Lorenzo, C. F.
1983-05-01
A computer program for simulating the steady state and transient performance of a four cylinder Stirling engine is presented. The thermodynamic model includes both continuity and energy equations and linear momentum terms (flow resistance). Each working space between the pistons is broken into seven control volumes. Drive dynamics and vehicle load effects are included. The model contains 70 state variables. Also included in the model are piston rod seal leakage effects. The computer program includes a model of a hydrogen supply system, from which hydrogen may be added to the system to accelerate the engine. Flow charts are provided.
Automatic programming via iterated local search for dynamic job shop scheduling.
Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen
2015-01-01
Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.
Optimum Repartition of Transport Capacities in the Logistic System using Dynamic Programming
Directory of Open Access Journals (Sweden)
Gheorghe BĂŞANU
2011-08-01
Full Text Available Transportations take an essential role in logistics, interconnecting the majority of processes and operations within logistic system. The efficient use of transportation capacity is a priority whose achievement can diminish logistic costs. This objective is today difficult to achieve due to increasing complexity of transportation monitoring and coordination. This complexity is determined by transportation number and diversity, by the volume and diversity of orders, by increasing the targets to be supplied.Dynamic programming represents a highly useful tool for logistic managers, considering that its specific techniques and methods are oriented toward solving problems related to resource optimum allocation and utilization.The present paper presents briefly a series of theoretical elements of dynamic programming applied in logistics, based on which it is shown a mathematic model to determine the optimum policy for transport capacity repartition for the area attached to a logistic centre, through three distribution centres.
Institute of Scientific and Technical Information of China (English)
HEWei; YANGSuqiong; YUANBaozong; LINBiqin
2004-01-01
Shortest path search has important practical applications and is related to optimization problem.This paper discusses a new algorithm time-synchronous heuristic dynamic programming search, which combined the pruning and global optimization of DP (Dynamic programming) and the partial search of heuristic strategy and found the shortest path in time O(n/kd) (k, d ≥ 1). Furthermore, the algorithm can be applied to find the K shortest paths between a pair of given nodes or all paths less than a given length within the same steps. Finally this algorithm was applied to the shortest path search on the real map and user could use spoken dialog to query shortcut in realtime, 90% of the system responses are correct.
Inamoto, Tsutomu; Tamaki, Hisashi; Murao, Hajime
In this paper, we present a modified dynamic programming (DP) method. The method is basically the same as the value iteration method (VI), a representative DP method, except the preprocess of a system's state transition model for reducing its complexity, and is called the dynamic programming on reduced models (DPRM). That reduction is achieved by imaginarily considering causes of the probabilistic behavior of a system, and then cutting off some causes with low occurring probabilities. In computational illustrations, VI, DPRM, and the real-time Q-learning method (RTQ) are applied to elevator operation problems, which can be modeled by using Markov decision processes. The results show that DPRM can compute quasi-optimal value functions which bring more effective allocations of elevators than value functions by RTQ in less computational times than VI. This characteristic is notable when the traffic pattern is complicated.
A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.
Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng
2017-09-08
Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.
A Case Study on Air Combat Decision Using Approximated Dynamic Programming
Directory of Open Access Journals (Sweden)
Yaofei Ma
2014-01-01
Full Text Available As a continuous state space problem, air combat is difficult to be resolved by traditional dynamic programming (DP with discretized state space. The approximated dynamic programming (ADP approach is studied in this paper to build a high performance decision model for air combat in 1 versus 1 scenario, in which the iterative process for policy improvement is replaced by mass sampling from history trajectories and utility function approximating, leading to high efficiency on policy improvement eventually. A continuous reward function is also constructed to better guide the plane to find its way to “winner” state from any initial situation. According to our experiments, the plane is more offensive when following policy derived from ADP approach other than the baseline Min-Max policy, in which the “time to win” is reduced greatly but the cumulated probability of being killed by enemy is higher. The reason is analyzed in this paper.
Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.
1973-01-01
A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the optimization of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.
Nagy, Ivan
2017-01-01
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation
Directory of Open Access Journals (Sweden)
R. T. N. Cardoso
2013-01-01
Full Text Available A heuristic algorithm is proposed for a class of stochastic discrete-time continuous-variable dynamic programming problems submitted to non-Gaussian disturbances. Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. Thus, decision makers are able to choose any quantile they wish. This new idea is carried out by using Monte Carlo simulations embedded in an approximate algorithm proposed to deterministic dynamic programming problems. The new method is tested in instances of the classical inventory control problem. The results obtained attest for the efficiency and efficacy of the algorithm in solving these important stochastic optimization problems.
A Generic Top-Down Dynamic-Programming Approach to Prefix-Free Coding
Golin, Mordecai; Yu, Jiajin
2008-01-01
Given a probability distribution over a set of n words to be transmitted, the Huffman Coding problem is to find a minimal-cost prefix free code for transmitting those words. The basic Huffman coding problem can be solved in O(n log n) time but variations are more difficult. One of the standard techniques for solving these variations utilizes a top-down dynamic programming approach. In this paper we show that this approach is amenable to dynamic programming speedup techniques, permitting a speedup of an order of magnitude for many algorithms in the literature for such variations as mixed radix, reserved length and one-ended coding. These speedups are immediate implications of a general structural property that permits batching together the calculation of many DP entries.
Multi-Quadratic Dynamic Programming Procedure of - Preserving Denoising for Medical Images
Pham, C. T.; Kopylov, A. V.
2015-05-01
In this paper, we present a computationally efficient technique for edge preserving in medical image smoothing, which is developed on the basis of dynamic programming multi-quadratic procedure. Additionally, we propose a new non-convex type of pair-wise potential functions, allow more flexibility to set a priori preferences, using different penalties for various ranges of differences between the values of adjacent image elements. The procedure of image analysis, based on the new data models, significantly expands the class of applied problems, and can take into account the presence of heterogeneities and discontinuities in the source data, while retaining high computational efficiency of the dynamic programming procedure and Kalman filterinterpolator. Comparative study shows, that our algorithm has high accuracy to speed ratio, especially in the case of high-resolution medical images.
Real-Time Reactive Power Distribution in Microgrids by Dynamic Programing
DEFF Research Database (Denmark)
Levron, Yoash; Beck, Yuval; Katzir, Liran
2017-01-01
combination of reactive powers, by means of dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The paper includes the results......In this paper a new real-time optimization method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain...... a solution by parts, using the dynamic programming method and Bellman equation. The proposed solution method is based on the fact that the microgrid is designed with a central feeder line to which clusters of generators and loads are connected, and is suitable for microgrids with ring topologies as well...
Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao
2013-07-01
This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
Optimal Control of a Fed-batch Fermentation Process by Neuro-Dynamic Programming
Directory of Open Access Journals (Sweden)
Tatiana Ilkova
2004-10-01
Full Text Available In this paper the method for optimal control of a fermentation process is presented, that is based on an approach for optimal control - Neuro-Dynamic programming. For this aim the approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this approach computing time and procedure are decreased and quality of the biomass at the end of the process is increased.
Summer Study Program in Geophysical Fluid Dynamics; Order and Disorder Planetary Dynamos
1988-05-01
PARTICIPANTS Fast Dynamos in Chaotic Flow Bruce Bayly 109 Observational Constraints on Theories of the Geodynamo Jeremy BloxhamIl i I Nonlinear...1986. Phys. Rev. Lett., 57, No. 22, 2800. 4’ %.’ I- 111 , OBSERVATIONAL CONSTRAINTS ON THEORIES OF THE GEODYNAMO Jeremy Bloxham Department of Earth... geodynamo ", 1987 Summer Program in Geophysical Fluid Dynamics, Woods Hole Oceanographic Institu- tion, this volume. Bolton, E.W., 1985. "Problems in
α-Coupled Fixed Points and Their Application in Dynamic Programming
Directory of Open Access Journals (Sweden)
J. Harjani
2014-01-01
Full Text Available We introduce the definition of α-coupled fixed point in the space of the bounded functions on a set S and we present a result about the existence and uniqueness of such points. Moreover, as an application of our result, we study the problem of existence and uniqueness of solutions for a class of systems of functional equations arising in dynamic programming.
A Multi-Scale Modeling and Experimental Program for the Dynamic Mechanical Response of Tissue
2014-12-09
Invited talk at the department of Biomedical Illustration and Visualization, UIC, (2014). Joseph Orgel (11) "How Collagen Structure and...A Multi-Scale Modeling and Experimental Program for the Dynamic Mechanical Response of Tissue We study the mechanical properties of collagen , which...and experiments to examine the theoretical results. The atomistic structure of collagen is determined by Xray diffraction, which provides the
Modeling Dynamic Programming Problems over Sequences and Trees with Inverse Coupled Rewrite Systems
2014-01-01
International audience; Dynamic programming is a classical algorithmic paradigm, which often allows the evaluation of a search space of exponential size in polynomial time. Recursive problem decomposition, tabulation of intermediate results for re-use, and Bellman's Principle of Optimality are its well-understood ingredients. However, algorithms often lack abstraction and are difficult to implement, tedious to debug, and delicate to modify. The present article proposes a generic framework for...
Direct heuristic dynamic programming for nonlinear tracking control with filtered tracking error.
Yang, Lei; Si, Jennie; Tsakalis, Konstantinos S; Rodriguez, Armando A
2009-12-01
This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2016-11-22
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
A Dynamic Programming Algorithm on Project-Gang Investment Decision-Making
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The investment decision-making of Project-Gang, the projects that are associated with one another on economy and technique, is studied. In order to find out the best Scheme that can make the maximum profit, a dynamic programming algorithm on the investment decision-making of Project-Gang is brought forward, and this algorithm can find out the best Scheme of distributing the m resources to the n Items in the time of O(m2n).
Optimal Output Regulation for Heterogeneous Multiagent Systems via Adaptive Dynamic Programming.
Zhang, Huaguang; Liang, Hongjing; Wang, Zhanshan; Feng, Tao
2017-01-01
In this paper, the optimal output regulation problem for partially model-free heterogeneous linear multiagent systems with disturbance generated by an exosystem is addressed by using adaptive dynamic programming and double compensator method. The topology graph for the information exchange of the agents has a spanning tree. The dynamic of individual agent is assumed to be nonidentical and of different dimensions. One distributed compensator is designed to deal with the nonidentical agents, and the other compensator is used to handle the optimal performance index. By constructing the double compensator, the distributed feedback control laws are designed to make the output of each agent synchronize with the reference output and minimize the energy of the output error simultaneously. To overcome the lack of the dynamics knowledge of each agent, a novel online policy iteration algorithm is developed to obtain the optimal feedback gain matrix. Finally, two examples are presented to illustrate the effectiveness of our results.
Shifman, M A; Windemuth, A; Schulten, K; Miller, P L
1992-04-01
Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper reviews these approaches and develops a straightforward but effective algorithm using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.
Daniluk, Andrzej
2007-01-01
A practical computing algorithm working in real time has been developed for calculations of the reflection high-energy electron diffraction from the molecular beam epitaxy growing surface. The calculations are based on a dynamical diffraction theory in which the electrons are scattered on a potential, which is periodic in the direction perpendicular to the surface. New version program summaryTitle of program:RHEED_v2 Catalogue identifier:ADUY_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUY_v1_1 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Catalogue identifier of previous version:ADUY Authors of the original program:A. Daniluk Does the new version supersede the original program:Yes Computer for which the new version is designed and others on which it has been tested: Pentium-based PC Operating systems or monitors under which the new version has been tested: Windows 9x, XP, NT, Linux Programming language used:C++ Memory required to execute with typical data:more than 1 MB Number of bits in a word:64 bits Number of processors used:1 Number of bytes in distributed program, including test data, etc.:1 074 131 No. of lines in distributed program, including test data, etc.:3408 Distribution format:tar.gz Nature of physical problem: Reflection high-energy electron diffraction (RHEED) is a very useful technique for studying the growth and the surface analysis of thin epitaxial structures prepared by the molecular beam epitaxy (MBE). RHEED rocking curves recorded from heteroepitaxial layers are used for the non-destructive evaluation of epilayer thickness and composition with a high degree of accuracy. Rocking curves from such heterostructures are often very complex because the thickness fringes from every layer beat together. Simulations based on dynamical diffraction theory are generally used to interpret the rocking curves of such structures from which very small changes in thickness and composition can be
Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin
2013-12-01
Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency.
Dynamic optimization of complex program controlling the structure of an enterprise's product range
Directory of Open Access Journals (Sweden)
Andrey Fedorovich Shorikov
2012-09-01
Full Text Available This paper reviews a methodical approach to solving multi-step dynamic problem of optimal integrated program management of a product portfolio structure of the enterprise. Any multiproduct manufacturing process depends on many factors, that is why the quality criteria in theeconomic andmathematicalmodel of the dynamics of the product portfolio structuremanagement of a company is a vector one, and therefore, optimization of the integrated product portfolio structure management of a company is multi-criteria optimization problem. With the help of the method of generalized criterion (method of vectorcriterion scalarization, a formed multicriteria problem is replaced by a one-criterion optimization problem of complex management program of product portfolio structure with a functional of quality, which is a convolution of a set (vector of the objective functions. The transformed problem is formulated and solved as a problem of optimal terminal program control in a class of linear discrete dynamical systems. The method proposed in this paper allows developing management solutions designed to create the optimal structure of an enterprise's product lines, contributing to optimization of profits as well as maintenance of the desired level of profit for a long period of time
Institute of Scientific and Technical Information of China (English)
JAHAN A; ABDOLSHAH M
2007-01-01
At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows: ① Minimizing deviation of customer's requirements. ② Maximizing the profit. ③ Minimizing the frequencies of changes in formula production. ④ Minimizing the inventory of final products. ⑤ Balancing the production sections with regard to rate in production. ⑥ Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that's how it is solved.
SOCIAL INTERFACE DYNAMICS IN FOOD PRODUCTION PROGRAM "ZERO HUNGER" OF NICARAGUA
Directory of Open Access Journals (Sweden)
Beverly Castillo Herrera
2015-07-01
Full Text Available This article uses the concept of social interface, coined by Norman Long (2007, to answer the question: How do the processes of planned intervention come into the world of life of individuals and groups? This concept is discussed in the dynamics of the “Zero Hunger“ Food Production Program implemented in Nicaragua since 2007. This research is qualitative. Interviews with women protagonists of the program in the north-central region were applied. The article shows how the concept of social interface permits to analyze the moments of discrepancies between planned and executed social programs, because the various stakeholders are involved in social interactions where interests, needs, power relations, interpretations, symbols and accumulated knowledge are circulating and interacting.
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All the calculat...... for estimating the modal damping parameters in a simply supported plane, vibrating beam model. Results show optimal number of sensors and their locations....... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...
Toh, H
1997-08-01
Two approximations were introduced into the double dynamic programming algorithm, in order to reduce the computational time for structural alignment. One of them was the so-called distance cut-off, which approximately describes the structural environment of each residue by its local environment. In the approximation, a sphere with a given radius is placed at the center of the side chain of each residue. The local environment of a residue is constituted only by the residues with side chain centers that are present within the sphere, which is expressed by a set of center-to-center distances from the side chain of the residue to those of all the other constituent residues. The residues outside the sphere are neglected from the local environment. Another approximation is associated with the distance cut-off, which is referred to here as the delta N cut-off. If two local environments are similar to each other, the numbers of residues constituting the environments are expected to be similar. The delta N cut-off was introduced based on the idea. If the difference between the numbers of the constituent residues of two local environments is greater than a given threshold value, delta N, the evaluation of the similarity between the local environments is skipped. The introduction of the two approximations dramatically reduced the computational time for structural alignment by the double dynamic programming algorithm. However, the approximations also decreased the accuracy of the alignment. To improve the accuracy with the approximations, a program with a two-step alignment algorithm was constructed. At first, an alignment was roughly constructed with the approximations. Then, the epsilon-suboptimal region for the alignment was determined. Finally, the double dynamic programming algorithm with full structural environments was applied to the residue pairs within the epsilon-suboptimal region to produce an improved alignment.
Directory of Open Access Journals (Sweden)
Amal F Soliman
2016-01-01
Conclusion Twelve weeks of intensive dynamic exercise program should be recommended to patients with FM as it was effective in decreasing the oxidative stress parameters, increasing the antioxidant parameters, and improving the clinical outcome of this disease.
User's manual for CNVUFAC, the general dynamics heat-transfer radiation view factor program
Energy Technology Data Exchange (ETDEWEB)
Wong, R. L.
1976-06-25
CNVUFAC, the General Dynamics heat-transfer radiation veiw factor program, has been adapted for use on the LLL CDC 7600 computer system. The input and output have been modified, and a node incrementing logic was included to make the code compatible with the TRUMP thermal analyzer and related codes. The program performs the multiple integration necessary to evaluate the geometric black-body radiaton node to node view factors. Card image output that contains node number and view factor information is generated for input into the related program GRAY. Program GRAY is then used to include the effects of gray-body emissivities and multiple reflections, generating the effective gray-body view factors usable in TRUMP. CNVUFAC uses an elemental area summation scheme to evaluate the multiple integrals. The program permits shadowing and self-shadowing. The basic configuration shapes that can be considered are cylinders, cones, spheres, ellipsoids, flat plates, disks, toroids, and polynomials of revolution. Portions of these shapes can also be considered.
Approximate dynamic programming recurrence relations for a hybrid optimal control problem
Lu, W.; Ferrari, S.; Fierro, R.; Wettergren, T. A.
2012-06-01
This paper presents a hybrid approximate dynamic programming (ADP) method for a hybrid dynamic system (HDS) optimal control problem, that occurs in many complex unmanned systems which are implemented via a hybrid architecture, regarding robot modes or the complex environment. The HDS considered in this paper is characterized by a well-known three-layer hybrid framework, which includes a discrete event controller layer, a discrete-continuous interface layer, and a continuous state layer. The hybrid optimal control problem (HOCP) is to nd the optimal discrete event decisions and the optimal continuous controls subject to a deterministic minimization of a scalar function regarding the system state and control over time. Due to the uncertainty of environment and complexity of the HOCP, the cost-to-go cannot be evaluated before the HDS explores the entire system state space; as a result, the optimal control, neither continuous nor discrete, is not available ahead of time. Therefore, ADP is adopted to learn the optimal control while the HDS is exploring the environment, because of the online advantage of ADP method. Furthermore, ADP can break the curses of dimensionality which other optimizing methods, such as dynamic programming (DP) and Markov decision process (MDP), are facing due to the high dimensions of HOCP.
A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism
Directory of Open Access Journals (Sweden)
Farhad Ghassemi Tari
2016-01-01
Full Text Available The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.
Enhancing dynamic graphical analysis with the Lisp-Stat language and the ViSta statistical program.
Ledesma, Rubén; Molina, J Gabriel; Young, Forrest W
2005-11-01
Presented is a sample of computerized methods aimed at multidimensional scaling and psychometric item analysis that offer a dynamic graphical interface to execute analyses and help visualize the results. These methods show how the Lisp-Stat programming language and the ViSta statistical program can be jointly applied to develop powerful computer applications that enhance dynamic graphical analysis methods. The feasibility of this combined strategy relies on two main features: (1) The programming architecture of ViSta enables users to add new statistical methods as plug-ins, which are integrated into the program environment and can make use of all the functions already available in ViSta (e.g., data manipulation, editing, printing); and (2) the set of powerful statistical and graphical functions integrated into the Lisp-Stat programming language provides the means for developing statistical methods with dynamic graphical visualizations, which can be implemented as ViSta plug-ins.
Optimal bipedal interactions with dynamic terrain: synthesis and analysis via nonlinear programming
Hubicki, Christian; Goldman, Daniel; Ames, Aaron
In terrestrial locomotion, gait dynamics and motor control behaviors are tuned to interact efficiently and stably with the dynamics of the terrain (i.e. terradynamics). This controlled interaction must be particularly thoughtful in bipeds, as their reduced contact points render them highly susceptible to falls. While bipedalism under rigid terrain assumptions is well-studied, insights for two-legged locomotion on soft terrain, such as sand and dirt, are comparatively sparse. We seek an understanding of how biological bipeds stably and economically negotiate granular media, with an eye toward imbuing those abilities in bipedal robots. We present a trajectory optimization method for controlled systems subject to granular intrusion. By formulating a large-scale nonlinear program (NLP) with reduced-order resistive force theory (RFT) models and jamming cone dynamics, the optimized motions are informed and shaped by the dynamics of the terrain. Using a variant of direct collocation methods, we can express all optimization objectives and constraints in closed-form, resulting in rapid solving by standard NLP solvers, such as IPOPT. We employ this tool to analyze emergent features of bipedal locomotion in granular media, with an eye toward robotic implementation.
A data base and analysis program for shuttle main engine dynamic pressure measurements
Coffin, T.
1986-01-01
A dynamic pressure data base management system is described for measurements obtained from space shuttle main engine (SSME) hot firing tests. The data were provided in terms of engine power level and rms pressure time histories, and power spectra of the dynamic pressure measurements at selected times during each test. Test measurements and engine locations are defined along with a discussion of data acquisition and reduction procedures. A description of the data base management analysis system is provided and subroutines developed for obtaining selected measurement means, variances, ranges and other statistics of interest are discussed. A summary of pressure spectra obtained at SSME rated power level is provided for reference. Application of the singular value decomposition technique to spectrum interpolation is discussed and isoplots of interpolated spectra are presented to indicate measurement trends with engine power level. Program listings of the data base management and spectrum interpolation software are given. Appendices are included to document all data base measurements.
Directory of Open Access Journals (Sweden)
Bruno H. Dias
2010-01-01
Full Text Available This paper presents a new approach for the expected cost-to-go functions modeling used in the stochastic dynamic programming (SDP algorithm. The SDP technique is applied to the long-term operation planning of electrical power systems. Using state space discretization, the Convex Hull algorithm is used for constructing a series of hyperplanes that composes a convex set. These planes represent a piecewise linear approximation for the expected cost-to-go functions. The mean operational costs for using the proposed methodology were compared with those from the deterministic dual dynamic problem in a case study, considering a single inflow scenario. This sensitivity analysis shows the convergence of both methods and is used to determine the minimum discretization level. Additionally, the applicability of the proposed methodology for two hydroplants in a cascade is demonstrated. With proper adaptations, this work can be extended to a complete hydrothermal system.
Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan
2014-12-01
In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method.
A Dynamic Programming Approach to Finite-horizon Coherent Quantum LQG Control
Vladimirov, Igor G
2011-01-01
The paper considers the coherent quantum Linear Quadratic Gaussian (CQLQG) control problem for time-varying quantum plants governed by linear quantum stochastic differential equations over a bounded time interval. A controller is sought among quantum linear systems satisfying physical realizability (PR) conditions. The latter describe the dynamic equivalence of the system to an open quantum harmonic oscillator and relate its state-space matrices to the free Hamiltonian, coupling and scattering operators of the oscillator. Using the Hamiltonian parameterization of PR controllers, the CQLQG problem is recast into an optimal control problem for a deterministic system governed by a differential Lyapunov equation. The state of this subsidiary system is the symmetric part of the quantum covariance matrix of the plant-controller state vector. The resulting covariance control problem is treated using dynamic programming and Pontryagin's minimum principle. The associated Hamilton-Jacobi-Bellman equation for the minimu...
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xinguo
2014-01-01
costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the optimal management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate......, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two....... A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due...
Directory of Open Access Journals (Sweden)
Arild Helseth
2015-12-01
Full Text Available Stochastic dual dynamic programming (SDDP has become a popular algorithm used in practical long-term scheduling of hydropower systems. The SDDP algorithm is computationally demanding, but can be designed to take advantage of parallel processing. This paper presents a novel parallel scheme for the SDDP algorithm, where the stage-wise synchronization point traditionally used in the backward iteration of the SDDP algorithm is partially relaxed. The proposed scheme was tested on a realistic model of a Norwegian water course, proving that the synchronization point relaxation significantly improves parallel efficiency.
Bellman, Richard
2015-01-01
Rapid advances in the physical and biological sciences and in related technologies have brought about equally farreaching changes in mathematical research. Focusing on control theory, invariant imbedding, dynamic programming, and quasilinearization, Mr. Bellman explores with ease and clarity the mathematical research problems arising from scientific questions in engineering, physics, biology, and medicine. Special attention is paid in these essays to the use of the digital computer in obtaining the numerical solution of numerical problems, its influence in the formulation of new and old scient
Aziz, Jonathan D.; Parker, Jeffrey S.; Scheeres, Daniel J.; Englander, Jacob A.
2017-01-01
Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging optimization problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory optimization about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to the eccentric anomaly and performing the optimization with differential dynamic programming. Fuel-optimal geocentric transfers are shown in excess of 1000 revolutions while subject to Earths J2 perturbation and lunar gravity.
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2008-01-01
in the system, the number of periods over the planning horizon and the time for solving a single-period economic dispatch problem. We have compared the DP-RSC1 algorithm with realistic power plants against the unit decommitment algorithm and the traditional priority listing method. The results show that the DP...... introduce in this paper the DP-RSC1 algorithm, which is a variant of the dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units and sequential commitment of units one by one. The time complexity of DP-RSC1 is proportional to the number of generating units...
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix
DEFF Research Database (Denmark)
Havgaard, Jakob Hull; Torarinsson, Elfar; Gorodkin, Jan
2007-01-01
not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving...... and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool...
Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems
2012-01-01
In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, th...
Optimization and analysis of decision trees and rules: Dynamic programming approach
Alkhalid, Abdulaziz
2013-08-01
This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.
Dynamic Simulations of Nonlinear Multi-Domain Systems Based on Genetic Programming and Bond Graphs
Institute of Scientific and Technical Information of China (English)
DI Wenhui; SUN Bo; XU Lixin
2009-01-01
A dynamic simulation method for non-linear systems based on genetic programming (GP) and bond graphs (BG) was developed to improve the design of nonlinear multi-domain energy conversion sys-tems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and space search ability of this method not only gives a more optimized convergence for the operation, but also reduces the generation time for the new circuit graph for the design of nonlinear multi-domain systems.
Larocca, Francesco; Chiu, Stephanie J; McNabb, Ryan P; Kuo, Anthony N; Izatt, Joseph A; Farsiu, Sina
2011-06-01
Segmentation of anatomical structures in corneal images is crucial for the diagnosis and study of anterior segment diseases. However, manual segmentation is a time-consuming and subjective process. This paper presents an automatic approach for segmenting corneal layer boundaries in Spectral Domain Optical Coherence Tomography images using graph theory and dynamic programming. Our approach is robust to the low-SNR and different artifact types that can appear in clinical corneal images. We show that our method segments three corneal layer boundaries in normal adult eyes more accurately compared to an expert grader than a second grader-even in the presence of significant imaging outliers.
Dynamic Programming Used to Align Protein Structures with a Spectrum Is Robust
Directory of Open Access Journals (Sweden)
Allen Holder
2013-11-01
Full Text Available Several efficient algorithms to conduct pairwise comparisons among large databases of protein structures have emerged in the recent literature. The central theme is the design of a measure between the Cα atoms of two protein chains, from which dynamic programming is used to compute an alignment. The efficiency and efficacy of these algorithms allows large-scale computational studies that would have been previously impractical. The computational study herein shows that the structural alignment algorithm eigen-decomposition alignment with the spectrum (EIGAs is robust against both parametric and structural variation.
2015-08-17
our best knowledge , this is the first study of using a “predictive” approach through a model network to design the event-triggered ADP. This is the...investigated in the com- munity before, to our best knowledge , this is the first study of using a “predictive” approach through a model network to...programming has been used to solve the optimal control for many years. However, due to the ” curse of di- mensionality” [9], [10], the adaptive dynamic
Human dynamics of spending: Longitudinal study of a coalition loyalty program
Yi, Il Gu; Jeong, Hyang Min; Choi, Woosuk; Jang, Seungkwon; Lee, Heejin; Kim, Beom Jun
2014-09-01
Large-scale data of a coalition loyalty program is analyzed in terms of the temporal dynamics of customers' behaviors. We report that the two main activities of a loyalty program, earning and redemption of points, exhibit very different behaviors. It is also found that as customers become older from their early 20's, both male and female customers increase their earning and redemption activities until they arrive at the turning points, beyond which both activities decrease. The positions of turning points as well as the maximum earned and redeemed points are found to differ for males and females. On top of these temporal behaviors, we identify that there exists a learning effect and customers learn how to earn and redeem points as their experiences accumulate in time.
Reconstruction of an inn fire scene using the Fire Dynamics Simulator (FDS) program.
Chi, Jen-Hao
2013-01-01
An inn fire occurring in the middle of the night usually causes a great deal more injuries and deaths. This article examines the case study of an inn fire accident that resulted in the most serious casualties in Taiwan's history. Data based on the official fire investigation report and NFPA921 regulations are used, and the fire scenes are reconstructed using the latest Fire Dynamics Simulator (FDS) program from NIST. The personnel evacuation time and time variants for various fire hazard factors of reconstructive analysis clarify the reason for such a high number of casualties. It reveals that the FDS program has come to play an essential role in fire investigation. The close comparison between simulation result and the actual fire scene also provides fire prevention engineers, a possible utilization of FDS to examine the effects of improved schemes for fire safety of buildings.
MacGillivray, Laurie; Goode, Gretchen S.
2016-01-01
Researchers of after-school tutoring primarily focus on educational outcomes with little attention to the social dynamics of such programs. In our qualitative case study, we examined the nature of interactions among tutors in a tutoring program at a homeless shelter for families. Employing Bourdieu's concepts of "social capital" and…
Bodley, C. S.; Devers, D. A.; Park, C. A.
1975-01-01
A theoretical development and associated digital computer program system is presented. The dynamic system (spacecraft) is modeled as an assembly of rigid and/or flexible bodies not necessarily in a topological tree configuration. The computer program system may be used to investigate total system dynamic characteristics including interaction effects between rigid and/or flexible bodies, control systems, and a wide range of environmental loadings. Additionally, the program system may be used for design of attitude control systems and for evaluation of total dynamic system performance including time domain response and frequency domain stability analyses. Volume 1 presents the theoretical developments including a description of the physical system, the equations of dynamic equilibrium, discussion of kinematics and system topology, a complete treatment of momentum wheel coupling, and a discussion of gravity gradient and environmental effects. Volume 2, is a program users' guide and includes a description of the overall digital program code, individual subroutines and a description of required program input and generated program output. Volume 3 presents the results of selected demonstration problems that illustrate all program system capabilities.
MacGillivray, Laurie; Goode, Gretchen S.
2016-01-01
Researchers of after-school tutoring primarily focus on educational outcomes with little attention to the social dynamics of such programs. In our qualitative case study, we examined the nature of interactions among tutors in a tutoring program at a homeless shelter for families. Employing Bourdieu's concepts of "social capital" and…
Institute of Scientific and Technical Information of China (English)
黄震春; 李三立
2002-01-01
Memory gap has become an essential factor influencing the peak performance of high-speed CPU-based systems. To fill this gap, enlarging cache capacity has been a traditional method based on static program locality principle. However, the order of instructions stored in I-Cache before being sent to Data Processing Unit (DPU) is a kind of useful information that has not ever been utilized before. So an architecture containing an Instruction Processing Unit (IPU) in parallel with the ordinary DPU is proposed. The IPU can prefetch,analyze and preprocess a large amount of instructions otherwise lying in the I-Cache untouched.It is more efficient than the conventional prefetch buffer that can only store several instructions for previewing. By IPU, Load Instructions can be preprocessed while the DPU is executing on data simultaneously. It is termed as "Instruction Processing Unit with LOokahead Cache"(IPULOC for short) in which the idea of dynamic program locality is presented. This paper describes the principle of IPULOC and illustrates the quantitative parameters for evaluation.Tools for simulating the IPULOC have been developed. The simulation result shows that it can improve program locality during program execution, and hence can improve the cache hit ratio correspondingly without further enlarging the on-chip cache that occupies a large portion of chip area.
Addressing gender dynamics and engaging men in HIV programs: lessons learned from Horizons research.
Pulerwitz, Julie; Michaelis, Annie; Verma, Ravi; Weiss, Ellen
2010-01-01
In the field of human immunodeficiency virus (HIV) prevention, there has been increasing interest in the role that gender plays in HIV and violence risk, and in successfully engaging men in the response. This article highlights findings from more than 10 studies in Asia, Africa, and Latin America--conducted from 1997 through 2007 as part of the Horizons program--that have contributed to understanding the relationship between gender and men's behaviors, developing useful measurement tools for gender norms, and designing and evaluating the impact of gender-focused program strategies. Studies showed significant associations between support for inequitable norms and risk, such as more partner violence and less condom use. Programmatic lessons learned ranged from insights into appropriate media messages, to strategies to engage men in critically reflecting upon gender inequality, to the qualities of successful program facilitators. The portfolio of work reveals the potential and importance of directly addressing gender dynamics in HIV- and violence-prevention programs for both men and women.
动态规划法在程序设计中的应用%Dynamic Programming in Application of Computer Programming
Institute of Scientific and Technical Information of China (English)
邓国强; 唐敏
2014-01-01
探讨动态规划法的本质及在计算机程序设计中的应用。提出求解Fibonacci序列的3种算法，即递归法、自底向上和自顶向下动态规划法，证明将动态规划法用于程序设计，能降低算法的时间复杂度和空间复杂度。%The nature of dynamic programming and its application for computer programming are discussed .We present three methods for solving Fibonacci sequence ,which are the recursive method ,bottom-up approach and top-down ap-proach respectively .The analysis about time complexity and space complexity for three algorithms is demonstrated that if use dynamic programming in computer programming ,the time and space complexity will be decreased .
Directory of Open Access Journals (Sweden)
Antti Silvast
2015-01-01
Full Text Available Since the 1980s, educational policies in many countries have aimed at improving the computer literacy and programming competencies of the population. Over the same period, the possibilities that people have seen regarding programming and everyday programming practices have emerged as an area of strong interest within historical scholarship. The paper contributes to these discussions by drawing on techniques of oral history to focus on programming hobbies and practices in Finland. Examining data from a massive survey of computer hobbyists (N = 1,453 and their recollections about personal computer use (largely during the 1980s, the paper gathers new information on what leads to people’s pursuit of or interest in programming and how their programming habits have changed over time. The study links together the gender and age dynamics in programming and shows how the respondents not only engaged with but also could become disengaged from programming for various reasons.
Ground test program for a full-size solar dynamic heat receiver
Sedgwick, L. M.; Kaufmann, K. J.; McLallin, K. L.; Kerslake, T. W.
Test hardware, facilities, and procedures were developed to conduct ground testing of a full-size, solar dynamic heat receiver in a partially simulated, low earth orbit environment. The heat receiver was designed to supply 102 kW of thermal energy to a helium and xenon gas mixture continuously over a 94 minute orbit, including up to 36 minutes of eclipse. The purpose of the test program was to quantify the receiver thermodynamic performance, its operating temperatures, and thermal response to changes in environmental and power module interface boundary conditions. The heat receiver was tested in a vacuum chamber using liquid nitrogen cold shrouds and an aperture cold plate. Special test equipment was designed to provide the required ranges in interface boundary conditions that typify those expected or required for operation as part of the solar dynamic power module on the Space Station Freedom. The support hardware includes an infrared quartz lamp heater with 30 independently controllable zones and a closed-Brayton cycle engine simulator to circulate and condition the helium-xenon gas mixture. The test article, test support hardware, facilities, and instrumentation developed to conduct the ground test program are all described.
A dynamic programming model for optimal planning of aquifer storage and recovery facility operations
Uddameri, V.
2007-01-01
Aquifer storage recovery (ASR) is an innovative technology with the potential to augment dwindling water resources in regions experiencing rapid growth and development. Planning and design of ASR systems requires quantifying how much water should be stored and appropriate times for storage and withdrawals within a planning period. A monthly scale planning model has been developed in this study to derive optimal (least cost) long-term policies for operating ASR systems and is solved using a recursive deterministic dynamic programming approach. The outputs of the model include annual costs of operation, the amount of water to be imported each month as well as the schedule for storage and extraction. A case study modeled after a proposed ASR system for Mustang Island and Padre Island service areas of the city of Corpus Christi is used to illustrate the utility of the developed model. The results indicate that for the assumed baseline demands, the ASR system is to be kept operational for a period of 4 months starting from May through August. Model sensitivity analysis indicated that increased seasonal shortages can be met using ASR with little additional costs. For the assumed cost structure, a 16% shortage increased the costs by 1.6%. However, the operation time of ASR increased from 4 to 8 months. The developed dynamic programming model is a useful tool to assess the feasibility of evaluating the use of ASR systems during regional-scale water resources planning endeavors.
Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming
Institute of Scientific and Technical Information of China (English)
Ming BAI; Yan ZHUANG; Wei WANG
2009-01-01
An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points(GCPs) is presented.To decrease time complexity without losing matching precision,using a multilevel search scheme,the coarse matching is processed in typical disparity space image,while the fine matching is processed in disparity-offset space image.In the upper level,GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint.Under the supervision of the highly reliable GCPs,bidirec-tional dynamic programming framework is employed to solve the inconsistency in the optimization path.In the lower level,to reduce running time,disparity-offset space is proposed to efficiently achieve the dense disparity image.In addition,an adaptive dual support-weight strategy is presented to aggregate matching cost,which considers photometric and geomet-ric information.Further,post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm,where missing stereo information is substituted from surrounding re-gions.To demonstrate the effectiveness of the algorithm,we present the two groups of experimental results for four widely used standard stereo data sets,including discussion on performance and comparison with other methods,which show that the algorithm has not only a fast speed,but also significantly improves the efficiency of holistic optimization.
Directory of Open Access Journals (Sweden)
Cheng-Hong Yang
2009-04-01
Full Text Available Single nucleotide polymorphisms (SNPs play an important role in personalized medicine. However, the SNP data reported in many association studies provide only the SNP nucleotide/amino acid position, without providing the SNP ID recorded in National Center for Biotechnology Information databases. A tool with the ability to provide SNP ID identification, with a user-friendly interface, is needed. In this paper, a dynamic programming algorithm was used to compare homologs when the processed input sequence is aligned with the SNP FASTA database. Our novel system provides a web-based tool that uses the National Center for Biotechnology Information dbSNP database, which provides SNP sequence identification and SNP FASTA formats. Freely selectable sequence formats for alignment can be used, including general sequence formats (ACGT, [dNTP1/dNTP2] or IUPAC formats and orientation with bidirectional sequence matching. In contrast to the National Center for Biotechnology Information SNP-BLAST, the proposed system always provides the correct targeted SNP ID (SNP hit, as well as nearby SNPs (flanking hits, arranged in their chromosomal order and contig positions. The system also solves problems inherent in SNP-BLAST, which cannot always provide the correct SNP ID for a given input sequence. Therefore, this system constitutes a novel application which uses dynamic programming to identify SNP IDs from the literature and keyed-in sequences for systematic association studies. It is freely available at http://bio.kuas.edu.tw/SNPosition/.
Jiang, Luan; Ling, Shan; Li, Qiang
2016-03-01
Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.
Automatic tracking of linear features on SPOT images using dynamic programming
Bonnefon, Regis; Dherete, Pierre; Desachy, Jacky
1999-12-01
Detection of geographic elements on images is important in the perspective of adding new elements in geographic databases which are sometimes old and so, some elements are not represented. Our goal is to look for linear features like roads, rivers or railways on SPOT images with a resolution of 10 meters. Several methods allow this detection to be realized and may be classified in three categories: (1) Detection operators: the best known is the DUDA Road Operator which determine the belonging degree of a pixel to a linear feature from several 5 X 5 filters. Results are often unsatisfactory. It exists too the Infinite Size Exponential Filter (ISEF), which is a derivative filter and allows edge, valley or roof profile to be found on the image. It can be utilized as an additional information for others methods. (2) Structural tracking: from a starting point, an analysis in several directions is performed to determine the best next point (features may be: homogeneity of radiometry, contrast with environment, ...). From this new point and with an updated direction, the process goes on. Difficulty of these methods is the consideration of occlusions (bridges, tunnels, dense vegetation, ...). (3) Dynamic programming: F* algorithm and snakes are the best known. They allow a path with a minimal cost to be found in a search window. Occlusions are not a problem but two points or more near the searched linear feature must be known to define the window. The method described below is a mixture of structural tracking and dynamic programming (F* algorithm).
Wang, Zheng; Liu, Xiaoping; Liu, Kefu; Li, Shuai; Wang, Huanqing
2017-10-01
In this paper, backstepping for a class of block strict-feedback nonlinear systems is considered. Since the input function could be zero for each backstepping step, the backstepping technique cannot be applied directly. Based on the assumption that nonlinear systems are polynomials, for each backstepping step, Lypunov function can be constructed in a polynomial form by sum of square (SOS) technique. The virtual control can be obtained by the Sontag feedback formula, which is equivalent to an optimal control-the solution of a Hamilton-Jacobi-Bellman equation. Thus, approximate dynamic programming (ADP) could be used to estimate value functions (Lyapunov functions) instead of SOS. Through backstepping technique, the control Lyapunov function (CLF) of the full system is constructed finally making use of the strict-feedback structure and a stabilizable controller can be obtained through the constructed CLF. The contributions of the proposed method are twofold. On one hand, introducing ADP into backstepping can broaden the application of the backstepping technique. A class of block strict-feedback systems can be dealt by the proposed method and the requirement of nonzero input function for each backstepping step can be relaxed. On the other hand, backstepping with surface dynamic control actually reduces the computation complexity of ADP through constructing one part of the CLF by solving semidefinite programming using SOS. Simulation results verify contributions of the proposed method.
Khan, Mohammad Ibrahim; Kamal, Md Sarwar
2015-03-01
Markov Chain is very effective in prediction basically in long data set. In DNA sequencing it is always very important to find the existence of certain nucleotides based on the previous history of the data set. We imposed the Chapman Kolmogorov equation to accomplish the task of Markov Chain. Chapman Kolmogorov equation is the key to help the address the proper places of the DNA chain and this is very powerful tools in mathematics as well as in any other prediction based research. It incorporates the score of DNA sequences calculated by various techniques. Our research utilize the fundamentals of Warshall Algorithm (WA) and Dynamic Programming (DP) to measures the score of DNA segments. The outcomes of the experiment are that Warshall Algorithm is good for small DNA sequences on the other hand Dynamic Programming are good for long DNA sequences. On the top of above findings, it is very important to measure the risk factors of local sequencing during the matching of local sequence alignments whatever the length.
Dynamic programming-based hot spot identification approach for pedestrian crashes.
Medury, Aditya; Grembek, Offer
2016-08-01
Network screening techniques are widely used by state agencies to identify locations with high collision concentration, also referred to as hot spots. However, most of the research in this regard has focused on identifying highway segments that are of concern to automobile collisions. In comparison, pedestrian hot spot detection has typically focused on analyzing pedestrian crashes in specific locations, such as at/near intersections, mid-blocks, and/or other crossings, as opposed to long stretches of roadway. In this context, the efficiency of the some of the widely used network screening methods has not been tested. Hence, in order to address this issue, a dynamic programming-based hot spot identification approach is proposed which provides efficient hot spot definitions for pedestrian crashes. The proposed approach is compared with the sliding window method and an intersection buffer-based approach. The results reveal that the dynamic programming method generates more hot spots with a higher number of crashes, while providing small hot spot segment lengths. In comparison, the sliding window method is shown to suffer from shortcomings due to a first-come-first-serve approach vis-à-vis hot spot identification and a fixed hot spot window length assumption.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun
2017-03-01
H∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.
Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.
Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2017-03-02
This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.
The Configuration Of Supply Chain Agritourism To Improve The Performance With Dynamic Programming
Directory of Open Access Journals (Sweden)
Sahnaz Ubud
2015-09-01
Full Text Available The purposes of this research is to implementation about the configuration of Supply Chain Agritourism in Mekarsari Tours Garden and result a decision making which must be done by top level management about their supply chain configuration. Because now Mekarsari, the biggest fruit garden in the world, have a lot of type of fruit which must be supply for the customer depend on the season with on time. So Mekarsari must know about their configuration from supplier to customer to improve their performance. The Respondents for this research is selected based on the results of supply chain maping from the worker in the garden, the top level management until the end customer. Supply chian network is formed consisting of farm workers to the end customers, especially those located in the tourist are of green land zone. The type of data is displayed in a supply chain modeling approach is to use the dynamic system. It’s consists of numeric data, the written data and mental models. That data is collected and processed into a design model. The design model is using system dynamics methodology. In compiling the system dynamics model has been used software Vensim Professional Academic Ventana 5.7. The result of this research is a configuration of Supply Chain Agritourism which is developed from the supplier until the end customer in Mekarsari tours Garden. From the Dynamic Programming, the result is a decision making which must be done by the top level management to improve the supply chain performance, especially in the green land zone.
AbouEisha, Hassan M.
2017-07-13
We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
Efficient and exact maximum likelihood quantisation of genomic features using dynamic programming.
Song, Mingzhou; Haralick, Robert M; Boissinot, Stéphane
2010-01-01
An efficient and exact dynamic programming algorithm is introduced to quantise a continuous random variable into a discrete random variable that maximises the likelihood of the quantised probability distribution for the original continuous random variable. Quantisation is often useful before statistical analysis and modelling of large discrete network models from observations of multiple continuous random variables. The quantisation algorithm is applied to genomic features including the recombination rate distribution across the chromosomes and the non-coding transposable element LINE-1 in the human genome. The association pattern is studied between the recombination rate, obtained by quantisation at genomic locations around LINE-1 elements, and the length groups of LINE-1 elements, also obtained by quantisation on LINE-1 length. The exact and density-preserving quantisation approach provides an alternative superior to the inexact and distance-based univariate iterative k-means clustering algorithm for discretisation.
Dynamic Programming for Re-Mapping Noisy Fixations in Translation Tasks
DEFF Research Database (Denmark)
Carl, Michael
2013-01-01
drifted center of the observed fixation onto the symbol directly below it. In this paper I extend this naïve fixation-to-symbol mapping by introducing background knowledge about the translation task. In a first step, the sequence of fixation-to- symbol mappings is extended into a lattice of several...... possible fixated symbols, including those on the line above and below the naïve fixation mapping. In a second step a dynamic programming algorithm applies a number of heuristics to find the best path through the lattice, based on the probable distance in characters, in words and in pixels between...... successive fixations and the symbol locations, so as to smooth the gazing path according to the background gazing model. A qualitative and quantitative evaluation shows that the algorithm increases the accuracy of the re-mapped symbol sequence....
DEFF Research Database (Denmark)
Davidsen, Claus; Cardenal, Silvio Javier Pereira; Liu, Suxia;
2015-01-01
of stochastic dynamic programming, to optimize water resources management in the Ziya River basin. Natural runoff from the upper basin was estimated with a rainfall-runoff model autocalibrated using in situ measured discharge. The runoff serial correlation was described by a Markov chain and used as input...... for the optimization model. This model was used to assess the economic impacts of ecosystem minimum flow constraints, limited groundwater pumping, and the middle route of the South–North Water Transfer Project (SNWTP). A regional climate shift has exacerbated water scarcity and increased water values, resulting...... in stricter water management. The results show that the SNWTP reduces the impacts of water scarcity and impacts optimal water management in the basin. The presented modeling framework provides an objective basis for the development of tools to avoid overpumping groundwater resources at minimum costs....
Directory of Open Access Journals (Sweden)
Shaolin Ji
2013-01-01
Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.
Gosavi, Abhijit
2014-08-01
In control systems theory, the Markov decision process (MDP) is a widely used optimization model involving selection of the optimal action in each state visited by a discrete-event system driven by Markov chains. The classical MDP model is suitable for an agent/decision-maker interested in maximizing expected revenues, but does not account for minimizing variability in the revenues. An MDP model in which the agent can maximize the revenues while simultaneously controlling the variance in the revenues is proposed. This work is rooted in machine learning/neural network concepts, where updating is based on system feedback and step sizes. First, a Bellman equation for the problem is proposed. Thereafter, convergent dynamic programming and reinforcement learning techniques for solving the MDP are provided along with encouraging numerical results on a small MDP and a preventive maintenance problem.
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Rauff Lind Christensen, Tue; Klose, Andreas; Andersen, Kim Allan
are neglected in the SSFCTP. The SSFCMCTP overcome this problem by incorporating a staircase cost structure in the cost function instead of the usual one used in SSFCTP. We present a dynamic programming algorithm for the resulting problem. To enhance the performance of the generic algorithm a number......The Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem (SSFCMCTP) is a problem with versatile applications. This problem is a generalization of the Single-Sink, Fixed-Charge Transportation Problem (SSFCTP), which has a fixed-charge, linear cost structure. However, in at least two...... of enhancements is employed. The problem instance is reduced by variable pegging using a Lagrangean relaxation from which also a flow augmentation scheme is derived. Additionally a reduction in the search space is employed along with a variable transformation which generalizes a transformation known from...
GUI Based Computer Programs for Analyzing Dynamic Signals Detected from a Physical Earthquake Model
Directory of Open Access Journals (Sweden)
Chung-Ru Wang
2013-06-01
Full Text Available Many methods are available to be used as tools for data analysis, such as Fast Fourier Transform (FFT and Hilbert Huang Transform (HHT. However, the raw data need to be pre-processed before applying those methods. To deal with considerable raw data, it should be processed in a fast and efficient way. In this research, the dynamic signal data are obtained from physical earthquake models. To process the huge amount of data is always complicated and time consuming. Customized GUI programs to pre-process and post-process data has been designed to make the raw signal data express its physical meaning rapid by a combination of the manual and automatic process. The research uses animations to display the signal change in time that the signal detected can be shown by a graph which is close to physical phenomena and makes the physical data meaning become more obvious.
Directory of Open Access Journals (Sweden)
Zongyuan Huang
2010-01-01
Full Text Available This paper is concerned with a kind of corporate international optimal portfolio and consumption choice problems, in which the investor can invest her or his wealth either in a domestic bond (bank account or in an oversea real project with production. The bank pays a lower interest rate for deposit and takes a higher rate for any loan. First, we show that Bellman's dynamic programming principle still holds in our setting; second, in terms of the foregoing principle, we obtain the investor's optimal portfolio proportion for a general maximizing expected utility problem and give the corresponding economic analysis; third, for the special but nontrivial Constant Relative Risk Aversion (CRRA case, we get the investors optimal investment and consumption solution; last but not least, we give some numerical simulation results to illustrate the influence of volatility parameters on the optimal investment strategy.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
Energy Technology Data Exchange (ETDEWEB)
Bokanowski, Olivier, E-mail: boka@math.jussieu.fr [Laboratoire Jacques-Louis Lions, Université Paris-Diderot (Paris 7) UFR de Mathématiques - Bât. Sophie Germain (France); Picarelli, Athena, E-mail: athena.picarelli@inria.fr [Projet Commands, INRIA Saclay & ENSTA ParisTech (France); Zidani, Hasnaa, E-mail: hasnaa.zidani@ensta.fr [Unité de Mathématiques appliquées (UMA), ENSTA ParisTech (France)
2015-02-15
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.
Using stochastic dynamic programming to support catchment-scale water resources management in China
DEFF Research Database (Denmark)
Davidsen, Claus; Cardenal, Silvio Javier Pereira; Liu, Suxia
2013-01-01
allocation costs for the different water sources (surface water, groundwater and external water) and fixed costs of water supply curtailment. The multiple reservoirs in the basin are aggregated into a single reservoir to reduce the dimensions of decisions. Water availability is estimated using a hydrological...... to low and extremely seasonal precipitation, and the intense agricultural production is highly dependent on irrigation. Large reservoirs provide water storage for dry months while groundwater and the external South-to-North Water Transfer Project are alternative sources of water. An optimization model...... based on stochastic dynamic programming has been developed. The objective function is to minimize the total cost of supplying water to the users, while satisfying minimum ecosystem flow constraints. Each user group (agriculture, domestic and industry) is characterized by fixed demands, fixed water...
Statistics of voltage drop in distribution circuits: a dynamic programming approach
Energy Technology Data Exchange (ETDEWEB)
Turitsyn, Konstantin S [Los Alamos National Laboratory
2010-01-01
We analyze a power distribution line with high penetration of distributed generation and strong variations of power consumption and generation levels. In the presence of uncertainty the statistical description of the system is required to assess the risks of power outages. In order to find the probability of exceeding the constraints for voltage levels we introduce the probability distribution of maximal voltage drop and propose an algorithm for finding this distribution. The algorithm is based on the assumption of random but statistically independent distribution of loads on buses. Linear complexity in the number of buses is achieved through the dynamic programming technique. We illustrate the performance of the algorithm by analyzing a simple 4-bus system with high variations of load levels.
Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming
Benzouai, Siham; Smara, Youcef
2010-12-01
The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.
A dynamical programming approach for controlling the directed abelian Dhar-Ramaswamy model
Cajueiro, Daniel O
2013-01-01
A dynamical programming approach is used to deal with the problem of controlling the directed abelian Dhar-Ramaswamy model on two-dimensional square lattice. Two strategies are considered to obtain explicit results to this task. First, the optimal solution of the problem is characterized by the solution of the Bellman equation obtained by numerical algorithms. Second, the solution is used as a benchmark to value how far from the optimum other heuristics that can be applied to larger systems are. This approach is the first attempt on the direction of schemes for controlling self-organized criticality that are based on optimization principles that consider explicitly a tradeoff between the size of the avalanches and the cost of intervention.
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Wei, Qinglai; Liu, Derong; Lin, Qiao
2016-08-03
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Variable Displacement Control of the Concrete Pumping System Based on Dynamic Programming
Directory of Open Access Journals (Sweden)
Ye Min
2017-01-01
Full Text Available To solve the problems of cylinder piston striking cylinder and the hydraulic shocking of the main pump, and causing energy waste problem, the method of variable displacement control of piston stroke was proposed. In order to achieve effective control of the piston stroke, variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder. And the control process was realized by Dynamic Programming(DP, the simulation and test results show that piston of concrete pumping system don’t strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy-saving purposes under varying loads. This control model built in the integration design space of structure variable and control variable is of guiding significance for solving open-loop system’s engineering problems.
Chiu, Stephanie J; Toth, Cynthia A; Bowes Rickman, Catherine; Izatt, Joseph A; Farsiu, Sina
2012-05-01
This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.
Q Value-Based Dynamic Programming with Boltzmann Distribution in Large Scale Road Network
Yu, Shanqing; Xu, Yelei; Mabu, Shingo; Mainali, Manoj Kanta; Shimada, Kaoru; Hirasawa, Kotaro
In this paper, a global optimal traffic assignment strategy, i.e., Q value-based Dynamic Programming with Boltzmann Distribution is applied to the Kitakyushu City traffic system. The main idea of the proposed traffic assignment strategy is to calculate the expected traveling time for each origin-destination pair and the probability of selecting the next section, then to generate a considerable number of route candidates for the drivers based on the calculated probability. In the simulation, how to select the temperature parameter and the number of the route candidates is discussed in detail. The comparison between the proposed method and the shortest path algorithms indicates that the proposed method could reduce the risk of the traffic congestion occurrence and save the traveling cost effectively. In addition, the computation time is given to reveal the feasibility of the proposed method in large scale networks.
Dynamic programming for infinite horizon boundary control problems of PDE's with age structure
Faggian, Silvia
2008-01-01
We develop the dynamic programming approach for a family of infinite horizon boundary control problems with linear state equation and convex cost. We prove that the value function of the problem is the unique regular solution of the associated stationary Hamilton--Jacobi--Bellman equation and use this to prove existence and uniqueness of feedback controls. The idea of studying this kind of problem comes from economic applications, in particular from models of optimal investment with vintage capital. Such family of problems has already been studied in the finite horizon case by Faggian. The infinite horizon case is more difficult to treat and it is more interesting from the point of view of economic applications, where what mainly matters is the behavior of optimal trajectories and controls in the long run. The study of infinite horizon is here performed through a nontrivial limiting procedure from the corresponding finite horizon problem.
Stochastic Dynamic Programming for Three-Echelon Inventory System of Limited Shelf Life Products
Directory of Open Access Journals (Sweden)
Galal Noha M.
2016-01-01
Full Text Available Coordination of inventory decisions within the supply chain is one of the major determinants of its competitiveness in the global market. Products with limited shelf life impose additional challenges in managing the inventory across the supply chain because of the additional wastage costs incurred in case of being stored beyond product’s useful life. This paper presents a stochastic dynamic programming model for inventory replenishment in a serial multi-echelon distribution supply chain. The model considers uncertain stationary discrete demand at the retailer and zero lead time. The objective is to minimize expected total costs across the supply chain echelons, while maintaining a preset service level. The results illustrate that a cost saving of around 17% is achievable due to coordinating inventory decisions across the supply chain.
Speed improvement of B-snake algorithm using dynamic programming optimization.
Charfi, Maher; Zrida, Jalel
2011-10-01
This paper presents a novel approach to contour approximation carried out by means of the B-snake algorithm and the dynamic programming (DP) optimization technique. Using the proposed strategy for contour point search procedure, computing complexity is reduced to O(N×M(2)), whereas the standard DP method has an O(N×M(4)) complexity, with N being the number of contour sample points and M being the number of candidates in the search space. The storage requirement was also decreased from N×M(3) to N×M memory elements. Some experiments on noise corrupted synthetic image, magnetic resonance, and computer tomography medical images have shown that the proposed approach results are equivalent to those obtained by the standard DP algorithm.
A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming
Directory of Open Access Journals (Sweden)
Wushan Cheng
2014-12-01
Full Text Available In order to maintain the stability and security of the power system, the uncertainty and intermittency of wind power must be taken into account in economic dispatch (ED problems. In this paper, a dynamic economic dispatch (DED model based on chance constrained programming is presented and an improved particle swarm optimization (PSO approach is proposed to solve the problem. Wind power is regarded as a random variable and is included in the chance constraint. New formulation of up and down spinning reserve constraints are presented under expectation meaning. The improved PSO algorithm combines a feasible region adjustment strategy with a hill climbing search operation based on the basic PSO. Simulations are performed under three distinct test systems with different generators. Results show that both the proposed DED model and the improved PSO approach are effective.
Stochastic optimal control in infinite dimension dynamic programming and HJB equations
Fabbri, Giorgio; Święch, Andrzej
2017-01-01
Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite ...
Dynamic Programming Optimization of Multi-rate Multicast Video-Streaming Services
Directory of Open Access Journals (Sweden)
Nestor Michael Caños Tiglao
2010-06-01
Full Text Available In large scale IP Television (IPTV and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS algorithm.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement
Srinivas, Niranjan
Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for
A Fuzzy Programming approach for formation of Virtual Cells under dynamic and uncertain conditions
Directory of Open Access Journals (Sweden)
R.Jayachitra,
2010-06-01
Full Text Available Inspired by principles and advantages of the group technology (GT philosophy, part family formation for a virtual Cellular Manufacturing System (VCMS using Fuzzy logic is designed for dynamic and uncertain conditions. In real manufacturing systems, the input parameters such as part demand and the capacity are fuzzy in nature. In such cases, the fluctuations in part demand and the availability of manufacturing facilities in each period can be regarded as fuzzy. In a dynamic environment, the planning horizon can be divided into smaller time periods where each period and/or each part has different product mix and demand. A mathematical model for virtual cellular manufacturing system as binary-integer programming is proposed to minimize the total costs consisting of fixed machine costs, variable costs of all machines and the logical group movement costs. To verify the behavior of the proposed model, a comprehensive example is solved by a branch- and-bound (B&B method with the LINGO 12.0 software and the virtual cells(VC are formed by defuzzification using maximizing decision level λ (lambda-cut and the computational results are reported and compared with simulated annealing algorithm and rank order clustering algorithm .
Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C
2016-11-01
Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models.
Sahoo, Avimanyu; Jagannathan, Sarangapani
2017-02-01
In this paper, an event-driven stochastic adaptive dynamic programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near optimal control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system dynamics are approximated by using a novel neural network (NN) identifier with event sampled state vector. The optimal control policy is generated via an actor NN by using the NN identifier and value function approximated by a critic NN through ADP. The stochastic NN identifier, actor, and critic NN weights are tuned at the event sampled instants leading to aperiodic weight tuning laws. Above all, an adaptive event sampling condition based on estimated NN weights is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals along with the approximation accuracy. The net result is event-driven stochastic ADP technique that can significantly reduce the computation and network transmissions. Finally, the analytical design is substantiated with simulation results.
Discrete-time nonlinear HJB solution using approximate dynamic programming: convergence proof.
Al-Tamimi, Asma; Lewis, Frank L; Abu-Khalaf, Murad
2008-08-01
Convergence of the value-iteration-based heuristic dynamic programming (HDP) algorithm is proven in the case of general nonlinear systems. That is, it is shown that HDP converges to the optimal control and the optimal value function that solves the Hamilton-Jacobi-Bellman equation appearing in infinite-horizon discrete-time (DT) nonlinear optimal control. It is assumed that, at each iteration, the value and action update equations can be exactly solved. The following two standard neural networks (NN) are used: a critic NN is used to approximate the value function, whereas an action network is used to approximate the optimal control policy. It is stressed that this approach allows the implementation of HDP without knowing the internal dynamics of the system. The exact solution assumption holds for some classes of nonlinear systems and, specifically, in the specific case of the DT linear quadratic regulator (LQR), where the action is linear and the value quadratic in the states and NNs have zero approximation error. It is stressed that, for the LQR, HDP may be implemented without knowing the system A matrix by using two NNs. This fact is not generally appreciated in the folklore of HDP for the DT LQR, where only one critic NN is generally used.
Li, Zhanjie; Zhang, Peipei; Lv, Jinyang; Cheng, Yufeng; Cui, Jianmin; Zhao, Huixian; Hu, Shengwu
2016-01-01
Rapeseed (Brassica napus L.) is an important oil crop worldwide and exhibits significant heterosis. Effective pollination control systems, which are closely linked to anther development, are a prerequisite for utilizing heterosis. The anther, which is the male organ in flowering plants, undergoes many metabolic processes during development. Although the gene expression patterns underlying pollen development are well studied in model plant Arabidopsis, the regulatory networks of genome-wide gene expression during rapeseed anther development is poorly understood, especially regarding metabolic regulations. In this study, we systematically analyzed metabolic processes occurring during anther development in rapeseed using ultrastructural observation and global transcriptome analysis. Anther ultrastructure exhibited that numerous cellular organelles abundant with metabolic materials, such as elaioplast, tapetosomes, plastids (containing starch deposits) etc. appeared, accompanied with anther structural alterations during anther development, suggesting many metabolic processes occurring. Global transcriptome analysis revealed dynamic changes in gene expression during anther development that corresponded to dynamic functional alterations between early and late anther developmental stages. The early stage anthers preferentially expressed genes involved in lipid metabolism that are related to pollen extine formation as well as elaioplast and tapetosome biosynthesis, whereas the late stage anthers expressed genes associated with carbohydrate metabolism to form pollen intine and to accumulate starch in mature pollen grains. Finally, a predictive gene regulatory module responsible for early pollen extine formation was generated. Taken together, this analysis provides a comprehensive understanding of dynamic gene expression programming of metabolic processes in the rapeseed anther, especially with respect to lipid and carbohydrate metabolism during pollen development. PMID
Sabar, Nasser R; Ayob, Masri; Kendall, Graham; Qu, Rong
2015-02-01
Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite.
Bernhard, Axel; Casalbuoni, Sara; Ferracin, Paolo; Garcia Fajardo, Laura; Gerstl, Stefan; Gethmann, Julian; Grau, Andreas; Huttel, Erhard; Khrushchev, Sergey; Mezentsev, Nikolai; Müller, Anke-Susanne; Papaphilippou, Yannis; Saez de Jauregui, David; Schmickler, Hermann; Schoerling, Daniel; Shkaruba, Vitaliy; Smale, Nigel; Tsukanov, Valery; Zisopoulos, Panagiotis; Zolotarev, Konstantin
2016-01-01
In a collaboration between CERN, BINP and KIT a prototype of a superconducting damping wiggler for the CLIC damping rings has been installed at the ANKA synchrotron light source. On the one hand, the foreseen experimental program aims at validating the technical design of the wiggler, particularly the conduction cooling concept applied in its cryostat design, in a long-term study. On the other hand, the wiggler's influence on the beam dynamics particularly in the presence of collective effects is planned to be investigated. ANKA's low-alpha short-bunch operation mode will serve as a model system for these studies on collective effects. To simulate these effects and to make verifiable predictions an accurate model of the ANKA storage ring in low-alpha mode, including the insertion devices is under parallel development. This contribution reports on the first operational experience with the CLIC damping wiggler prototype in the ANKA storage ring and steps towards the planned advanced experimental program with th...
Ibarra, Ignacio L; Melo, Francisco
2010-07-01
Dynamic programming (DP) is a general optimization strategy that is successfully used across various disciplines of science. In bioinformatics, it is widely applied in calculating the optimal alignment between pairs of protein or DNA sequences. These alignments form the basis of new, verifiable biological hypothesis. Despite its importance, there are no interactive tools available for training and education on understanding the DP algorithm. Here, we introduce an interactive computer application with a graphical interface, for the purpose of educating students about DP. The program displays the DP scoring matrix and the resulting optimal alignment(s), while allowing the user to modify key parameters such as the values in the similarity matrix, the sequence alignment algorithm version and the gap opening/extension penalties. We hope that this software will be useful to teachers and students of bioinformatics courses, as well as researchers who implement the DP algorithm for diverse applications. The software is freely available at: http:/melolab.org/sat. The software is written in the Java computer language, thus it runs on all major platforms and operating systems including Windows, Mac OS X and LINUX. All inquiries or comments about this software should be directed to Francisco Melo at fmelo@bio.puc.cl.
Malroy, Eric T.
2007-01-01
The programs, arrays and logic structure were developed to enable the dynamic update of conductors in thermal desktop. The MatLab program FMHTPRE.m processes the Thermal Desktop conductors and sets up the arrays. The user needs to manually copy portions of the output to different input regions in Thermal Desktop. Also, Fortran subroutines are provided that perform the actual updates to the conductors. The subroutines are setup for helium gas, but the equations can be modified for other gases. The maximum number of free molecular conductors allowed is 10,000 for a given radiation task. Additional radiation tasks for FMHT can be generated to account for more conductors. Modifications to the Fortran subroutines may be warranted, when the mode of heat transfer is in the mixed or continuum mode. The FMHT Thermal Desktop model should be activated by using the "Case Set Manager" once the model is setup. Careful setup of the model is needed to avoid excessive solve times.
A dynamic food-chain model and program for predicting the consequences of nuclear accident
Institute of Scientific and Technical Information of China (English)
1998-01-01
A dynamic food-chain model and program, DYFOM-95, forpredicting the radiological consequences of nuclear accident hasbeen developed, which is not only suitable to the West food-chainbut also to Chinese food chain. The following processes, caused byaccident release which will make an impact on radionuclideconcentration in the edible parts of vegetable are considered: dryand wet deposition interception and initial retention,translocation, percolation, root uptake and tillage. Activityintake rate of animals, effects of processing and activity intakeof human through ingestion pathway are also considered incalculations. The effects of leaf area index LAI of vegetable areconsidered in dry deposition model. A method for calculating thecontribution of rain with different period and different intensityto total wet deposition is established. The program contains 1 maincode and 5 sub-codes to calculate dry and wet deposition on surfaceof vegetable and soil, translocation of nuclides in vegetable,nuclide concentration in the edible parts of vegetable and inanimal products and activity intake of human and so on.
Mogo, César; Brandão, João
2014-06-30
READY (REActive DYnamics) is a program for studying reactive dynamic systems using a global potential energy surface (PES) built from previously existing PESs corresponding to each of the most important elementary reactions present in the system. We present an application to the combustion dynamics of a mixture of hydrogen and oxygen using accurate PESs for all the systems involving up to four oxygen and hydrogen atoms. Results at the temperature of 4000 K and pressure of 2 atm are presented and compared with model based on rate constants. Drawbacks and advantages of this approach are discussed and future directions of research are pointed out.
Kouramas, K.I.
2011-08-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
Bamzai, A.
2003-04-01
This talk will highlight science and application activities of the CDEP and RISA programs at NOAA OGP. CDEP, through a set of Applied Research Centers (ARCs), supports NOAA's program of quantitative assessments and predictions of global climate variability and its regional implications on time scales of seasons to centuries. The RISA program consolidates results from ongoing disciplinary process research under an integrative framework. Examples of joint CDEP-RISA activities will be presented. Future directions and programmatic challenges will also be discussed.
Directory of Open Access Journals (Sweden)
John Shaji
2009-05-01
Full Text Available The purpose of the study was to compare, analyze the individual and combined effect of plyometric training program and dynamic stretching on vertical jump and agility. The subjects included 45, healthy male collegiate basketball players between the ages of 18-25. All subjects were tested in the vertical jump and agility using the Sergeant Jump test and T-test respectively prior to starting the dynamic stretching and plyometric training program. The subjects then completed a four week plyometric training program and were retested. Univariate ANOVA was conducted to analyze the change scores (post – pre in the independent variables by group (plyometric, dynamic stretching and combined with pre scores as covariates. The Univariate ANOVA revealed a significant group effect for Sergeant Jump test F = 12.95, P = 0.000 for Dynamic stretching group, F = 12.55, P = 0.000 for Plyometric training group and F = 15.11, P = 0.000 for combined group. The combined group reveled, maximum increase in the height when compared with the pretest scores. For the T-Test agility scores a significant group effect was found F = 2.00, P = 0.043 for Plyometric training group, F = 9.14, P = 0.000 for combined group while dynamic stretching group F = 2.11, P = 0.088 reveled non significant results. The findings suggested that two days of plyometric training a week in combination with dynamic stretching for four weeks is sufficient enough to show improvements in vertical jump height and agility. The results also suggest that two days of plyometric training and dynamic stretching are equally effective in improving vertical jump height. In contrast dynamic stretching two days a week for four weeks was not sufficient enough to show improvements in agility while plyometric training was sufficient.
Teachers' Scaffolding of Students' Learning of Geometry While Using a Dynamic Geometry Program
Dove, Anthony; Hollenbrands, Karen
2014-01-01
This study examined the scaffolds that three high school mathematics teachers provided to their geometry students as they used technology to explore geometric ideas. Teachers often used structured activities using a dynamic geometry program and provided significant emotive feedback while students worked through the tasks. This provided…
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix.
Directory of Open Access Journals (Sweden)
Jakob H Havgaard
2007-10-01
Full Text Available It has become clear that noncoding RNAs (ncRNA play important roles in cells, and emerging studies indicate that there might be a large number of unknown ncRNAs in mammalian genomes. There exist computational methods that can be used to search for ncRNAs by comparing sequences from different genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained. Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool for searching for new ncRNAs. The software package is available for download at http://foldalign.ku.dk.
Xu, Hao; Jagannathan, Sarangapani
2013-03-01
The stochastic optimal controller design for the nonlinear networked control system (NNCS) with uncertain system dynamics is a challenging problem due to the presence of both system nonlinearities and communication network imperfections, such as random delays and packet losses, which are not unknown a priori. In the recent literature, neuro dynamic programming (NDP) techniques, based on value and policy iterations, have been widely reported to solve the optimal control of general affine nonlinear systems. However, for realtime control, value and policy iterations-based methodology are not suitable and time-based NDP techniques are preferred. In addition, output feedback-based controller designs are preferred for implementation. Therefore, in this paper, a novel NNCS representation incorporating the system uncertainties and network imperfections is introduced first by using input and output measurements for facilitating output feedback. Then, an online neural network (NN) identifier is introduced to estimate the control coefficient matrix, which is subsequently utilized for the controller design. Subsequently, the critic and action NNs are employed along with the NN identifier to determine the forward-in-time, time-based stochastic optimal control of NNCS without using value and policy iterations. Here, the value function and control inputs are updated once a sampling instant. By using novel NN weight update laws, Lyapunov theory is used to show that all the closed-loop signals and NN weights are uniformly ultimately bounded in the mean while the approximated control input converges close to its target value with time. Simulation results are included to show the effectiveness of the proposed scheme.
Fotiadou, Eleni G; Neofotistou, Konstantina H; Sidiropoulou, Maria P; Tsimaras, Vasilios K; Mandroukas, Athanasios K; Angelopoulou, Nickoletta A
2009-10-01
The purpose of this study was to examine the effect of a rhythmic gymnastics program on the dynamic balance ability of a group of adults with intellectual disability (ID). The sample consisted of 18 adults with ID. The control group consisted of 8 adults and an intervention group of 10. The subjects were assigned to each group according to their desire to participate or not in the intervention program. Both groups were comparable in terms of age, weight, height, IQ, and socioeconomic background. The intervention group received a 12-week rhythmic gymnastics program at a frequency of 3 lessons per week, of 45 minutes. The methods of data collection included pre/post-test measurements of the dynamic balance for all subjects of both groups. The dynamic balance ability was measured by means of a balance deck (Lafayette) and was determined by the number of seconds the subject could remain standing on the platform of the stabilometer in durations of 30-, 45-, and 60-second intervals. As the results indicated, the intervention group showed a statistically significant improvement (p gymnastics program when compared with the control group. It is concluded that adults with ID can improve their balance ability with the application of a well-designed rhythmic gymnastics program.
EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon–Mann–Whitney Test
Directory of Open Access Journals (Sweden)
Alexander Marx
2016-02-01
Full Text Available In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney (WMW test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD. We found that approximated P values were generally higher than the exact solution provided by EDISON-WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.
EDISON-WMW:Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test
Institute of Scientific and Technical Information of China (English)
Alexander Marx; Christina Backes; Eckart Meese; Hans-Peter Lenhof; Andreas Keller
2016-01-01
In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney (WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calcu-late the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we pre-sented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molec-ular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD). We found that approximated P values were generally higher than the exact solution provided by EDISONWMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http:// www.ccb.uni-saarland.de/software/wtest/.
EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test.
Marx, Alexander; Backes, Christina; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas
2016-02-01
In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon-Mann-Whitney (WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD). We found that approximated P values were generally higher than the exact solution provided by EDISON-WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.
Timp, Sheila; Karssemeijer, Nico
2004-05-01
Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area Az under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in Az values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant.
Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter
2014-05-01
Optimal management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to optimize conjunctive use of scarce surface water and groundwater resources under uncertainty is presented. A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the optimal management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate and future costs for given surface water reservoir and groundwater aquifer end storages. The immediate cost is found by solving a simple linear allocation sub-problem, and the future costs are assessed by interpolation in the total cost matrix from the following time step. Total costs for all stages, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two-reservoir system the future cost function would have to be represented by a set of planes, and strict convexity in both the surface water and groundwater dimension cannot be maintained
Playa Soil Moisture and Evaporation Dynamics During the MATERHORN Field Program
Hang, Chaoxun; Nadeau, Daniel F.; Jensen, Derek D.; Hoch, Sebastian W.; Pardyjak, Eric R.
2016-06-01
We present an analysis of field data collected over a desert playa in western Utah, USA in May 2013, the most synoptically active month of the year, as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. The results show that decreasing surface albedo, decreasing Bowen ratio and increasing net radiation with increasing soil moisture sustained a powerful positive feedback mechanism promoting large evaporation rates immediately following rain events. Additionally, it was found that, while nocturnal evaporation was negligible during dry periods, it was quite significant (up to 30 % of the daily cumulative flux) during nights following rain events. Our results further show that the highest spatial variability in surface soil moisture is found under dry conditions. Finally, we report strong spatial heterogeneities in evaporation rates following a rain event. The cumulative evaporation for the different sampling sites over a five-day period varied from ≈ 0.1 to ≈ 6.6 mm. Overall, this study allows us to better understand the mechanisms underlying soil moisture dynamics of desert playas as well as evaporation following occasional rain events.
Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit
2010-01-01
The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.
Kremen, Arie; Tsompanakis, Yiannis
2010-04-01
The slope-stability of a proposed vertical extension of a balefill was investigated in the present study, in an attempt to determine a geotechnically conservative design, compliant with New Jersey Department of Environmental Protection regulations, to maximize the utilization of unclaimed disposal capacity. Conventional geotechnical analytical methods are generally limited to well-defined failure modes, which may not occur in landfills or balefills due to the presence of preferential slip surfaces. In addition, these models assume an a priori stress distribution to solve essentially indeterminate problems. In this work, a different approach has been applied, which avoids several of the drawbacks of conventional methods. Specifically, the analysis was performed in a two-stage process: (a) calculation of stress distribution, and (b) application of an optimization technique to identify the most probable failure surface. The stress analysis was performed using a finite element formulation and the location of the failure surface was located by dynamic programming optimization method. A sensitivity analysis was performed to evaluate the effect of the various waste strength parameters of the underlying mathematical model on the results, namely the factor of safety of the landfill. Although this study focuses on the stability investigation of an expanded balefill, the methodology presented can easily be applied to general geotechnical investigations.
Borisagar, Viral H; Zaveri, Mukesh A
2014-01-01
A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.
Directory of Open Access Journals (Sweden)
Viral H. Borisagar
2014-01-01
Full Text Available A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.
Akkus, Zeynettin; Bayat, Mahdi; Cheong, Mathew; Viksit, Kumar; Erickson, Bradley J; Alizad, Azra; Fatemi, Mostafa
2016-10-01
Tissue stiffness is often linked to underlying pathology and can be quantified by measuring the mechanical transient transverse wave speed (TWS) within the medium. Time-of-flight methods based on correlation of the transient signals or tracking of peaks have been used to quantify the TWS from displacement maps obtained with ultrasound pulse-echo techniques. However, it is challenging to apply these methods to in vivo data because of tissue inhomogeneity, noise and artifacts that produce outliers. In this study, we introduce a robust and fully automated method based on dynamic programming to estimate TWS in tissues with known geometries. The method is validated using ultrasound bladder vibrometry data from an in vivo study. We compared the results of our method with those of time-of-flight techniques. Our method performs better than time-of-flight techniques. In conclusion, we present a robust and accurate TWS detection method that overcomes the difficulties of time-of-flight methods.
Speech recognition using Kohonen neural networks, dynamic programming, and multi-feature fusion
Stowe, Francis S.
1990-12-01
The purpose of this thesis was to develop and evaluate the performance of a three-feature speech recognition system. The three features used were LPC spectrum, formants (F1/F2), and cepstrum. The system uses Kohonen neural networks, dynamic programming, and a rule-based, feature-fusion process which integrates the three input features into one output result. The first half of this research involved evaluating the system in a speaker-dependent atmosphere. For this, the 70 word F-16 cockpit command vocabulary was used and both isolated and connected speech was tested. Results obtained are compared to a two-feature system with the same system configuration. Isolated-speech testing yielded 98.7 percent accuracy. Connected-speech testing yielded 75/0 percent accuracy. The three-feature system performed an average of 1.7 percent better than the two-feature system for isolated-speech. The second half of this research was concerned with the speaker-independent performance of the system. First, cross-speaker testing was performed using an updated 86 word library. In general, this testing yielded less than 50 percent accuracy. Then, testing was performed using averaged templates. This testing yielded an overall average in-template recognition rate of approximately 90 percent and an out-of-template recognition rate of approximately 75 percent.
A clique-based method using dynamic programming for computing edit distance between unordered trees.
Mori, Tomoya; Tamura, Takeyuki; Fukagawa, Daiji; Takasu, Atsuhiro; Tomita, Etsuji; Akutsu, Tatsuya
2012-10-01
Many kinds of tree-structured data, such as RNA secondary structures, have become available due to the progress of techniques in the field of molecular biology. To analyze the tree-structured data, various measures for computing the similarity between them have been developed and applied. Among them, tree edit distance is one of the most widely used measures. However, the tree edit distance problem for unordered trees is NP-hard. Therefore, it is required to develop efficient algorithms for the problem. Recently, a practical method called clique-based algorithm has been proposed, but it is not fast for large trees. This article presents an improved clique-based method for the tree edit distance problem for unordered trees. The improved method is obtained by introducing a dynamic programming scheme and heuristic techniques to the previous clique-based method. To evaluate the efficiency of the improved method, we applied the method to comparison of real tree structured data such as glycan structures. For large tree-structures, the improved method is much faster than the previous method. In particular, for hard instances, the improved method achieved more than 100 times speed-up.
Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.
Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan
2016-08-01
Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.
Dynamic Programming for Instance Annotation in Multi-instance Multi-label Learning.
Pham, Anh; Raich, Raviv; Fern, Xiaoli
2017-01-05
Labeling data for classification requires significant human effort. To reduce labeling cost, instead of labeling every instance, a group of instances (bag) is labeled by a single bag label. Computer algorithms are then used to infer the label for each instance in a bag, a process referred to as instance annotation. This task is challenging due to the ambiguity regarding the instance labels. We propose a discriminative probabilistic model for the instance annotation problem and introduce an expectation maximization framework for inference, based on the maximum likelihood approach. For many probabilistic approaches, brute-force computation of the instance label posterior probability given its bag label is exponential in the number of instances in the bag. Our contribution is a dynamic programming method for computing the posterior that is linear in the number of instances. We evaluate our methods using both benchmark and real world data sets, in the domain of bird song, image annotation, and activity recognition. In many cases, the proposed framework outperforms, sometimes significantly, the current state-of-the-art MIML learning methods, both in instance label prediction and bag label prediction.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.
Zhang, Qichao; Zhao, Dongbin; Wang, Ding
2016-10-18
In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.
Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.
Wei, Qinglai; Liu, Derong; Lin, Qiao; Song, Ruizhuo
2017-01-27
In this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.
Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems.
Liu, Derong; Wei, Qinglai
2014-03-01
This paper is concerned with a new discrete-time policy iteration adaptive dynamic programming (ADP) method for solving the infinite horizon optimal control problem of nonlinear systems. The idea is to use an iterative ADP technique to obtain the iterative control law, which optimizes the iterative performance index function. The main contribution of this paper is to analyze the convergence and stability properties of policy iteration method for discrete-time nonlinear systems for the first time. It shows that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation. It is also proven that any of the iterative control laws can stabilize the nonlinear systems. Neural networks are used to approximate the performance index function and compute the optimal control law, respectively, for facilitating the implementation of the iterative ADP algorithm, where the convergence of the weight matrices is analyzed. Finally, the numerical results and analysis are presented to illustrate the performance of the developed method.
Detecting Wash Trade in Financial Market Using Digraphs and Dynamic Programming.
Cao, Yi; Li, Yuhua; Coleman, Sonya; Belatreche, Ammar; McGinnity, Thomas Martin
2016-11-01
A wash trade refers to the illegal activities of traders who utilize carefully designed limit orders to manually increase the trading volumes for creating a false impression of an active market. As one of the primary formats of market abuse, a wash trade can be extremely damaging to the proper functioning and integrity of capital markets. The existing work focuses on collusive clique detections based on certain assumptions of trading behaviors. Effective approaches for analyzing and detecting wash trade in a real-life market have yet to be developed. This paper analyzes and conceptualizes the basic structures of the trading collusion in a wash trade by using a directed graph of traders. A novel method is then proposed to detect the potential wash trade activities involved in a financial instrument by first recognizing the suspiciously matched orders and then further identifying the collusions among the traders who submit such orders. Both steps are formulated as a simplified form of the knapsack problem, which can be solved by dynamic programming approaches. The proposed approach is evaluated on seven stock data sets from the NASDAQ and the London Stock Exchange. The experimental results show that the proposed approach can effectively detect all primary wash trade scenarios across the selected data sets.
Mathews, David H.; Disney, Matthew D.; Childs, Jessica L.; Schroeder, Susan J.; Zuker, Michael; Turner, Douglas H.
2004-01-01
A dynamic programming algorithm for prediction of RNA secondary structure has been revised to accommodate folding constraints determined by chemical modification and to include free energy increments for coaxial stacking of helices when they are either adjacent or separated by a single mismatch. Furthermore, free energy parameters are revised to account for recent experimental results for terminal mismatches and hairpin, bulge, internal, and multibranch loops. To demonstrate the applicability of this method, in vivo modification was performed on 5S rRNA in both Escherichia coli and Candida albicans with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate, dimethyl sulfate, and kethoxal. The percentage of known base pairs in the predicted structure increased from 26.3% to 86.8% for the E. coli sequence by using modification constraints. For C. albicans, the accuracy remained 87.5% both with and without modification data. On average, for these sequences and a set of 14 sequences with known secondary structure and chemical modification data taken from the literature, accuracy improves from 67% to 76%. This enhancement primarily reflects improvement for three sequences that are predicted with <40% accuracy on the basis of energetics alone. For these sequences, inclusion of chemical modification constraints improves the average accuracy from 28% to 78%. For the 11 sequences with <6% pseudoknotted base pairs, structures predicted with constraints from chemical modification contain on average 84% of known canonical base pairs. PMID:15123812
Cui, Yunduan; Matsubara, Takamitsu; Sugimoto, Kenji
2017-06-29
We propose a new value function approach for model-free reinforcement learning in Markov decision processes involving high dimensional states that addresses the issues of brittleness and intractable computational complexity, therefore rendering the value function approach based reinforcement learning algorithms applicable to high dimensional systems. Our new algorithm, Kernel Dynamic Policy Programming (KDPP) smoothly updates the value function in accordance to the Kullback-Leibler divergence between current and updated policies. Stabilizing the learning in this manner enables the application of the kernel trick to value function approximation, which greatly reduces computational requirements for learning in high dimensional state spaces. The performance of KDPP against other kernel trick based value function approaches is first investigated in a simulated n DOF manipulator reaching task, where only KDPP efficiently learned a viable policy at n=40. As an application to a real world high dimensional robot system, KDPP successfully learned the task of unscrewing a bottle cap via a Pneumatic Artificial Muscle (PAM) driven robotic hand with tactile sensors; a system with a state space of 32 dimensions, while given limited samples and with ordinary computing resources. Copyright © 2017 Elsevier Ltd. All rights reserved.
Vakanski, A; Mantegh, I; Irish, A; Janabi-Sharifi, F
2012-08-01
The main objective of this paper is to develop an efficient method for learning and reproduction of complex trajectories for robot programming by demonstration. Encoding of the demonstrated trajectories is performed with hidden Markov model, and generation of a generalized trajectory is achieved by using the concept of key points. Identification of the key points is based on significant changes in position and velocity in the demonstrated trajectories. The resulting sequences of trajectory key points are temporally aligned using the multidimensional dynamic time warping algorithm, and a generalized trajectory is obtained by smoothing spline interpolation of the clustered key points. The principal advantage of our proposed approach is utilization of the trajectory key points from all demonstrations for generation of a generalized trajectory. In addition, variability of the key points' clusters across the demonstrated set is employed for assigning weighting coefficients, resulting in a generalization procedure which accounts for the relevance of reproduction of different parts of the trajectories. The approach is verified experimentally for trajectories with two different levels of complexity.
PRONTO 2D: A two-dimensional transient solid dynamics program
Energy Technology Data Exchange (ETDEWEB)
Taylor, L.M.; Flanagan, D.P.
1987-03-01
PRONTO 2D is a two-dimensional transient solid dynamics code for analyzing large deformations of highly nonlinear materials subjected to extremely high strain rates. This Lagrangian finite element program uses an explicit time integration operator to integrate the equations of motion. Four node uniform strain quadrilateral elements are used in the finite element formulation. A number of new numerical algorithms which have been developed for the code are described in this report. An adaptive time step control algorithm is described which greatly improves stability as well as performance in plasticity problems. A robust hourglass control scheme which eliminates hourglass distortions without disturbing the finite element solution is included. All constitutive models in PRONTO are cast in an unrotated configuration defined using the rotation determined from the polar decomposition of the deformation gradient. An accurate incremental algorithm was developed to determine this rotation and is described in detail. A robust contact algorithm was developed which allows for the impact and interaction of deforming contact surfaces of quite general geometry. A number of numerical examples are presented to demonstrate the utility of these algorithms. 41 refs., 51 figs., 5 tabs.
Using stochastic dual dynamic programming in problems with multiple near-optimal solutions
Rougé, Charles; Tilmant, Amaury
2016-05-01
Stochastic dual dynamic programming (SDDP) is one of the few algorithmic solutions available to optimize large-scale water resources systems while explicitly considering uncertainty. This paper explores the consequences of, and proposes a solution to, the existence of multiple near-optimal solutions (MNOS) when using SDDP for mid or long-term river basin management. These issues arise when the optimization problem cannot be properly parametrized due to poorly defined and/or unavailable data sets. This work shows that when MNOS exists, (1) SDDP explores more than one solution trajectory in the same run, suggesting different decisions in distinct simulation years even for the same point in the state-space, and (2) SDDP is shown to be very sensitive to even minimal variations of the problem setting, e.g., initial conditions—we call this "algorithmic chaos." Results that exhibit such sensitivity are difficult to interpret. This work proposes a reoptimization method, which simulates system decisions by periodically applying cuts from one given year from the SDDP run. Simulation results obtained through this reoptimization approach are steady state solutions, meaning that their probability distributions are stable from year to year.
Automated breast segmentation of fat and water MR images using dynamic programming.
Rosado-Toro, José A; Barr, Tomoe; Galons, Jean-Philippe; Marron, Marilyn T; Stopeck, Alison; Thomson, Cynthia; Thompson, Patricia; Carroll, Danielle; Wolf, Eszter; Altbach, María I; Rodríguez, Jeffrey J
2015-02-01
To develop and test an algorithm that outlines the breast boundaries using information from fat and water magnetic resonance images. Three algorithms were implemented and tested using registered fat and water magnetic resonance images. Two of the segmentation algorithms are simple extensions of the techniques used for contrast-enhanced images: one algorithm uses clustering and local gradient (CLG) analysis and the other algorithm uses a Hessian-based sheetness filter (HSF). The third segmentation algorithm uses k-means++ and dynamic programming (KDP) for finding the breast pixels. All three algorithms separate the left and right breasts using either a fixed region or a morphological method. The performance is quantified using a mutual overlap (Dice) metric and a pectoral muscle boundary error. The algorithms are evaluated against three manual tracers using 266 breast images from 14 female subjects. The KDP algorithm has a mean overlap percentage improvement that is statistically significant relative to the HSF and CLG algorithms. When using a fixed region to remove the tissue between breasts with tracer 1 as a reference, the KDP algorithm has a mean overlap of 0.922 compared to 0.864 (P algorithm is independent of breast density. We developed a new automated segmentation algorithm (KDP) to isolate breast tissue from magnetic resonance fat and water images. KDP outperforms the other techniques that focus on local analysis (CLG and HSF) and yields a performance similar to human tracers. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.
Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining
Hussain, Shahid
2016-07-10
This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.
A Dynamic Programming Algorithm For (1,2)-Exemplar Breakpoint Distance.
Wei, Zhexue; Zhu, Daming; Wang, Lusheng
2015-07-01
The exemplar breakpoint distance problem is motivated by finding conserved sets of genes between two genomes. It asks to find respective exemplars in two genomes to minimize the breakpoint distance between them. If one genome has no repeated gene (called trivial genome) and the other has genes repeating at most twice, it is referred to as the (1, 2)-exemplar breakpoint distance problem, EBD(1, 2) for short. Little has been done on algorithm design for this problem by now. In this article, we propose a parameter to describe the maximum physical span between two copies of a gene in a genome, and based on it, design a fixed-parameter algorithm for EBD(1, 2). Using a dynamic programming approach, our algorithm can take O(4(s)n(2)) time and O(4(s)n) space to solve an EBD(1, 2) instance that has two genomes of n genes where the second genome has each two copies of a gene spanning at most s copies of the genes. Our algorithm can also be used to compute the maximum adjacencies between two genomes. The algorithm has been implemented in C++. Simulations on randomly generated data have verified the effectiveness of our algorithm. The software package is available from the authors.
Itoh, Yoshiaki; Tanaka, Kazuyo
2004-08-01
Word frequency in a document has often been utilized in text searching and summarization. Similarly, identifying frequent words or phrases in a speech data set for searching and summarization would also be meaningful. However, obtaining word frequency in a speech data set is difficult, because frequent words are often special terms in the speech and cannot be recognized by a general speech recognizer. This paper proposes another approach that is effective for automatic extraction of such frequent word sections in a speech data set. The proposed method is applicable to any domain of monologue speech, because no language models or specific terms are required in advance. The extracted sections can be regarded as speech labels of some kind or a digest of the speech presentation. The frequent word sections are determined by detecting similar sections, which are sections of audio data that represent the same word or phrase. The similar sections are detected by an efficient algorithm, called Shift Continuous Dynamic Programming (Shift CDP), which realizes fast matching between arbitrary sections in the reference speech pattern and those in the input speech, and enables frame-synchronous extraction of similar sections. In experiments, the algorithm is applied to extract the repeated sections in oral presentation speeches recorded in academic conferences in Japan. The results show that Shift CDP successfully detects similar sections and identifies the frequent word sections in individual presentation speeches, without prior domain knowledge, such as language models and terms.
Implementation of a Small Type DC Microgrid Based on Fuzzy Control and Dynamic Programming
Directory of Open Access Journals (Sweden)
Chin-Hsing Cheng
2016-09-01
Full Text Available A DC microgrid (DC-MG is a novel power system that uses DC distribution in order to provide high quality power. The study system is made by a photovoltaic array (PV, a wind generator (WG, a fuel cell (FC, and an energy storage system (ESS to establish a small type DC microgrid, with the bus being established by DC/DC converters with fuzzy controllers. An overall power dispatch was designed for the proposed system to distribute the power flows among the different energy sources and the storage unit in the system in order to satisfy the load requirements throughout an entire 24-h period. The structure of a power supervisor based on an optimal power dispatch algorithm is here proposed. Optimization was performed using dynamic programming (DP. In this paper, a system configuration of a DC microgrid is analyzed in different scenarios to show the efficacy of the control for all devices for the variable weather conditions with different DC loads. Thus, the voltage level and the power flow of the system are shown for different load conditions.
Directory of Open Access Journals (Sweden)
Nisha
2015-03-01
Full Text Available BACKGROUND: Balance is highly integrative dynamic process involving coordination of multiple neurological pathways that allows for the maintenance of the COG over BOS . Football players often perform lower extremity passing , shooting , twisting , cutting and dribbling skills while wearing shoes , these actions require body to be in the equilibrium position to perform the task . This leads to t he conclusion of the great importance of the ability of balance in football . AIMS: 1 . To study the effect of 4 week multidirectional balance board training on dynamic balance in football players . 2 . To study the effect of 4 week Both Sides Up ball training on dynamic balance in football players . 3 . To compare the effect of multidirectional balance board training program and BOSU ball training program on dynamic balance in football players . STUDY DESIGN: Randomized Clinical trial . METHODS: Total of 60 competitive badminton players with age group between18 - 25 were recruited in this study . The participants were allocated into 2 groups viz ., Group A (multidirectional balance board training and Group B (BOSU ball Training for a period of 4 we eks . Participants were test for SEBT and vertical jump test on first day and after 4 weeks of balance training . STATISTICAL ANALYSIS: Student t test , Chi - Square Test . RESULTS: The data analysis and statistical inference showed that , after 4 weeks of balanc e training there was improvement in dynamic balance in both the groups but there was no significant difference in dynamic balance between two groups . As seen by difference in the SEBT and VJT scores pre and post training with p<0 . 001 . CONCLUSION: 4 weeks balance training using BOSU and multidirectional balance board is effective in improving dynamic balance and vertical jump performance in football players and also can be used as a component of multifaceted training to improve dynamic balance and game skills
1991-01-01
A Science Definition Team was established in December 1990 by the Space Physics Division, NASA, to develop a satellite program to conduct research on the energetics, dynamics, and chemistry of the mesosphere and lower thermosphere/ionosphere. This two-volume publication describes the TIMED (Thermosphere-Ionosphere-Mesosphere, Energetics and Dynamics) mission and associated science program. The report outlines the scientific objectives of the mission, the program requirements, and the approach towards meeting these requirements.
A system dynamics model of a large R&D program
Ahn, Namsung
Organizations with large R&D activities must deal with a hierarchy of decision regarding resource allocation. At the highest level of allocation, the decision is related to the total allocation to R&D as some portion of revenue. The middle level of allocation deals with the allocation among phases of the R&D process. The lowest level of decisions relates to the resource allocation to specific projects within a specific phase. This study focuses on developing an R&D model to deal with the middle level of allocation, i.e., the allocation among phases of research such as basic research, development, and demonstration. The methodology used to develop the R&D model is System Dynamics. Our modeling concept is innovative in representing each phase of R&D as consisting of two parts: projects under way, and an inventory of successful but not-yet- exploited projects. In a simple world, this concept can yield an exact analytical solution for allocation of resources among phases. But in a real world, the concept should be improved by adding more complex structures with nonlinear behaviors. Two particular nonlinear feedbacks are incorporated into the R&D model. The probability of success for any specific project is assumed partly dependent upon resources allocated to the project. Further, the time required to reach a conclusion regarding the success or failure of a project is also assumed dependent upon the level of resources allocated. In addition, the number of successful projects partly depends on the inventory of potential ideas in the previous stage that can be exploited. This model can provide R&D management with insights into the effect of changing allocations to phases whether those changes are internally or externally driven. With this model, it is possible to study the effectiveness of management decisions in a continuous fashion. Managers can predict payoffs for a host of different policies. In addition, as new research results accumulate, a re- assessment of program
A dynamic programming model for optimising feeding and slaughter decisions regarding fattening pigs
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J. K. NIEMI
2008-12-01
Full Text Available Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The state of nature and the genotype of a pig are known in the analysis. The results suggest that producer can benefit from improvements in the pigs genotype. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results also suggest that the producer can benefit from flexible feeding technology. Typically, such a technology provides incentives to feed piglets with protein-rich feed. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pigs biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects.;
Dattani, Nikesh S.
2013-12-01
This MATLAB program calculates the dynamics of the reduced density matrix of an open quantum system modeled either by the Feynman-Vernon model or the Caldeira-Leggett model. The user gives the program a Hamiltonian matrix that describes the open quantum system as if it were in isolation, a matrix of the same size that describes how that system couples to its environment, and a spectral distribution function and temperature describing the environment’s influence on it, in addition to the open quantum system’s initial density matrix and a grid of times. With this, the program returns the reduced density matrix of the open quantum system at all moments specified by that grid of times (or just the last moment specified by the grid of times if the user makes this choice). This overall calculation can be divided into two stages: the setup of the Feynman integral, and the actual calculation of the Feynman integral for time propagation of the density matrix. When this program calculates this propagation on a multi-core CPU, it is this propagation that is usually the rate-limiting step of the calculation, but when it is calculated on a GPU, the propagation is calculated so quickly that the setup of the Feynman integral can actually become the rate-limiting step. The overhead of transferring information from the CPU to the GPU and back seems to have a negligible effect on the overall runtime of the program. When the required information cannot fit on the GPU, the user can choose to run the entire program on a CPU. Catalogue identifier: AEPX_v1_0. Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEPX_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.: 703. No. of bytes in distributed program, including test data, etc.: 11026. Distribution format: tar.gz. Programming
Wawro, Martha; Haden, Carol
2014-06-01
The Solar Dynamics Observatory’s (SDO) education and public outreach (EPO) team has developed and implemented a number of formal education programs for K-12 students and teachers. Programs include the Day At Goddard field trip for high school students, SDO Ambassador in the Classroom outreach to elementary classrooms, and teacher support materials for solar science education. These programs have been designed to foster student interest and engagement in science especially solar science, and increase their awareness and interest in NASA and STEM careers. Magnolia Consulting, who worked closely with the SDO EPO team to both design a substantive evaluation program, as well as improve the education programs offered, has extensively evaluated these programs. Evaluation findings indicate that teachers highly value the opportunities and resources provided by SDO EPO and that student impacts include increased interest and engagement in solar science topics and awareness of STEM careers. This presentation will be a summary of the results of the evaluation of these formal education programs including lessons learned that can be of value to the STEM EPO community.
Energy Technology Data Exchange (ETDEWEB)
Masciola, M.; Jonkman, J.; Robertson, A.
2014-03-01
Techniques to model dynamic mooring lines come in various forms. The most widely used models include either a heuristic representation of the physics (such as a Lumped-Mass, LM, system), a Finite-Element Analysis (FEA) discretization of the lines (discretized in space), or a Finite-Difference (FD) model (which is discretized in both space and time). In this paper, we explore the features of the various models, weigh the advantages of each, and propose a plan for implementing one dynamic mooring line model into the open-source Mooring Analysis Program (MAP). MAP is currently used as a module for the FAST offshore wind turbine computer-aided engineering (CAE) tool to model mooring systems quasi-statically, although dynamic mooring capabilities are desired. Based on the exploration in this manuscript, the lumped-mass representation is selected for implementation in MAP based on its simplicity, computational cost, and ability to provide similar physics captured by higher-order models.
Molodenskii, D. S.
2017-01-01
A VecDec4SAS program has been developed to provide a fast and easy description of the dynamics of any process occurring in a nanoparticle solution observed by the small-angle scattering technique. The process should be characterized by the some conditional initial and final stages, in fractions of which all intermediate data are expanded. The program makes it possible to estimate the adequacy of two-basis approximation and indicate the presence of an additional process introducing a systematic error into the initial data. Scattering curves for human serum albumin protein in solutions with pH 7.4 and 3.0 and a concentration of 20 mg/mL, obtained on the DICSY station at the National Research Centre "Kurchatov Institute" in the solution temperature range from 25 to 70°C, were taken to be initial data to illustrate the potential of the program.
Directory of Open Access Journals (Sweden)
Livia BOBU
2015-09-01
Full Text Available In most of the developing countries, dental caries continues to represent a major issue of public health. In Romania, the National Program for Oral and Dental Diseases Prevention was implemented between 1999-2010, addressed to children attending primary school and consisting of weekly mouth rinses with 0.2% NaF solution. In the present study, the dynamic evolution of oral health status of schoolchildren aged 6-12 years in Iasi, under the impact of this Program, was analyzed. The results showed a decreasing trend in the prevalence and incidence of dental caries, a constant decrease of caries experience indices DMFT and DMFS and, within them, the increasing trend of fillings indicator FS and the decrease of deep lesions weight. The conclusion is that tooth decay has declined in schoolchildren in Iasi during the development of the National Prevention Program.
Wölfer, Ralf; Scheithauer, Herbert
2014-01-01
Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior.
Using stochastic dynamic programming to support catchment-scale water resources management in China
Davidsen, Claus; Pereira-Cardenal, Silvio Javier; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter
2013-04-01
A hydro-economic modelling approach is used to optimize reservoir management at river basin level. We demonstrate the potential of this integrated approach on the Ziya River basin, a complex basin on the North China Plain south-east of Beijing. The area is subject to severe water scarcity due to low and extremely seasonal precipitation, and the intense agricultural production is highly dependent on irrigation. Large reservoirs provide water storage for dry months while groundwater and the external South-to-North Water Transfer Project are alternative sources of water. An optimization model based on stochastic dynamic programming has been developed. The objective function is to minimize the total cost of supplying water to the users, while satisfying minimum ecosystem flow constraints. Each user group (agriculture, domestic and industry) is characterized by fixed demands, fixed water allocation costs for the different water sources (surface water, groundwater and external water) and fixed costs of water supply curtailment. The multiple reservoirs in the basin are aggregated into a single reservoir to reduce the dimensions of decisions. Water availability is estimated using a hydrological model. The hydrological model is based on the Budyko framework and is forced with 51 years of observed daily rainfall and temperature data. 23 years of observed discharge from an in-situ station located downstream a remote mountainous catchment is used for model calibration. Runoff serial correlation is described by a Markov chain that is used to generate monthly runoff scenarios to the reservoir. The optimal costs at a given reservoir state and stage were calculated as the minimum sum of immediate and future costs. Based on the total costs for all states and stages, water value tables were generated which contain the marginal value of stored water as a function of the month, the inflow state and the reservoir state. The water value tables are used to guide allocation decisions in
Exactly computing the parsimony scores on phylogenetic networks using dynamic programming.
Kannan, Lavanya; Wheeler, Ward C
2014-04-01
Scoring a given phylogenetic network is the first step that is required in searching for the best evolutionary framework for a given dataset. Using the principle of maximum parsimony, we can score phylogenetic networks based on the minimum number of state changes across a subset of edges of the network for each character that are required for a given set of characters to realize the input states at the leaves of the networks. Two such subsets of edges of networks are interesting in light of studying evolutionary histories of datasets: (i) the set of all edges of the network, and (ii) the set of all edges of a spanning tree that minimizes the score. The problems of finding the parsimony scores under these two criteria define slightly different mathematical problems that are both NP-hard. In this article, we show that both problems, with scores generalized to adding substitution costs between states on the endpoints of the edges, can be solved exactly using dynamic programming. We show that our algorithms require O(m(p)k) storage at each vertex (per character), where k is the number of states the character can take, p is the number of reticulate vertices in the network, m = k for the problem with edge set (i), and m = 2 for the problem with edge set (ii). This establishes an O(nm(p)k(2)) algorithm for both the problems (n is the number of leaves in the network), which are extensions of Sankoff's algorithm for finding the parsimony scores for phylogenetic trees. We will discuss improvements in the complexities and show that for phylogenetic networks whose underlying undirected graphs have disjoint cycles, the storage at each vertex can be reduced to O(mk), thus making the algorithm polynomial for this class of networks. We will present some properties of the two approaches and guidance on choosing between the criteria, as well as traverse through the network space using either of the definitions. We show that our methodology provides an effective means to
Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles
Directory of Open Access Journals (Sweden)
Lai Po-Ting
2011-02-01
Full Text Available Abstract Background Experimentally verified protein-protein interactions (PPIs cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be facilitated by employing text-mining systems to identify genes which play the interactor role in PPIs and to map these genes to unique database identifiers (interactor normalization task or INT and then to return a list of interaction pairs for each article (interaction pair task or IPT. These two tasks are evaluated in terms of the area under curve of the interpolated precision/recall (AUC iP/R score because the order of identifiers in the output list is important for ease of curation. Results Our INT system developed for the BioCreAtIvE II.5 INT challenge achieved a promising AUC iP/R of 43.5% by using a support vector machine (SVM-based ranking procedure. Using our new re-ranking algorithm, we have been able to improve system performance (AUC iP/R by 1.84%. Our experimental results also show that with the re-ranked INT results, our unsupervised IPT system can achieve a competitive AUC iP/R of 23.86%, which outperforms the best BC II.5 INT system by 1.64%. Compared to using only SVM ranked INT results, using re-ranked INT results boosts AUC iP/R by 7.84%. Statistical significance t-test results show that our INT/IPT system with re-ranking outperforms that without re-ranking by a statistically significant difference. Conclusions In this paper, we present a new re-ranking algorithm that considers co-occurrence among identifiers in an article to improve INT and IPT ranking results. Combining the re-ranked INT results with an unsupervised approach to find associations among interactors, the proposed method can boost the IPT performance. We also implement score computation using dynamic programming, which is faster and more efficient than traditional approaches.
Turner, Sean; Galelli, Stefano; Wilcox, Karen
2015-04-01
Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating
A dynamic programming approach for quickly estimating large network-based MEV models
DEFF Research Database (Denmark)
Mai, Tien; Frejinger, Emma; Fosgerau, Mogens
2017-01-01
by a rooted, directed graph where each node without successor is an alternative. We formulate a family of MEV models as dynamic discrete choice models on graphs of correlation structures and show that the dynamic models are consistent with MEV theory and generalize the network MEV model (Daly and Bierlaire...
Bai, Fang; Liao, Sha; Gu, Junfeng; Jiang, Hualiang; Wang, Xicheng; Li, Honglin
2015-04-27
Metalloproteins, particularly zinc metalloproteins, are promising therapeutic targets, and recent efforts have focused on the identification of potent and selective inhibitors of these proteins. However, the ability of current drug discovery and design technologies, such as molecular docking and molecular dynamics simulations, to probe metal-ligand interactions remains limited because of their complicated coordination geometries and rough treatment in current force fields. Herein we introduce a robust, multiobjective optimization algorithm-driven metalloprotein-specific docking program named MpSDock, which runs on a scheme similar to consensus scoring consisting of a force-field-based scoring function and a knowledge-based scoring function. For this purpose, in this study, an effective knowledge-based zinc metalloprotein-specific scoring function based on the inverse Boltzmann law was designed and optimized using a dynamic sampling and iteration optimization strategy. This optimization strategy can dynamically sample and regenerate decoy poses used in each iteration step of refining the scoring function, thus dramatically improving both the effectiveness of the exploration of the binding conformational space and the sensitivity of the ranking of the native binding poses. To validate the zinc metalloprotein-specific scoring function and its special built-in docking program, denoted MpSDockZn, an extensive comparison was performed against six universal, popular docking programs: Glide XP mode, Glide SP mode, Gold, AutoDock, AutoDock4Zn, and EADock DSS. The zinc metalloprotein-specific knowledge-based scoring function exhibited prominent performance in accurately describing the geometries and interactions of the coordination bonds between the zinc ions and chelating agents of the ligands. In addition, MpSDockZn had a competitive ability to sample and identify native binding poses with a higher success rate than the other six docking programs.
Modelling the Influence of Awareness Programs by Media on the Drinking Dynamics
Directory of Open Access Journals (Sweden)
Hai-Feng Huo
2014-01-01
Full Text Available We develop a nonlinear mathematical model with the effect of awareness programs on the binge drinking. Due to the fact that awareness programs are capable of inducing behavioral changes in nondrinkers, we introduce a separate class by avoiding contacts with the heavy drinkers. Furthermore we assume that cumulative density of awareness programs increases at a rate proportional to the number of heavy drinkers. We establish some sufficient conditions for the stability of the alcohol free and the alcohol present equilibria and give some numerical simulations to explain our main result. Our results show that awareness programs is an effective measure in reducing alcohol problems.
Demonstration Program for Low-Cost, High-Energy-Saving Dynamic Windows
2014-09-01
Design The scope of this project was to demonstrate the impact of dynamic windows via energy savings and HVAC peak-load reduction; to validate the...dominated by the internal thermal loads of office equipment (example AC 7) so the HVAC energy savings are lower in those zones. Figure 8. Plot...of daily HVAC energy consumption in four representative zones, before and after dynamic windows retrofit. Overall, energy savings in all eastern
Veiga-Lopez, Almudena; Astapova, Olga I; Aizenberg, Esther F; Lee, James S; Padmanabhan, Vasantha
2009-04-01
Prenatal testosterone excess leads to neuroendocrine and periovulatory disruptions in the offspring culminating in progressive loss of cyclicity. It is unknown whether the mediary of these disruptions is androgen or estrogen, because testosterone can be aromatized to estrogen. Taking a reproductive life span approach of studying control, prenatal testosterone, and dihydrotestosterone-treated offspring, this study tested the hypothesis that disruptions in estradiol-negative but not -positive feedback effects are programmed by androgenic actions of testosterone and that these disruptions in turn will have an impact on the periovulatory hormonal dynamics. The approach was to test estradiol-negative and -positive feedback responses of all three groups of ovary-intact females during prepubertal age and then compare the periovulatory dynamics of luteinizing hormone, follicle-stimulating hormone, estradiol, and progesterone during the first breeding season. The findings show that estradiol-negative but not estradiol-positive feedback disruptions in prenatal testosterone-treated females are programmed by androgenic actions of prenatal testosterone excess and that follicular phase estradiol and gonadotropins surge disruptions during reproductive life are consistent with estrogenic programming. Additional studies carried out testing estradiol-positive feedback response over time found progressive deterioration of estradiol-positive feedback in prenatal testosterone-treated sheep until the time of puberty. Together, these findings provide insight into the mechanisms by which prenatal testosterone disrupts the reproductive axis. The findings may be of translational relevance since daughters of mothers with hyperandrogenism are at risk of increased exposure to androgens.
Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Maduskar, Pragnya, E-mail: pragnya.maduskar@radboudumc.nl; Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van [Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Jong, Pim A. de [Department of Radiology, University Medical Center Utrecht, 3584 CX (Netherlands); Peters-Bax, Liesbeth [Department of Radiology, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Dawson, Rodney [University of Cape Town Lung Institute, Cape Town 7700 (South Africa); Ayles, Helen [Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT (United Kingdom)
2014-07-15
Purpose: Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. Methods: A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. Results: The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were
Image Enhancement Using Linear Programming Method for High Dynamic Range Image
Directory of Open Access Journals (Sweden)
S. Yamini
2014-01-01
Full Text Available Now a days in Telecommunication areas the contrast gain is considered as a major constraints. For the enhancement purpose, the technique called Histogram Equalization is involved, but due to over enhancement and not such gain is been obtained. So that for the OCTM is been proposed, where the constraints of HE is been rectified. OCTM gives better efficiency and it is been solved by Linear programming. In this paper the enhancement of HDR Image using linear Programming is done. According to it HDR Image is constructed using the multiple exposures and its contrast is enhanced using the OCTM method using Linear Programming.
Directory of Open Access Journals (Sweden)
Huei Peng
2013-04-01
Full Text Available This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT. A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP and Pontryagin’s Minimum Principle (PMP are applied to obtain the optimal solutions. Tuning with the appropriate co-states, the PMP solution is found to be very close to that from DP. The solution for the gear shifting in PMP has an algebraic expression associated with the vehicular velocity and can be implemented more efficiently in the control algorithm. The computation time of PMP is significantly less than DP.
The Expansion of Dynamic Solving Process About a Class of Non-linear Programming Problems
Institute of Scientific and Technical Information of China (English)
ZANG Zhen-chun
2001-01-01
In this paper, we research non-linear programming problems which have a given specialstructure, some simple forms of this kind structure have been solved in some papers, here we focus on othercomplex ones.
THE DEVELOPMENT OF AN EBook WITH DYNAMIC CONTENT FOR THE INTRODUCTION OF ALGORITHMS and PROGRAMMING
Directory of Open Access Journals (Sweden)
Gürcan Çetin
2016-12-01
Full Text Available It is very important that the content of Algorithms and Programming course is understood by Computer Engineering students. The eBook designed in this study provides a better explanation of the flow diagrams and programming logic of the algorithms used in the introduction to programming, as well as the abstract processing steps in the computer memory and CPU during programming are animated and visualized by means of computer animations and simulations. The EPUB 3.0 based training content, developed by using animation and interactive content, is expected to create new opportunities for students at anytime and anywhere access. This work also includes the development process of an EPUB 3.0 based eBook for use on computers or mobile devices.
Zhang, Huaguang; Song, Ruizhuo; Wei, Qinglai; Zhang, Tieyan
2011-12-01
In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.
Amin, Talha
2013-01-01
In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.
Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.
Fu, Yue; Fu, Jun; Chai, Tianyou
2015-12-01
In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.
Qiu, J. P.; Niu, D. X.
Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.
Mikic, Zoran; Grebowsky, Joseph M. (Technical Monitor)
2001-01-01
This report covers technical progress during the fourth quarter of the second year of NASA Sun-Earth Connections Theory Program (SECTP) contract 'The Structure and Dynamics of the Solar Corona and Inner Heliosphere,' NAS5-99188, between NASA and Science Applications International Corporation, and covers the period May 16,2001 to August 15, 2001. Under this contract SAIC and the University of California, Irvine (UCI) have conducted research into theoretical modeling of active regions, the solar corona, and the inner heliosphere, using the MHD model.
DEFF Research Database (Denmark)
Solov'yov, Ilia; Yakubovich, Alexander V.; Nikolaev, Pavel V.;
2012-01-01
We present a multipurpose computer code MesoBioNano Explorer (MBN Explorer). The package allows to model molecular systems of varied level of complexity. In particular, MBN Explorer is suited to compute system's energy, to optimize molecular structure as well as to consider the molecular and random...... walk dynamics. MBN Explorer allows to use a broad variety of interatomic potentials, to model different molecular systems, such as atomic clusters, fullerenes, nanotubes, polypeptides, proteins, DNA, composite systems, nanofractals, and so on. A distinct feature of the program, which makes...
Goodman, Lawrence E
2001-01-01
Beginning text presents complete theoretical treatment of mechanical model systems and deals with technological applications. Topics include introduction to calculus of vectors, particle motion, dynamics of particle systems and plane rigid bodies, technical applications in plane motions, theory of mechanical vibrations, and more. Exercises and answers appear in each chapter.
Application of linear programming techniques for controlling linear dynamic plants in real time
Gabasov, R.; Kirillova, F. M.; Ha, Vo Thi Thanh
2016-03-01
The problem of controlling a linear dynamic plant in real time given its nondeterministic model and imperfect measurements of the inputs and outputs is considered. The concepts of current distributions of the initial state and disturbance parameters are introduced. The method for the implementation of disclosable loop using the separation principle is described. The optimal control problem under uncertainty conditions is reduced to the problems of optimal observation, optimal identification, and optimal control of the deterministic system. To extend the domain where a solution to the optimal control problem under uncertainty exists, a two-stage optimal control method is proposed. Results are illustrated using a dynamic plant of the fourth order.
Dattani, Nikesh S
2012-01-01
This MATLAB program calculates the dynamics of the reduced density matrix of an open quantum system modeled by the Feynman-Vernon model. The user gives the program a vector describing the coordinate of an open quantum system, a hamiltonian matrix describing its energy, and a spectral distribution function and temperature describing the environment's influence on it, in addition to the open quantum system's intial density matrix and a grid of times. With this, the program returns the reduced density matrix of the open quantum system at all (or some) moments specified by that grid of times. This overall calculation can be divided into two stages: the setup of the Feynman integral, and the actual calculation of the Feynman integral for time-propagation of the density matrix. When this program calculates this propagation on a multi-core CPU, it is this propagation that is usually the rate limiting step of the calculation, but when it is calculated on a GPU, the propagation is calculated so quickly that the setup ...
Marshall, Neil; Buteau, Chantal
2014-01-01
As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…
JED: a Java Essential Dynamics Program for comparative analysis of protein trajectories.
David, Charles C; Singam, Ettayapuram Ramaprasad Azhagiya; Jacobs, Donald J
2017-05-25
Essential Dynamics (ED) is a common application of principal component analysis (PCA) to extract biologically relevant motions from atomic trajectories of proteins. Covariance and correlation based PCA are two common approaches to determine PCA modes (eigenvectors) and their eigenvalues. Protein dynamics can be characterized in terms of Cartesian coordinates or internal distance pairs. In understanding protein dynamics, a comparison of trajectories taken from a set of proteins for similarity assessment provides insight into conserved mechanisms. Comprehensive software is needed to facilitate comparative-analysis with user-friendly features that are rooted in best practices from multivariate statistics. We developed a Java based Essential Dynamics toolkit called JED to compare the ED from multiple protein trajectories. Trajectories from different simulations and different proteins can be pooled for comparative studies. JED implements Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) as options to construct covariance (Q) or correlation (R) matrices. Statistical methods are implemented for treating outliers, benchmarking sampling adequacy, characterizing the precision of Q and R, and reporting partial correlations. JED output results as text files that include transformed coordinates for aligned structures, several metrics that quantify protein mobility, PCA modes with their eigenvalues, and displacement vector (DV) projections onto the top principal modes. Pymol scripts together with PDB files allow movies of individual Q- and R-cPCA modes to be visualized, and the essential dynamics occurring within user-selected time scales. Subspaces defined by the top eigenvectors are compared using several statistical metrics to quantify similarity/overlap of high dimensional vector spaces. Free energy landscapes can be generated for both cPCA and dpPCA. JED offers a convenient toolkit that encourages best practices in applying multivariate
Dynamically Translating Binary Code for Multi-Threaded Programs Using Shared Code Cache
Institute of Scientific and Technical Information of China (English)
Chia-Lun Liu; Jiunn-Yeu Chen; Wuu Yang; Wei-Chung Hsu
2014-01-01
mc2llvm is a process-level ARM-to-x86 binary translator developed in our lab in the past several years. Currently, it is able to emulate single-threaded programs. We extend mc2llvm to emulate multi-threaded programs. Our main task is to reconstruct its architecture for multi-threaded programs. Register mapping, code cache management, and address mapping in mc2llvm have all been modified. In addition, to further speed up the emulation, we collect hot paths, aggressively optimize and generate code for them at run time. Additional threads are used to alleviate the overhead. Thus, when the same hot path is walked through again, the corresponding optimized native code will be executed instead. In our experiments, our system is 8.8X faster than QEMU (quick emulator) on average when emulating the specified benchmarks with 8 guest threads.
Liao, Bolin; Zhang, Yunong; Jin, Long
2016-02-01
In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.
Zhang, Jilie; Zhang, Huaguang; Liu, Zhenwei; Wang, Yingchun
2015-07-01
In this paper, we consider the problem of developing a controller for continuous-time nonlinear systems where the equations governing the system are unknown. Using the measurements, two new online schemes are presented for synthesizing a controller without building or assuming a model for the system, by two new implementation schemes based on adaptive dynamic programming (ADP). To circumvent the requirement of the prior knowledge for systems, a precompensator is introduced to construct an augmented system. The corresponding Hamilton-Jacobi-Bellman (HJB) equation is solved by adaptive dynamic programming, which consists of the least-squared technique, neural network approximator and policy iteration (PI) algorithm. The main idea of our method is to sample the information of state, state derivative and input to update the weighs of neural network by least-squared technique. The update process is implemented in the framework of PI. In this paper, two new implementation schemes are presented. Finally, several examples are given to illustrate the effectiveness of our schemes.
Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo
2016-04-22
A data-driven adaptive tracking control approach is proposed for a class of continuous-time nonlinear systems using a recent developed goal representation heuristic dynamic programming (GrHDP) architecture. The major focus of this paper is on designing a multivariable tracking scheme, including the filter-based action network (FAN) architecture, and the stability analysis in continuous-time fashion. In this design, the FAN is used to observe the system function, and then generates the corresponding control action together with the reference signals. The goal network will provide an internal reward signal adaptively based on the current system states and the control action. This internal reward signal is assigned as the input for the critic network, which approximates the cost function over time. We demonstrate its improved tracking performance in comparison with the existing heuristic dynamic programming (HDP) approach under the same parameter and environment settings. The simulation results of the multivariable tracking control on two examples have been presented to show that the proposed scheme can achieve better control in terms of learning speed and overall performance.
Nordin, Noraimi Azlin Mohd; Omar, Mohd; Sharif, S. Sarifah Radiah
2017-04-01
Companies are looking forward to improve their productivity within their warehouse operations and distribution centres. In a typical warehouse operation, order picking contributes more than half percentage of the operating costs. Order picking is a benchmark in measuring the performance and productivity improvement of any warehouse management. Solving order picking problem is crucial in reducing response time and waiting time of a customer in receiving his demands. To reduce the response time, proper routing for picking orders is vital. Moreover, in production line, it is vital to always make sure the supplies arrive on time. Hence, a sample routing network will be applied on EP Manufacturing Berhad (EPMB) as a case study. The Dijkstra's algorithm and Dynamic Programming method are applied to find the shortest distance for an order picker in order picking. The results show that the Dynamic programming method is a simple yet competent approach in finding the shortest distance to pick an order that is applicable in a warehouse within a short time period.
Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun
2016-02-01
As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
Dynamics and Control of Orbiting Space Structures NASA Advanced Design Program (ADP)
Cruse, T. A.
1996-01-01
The report summarizes the advanced design program in the mechanical engineering department at Vanderbilt University for the academic years 1994-1995 and 1995-1996. Approximately 100 students participated in the two years of the subject grant funding. The NASA-oriented design projects that were selected included lightweight hydrogen propellant tank for the reusable launch vehicle, a thermal barrier coating test facility, a piezoelectric motor for space antenna control, and a lightweight satellite for automated materials processing. The NASA supported advanced design program (ADP) has been a success and a number of graduates are working in aerospace and are doing design.
Directory of Open Access Journals (Sweden)
Abdolhamid Daneshjoo
Full Text Available PURPOSE: The study investigated the effects of FIFA 11+ and HarmoKnee, both being popular warm-up programs, on proprioception, and on the static and dynamic balance of professional male soccer players. METHODS: Under 21 year-old soccer players (n = 36 were divided randomly into 11+, HarmoKnee and control groups. The programs were performed for 2 months (24 sessions. Proprioception was measured bilaterally at 30°, 45° and 60° knee flexion using the Biodex Isokinetic Dynamometer. Static and dynamic balances were evaluated using the stork stand test and Star Excursion Balance Test (SEBT, respectively. RESULTS: The proprioception error of dominant leg significantly decreased from pre- to post-test by 2.8% and 1.7% in the 11+ group at 45° and 60° knee flexion, compared to 3% and 2.1% in the HarmoKnee group. The largest joint positioning error was in the non-dominant leg at 30° knee flexion (mean error value = 5.047, (p<0.05. The static balance with the eyes opened increased in the 11+ by 10.9% and in the HarmoKnee by 6.1% (p<0.05. The static balance with eyes closed significantly increased in the 11+ by 12.4% and in the HarmoKnee by 17.6%. The results indicated that static balance was significantly higher in eyes opened compared to eyes closed (p = 0.000. Significant improvements in SEBT in the 11+ (12.4% and HarmoKnee (17.6% groups were also found. CONCLUSION: Both the 11+ and HarmoKnee programs were proven to be useful warm-up protocols in improving proprioception at 45° and 60° knee flexion as well as static and dynamic balance in professional male soccer players. Data from this research may be helpful in encouraging coaches or trainers to implement the two warm-up programs in their soccer teams.
Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong
2011-12-01
In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.
Energy Technology Data Exchange (ETDEWEB)
Panin, Anatoly, E-mail: a.panin@fz-juelich.de [Forschungszentrum Jülich GmbH, Institut für Energie- und Klimaforschung – Plasmaphysik, 52425 Jülich (Germany); Khovayko, Mikhail [St. Petersburg Polytechnic University, Mechanics and Control Processes Department, Computational Mechanics Laboratory, 195251 St. Petersburg (Russian Federation); Krasikov, Yury [Forschungszentrum Jülich GmbH, Institut für Energie- und Klimaforschung – Plasmaphysik, 52425 Jülich (Germany); Nemov, Alexander [St. Petersburg Polytechnic University, Mechanics and Control Processes Department, Computational Mechanics Laboratory, 195251 St. Petersburg (Russian Federation); Biel, Wolfgang; Mertens, Philippe; Neubauer, Olaf; Schrader, Michael [Forschungszentrum Jülich GmbH, Institut für Energie- und Klimaforschung – Plasmaphysik, 52425 Jülich (Germany)
2015-10-15
To prolong a lifetime of the ITER first diagnostic mirrors some protective shutters can be engaged. A concept of an elastic shutter that operates frictionless in vacuum has been studied at the Forschungszentrum Jülich, Germany. Under actuation two shutter arms (∼2 m long) bend laterally between two pairs of limiting bumpers thus shielding the optical aperture or opening it for measurements. To increase the shutter efficiency the transition time between its open and closed states can be minimized. This demands a fast shutter that operates in fractions of a second and exhibit essentially dynamic behavior, like impacts with the bumpers that cause the shutter arms’ bouncing and oscillations. The paper presents numerical studies of the shutter dynamic behavior using the explicit and implicit 3D FE transient structural modeling. Simple 1D analytical model was developed to predict the shutter impact kinetic energy that mostly determines its further dynamic response. The structure sensitivity to different parameters was studied and ways for its optimization were laid down. A parametric shutter mockup with easily changeable mechanical characteristics was manufactured. A test program aimed for further shutter optimization, basing on the analysis performed and engaging powerful capabilities of the parametric shutter mockup is discussed in the paper.
On Static and Dynamic Control-Flow Information in Program Analysis and Transformation
DEFF Research Database (Denmark)
Damian, Daniel
, while the same CPS transformation does not affect continuation-based partial evaluation and its corresponding binding-time analysis. As an intermediate result, we show that reducing a program in the computational metalanguage to monadic normal form also improves binding times for traditional partial...
2012-03-30
... Joint Program Office, Research and Innovative Technology Administration, U.S. Department of... May 24, 2012 at the Gaylord National Hotel and Convention Center, 201 Waterfront Street, National... to high-quality, real-time and archived, multi-modal transportation data that is captured from...
DYNAMIC COMPLEMENTARITY IN EXPORT PROMOTION: THE MARKET ACCESS PROGRAM IN FRUITS AND VEGETABLES
Richards, Timothy J.; Patterson, Paul M.
1998-01-01
Government-supported promotion in foreign markets may justified when market failures exist, such as spillover externalities, where promotion of one commodity positively influences exports of another, or when market uncertainties cause planning horizons to be shorter than the persistent effects of promotion. A dynamic model of U.S. apple, almond, grape, and wine export supply is developed to test for these market failures. Promotion is viewed as an investment in establishing and maintaining a ...
Stochastic linear dynamical programming in order to apply it in energy modelling
Energy Technology Data Exchange (ETDEWEB)
El Hachem, S.
1995-11-01
This thesis contributes to the development of new algorithms for the computation of stochastic dynamic problem and its mini-maxi variant for the case of imperfect knowledge on random data. The proposed algorithms are scenarios aggregation type. It also contributes to integrate these algorithms in a decision support approach and to discuss the stochastic modeling of two energy problems: the refining and the portfolio gas contracts. (author). 112 refs., 5 tabs.
基于动态规划法的微网动态经济调度%Dynamic Economic Dispatch of Microgrid Based on Dynamic Programming
Institute of Scientific and Technical Information of China (English)
赵健; 王茗萱
2016-01-01
针对微网中微源的动态特性，如风力发电和光伏发电出力的随机性以及蓄电池运行过程中在时间上的耦合性，阐述了对微网经济调度进行动态研究的关键性。分析了风力发电、光伏发电、微型燃气轮机、柴油发电机和铅酸蓄电池的输出特性以及成本组成，以微网成本最小为目标建立数学模型并确定该模型的约束条件，结合微源的动态特性，利用动态规划法进行求解，通过算例得到微网中各个微源的出力以及微网的最小成本，验证了该模型和算法的有效性。%For the problem of the randomness of the wind power and photovoltaic power output as well as the battery in time during the operation of coupling,the importance of studying the dynamic economic dispatch of net is expounded. With the analysis of the working principle of photovoltaic power generation,the micro gas tur-bine,diesel generators,lead-acid battery,and to establish the micro source, s cost model,and puts forward the dynamic theory,establishing dynamic mathematical model as the target of micro network cost minimum and de-termining the constraints of the model,the piconets in different distributed power optimization scheduling prob-lem is solved. Thus improving the micro operation economy of the network. Based on dynamic programming to optimize micro network economy,and the validity of the model and algorithm is verified by an example.
Disentangling the dynamic core: a research program for a neurodynamics at the large-scale.
Le Van Quyen, Michel
2003-01-01
My purpose in this paper is to sketch a research direction based on Francisco Varela's pioneering work in neurodynamics (see also Rudrauf et al. 2003, in this issue). Very early on he argued that the internal coherence of every mental-cognitive state lies in the global self-organization of the brain activities at the large-scale, constituting a fundamental pole of integration called here a "dynamic core". Recent neuroimaging evidence appears to broadly support this hypothesis and suggests that a global brain dynamics emerges at the large scale level from the cooperative interactions among widely distributed neuronal populations. Despite a growing body of evidence supporting this view, our understanding of these large-scale brain processes remains hampered by the lack of a theoretical language for expressing these complex behaviors in dynamical terms. In this paper, I propose a rough cartography of a comprehensive approach that offers a conceptual and mathematical framework to analyze spatio-temporal large-scale brain phenomena. I emphasize how these nonlinear methods can be applied, what property might be inferred from neuronal signals, and where one might productively proceed for the future. This paper is dedicated, with respect and affection, to the memory of Francisco Varela.
Solving a class of geometric programming problems by an efficient dynamic model
Nazemi, Alireza; Sharifi, Elahe
2013-03-01
In this paper, a neural network model is constructed on the basis of the duality theory, optimization theory, convex analysis theory, Lyapunov stability theory and LaSalle invariance principle to solve geometric programming (GP) problems. The main idea is to convert the GP problem into an equivalent convex optimization problem. A neural network model is then constructed for solving the obtained convex programming problem. By employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the original problem. The simulation results also show that the proposed neural network is feasible and efficient.
RAD750 SBC Usage for the Solar Dynamics Observatory (SDO) Program
Li, Kenneth
2005-01-01
This presentation focuses on the first space weather research mission in the Living with a Star (LWS) Program. The science objective of the mission is to understand the solar variations that influence life on Earth. The mission is developed and managed by NASA/GSFC with a launch date in 2008 on a five-year mission using a geosynchronous inclined orbit. Involved with the mission are three science instruments: a helloseisic and magnetic imagery (HMI), extreme ultraviolet variability experiment (EVE), and solar helispheric activity research prediction program (SHARPP). 6U qualification Vib test has been completed with successful results (no interrupts detected at 1 nanosecond). Other test result to be reported at workshop.
A hybrid programming model for compressible gas dynamics using openCL
Energy Technology Data Exchange (ETDEWEB)
Bergen, Benjamin Karl [Los Alamos National Laboratory; Daniels, Marcus G [Los Alamos National Laboratory; Weber, Paul M [Los Alamos National Laboratory
2010-01-01
The current trend towards multicore/manycore and accelerated architectures presents challenges, both in portability, and also in the choices that developers must make on how to use the resources that these architectures provide. This paper explores some of the possibilities that are enabled by the Open Computing Language (OpenCL), and proposes a programming model that allows developers and scientists to more fully subscribe hybrid compute nodes, while, at the same time, reducing the impact of system failure.
Directory of Open Access Journals (Sweden)
S. Sofana Reka
2016-09-01
Full Text Available This paper proposes a cloud computing framework in smart grid environment by creating small integrated energy hub supporting real time computing for handling huge storage of data. A stochastic programming approach model is developed with cloud computing scheme for effective demand side management (DSM in smart grid. Simulation results are obtained using GUI interface and Gurobi optimizer in Matlab in order to reduce the electricity demand by creating energy networks in a smart hub approach.
Ryan, J. W.; Ma, C.; Caprette, D. S.
1993-01-01
The Goddard VLBI group reports the results of analyzing 1648 Mark 3 data sets acquired from fixed and mobile observing sites through the end of 1991, and available to the Crustal Dynamics Project. Two large solutions were used to obtain Earth rotation parameters, nutation offsets, radio source positions, site positions, site velocities, and baseline evolution. Site positions are tabulated on a yearly basis for 1979 to 1995, inclusive. Site velocities are presented in both geocentric Cartesian and topocentric coordinates. Baseline evolution is plotted for 200 baselines, and individual length determinations are presented for an additional 356 baselines. This report includes 155 quasar radio sources, 96 fixed stations and mobile sites, and 556 baselines.
Bevilacqua, R.; Romano, M.
2008-01-01
The article of record may be found at http://www.e-ndst.kiev.ua Autonomous close flight and docking of a chaser spacecraft to a target are still challenging problems. In this paper the Hill–Clohessy–Wiltshire equations are taken as dynamic model and inverted, after a variable change, in order to be used by a control algorithm to drive the chaser spacecraft along a specified path. The path parameterization is performed by using cubic B- splines and by having the curvilinear abscissa as para...
Padmanabhan, V; Smith, P; Veiga-Lopez, A
2012-08-01
Prenatal testosterone (T) excess leads to reproductive dysfunctions in sheep with obesity exaggerating such defects. Developmental studies found ovarian reserve is similar in control and prenatal T sheep at fetal day 140, with prenatal T females showing increased follicular recruitment and persistence at 10 months of age (postpubertal). This study tested if prenatal T sheep show accelerated depletion prepubertally and if depletion of ovarian reserve would explain loss of cyclicity in prenatal T females and its amplification by postnatal obesity. Stereological examinations were performed at 5 (prepubertal, control and prenatal T) and 21 months (control, prenatal T and prenatal T obese, following estrus synchronization) of age. Obesity was induced by overfeeding from weaning. At 5 months, prenatal T females had 46% less primordial follicles than controls (P obesity did not exaggerate the impact of prenatal T on follicular recruitment indicating that compounding effects of obesity on loss of cyclicity females is not due to depletion of ovarian reserve. Assessment of follicular dynamics across several time points during the reproductive life span (this and earlier study combined) provides evidence supportive of a shift in follicular dynamics in prenatal T females from one of accelerated follicular depletion initiated prior to puberty to stockpiling of growing follicles after puberty, a time point critical in the development of the polycystic ovary syndrome phenotype.
Directory of Open Access Journals (Sweden)
Vasileios K. Tsimaras
2015-04-01
Full Text Available Traditional dance is gaining popularity as an intervention choice for improving poor balance ability of people with intellectual disability (ID. Balance improvement for individuals with ID through dance provides opportunities for participation in sport activities and promotes independent living. This short review provides in brief research evidence of dynamic balance improvement as measured by means of a balance deck in duration of 30, 45, and 60 sec intervals, highlighting the need to incorporate traditional dance programs in Physical Education (PE lessons applied on participants with ID. Overall, traditional dances provide emotional and cognitive interaction that has a direct positive effect on quality of life and successful motor performance of individuals with ID.
Energy Technology Data Exchange (ETDEWEB)
Abbasy, N.H. [College of Technological Studies, Shuwaikh (Kuwait); Elfayoumy, M.K. [Univ. of Alexandria (Egypt). Dept. of Electrical Engineering
1995-11-01
An improved two stages solution model to the unit commitment of thermal units is developed in this paper. In the first stage a pre-schedule is generated using a high quality trained artificial neural net (ANN). A dynamic programming (DP) algorithm is implemented and applied in the second stage for the final determination of the commitment states. The developed solution model avoids the complications imposed by the generation of the variable window structure, proposed by other techniques. A unified approach for the treatment of the ANN is also developed in the paper. The validity of the proposed technique is proved via numerical applications to both sample and small practical power systems. 12 refs, 9 tabs
Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai
2011-01-01
In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method.
Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang
2016-10-03
In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.
AbouEisha, Hassan M.
2014-06-06
In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm. Thus, the criterion for the optimization of the elimination tree is the computational cost associated with the multi-frontal solver algorithm executed over such tree. We illustrate the paper with several examples of optimal trees found for grids with point, isotropic edge and anisotropic edge mixed with point singularity. We show the comparison of the execution time of the multi-frontal solver algorithm with results of MUMPS solver with METIS library, implementing the nested dissection algorithm.
Biswas, Abhishek; Ranjan, Desh; Zubair, Mohammad; He, Jing
2015-09-01
The determination of secondary structure topology is a critical step in deriving the atomic structures from the protein density maps obtained from electron cryomicroscopy technique. This step often relies on matching the secondary structure traces detected from the protein density map to the secondary structure sequence segments predicted from the amino acid sequence. Due to inaccuracies in both sources of information, a pool of possible secondary structure positions needs to be sampled. One way to approach the problem is to first derive a small number of possible topologies using existing matching algorithms, and then find the optimal placement for each possible topology. We present a dynamic programming method of Θ(Nq(2)h) to find the optimal placement for a secondary structure topology. We show that our algorithm requires significantly less computational time than the brute force method that is in the order of Θ(q(N) h).
Bade, W. L.; Yos, J. M.
1975-01-01
A computer program for calculating quasi-one-dimensional gas flow in axisymmetric and two-dimensional nozzles and rectangular channels is presented. Flow is assumed to start from a state of thermochemical equilibrium at a high temperature in an upstream reservoir. The program provides solutions based on frozen chemistry, chemical equilibrium, and nonequilibrium flow with finite reaction rates. Electronic nonequilibrium effects can be included using a two-temperature model. An approximate laminar boundary layer calculation is given for the shear and heat flux on the nozzle wall. Boundary layer displacement effects on the inviscid flow are considered also. Chemical equilibrium and transport property calculations are provided by subroutines. The code contains precoded thermochemical, chemical kinetic, and transport cross section data for high-temperature air, CO2-N2-Ar mixtures, helium, and argon. It provides calculations of the stagnation conditions on axisymmetric or two-dimensional models, and of the conditions on the flat surface of a blunt wedge. The primary purpose of the code is to describe the flow conditions and test conditions in electric arc heated wind tunnels.
Automatic Identification of Closed-Loop Wind Turbine Dynamics via Genetic Programming
Energy Technology Data Exchange (ETDEWEB)
La Cava, William; Danai, Kourosh; Lackner, Matthew; Spector, Lee; Fleming, Paul; Wright, Alan
2015-10-03
Wind turbines are nonlinear systems that operate in turbulent environments. As such, their behavior is difficult to characterize accurately across a wide range of operating conditions by physically meaningful models. Customarily, data-based models of wind turbines are defined in 'black box' format, lacking in both conciseness and physical intelligibility. To address this deficiency, we identify models of a modern horizontal-axis wind turbine in symbolic form using a recently developed symbolic regression method. The method used relies on evolutionary multi-objective optimization to produce succinct dynamic models from operational data without 'a priori' knowledge of the system. We compare the produced models with models derived by other methods for their estimation capacity and evaluate the tradeoff between model intelligibility and accuracy. Several succinct models are found that predict wind turbine behavior as well as or better than more complex alternatives derived by other methods.
A Dynamic Programming-Based Heuristic for the Shift Design Problem in Airport Ground Handling
DEFF Research Database (Denmark)
Clausen, Tommy
We consider the heterogeneous shift design problem for a workforce with multiple skills, where work shifts are created to cover a given demand as well as possible while minimizing cost and satisfying a flexible set of constraints. We focus mainly on applications within airport ground handling where...... the demand can be highly irregular and specified on time intervals as short as five minutes. Ground handling operations are subject to a high degree of cooperation and specialization that require workers with different qualifications to be planned together. Different labor regulations or organizational rules...... can apply to different ground handling operations, so the rules and restrictions can be numerous and vary significantly. This is modeled using flexible volume constraints that limit the creation of certain shifts. We present a fast heuristic for the heterogeneous shift design problem based on dynamic...
Dynamic T cell migration program provides resident memory within intestinal epithelium
Choo, Daniel; Vezys, Vaiva; Wherry, E. John; Duraiswamy, Jaikumar; Akondy, Rama; Wang, Jun; Casey, Kerry A.; Barber, Daniel L.; Kawamura, Kim S.; Fraser, Kathryn A.; Webby, Richard J.; Brinkmann, Volker; Butcher, Eugene C.; Newell, Kenneth A.
2010-01-01
Migration to intestinal mucosa putatively depends on local activation because gastrointestinal lymphoid tissue induces expression of intestinal homing molecules, whereas skin-draining lymph nodes do not. This paradigm is difficult to reconcile with reports of intestinal T cell responses after alternative routes of immunization. We reconcile this discrepancy by demonstrating that activation within spleen results in intermediate induction of homing potential to the intestinal mucosa. We further demonstrate that memory T cells within small intestine epithelium do not routinely recirculate with memory T cells in other tissues, and we provide evidence that homing is similarly dynamic in humans after subcutaneous live yellow fever vaccine immunization. These data explain why systemic immunization routes induce local cell-mediated immunity within the intestine and indicate that this tissue must be seeded with memory T cell precursors shortly after activation. PMID:20156972
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix
DEFF Research Database (Denmark)
Havgaard, Jakob Hull; Torarinsson, Elfar; Gorodkin, Jan
2007-01-01
genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may...... the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained....... Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned...
Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications
Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid
1999-01-01
The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.
Summer study program in geophysical fluid dynamics, Woods Hole Oceanographic Institution: Chaos
Veronis, G.; Hudon, L. M.
1985-11-01
The explosive growth of dynamical system theory stems in large part from the realization that it is applicable to many natural phenomena. Indeed, much of the theoretical development has been sparked by numerical and laboratory experiments which exhibit ordered sequences of behavior that call for a general framework of interpretation. Five lectures exposed us to elementaty examples of bifurcation and chaos, to symmetry breaking, normal forms and temporal and spatial disorder, as well as to pertinent fluid mechanical and astrophysical phenomena. In addition are the development with an elegant summary of different types of intermittency; Seminars on phase instability and turbulence as an extension of the lecture series; and the fascinating correspondence between the frequencies observed in one recent fluid mechanics experiment, and results from number theory relating the Fibonacci series to the golden mean.
Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs
RIngenburg, Michael F.
Energy efficiency is a key concern in the design of modern computer systems. One promising approach to energy-efficient computation, approximate computing, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This thesis presents dynamic analysis tools to study, debug, and monitor the quality and energy efficiency of approximate computations. We propose three styles of tools: prototyping tools that allow developers to experiment with approximation in their applications, online tools that instrument code to determine the key sources of error, and online tools that monitor the quality of deployed applications in real time. Our prototyping tool is based on an extension to the functional language OCaml. We add approximation constructs to the language, an approximation simulator to the runtime, and profiling and auto-tuning tools for studying and experimenting with energy-quality tradeoffs. We also present two online debugging tools and three online monitoring tools. The first online tool identifies correlations between output quality and the total number of executions of, and errors in, individual approximate operations. The second tracks the number of approximate operations that flow into a particular value. Our online tools comprise three low-cost approaches to dynamic quality monitoring. They are designed to monitor quality in deployed applications without spending more energy than is saved by approximation. Online monitors can be used to perform real time adjustments to energy usage in order to meet specific quality goals. We present prototype implementations of all of these tools and describe their usage with several applications. Our prototyping, profiling, and autotuning tools allow us to experiment with approximation strategies and identify new strategies, our online tools succeed in providing new insights into the effects of approximation on output quality, and our monitors succeed in
Veiga-Lopez, A; Ye, W; Phillips, D J; Herkimer, C; Knight, P G; Padmanabhan, V
2008-04-01
Prenatal testosterone excess leads to neuroendocrine, ovarian, and metabolic disruptions, culminating in reproductive phenotypes mimicking that of women with polycystic ovary syndrome (PCOS). The objective of this study was to determine the consequences of prenatal testosterone treatment on periovulatory hormonal dynamics and ovulatory outcomes. To generate prenatal testosterone-treated females, pregnant sheep were injected intramuscularly (days 30-90 of gestation, term=147 days) with 100 mg of testosterone-propionate in cottonseed oil semi-weekly. Female offspring born to untreated control females and prenatal testosterone-treated females were then studied during their first two breeding seasons. Sheep were given two injections of prostaglandin F2alpha 11 days apart, and blood samples were collected at 2-h intervals for 120 h, 10-min intervals for 8 h during the luteal phase (first breeding season only), and daily for an additional 15 days to characterize changes in reproductive hormonal dynamics. During the first breeding season, prenatal testosterone-treated females manifested disruptions in the timing and magnitude of primary gonadotropin surges, luteal defects, and reduced responsiveness to progesterone negative feedback. Disruptions in the periovulatory sequence of events during the second breeding season included: 1) delayed but increased preovulatory estradiol rise, 2) delayed and severely reduced primary gonadotropin surge in prenatal testosterone-treated females having an LH surge, 3) tendency for an amplified secondary FSH surge and a shift in the relative balance of FSH regulatory proteins, and 4) luteal responses that ranged from normal to anovulatory. These outcomes are likely to be of relevance to developmental origin of infertility disorders and suggest that differences in fetal exposure or fetal susceptibility to testosterone may account for the variability in reproductive phenotypes.
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.
Karemere, Hermès; Ribesse, Nathalie; Kahindo, Jean-Bosco; Macq, Jean
2015-01-01
In many African countries, first referral hospitals received little attention from development agencies until recently. We report the evolution of two of them in an unstable region like Eastern Democratic Republic of Congo when receiving the support from development aid program. Specifically, we aimed at studying how actors' network and institutional framework evolved over time and what could matter the most when looking at their performance in such an environment. We performed two cases studies between 2006 and 2010. We used multiple sources of data: reports to document events; health information system for hospital services production, and "key-informants" interviews to interpret the relation between interventions and services production. Our analysis was inspired from complex adaptive system theory. It started from the analysis of events implementation, to explore interaction process between the main agents in each hospital, and the consequence it could have on hospital health services production. This led to the development of new theoretical propositions. Two events implemented in the frame of the development aid program were identified by most of the key-informants interviewed as having the greatest impact on hospital performance: the development of a hospital plan and the performance based financing. They resulted in contrasting interaction process between the main agents between the two hospitals. Two groups of services production were reviewed: consultation at outpatient department and admissions, and surgery. The evolution of both groups of services production were different between both hospitals. By studying two first referral hospitals through the lens of a Complex Adaptive System, their performance in a context of development aid takes a different meaning. Success is not only measured through increased hospital production but through meaningful process of hospital agents'" network adaptation. Expected process is not necessarily a change; strengthened
Energy Technology Data Exchange (ETDEWEB)
Silva, Marcelo Mariano da
2008-01-15
The search for high performance and low cost hardware and software solutions always guides the developments performed at the IEN parallel computing laboratory. In this context, this dissertation about the building of programs for visualization of computational fluid dynamics (CFD) simulations using the open source software OpenDx was written. The programs developed are useful to produce videos and images in two or three dimensions. They are interactive, easily to use and were designed to serve fluid dynamics researchers. A detailed description about how this programs were developed and the complete instructions of how to use them was done. The use of OpenDx as development tool is also introduced. There are examples that help the reader to understand how programs can be useful for many applications. (author)
Energy Technology Data Exchange (ETDEWEB)
Sofronov, I.D.; Voronin, B.L.; Butnev, O.I. [VNIIEF (Russian Federation)] [and others
1997-12-31
The aim of the work performed is to develop a 3D parallel program for numerical calculation of gas dynamics problem with heat conductivity on distributed memory computational systems (CS), satisfying the condition of numerical result independence from the number of processors involved. Two basically different approaches to the structure of massive parallel computations have been developed. The first approach uses the 3D data matrix decomposition reconstructed at temporal cycle and is a development of parallelization algorithms for multiprocessor CS with shareable memory. The second approach is based on using a 3D data matrix decomposition not reconstructed during a temporal cycle. The program was developed on 8-processor CS MP-3 made in VNIIEF and was adapted to a massive parallel CS Meiko-2 in LLNL by joint efforts of VNIIEF and LLNL staffs. A large number of numerical experiments has been carried out with different number of processors up to 256 and the efficiency of parallelization has been evaluated in dependence on processor number and their parameters.
Directory of Open Access Journals (Sweden)
H. Rezazadeh
2009-04-01
Full Text Available The concept of virtual cellular manufacturing system (VCMS is finding acceptance among researchers as an extension to grouptechnology. In fact, in order to realize benefits of cellular manufacturing system in the functional layout, the VCMS createsprovisional groups of resources (machines, parts and workers in the production planning and control system. This paperdevelops a mathematical model to design the VCMS under a dynamic environment with a more integrated approach whereproduction planning, system reconfiguration and workforce requirements decisions are incorporated. The advantages of theproposed model are as follows: considering the operations sequence, alternative process plans for part types, machine timecapacity,worker time‐capacity, cross‐training, lot splitting, maximal cell size, balanced workload for cells and workers. Anefficient linear programming embedded particle swarm optimization algorithm is used to solve the proposed model. Thealgorithm searches over the 0‐1 integer variables and for each 0‐1 integer solution visited; corresponding values of integervariables are determined by solving a linear programming sub‐problem using the simplex algorithm. Numerical examples showthat the proposed method is efficient and effective in searching for near optimal solutions.
Directory of Open Access Journals (Sweden)
François Rebaudo
2011-10-01
Full Text Available Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM combining social (diffusion theory and biological (pest population dynamics models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.
Directory of Open Access Journals (Sweden)
Burke Les J
2007-10-01
Full Text Available Abstract Background Expression profiling of embryonic stem (ES cell differentiation in the presence of serum has been performed previously. It remains unclear if transcriptional activation is dependent on complex growth factor mixtures in serum or whether this process is intrinsic to ES cells once the stem cell program has been inactivated. The aims of this study were to determine the transcriptional programs associated with the stem cell state and to characterize mesoderm differentiation between serum and serum-free culture. Results ES cells were differentiated as embryoid bodies in 10% FBS or serum-free media containing BMP4 (2 ng/ml, and expression profiled using 47 K Illumina(R Sentrix arrays. Statistical methods were employed to define gene sets characteristic of stem cell, epiblast and primitive streak programs. Although the initial differentiation profile was similar between the two culture conditions, cardiac gene expression was inhibited in serum whereas blood gene expression was enhanced. Also, expression of many members of the Kruppel-like factor (KLF family of transcription factors changed dramatically during the first few days of differentiation. KLF2 and KLF4 co-localized with OCT4 in a sub-nuclear compartment of ES cells, dynamic changes in KLF-DNA binding activities occurred upon differentiation, and strong bio-informatic evidence for direct regulation of many stem cell genes by KLFs was found. Conclusion Down regulation of stem cell genes and activation of epiblast/primitive streak genes is similar in serum and defined media, but subsequent mesoderm differentiation is strongly influenced by the composition of the media. In addition, KLF family members are likely to be important regulators of many stem cell genes.
Rebaudo, François; Dangles, Olivier
2011-10-01
Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.
Xiao, Jingjie
A key hurdle for implementing real-time pricing of electricity is a lack of consumers' responses. Solutions to overcome the hurdle include the energy management system that automatically optimizes household appliance usage such as plug-in hybrid electric vehicle charging (and discharging with vehicle-to-grid) via a two-way communication with the grid. Real-time pricing, combined with household automation devices, has a potential to accommodate an increasing penetration of plug-in hybrid electric vehicles. In addition, the intelligent energy controller on the consumer-side can help increase the utilization rate of the intermittent renewable resource, as the demand can be managed to match the output profile of renewables, thus making the intermittent resource such as wind and solar more economically competitive in the long run. One of the main goals of this dissertation is to present how real-time retail pricing, aided by control automation devices, can be integrated into the wholesale electricity market under various uncertainties through approximate dynamic programming. What distinguishes this study from the existing work in the literature is that whole- sale electricity prices are endogenously determined as we solve a system operator's economic dispatch problem on an hourly basis over the entire optimization horizon. This modeling and algorithm framework will allow a feedback loop between electricity prices and electricity consumption to be fully captured. While we are interested in a near-optimal solution using approximate dynamic programming; deterministic linear programming benchmarks are use to demonstrate the quality of our solutions. The other goal of the dissertation is to use this framework to provide numerical evidence to the debate on whether real-time pricing is superior than the current flat rate structure in terms of both economic and environmental impacts. For this purpose, the modeling and algorithm framework is tested on a large-scale test case
Convergence of Weighted Min-Sum Decoding Via Dynamic Programming on Trees
Jian, Yung-Yih
2011-01-01
Applying the max-product (and belief-propagation) algorithms to loopy graphs is now quite popular for best assignment problems. This is largely due to their low computational complexity and impressive performance in practice. Still, there is no general understanding of the conditions required for convergence and/or the optimality of converged solutions. This paper presents an analysis of both attenuated max-product (AMP) decoding and weighted min-sum (WMS) decoding for LDPC codes which guarantees convergence to a fixed point when a weight parameter, {\\beta}, is sufficiently small. It also shows that, if the fixed point satisfies some consistency conditions, then it must be both the linear-programming (LP) and maximum-likelihood (ML) solution. For (dv,dc)-regular LDPC codes, the weight must satisfy {\\beta}(dv-1) \\leq 1 whereas the results proposed by Frey and Koetter require instead that {\\beta}(dv-1)(dc-1) 1 is also given. Finally, connections are explored with recent work by Arora et al. on the threshold of...
Qualitative assessment of the role of public health education program on HIV transmission dynamics.
Hussaini, N; Winter, M; Gumel, A B
2011-09-01
This paper presents a non-linear deterministic model for assessing the impact of public health education campaign on curtailing the spread of the human immunodeficiency virus (HIV) pandemic in a population. Rigorous qualitative analysis of the model reveals that it exhibits the phenomenon of backward bifurcation (BB), where a stable disease-free equilibrium coexists with a stable endemic equilibrium when a certain threshold quantity, known as the 'effective reproduction number' ('Reff), is less than unity. The epidemiological implication of BB is that a public health education campaign could fail to effectively control HIV even when the classical requirement of having the associated reproduction number less than unity is satisfied. Furthermore, an explicit threshold value is derived above which such an education campaign could lead to detrimental outcome (increase disease burden) and below which it would have positive population-level impact (reduce disease burden in the community). It is shown that the BB phenomenon is caused by imperfect efficacy of the public health education program. The model is used to assess the potential impact of some targeted public health education campaigns using data from numerous countries.
Cottrell, Paul Edward
There is a lack of research in the area of hedging future contracts, especially in illiquid or very volatile market conditions. It is important to understand the volatility of the oil and currency markets because reduced fluctuations in these markets could lead to better hedging performance. This study compared different hedging methods by using a hedging error metric, supplementing the Receding Horizontal Control and Stochastic Programming (RHCSP) method by utilizing the London Interbank Offered Rate with the Levy process. The RHCSP hedging method was investigated to determine if improved hedging error was accomplished compared to the Black-Scholes, Leland, and Whalley and Wilmott methods when applied on simulated, oil, and currency futures markets. A modified RHCSP method was also investigated to determine if this method could significantly reduce hedging error under extreme market illiquidity conditions when applied on simulated, oil, and currency futures markets. This quantitative study used chaos theory and emergence for its theoretical foundation. An experimental research method was utilized for this study with a sample size of 506 hedging errors pertaining to historical and simulation data. The historical data were from January 1, 2005 through December 31, 2012. The modified RHCSP method was found to significantly reduce hedging error for the oil and currency market futures by the use of a 2-way ANOVA with a t test and post hoc Tukey test. This study promotes positive social change by identifying better risk controls for investment portfolios and illustrating how to benefit from high volatility in markets. Economists, professional investment managers, and independent investors could benefit from the findings of this study.
Kularathna, M.D.U.P.
1992-01-01
The technique of Stochastic Dynamic Programming (SDP) is ideally suited for operation policy analyses of water resources systems. However SDP has a major drawback which is appropriately termed as its "curse of dimensionality".Aggregation/Disaggregation techniques based on SDP and simulation are pres
Analysis of Natural Frequencies in the Universal Programs for Dynamic Processes Analysis
Directory of Open Access Journals (Sweden)
V. A. Trudonoshin
2016-01-01
Full Text Available Finding the natural frequencies of complex technical objects is an important design procedure. This type of analysis allows us to determine the resonant frequencies and, as a consequence, to avoid their adverse impact on dynamics the projected object or that of under study. This applies to both the objects with distributed parameters, and the objects with lumped parameters. As to the first type of the objects, in almost every package that implements the finite element method, this type of analysis is available. The situation is different for the objects with lumped parameters. Methods to have the mathematical models for these objects look to implicit methods of numerical integration of ordinary differential equations. And the component equations of the reactive branches are sampled by numerical integration formulas, and the derivatives of state variables disappear from the vector of the unknowns of a mathematical model. In this case, talk about the implementation of the procedure for finding natural frequencies by finding eigenvalues is simply unnecessary. In cases where a mathematical model of the object is given in the normal Cauchy form, obtaining the natural frequencies is reduced to finding the eigenvalues of the coefficient matrix. There are methods to form the mathematical models in which the derivatives of the state variables make a sub-vector of the vector of unknowns. These are generalized, advanced nodal methods, and an advanced nodal one for mechanical systems. There can be a try for reduction of the mathematical models of objects, obtained by these methods, to the normal Cauchy form. The article discusses a similar procedure for the generalized and advanced nodal methods. As for the extended nodal method for mechanical systems there is specifics the article does not show. For the model obtained by generalized method the vector of unknown variables is permutated so that a sub-vector of the derivatives of the state variables was in
Directory of Open Access Journals (Sweden)
McConville Malcolm J
2007-10-01
Full Text Available Abstract Background Gas chromatography-mass spectrometry (GC-MS is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies. Results A new approach for matching signal peaks based on dynamic programming is presented. The proposed approach relies on both peak retention times and mass spectra. The alignment of more than two peak lists involves three steps: (1 all possible pairs of peak lists are aligned, and similarity of each pair of peak lists is estimated; (2 the guide tree is built based on the similarity between the peak lists; (3 peak lists are progressively aligned starting with the two most similar peak lists, following the guide tree until all peak lists are exhausted. When two or more experiments are performed on different sample states and each consisting of multiple replicates, peak lists within each set of replicate experiments are aligned first (within-state alignment, and subsequently the resulting alignments are aligned themselves (between-state alignment. When more than two sets of replicate experiments are present, the between-state alignment also employs the guide tree. We demonstrate the usefulness of this approach on GC-MS metabolic profiling experiments acquired on wild-type and mutant Leishmania mexicana parasites. Conclusion We propose a progressive method to match signal peaks across multiple GC-MS experiments based on dynamic programming. A sensitive peak similarity function is proposed to balance peak retention time and peak
基于LINGO的优化问题动态规划法求解%Solving Optimization Problem by Dynamic Programming Method Using LINGO
Institute of Scientific and Technical Information of China (English)
度巍; 曾飞
2014-01-01
The paper describes the use of LINGO,pointing outing that LINGO can solve dynamic programming problems with-out the objective function.The shortest path problem and lotsizing problem are solved by dynamic programming method, Cor-responding LINGO codes are provided. The teaching of LINGO enhances the students' understanding of the dynamic program-ming while increasing the ability to use optimization software programming to solve the problem.%介绍了LINGO优化软件的使用，指出LINGO在求解动态规划问题时可以不需要目标函数。基于LINGO分别对最短路问题和生产批量计划问题使用动态规划法进行了求解，给出了相应的LINGO求解代码，增强了学生对动态规划法的理解同时提高了使用优化软件编程解决问题的能力。
Sandner, Raimar; Vukics, András
2014-09-01
++ libraries, GNU Scientific Library, Blitz++, FLENS, NumPy, SciPy Catalogue identifier of previous version: AELU_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183 (2012) 1381 Does the new version supersede the previous version?: Yes Nature of problem: Definition of (open) composite quantum systems out of elementary building blocks [2,3]. Manipulation of such systems, with emphasis on dynamical simulations such as Master-equation evolution [4] and Monte Carlo wave-function simulation [5]. Solution method: Master equation, Monte Carlo wave-function method Reasons for new version: The new version is mainly a feature release, but it does correct some problems of the previous version, especially as regards the build system. Summary of revisions: We give an example for a typical Python script implementing the ring-cavity system presented in Sec. 3.3 of Ref. [2]: Restrictions: Total dimensionality of the system. Master equation-few thousands. Monte Carlo wave-function trajectory-several millions. Unusual features: Because of the heavy use of compile-time algorithms, compilation of programs written in the framework may take a long time and much memory (up to several GBs). Additional comments: The framework is not a program, but provides and implements an application-programming interface for developing simulations in the indicated problem domain. We use several C++11 features which limits the range of supported compilers (g++ 4.7, clang++ 3.1) Documentation, http://cppqed.sourceforge.net/ Running time: Depending on the magnitude of the problem, can vary from a few seconds to weeks. References: [1] Entry point: http://cppqed.sf.net [2] A. Vukics, C++QEDv2: The multi-array concept and compile-time algorithms in the definition of composite quantum systems, Comp. Phys. Comm. 183(2012)1381. [3] A. Vukics, H. Ritsch, C++QED: an object-oriented framework for wave-function simulations of cavity QED systems, Eur. Phys. J. D 44 (2007) 585. [4] H. J. Carmichael, An Open
凹资源配置问题的混合动态规划方法%A Hybrid Dynamic Programming Method for Concave Resource Allocation Problems
Institute of Scientific and Technical Information of China (English)
姜计荣; 孙小玲
2005-01-01
Concave resource allocation problem is an integer programming problem of minimizing a nonincreasing concave function subject to a convex nondecreasing constraint and bounded integer variables. This class of problems are encountered in optimization models involving economies of scale. In this paper, a new hybrid dynamic programming method was proposed for solving concave resource allocation problems. A convex underestimating function was used to approximate the objective function and the resulting convex subproblem was solved with dynamic programming technique after transforming it into a 0-1 linear knapsack problem. To ensure the convergence, monotonicity and domain cut technique was employed to remove certain integer boxes and partition the Reviseddomain into a union of integer boxes. Computational results were given to show the efficiency of the algorithm.
Institute of Scientific and Technical Information of China (English)
Yujie Wei; Yongheng Jiang; Dexian Huang⁎
2014-01-01
This paper introduces a practical solving scheme of gradetransition trajectory optimization (GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymerization, differential/algebraic equations (DAEs) always cause great computational burden and system non-linearity usual y makes GTTO non-convex bearing multiple optima. Therefore, coupled with the three-stage decomposi-tion model, a three-section algorithm of dynamic programming (TSDP) is proposed based on the general iteration mechanism of iterative programming (IDP) and incorporated with adaptivegrid allocation scheme and heuristic modifications. The algorithm iteratively performs dynamic programming with heuristic modifications under constant calculation loads and adaptively allocates the valued computational resources to the regions that can further improve the optimality under the guidance of local error estimates. TSDP is finally compared with IDP and interior point method (IP) to verify its efficiency of computation.
Directory of Open Access Journals (Sweden)
Vidya Subramanian
Full Text Available The histone H2A variant H2A.Z is essential for embryonic development and for proper control of developmental gene expression programs in embryonic stem cells (ESCs. Divergent regions of amino acid sequence of H2A.Z likely determine its functional specialization compared to core histone H2A. For example, H2A.Z contains three divergent residues in the essential C-terminal acidic patch that reside on the surface of the histone octamer as an uninterrupted acidic patch domain; however, we know little about how these residues contribute to chromatin structure and function. Here, we show that the divergent amino acids Gly92, Asp97, and Ser98 in the H2A.Z C-terminal acidic patch (H2A.Z(AP3 are critical for lineage commitment during ESC differentiation. H2A.Z is enriched at most H3K4me3 promoters in ESCs including poised, bivalent promoters that harbor both activating and repressive marks, H3K4me3 and H3K27me3 respectively. We found that while H2A.Z(AP3 interacted with its deposition complex and displayed a highly similar distribution pattern compared to wild-type H2A.Z, its enrichment levels were reduced at target promoters. Further analysis revealed that H2A.Z(AP3 was less tightly associated with chromatin, suggesting that the mutant is more dynamic. Notably, bivalent genes in H2A.Z(AP3 ESCs displayed significant changes in expression compared to active genes. Moreover, bivalent genes in H2A.Z(AP3 ESCs gained H3.3, a variant associated with higher nucleosome turnover, compared to wild-type H2A.Z. We next performed single cell imaging to measure H2A.Z dynamics. We found that H2A.Z(AP3 displayed higher mobility in chromatin compared to wild-type H2A.Z by fluorescent recovery after photobleaching (FRAP. Moreover, ESCs treated with the transcriptional inhibitor flavopiridol resulted in a decrease in the H2A.Z(AP3 mobile fraction and an increase in its occupancy at target genes indicating that the mutant can be properly incorporated into chromatin
Shilovsky, G A; Putyatina, T S; Lysenkov, S N; Ashapkin, V V; Luchkina, O S; Markov, A V; Skulachev, V P
2016-12-01
Accumulation of various types of lesions in the course of aging increases an organism's vulnerability and results in a monotonous elevation of mortality rate, irrespective of the position of a species on the evolutionary tree. Stroustrup et al. (Nature, 530, 103-107) [1] showed in 2016 that in the nematode Caenorhabditis elegans, longevity-altering factors (e.g. oxidative stress, temperature, or diet) do not change the shape of the survival curve, but either stretch or shrink it along the time axis, which the authors attributed to the existence of an "aging program". Modification of the accelerated failure time model by Stroustrup et al. uses temporal scaling as a basic approach for distinguishing between quantitative and qualitative changes in aging dynamics. Thus we analyzed data on the effects of various longevity-increasing genetic manipulations in flies, worms, and mice and used several models to choose a theory that would best fit the experimental results. The possibility to identify the moment of switch from a mortality-governing pathway to some other pathways might be useful for testing geroprotective drugs. In this work, we discuss this and other aspects of temporal scaling.
Walsh, Thomas P; Webber, Caleb; Searle, Stephen; Sturrock, Shane S; Barton, Geoffrey J
2008-07-01
SCANPS performs iterative profile searching similar to PSI-BLAST but with full dynamic programing on each cycle and on-the-fly estimation of significance. This combination gives good sensitivity and selectivity that outperforms PSI-BLAST in domain-searching benchmarks. Although computationally expensive, SCANPS exploits onchip parallelism (MMX and SSE2 instructions on Intel chips) as well as MPI parallelism to give acceptable turnround times even for large databases. A web server developed to run SCANPS searches is now available at http://www.compbio.dundee.ac.uk/www-scanps. The server interface allows a range of different protein sequence databases to be searched including the SCOP database of protein domains. The server provides the user with regularly updated versions of the main protein sequence databases and is backed up by significant computing resources which ensure that searches are performed rapidly. For SCOP searches, the results may be viewed in a new tree-based representation that reflects the structure of the SCOP hierarchy; this aids the user in placing each hit in the context of its SCOP classification and understanding its relationship to other domains in SCOP.
Directory of Open Access Journals (Sweden)
Shaojun Xia, Lingen Chen, Fengrui Sun
2012-01-01
Full Text Available A multistage endoreversible Carnot heat engine system operating with a finite thermal capacity high-temperature black photon fluid reservoir and the heat transfer law is investigated in this paper. Optimal control theory is applied to derive the continuous Hamilton-Jacobi-Bellman (HJB equations, which determine the optimal fluid temperature configurations for maximum power output under the conditions of fixed initial time and fixed initial temperature of the driving fluid. Based on the general optimization results, the analytical solution for the case with pseudo-Newtonian heat transfer law is further obtained. Since there are no analytical solutions for the radiative heat transfer law, the continuous HJB equations are discretized and the dynamic programming (DP algorithm is adopted to obtain the complete numerical solutions, and the relationships among the maximum power output of the system, the process period and the fluid temperatures are discussed in detail. The optimization results obtained for the radiative heat transfer law are also compared with those obtained for pseudo-Newtonian heat transfer law and stage-by-stage optimization strategy. The obtained results can provide some theoretical guidelines for the optimal designs and operations of solar energy conversion and transfer systems.
Cao, Ning; Zhang, Huaguang; Luo, Yanhong; Feng, Dezhi
2012-09-01
In this article, a novel iteration algorithm named two-stage approximate dynamic programming (TSADP) is proposed to seek the solution of nonlinear switched optimal control problem. At each iteration of TSADP, a multivariate optimal control problem is transformed to be a certain number of univariate optimal control problems. It is shown that the value function at each iteration can be characterised pointwisely by a set of smooth functions recursively obtained from TSADP, and the associated control policy, continuous control and switching control law included, is explicitly provided in a state-feedback form. Moreover, the convergence and optimality of TSADP is strictly proven. To implement this algorithm efficiently, neural networks, critic and action networks, are utilised to approximate the value function and continuous control law, respectively. Thus, the value function is expressed by the weights of critic networks pointwise. Besides, redundant weights are ruled out at each iteration to simplify the exponentially increasing computation burden. Finally, a simulation example is provided to demonstrate its effectiveness.
LoMauro, Antonella; Cesareo, Ambra; Agosti, Fiorenza; Tringali, Gabriella; Salvadego, Desy; Grassi, Bruno; Sartorio, Alessandro; Aliverti, Andrea
2016-06-01
The objective of this study was to characterize static and dynamic thoraco-abdominal volumes in obese adolescents and to test the effects of a 3-week multidisciplinary body weight reduction program (MBWRP), entailing an energy-restricted diet, psychological and nutritional counseling, aerobic physical activity, and respiratory muscle endurance training (RMET), on these parameters. Total chest wall (VCW), pulmonary rib cage (VRC,p), abdominal rib cage (VRC,a), and abdominal (VAB) volumes were measured on 11 male adolescents (Tanner stage: 3-5; BMI standard deviation score: >2; age: 15.9 ± 1.3 years; percent body fat: 38.4%) during rest, inspiratory capacity (IC) maneuver, and incremental exercise on a cycle ergometer at baseline and after 3 weeks of MBWRP. At baseline, the progressive increase in tidal volume was achieved by an increase in end-inspiratory VCW (p obese adolescents adopt a thoraco-abdominal operational pattern characterized by abdominal rib cage hyperinflation as a form of lung recruitment during incremental cycle exercise. Additionally, a short period of MBWRP including RMET is associated with improved exercise performance, lung and chest wall volume recruitment, unloading of respiratory muscles, and reduced dyspnea.
Laird, Philip
1992-01-01
We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.
Energy Technology Data Exchange (ETDEWEB)
Bdzil, J.B. [Los Alamos National Lab., NM (United States); Jackson, T.L. [Univ. of Illinois, Urbana, IL (United States). Center for Simulation of Advanced Rockets; Stewart, D.S. [Univ. of Illinois, Urbana, IL (United States). Theoretical and Applied Mechanics
1999-02-02
In the design of explosive systems the generic problem that one must consider is the propagation of a well-developed detonation wave sweeping through an explosive charge with a complex shape. At a given instant of time the lead detonation shock is a surface that occupies a region of the explosive and has a dimension that is characteristic of the explosive device, typically on the scale of meters. The detonation shock is powered by a detonation reaction zone, sitting immediately behind the shock, which is on the scale of 1 millimeter or less. Thus, the ratio of the reaction zone thickness to the device dimension is of the order of 1/1,000 or less. This scale disparity can lead to great difficulties in computing three-dimensional detonation dynamics. An attack on the dilemma for the computation of detonation systems has lead to the invention of sub-scale models for a propagating detonation front that they refer to herein as program burn models. The program burn model seeks not to resolve the fine scale of the reaction zone in the sense of a DNS simulation. The goal of a program burn simulation is to resolve the hydrodynamics in the inert product gases on a grid much coarser than that required to resolve a physical reaction zone. The authors first show that traditional program burn algorithms for detonation hydrocodes used for explosive design are inconsistent and yield incorrect shock dynamic behavior. To overcome these inconsistencies, they are developing a new class of program burn models based on detonation shock dynamic (DSD) theory. It is hoped that this new class will yield a consistent and robust algorithm which reflects the correct shock dynamic behavior.
Secure Dynamic Program Repartitioning
DEFF Research Database (Denmark)
Hansen, Rene Rydhoff; Probst, Christian
2005-01-01
, but the partitioning compiler becomes a part of the network and can recompile applications, thus alowing hosts to enter or leave the framework. We contend that this setting is superior to static partitioning, since it allows redistribution of data and computations. This is especialy beneficial if the new host alows...
Directory of Open Access Journals (Sweden)
Baier Herwig
2009-06-01
reveal an unexpected role for NSF in hypothalamic development, with mutant 5 days post-fertilization larvae exhibiting a stage-dependent loss of neuroendocrine transcripts and a corresponding accumulation of neuropeptides in the soma. Based on our collective findings, we speculate that neuroendocrine transcriptional programs adapt dynamically to both the supply and demand for neuropeptides to ensure adequate homeostatic responses.
Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Engelund Holm, Peter; Trapp, Stefan; Rosbjerg, Dan; Bauer-Gottwein, Peter
2015-04-01
Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen concentrations. Inelastic water demands, fixed water allocation curtailment costs and fixed wastewater treatment costs (before and after use) are estimated for the water users (agriculture, industry and domestic). If the BOD concentration exceeds a given user pollution thresh-old, the user will need to pay for pre-treatment of the water before use. Similarly, treatment of the return flow can reduce the BOD load to the river. A traditional SDP approach is used to solve one-step-ahead sub-problems for all combinations of discrete reservoir storage, Markov Chain inflow clas-ses and monthly time steps. Pollution concentration nodes are introduced for each user group and untreated return flow from the users contribute to increased BOD concentrations in the river. The pollutant concentrations in each node depend on multiple decision variables (allocation and wastewater treatment) rendering the objective function non-linear. Therefore, the pollution concen-tration decisions are outsourced to a genetic algorithm, which calls a linear program to determine the remainder of the decision
Airoldi, Edoardo M; Miller, Darach; Athanasiadou, Rodoniki; Brandt, Nathan; Abdul-Rahman, Farah; Neymotin, Benjamin; Hashimoto, Tatsu; Bahmani, Tayebeh; Gresham, David
2016-04-15
Cell growth rate is regulated in response to the abundance and molecular form of essential nutrients. InSaccharomyces cerevisiae(budding yeast), the molecular form of environmental nitrogen is a major determinant of cell growth rate, supporting growth rates that vary at least threefold. Transcriptional control of nitrogen use is mediated in large part by nitrogen catabolite repression (NCR), which results in the repression of specific transcripts in the presence of a preferred nitrogen source that supports a fast growth rate, such as glutamine, that are otherwise expressed in the presence of a nonpreferred nitrogen source, such as proline, which supports a slower growth rate. Differential expression of the NCR regulon and additional nitrogen-responsive genes results in >500 transcripts that are differentially expressed in cells growing in the presence of different nitrogen sources in batch cultures. Here we find that in growth rate-controlled cultures using nitrogen-limited chemostats, gene expression programs are strikingly similar regardless of nitrogen source. NCR expression is derepressed in all nitrogen-limiting chemostat conditions regardless of nitrogen source, and in these conditions, only 34 transcripts exhibit nitrogen source-specific differential gene expression. Addition of either the preferred nitrogen source, glutamine, or the nonpreferred nitrogen source, proline, to cells growing in nitrogen-limited chemostats results in rapid, dose-dependent repression of the NCR regulon. Using a novel means of computational normalization to compare global gene expression programs in steady-state and dynamic conditions, we find evidence that the addition of nitrogen to nitrogen-limited cells results in the transient overproduction of transcripts required for protein translation. Simultaneously, we find that that accelerated mRNA degradation underlies the rapid clearing of a subset of transcripts, which is most pronounced for the highly expressed NCR
Energy Technology Data Exchange (ETDEWEB)
Muench, T.J.; Wooders, M.H.; McLean, R.
1976-08-01
Two models are developed that can estimate derived fuel demands in single-family dwellings, given fixed final demand for space heat by states. One is an extension of a single-period linear programming model of the nation's energy system, the Brookhaven Energy System Optimization Model. In it the demand for single-family space heat is disaggregated by state and type of home-heating system. The other is a multiple-period dynamic programming model of single-family space heat demand, also disaggregated by state and type of system. Preliminary results for each model are presented and compared.
Zhang, Liangxia; Cao, Wei; Fan, Jiangwen
2016-09-01
To mitigate impacts of sandstorms on northern China, the Chinese government launched the Beijing-Tianjin Sand Source Control Program (BTSSCP) in 2000. The associated practices (i.e., cultivation, enclosure, and aerial seeding) were expected to greatly enhance grassland carbon sequestration. However, the BTSSCP-induced soil organic carbon (SOC) dynamics remain elusive at a regional level. Using the Xilingol League in Inner Mongolia for a case study, we examined the impacts from 2000 to 2006 of the BTSSCP on SOC stocks using the IPCC carbon budget inventory method. Results indicated that over all practices SOC storage increased by 1.7%, but there were large differences between practices. SOC increased most rapidly at the rate of 0.3 Mg C•ha-1•yr-1 under cultivation, but decreased significantly under aerial seeding with moderate or heavy grazing (0.3 vs.0.6 Mg C•ha-1•yr-1). SOC increases varied slightly for grassland types, ranging from 0.10 Mg C•ha-1•yr-1 for temperate desert steppe to 0.16 Mg C•ha-1•yr-1 for temperate meadow steppe and lowland meadow. The overall economic benefits of the SOC sink were estimated to be 4.0 million CNY. Aerial seeding with no grazing was found to be the most cost-effective practice. Finally, we indicated that at least 55.5 years (shortest for cultivation) were needed for the grasslands to reach their potential carbon stocks. Our findings highlight the importance and effectiveness of BTSSCP in promoting terrestrial carbon sequestration which may help mitigate climate change, and further stress the need for more attention to the effectiveness of specific practices.
Akkus, Zeynettin; Hoogi, Assaf; Renaud, Guillaume; ten Kate, Gerrit L.; van den Oord, Stijn C. H.; Schinkel, Arend F. L.; de Jong, Nico; van der Steen, Antonius F. W.; Bosch, Johan G.
2012-03-01
Intraplaque neovascularization (IPN) has been linked with progressive atherosclerotic disease and plaque instability in several studies. Quantification of IPN may allow early detection of vulnerable plaques. A dedicated motion compensation method with normalized-cross-correlation (NCC) block matching combined with multidimensional (2D+time) dynamic programming (MDP) was developed for quantification of IPN in small plaques (images of carotid arteries were acquired by a Philips iU22 system with a L9-3 linear array probe. The motion pattern for the plaque region was obtained from the Bmode images with MDP. MDP results were evaluated in-vitro by a phantom and in-vivo by comparing to manual tracking of three experts for multibeat-image-sequences (MIS) of 11 plaques. In the in-vivo images, the absolute error was 72+/-55μm (mean+/-SD) for X (longitudinal) and 34+/-23μm for Y (radial). The method's success rate was visually assessed on 67 MIS. The tracking was considered failed if it deviated >2 pixels (~200μm) from true motion in any frame. Tracking was scored as fully successful in 63 MIS (94%) for MDP vs. 52(78%) for FT. The range of displacement over these 63 was 1045+/-471μm (X) and 395+/-216μm (Y). The tracking sporadically failed in 4 MIS (6%) due to poor image quality, jugular vein proximity and out-of-plane motion. Motion compensation showed improved lumen-plaque contrast separation. In conclusion, the proposed method is sufficiently accurate and successful for in vivo application.
Zhang, Hengzhong; Rustad, James R; Banfield, Jillian F
2007-06-14
We have investigated the bonding of water molecules to the surfaces of ZnS nanoparticles (approximately 2-3 nm sphalerite) using temperature-programmed desorption (TPD). The activation energy for water desorption was derived as a function of the surface coverage through kinetic modeling of the experimental TPD curves. The binding energy of water equals the activation energy of desorption if it is assumed that the activation energy for adsorption is nearly zero. Molecular dynamics (MD) simulations of water adsorption on 3 and 5 nm sphalerite nanoparticles provided insights into the adsorption process and water binding at the atomic level. Water binds with the ZnS nanoparticle surface mainly via formation of Zn-O bonds. As compared with bulk ZnS crystals, ZnS nanoparticles can adsorb more water molecules per unit surface area due to the greatly increased curvature, which increases the distance between adjacent adsorbed molecules. Results from both TPD and MD show that the water binding energy increases with decreasing the water surface coverage. We attribute the increase in binding energy with decreasing surface water coverage to the increasing degree of surface under-coordination as removal of water molecules proceeds. MD also suggests that the water binding energy increases with decreasing particle size due to the further distance and hence lower interaction between adsorbed water molecules on highly curved smaller particle surfaces. Results also show that the binding energy, and thus the strength of interaction of water, is highest in isolated nanoparticles, lower in nanoparticle aggregates, and lowest in bulk crystals. Given that water binding is driven by surface energy reduction, we attribute the decreased binding energy for aggregated as compared to isolated particles to the decrease in surface energy that occurs as the result of inter-particle interactions.
Directory of Open Access Journals (Sweden)
Mahmoud Mohammadghasemi
2016-06-01
Full Text Available I n this study, water management allocated to the agricultural sector’was analyzed using stochastic dynamic programming under uncertainty conditions. The technical coefficients used in the study referred to the agricultural years, 2013-2014. They were obtained through the use of simple random sampling of 250 farmers in the region for crops wheat, barley, melon, watermelon and ruby grapes under the scenarios of drought, wet, normal, and water required in the most sensitive growth stages. Production function and profit function were obtained from the yield-water-product function of crops using Eviews software. Expected net profit of the system and optimal allocation of water were also calculated based on the GAMS economic analysis software. The results revealed that 14% of the cases over the past 30 years had wet years (high, 47% of the time and that 39% had experienced drought (low and normal (average years. In the best case, i.e. with high current levels, respectively at, 58, 67, 54, and 48% of water requirements for these crops and, in the worst case (with low current levels, 47, 35, 49, 53 and 48% of the water requirements provided during the most sensitive growth stages. Moreover, the results showed that the cultivation of the ruby grape was the best product with the highest expected profit in normal and rainfall conditions. In general, when the expected value of net profit is positive, managers would act optimistically and they would promise the optimal level of water provided to the farmers. Conversely, when the net value is negative they would prefer to be more conservative and would promise a lesser amount of water provided to the farmers. Hence, if the promised water to the farmer is not wasted, he will choose the loss incurred from a lesser harvest.
Energy Technology Data Exchange (ETDEWEB)
Edo, S.; Kenmoku, Y.; Sakakibara, T. [Toyohashi University of Technology, Aichi (Japan); Nakagawa, S. [Maizuru College of Technology, Kyoto (Japan); Kawamoto, T. [Shizuoka University, Shizuoka (Japan)
1997-11-25
With regard to utilization of a solar/electric hot-water system, a discussion was given by using a dynamic programming method on operation of a system which minimizes power charge. The discussed system is an installation in a welfare facility accommodating 100 persons, where solar heat is stored in a heat storage tank from a heat collector, and utilized for hot water supply. If the solar heat is insufficient for required hot water quantity, the water is heated by using an electric heater. The discussion compared the system operation using the dynamic programming method with the following two systems: the operation method 1, which does not utilize insolation forecast and the operation method 2, in which insolation forecast is utilized and late-night electric power is utilized for heating water in shortage. As a result of the calculation, the operation using the dynamic programming method conducts heat storage by utilizing the late-night power even if insolation is sufficient in winter in order to suppress heating by utilizing late-night power for days with less insolation. Thus, suppression is given on excessive utilization of day-time power and on rise in annual maximum power demand. It was found that the present system reduces power consumption by 37.7% when compared with the operation method 1, and 22.7% when compared even with the operation method 2. 3 refs., 5 figs., 3 tabs.
Shorikov, A. F.
2016-12-01
This article discusses the discrete-time dynamical system consisting from two controlled objects and described by a linear recurrent vector equations in the presence of uncertain perturbations. This dynamical system has two levels of a control: dominant level (the first level or the level I) and subordinate level (the second level or the level II) and both have different linear terminal criterions of functioning and united a priori by determined information and control connections. It is assumed that the sets constraining all a priori undefined parameters are known and they are a finite sets or convex, closed and bounded polyhedrons in the corresponding finite-dimensional vector spaces. For the dynamical system in question, we propose a mathematical formalization in the form of solving two-level hierarchical minimax program control problem with incomplete information. In this article for solving of the investigated problem is proposed the algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems. The results obtained in this article can be used for computer simulation of an actual dynamical processes and for designing controlling and navigation systems.
Molnia, B. F.; Friesen, B.; Wilson, E.; Noble, S.
2015-12-01
On July 15, 2009, the National Academy of Sciences (NAS) released a report, Scientific Value of Arctic Sea Ice Imagery Derived Products, advocating public release of Arctic images derived from classified data. In the NAS press release that announced the release, report lead Stephanie Pfirman states "To prepare for a possibly ice-free Arctic and its subsequent effects on the environment, economy, and national security, it is critical to have accurate projections of changes over the next several decades." In the same release NAS President Ralph Cicerone states "We hope that these images are the first of many that could help scientists learn how the changing climate could impact the environment and our society." The same day, Secretary of the Interior Ken Salazar announced that the requested images had been released and were available to the public on a US Geological Survey Global Fiducials Program (GFP) Library website (http://gfl.usgs.gov). The website was developed by the USGS to provide public access to the images and to support environmental analysis of global climate-related science. In the statement describing the release titled, Information Derived from Classified Materials Will Aid Understanding of Changing Climate, Secretary Salazar states "We need the best data from all places if we are to meet the challenges that rising carbon emissions are creating. This information will be invaluable to scientists, researchers, and the public as we tackle climate change." Initially about 700 Arctic sea ice images were released. Six years later, the number exceeds 1,500. The GFP continues to facilitate the acquisition of new Arctic sea ice imagery from US National Imagery Systems. This example demonstrates how information about dynamically changing Arctic sea ice continues to be effectively communicated to the public by the GFP. In addition to Arctic sea ice imagery, the GFP has publicly released imagery time series of more than 125 other environmentally important
Institute of Scientific and Technical Information of China (English)
张洪武; 张新伟
2002-01-01
The objective of the paper is to develop a new algorithm for numericalsolution of dynamic elastic-plastic strain hardening/softening problems. The gradientdependent model is adopted in the numerical model to overcome the result mesh-sensitivity problem in the dynamic strain softening or strain localization analysis.The equations for the dynamic elastic-plastic problems are derived in terms of theparametric variational principle, which is valid for associated, non-associated andstrain softening plastic constitutive models in the finite element analysis. The preciseintegration method, which has been widely used for discretization in time domain ofthe linear problems, is introduced for the solution of dynamic nonlinear equations.The new algorithm proposed is based on the combination of the parametric quadraticprogramming method and the precise integration method and has all the advantagesin both of the algorithms. Results of numerical examples demonstrate not only thevalidity, but also the advantages of the algorithm proposed for the numerical solutionof nonlinear dynamic problems.
MPI程序的Petri网模型及其动态性质%MPI Programs' Petri Net Model and Its Dynamic Properties
Institute of Scientific and Technical Information of China (English)
崔焕庆; 吴哲辉
2006-01-01
对并行程序进行验证以保证正确性是很重要的,但是由于并行程序比串行程序要复杂得多,因此有必要建立它们的模型.MPI是目前应用最广泛的基于消息传递的并行程序编程标准之一.基于MPI程序的特点,提出了MPI并行程序的Petri网模型--MPINet,给出了MPI函数的基本Petri网模型及对程序建模的基本步骤.定义了静态可执行的和并行正确的并行程序,并研究了MPINet的动态性质,包括安全性、可达性、可逆性以及活性.这些方法可以用于其他并行编程标准的分析.%It is very important to verify parallel programs to assure the correctness, but they are more complicated than the sequential ones, so it is necessary to model the program. MPI is one of the most popular standards used to program parallel applications based on message passing. Based on characteristics of MPI program, the Petri net model of MPI parallel program--MPINet was presented, and the basic Petri net models of MPI functions and basic steps to build the program's model were given. The concepts of statically executable and concurrent correct parallel program were discussed, and dynamic properties including safeness, reachability, reversibility and liveness were studied. All these methods can easily be used to the other parallel programming standards.
National Center on Performance Incentives, 2009
2009-01-01
A recent report published by the National Center on Performance Incentives (NCPI) presents findings from the second-year evaluation of the Texas Educator Excellence Grant (TEEG) program, a statewide educator incentive program that operated in Texas. As part of this larger study, evaluators administered a survey to educators to learn about their…
Waiboer, Robert Rens
2007-01-01
Robotised laser welding is an innovative joining technique which is increasingly finding applications, especially in the automotive industry. In order to reduce the time needed to prepare and programthe laser welding robot, off-line programming systems are used. The off-line programming systems curr
Sandrey, Michelle A; Mitzel, Jonathan G
2013-11-01
Core training specifically for track and field athletes is vague, and it is not clear how it affects dynamic balance and core-endurance measures. To determine the effects of a 6-week core-stabilization-training program for high school track and field athletes on dynamic balance and core endurance. Test-retest. High school in north central West Virginia. Thirteen healthy high school student athletes from 1 track and field team volunteered for the study. Subjects completed pretesting 1 wk before data collection. They completed a 6-wk core-stabilization program designed specifically for track and field athletes. The program consisted of 3 levels with 6 exercises per level and lasted for 30 min each session 3 times per week. Subjects progressed to the next level at 2-wk intervals. After 6 wk, posttesting was conducted The subjects were evaluated using the Star Excursion Balance Test (SEBT) for posteromedial (PM), medial (M), and anteromedial (AM) directions; abdominal-fatigue test (AFT); back-extensor test (BET); and side-bridge test (SBT) for the right and left sides. Posttest results significantly improved for all 3 directions of the SEBT (PM, M, and AM), AFT, BET, right SBT, and left SBT. Effect size was large for all variables except for PM and AM, where a moderate effect was noted. Minimal-detectable-change scores exceeded the error of the measurements for all dependent variables. After the 6-wk core-stabilization-training program, measures of the SEBT, AFT, BET, and SBT improved, thus advocating the use of this core-stabilization-training program for track and field athletes.
Bergstra, J.A.; Bethke, I.
2002-01-01
Molecular dynamics is a model for the structure and meaning of object based programming systems. In molecular dynamics the memory state of a system is modeled as a fluid consisting of a collection of molecules. Each molecule is a collection of atoms with bindings between them. A computation is model
Kalantari, A S; Cabrera, V E
2012-10-01
The objective of this study was to determine the effect of reproductive performance on dairy cattle herd value. Herd value was defined as the herd's average retention payoff (RPO). Individual cow RPO is the expected profit from keeping the cow compared with immediate replacement. First, a daily dynamic programming model was developed to calculate the RPO of all cow states in a herd. Second, a daily Markov chain model was applied to estimate the herd demographics. Finally, the herd value was calculated by aggregating the RPO of all cows in the herd. Cow states were described by 5 milk yield classes (76, 88, 100, 112, and 124% with respect to the average), 9 lactations, 750 d in milk, and 282 d in pregnancy. Five different reproductive programs were studied (RP1 to RP5). Reproductive program 1 used 100% timed artificial insemination (TAI; 42% conception rate for first TAI and 30% for second and later services) and the other programs combined TAI with estrus detection. The proportion of cows receiving artificial insemination after estrus detection ranged from 30 to 80%, and conception rate ranged from 25 to 35%. These 5 reproductive programs were categorized according to their 21-d pregnancy rate (21-d PR), which is an indication of the rate that eligible cows become pregnant every 21 d. The 21-d PR was 17% for RP1, 14% for RP2, 16% for RP3, 18% for RP4, and 20% for RP5. Results showed a positive relationship between 21-d PR and herd value. The most extreme herd value difference between 2 reproductive programs was $77/cow per yr for average milk yield (RP5 - RP2), $13/cow per yr for lowest milk yield (RP5 - RP1), and $160/cow per yr for highest milk yield (RP5 - RP2). Reproductive programs were ranked based on their calculated herd value. With the exception of the best reproductive program (RP5), all other programs showed some level of ranking change according to milk yield. The most dramatic ranking change was observed in RP1, which moved from being the worst ranked
Hutt, Kimberley; Redding, Emma
2014-03-01
Visual conditions for a dancer vary greatly between theatrical performance environments and dance studios, and this variability may be detrimental to their dynamic balance performance, particularly under stage lighting. In order to maintain balance control, dancers reportedly rely heavily on visual input, yet those who rely more on proprioceptive strategies for balancing have been found to be more stable. The purpose of this study was to assess the capability of an eyes-closed, dance-specific training program to nurture in dancers proprioceptive mechanisms that may facilitate their dynamic balance control. Eighteen elite pre-professional ballet dancers were randomly assigned to either a control (eyes open) or experimental (eyes closed) group for the intervention. The balance abilities of all subjects were tested using five dance-specific variations of the Star Excursion Balance Test before and after a 4 week balance intervention. Reach distance and time to complete the tests were recorded separately as indirect measurements of dynamic balance. The intervention consisted of dance-specific, eyes-closed exercises integrated into the dancers' daily ballet class and designed progressively to challenge the dancers' balance. During the intervention period, the control group undertook the same exercise program with their eyes open. Results revealed significant improvements in time to complete the three "timed" balance tests, and distances reached significantly improved in one of the two "reach" balance tests. No significant improvements were observed in the control group for any variation of the tests. These results indicate that dancers can be trained to adopt proprioceptive strategies to maintain dynamic balance, which consequently improves their balance performance. Such findings could encourage use of eyes-closed training in daily dance classes due to its potential to improve dancers' balance control.
SMDP基于性能势的神经元动态规划%Performance Potential-based Neuro-dynamic Programming for SMDPs
Institute of Scientific and Technical Information of China (English)
唐昊; 袁继彬; 陆阳; 程文娟
2005-01-01
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimization of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamic programming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performance error bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, a numerical example is provided.
Energy Technology Data Exchange (ETDEWEB)
Ohhira, Mitsuru (Power Reactor and Nuclear Fuel Development Corp., Tokyo (Japan))
1990-12-01
Private buildings applied base isolation system, are on the practical stage now. So, under Construction and Maintenance Management Office, we are doing an application study of base isolation system to nuclear fuel facilities. On the process of this study, we have developed Dynamic Analysis Program-Base Isolation System (DAP-BS) which is able to run a 32-bit personal computer. Using this program, we can analyze a 3-dimensional structure, and evaluate the various properties of base isolation parts that are divided into maximum 16 blocks. And from the results of some simulation analyses, we thought that DAP-BS had good reliability and marketability. So, we put DAP-BS on the market. (author).
Energy Technology Data Exchange (ETDEWEB)
Dey, M.K. [Nuclear Regulatory Commission, Washington, DC (United States). Office of Nuclear Regulatory Research
1999-09-01
This paper proposes a conceptual framework for developing a fire protection program at nuclear power plants based on probabilistic risk analysis (PRA) of fire hazards, and modeling the dynamics of fire effects. The process for categorizing nuclear power plant fire areas based on risk is described, followed by a discussion of fire safety design methods that can be used for different areas of the plant, depending on the degree of threat to plant safety from the fire hazard. This alternative framework has the potential to make programs more cost-effective, and comprehensive, since it will allow a more systematic and broader examination of fire risk, and provide a means to distinguish between high and low risk fire contributors. (orig.)
DEFF Research Database (Denmark)
Krommes, Kasper; Bandholm, Thomas; Jakobsen, Markus D
2017-01-01
BACKGROUND: Training intensity is an important variable in strength training and above 80% of one repetition maximum is recommended for promoting strength for athletes. Four dynamic and two isometric on-field exercises are included in the Hölmich groin-injury prevention study that initially failed...... to show a reduction in groin injuries in soccer players. It has been speculated that exercise-intensity in this groin-injury prevention program was too low to induce the strength gains necessary to protect against groin-related injuries. PURPOSE: To estimate the intensity of the six exercises from...... in the Hölmich groin injury prevention program, except cross-county skiing, is sufficient to be considered strength-training for specific muscle groups in and around the groin region. LEVEL OF EVIDENCE: 3....
Energy Technology Data Exchange (ETDEWEB)
Veiga-Lopez, A.; Beckett, E.M.; Abi Salloum, B. [Department of Pediatrics, University of Michigan, Ann Arbor, MI (United States); Ye, W. [Department of Biostatistics, University of Michigan, Ann Arbor, MI (United States); Padmanabhan, V., E-mail: vasantha@umich.edu [Department of Pediatrics, University of Michigan, Ann Arbor, MI (United States); The Reproductive Sciences Program, University of Michigan, Ann Arbor, MI (United States)
2014-09-01
Developmental exposure to BPA adversely affects reproductive function. In sheep, prenatal BPA treatment induces reproductive neuroendocrine defects, manifested as LH excess and dampened LH surge and perturbs early ovarian gene expression. In this study we hypothesized that prenatal BPA treatment will also disrupt ovarian follicular dynamics. Pregnant sheep were treated from days 30 to 90 of gestation with 3 different BPA doses (0.05, 0.5, or 5 mg/kg BW/day). All female offspring were estrus synchronized and transrectal ultrasonography was performed daily for 22 days to monitor ovarian follicular and corpora lutea dynamics. Blood samples were collected to assess preovulatory hormonal changes and luteal progesterone dynamics. Statistical analysis revealed that the time interval between the estradiol rise and the preovulatory LH surge was shortened in the BPA-treated females. None of the three BPA doses had an effect on corpora lutea, progestogenic cycles, and mean number or duration of ovulatory and non-ovulatory follicles. However, differences in follicular count trajectories were evident in all three follicular size classes (2–3 mm, 4–5 mm, and ≥ 6 mm) of prenatal BPA-treated animals compared to controls. Number of follicular waves tended also to be more variable in the prenatal BPA-treated groups ranging from 2 to 5 follicular waves per cycle, while this was restricted to 3 to 4 waves in control females. These changes in ovarian follicular dynamics coupled with defects in time interval between estradiol rise and preovulatory LH release are likely to lead to subfertility in prenatal BPA-treated females. - Highlights: • Prenatal BPA shortens interval between estradiol rise and preovulatory LH surge. • Prenatal BPA affects follicular count trajectory and follicular wave occurrence. • Prenatal BPA does not affect ovulatory rate and progesterone dynamics.
基于动态规划算法的云任务分配策略%Cloud task allocation strategy based on dynamic programming algorithm
Institute of Scientific and Technical Information of China (English)
赵立慧; 李美安; 王蒙
2013-01-01
针对已有的基于蚁群算法的任务分配策略资源利用率低、算法时间复杂度高、任务分配效率低的问题,提出一种基于动态规划算法的任务分配策略.该算法利用动态规划的思想将等待执行任务均分后动态分配给不同节点,在迭代计算后得到任务分配最优方案,保证任务完成时间为全局最短完成时间,从而提高资源利用率,降低时间复杂度,减少时间的耗费.通过理论分析和Cloudsim仿真实验证明基于动态规划算法的云任务分配时间复杂度低,任务完成时间短,能够提高任务分配效率.%The existing task allocation strategy based on ant colony algorithm has many problems like low resource utilizaton rate,high algorithm time complexity and low efficiency of the allocation of tasks.The authors put forward a task allocation strategy based on dynamic programming algorithm.The algorithm applied dynamic programming ideas and divided the waiting task into average parts then distributed them to different nodes dynamically,the optimal plan for task allocation obtained after the iterative calculation,ensuring the task completion time be the shortest one,so as to improve resource utilization rate,and reduce the time complexity.The theoretical analysis and Cloudsim simulation results prove that the time complexity of the cloud task allocation based on dynamic programming algorithm is low and the task completion time is short.The results show that this method can improve the efficiency of the allocation of tasks.
Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.
2015-08-01
The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.
Lewis, Sandra; And Others
1985-01-01
Sixteen hearing-impaired children, aged 6 to 10 years, participated in a six-week posture and body awareness activity program. Pre- and posttests showed that the balance of the experimental group Ss improved, whereas the balance of the control group Ss did not improve. (Author/CL)
Daniluk, Andrzej
2011-06-01
problems of this type, the computational and threading layers of the project have been implemented in the form of one design pattern as a part of Model-View-Controller architecture. Reasons for new version: Responding to the users' feedback the Growth09 project has been upgraded to a standard that allows the carrying out of sample computations of the RHEED intensities for a disordered surface for a wide range of single- and epitaxial hetero-structures. The design pattern on which the project is based has also been improved. It is shown that this model can be effectively used for multithreaded growth simulations of thin epitaxial layers and corresponding RHEED intensities for a wide range of single- and hetero-structures. Responding to the users' feedback the present release has been implemented using a well-documented free compiler [1] not requiring the special configuration and installation additional libraries. Summary of revisions: The logical structure of the Growth09 program has been modified according to the scheme showed in Fig. 1. The class diagram in Fig. 1 is a static view of the main platform-specific elements of the GrowthCP architecture. Fig. 2 provides a dynamic view by showing the creation and destruction simplistic sequence diagram for the process. The program requires the user to provide the appropriate parameters in the form of a knowledge base for the crystal structures under investigation. These parameters are loaded from the parameters. ini files at run-time. Instructions to prepare the .ini files can be found in the new distribution. The program enables carrying out different growth models and one-dimensional dynamical RHEED calculations for the fcc lattice with basis of three-atoms, fcc lattice with basis of two-atoms, fcc lattice with single atom basis, Zinc-Blende, Sodium Chloride, and Wurtzite crystalline structures and hetero-structures, but yet the Fourier component of the scattering potential in the TRHEEDCalculations.crystPotUgXXX() procedure
Van der Borght, Stefaan F; Schim van der Loeff, Maarten F; Clevenbergh, Philippe; Kabarega, Jean Pierre; Kamo, Emmanuel; van Cranenburgh, Katinka; Rijckborst, Henk; Lange, Joep M; Rinke de Wit, Tobias F
2010-02-01
High uptake of HIV voluntary counseling and testing (VCT) services is important for the success of HIV workplace programs in sub-Saharan Africa. From 2001 onwards, Heineken, a multinational brewing company, implemented a comprehensive HIV prevention and treatment program for employees and their dependents of its African subsidiaries. Confidential in-house VCT is part of this program. VCT uptake dynamics over time, and factors associated with early uptake were studied. Between September 2001 and December 2007, 9723 adult beneficiaries were tested for HIV in 14 company sites in five African countries. Three hundred and seventy (3.8%) of tested persons were infected with HIV-1. During the first 12 months 1412 tests were done, compared to 8311 tests in the subsequent years. The annual average uptake of testing among eligible persons varied between 15 and 32%. The coverage was higher among female compared to male employees, and higher among female compared to male spouses. Distinct peaks in uptake were linked to specific local events. HIV-1 infected persons were significantly more likely to be tested in the early period. The proportion of HIV-1 infected persons among testees was 8.8% in the first 12 months compared to 3.0% in the subsequent period (p<0.001). HIV-1 infected persons diagnosed in the early period were in a more advanced clinical stage, and had a significantly lower CD4 count than those tested later (median CD4 count 227 vs. 314 cells/microl; p=0.002). In this workplace program, HIV-1 infected individuals came earlier for an HIV test than uninfected people, and people with advanced infection came earlier than those with less advanced disease. Employees' spouses are harder to reach than employees and extra efforts should be undertaken to reach them as well. Uptake of HIV testing can be actively influenced by educational or promotional activities.
Curriculum Development of Learning Field of .NET Dynamic Website Programming%《.NET动态网站编程》学习领域课程开发
Institute of Scientific and Technical Information of China (English)
李萍
2013-01-01
该文基于对工作过程的学习领域课程开发的理论研究，以软件开发工作流程分析为依据，对《.NET动态网站编程》学习领域课程进行工作过程系统化的教学设计，改革教学方法和考核方式，取得了较好的教学效果。%Based on the theoretical research on curriculum development of learning field and the working process of software de?velopment, this paper describes the teaching design about learning field curriculum of .NET dynamic website programming. Then through reforming teaching method and examination method, we have obtained the good teaching effect.
Imai, H.
2009-08-01
Our Japanese astronomical community is proposing the VSOP-2 key science programs (KSPs) for study of the dynamics of the Milky Way Galaxy (MWG) on the basis of high precision astrometry of h2o maser sources. High angular resolution of VSOP-2 is expected to simultaneously perform 10 micro-arcsecond (μas) level astrometry, which enables the determination of annual parallaxes and secular motions of the maser sources. The proposed KSPs cover the whole scale of the MWG in both the northern or southern hemispheres, except for the Galactic center region. In the southern hemisphere, in particular, ASTRO-G's orbit should provide a great opportunity for obtaining good image quality and astrometric accuracy with a relatively small number of ground-based telescopes. h2o maser sources located behind the Galactic center and in the Large and Small Magellanic Clouds are expected to be the main target sources for the proposed KSPs.
Firm entry and aggregate efficiency growth: An optimal dynamic - Program of entry and R&D investment
Directory of Open Access Journals (Sweden)
Asma Raies
2013-12-01
Full Text Available The effect of entry on the aggregate efficiency growth is still theoretically and empirically unresolved. Many studies focused on this effect in short and long-run, without considering the dynamic transition and how do entry affect the convergence of the industrytoward its long-run equilibrium? This paper aims to provide an answer and to fill this gap by employingoptimal control principles. Our model exhibits saddlepath stability and shows that the effect of entry and entry liberalizing policy (reducing the entry cost on the aggregate efficiency growth may be positive, negative or nil depending on the industry’s initial characteristics (size and R&D. This theoretical result can justify the inconclusive current empirical evidence.
Chen, Mohan; Xia, Junchao; Huang, Chen; Dieterich, Johannes M.; Hung, Linda; Shin, Ilgyou; Carter, Emily A.
2015-05-01
Orbital-free density functional theory (OFDFT) is a linear-scaling first-principles quantum mechanics method used to calculate the ground-state energy of a given system. Here we present a new version of PRinceton Orbital-Free Electronic Structure Software (PROFESS) with new features. First, PROFESS 3.0 provides a set of new kinetic energy density functionals (KEDFs) which are designed to model semiconductors or transition metals. Specifically, PROFESS 3.0 includes the Huang-Carter (HC) KEDF [1], a density decomposition method with fixed localized electronic density [2], the Wang-Govind-Carter (WGC) decomposition KEDF [3], and the Enhanced von Weizsäcker (EvW)-WGC KEDF [4]. Other major new functions are included, such as molecular dynamics with different statistical mechanical ensembles and spin-polarized density optimizers.
利用CPDH和动态规划算法的形状检索%Shape retrieval based on CPDH and dynamic programming algorithm
Institute of Scientific and Technical Information of China (English)
束鑫; 吴小俊; 潘磊
2011-01-01
用形状轮廓上点的坐标位置相对于形状重心位置的分布关系描述形状,提出一种极坐标下形状轮廓点分布直方图描述符(contour points distribution histogram),该描述符不仅符合人眼的视觉直观感受、计算简单,而且其本质上具有缩放和平移不变性.用动态规划算法(dynamic programming algorithm)来度量轮廓点分布直方图之间的距离,部分解决了轮廓点分布直方图对于旋转不变性的要求.在多个形状图像数据库中的实验结果表明,该方法在单目标封闭轮廓的形状图像检索中取得了良好效果.%Using the distribution relations between the coordinates of the points on shape contour and the centroid of the shape to describe a shape, a novel shape descriptor CPDH (contour points distribution histogram) is proposed under polar coordinate.This descriptor not only satisfies the human' s visual perception and easy to be calculated, but also it essentially has the properties of invariant to scaling and translation.We also suggest using the Dynamic Programming Algorithm to measure the distance between CPDHs, and that the DP algorithm can partly solve the need of the CPDH' s invariant to rotation.With a great deal of experiments in several shape databases, it is shown that this algorithm, used in image retrieval of shape with a single closed contour, can get favorable results.
Dynamic Logic with Trace Semantics
Beckert, Bernhard; Bruns, Daniel
2013-01-01
Dynamic logic is an established instrument for program verification and for reasoning about the semantics of programs and programming languages. In this paper, we define an extension of dynamic logic, called Dynamic Trace Logic (DTL), which combines the expressiveness of program logics such as dynamic logic with that of temporal logic. And we present a sound and relatively complete sequent calculus for proving validity of DTL formulae. Due to its expressiveness, DTL can serve as a basis for p...
York, Paul H; Carter, Alex B; Chartrand, Kathryn; Sankey, Tonia; Wells, Linda; Rasheed, Michael A
2015-08-17
Global seagrass research efforts have focused on shallow coastal and estuarine seagrass populations where alarming declines have been recorded. Comparatively little is known about the dynamics of deep-water seagrasses despite evidence that they form extensive meadows in some parts of the world. Deep-water seagrasses are subject to similar anthropogenic threats as shallow meadows, particularly along the Great Barrier Reef lagoon where they occur close to major population centres. We examine the dynamics of a deep-water seagrass population in the GBR over an 8 year period during which time a major capital dredging project occurred. Seasonal and inter-annual changes in seagrasses were assessed as well as the impact of dredging. The seagrass population was found to occur annually, generally present between July and December each year. Extensive and persistent turbid plumes from a large dredging program over an 8 month period resulted in a failure of the seagrasses to establish in 2006, however recruitment occurred the following year and the regular annual cycle was re-established. Results show that despite considerable inter annual variability, deep-water seagrasses had a regular annual pattern of occurrence, low resistance to reduced water quality but a capacity for rapid recolonisation on the cessation of impacts.
突发事件下车辆路径问题的动态规划算法%Dynamic Programming Algorithm of Vehicle Routing Problems under Emergencies
Institute of Scientific and Technical Information of China (English)
欧微; 焦丽萍
2011-01-01
突发事件下的车辆运输具有紧迫性、动态性和随机不确定性等特点.本文研究了突发事件下动态车辆路径问题的数学模型,构建了一种基于混沌优化的动态规划算法,为此通过路径计算和动态规划两个模块来实现车辆路径的动态规划.为实现从混沌运动空间向问题可行解空间的有效映射,提出了相应的编码方法和操作算子.最后进行仿真,通过对静态环境、道路受损和道路拥塞三种情况的分析,验证了实时修订路经的有效性和实用性,为突发事件提供参考.%The vehicle transportation under emergencies is a kind of emergent, dynamic and random problems. The mathematics model of Dynamic Vehicle Routing Problems (DVRP) under emergencies is proposed, and an ap-proach solving DVRP based on chaos optimization is formulated, in which a route computing module and a dynamic programming module are introduced, and the corresponding coding method and operators are proposed to mapping the chaos space to feasible solution space. Finally, three cases of initial - state, road - damaged and road - congested are analyzed separately to demonstrate the necessary of real - time route adjusting and the efficiency of the proposed algorithm by computer simulations.
Crain, J; McFaull, S; Thompson, W; Skinner, R; Do, M T; Fréchette, M; Mukhi, S
2016-06-01
This status report on the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP), an emergency department-based injury and poisoning surveillance system, describes the result of migrating from a centralized data entry and coding process to a decentralized process, the web-based eCHIRPP system, in 2011. This secure system is improving the CHIRPP's overall flexibility and timeliness, which are key attributes of an effective surveillance system. The integrated eCHIRPP platform enables near real-time data entry and access, has user-friendly data management and analysis tools, and allows for easier communication and connectivity across the CHIRPP network through an online collaboration centre. Current pilot testing of automated data monitoring and trend analysis tools-designed to monitor and flag incoming data according to predefined criteria (for example, a new consumer product)-is revealing eCHIRPP's potential for providing early warnings of new hazards, issues and trends.
Directory of Open Access Journals (Sweden)
J. Crain
2016-06-01
Full Text Available This status report on the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP, an emergency department-based injury and poisoning surveillance system, describes the result of migrating from a centralized data entry and coding process to a decentralized process, the web-based eCHIRPP system, in 2011. This secure system is improving the CHIRPP’s overall flexibility and timeliness, which are key attributes of an effective surveillance system. The integrated eCHIRPP platform enables near real-time data entry and access, has user-friendly data management and analysis tools, and allows for easier communication and connectivity across the CHIRPP network through an online collaboration centre. Current pilot testing of automated data monitoring and trend analysis tools—designed to monitor and flag incoming data according to predefined criteria (for example, a new consumer product—is revealing eCHIRPP’s potential for providing early warnings of new hazards, issues and trends.
Avraamova, O G; Kulazhenko, T V; Gabitova, K F
2016-01-01
The paper presents the assessment of tooth decay prevalence in clinically homogenous groups of children receiving long-term preventive program (PP) in school dental facilities. Five-years PP were introduced in clinical practice in 2 Moscow schools. Preventive treatment was performed by dental hygienist. The results show that systematic preventive treatment in school dental offices starting from elementary school allows reducing dental caries incidence 46-53% and stabilize the incidence of caries complications. It should be mentioned though that analysis of individualized outcomes proves heterogeneity of study results despite of equal conditions of PP. Potentially significant hence is early diagnostics and treatment of initial caries forms as demineralization foci, especially in children with intensive tooth decay. Optimization of pediatric dentist and dental hygienist activity in school dental facilities is the main factor of caries prevention efficiency.
Directory of Open Access Journals (Sweden)
Kotenko К.V.
2013-12-01
Full Text Available The study aimed the development and assessment of features of corrective action of a medical complex on a lipid imbalance at patients with obesity. Material and methods. For an assessment of features of corrective action of a medical complex on a lipid imbalance at patients with obesity in research I was 50 male patients with obesity and frustration of the reproductive sphere aged from 24 to 68 years were included, middle age was 38,5±6,1 years and 7 healthy persons, men of comparable age without any pathological states, results of which all researches were accepted to values of norm. To all patients included in research, except all-clinical inspection calculation of an index of body weight and the relation of a circle of a waist to a circle of hips, measurement of arterial pressure were applied questioning concerning food and food behavior, anthropometry (growth the body weight, a circle of a waist and hips. Besides all patients conducted laboratory methods the researches including definition of atherogenic fractions of lipids (the general cholesterol, triglycerides, LPNPand LPVP. Researches were conducted before treatment and after a course of treatment. Results. The effective complex program for restoration of reproductive function at patients with obesity is developed. Conclusion. Application of the developed comprehensive program more than its separate components caused the expressed reduction of body weight, mainly due to reduction of fatty tissue and manifestations of visceral obesity in patients with obesity and violation of reproductive function, including due to elimination of metabolic imbalance.
Padmanabhan, Vasantha; Veiga-Lopez, Almudena; Herkimer, Carol; Abi Salloum, Bachir; Moeller, Jacob; Beckett, Evan; Sreedharan, Rohit
2015-07-01
Prenatal T excess induces maternal hyperinsulinemia, early puberty, and reproductive/metabolic defects in the female similar to those seen in women with polycystic ovary syndrome. This study addressed the organizational/activational role of androgens and insulin in programming pubertal advancement and periovulatory LH surge defects. Treatment groups included the following: 1) control; 2) prenatal T; 3) prenatal T plus prenatal androgen antagonist, flutamide; 4) prenatal T plus prenatal insulin sensitizer, rosiglitazone; 5) prenatal T and postnatal flutamide; 6) prenatal T and postnatal rosiglitazone; and 7) prenatal T and postnatal metformin. Prenatal treatments spanned 30-90 days of gestation and postnatal treatments began at approximately 8 weeks of age and continued throughout. Blood samples were taken twice weekly, beginning at approximately 12 weeks of age to time puberty. Two-hour samples after the synchronization with prostaglandin F2α were taken for 120 hours to characterize LH surge dynamics at 7 and 19 months of age. Prenatal T females entered puberty earlier than controls, and all interventions prevented this advancement. Prenatal T reduced the percentage of animals having LH surge, and females that presented LH surge exhibited delayed timing and dampened amplitude of the LH surge. Prenatal androgen antagonist, but not other interventions, restored LH surges without normalizing the timing of the surge. Normalization of pubertal timing with prenatal/postnatal androgen antagonist and insulin sensitizer interventions suggests that pubertal advancement is programmed by androgenic actions of T involving insulin as a mediary. Restoration of LH surges by cotreatment with androgen antagonist supports androgenic programming at the organizational level.
Procacci, Piero
2016-06-27
We present a new release (6.0β) of the ORAC program [Marsili et al. J. Comput. Chem. 2010, 31, 1106-1116] with a hybrid OpenMP/MPI (open multiprocessing message passing interface) multilevel parallelism tailored for generalized ensemble (GE) and fast switching double annihilation (FS-DAM) nonequilibrium technology aimed at evaluating the binding free energy in drug-receptor system on high performance computing platforms. The production of the GE or FS-DAM trajectories is handled using a weak scaling parallel approach on the MPI level only, while a strong scaling force decomposition scheme is implemented for intranode computations with shared memory access at the OpenMP level. The efficiency, simplicity, and inherent parallel nature of the ORAC implementation of the FS-DAM algorithm, project the code as a possible effective tool for a second generation high throughput virtual screening in drug discovery and design. The code, along with documentation, testing, and ancillary tools, is distributed under the provisions of the General Public License and can be freely downloaded at www.chim.unifi.it/orac .
Elhanati, Yuval; Marcou, Quentin; Mora, Thierry; Walczak, Aleksandra M.
2016-01-01
Motivation: The diversity of the immune repertoire is initially generated by random rearrangements of the receptor gene during early T and B cell development. Rearrangement scenarios are composed of random events—choices of gene templates, base pair deletions and insertions—described by probability distributions. Not all scenarios are equally likely, and the same receptor sequence may be obtained in several different ways. Quantifying the distribution of these rearrangements is an essential baseline for studying the immune system diversity. Inferring the properties of the distributions from receptor sequences is a computationally hard problem, requiring enumerating every possible scenario for every sampled receptor sequence. Results: We present a Hidden Markov model, which accounts for all plausible scenarios that can generate the receptor sequences. We developed and implemented a method based on the Baum–Welch algorithm that can efficiently infer the parameters for the different events of the rearrangement process. We tested our software tool on sequence data for both the alpha and beta chains of the T cell receptor. To test the validity of our algorithm, we also generated synthetic sequences produced by a known model, and confirmed that its parameters could be accurately inferred back from the sequences. The inferred model can be used to generate synthetic sequences, to calculate the probability of generation of any receptor sequence, as well as the theoretical diversity of the repertoire. We estimate this diversity to be ≈1023 for human T cells. The model gives a baseline to investigate the selection and dynamics of immune repertoires. Availability and implementation: Source code and sample sequence files are available at https://bitbucket.org/yuvalel/repgenhmm/downloads. Contact: elhanati@lpt.ens.fr or tmora@lps.ens.fr or awalczak@lpt.ens.fr PMID:27153709
Institute of Scientific and Technical Information of China (English)
李雪; 聂兰顺; 齐文艳; 战德臣
2015-01-01
针对物流配送服务业中，车辆调度问题日渐呈现任务规模大，车辆类型多、属性多，调度实时性要求越来越高等特点，提出了基于近似动态规划的动态车辆调度算法。根据当前的任务需求与车辆状态以及相应的约束条件作出相应的调度，并且对一些样本进行训练，得到了一个近似价值函数。通过该价值函数，即可对任务迅速作出相应的决策。仿真模拟实验证明了该算法的有效性和优越性。%Vehicle scheduling in service industry of logistics distribution was presenting features including the tasks tended to be of large scale,vehicles were multi-type and had multiple attributes as well as high demands for real-time scheduling.To solve these problems,this paper proposed a dy-namic vehicle scheduling algorithm based on the approximate dynamic programming.An approximate value function was obtained through training of some samples,and according to mission require-ments,vehicle state and conditions,and quick scheduling decisions could be made with the value func-tion.The simulation test has proved the correctness and effectiveness of the algorithm.
Chambers, Joseph
2010-01-01
community, Leonardo da Vinci, George Cayley, and the Wright brothers are examples of early aviation pioneers who frequently used models during their scientific efforts to understand and develop flying machines. Progress in the technology associated with model testing in worldwide applications has firmly established model aircraft as a key element in new aerospace research and development programs. Models are now routinely used in many applications and roles, including aerodynamic data gathering in wind tunnel investigations for the analysis of full-scale aircraft designs, proof-of-concept demonstrators for radical aeronautical concepts, and problem-solving exercises for vehicles already in production. The most critical contributions of aerospace models are to provide confidence and risk reduction for new designs and to enhance the safety and efficiency of existing configurations.
Shih, Ching-Hsiang
2012-01-01
Software technology is adopted by the current research to improve the Drag-and-Drop abilities of two people with multiple disabilities and minimal motor control. This goal was realized through a Dynamic Drag-and-Drop Assistive Program (DDnDAP) in which the complex dragging process is replaced by simply poking the mouse wheel and clicking. However,…