WorldWideScience

Sample records for evolutionary programming based

  1. EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

    Science.gov (United States)

    Wagh, Aditi; Wilensky, Uri

    2018-04-01

    Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

  2. An evolutionary programming based simulated annealing method for solving the unit commitment problem

    Energy Technology Data Exchange (ETDEWEB)

    Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605014 (India); Mohan, M.R. [Department of EEE, Anna University, Chennai 600 025 (India)

    2007-09-15

    This paper presents a new approach to solve the short-term unit commitment problem using an evolutionary programming based simulated annealing method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming, which happens to be a global optimisation technique for solving unit commitment Problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status (''flat start''). Here the parents are obtained from a pre-defined set of solution's, i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. The best population is selected by evolutionary strategy. The Neyveli Thermal Power Station (NTPS) Unit-II in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consists of 10, 26, 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using the Evolutionary Programming method and other conventional methods like Dynamic Programming, Lagrangian Relaxation and Simulated Annealing and Tabu Search in reaching proper unit commitment. (author)

  3. A chaos-based evolutionary algorithm for general nonlinear programming problems

    International Nuclear Information System (INIS)

    El-Shorbagy, M.A.; Mousa, A.A.; Nasr, S.M.

    2016-01-01

    In this paper we present a chaos-based evolutionary algorithm (EA) for solving nonlinear programming problems named chaotic genetic algorithm (CGA). CGA integrates genetic algorithm (GA) and chaotic local search (CLS) strategy to accelerate the optimum seeking operation and to speed the convergence to the global solution. The integration of global search represented in genetic algorithm and CLS procedures should offer the advantages of both optimization methods while offsetting their disadvantages. By this way, it is intended to enhance the global convergence and to prevent to stick on a local solution. The inherent characteristics of chaos can enhance optimization algorithms by enabling it to escape from local solutions and increase the convergence to reach to the global solution. Twelve chaotic maps have been analyzed in the proposed approach. The simulation results using the set of CEC’2005 show that the application of chaotic mapping may be an effective strategy to improve the performances of EAs.

  4. A heuristic ranking approach on capacity benefit margin determination using Pareto-based evolutionary programming technique.

    Science.gov (United States)

    Othman, Muhammad Murtadha; Abd Rahman, Nurulazmi; Musirin, Ismail; Fotuhi-Firuzabad, Mahmud; Rajabi-Ghahnavieh, Abbas

    2015-01-01

    This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  5. A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique

    Directory of Open Access Journals (Sweden)

    Muhammad Murtadha Othman

    2015-01-01

    Full Text Available This paper introduces a novel multiobjective approach for capacity benefit margin (CBM assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE in various conditions. Eventually, the power transfer based available transfer capability (ATC is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  6. New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming

    International Nuclear Information System (INIS)

    Attaviriyanupap, Pathom; Kita, Hiroyuki; Tanaka, Eiichi; Hasegawa, Jun

    2005-01-01

    In this paper, a new bidding strategy for a day-ahead market is formulated. The proposed algorithm is developed from the viewpoint of a generation company wishing to maximize a profit as a participant in the deregulated power and reserve markets. Separate power and reserve markets are considered, both are operated by clearing price auction system. The optimal bidding parameters for both markets are determined by solving an optimization problem that takes unit commitment constraints such as generating limits and unit minimum up/down time constraints into account. This is a non-convex and non-differentiable which is difficult to solve by traditional optimization techniques. In this paper, evolutionary programming is used to solve the problem. The algorithm is applied to both single-sided and double-sided auctions, numerical simulations are carried out to demonstrate the performance of the proposed scheme compared with those obtained from a sequential quadratic programming. (author)

  7. Evolutionary programming-based univector field navigation method for past mobile robots.

    Science.gov (United States)

    Kim, Y J; Kim, J H; Kwon, D S

    2001-01-01

    Most of navigation techniques with obstacle avoidance do not consider the robot orientation at the target position. These techniques deal with the robot position only and are independent of its orientation and velocity. To solve these problems this paper proposes a novel univector field method for fast mobile robot navigation which introduces a normalized two dimensional vector field. The method provides fast moving robots with the desired posture at the target position and obstacle avoidance. To obtain the sub-optimal vector field, a function approximator is used and trained by evolutionary programming. Two kinds of vector fields are trained, one for the final posture acquisition and the other for obstacle avoidance. Computer simulations and real experiments are carried out for a fast moving mobile robot to demonstrate the effectiveness of the proposed scheme.

  8. EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

    Science.gov (United States)

    Wagh, Aditi; Wilensky, Uri

    2018-01-01

    Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience…

  9. Evolutionary epistemology a multiparadigm program

    CERN Document Server

    Pinxten, Rik

    1987-01-01

    This volume has its already distant origin in an inter­national conference on Evolutionary Epistemology the editors organized at the University of Ghent in November 1984. This conference aimed to follow up the endeavor started at the ERISS (Epistemologically Relevant Internalist Sociology of Science) conference organized by Don Campbell and Alex Rosen­ berg at Cazenovia Lake, New York, in June 1981, whilst in­ jecting the gist of certain current continental intellectual developments into a debate whose focus, we thought, was in danger of being narrowed too much, considering the still underdeveloped state of affairs in the field. Broadly speaking, evolutionary epistemology today con­ sists of two interrelated, yet qualitatively distinct inves­ tigative efforts. Both are drawing on Darwinian concepts, which may explain why many people have failed to discriminate them. One is the study of the evolution of the cognitive apparatus of living organisms, which is first and foremost the province of biologists and...

  10. Evolutionary programming as a platform for in silico metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Rocha, Isabel; Förster, Jochen

    2005-01-01

    , and it is therefore interesting to develop new faster algorithms. Results In this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters...... of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span several different pathways and may be necessary for solving challenging metabolic engineering problems....

  11. Individual-based modeling of ecological and evolutionary processes

    Science.gov (United States)

    DeAngelis, Donald L.; Mooij, Wolf M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

  12. Evolutionary programming as a platform for in silico metabolic engineering

    Directory of Open Access Journals (Sweden)

    Förster Jochen

    2005-12-01

    Full Text Available Abstract Background Through genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms. Results In this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters in industrial fermentations, one linear and other non-linear, by using a genome-scale model of the yeast Saccharomyces cerevisiae. Potential metabolic engineering targets for improved production of succinic acid, glycerol and vanillin are identified and underlying flux changes for the predicted mutants are discussed. Conclusion We show that evolutionary programming enables solving large gene knockout problems in relatively short computational time. The proposed algorithm also allows the optimization of non-linear objective functions or incorporation of non-linear constraints and additionally provides a family of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span

  13. Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming

    Science.gov (United States)

    Imani, Moslem; You, Rey-Jer; Kuo, Chung-Yen

    2014-10-01

    Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE = 0.035) and maximum coefficient of determination (R2 = 0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN.

  14. Optimum dispatching by using evolutionary programming; Despacho optimo utilizando programacao evolucionaria

    Energy Technology Data Exchange (ETDEWEB)

    Proenca, Luis Miguel; Pinto, Joao Luis; Matos, Manuel Antonio [Instituto de Engenharia de Sistemas e Computadores (INESC), Porto (Portugal). E-mail: lproenca@inescn.pt; jpinto@duque.inescn.pt; mmatos@inescn.pt

    1999-07-01

    This paper presents a methodology for solving the problem of the optimum dispatching based on the Evolutionary Programming. Also, a software module is described which is based on this integrated approach, integrated in a real system for power systems control and having a high contribution from renewable resources, in the framework of the CARE European project.

  15. Evolutionary programming for neutron instrument optimisation

    Energy Technology Data Exchange (ETDEWEB)

    Bentley, Phillip M. [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany)]. E-mail: phillip.bentley@hmi.de; Pappas, Catherine [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany); Habicht, Klaus [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany); Lelievre-Berna, Eddy [Institut Laue-Langevin, 6 rue Jules Horowitz, BP 156, 38042 Grenoble Cedex 9 (France)

    2006-11-15

    Virtual instruments based on Monte-Carlo techniques are now integral part of novel instrumentation development and the existing codes (McSTAS and Vitess) are extensively used to define and optimise novel instrumental concepts. Neutron spectrometers, however, involve a large number of parameters and their optimisation is often a complex and tedious procedure. Artificial intelligence algorithms are proving increasingly useful in such situations. Here, we present an automatic, reliable and scalable numerical optimisation concept based on the canonical genetic algorithm (GA). The algorithm was used to optimise the 3D magnetic field profile of the NSE spectrometer SPAN, at the HMI. We discuss the potential of the GA which combined with the existing Monte-Carlo codes (Vitess, McSTAS, etc.) leads to a very powerful tool for automated global optimisation of a general neutron scattering instrument, avoiding local optimum configurations.

  16. Evolutionary programming for neutron instrument optimisation

    International Nuclear Information System (INIS)

    Bentley, Phillip M.; Pappas, Catherine; Habicht, Klaus; Lelievre-Berna, Eddy

    2006-01-01

    Virtual instruments based on Monte-Carlo techniques are now integral part of novel instrumentation development and the existing codes (McSTAS and Vitess) are extensively used to define and optimise novel instrumental concepts. Neutron spectrometers, however, involve a large number of parameters and their optimisation is often a complex and tedious procedure. Artificial intelligence algorithms are proving increasingly useful in such situations. Here, we present an automatic, reliable and scalable numerical optimisation concept based on the canonical genetic algorithm (GA). The algorithm was used to optimise the 3D magnetic field profile of the NSE spectrometer SPAN, at the HMI. We discuss the potential of the GA which combined with the existing Monte-Carlo codes (Vitess, McSTAS, etc.) leads to a very powerful tool for automated global optimisation of a general neutron scattering instrument, avoiding local optimum configurations

  17. Evolutionary Based Solutions for Green Computing

    CERN Document Server

    Kołodziej, Joanna; Li, Juan; Zomaya, Albert

    2013-01-01

    Today’s highly parameterized large-scale distributed computing systems may be composed  of a large number of various components (computers, databases, etc) and must provide a wide range of services. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system’s services and resources, and different, often conflicting, expectations and requirements. Moreover, the information and data processed in such dynamic environments may be incomplete, imprecise, fragmentary, and overloading. All of the above mentioned issues require some intelligent scalable methodologies for the management of the whole complex structure, which unfortunately may increase the energy consumption of such systems.   This book in its eight chapters, addresses the fundamental issues related to the energy usage and the optimal low-cost system design in high performance ``green computing’’ systems. The recent evolutionary and general metaheuristic-based solutions ...

  18. An Improved Evolutionary Programming with Voting and Elitist Dispersal Scheme

    Science.gov (United States)

    Maity, Sayan; Gunjan, Kumar; Das, Swagatam

    Although initially conceived for evolving finite state machines, Evolutionary Programming (EP), in its present form, is largely used as a powerful real parameter optimizer. For function optimization, EP mainly relies on its mutation operators. Over past few years several mutation operators have been proposed to improve the performance of EP on a wide variety of numerical benchmarks. However, unlike real-coded GAs, there has been no fitness-induced bias in parent selection for mutation in EP. That means the i-th population member is selected deterministically for mutation and creation of the i-th offspring in each generation. In this article we present an improved EP variant called Evolutionary Programming with Voting and Elitist Dispersal (EPVE). The scheme encompasses a voting process which not only gives importance to best solutions but also consider those solutions which are converging fast. By introducing Elitist Dispersal Scheme we maintain the elitism by keeping the potential solutions intact and other solutions are perturbed accordingly, so that those come out of the local minima. By applying these two techniques we can be able to explore those regions which have not been explored so far that may contain optima. Comparison with the recent and best-known versions of EP over 25 benchmark functions from the CEC (Congress on Evolutionary Computation) 2005 test-suite for real parameter optimization reflects the superiority of the new scheme in terms of final accuracy, speed, and robustness.

  19. On the Evolutionary Bases of Consumer Reinforcement

    Science.gov (United States)

    Nicholson, Michael; Xiao, Sarah Hong

    2010-01-01

    This article locates consumer behavior analysis within the modern neo-Darwinian synthesis, seeking to establish an interface between the ultimate-level theorizing of human evolutionary psychology and the proximate level of inquiry typically favored by operant learning theorists. Following an initial overview of the central tenets of neo-Darwinism,…

  20. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    International Nuclear Information System (INIS)

    Xu Ruirui; Chen Tianlun; Gao Chengfeng

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  1. Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

    Directory of Open Access Journals (Sweden)

    Paul Jean Etienne Jeszensky

    2005-02-01

    Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

  2. An Efficient Evolutionary Based Method For Image Segmentation

    OpenAIRE

    Aslanzadeh, Roohollah; Qazanfari, Kazem; Rahmati, Mohammad

    2017-01-01

    The goal of this paper is to present a new efficient image segmentation method based on evolutionary computation which is a model inspired from human behavior. Based on this model, a four layer process for image segmentation is proposed using the split/merge approach. In the first layer, an image is split into numerous regions using the watershed algorithm. In the second layer, a co-evolutionary process is applied to form centers of finals segments by merging similar primary regions. In the t...

  3. Individual-based modeling of ecological and evolutionary processes

    NARCIS (Netherlands)

    DeAngelis, D.L.; Mooij, W.M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential and difference equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis

  4. Designers' Cognitive Thinking Based on Evolutionary Algorithms

    OpenAIRE

    Zhang Shutao; Jianning Su; Chibing Hu; Peng Wang

    2013-01-01

    The research on cognitive thinking is important to construct the efficient intelligent design systems. But it is difficult to describe the model of cognitive thinking with reasonable mathematical theory. Based on the analysis of design strategy and innovative thinking, we investigated the design cognitive thinking model that included the external guide thinking of "width priority - depth priority" and the internal dominated thinking of "divergent thinking - convergent thinking", built a reaso...

  5. Development of antibiotic regimens using graph based evolutionary algorithms.

    Science.gov (United States)

    Corns, Steven M; Ashlock, Daniel A; Bryden, Kenneth M

    2013-12-01

    This paper examines the use of evolutionary algorithms in the development of antibiotic regimens given to production animals. A model is constructed that combines the lifespan of the animal and the bacteria living in the animal's gastro-intestinal tract from the early finishing stage until the animal reaches market weight. This model is used as the fitness evaluation for a set of graph based evolutionary algorithms to assess the impact of diversity control on the evolving antibiotic regimens. The graph based evolutionary algorithms have two objectives: to find an antibiotic treatment regimen that maintains the weight gain and health benefits of antibiotic use and to reduce the risk of spreading antibiotic resistant bacteria. This study examines different regimens of tylosin phosphate use on bacteria populations divided into Gram positive and Gram negative types, with a focus on Campylobacter spp. Treatment regimens were found that provided decreased antibiotic resistance relative to conventional methods while providing nearly the same benefits as conventional antibiotic regimes. By using a graph to control the information flow in the evolutionary algorithm, a variety of solutions along the Pareto front can be found automatically for this and other multi-objective problems. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Efficient fractal-based mutation in evolutionary algorithms from iterated function systems

    Science.gov (United States)

    Salcedo-Sanz, S.; Aybar-Ruíz, A.; Camacho-Gómez, C.; Pereira, E.

    2018-03-01

    In this paper we present a new mutation procedure for Evolutionary Programming (EP) approaches, based on Iterated Function Systems (IFSs). The new mutation procedure proposed consists of considering a set of IFS which are able to generate fractal structures in a two-dimensional phase space, and use them to modify a current individual of the EP algorithm, instead of using random numbers from different probability density functions. We test this new proposal in a set of benchmark functions for continuous optimization problems. In this case, we compare the proposed mutation against classical Evolutionary Programming approaches, with mutations based on Gaussian, Cauchy and chaotic maps. We also include a discussion on the IFS-based mutation in a real application of Tuned Mass Dumper (TMD) location and optimization for vibration cancellation in buildings. In both practical cases, the proposed EP with the IFS-based mutation obtained extremely competitive results compared to alternative classical mutation operators.

  7. Evolutionary programming for goal-driven dynamic planning

    Science.gov (United States)

    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

  8. Ifuzzer : An evolutionary interpreter fuzzer using genetic programming

    NARCIS (Netherlands)

    Veggalam, Spandan; Rawat, Sanjay; Haller, Istvan; Bos, Herbert

    We present an automated evolutionary fuzzing technique to find bugs in JavaScript interpreters. Fuzzing is an automated black box testing technique used for finding security vulnerabilities in the software by providing random data as input. However, in the case of an interpreter, fuzzing is

  9. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

    Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  10. Evolutionary game theory using agent-based methods.

    Science.gov (United States)

    Adami, Christoph; Schossau, Jory; Hintze, Arend

    2016-12-01

    Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Evolutionary modeling-based approach for model errors correction

    Directory of Open Access Journals (Sweden)

    S. Q. Wan

    2012-08-01

    Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

    On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

  12. Analog Circuit Design Optimization Based on Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Mansour Barari

    2014-01-01

    Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.

  13. The wind power prediction research based on mind evolutionary algorithm

    Science.gov (United States)

    Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

    2018-04-01

    When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

  14. Analog Group Delay Equalizers Design Based on Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    M. Laipert

    2006-04-01

    Full Text Available This paper deals with a design method of the analog all-pass filter designated for equalization of the group delay frequency response of the analog filter. This method is based on usage of evolutionary algorithm, the Differential Evolution algorithm in particular. We are able to design such equalizers to be obtained equal-ripple group delay frequency response in the pass-band of the low-pass filter. The procedure works automatically without an input estimation. The method is presented on solving practical examples.

  15. Some results on ethnic conflicts based on evolutionary game simulation

    Science.gov (United States)

    Qin, Jun; Yi, Yunfei; Wu, Hongrun; Liu, Yuhang; Tong, Xiaonian; Zheng, Bojin

    2014-07-01

    The force of the ethnic separatism, essentially originating from the negative effect of ethnic identity, is damaging the stability and harmony of multiethnic countries. In order to eliminate the foundation of the ethnic separatism and set up a harmonious ethnic relationship, some scholars have proposed a viewpoint: ethnic harmony could be promoted by popularizing civic identity. However, this viewpoint is discussed only from a philosophical prospective and still lacks support of scientific evidences. Because ethnic group and ethnic identity are products of evolution and ethnic identity is the parochialism strategy under the perspective of game theory, this paper proposes an evolutionary game simulation model to study the relationship between civic identity and ethnic conflict based on evolutionary game theory. The simulation results indicate that: (1) the ratio of individuals with civic identity has a negative association with the frequency of ethnic conflicts; (2) ethnic conflict will not die out by killing all ethnic members once for all, and it also cannot be reduced by a forcible pressure, i.e., increasing the ratio of individuals with civic identity; (3) the average frequencies of conflicts can stay in a low level by promoting civic identity periodically and persistently.

  16. Iris double recognition based on modified evolutionary neural network

    Science.gov (United States)

    Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

    2017-11-01

    Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

  17. Android malware detection based on evolutionary super-network

    Science.gov (United States)

    Yan, Haisheng; Peng, Lingling

    2018-04-01

    In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

  18. Training the Millennial learner through experiential evolutionary scaffolding: implications for clinical supervision in graduate education programs.

    Science.gov (United States)

    Venne, Vickie L; Coleman, Darrell

    2010-12-01

    They are the Millennials--Generation Y. Over the next few decades, they will be entering genetic counseling graduate training programs and the workforce. As a group, they are unlike previous youth generations in many ways, including the way they learn. Therefore, genetic counselors who teach and supervise need to understand the Millennials and explore new ways of teaching to ensure that the next cohort of genetic counselors has both skills and knowledge to represent our profession well. This paper will summarize the distinguishing traits of the Millennial generation as well as authentic learning and evolutionary scaffolding theories of learning that can enhance teaching and supervision. We will then use specific aspects of case preparation during clinical rotations to demonstrate how incorporating authentic learning theory into evolutionary scaffolding results in experiential evolutionary scaffolding, a method that potentially offers a more effective approach when teaching Millennials. We conclude with suggestions for future research.

  19. Economic optimization and evolutionary programming when using remote sensing data

    OpenAIRE

    Shamin Roman; Alberto Gabriel Enrike; Uryngaliyeva Ayzhana; Semenov Aleksandr

    2018-01-01

    The article considers the issues of optimizing the use of remote sensing data. Built a mathematical model to describe the economic effect of the use of remote sensing data. It is shown that this model is incorrect optimisation task. Given a numerical method of solving this problem. Also discusses how to optimize organizational structure by using genetic algorithm based on remote sensing. The methods considered allow the use of remote sensing data in an optimal way. The proposed mathematical m...

  20. A Novel Multiobjective Evolutionary Algorithm Based on Regression Analysis

    Directory of Open Access Journals (Sweden)

    Zhiming Song

    2015-01-01

    Full Text Available As is known, the Pareto set of a continuous multiobjective optimization problem with m objective functions is a piecewise continuous (m-1-dimensional manifold in the decision space under some mild conditions. However, how to utilize the regularity to design multiobjective optimization algorithms has become the research focus. In this paper, based on this regularity, a model-based multiobjective evolutionary algorithm with regression analysis (MMEA-RA is put forward to solve continuous multiobjective optimization problems with variable linkages. In the algorithm, the optimization problem is modelled as a promising area in the decision space by a probability distribution, and the centroid of the probability distribution is (m-1-dimensional piecewise continuous manifold. The least squares method is used to construct such a model. A selection strategy based on the nondominated sorting is used to choose the individuals to the next generation. The new algorithm is tested and compared with NSGA-II and RM-MEDA. The result shows that MMEA-RA outperforms RM-MEDA and NSGA-II on the test instances with variable linkages. At the same time, MMEA-RA has higher efficiency than the other two algorithms. A few shortcomings of MMEA-RA have also been identified and discussed in this paper.

  1. The Research of Disease Spots Extraction Based on Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Kangshun Li

    2017-01-01

    Full Text Available According to the characteristics of maize disease spot performance in the image, this paper designs two-histogram segmentation method based on evolutionary algorithm, which combined with the analysis of image of maize diseases and insect pests, with full consideration of color and texture characteristic of the lesion of pests and diseases, the chroma and gray image, composed of two tuples to build a two-dimensional histogram, solves the problem of one-dimensional histograms that cannot be clearly divided into target and background bimodal distribution and improved the traditional two-dimensional histogram application in pest damage lesion extraction. The chromosome coding suitable for the characteristics of lesion image is designed based on second segmentation of the genetic algorithm Otsu. Determining initial population with analysis results of lesion image, parallel selection, optimal preservation strategy, and adaptive mutation operator are used to improve the search efficiency. Finally, by setting the fluctuation threshold, we continue to search for the best threshold in the range of fluctuations for implementation of global search and local search.

  2. Optimization of heat transfer utilizing graph based evolutionary algorithms

    International Nuclear Information System (INIS)

    Bryden, Kenneth M.; Ashlock, Daniel A.; McCorkle, Douglas S.; Urban, Gregory L.

    2003-01-01

    This paper examines the use of graph based evolutionary algorithms (GBEAs) for optimization of heat transfer in a complex system. The specific case examined in this paper is the optimization of heat transfer in a biomass cookstove utilizing three-dimensional computational fluid dynamics to generate the fitness function. In this stove hot combustion gases are used to heat a cooking surface. The goal is to provide an even spatial temperature distribution on the cooking surface by redirecting the flow of combustion gases with baffles. The variables in the optimization are the position and size of the baffles, which are described by integer values. GBEAs are a novel type of EA in which a topology or geography is imposed on an evolving population of solutions. The choice of graph controls the rate at which solutions can spread within the population, impacting the diversity of solutions and convergence rate of the EAs. In this study, the choice of graph in the GBEAs changes the number of mating events required for convergence by a factor of approximately 2.25 and the diversity of the population by a factor of 2. These results confirm that by tuning the graph and parameters in GBEAs, computational time can be significantly reduced

  3. Swainsonine, a novel fungal metabolite: optimization of fermentative production and bioreactor operations using evolutionary programming.

    Science.gov (United States)

    Singh, Digar; Kaur, Gurvinder

    2014-08-01

    The optimization of bioreactor operations towards swainsonine production was performed using an artificial neural network coupled evolutionary program (EP)-based optimization algorithm fitted with experimental one-factor-at-a-time (OFAT) results. The effects of varying agitation (300-500 rpm) and aeration (0.5-2.0 vvm) rates for different incubation hours (72-108 h) were evaluated in bench top bioreactor. Prominent scale-up parameters, gassed power per unit volume (P g/V L, W/m(3)) and volumetric oxygen mass transfer coefficient (K L a, s(-1)) were correlated with optimized conditions. A maximum of 6.59 ± 0.10 μg/mL of swainsonine production was observed at 400 rpm-1.5 vvm at 84 h in OFAT experiments with corresponding P g/VL and K L a values of 91.66 W/m(3) and 341.48 × 10(-4) s(-1), respectively. The EP optimization algorithm predicted a maximum of 10.08 μg/mL of swainsonine at 325.47 rpm, 1.99 vvm and 80.75 h against the experimental production of 7.93 ± 0.52 μg/mL at constant K L a (349.25 × 10(-4) s(-1)) and significantly reduced P g/V L (33.33 W/m(3)) drawn by the impellers.

  4. Multi-objective mixture-based iterated density estimation evolutionary algorithms

    NARCIS (Netherlands)

    Thierens, D.; Bosman, P.A.N.

    2001-01-01

    We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (MIDEA). The MIDEA algorithm is a prob- abilistic model building evolutionary algo- rithm that constructs at each generation a mixture of factorized probability

  5. SIMULATING AN EVOLUTIONARY MULTI-AGENT BASED MODEL OF THE STOCK MARKET

    Directory of Open Access Journals (Sweden)

    Diana MARICA

    2015-08-01

    Full Text Available The paper focuses on artificial stock market simulations using a multi-agent model incorporating 2,000 heterogeneous agents interacting on the artificial market. The agents interaction is due to trading activity on the market through a call auction trading mechanism. The multi-agent model uses evolutionary techniques such as genetic programming in order to generate an adaptive and evolving population of agents. Each artificial agent is endowed with wealth and a genetic programming induced trading strategy. The trading strategy evolves and adapts to the new market conditions through a process called breeding, which implies that at each simulation step, new agents with better trading strategies are generated by the model, from recombining the best performing trading strategies and replacing the agents which have the worst performing trading strategies. The simulation model was build with the help of the simulation software Altreva Adaptive Modeler which offers a suitable platform for financial market simulations of evolutionary agent based models, the S&P500 composite index being used as a benchmark for the simulation results.

  6. Perception-based Co-evolutionary Reinforcement Learning for UAV Sensor Allocation

    National Research Council Canada - National Science Library

    Berenji, Hamid

    2003-01-01

    .... A Perception-based reasoning approach based on co-evolutionary reinforcement learning was developed for jointly addressing sensor allocation on each individual UAV and allocation of a team of UAVs...

  7. Evolutionary Nephrology.

    Science.gov (United States)

    Chevalier, Robert L

    2017-05-01

    Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as "maladaptive." In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic) adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ~40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons), evolutionary selection for APOL1 mutations (that provide resistance to trypanosome infection, a tradeoff), and modern life experience (Western diet mismatch leading to diabetes and hypertension). Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo), developmental programming and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.

  8. Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

    Science.gov (United States)

    Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

    2017-08-08

    Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

  9. A network growth model based on the evolutionary ultimatum game

    International Nuclear Information System (INIS)

    Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S

    2012-01-01

    In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)

  10. Financing Competency Based Programs.

    Science.gov (United States)

    Daniel, Annette

    Literature on the background, causes, and current prevalence of competency based programs is synthesized in this report. According to one analysis of the actual and probable costs of minimum competency testing, estimated costs for test development, test administration, bureaucratic structures, and remedial programs for students who cannot pass the…

  11. A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Wanxing Sheng

    2013-01-01

    Full Text Available A distribution generation (DG multiobjective optimization method based on an improved Pareto evolutionary algorithm is investigated in this paper. The improved Pareto evolutionary algorithm, which introduces a penalty factor in the objective function constraints, uses an adaptive crossover and a mutation operator in the evolutionary process and combines a simulated annealing iterative process. The proposed algorithm is utilized to the optimize DG injection models to maximize DG utilization while minimizing system loss and environmental pollution. A revised IEEE 33-bus system with multiple DG units was used to test the multiobjective optimization algorithm in a distribution power system. The proposed algorithm was implemented and compared with the strength Pareto evolutionary algorithm 2 (SPEA2, a particle swarm optimization (PSO algorithm, and nondominated sorting genetic algorithm II (NGSA-II. The comparison of the results demonstrates the validity and practicality of utilizing DG units in terms of economic dispatch and optimal operation in a distribution power system.

  12. Species co-evolutionary algorithm: a novel evolutionary algorithm based on the ecology and environments for optimization

    DEFF Research Database (Denmark)

    Li, Wuzhao; Wang, Lei; Cai, Xingjuan

    2015-01-01

    and affect each other in many ways. The relationships include competition, predation, parasitism, mutualism and pythogenesis. In this paper, we consider the five relationships between solutions to propose a co-evolutionary algorithm termed species co-evolutionary algorithm (SCEA). In SCEA, five operators...

  13. Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

    Science.gov (United States)

    Taylan, Fatih

    2011-04-01

    In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

  14. Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

    Science.gov (United States)

    Zhao, Qiangfu; Liu, Yong

    2015-01-01

    A fitness landscape presents the relationship between individual and its reproductive success in evolutionary computation (EC). However, discrete and approximate landscape in an original search space may not support enough and accurate information for EC search, especially in interactive EC (IEC). The fitness landscape of human subjective evaluation in IEC is very difficult and impossible to model, even with a hypothesis of what its definition might be. In this paper, we propose a method to establish a human model in projected high dimensional search space by kernel classification for enhancing IEC search. Because bivalent logic is a simplest perceptual paradigm, the human model is established by considering this paradigm principle. In feature space, we design a linear classifier as a human model to obtain user preference knowledge, which cannot be supported linearly in original discrete search space. The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search. From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly. PMID:25879050

  15. Evolutionary Nephrology

    Directory of Open Access Journals (Sweden)

    Robert L. Chevalier

    2017-05-01

    Full Text Available Progressive kidney disease follows nephron loss, hyperfiltration, and incomplete repair, a process described as “maladaptive.” In the past 20 years, a new discipline has emerged that expands research horizons: evolutionary medicine. In contrast to physiologic (homeostatic adaptation, evolutionary adaptation is the result of reproductive success that reflects natural selection. Evolutionary explanations for physiologically maladaptive responses can emerge from mismatch of the phenotype with environment or from evolutionary tradeoffs. Evolutionary adaptation to a terrestrial environment resulted in a vulnerable energy-consuming renal tubule and a hypoxic, hyperosmolar microenvironment. Natural selection favors successful energy investment strategy: energy is allocated to maintenance of nephron integrity through reproductive years, but this declines with increasing senescence after ∼40 years of age. Risk factors for chronic kidney disease include restricted fetal growth or preterm birth (life history tradeoff resulting in fewer nephrons, evolutionary selection for APOL1 mutations (which provide resistance to trypanosome infection, a tradeoff, and modern life experience (Western diet mismatch leading to diabetes and hypertension. Current advances in genomics, epigenetics, and developmental biology have revealed proximate causes of kidney disease, but attempts to slow kidney disease remain elusive. Evolutionary medicine provides a complementary approach by addressing ultimate causes of kidney disease. Marked variation in nephron number at birth, nephron heterogeneity, and changing susceptibility to kidney injury throughout the life history are the result of evolutionary processes. Combined application of molecular genetics, evolutionary developmental biology (evo-devo, developmental programming, and life history theory may yield new strategies for prevention and treatment of chronic kidney disease.

  16. An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization

    Directory of Open Access Journals (Sweden)

    Rafał Dreżewski

    2017-08-01

    Full Text Available Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a more classical approach—the trend-following algorithm. During the experiments historical data from the Warsaw Stock Exchange is used in order to assess the performance of the compared algorithms. Finally, we draw some conclusions from these experiments, showing the strong and weak points of all the techniques.

  17. Motivational and evolutionary aspects of a physical exercise training program: a longitudinal study.

    Directory of Open Access Journals (Sweden)

    João Paulo Pereira Rosa

    2015-05-01

    Full Text Available Several studies have indicated that motivational level and prior expectations are relevant aspects to increase commitment to physical activity. Moreover, these aspects are not properly described in terms of proximal (Self Determination Theory and distal (evolutionary explanations in the literature. This paper aims to verify if level of motivation (BREQ-2 and expectations regarding regular physical exercise (IMPRAF-54 before starting a one-year exercise program could determine likelihood of completion. Ninety-four volunteers (53 women included a completed protocol group (CPG n=21 and drop-out group (DG n=73. The IMPRAF-54 scale was used to assess six different expectations associated with physical activity, and the BREQ-2 inventory was used to assess the level of motivation in five steps (from amotivation to intrinsic motivation. Both questionnaires were assessed before the regular exercise program. The CPG group presented higher sociability and lower pleasure scores according to IMPRAF-54 domains. A logistic regression showed that a one-point increment on sociability score increased the chance of completing the program by 10%, and the same one-point increment on pleasure score reduced the chance of completing the protocol by 16%. ROC curves were also calculated to establish IMPRAF-54 cutoffs for adherence (Sociability - 18.5 points – 81% sensibility/50% specificity and dropout (Pleasure – 25.5 points – 86% sensibility/20% specificity of the exercise protocol. Our results indicate that an expectation of social interaction was a positive factor in predicting adherence to exercise. Grounded in SDT and its innate needs (competence, autonomy, relatedness, physical exercise is not an end; it is a means to achieve autonomy and self-cohesion. The association of physical activity with social practices, like in hunter-gathering groups, can engage people to be physically active and can provide better results in adherence exercise programs for the

  18. Motivational and evolutionary aspects of a physical exercise training program: a longitudinal study

    Science.gov (United States)

    Rosa, João P. P.; de Souza, Altay A. L.; de Lima, Giscard H. O.; Rodrigues, Dayane F.; de Aquino Lemos, Valdir; da Silva Alves, Eduardo; Tufik, Sergio; de Mello, Marco T.

    2015-01-01

    Several studies have indicated that motivational level and prior expectations influence one’s commitment to physical activity. Moreover, these aspects are not properly described in terms of proximal (SDT, Self Determination Theory) and distal (evolutionary) explanations in the literature. This paper aims to verify if level of motivation (BREQ-2, Behavioral Regulation in Exercise Questionnaire-2) and expectations regarding regular physical exercise (IMPRAF-54) before starting a 1-year exercise program could determine likelihood of completion. Ninety-four volunteers (53 women) included a completed protocol group (CPG; n = 21) and drop-out group (n = 73). The IMPRAF-54 scale was used to assess six different expectations associated with physical activity, and the BREQ-2 inventory was used to assess the level of motivation in five steps (from amotivation to intrinsic motivation). Both questionnaires were assessed before starting a regular exercise program. The CPG group presented higher sociability and lower pleasure scores according to IMPRAF-54 domains. A logistic regression analysis showed that a one-point increment on sociability score increased the chance of completing the program by 10%, and the same one-point increment on pleasure score reduced the chance of completing the protocol by 16%. ROC curves were also calculated to establish IMPRAF-54 cutoffs for adherence (Sociability – 18.5 points – 81% sensibility/50% specificity) and dropout (Pleasure – 25.5 points – 86% sensibility/20% specificity) of the exercise protocol. Our results indicate that an expectation of social interaction was a positive factor in predicting adherence to exercise. Grounded in SDT and its innate needs (competence, autonomy, relatedness), physical exercise is not an end; it is a means to achieve autonomy and self-cohesion. The association of physical activity with social practices, as occurs in hunter-gathering groups, can engage people to be physically active and can provide

  19. CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

    Science.gov (United States)

    Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

    2016-01-01

    1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

  20. HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

    Science.gov (United States)

    Majid, Abdul; Ali, Safdar

    2015-01-01

    We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

  1. Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

    DEFF Research Database (Denmark)

    Wang, Yong; Cai, Zixing; Zhou, Yuren

    2009-01-01

    A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

  2. Study on Cooperative Mechanism of Prefabricated Producers Based on Evolutionary Game Theory

    Directory of Open Access Journals (Sweden)

    Tongyao Feng

    2017-01-01

    Full Text Available Good cooperation mechanism is an important guarantee for the advancement of industrialization construction. To strengthen the partnership between producers, we analyze the behavior evolution trend of both parties using an evolutionary game theory. Based on the original model, the mechanism of coordination and cooperation between prefabricated producers is explained under the condition of punishment and incentive. The results indicate that stable evolutionary strategies exist under both cooperation and noncooperation, and the evolutionary results are influenced by the initial proportion of both decision-making processes. The government can support the production enterprises to establish a solid partnership through effective punishment and incentive mechanisms to reduce the initial cost in the supply chain of prefabricated construction, resulting in a win-win situation.

  3. Integrating EMDR into an evolutionary-based therapy for depression: a case study

    OpenAIRE

    Krupnik, Valery

    2015-01-01

    Key Clinical Message We present an intervention in a case of major depression, where eye movement desensitization and reprocessing (EMDR) therapy was integrated into an evolutionary-based psychotherapy for depression. At the end of the treatment and at follow up assessment we observed a more accepting disposition and decreased depressive but not anxiety symptoms.

  4. Integrating EMDR into an evolutionary-based therapy for depression: a case study

    Science.gov (United States)

    Krupnik, Valery

    2015-01-01

    Key Clinical Message We present an intervention in a case of major depression, where eye movement desensitization and reprocessing (EMDR) therapy was integrated into an evolutionary-based psychotherapy for depression. At the end of the treatment and at follow up assessment we observed a more accepting disposition and decreased depressive but not anxiety symptoms. PMID:25984310

  5. Social referencing and child anxiety: the evolutionary based role of fathers' versus mothers' signals

    NARCIS (Netherlands)

    Möller, E.L.; Majdandžić, M.; Vriends, N.; Bögels, S.M.

    2014-01-01

    Children use signals from others to guide their behavior when confronted with potentially dangerous situations, so called social referencing. Due to evolutionary based different expertise of fathers and mothers, parents might be different social references for their children. The present study

  6. Sea Basing: Evolutionary Naval Doctrine and Military Transformation

    National Research Council Canada - National Science Library

    Gentry, Robin

    2004-01-01

    .... Sea Basing through a combination of naval platforms provides the bridge for the American military forces between the advance force operations needed to prepare the battlespace and the war-winning...

  7. Cat swarm optimization based evolutionary framework for multi document summarization

    Science.gov (United States)

    Rautray, Rasmita; Balabantaray, Rakesh Chandra

    2017-07-01

    Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.

  8. Symmetry-based reciprocity: evolutionary constraints on a proximate mechanism.

    Science.gov (United States)

    Campennì, Marco; Schino, Gabriele

    2016-01-01

    Background. While the evolution of reciprocal cooperation has attracted an enormous attention, the proximate mechanisms underlying the ability of animals to cooperate reciprocally are comparatively neglected. Symmetry-based reciprocity is a hypothetical proximate mechanism that has been suggested to be widespread among cognitively unsophisticated animals. Methods. We developed two agent-based models of symmetry-based reciprocity (one relying on an arbitrary tag and the other on interindividual proximity) and tested their ability both to reproduce significant emergent features of cooperation in group living animals and to promote the evolution of cooperation. Results. Populations formed by agents adopting symmetry-based reciprocity showed differentiated "social relationships" and a positive correlation between cooperation given and received: two common aspects of animal cooperation. However, when reproduction and selection across multiple generations were added to the models, agents adopting symmetry-based reciprocity were outcompeted by selfish agents that never cooperated. Discussion. In order to evolve, hypothetical proximate mechanisms must be able to stand competition from alternative strategies. While the results of our simulations require confirmation using analytical methods, we provisionally suggest symmetry-based reciprocity is to be abandoned as a possible proximate mechanism underlying the ability of animals to reciprocate cooperative interactions.

  9. An evolutionary approach for colour constancy based on gamut ...

    Indian Academy of Sciences (India)

    Many colour constancy algorithms have been proposed to achieve a good performance in this field. The gamut mapping algorithm is one of the most accurate and promising algorithms based on gamut assumption: illuminant can be estimated by comparing the colours distribution in the current image to acanonical gamut ...

  10. Controller Design of DFIG Based Wind Turbine by Using Evolutionary Soft Computational Techniques

    Directory of Open Access Journals (Sweden)

    O. P. Bharti

    2017-06-01

    Full Text Available This manuscript illustrates the controller design for a doubly fed induction generator based variable speed wind turbine by using a bioinspired scheme. This methodology is based on exploiting two proficient swarm intelligence based evolutionary soft computational procedures. The particle swarm optimization (PSO and bacterial foraging optimization (BFO techniques are employed to design the controller intended for small damping plant of the DFIG. Wind energy overview and DFIG operating principle along with the equivalent circuit model is adequately discussed in this paper. The controller design for DFIG based WECS using PSO and BFO are described comparatively in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power, and DC-Link voltage have slightly improved with the evolutionary soft computational procedure. Lastly, the obtained output is equated with a standard technique for performance improvement of DFIG based wind energy conversion system.

  11. Drug-target interaction prediction from PSSM based evolutionary information.

    Science.gov (United States)

    Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-01-01

    The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Part E: Evolutionary Computation

    DEFF Research Database (Denmark)

    2015-01-01

    of Computational Intelligence. First, comprehensive surveys of genetic algorithms, genetic programming, evolution strategies, parallel evolutionary algorithms are presented, which are readable and constructive so that a large audience might find them useful and – to some extent – ready to use. Some more general...... kinds of evolutionary algorithms, have been prudently analyzed. This analysis was followed by a thorough analysis of various issues involved in stochastic local search algorithms. An interesting survey of various technological and industrial applications in mechanical engineering and design has been...... topics like the estimation of distribution algorithms, indicator-based selection, etc., are also discussed. An important problem, from a theoretical and practical point of view, of learning classifier systems is presented in depth. Multiobjective evolutionary algorithms, which constitute one of the most...

  13. Integrated data base program

    International Nuclear Information System (INIS)

    Notz, K.J.

    1981-01-01

    The IDB Program provides direct support to the DOE Nuclear Waste Management and Fuel Cycle Programs and their lead sites and support contractors by providing and maintaining a current, integrated data base of spent fuel and radioactive waste inventories and projections. All major waste types (HLW, TRU, and LLW) and sources (government, commerical fuel cycle, and I/I) are included. A major data compilation was issued in September, 1981: Spent Fuel and Radioactive Waste Inventories and Projections as of December 31, 1980, DOE/NE-0017. This report includes chapters on Spent Fuel, HLW, TRU Waste, LLW, Remedial Action Waste, Active Uranium Mill Tailings, and Airborne Waste, plus Appendices with more detailed data in selected areas such as isotopics, radioactivity, thermal power, projections, and land usage. The LLW sections include volumes, radioactivity, thermal power, current inventories, projected inventories and characteristics, source terms, land requirements, and a breakdown in terms of government/commercial and defense/fuel cycle/I and I

  14. A security mechanism based on evolutionary game in fog computing.

    Science.gov (United States)

    Sun, Yan; Lin, Fuhong; Zhang, Nan

    2018-02-01

    Fog computing is a distributed computing paradigm at the edge of the network and requires cooperation of users and sharing of resources. When users in fog computing open their resources, their devices are easily intercepted and attacked because they are accessed through wireless network and present an extensive geographical distribution. In this study, a credible third party was introduced to supervise the behavior of users and protect the security of user cooperation. A fog computing security mechanism based on human nervous system is proposed, and the strategy for a stable system evolution is calculated. The MATLAB simulation results show that the proposed mechanism can reduce the number of attack behaviors effectively and stimulate users to cooperate in application tasks positively.

  15. Design of synthetic biological logic circuits based on evolutionary algorithm.

    Science.gov (United States)

    Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei

    2013-08-01

    The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.

  16. A security mechanism based on evolutionary game in fog computing

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2018-02-01

    Full Text Available Fog computing is a distributed computing paradigm at the edge of the network and requires cooperation of users and sharing of resources. When users in fog computing open their resources, their devices are easily intercepted and attacked because they are accessed through wireless network and present an extensive geographical distribution. In this study, a credible third party was introduced to supervise the behavior of users and protect the security of user cooperation. A fog computing security mechanism based on human nervous system is proposed, and the strategy for a stable system evolution is calculated. The MATLAB simulation results show that the proposed mechanism can reduce the number of attack behaviors effectively and stimulate users to cooperate in application tasks positively.

  17. Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

    Science.gov (United States)

    Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem

    2018-01-01

    In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

  18. Vanpool trip planning based on evolutionary multiple objective optimization

    Science.gov (United States)

    Zhao, Ming; Yang, Disheng; Feng, Shibing; Liu, Hengchang

    2017-08-01

    Carpool and vanpool draw a lot of researchers’ attention, which is the emphasis of this paper. A concrete vanpool operation definition is given, based on the given definition, this paper tackles vanpool operation optimization using user experience decline index(UEDI). This paper is focused on making each user having identical UEDI and the system having minimum sum of all users’ UEDI. Three contributions are made, the first contribution is a vanpool operation scheme diagram, each component of the scheme is explained in detail. The second contribution is getting all customer’s UEDI as a set, standard deviation and sum of all users’ UEDI set are used as objectives in multiple objective optimization to decide trip start address, trip start time and trip destination address. The third contribution is a trip planning algorithm, which tries to minimize the sum of all users’ UEDI. Geographical distribution of the charging stations and utilization rate of the charging stations are considered in the trip planning process.

  19. Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

    Directory of Open Access Journals (Sweden)

    Azmat Ullah

    Full Text Available In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA with Interior Point Algorithm (IPA is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

  20. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  1. A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence

    OpenAIRE

    Kiwia, D; Dehghantanha, A; Choo, K-KR; Slaughter, J

    2017-01-01

    Malware such as banking Trojans are popular with financially-motivated cybercriminals. Detection of banking Trojans remains a challenging task, due to the constant evolution of techniques used to obfuscate and circumvent existing detection and security solutions. Having a malware taxonomy can facilitate the design of mitigation strategies such as those based on evolutionary computational intelligence. Specifically, in this paper, we propose a cyber kill chain based taxonomy of banking Trojans...

  2. A Self-adaptive Dynamic Evaluation Model for Diabetes Mellitus, Based on Evolutionary Strategies

    Directory of Open Access Journals (Sweden)

    An-Jiang Lu

    2016-03-01

    Full Text Available In order to evaluate diabetes mellitus objectively and accurately, this paper builds a self-adaptive dynamic evaluation model for diabetes mellitus, based on evolutionary strategies. First of all, on the basis of a formalized description of the evolutionary process of diabetes syndromes, using a state transition function, it judges whether a disease is evolutionary, through an excitation parameter. It then, provides evidence for the rebuilding of the evaluation index system. After that, by abstracting and rebuilding the composition of evaluation indexes, it makes use of a heuristic algorithm to determine the composition of the evolved evaluation index set of diabetes mellitus, It then, calculates the weight of each index in the evolved evaluation index set of diabetes mellitus by building a dependency matrix and realizes the self-adaptive dynamic evaluation of diabetes mellitus under an evolutionary environment. Using this evaluation model, it is possible to, quantify all kinds of diagnoses and treatment experiences of diabetes and finally to adopt ideal diagnoses and treatment measures for different patients with diabetics.

  3. The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

    Directory of Open Access Journals (Sweden)

    Dazhi Jiang

    2015-01-01

    Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

  4. A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Sho Fukuda

    2014-12-01

    Full Text Available Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that several studies have been tried to achieve. In recent years, probability-based evolutionary algorithms have been proposed as a new efficient approach to learn Bayesian networks. In this paper, we target on one of the probability-based evolutionary algorithms called PBIL (Probability-Based Incremental Learning, and propose a new mutation operator. Through performance evaluation, we found that the proposed mutation operator has a good performance in learning Bayesian networks

  5. Optimum topology for radial networks by using evolutionary computer programming; Topologia optima de redes radiais utilizando programacao evolucionaria

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Joao Luis [Instituto de Engenhariade Sistemas e Computadores (INESC), Porto (Portugal). E-mail: jpinto@duque.inescn.pt; Proenca, Luis Miguel [Instituto Superior de Linguas e Administracao (ISLA), Gaia (Portugal). E-mail: lproenca@inescn.pt

    1999-07-01

    This paper describes the using of Evolutionary Programming techniques for determination of the radial electric network topology, considering investment costs and losses. The work aims to demonstrate the particular easiness of coding and implementation and the parallelism implicit to the method as well, giving outstanding performance levels. As test example, a 43 bars and 75 alternative lines network has been used by describing an implementation of the algorithm in an Object Oriented platform.

  6. Design of problem-specific evolutionary algorithm/mixed-integer programming hybrids: two-stage stochastic integer programming applied to chemical batch scheduling

    Science.gov (United States)

    Urselmann, Maren; Emmerich, Michael T. M.; Till, Jochen; Sand, Guido; Engell, Sebastian

    2007-07-01

    Engineering optimization often deals with large, mixed-integer search spaces with a rigid structure due to the presence of a large number of constraints. Metaheuristics, such as evolutionary algorithms (EAs), are frequently suggested as solution algorithms in such cases. In order to exploit the full potential of these algorithms, it is important to choose an adequate representation of the search space and to integrate expert-knowledge into the stochastic search operators, without adding unnecessary bias to the search. Moreover, hybridisation with mathematical programming techniques such as mixed-integer programming (MIP) based on a problem decomposition can be considered for improving algorithmic performance. In order to design problem-specific EAs it is desirable to have a set of design guidelines that specify properties of search operators and representations. Recently, a set of guidelines has been proposed that gives rise to so-called Metric-based EAs (MBEAs). Extended by the minimal moves mutation they allow for a generalization of EA with self-adaptive mutation strength in discrete search spaces. In this article, a problem-specific EA for process engineering task is designed, following the MBEA guidelines and minimal moves mutation. On the background of the application, the usefulness of the design framework is discussed, and further extensions and corrections proposed. As a case-study, a two-stage stochastic programming problem in chemical batch process scheduling is considered. The algorithm design problem can be viewed as the choice of a hierarchical decision structure, where on different layers of the decision process symmetries and similarities can be exploited for the design of minimal moves. After a discussion of the design approach and its instantiation for the case-study, the resulting problem-specific EA/MIP is compared to a straightforward application of a canonical EA/MIP and to a monolithic mathematical programming algorithm. In view of the

  7. Base Research Program

    Energy Technology Data Exchange (ETDEWEB)

    Everett Sondreal; John Hendrikson

    2009-03-31

    In June 2009, the Energy & Environmental Research Center (EERC) completed 11 years of research under the U.S. Department of Energy (DOE) Base Cooperative Agreement No. DE-FC26-98FT40320 funded through the Office of Fossil Energy (OFE) and administered at the National Energy Technology Laboratory (NETL). A wide range of diverse research activities were performed under annual program plans approved by NETL in seven major task areas: (1) resource characterization and waste management, (2) air quality assessment and control, (3) advanced power systems, (4) advanced fuel forms, (5) value-added coproducts, (6) advanced materials, and (7) strategic studies. This report summarizes results of the 67 research subtasks and an additional 50 strategic studies. Selected highlights in the executive summary illustrate the contribution of the research to the energy industry in areas not adequately addressed by the private sector alone. During the period of performance of the agreement, concerns have mounted over the impact of carbon emissions on climate change, and new programs have been initiated by DOE to ensure that fossil fuel resources along with renewable resources can continue to supply the nation's transportation fuel and electric power. The agreement has addressed DOE goals for reductions in CO{sub 2} emissions through efficiency, capture, and sequestration while expanding the supply and use of domestic energy resources for energy security. It has further contributed to goals for near-zero emissions from highly efficient coal-fired power plants; environmental control capabilities for SO{sub 2}, NO{sub x}, fine respirable particulate (PM{sub 2.5}), and mercury; alternative transportation fuels including liquid synfuels and hydrogen; and synergistic integration of fossil and renewable resources (e.g., wind-, biomass-, and coal-based electrical generation).

  8. An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

    Science.gov (United States)

    Deb, Kalyanmoy; Sinha, Ankur

    2010-01-01

    Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

  9. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  10. [Evolutionary medicine].

    Science.gov (United States)

    Wjst, M

    2013-12-01

    Evolutionary medicine allows new insights into long standing medical problems. Are we "really stoneagers on the fast lane"? This insight might have enormous consequences and will allow new answers that could never been provided by traditional anthropology. Only now this is made possible using data from molecular medicine and systems biology. Thereby evolutionary medicine takes a leap from a merely theoretical discipline to practical fields - reproductive, nutritional and preventive medicine, as well as microbiology, immunology and psychiatry. Evolutionary medicine is not another "just so story" but a serious candidate for the medical curriculum providing a universal understanding of health and disease based on our biological origin. © Georg Thieme Verlag KG Stuttgart · New York.

  11. Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

    Science.gov (United States)

    Xu, Xiao-Feng

    2018-03-01

    Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

  12. Ni-MH batteries state-of-charge prediction based on immune evolutionary network

    International Nuclear Information System (INIS)

    Cheng Bo; Zhou Yanlu; Zhang Jiexin; Wang Junping; Cao Binggang

    2009-01-01

    Based on clonal selection theory, an improved immune evolutionary strategy is presented. Compared with conventional evolutionary strategy algorithm (CESA) and immune monoclonal strategy algorithm (IMSA), experimental results show that the proposed algorithm is of high efficiency and can effectively prevent premature convergence. A three-layer feed-forward neural network is presented to predict state-of-charge (SOC) of Ni-MH batteries. Initially, partial least square regression (PLSR) is used to select input variables. Then, five variables, battery terminal voltage, voltage derivative, voltage second derivative, discharge current and battery temperature, are selected as the inputs of NN. In order to overcome the weakness of BP algorithm, the new algorithm is adopted to train weights. Finally, under the state of dynamic power cycle, the predicted SOC and the actual SOC are compared to verify the proposed neural network with acceptable accuracy (5%).

  13. Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

    Science.gov (United States)

    Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung

    2016-07-01

    In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

  14. Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

    Science.gov (United States)

    Wagh, Aditi

    Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

  15. Preferential selection based on strategy persistence and memory promotes cooperation in evolutionary prisoner's dilemma games

    Science.gov (United States)

    Liu, Yuanming; Huang, Changwei; Dai, Qionglin

    2018-06-01

    Strategy imitation plays a crucial role in evolutionary dynamics when we investigate the spontaneous emergence of cooperation under the framework of evolutionary game theory. Generally, when an individual updates his strategy, he needs to choose a role model whom he will learn from. In previous studies, individuals choose role models randomly from their neighbors. In recent works, researchers have considered that individuals choose role models according to neighbors' attractiveness characterized by the present network topology or historical payoffs. Here, we associate an individual's attractiveness with the strategy persistence, which characterizes how frequently he changes his strategy. We introduce a preferential parameter α to describe the nonlinear correlation between the selection probability and the strategy persistence and the memory length of individuals M into the evolutionary games. We investigate the effects of α and M on cooperation. Our results show that cooperation could be promoted when α > 0 and at the same time M > 1, which corresponds to the situation that individuals are inclined to select their neighbors with relatively higher persistence levels during the evolution. Moreover, we find that the cooperation level could reach the maximum at an optimal memory length when α > 0. Our work sheds light on how to promote cooperation through preferential selection based on strategy persistence and a limited memory length.

  16. The hormetic zone: an ecological and evolutionary perspective based upon habitat characteristics and fitness selection.

    Science.gov (United States)

    Parsons, P A

    2001-12-01

    Fitness varies nonlinearly with environmental variables such as temperature, water availability, and nutrition, with maximum fitness at intermediate levels between more stressful extremes. For environmental agents that are highly toxic at exposures that substantially exceed background levels, fitness is maximized at concentrations near zero--a phenomenon often referred to as hormesis. Two main components are suggested: (1) background hormesis, which derives from the direct adaptation of organisms to their habitats; and (2) stress-derived hormonesis, which derives from metabolic reserves that are maintained as an adaptation to environmental stresses through evolutionary time. These reserves provide protection from lesser correlated stresses. This article discusses illustrative examples, including ethanol and ionizing radiation, aimed at placing hormesis into an ecological and evolutionary context. A unifying approach comes from fitness-stress continua that underlie responses to abiotic variables, whereby selection for maximum metabolic efficiency and hence fitness in adaptation to habitats in nature underlies hormetic zones. Within this reductionist model, more specific metabolic mechanisms to explain hormesis are beginning to emerge, depending upon the agent and the taxon in question. Some limited research possibilities based upon this evolutionary perspective are indicated.

  17. Understanding herding based on a co-evolutionary model for strategy and game structure

    International Nuclear Information System (INIS)

    Wang, Tao; Huang, Keke; Cheng, Yuan; Zheng, Xiaoping

    2015-01-01

    Highlights: •We model herding effect in emergency from perspective of evolutionary game theory. •Rational subpopulation survives only when the game parameter is significantly large. •Herding effect may arise if the relative rewarding for rational agents is small. •Increasing the relative rewarding for rational agents will prevent herding effect. •The evolution result is unstable if the game parameter approaches critical points. -- Abstract: So far, there has been no conclusion on the mechanism for herding, which is often discussed in the academia. Assuming escaping behavior of individuals in emergency is rational rather than out of panic according to recent findings in social psychology, we investigate the behavioral evolution of large crowds from the perspective of evolutionary game theory. Specifically, evolution of the whole population divided into two subpopulations, namely the co-evolution of strategy and game structure, is numerically simulated based on the game theoretical models built and the evolutionary rule designed, and a series of phenomena including extinction of one subpopulation and herding effect are predicted in the proposed framework. Furthermore, if the rewarding for rational agents becomes significantly larger than that for emotional ones, herding effect will disappear. It is exciting that some phase transition points with interesting properties for the system can be found. In addition, our model framework is able to explain the fact that it is difficult for mavericks to prevail in society. The current results of this work will be helpful in understanding and restraining herding effect in real life

  18. USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

    Science.gov (United States)

    Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

  19. Evolutionary patterns of RNA-based duplication in non-mammalian chordates.

    Directory of Open Access Journals (Sweden)

    Ming Chen

    Full Text Available The role of RNA-based duplication, or retroposition, in the evolution of new gene functions in mammals, plants, and Drosophila has been widely reported. However, little is known about RNA-based duplication in non-mammalian chordates. In this study, we screened ten non-mammalian chordate genomes for retrocopies and investigated their evolutionary patterns. We identified numerous retrocopies in these species. Examination of the age distribution of these retrocopies revealed no burst of young retrocopies in ancient chordate species. Upon comparing these non-mammalian chordate species to the mammalian species, we observed that a larger fraction of the non-mammalian retrocopies was under strong evolutionary constraints than mammalian retrocopies are, as evidenced by signals of purifying selection and expression profiles. For the Western clawed frog, Medaka, and Sea squirt, many retrogenes have evolved gonad and brain expression patterns, similar to what was observed in human. Testing of retrogene movement in the Medaka genome, where the nascent sex chrosomes have been well assembled, did not reveal any significant gene movement. Taken together, our analyses demonstrate that RNA-based duplication generates many functional genes and can make a significant contribution to the evolution of non-mammalian genomes.

  20. Pipe break prediction based on evolutionary data-driven methods with brief recorded data

    International Nuclear Information System (INIS)

    Xu Qiang; Chen Qiuwen; Li Weifeng; Ma Jinfeng

    2011-01-01

    Pipe breaks often occur in water distribution networks, imposing great pressure on utility managers to secure stable water supply. However, pipe breaks are hard to detect by the conventional method. It is therefore necessary to develop reliable and robust pipe break models to assess the pipe's probability to fail and then to optimize the pipe break detection scheme. In the absence of deterministic physical models for pipe break, data-driven techniques provide a promising approach to investigate the principles underlying pipe break. In this paper, two data-driven techniques, namely Genetic Programming (GP) and Evolutionary Polynomial Regression (EPR) are applied to develop pipe break models for the water distribution system of Beijing City. The comparison with the recorded pipe break data from 1987 to 2005 showed that the models have great capability to obtain reliable predictions. The models can be used to prioritize pipes for break inspection and then improve detection efficiency.

  1. Planning the expansion of transmission with evolutionary programming; Planeacion de la expansion de transmision con programacion evolutiva

    Energy Technology Data Exchange (ETDEWEB)

    Ceciliano Meza, Jose Luis; Nieva Gomez, Rolando [Instituto de Investigaciones Electricas, Temixco, Morelos (Mexico)

    1999-07-01

    A method of evolutionary programming for the planning of transmission networks in electrical power systems is presented. This is a whole problem mixed and nonlinear, with a combinatory nature that leads to a very large number of possible solutions for electrical systems of medium and large scale. The problem of transmission planning is described briefly and later it is formulated in mathematical terms. The proposed algorithm of evolutionary programming is applied to a large scale network that is representative of the Mexican electrical system. [Spanish] Se presenta un metodo de programacion evolutiva para la planeacion de redes de transmision en sistemas electricos de potencia. Este es un problema entero mixto y no lineal, con una naturaleza combinatoria que conduce a un numero muy grande de soluciones posibles para sistemas electricos de mediana y gran escala. Se describe brevemente el problema de planeacion de transmision y posteriormente se formula en terminos matematicos. El algoritmo propuesto de programacion evolutiva se aplica a una red electrica de gran escala que es representativa del sistema electrico Mexicano.

  2. Chaotic Multiobjective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Hui Lu

    2014-01-01

    Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.

  3. Time warping of evolutionary distant temporal gene expression data based on noise suppression

    Directory of Open Access Journals (Sweden)

    Papatsenko Dmitri

    2009-10-01

    Full Text Available Abstract Background Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution. Results We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae and fission (Schizosaccharomyces pombe yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment. Conclusion Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

  4. Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

    Science.gov (United States)

    Xu, Weijia; Ozer, Stuart; Gutell, Robin R

    2009-01-01

    With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

  5. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Zhang Huifeng; Zhou Jianzhong; Zhang Yongchuan; Lu Youlin; Wang Yongqiang

    2013-01-01

    Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  6. Evolutionary-Hierarchical Bases of the Formation of Cluster Model of Innovation Economic Development

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

    Full Text Available The functioning of a modern economic system is based on the interaction of objects of different hierarchical levels. Thus, the problem of the study of innovation processes taking into account the mutual influence of the activities of these economic actors becomes important. The paper dwells evolutionary basis for the formation of models of innovation development on the basis of micro and macroeconomic analysis. Most of the concepts recognized that despite a big number of diverse models, the coordination of the relations between economic agents is of crucial importance for the successful innovation development. According to the results of the evolutionary-hierarchical analysis, the authors reveal key phases of the development of forms of business cooperation, science and government in the domestic economy. It has become the starting point of the conception of the characteristics of the interaction in the cluster models of innovation development of the economy. Considerable expectancies on improvement of the national innovative system are connected with the development of cluster and network structures. The main objective of government authorities is the formation of mechanisms and institutions that will foster cooperation between members of the clusters. The article explains that the clusters cannot become the factors in the growth of the national economy, not being an effective tool for interaction between the actors of the regional innovative systems.

  7. Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm

    International Nuclear Information System (INIS)

    Ahmadi, Pouria; Rosen, Marc A.; Dincer, Ibrahim

    2012-01-01

    A comprehensive thermodynamic modeling and optimization is reported of a polygeneration energy system for the simultaneous production of heating, cooling, electricity and hot water from a common energy source. This polygeneration system is composed of four major parts: gas turbine (GT) cycle, Rankine cycle, absorption cooling cycle and domestic hot water heater. A multi-objective optimization method based on an evolutionary algorithm is applied to determine the best design parameters for the system. The two objective functions utilized in the analysis are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized by using an evolutionary algorithm. To provide a deeper insight, the Pareto frontier is shown for multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. Finally, a sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO 2 emission and exergy efficiency.

  8. Towards Behavior Control for Evolutionary Robot Based on RL with ENN

    Directory of Open Access Journals (Sweden)

    Jingan Yang

    2012-03-01

    Full Text Available This paper proposes a behavior-switching control strategy of anevolutionary robotics based on Artificial NeuralNetwork (ANN and Genetic Algorithms (GA. This method is able not only to construct thereinforcement learning models for autonomous robots and evolutionary robot modules thatcontrol behaviors and reinforcement learning environments, and but also to perform thebehavior-switching control and obstacle avoidance of an evolutionary robotics (ER intime-varying environments with static and moving obstacles by combining ANN and GA.The experimental results on thebasic behaviors and behavior-switching control have demonstrated that ourmethod can perform the decision-making strategy and parameters set opimization ofFNN and GA by learning and can escape successfully from the trap of a localminima and avoid \\emph{"motion deadlock" status} of humanoid soccer robotics agents,and reduce the oscillation of the planned trajectory betweenthe multiple obstacles by crossover and mutation. Some results of the proposed algorithmhave been successfully applied to our simulation humanoid robotics soccer team CIT3Dwhich won \\emph{the 1st prize} of RoboCup Championship and ChinaOpen2010 (July 2010 and \\emph{the $2^{nd}$ place}of the official RoboCup World Championship on 5-11 July, 2011 in Istanbul, Turkey.As compared with the conventional behavior network and the adaptive behavior method,the genetic encoding complexity of our algorithm is simplified, and the networkperformance and the {\\em convergence rate $\\rho$} have been greatlyimproved.

  9. Evolutionary Process for Integrating COTS-Based Systems (EPIC): An Overview. Key Elements in Building, Fielding, and Supporting Commercial-off-the-Shelf (COTS) Based Solutions

    National Research Council Canada - National Science Library

    Albert, Cecilia

    2002-01-01

    .... The Evolutionary Process for Integrating COTS-based systems (EPIC) redefines acquisition, management, and engineering practices to more effectively leverage the COTS marketplace and other sources of pre-existing components...

  10. Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

    Science.gov (United States)

    Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

    2018-03-01

    This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

  11. Evolutionary principles and their practical application.

    Science.gov (United States)

    Hendry, Andrew P; Kinnison, Michael T; Heino, Mikko; Day, Troy; Smith, Thomas B; Fitt, Gary; Bergstrom, Carl T; Oakeshott, John; Jørgensen, Peter S; Zalucki, Myron P; Gilchrist, George; Southerton, Simon; Sih, Andrew; Strauss, Sharon; Denison, Robert F; Carroll, Scott P

    2011-03-01

    Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.

  12. Structure-based Markov random field model for representing evolutionary constraints on functional sites.

    Science.gov (United States)

    Jeong, Chan-Seok; Kim, Dongsup

    2016-02-24

    Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

  13. Energy demand forecasting in Iranian metal industry using linear and nonlinear models based on evolutionary algorithms

    International Nuclear Information System (INIS)

    Piltan, Mehdi; Shiri, Hiva; Ghaderi, S.F.

    2012-01-01

    Highlights: ► Investigating different fitness functions for evolutionary algorithms in energy forecasting. ► Energy forecasting of Iranian metal industry by value added, energy prices, investment and employees. ► Using real-coded instead of binary-coded genetic algorithm decreases energy forecasting error. - Abstract: Developing energy-forecasting models is known as one of the most important steps in long-term planning. In order to achieve sustainable energy supply toward economic development and social welfare, it is required to apply precise forecasting model. Applying artificial intelligent models for estimation complex economic and social functions is growing up considerably in many researches recently. In this paper, energy consumption in industrial sector as one of the critical sectors in the consumption of energy has been investigated. Two linear and three nonlinear functions have been used in order to forecast and analyze energy in the Iranian metal industry, Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) are applied to attain parameters of the models. The Real-Coded Genetic Algorithm (RCGA) has been developed based on real numbers, which is introduced as a new approach in the field of energy forecasting. In the proposed model, electricity consumption has been considered as a function of different variables such as electricity tariff, manufacturing value added, prevailing fuel prices, the number of employees, the investment in equipment and consumption in the previous years. Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Deviation (MAD) and Mean Absolute Percent Error (MAPE) are the four functions which have been used as the fitness function in the evolutionary algorithms. The results show that the logarithmic nonlinear model using PSO algorithm with 1.91 error percentage has the best answer. Furthermore, the prediction of electricity consumption in industrial sector of Turkey and also Turkish industrial sector

  14. Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Chien-Ho Ko

    2013-01-01

    Full Text Available Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs, Fuzzy Logic (FL, and Neural Networks (NNs. FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  15. Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

    Science.gov (United States)

    Ko, Chien-Ho

    2013-01-01

    Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  16. An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts.

    Science.gov (United States)

    Jiang, Shouyong; Yang, Shengxiang

    2016-02-01

    The multiobjective evolutionary algorithm based on decomposition (MOEA/D) has been shown to be very efficient in solving multiobjective optimization problems (MOPs). In practice, the Pareto-optimal front (POF) of many MOPs has complex characteristics. For example, the POF may have a long tail and sharp peak and disconnected regions, which significantly degrades the performance of MOEA/D. This paper proposes an improved MOEA/D for handling such kind of complex problems. In the proposed algorithm, a two-phase strategy (TP) is employed to divide the whole optimization procedure into two phases. Based on the crowdedness of solutions found in the first phase, the algorithm decides whether or not to delicate computational resources to handle unsolved subproblems in the second phase. Besides, a new niche scheme is introduced into the improved MOEA/D to guide the selection of mating parents to avoid producing duplicate solutions, which is very helpful for maintaining the population diversity when the POF of the MOP being optimized is discontinuous. The performance of the proposed algorithm is investigated on some existing benchmark and newly designed MOPs with complex POF shapes in comparison with several MOEA/D variants and other approaches. The experimental results show that the proposed algorithm produces promising performance on these complex problems.

  17. Origin and evolutionary history of freshwater Rhodophyta: further insights based on phylogenomic evidence.

    Science.gov (United States)

    Nan, Fangru; Feng, Jia; Lv, Junping; Liu, Qi; Fang, Kunpeng; Gong, Chaoyan; Xie, Shulian

    2017-06-07

    Freshwater representatives of Rhodophyta were sampled and the complete chloroplast and mitochondrial genomes were determined. Characteristics of the chloroplast and mitochondrial genomes were analyzed and phylogenetic relationship of marine and freshwater Rhodophyta were reconstructed based on the organelle genomes. The freshwater member Compsopogon caeruleus was determined for the largest chloroplast genome among multicellular Rhodophyta up to now. Expansion and subsequent reduction of both the genome size and GC content were observed in the Rhodophyta except for the freshwater Compsopogon caeruleus. It was inferred that the freshwater members of Rhodophyta occurred through diverse origins based on evidence of genome size, GC-content, phylogenomic analysis and divergence time estimation. The freshwater species Compsopogon caeruleus and Hildenbrandia rivularis originated and evolved independently at the inland water, whereas the Bangia atropurpurea, Batrachospermum arcuatum and Thorea hispida are derived from the marine relatives. The typical freshwater representatives Thoreales and Batrachospermales are probably derived from the marine relative Palmaria palmata at approximately 415-484 MYA. The origin and evolutionary history of freshwater Rhodophyta needs to be testified with more organelle genome sequences and wider global sampling.

  18. Evolutionary Agent-based Models to design distributed water management strategies

    Science.gov (United States)

    Giuliani, M.; Castelletti, A.; Reed, P. M.

    2012-12-01

    There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

  19. Electrochemical impedance spectroscopy of supercapacitors: A novel analysis approach using evolutionary programming

    Science.gov (United States)

    Oz, Alon; Hershkovitz, Shany; Tsur, Yoed

    2014-11-01

    In this contribution we present a novel approach to analyze impedance spectroscopy measurements of supercapacitors. Transforming the impedance data into frequency-dependent capacitance allows us to use Impedance Spectroscopy Genetic Programming (ISGP) in order to find the distribution function of relaxation times (DFRT) of the processes taking place in the tested device. Synthetic data was generated in order to demonstrate this technique and a model for supercapacitor ageing process has been obtained.

  20. Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul

    2015-04-01

    The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Optimal design of a spherical parallel manipulator based on kinetostatic performance using evolutionary techniques

    Energy Technology Data Exchange (ETDEWEB)

    Daneshmand, Morteza [University of Tartu, Tartu (Estonia); Saadatzi, Mohammad Hossein [Colorado School of Mines, Golden (United States); Kaloorazi, Mohammad Hadi [École de Technologie Supérieur, Montréal (Canada); Masouleh, Mehdi Tale [University of Tehran, Tehran (Iran, Islamic Republic of); Anbarjafari, Gholamreza [Hasan Kalyoncu University, Gaziantep (Turkmenistan)

    2016-03-15

    This study aims to provide an optimal design for a Spherical parallel manipulator (SPM), namely, the Agile Eye. This aim is approached by investigating kinetostatic performance and workspace and searching for the most promising design. Previously recommended designs are examined to determine whether they provide acceptable kinetostatic performance and workspace. Optimal designs are provided according to different kinetostatic performance indices, especially kinematic sensitivity. The optimization process is launched based on the concept of the genetic algorithm. A single-objective process is implemented in accordance with the guidelines of an evolutionary algorithm called differential evolution. A multi-objective procedure is then provided following the reasoning of the nondominated sorting genetic algorithm-II. This process results in several sets of Pareto points for reconciliation between kinetostatic performance indices and workspace. The concept of numerous kinetostatic performance indices and the results of optimization algorithms are elaborated. The conclusions provide hints on the provided set of designs and their credibility to provide a well-conditioned workspace and acceptable kinetostatic performance for the SPM under study, which can be well extended to other types of SPMs.

  2. Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2013-01-01

    Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  3. Attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm.

    Science.gov (United States)

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

    In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  4. Towards an evolutionary theory of the origin of life based on kinetics and thermodynamics.

    Science.gov (United States)

    Pascal, Robert; Pross, Addy; Sutherland, John D

    2013-11-06

    A sudden transition in a system from an inanimate state to the living state-defined on the basis of present day living organisms-would constitute a highly unlikely event hardly predictable from physical laws. From this uncontroversial idea, a self-consistent representation of the origin of life process is built up, which is based on the possibility of a series of intermediate stages. This approach requires a particular kind of stability for these stages-dynamic kinetic stability (DKS)-which is not usually observed in regular chemistry, and which is reflected in the persistence of entities capable of self-reproduction. The necessary connection of this kinetic behaviour with far-from-equilibrium thermodynamic conditions is emphasized and this leads to an evolutionary view for the origin of life in which multiplying entities must be associated with the dissipation of free energy. Any kind of entity involved in this process has to pay the energetic cost of irreversibility, but, by doing so, the contingent emergence of new functions is made feasible. The consequences of these views on the studies of processes by which life can emerge are inferred.

  5. Remembering the evolutionary Freud.

    Science.gov (United States)

    Young, Allan

    2006-03-01

    Throughout his career as a writer, Sigmund Freud maintained an interest in the evolutionary origins of the human mind and its neurotic and psychotic disorders. In common with many writers then and now, he believed that the evolutionary past is conserved in the mind and the brain. Today the "evolutionary Freud" is nearly forgotten. Even among Freudians, he is regarded to be a red herring, relevant only to the extent that he diverts attention from the enduring achievements of the authentic Freud. There are three ways to explain these attitudes. First, the evolutionary Freud's key work is the "Overview of the Transference Neurosis" (1915). But it was published at an inopportune moment, forty years after the author's death, during the so-called "Freud wars." Second, Freud eventually lost interest in the "Overview" and the prospect of a comprehensive evolutionary theory of psychopathology. The publication of The Ego and the Id (1923), introducing Freud's structural theory of the psyche, marked the point of no return. Finally, Freud's evolutionary theory is simply not credible. It is based on just-so stories and a thoroughly discredited evolutionary mechanism, Lamarckian use-inheritance. Explanations one and two are probably correct but also uninteresting. Explanation number three assumes that there is a fundamental difference between Freud's evolutionary narratives (not credible) and the evolutionary accounts of psychopathology that currently circulate in psychiatry and mainstream journals (credible). The assumption is mistaken but worth investigating.

  6. Evolutionary principles and their practical application

    DEFF Research Database (Denmark)

    Hendry, A. P.; Kinnison, M. T.; Heino, M.

    2011-01-01

    Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles...... are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design...... of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently...

  7. Empirical tests of natural selection-based evolutionary accounts of ADHD: a systematic review.

    Science.gov (United States)

    Thagaard, Marthe S; Faraone, Stephen V; Sonuga-Barke, Edmund J; Østergaard, Søren D

    2016-10-01

    ADHD is a prevalent and highly heritable mental disorder associated with significant impairment, morbidity and increased rates of mortality. This combination of high prevalence and high morbidity/mortality seen in ADHD and other mental disorders presents a challenge to natural selection-based models of human evolution. Several hypotheses have been proposed in an attempt to resolve this apparent paradox. The aim of this study was to review the evidence for these hypotheses. We conducted a systematic review of the literature on empirical investigations of natural selection-based evolutionary accounts for ADHD in adherence with the PRISMA guideline. The PubMed, Embase, and PsycINFO databases were screened for relevant publications, by combining search terms covering evolution/selection with search terms covering ADHD. The search identified 790 records. Of these, 15 full-text articles were assessed for eligibility, and three were included in the review. Two of these reported on the evolution of the seven-repeat allele of the ADHD-associated dopamine receptor D4 gene, and one reported on the results of a simulation study of the effect of suggested ADHD-traits on group survival. The authors of the three studies interpreted their findings as favouring the notion that ADHD-traits may have been associated with increased fitness during human evolution. However, we argue that none of the three studies really tap into the core symptoms of ADHD, and that their conclusions therefore lack validity for the disorder. This review indicates that the natural selection-based accounts of ADHD have not been subjected to empirical test and therefore remain hypothetical.

  8. Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms

    NARCIS (Netherlands)

    Zhao, J.; Basto, Fernandes V.; Jiao, L.; Yevseyeva, I.; Asep, Maulana A.; Li, R.; Bäck, T.H.W.; Tang, T.; Michael, Emmerich T. M.

    2016-01-01

    The receiver operating characteristic (ROC) and detection error tradeoff(DET) curves are frequently used in the machine learning community to analyze the performance of binary classifiers. Recently, the convex-hull-based multiobjective genetic programming algorithm was proposed and successfully

  9. A study of driver's route choice behavior based on evolutionary game theory.

    Science.gov (United States)

    Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

    2014-01-01

    This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

  10. A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory

    Directory of Open Access Journals (Sweden)

    Xiaowei Jiang

    2014-01-01

    Full Text Available This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

  11. Evolutionary computation in zoology and ecology.

    Science.gov (United States)

    Boone, Randall B

    2017-12-01

    Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species' niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate.

  12. Blockmodeling and the Estimation of Evolutionary Architectural Growth in Major Defense Acquisition Programs

    Science.gov (United States)

    2016-04-30

    attachment probabilities ∑ , 6d. For each interface established in (6c), assign complexity ( wiX ), Connection Option B 6a. Attach X to subsystems...using attachment probabilities ∑ , 6b. For each interface established in (6a), assign complexity ( wiX ), Cost Estimation 7. Estimate the cost for...Connection Option A does not condition interface complexities based on the connected subsystems’ positions of assignment (i.e., wiX ,l), as any

  13. ERC analysis: web-based inference of gene function via evolutionary rate covariation.

    Science.gov (United States)

    Wolfe, Nicholas W; Clark, Nathan L

    2015-12-01

    The recent explosion of comparative genomics data presents an unprecedented opportunity to construct gene networks via the evolutionary rate covariation (ERC) signature. ERC is used to identify genes that experienced similar evolutionary histories, and thereby draws functional associations between them. The ERC Analysis website allows researchers to exploit genome-wide datasets to infer novel genes in any biological function and to explore deep evolutionary connections between distinct pathways and complexes. The website provides five analytical methods, graphical output, statistical support and access to an increasing number of taxonomic groups. Analyses and data at http://csb.pitt.edu/erc_analysis/ nclark@pitt.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Fixation Probabilities of Evolutionary Graphs Based on the Positions of New Appearing Mutants

    Directory of Open Access Journals (Sweden)

    Pei-ai Zhang

    2014-01-01

    Full Text Available Evolutionary graph theory is a nice measure to implement evolutionary dynamics on spatial structures of populations. To calculate the fixation probability is usually regarded as a Markov chain process, which is affected by the number of the individuals, the fitness of the mutant, the game strategy, and the structure of the population. However the position of the new mutant is important to its fixation probability. Here the position of the new mutant is laid emphasis on. The method is put forward to calculate the fixation probability of an evolutionary graph (EG of single level. Then for a class of bilevel EGs, their fixation probabilities are calculated and some propositions are discussed. The conclusion is obtained showing that the bilevel EG is more stable than the corresponding one-rooted EG.

  15. Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

    Science.gov (United States)

    Wang, Lin; Liu, Gaozhi

    2018-02-01

    This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

  16. Influence of TCSC Devices on Congestion Management in a Deregulated Power System Using Evolutionary Programming Technique

    Science.gov (United States)

    Ananthichristy, A., Dr.; Elanthirayan, R.; Brindha, R., Dr.; Siddhiq, M. S.; Venkatesh, N.; Harshit, M. V.; Nikhilreddy, M.

    2018-04-01

    Congestion management is one of the technical challenges in power system deregulation. In deregulated electricity market it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. Transmission congestion occurs when there is insufficient transmission capacity to simultaneously accommodate all constraints for transmission of a line. Flexible Alternative Current Transmission System (FACTS) devices can be an alternative to reduce the flows in the heavily loaded lines, resulting in an increased loadability, low system loss, improved stability of the network, reduced cost of production and fulfilled contractual requirement by controlling the power flow in the network. A method to determine the optimal location of FACTS has been suggested based on reduction of total system VAR power losses. The simulation was done on IEEE 14 bus system and results were obtained.

  17. A new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting

    International Nuclear Information System (INIS)

    Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo

    2008-01-01

    In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)

  18. Identify alternative splicing events based on position-specific evolutionary conservation.

    Directory of Open Access Journals (Sweden)

    Liang Chen

    Full Text Available The evolution of eukaryotes is accompanied by the increased complexity of alternative splicing which greatly expands genome information. One of the greatest challenges in the post-genome era is a complete revelation of human transcriptome with consideration of alternative splicing. Here, we introduce a comparative genomics approach to systemically identify alternative splicing events based on the differential evolutionary conservation between exons and introns and the high-quality annotation of the ENCODE regions. Specifically, we focus on exons that are included in some transcripts but are completely spliced out for others and we call them conditional exons. First, we characterize distinguishing features among conditional exons, constitutive exons and introns. One of the most important features is the position-specific conservation score. There are dramatic differences in conservation scores between conditional exons and constitutive exons. More importantly, the differences are position-specific. For flanking intronic regions, the differences between conditional exons and constitutive exons are also position-specific. Using the Random Forests algorithm, we can classify conditional exons with high specificities (97% for the identification of conditional exons from intron regions and 95% for the classification of known exons and fair sensitivities (64% and 32% respectively. We applied the method to the human genome and identified 39,640 introns that actually contain conditional exons and classified 8,813 conditional exons from the current RefSeq exon list. Among those, 31,673 introns containing conditional exons and 5,294 conditional exons classified from known exons cannot be inferred from RefSeq, UCSC or Ensembl annotations. Some of these de novo predictions were experimentally verified.

  19. Evolutionary fitness as a function of pubertal age in 22 subsistence-based traditional societies

    Directory of Open Access Journals (Sweden)

    Gawlik Aneta

    2011-06-01

    Full Text Available Abstract Context The age of puberty has fallen over the past 130 years in industrialized, western countries, and this fall is widely referred to as the secular trend for earlier puberty. The current study was undertaken to test two evolutionary theories: (a the reproductive system maximizes the number of offspring in response to positive environmental cues in terms of energy balance, and (b early puberty is a trade-off response for high mortality rate and reduced resource availability. Methods Using a sample of 22 natural-fertility societies of mostly tropical foragers, horticulturalists, and pastoralists from Africa, South America, Australia, and Southeastern Asia, this study compares indices of adolescence growth and menarche with those of fertility fitness in these non-industrial, traditional societies. Results The average age at menarche correlated with the first reproduction, but did not correlate with the total fertility rate TFR or reproductive fitness. The age at menarche correlated negatively with their average adult body mass, and the average adult body weight positively correlated with reproductive fitness. Survivorship did not correlate with the age at menarche or age indices of the adolescent growth spurt. The population density correlated positively with the age at first reproduction, but not with menarche age, TFR, or reproductive fitness. Conclusions Based on our analyses, we reject the working hypotheses that reproductive fitness is enhanced in societies with early puberty or that early menarche is an adaptive response to greater mortality risk. Whereas body mass is a measure of resources is tightly associated with fitness, the age of menarche is not.

  20. Evolutionary History of Saber-Toothed Cats Based on Ancient Mitogenomics.

    Science.gov (United States)

    Paijmans, Johanna L A; Barnett, Ross; Gilbert, M Thomas P; Zepeda-Mendoza, M Lisandra; Reumer, Jelle W F; de Vos, John; Zazula, Grant; Nagel, Doris; Baryshnikov, Gennady F; Leonard, Jennifer A; Rohland, Nadin; Westbury, Michael V; Barlow, Axel; Hofreiter, Michael

    2017-11-06

    Saber-toothed cats (Machairodontinae) are among the most widely recognized representatives of the now largely extinct Pleistocene megafauna. However, many aspects of their ecology, evolution, and extinction remain uncertain. Although ancient-DNA studies have led to huge advances in our knowledge of these aspects of many other megafauna species (e.g., mammoths and cave bears), relatively few ancient-DNA studies have focused on saber-toothed cats [1-3], and they have been restricted to short fragments of mitochondrial DNA. Here we investigate the evolutionary history of two lineages of saber-toothed cats (Smilodon and Homotherium) in relation to living carnivores and find that the Machairodontinae form a well-supported clade that is distinct from all living felids. We present partial mitochondrial genomes from one S. populator sample and three Homotherium sp. samples, including the only Late Pleistocene Homotherium sample from Eurasia [4]. We confirm the identification of the unique Late Pleistocene European fossil through ancient-DNA analyses, thus strengthening the evidence that Homotherium occurred in Europe over 200,000 years later than previously believed. This in turn forces a re-evaluation of its demography and extinction dynamics. Within the Machairodontinae, we find a deep divergence between Smilodon and Homotherium (∼18 million years) but limited diversity between the American and European Homotherium specimens. The genetic data support the hypothesis that all Late Pleistocene (or post-Villafrancian) Homotherium should be considered a single species, H. latidens, which was previously proposed based on morphological data [5, 6]. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. An Extensible Component-Based Multi-Objective Evolutionary Algorithm Framework

    DEFF Research Database (Denmark)

    Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

    2017-01-01

    The ability to easily modify the problem definition is currently missing in Multi-Objective Evolutionary Algorithms (MOEA). Existing MOEA frameworks do not support dynamic addition and extension of the problem formulation. The existing frameworks require a re-specification of the problem definition...

  2. Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences.

    Science.gov (United States)

    Zheng, Xiaoyan; Cai, Danying; Potter, Daniel; Postman, Joseph; Liu, Jing; Teng, Yuanwen

    2014-11-01

    Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence datasets. Phylogenetic trees based on both cpDNA and nuclear LFY2int2-N (LN) data resulted in poor resolution, especially, only five primary species were monophyletic in the LN tree. A phylogenetic network of LN suggested that reticulation caused by hybridization is one of the major evolutionary processes for Pyrus species. Polytomies of the gene trees and star-like structure of cpDNA networks suggested rapid radiation is another major evolutionary process, especially for the occidental species. Pyrus calleryana and P. regelii were the earliest diverged Pyrus species. Two North African species, P. cordata, P. spinosa and P. betulaefolia were descendent of primitive stock Pyrus species and still share some common molecular characters. Southwestern China, where a large number of P. pashia populations are found, is probably the most important diversification center of Pyrus. More accessions and nuclear genes are needed for further understanding the evolutionary histories of Pyrus. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Multi-step-prediction of chaotic time series based on co-evolutionary recurrent neural network

    International Nuclear Information System (INIS)

    Ma Qianli; Zheng Qilun; Peng Hong; Qin Jiangwei; Zhong Tanwei

    2008-01-01

    This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability of recurrent neural network to incorporate past experience due to internal recurrence. The effectiveness of CERNN is evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey-Glass series and real-world sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic time series

  4. Investigation of Evolutionary Pheromone Communication Based on External Measurement and Emergence of Swarm Intelligence

    OpenAIRE

    川村, 秀憲; 山本, 雅人; 大内, 東

    2001-01-01

    In this paper, we focus on the emergence phenomenon related with artificial pheromone communication and swarm intelligence among many agents in Ants War environment, in which two colonies of artificial ant agents compete for the limited number of food items in order to survive in evolutionary process. The purpose of this research is to clarify the emerging process of communication and the relationship between communication and swarm intelligence. For investigation of communication, we introdu...

  5. A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

    Science.gov (United States)

    2011-03-01

    pertinent example of the application of Evolutionary Algorithms to pattern recognition comes from Radtke et al. [130]. The authors apply Multi- Objective...J., T. Zseby, and B. Claise. S. Zander,” Requirements for IP Flow Information Export (IPFIX). Technical report, RFC 3917, October 2004. [130] Radtke ...hal.inria.fr/inria-00104200/en/. [131] Radtke , P.V.W., T. Wong, and R. Sabourin. “A multi-objective memetic al- gorithm for intelligent feature extraction

  6. Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

    Directory of Open Access Journals (Sweden)

    Nolan Priedigkeit

    2015-02-01

    Full Text Available Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC, is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting "disease map" network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.

  7. Evolutionary thinking

    Science.gov (United States)

    Hunt, Tam

    2014-01-01

    Evolution as an idea has a lengthy history, even though the idea of evolution is generally associated with Darwin today. Rebecca Stott provides an engaging and thoughtful overview of this history of evolutionary thinking in her 2013 book, Darwin's Ghosts: The Secret History of Evolution. Since Darwin, the debate over evolution—both how it takes place and, in a long war of words with religiously-oriented thinkers, whether it takes place—has been sustained and heated. A growing share of this debate is now devoted to examining how evolutionary thinking affects areas outside of biology. How do our lives change when we recognize that all is in flux? What can we learn about life more generally if we study change instead of stasis? Carter Phipps’ book, Evolutionaries: Unlocking the Spiritual and Cultural Potential of Science's Greatest Idea, delves deep into this relatively new development. Phipps generally takes as a given the validity of the Modern Synthesis of evolutionary biology. His story takes us into, as the subtitle suggests, the spiritual and cultural implications of evolutionary thinking. Can religion and evolution be reconciled? Can evolutionary thinking lead to a new type of spirituality? Is our culture already being changed in ways that we don't realize by evolutionary thinking? These are all important questions and Phipps book is a great introduction to this discussion. Phipps is an author, journalist, and contributor to the emerging “integral” or “evolutionary” cultural movement that combines the insights of Integral Philosophy, evolutionary science, developmental psychology, and the social sciences. He has served as the Executive Editor of EnlightenNext magazine (no longer published) and more recently is the co-founder of the Institute for Cultural Evolution, a public policy think tank addressing the cultural roots of America's political challenges. What follows is an email interview with Phipps. PMID:26478766

  8. Evolutionary Demography

    DEFF Research Database (Denmark)

    Levitis, Daniel

    2015-01-01

    of biological and cultural evolution. Demographic variation within and among human populations is influenced by our biology, and therefore by natural selection and our evolutionary background. Demographic methods are necessary for studying populations of other species, and for quantifying evolutionary fitness......Demography is the quantitative study of population processes, while evolution is a population process that influences all aspects of biological organisms, including their demography. Demographic traits common to all human populations are the products of biological evolution or the interaction...

  9. Exercise Based- Pain Relief Program

    DEFF Research Database (Denmark)

    Zadeh, Mahdi Hossein

    in the current study was to use exercise induced- muscle damage followed by ECC as an acute pain model and observe its effects on the sensitivity of the nociceptive system and blood supply in healthy subjects. Then, the effect of a repeated bout of the same exercise as a healthy pain relief strategy......Exercise-based pain management programs are suggested for relieving from musculoskeletal pain; however the pain experienced after unaccustomed, especially eccentric exercise (ECC) alters people´s ability to participate in therapeutic exercises. Subsequent muscle pain after ECC has been shown...... to cause localized pressure pain and hyperalgesia. A prior bout of ECC has been repeatedly reported to produce a protective adaptation known as repeated bout effect (RBE). One of the main scopes of the current project was to investigate the adaptations by which the RBE can be resulted from. The approach...

  10. Comparison of evolutionary computation algorithms for solving bi ...

    Indian Academy of Sciences (India)

    failure probability. Multiobjective Evolutionary Computation algorithms (MOEAs) are well-suited for Multiobjective task scheduling on heterogeneous environment. The two Multi-Objective Evolutionary Algorithms such as Multiobjective Genetic. Algorithm (MOGA) and Multiobjective Evolutionary Programming (MOEP) with.

  11. A Study on Standard Competition with Network Effect Based on Evolutionary Game Model

    Science.gov (United States)

    Wang, Ye; Wang, Bingdong; Li, Kangning

    Owing to networks widespread in modern society, standard competition with network effect is now endowed with new connotation. This paper aims to study the impact of network effect on standard competition; it is organized in the mode of "introduction-model setup-equilibrium analysis-conclusion". Starting from a well-structured model of evolutionary game, it is then extended to a dynamic analysis. This article proves both theoretically and empirically that whether or not a standard can lead the market trends depends on the utility it would bring, and the author also discusses some advisable strategies revolving around the two factors of initial position and border break.

  12. Evolutionary strategy to develop learning-based decision systems. Application to breast cancer and liver fibrosis stadialization.

    Science.gov (United States)

    Gorunescu, Florin; Belciug, Smaranda

    2014-06-01

    The purpose of this paper is twofold: first, to propose an evolutionary-based method for building a decision model and, second, to assess and validate the model's performance using five different real-world medical datasets (breast cancer and liver fibrosis) by comparing it with state-of-the-art machine learning techniques. The evolutionary-inspired approach has been used to develop the learning-based decision model in the following manner: the hybridization of algorithms has been considered as "crossover", while the development of new variants which can be thought of as "mutation". An appropriate hierarchy of the component algorithms was established based on a statistically built fitness measure. A synergetic decision-making process, based on a weighted voting system, involved the collaboration between the selected algorithms in making the final decision. Well-established statistical performance measures and comparison tests have been extensively used to design and implement the model. Finally, the proposed method has been tested on five medical datasets, out of which four publicly available, and contrasted with state-of-the-art techniques, showing its efficiency in supporting the medical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

    Science.gov (United States)

    List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

    2016-08-20

    For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to

  14. Applying Evolutionary Prototyping In Developing LMIS: A Spatial Web-Based System For Land Management

    Science.gov (United States)

    Agustiono, W.

    2018-01-01

    Software development project is a difficult task. Especially for software designed to comply with regulations that are constantly being introduced or changed, it is almost impossible to make just one change during the development process. Even if it is possible, nonetheless, the developers may take bulk of works to fix the design to meet specified needs. This iterative work also means that it takes additional time and potentially leads to failing to meet the original schedule and budget. In such inevitable changes, it is essential for developers to carefully consider and use an appropriate method which will help them carry out software project development. This research aims to examine the implementation of a software development method called evolutionary prototyping for developing software for complying regulation. It investigates the development of Land Management Information System (pseudonym), initiated by the Australian government, for use by farmers to meet regulatory demand requested by Soil and Land Conservation Act. By doing so, it sought to provide understanding the efficacy of evolutionary prototyping in helping developers address frequent changing requirements and iterative works but still within schedule. The findings also offer useful practical insights for other developers who seek to build similar regulatory compliance software.

  15. An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction

    Science.gov (United States)

    Dash, Rajashree

    2017-11-01

    Forecasting purchasing power of one currency with respect to another currency is always an interesting topic in the field of financial time series prediction. Despite the existence of several traditional and computational models for currency exchange rate forecasting, there is always a need for developing simpler and more efficient model, which will produce better prediction capability. In this paper, an evolutionary framework is proposed by using an improved shuffled frog leaping (ISFL) algorithm with a computationally efficient functional link artificial neural network (CEFLANN) for prediction of currency exchange rate. The model is validated by observing the monthly prediction measures obtained for three currency exchange data sets such as USD/CAD, USD/CHF, and USD/JPY accumulated within same period of time. The model performance is also compared with two other evolutionary learning techniques such as Shuffled frog leaping algorithm and Particle Swarm optimization algorithm. Practical analysis of results suggest that, the proposed model developed using the ISFL algorithm with CEFLANN network is a promising predictor model for currency exchange rate prediction compared to other models included in the study.

  16. Evolutionary Expectations

    DEFF Research Database (Denmark)

    Nash, Ulrik William

    2014-01-01

    , they are correlated among people who share environments because these individuals satisfice within their cognitive bounds by using cues in order of validity, as opposed to using cues arbitrarily. Any difference in expectations thereby arise from differences in cognitive ability, because two individuals with identical...... cognitive bounds will perceive business opportunities identically. In addition, because cues provide information about latent causal structures of the environment, changes in causality must be accompanied by changes in cognitive representations if adaptation is to be maintained. The concept of evolutionary......The concept of evolutionary expectations descends from cue learning psychology, synthesizing ideas on rational expectations with ideas on bounded rationality, to provide support for these ideas simultaneously. Evolutionary expectations are rational, but within cognitive bounds. Moreover...

  17. Evolutionary Awareness

    Directory of Open Access Journals (Sweden)

    Gregory Gorelik

    2014-10-01

    Full Text Available In this article, we advance the concept of “evolutionary awareness,” a metacognitive framework that examines human thought and emotion from a naturalistic, evolutionary perspective. We begin by discussing the evolution and current functioning of the moral foundations on which our framework rests. Next, we discuss the possible applications of such an evolutionarily-informed ethical framework to several domains of human behavior, namely: sexual maturation, mate attraction, intrasexual competition, culture, and the separation between various academic disciplines. Finally, we discuss ways in which an evolutionary awareness can inform our cross-generational activities—which we refer to as “intergenerational extended phenotypes”—by helping us to construct a better future for ourselves, for other sentient beings, and for our environment.

  18. Performance-based planning and programming guidebook.

    Science.gov (United States)

    2013-09-01

    "Performance-based planning and programming (PBPP) refers to the application of performance management principles within the planning and programming processes of transportation agencies to achieve desired performance outcomes for the multimodal tran...

  19. A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

    Directory of Open Access Journals (Sweden)

    Jing Chen

    2013-01-01

    Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

  20. The influence of selection on the evolutionary distance estimated from the base changes observed between homologous nucleotide sequences.

    Science.gov (United States)

    Otsuka, J; Kawai, Y; Sugaya, N

    2001-11-21

    In most studies of molecular evolution, the nucleotide base at a site is assumed to change with the apparent rate under functional constraint, and the comparison of base changes between homologous genes is thought to yield the evolutionary distance corresponding to the site-average change rate multiplied by the divergence time. However, this view is not sufficiently successful in estimating the divergence time of species, but mostly results in the construction of tree topology without a time-scale. In the present paper, this problem is investigated theoretically by considering that observed base changes are the results of comparing the survivals through selection of mutated bases. In the case of weak selection, the time course of base changes due to mutation and selection can be obtained analytically, leading to a theoretical equation showing how the selection has influence on the evolutionary distance estimated from the enumeration of base changes. This result provides a new method for estimating the divergence time more accurately from the observed base changes by evaluating both the strength of selection and the mutation rate. The validity of this method is verified by analysing the base changes observed at the third codon positions of amino acid residues with four-fold codon degeneracy in the protein genes of mammalian mitochondria; i.e. the ratios of estimated divergence times are fairly well consistent with a series of fossil records of mammals. Throughout this analysis, it is also suggested that the mutation rates in mitochondrial genomes are almost the same in different lineages of mammals and that the lineage-specific base-change rates indicated previously are due to the selection probably arising from the preference of transfer RNAs to codons.

  1. Repository-Based Software Engineering Program: Working Program Management Plan

    Science.gov (United States)

    1993-01-01

    Repository-Based Software Engineering Program (RBSE) is a National Aeronautics and Space Administration (NASA) sponsored program dedicated to introducing and supporting common, effective approaches to software engineering practices. The process of conceiving, designing, building, and maintaining software systems by using existing software assets that are stored in a specialized operational reuse library or repository, accessible to system designers, is the foundation of the program. In addition to operating a software repository, RBSE promotes (1) software engineering technology transfer, (2) academic and instructional support of reuse programs, (3) the use of common software engineering standards and practices, (4) software reuse technology research, and (5) interoperability between reuse libraries. This Program Management Plan (PMP) is intended to communicate program goals and objectives, describe major work areas, and define a management report and control process. This process will assist the Program Manager, University of Houston at Clear Lake (UHCL) in tracking work progress and describing major program activities to NASA management. The goal of this PMP is to make managing the RBSE program a relatively easy process that improves the work of all team members. The PMP describes work areas addressed and work efforts being accomplished by the program; however, it is not intended as a complete description of the program. Its focus is on providing management tools and management processes for monitoring, evaluating, and administering the program; and it includes schedules for charting milestones and deliveries of program products. The PMP was developed by soliciting and obtaining guidance from appropriate program participants, analyzing program management guidance, and reviewing related program management documents.

  2. Analysis of Urban Car Owners Commute Mode Choice Based on Evolutionary Game Model

    Directory of Open Access Journals (Sweden)

    Huawei Gong

    2015-01-01

    Full Text Available With the aggravation of the traffic congestion in the city, car owners will have to give up commuting with private cars and take the public transportation instead. The paper uses the replication dynamic mechanism to simulate the learning and adjustment mechanism of the automobile owners commuting mode selection. The evolutionary stable strategy is used to describe the long-term evolution of competition game trend. Finally we simulate equilibrium and stability of an evolution of the game under a payoff imbalance situation. The research shows that a certain proportion of car owners will choose public transit under the pressure of public transport development and heavy traffic, and the proportion will be closely related to the initial conditions and urban transportation development policy.

  3. Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems

    DEFF Research Database (Denmark)

    Lissovoi, Andrei

    the dynamic optimum for finite alphabets up to size μ, while MMAS is able to do so for any finite alphabet size. Parallel Evolutionary Algorithms on Maze. We prove that while a (1 + λ) EA is unable to track the optimum of the dynamic fitness function Maze for offspring population size up to λ = O(n1-ε......This thesis presents new running time analyses of nature-inspired algorithms on various dynamic problems. It aims to identify and analyse the features of algorithms and problem classes which allow efficient optimization to occur in the presence of dynamic behaviour. We consider the following...... settings: λ-MMAS on Dynamic Shortest Path Problems. We investigate how in-creasing the number of ants simulated per iteration may help an ACO algorithm to track optimum in a dynamic problem. It is shown that while a constant number of ants per-vertex is sufficient to track some oscillations, there also...

  4. Studying the evolutionary relationships and phylogenetic trees of 21 groups of tRNA sequences based on complex networks.

    Science.gov (United States)

    Wei, Fangping; Chen, Bowen

    2012-03-01

    To find out the evolutionary relationships among different tRNA sequences of 21 amino acids, 22 networks are constructed. One is constructed from whole tRNAs, and the other 21 networks are constructed from the tRNAs which carry the same amino acids. A new method is proposed such that the alignment scores of any two amino acids groups are determined by the average degree and the average clustering coefficient of their networks. The anticodon feature of isolated tRNA and the phylogenetic trees of 21 group networks are discussed. We find that some isolated tRNA sequences in 21 networks still connect with other tRNAs outside their group, which reflects the fact that those tRNAs might evolve by intercrossing among these 21 groups. We also find that most anticodons among the same cluster are only one base different in the same sites when S ≥ 70, and they stay in the same rank in the ladder of evolutionary relationships. Those observations seem to agree on that some tRNAs might mutate from the same ancestor sequences based on point mutation mechanisms.

  5. An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration

    Energy Technology Data Exchange (ETDEWEB)

    Niknam, Taher [Electronic and Electrical Engineering Department, Shiraz University of Technology, Shiraz (Iran)

    2009-08-15

    This paper introduces a robust searching hybrid evolutionary algorithm to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The main objective of the DFR is to minimize the real power loss, deviation of the nodes' voltage, the number of switching operations, and balance the loads on the feeders. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. This paper presents a new approach based on norm3 for the DFR problem. In the proposed method, the objective functions are considered as a vector and the aim is to maximize the distance (norm2) between the objective function vector and the worst objective function vector while the constraints are met. Since the proposed DFR is a multi objective and non-differentiable optimization problem, a new hybrid evolutionary algorithm (EA) based on the combination of the Honey Bee Mating Optimization (HBMO) and the Discrete Particle Swarm Optimization (DPSO), called DPSO-HBMO, is implied to solve it. The results of the proposed reconfiguration method are compared with the solutions obtained by other approaches, the original DPSO and HBMO over different distribution test systems. (author)

  6. Evolutionary robotics

    Indian Academy of Sciences (India)

    In evolutionary robotics, a suitable robot control system is developed automatically through evolution due to the interactions between the robot and its environment. It is a complicated task, as the robot and the environment constitute a highly dynamical system. Several methods have been tried by various investigators to ...

  7. Molecular bases and evolutionary dynamics of self-incompatibility in the Pyrinae (Rosaceae).

    Science.gov (United States)

    De Franceschi, Paolo; Dondini, Luca; Sanzol, Javier

    2012-06-01

    The molecular bases of the gametophytic self-incompatibility (GSI) system of species of the subtribe Pyrinae (Rosaceae), such as apple and pear, have been widely studied in the last two decades. The characterization of S-locus genes and of the mechanisms underlying pollen acceptance or rejection have been topics of major interest. Besides the single pistil-side S determinant, the S-RNase, multiple related S-locus F-box genes seem to be involved in the determination of pollen S specificity. Here, we collect and review the state of the art of GSI in the Pyrinae. We emphasize recent genomic data that have contributed to unveiling the S-locus structure of the Pyrinae, and discuss their consistency with the models of self-recognition that have been proposed for Prunus and the Solanaceae. Experimental data suggest that the mechanism controlling pollen-pistil recognition specificity of the Pyrinae might fit well with the collaborative 'non-self' recognition system proposed for Petunia (Solanaceae), whereas it presents relevant differences with the mechanism exhibited by the species of the closely related genus Prunus, which uses a single evolutionarily divergent F-box gene as the pollen S determinant. The possible involvement of multiple pollen S genes in the GSI system of Pyrinae, still awaiting experimental confirmation, opens up new perspectives to our understanding of the evolution of S haplotypes, and of the evolution of S-RNase-based GSI within the Rosaceae family. Whereas S-locus genes encode the players determining self-recognition, pollen rejection in the Pyrinae seems to involve a complex cascade of downstream cellular events with significant similarities to programmed cell death.

  8. An affinity-based evolutionary model of the diffusion of knowledge

    Directory of Open Access Journals (Sweden)

    Roberto Luiz Souza Monteiro

    2015-08-01

    Full Text Available In this paper, we present a theoretical model that can simulate the diffusion of knowledge in social networks using an evolutionary approach. We assume that social networks built on processes of collaboration and cooperation among stakeholders (people and companies evolve like living organisms, as described by Charles Darwin in The Origin of Species. We propose an evolutionary model of the diffusion of knowledge, in which stakeholders are knowledge propagators and/or receivers, depending on their customizable attributes. We consider each attribute as a gene that constitutes a chromosome. As in Darwin's theory, the proposed model achieves the processes of crossover and mutation between stakeholders for several generations, until a maximum number of generations is reached. The main contribution of the model is the creation of an environment that is conducive to the study of the dynamics of network cooperation, which uses the stakeholders’ attributes as parameters. Modelo evolutivo de difusión del conocimiento basado en afinidad Resumen En este artículo presentamos un modelo teórico capaz de simular la difusión del conocimiento en redes sociales, usando una aproximación evolutiva. Partimos del presupuesto que redes sociales constituidas por procesos de cooperación entre actores (e.g. personas, empresas, etc. evolucionan de forma semejante a los organismos vivos, como ha sido descrito por Charles Darwin en El Origen de las Especies. Proponemos un modelo evolutivo de difusión del conocimiento, donde los actores son propagadores y/o retenedores de conocimiento, dependiendo de atributos ajustables que cada actor presenta. Consideramos cada atributo un gen que constituye a un cromosoma. Similar a la teoría de Darwin, el modelo propuesto realiza los procesos de crossover y mutación entre los actores por diversas generaciones, hasta que se obtiene un número máximo de generaciones. La principal contribución del modelo es la creación de un

  9. At the crossroads of evolutionary computation and music: self-programming synthesizers, swarm orchestras and the origins of melody.

    Science.gov (United States)

    Miranda, Eduardo Reck

    2004-01-01

    This paper introduces three approaches to using Evolutionary Computation (EC) in Music (namely, engineering, creative and musicological approaches) and discusses examples of representative systems that have been developed within the last decade, with emphasis on more recent and innovative works. We begin by reviewing engineering applications of EC in Music Technology such as Genetic Algorithms and Cellular Automata sound synthesis, followed by an introduction to applications where EC has been used to generate musical compositions. Next, we introduce ongoing research into EC models to study the origins of music and detail our own research work on modelling the evolution of melody. Copryright 2004 Massachusetts Institute of Technology

  10. Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes

    Directory of Open Access Journals (Sweden)

    Guang-Dong Zhou

    2015-01-01

    Full Text Available Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.

  11. Quantitative Trait Loci Mapping Problem: An Extinction-Based Multi-Objective Evolutionary Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Nicholas S. Flann

    2013-09-01

    Full Text Available The Quantitative Trait Loci (QTL mapping problem aims to identify regions in the genome that are linked to phenotypic features of the developed organism that vary in degree. It is a principle step in determining targets for further genetic analysis and is key in decoding the role of specific genes that control quantitative traits within species. Applications include identifying genetic causes of disease, optimization of cross-breeding for desired traits and understanding trait diversity in populations. In this paper a new multi-objective evolutionary algorithm (MOEA method is introduced and is shown to increase the accuracy of QTL mapping identification for both independent and epistatic loci interactions. The MOEA method optimizes over the space of possible partial least squares (PLS regression QTL models and considers the conflicting objectives of model simplicity versus model accuracy. By optimizing for minimal model complexity, MOEA has the advantage of solving the over-fitting problem of conventional PLS models. The effectiveness of the method is confirmed by comparing the new method with Bayesian Interval Mapping approaches over a series of test cases where the optimal solutions are known. This approach can be applied to many problems that arise in analysis of genomic data sets where the number of features far exceeds the number of observations and where features can be highly correlated.

  12. Altruism, egoism, or neither: A cognitive-efficiency-based evolutionary biological perspective on helping behavior.

    Science.gov (United States)

    Schulz, Armin W

    2016-04-01

    I argue for differences in the cognitive efficiency of different psychologies underlying helping behavior, and present an account of the adaptive pressures that result from these differences. Specifically, I argue that organisms often face pressure to move away from only being egoistically motivated to help: non-egoistic organisms are often able to determine how to help other organisms more quickly and with less recourse to costly cognitive resources like concentration and attention. Furthermore, I also argue that, while these pressures away from pure egoism can lead to the evolution of altruists, they can also lead to the evolution of reciprocation-focused behaviorist helpers or even of reflex-driven helpers (who are neither altruists nor egoists). In this way, I seek to broaden the set of considerations typically taken into account when assessing the evolution of the psychology of helping behavior-which tend to be restricted to matters of reliability-and also try to make clearer the role of evolutionary biological considerations in the discussion of this apparently straightforwardly psychological phenomenon. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Geomagnetic Navigation of Autonomous Underwater Vehicle Based on Multi-objective Evolutionary Algorithm.

    Science.gov (United States)

    Li, Hong; Liu, Mingyong; Zhang, Feihu

    2017-01-01

    This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments.

  14. An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

    Science.gov (United States)

    Darbandi, Payam; Pourboghrat, Farhang

    2011-08-01

    Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

  15. An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

    International Nuclear Information System (INIS)

    Darbandi, Payam; Pourboghrat, Farhang

    2011-01-01

    Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

  16. Evolutionary institutionalism.

    Science.gov (United States)

    Fürstenberg, Dr Kai

    Institutions are hard to define and hard to study. Long prominent in political science have been two theories: Rational Choice Institutionalism (RCI) and Historical Institutionalism (HI). Arising from the life sciences is now a third: Evolutionary Institutionalism (EI). Comparative strengths and weaknesses of these three theories warrant review, and the value-to-be-added by expanding the third beyond Darwinian evolutionary theory deserves consideration. Should evolutionary institutionalism expand to accommodate new understanding in ecology, such as might apply to the emergence of stability, and in genetics, such as might apply to political behavior? Core arguments are reviewed for each theory with more detailed exposition of the third, EI. Particular attention is paid to EI's gene-institution analogy; to variation, selection, and retention of institutional traits; to endogeneity and exogeneity; to agency and structure; and to ecosystem effects, institutional stability, and empirical limitations in behavioral genetics. RCI, HI, and EI are distinct but complementary. Institutional change, while amenable to rational-choice analysis and, retrospectively, to criticaljuncture and path-dependency analysis, is also, and importantly, ecological. Stability, like change, is an emergent property of institutions, which tend to stabilize after change in a manner analogous to allopatric speciation. EI is more than metaphorically biological in that institutional behaviors are driven by human behaviors whose evolution long preceded the appearance of institutions themselves.

  17. Rapid, value-based, evolutionary acquisition and its application to a USMC tactical service orientated architecture

    OpenAIRE

    Ferrel, Tyrone H.

    2009-01-01

    Approved for public release, distribution unlimited Over budget, behind schedule, and underperforming information technology acquisition programs plague not only the USMC, but almost all government agencies and many private sector entities as well. Causes of this crisis abound and one cannot easily or narrowly define them because of their seemingly disparate and far-reaching nature. This thesis first defines what truly constitutes an acquisition program's success versus its failure an...

  18. MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

    Science.gov (United States)

    Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

    2012-10-15

    There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

  19. A mobile element-based evolutionary history of guenons (tribe Cercopithecini

    Directory of Open Access Journals (Sweden)

    Tosi Anthony J

    2007-01-01

    Full Text Available Abstract Background Guenons (tribe Cercopithecini are a species-rich group of primates that have attracted considerable attention from both primatologists and evolutionary biologists. The complex speciation pattern has made the elucidation of their relationships a challenging task, and many questions remain unanswered. SINEs are a class of non-autonomous mobile elements and are essentially homoplasy-free characters with known ancestral states, making them useful genetic markers for phylogenetic studies. Results We identified 151 novel Alu insertion loci from 11 species of tribe Cercopithecini, and used these insertions and 17 previously reported loci to infer a phylogenetic tree of the tribe Cercopithecini. Our results robustly supported the following relationships: (i Allenopithecus is the basal lineage within the tribe; (ii Cercopithecus lhoesti (L'Hoest's monkey forms a clade with Chlorocebus aethiops (African green monkey and Erythrocebus patas (patas monkey, supporting a single arboreal to terrestrial transition within the tribe; (iii all of the Cercopithecus except C. lhoesti form a monophyletic group; and (iv contrary to the common belief that Miopithecus is one of the most basal lineages in the tribe, M. talapoin (talapoin forms a clade with arboreal members of Cercopithecus, and the terrestrial group (C. lhoesti, Chlorocebus aethiops and E. patas diverged from this clade after the divergence of Allenopithecus. Some incongruent loci were found among the relationships within the arboreal Cercopithecus group. Several factors, including incomplete lineage sorting, concurrent polymorphism and hybridization between species may have contributed to the incongruence. Conclusion This study presents one of the most robust phylogenetic hypotheses for the tribe Cercopithecini and demonstrates the advantages of SINE insertions for phylogenetic studies.

  20. Investigating preferences for color-shape combinations with gaze driven optimization method based on evolutionary algorithms.

    Science.gov (United States)

    Holmes, Tim; Zanker, Johannes M

    2013-01-01

    Studying aesthetic preference is notoriously difficult because it targets individual experience. Eye movements provide a rich source of behavioral measures that directly reflect subjective choice. To determine individual preferences for simple composition rules we here use fixation duration as the fitness measure in a Gaze Driven Evolutionary Algorithm (GDEA), which has been demonstrated as a tool to identify aesthetic preferences (Holmes and Zanker, 2012). In the present study, the GDEA was used to investigate the preferred combination of color and shape which have been promoted in the Bauhaus arts school. We used the same three shapes (square, circle, triangle) used by Kandinsky (1923), with the three color palette from the original experiment (A), an extended seven color palette (B), and eight different shape orientation (C). Participants were instructed to look for their preferred circle, triangle or square in displays with eight stimuli of different shapes, colors and rotations, in an attempt to test for a strong preference for red squares, yellow triangles and blue circles in such an unbiased experimental design and with an extended set of possible combinations. We Tested six participants extensively on the different conditions and found consistent preferences for color-shape combinations for individuals, but little evidence at the group level for clear color/shape preference consistent with Kandinsky's claims, apart from some weak link between yellow and triangles. Our findings suggest substantial inter-individual differences in the presence of stable individual associations of color and shapes, but also that these associations are robust within a single individual. These individual differences go some way toward challenging the claims of the universal preference for color/shape combinations proposed by Kandinsky, but also indicate that a much larger sample size would be needed to confidently reject that hypothesis. Moreover, these experiments highlight the

  1. Investigating preferences for colour-shape combinations with gaze driven optimization method based on evolutionary algorithms.

    Directory of Open Access Journals (Sweden)

    Tim eHolmes

    2013-12-01

    Full Text Available Studying aesthetic preference is notoriously difficult because it targets individual experience. Eye movements provide a rich source of behavioural measures that directly reflect subjective choice. To determine individual preferences for simple composition rules we here use fixation duration as the fitness measure in a Gaze Driven Evolutionary Algorithm (GDEA, which has been used as a tool to identify aesthetic preferences (Holmes & Zanker, 2012. In the present study, the GDEA was used to investigate the preferred combination of colour and shape which have been promoted in the Bauhaus arts school. We used the same 3 shapes (square, circle, triangle used by Kandinsky (1923, with the 3 colour palette from the original experiment (A, an extended 7 colour palette (B, and 8 different shape orientation (C. Participants were instructed to look for their preferred circle, triangle or square in displays with 8 stimuli of different shapes, colours and rotations, in an attempt to test for a strong preference for red squares, yellow triangles and blue circles in such an unbiased experimental design and with an extended set of possible combinations. We Tested 6 participants extensively on the different conditions and found consistent preferences for individuals, but little evidence at the group level for preference consistent with Kandinsky’s claims, apart from some weak link between yellow and triangles. Our findings suggest substantial inter-individual differences in the presence of stable individual associations of colour and shapes, but also that these associations are robust within a single individual. These individual differences go some way towards challenging the claims of the universal preference for colour/shape combinations proposed by Kandinsky, but also indicate that a much larger sample size would be needed to confidently reject that hypothesis. Moreover, these experiments highlight the vast potential of the GDEA in experimental aesthetics

  2. Applying evolutionary anthropology.

    Science.gov (United States)

    Gibson, Mhairi A; Lawson, David W

    2015-01-01

    Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. © 2015 Wiley Periodicals, Inc.

  3. Applying Evolutionary Anthropology

    Science.gov (United States)

    Gibson, Mhairi A; Lawson, David W

    2015-01-01

    Evolutionary anthropology provides a powerful theoretical framework for understanding how both current environments and legacies of past selection shape human behavioral diversity. This integrative and pluralistic field, combining ethnographic, demographic, and sociological methods, has provided new insights into the ultimate forces and proximate pathways that guide human adaptation and variation. Here, we present the argument that evolutionary anthropological studies of human behavior also hold great, largely untapped, potential to guide the design, implementation, and evaluation of social and public health policy. Focusing on the key anthropological themes of reproduction, production, and distribution we highlight classic and recent research demonstrating the value of an evolutionary perspective to improving human well-being. The challenge now comes in transforming relevance into action and, for that, evolutionary behavioral anthropologists will need to forge deeper connections with other applied social scientists and policy-makers. We are hopeful that these developments are underway and that, with the current tide of enthusiasm for evidence-based approaches to policy, evolutionary anthropology is well positioned to make a strong contribution. PMID:25684561

  4. Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

    Science.gov (United States)

    José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

    2011-07-01

    Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

  5. Evolutionary Statistical Procedures

    CERN Document Server

    Baragona, Roberto; Poli, Irene

    2011-01-01

    This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a

  6. Contemporary issues in evolutionary biology

    Indian Academy of Sciences (India)

    These discussions included, among others, the possible consequences of nonDNA-based inheritance—epigenetics and cultural evolution, niche construction, and developmental mechanisms on our understanding of the evolutionary process, speciation, complexity in biology, and constructing a formal evolutionary theory.

  7. A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

    Science.gov (United States)

    Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

    2018-04-01

    Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods

  8. Proteomics in evolutionary ecology.

    Science.gov (United States)

    Baer, B; Millar, A H

    2016-03-01

    Evolutionary ecologists are traditionally gene-focused, as genes propagate phenotypic traits across generations and mutations and recombination in the DNA generate genetic diversity required for evolutionary processes. As a consequence, the inheritance of changed DNA provides a molecular explanation for the functional changes associated with natural selection. A direct focus on proteins on the other hand, the actual molecular agents responsible for the expression of a phenotypic trait, receives far less interest from ecologists and evolutionary biologists. This is partially due to the central dogma of molecular biology that appears to define proteins as the 'dead-end of molecular information flow' as well as technical limitations in identifying and studying proteins and their diversity in the field and in many of the more exotic genera often favored in ecological studies. Here we provide an overview of a newly forming field of research that we refer to as 'Evolutionary Proteomics'. We point out that the origins of cellular function are related to the properties of polypeptide and RNA and their interactions with the environment, rather than DNA descent, and that the critical role of horizontal gene transfer in evolution is more about coopting new proteins to impact cellular processes than it is about modifying gene function. Furthermore, post-transcriptional and post-translational processes generate a remarkable diversity of mature proteins from a single gene, and the properties of these mature proteins can also influence inheritance through genetic and perhaps epigenetic mechanisms. The influence of post-transcriptional diversification on evolutionary processes could provide a novel mechanistic underpinning for elements of rapid, directed evolutionary changes and adaptations as observed for a variety of evolutionary processes. Modern state-of the art technologies based on mass spectrometry are now available to identify and quantify peptides, proteins, protein

  9. Planning the expansion of electrical transmission networks with evolutionary programming; Planeacion de la expansion de redes de transmision electrica con programacion evolucionaria

    Energy Technology Data Exchange (ETDEWEB)

    Ceciliano Meza, Jose Luis

    1997-12-31

    In this work it is presented for the first time in the literature the solution of the problem of the planning the expansion of an electrical transmission network (PERTE) with the use of the Evolutionary Programming. The evolutionary programming is a stochastic method of optimization with similar characteristics to the generic algorithms, but different. During the development of this work it is shown what each one of these two heuristic methods of optimization consist of. Additionally, the main characteristics of other two heuristic methods known in the literature are described (Tabu Searching and Simulated Annealing). These two methods together with the genetic algorithms and decomposition of Benders have also been used to solve the problem of planning PERTE. The operation of the proposed algorithm of evolutionary programming was tested in two networks of electrical transmission. The first case of test is a system which is known in the literature. The second case is a representative system of the electrical transmission network of Central America. The results obtained improve all the results shown when applying different heuristic methods of optimization (genetic algorithms, simulated annealing and Tabu searching) to solve the same problem. [Espanol] En este trabajo se presenta por primera vez en la literatura, la solucion del problema de la planeacion de expansion de una red de transmision electrica (PERTE) con el uso de la Programacion Evolucionaria. La programacion evolucionaria es un metodo estocastico de optimizacion con caracteristicas similares a los algoritmos geneticos, pero diferente. Durante el desarrollo de este trabajo se muestra en que consiste cada uno de estos dos metodos heuristicos de optimizacion. Ademas, se describen las caracteristicas principales de otros dos metodos heuristicos conocidos en la literatura (busqueda Tabu y Recorrido Simulado). Estos dos metodos juntos con los algoritmos geneticos y descomposicion de Benders tambien han sido

  10. Community-Based Native Teacher Education Programs.

    Science.gov (United States)

    Heimbecker, Connie; Minner, Sam; Prater, Greg

    This paper describes two exemplary school-based Native teacher education programs offered by Northern Arizona University (NAU) to serve Navajo students and by Lakehead University (Ontario) to serve members of the Nishnabe Nation of northern Ontario. The Reaching American Indian Special/Elementary Educators (RAISE) program is located in Kayenta,…

  11. Evolutionary Explanations of Eating Disorders

    Directory of Open Access Journals (Sweden)

    Igor Kardum

    2008-12-01

    Full Text Available This article reviews several most important evolutionary mechanisms that underlie eating disorders. The first part clarifies evolutionary foundations of mental disorders and various mechanisms leading to their development. In the second part selective pressures and evolved adaptations causing contemporary epidemic of obesity as well as differences in dietary regimes and life-style between modern humans and their ancestors are described. Concerning eating disorders, a number of current evolutionary explanations of anorexia nervosa are presented together with their main weaknesses. Evolutionary explanations of eating disorders based on the reproductive suppression hypothesis and its variants derived from kin selection theory and the model of parental manipulation were elaborated. The sexual competition hypothesis of eating disorder, adapted to flee famine hypothesis as well as explanation based on the concept of social attention holding power and the need to belonging were also explained. The importance of evolutionary theory in modern conceptualization and research of eating disorders is emphasized.

  12. Microservices as an Evolutionary Architecture of Component-Based Development: A Think-aloud Study

    OpenAIRE

    Parizi, Reza M.

    2018-01-01

    Microservices become a fast growing and popular architectural style based on service-oriented development. One of the major advantages using component-based approaches is to support reuse. In this paper, we present a study of microservices and how these systems are related to the traditional abstract models of component-based systems. This research focuses on the core properties of microservices including their scalability, availability and resilience, consistency, coupling and cohesion, and ...

  13. Open Issues in Evolutionary Robotics.

    Science.gov (United States)

    Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

  14. An Evolutionary, Agent-Based Model to Aid in Computer Intrusion Detection and Prevention

    National Research Council Canada - National Science Library

    Shargel, Ben; Bonabeau, Eric; Budynek, Julien; Gaudiano, Paolo

    2005-01-01

    We have developed a realistic agent-based simulation model of hacker behavior. In the model, hacker scripts are generated using a simple but powerful hacker grammar that has the potential to cover all possible hacker scripts...

  15. Dynamic Power Dispatch Considering Electric Vehicles and Wind Power Using Decomposition Based Multi-Objective Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Boyang Qu

    2017-12-01

    Full Text Available The intermittency of wind power and the large-scale integration of electric vehicles (EVs bring new challenges to the reliability and economy of power system dispatching. In this paper, a novel multi-objective dynamic economic emission dispatch (DEED model is proposed considering the EVs and uncertainties of wind power. The total fuel cost and pollutant emission are considered as the optimization objectives, and the vehicle to grid (V2G power and the conventional generator output power are set as the decision variables. The stochastic wind power is derived by Weibull probability distribution function. Under the premise of meeting the system energy and user’s travel demand, the charging and discharging behavior of the EVs are dynamically managed. Moreover, we propose a two-step dynamic constraint processing strategy for decision variables based on penalty function, and, on this basis, the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D algorithm is improved. The proposed model and approach are verified by the 10-generator system. The results demonstrate that the proposed DEED model and the improved MOEA/D algorithm are effective and reasonable.

  16. The UDP glucuronosyltransferase gene superfamily: suggested nomenclature based on evolutionary divergence

    NARCIS (Netherlands)

    Burchell, B.; Nebert, D. W.; Nelson, D. R.; Bock, K. W.; Iyanagi, T.; Jansen, P. L.; Lancet, D.; Mulder, G. J.; Chowdhury, J. R.; Siest, G.

    1991-01-01

    A nomenclature system for the UDP glucuronosyltransferase superfamily is proposed, based on divergent evolution of the genes. A total of 26 distinct cDNAs in five mammalian species have been sequenced to date. Comparison of the deduced amino acid sequences leads to the definition of two families and

  17. Evolutionary stellar population synthesis with MILES : I. The base models and a new line index system

    NARCIS (Netherlands)

    Vazdekis, A.; Sanchez-Blazquez, P.; Falcon-Barroso, J.; Cenarro, A. J.; Beasley, M. A.; Cardiel, N.; Gorgas, J.; Peletier, R. F.

    2010-01-01

    We present synthetic spectral energy distributions (SEDs) for single-age, single-metallicity stellar populations (SSPs) covering the full optical spectral range at moderately high resolution [full width at half-maximum (FWHM) = 2.3Å]. These SEDs constitute our base models, as they combine

  18. Solving Linear Equations by Classical Jacobi-SR Based Hybrid Evolutionary Algorithm with Uniform Adaptation Technique

    OpenAIRE

    Jamali, R. M. Jalal Uddin; Hashem, M. M. A.; Hasan, M. Mahfuz; Rahman, Md. Bazlar

    2013-01-01

    Solving a set of simultaneous linear equations is probably the most important topic in numerical methods. For solving linear equations, iterative methods are preferred over the direct methods especially when the coefficient matrix is sparse. The rate of convergence of iteration method is increased by using Successive Relaxation (SR) technique. But SR technique is very much sensitive to relaxation factor, {\\omega}. Recently, hybridization of classical Gauss-Seidel based successive relaxation t...

  19. 45 CFR 1306.33 - Home-based program option.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Home-based program option. 1306.33 Section 1306.33... PROGRAM HEAD START STAFFING REQUIREMENTS AND PROGRAM OPTIONS Head Start Program Options § 1306.33 Home-based program option. (a) Grantees implementing a home-based program option must: (1) Provide one home...

  20. Molluscan Evolutionary Genomics

    Energy Technology Data Exchange (ETDEWEB)

    Simison, W. Brian; Boore, Jeffrey L.

    2005-12-01

    In the last 20 years there have been dramatic advances in techniques of high-throughput DNA sequencing, most recently accelerated by the Human Genome Project, a program that has determined the three billion base pair code on which we are based. Now this tremendous capability is being directed at other genome targets that are being sampled across the broad range of life. This opens up opportunities as never before for evolutionary and organismal biologists to address questions of both processes and patterns of organismal change. We stand at the dawn of a new 'modern synthesis' period, paralleling that of the early 20th century when the fledgling field of genetics first identified the underlying basis for Darwin's theory. We must now unite the efforts of systematists, paleontologists, mathematicians, computer programmers, molecular biologists, developmental biologists, and others in the pursuit of discovering what genomics can teach us about the diversity of life. Genome-level sampling for mollusks to date has mostly been limited to mitochondrial genomes and it is likely that these will continue to provide the best targets for broad phylogenetic sampling in the near future. However, we are just beginning to see an inroad into complete nuclear genome sequencing, with several mollusks and other eutrochozoans having been selected for work about to begin. Here, we provide an overview of the state of molluscan mitochondrial genomics, highlight a few of the discoveries from this research, outline the promise of broadening this dataset, describe upcoming projects to sequence whole mollusk nuclear genomes, and challenge the community to prepare for making the best use of these data.

  1. Base Program on Energy Related Research

    Energy Technology Data Exchange (ETDEWEB)

    Western Research Institute

    2008-06-30

    The main objective of the Base Research Program was to conduct both fundamental and applied research that will assist industry in developing, deploying, and commercializing efficient, nonpolluting fossil energy technologies that can compete effectively in meeting the energy requirements of the Nation. In that regard, tasks proposed under the WRI research areas were aligned with DOE objectives of secure and reliable energy; clean power generation; development of hydrogen resources; energy efficiency and development of innovative fuels from low and no-cost sources. The goal of the Base Research Program was to develop innovative technology solutions that will: (1) Increase the production of United States energy resources--coal, natural gas, oil, and renewable energy resources; (2) Enhance the competitiveness of United States energy technologies in international markets and assist in technology transfer; (3) Reduce the nation's dependence on foreign energy supplies and strengthen both the United States and regional economies; and (4) Minimize environmental impacts of energy production and utilization. This report summarizes the accomplishments of the overall Base Program. This document represents a stand-alone Final Report for the entire Program. It should be noted that an interim report describing the Program achievements was prepared in 2003 covering the progress made under various tasks completed during the first five years of this Program.

  2. CCHMM_PROF: a HMM-based coiled-coil predictor with evolutionary information

    DEFF Research Database (Denmark)

    Bartoli, Lisa; Fariselli, Piero; Krogh, Anders

    2009-01-01

    tools are available for predicting coiled-coil domains in protein sequences, including those based on position-specific score matrices and machine learning methods. RESULTS: In this article, we introduce a hidden Markov model (CCHMM_PROF) that exploits the information contained in multiple sequence...... alignments (profiles) to predict coiled-coil regions. The new method discriminates coiled-coil sequences with an accuracy of 97% and achieves a true positive rate of 79% with only 1% of false positives. Furthermore, when predicting the location of coiled-coil segments in protein sequences, the method reaches...

  3. Towards a mechanistic foundation of evolutionary theory.

    Science.gov (United States)

    Doebeli, Michael; Ispolatov, Yaroslav; Simon, Burt

    2017-02-15

    Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.

  4. Prediction of strain energy-based liquefaction resistance of sand-silt mixtures: An evolutionary approach

    Science.gov (United States)

    Baziar, Mohammad H.; Jafarian, Yaser; Shahnazari, Habib; Movahed, Vahid; Amin Tutunchian, Mohammad

    2011-11-01

    Liquefaction is a catastrophic type of ground failure, which usually occurs in loose saturated soil deposits under earthquake excitations. A new predictive model is presented in this study to estimate the amount of strain energy density, which is required for the liquefaction triggering of sand-silt mixtures. A wide-ranging database containing the results of cyclic tests on sand-silt mixtures was first gathered from previously published studies. Input variables of the model were chosen from the available understandings evolved from the previous studies on the strain energy-based liquefaction potential assessment. In order to avoid overtraining, two sets of validation data were employed and a particular monitoring was made on the behavior of the evolved models. Results of a comprehensive parametric study on the proposed model are in accord with the previously published experimental observations. Accordingly, the amount of strain energy required for liquefaction onset increases with increase in initial effective overburden pressure, relative density, and mean grain size. The effect of nonplastic fines on strain energy-based liquefaction resistance shows a more complicated behavior. Accordingly, liquefaction resistance increases with increase in fines up to about 10-15% and then starts to decline for a higher increase in fines content. Further verifications of the model were carried out using the valuable results of some downhole array data as well as centrifuge model tests. These verifications confirm that the proposed model, which was derived from laboratory data, can be successfully utilized under field conditions.

  5. Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

    Science.gov (United States)

    Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

    2017-08-01

    Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

  6. Evolutionary stability and resistance to cheating in an indirect reciprocity model based on reputation

    Science.gov (United States)

    Martinez-Vaquero, Luis A.; Cuesta, José A.

    2013-05-01

    Indirect reciprocity is one of the main mechanisms to explain the emergence and sustainment of altruism in societies. The standard approach to indirect reciprocity is reputation models. These are games in which players base their decisions on their opponent's reputation gained in past interactions with other players (moral assessment). The combination of actions and moral assessment leads to a large diversity of strategies; thus determining the stability of any of them against invasions by all the others is a difficult task. We use a variant of a previously introduced reputation-based model that let us systematically analyze all these invasions and determine which ones are successful. Accordingly, we are able to identify the third-order strategies (those which, apart from the action, judge considering both the reputation of the donor and that of the recipient) that are evolutionarily stable. Our results reveal that if a strategy resists the invasion of any other one sharing its same moral assessment, it can resist the invasion of any other strategy. However, if actions are not always witnessed, cheaters (i.e., individuals with a probability of defecting regardless of the opponent's reputation) have a chance to defeat the stable strategies for some choices of the probabilities of cheating and of being witnessed. Remarkably, by analyzing this issue with adaptive dynamics we find that whether an honest population resists the invasion of cheaters is determined by a Hamilton-like rule, with the probability that the cheat is discovered playing the role of the relatedness parameter.

  7. An Ensemble Based Evolutionary Approach to the Class Imbalance Problem with Applications in CBIR

    Directory of Open Access Journals (Sweden)

    Aun Irtaza

    2018-03-01

    Full Text Available In order to lower the dependence on textual annotations for image searches, the content based image retrieval (CBIR has become a popular topic in computer vision. A wide range of CBIR applications consider classification techniques, such as artificial neural networks (ANN, support vector machines (SVM, etc. to understand the query image content to retrieve relevant output. However, in multi-class search environments, the retrieval results are far from optimal due to overlapping semantics amongst subjects of various classes. The classification through multiple classifiers generate better results, but as the number of negative examples increases due to highly correlated semantic classes, classification bias occurs towards the negative class, hence, the combination of the classifiers become even more unstable particularly in one-against-all classification scenarios. In order to resolve this issue, a genetic algorithm (GA based classifier comity learning (GCCL method is presented in this paper to generate stable classifiers by combining ANN with SVMs through asymmetric and symmetric bagging. The proposed approach resolves the classification disagreement amongst different classifiers and also resolves the class imbalance problem in CBIR. Once the stable classifiers are generated, the query image is presented to the trained model to understand the underlying semantic content of the query image for association with the precise semantic class. Afterwards, the feature similarity is computed within the obtained class to generate the semantic response of the system. The experiments reveal that the proposed method outperforms various state-of-the-art methods and significantly improves the image retrieval performance.

  8. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

    Science.gov (United States)

    2018-01-01

    Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

  9. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

    Directory of Open Access Journals (Sweden)

    Hazlee Azil Illias

    Full Text Available Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM with modified evolutionary particle swarm optimisation (EPSO algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO-Time Varying Acceleration Coefficient (TVAC technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

  10. Evolutionary Game Theory-Based Evaluation of P2P File-Sharing Systems in Heterogeneous Environments

    Directory of Open Access Journals (Sweden)

    Yusuke Matsuda

    2010-01-01

    Full Text Available Peer-to-Peer (P2P file sharing is one of key technologies for achieving attractive P2P multimedia social networking. In P2P file-sharing systems, file availability is improved by cooperative users who cache and share files. Note that file caching carries costs such as storage consumption and processing load. In addition, users have different degrees of cooperativity in file caching and they are in different surrounding environments arising from the topological structure of P2P networks. With evolutionary game theory, this paper evaluates the performance of P2P file sharing systems in such heterogeneous environments. Using micro-macro dynamics, we analyze the impact of the heterogeneity of user selfishness on the file availability and system stability. Further, through simulation experiments with agent-based dynamics, we reveal how other aspects, for example, synchronization among nodes and topological structure, affect the system performance. Both analytical and simulation results show that the environmental heterogeneity contributes to the file availability and system stability.

  11. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

    Science.gov (United States)

    Illias, Hazlee Azil; Zhao Liang, Wee

    2018-01-01

    Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

  12. An AmI-Based Software Architecture Enabling Evolutionary Computation in Blended Commerce: The Shopping Plan Application

    Directory of Open Access Journals (Sweden)

    Giuseppe D’Aniello

    2015-01-01

    Full Text Available This work describes an approach to synergistically exploit ambient intelligence technologies, mobile devices, and evolutionary computation in order to support blended commerce or ubiquitous commerce scenarios. The work proposes a software architecture consisting of three main components: linked data for e-commerce, cloud-based services, and mobile apps. The three components implement a scenario where a shopping mall is presented as an intelligent environment in which customers use NFC capabilities of their smartphones in order to handle e-coupons produced, suggested, and consumed by the abovesaid environment. The main function of the intelligent environment is to help customers define shopping plans, which minimize the overall shopping cost by looking for best prices, discounts, and coupons. The paper proposes a genetic algorithm to find suboptimal solutions for the shopping plan problem in a highly dynamic context, where the final cost of a product for an individual customer is dependent on his previous purchases. In particular, the work provides details on the Shopping Plan software prototype and some experimentation results showing the overall performance of the genetic algorithm.

  13. Topics in Semantics-based Program Manipulation

    DEFF Research Database (Denmark)

    Grobauer, Bernt

    four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

  14. Reliability-based optimization of an active vibration controller using evolutionary algorithms

    Science.gov (United States)

    Saraygord Afshari, Sajad; Pourtakdoust, Seid H.

    2017-04-01

    Many modern industrialized systems such as aircrafts, rotating turbines, satellite booms, etc. cannot perform their desired tasks accurately if their uninhibited structural vibrations are not controlled properly. Structural health monitoring and online reliability calculations are emerging new means to handle system imposed uncertainties. As stochastic forcing are unavoidable, in most engineering systems, it is often needed to take them into the account for the control design process. In this research, smart material technology is utilized for structural health monitoring and control in order to keep the system in a reliable performance range. In this regard, a reliability-based cost function is assigned for both controller gain optimization as well as sensor placement. The proposed scheme is implemented and verified for a wing section. Comparison of results for the frequency responses is considered to show potential applicability of the presented technique.

  15. Effect of network topology on the evolutionary ultimatum game based on the net-profit decision

    Science.gov (United States)

    Ye, Shun-Qiang; Wang, Lu; Jones, Michael C.; Ye, Ye; Wang, Meng; Xie, Neng-Gang

    2016-04-01

    The ubiquity of altruist behavior amongst humans has long been a significant puzzle in the social sciences. Ultimatum game has proved to be a useful tool for explaining altruistic behavior among selfish individuals. In an ultimatum game where alternating roles exist, we suppose that players make their decisions based on the net profit of their own. In this paper, we specify a player's strategy with two parameters: offer level α ∈ [ 0,1) and net profit acceptance level β ∈ [ - 1,1). By Monte Carlo simulation, we analyze separately the effect of the size of the neighborhood, the small-world property and the heterogeneity of the degree distributions of the networks. Results show that compared with results observed for homogeneous networks, heterogeneous networks lead to more rational outcomes. Moreover, network structure has no effect on the evolution of kindness level, so moderate kindness is adaptable to any social groups and organizations.

  16. Evolutionary constrained optimization

    CERN Document Server

    Deb, Kalyanmoy

    2015-01-01

    This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful...

  17. Optimal Management Of Renewable-Based Mgs An Intelligent Approach Through The Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Mehdi Nafar

    2015-08-01

    Full Text Available Abstract- This article proposes a probabilistic frame built on Scenario fabrication to considerate the uncertainties in the finest action managing of Micro Grids MGs. The MG contains different recoverable energy resources such as Wind Turbine WT Micro Turbine MT Photovoltaic PV Fuel Cell FC and one battery as the storing device. The advised frame is based on scenario generation and Roulette wheel mechanism to produce different circumstances for handling the uncertainties of altered factors. It habits typical spreading role as a probability scattering function of random factors. The uncertainties which are measured in this paper are grid bid alterations cargo request calculating error and PV and WT yield power productions. It is well-intentioned to asset that solving the MG difficult for 24 hours of a day by considering diverse uncertainties and different constraints needs one powerful optimization method that can converge fast when it doesnt fall in local optimal topic. Simultaneously single Group Search Optimization GSO system is presented to vision the total search space globally. The GSO algorithm is instigated from group active of beasts. Also the GSO procedure one change is similarly planned for this algorithm. The planned context and way is applied o one test grid-connected MG as a typical grid.

  18. Analysis of China's real estate prices and macroeconomy based on evolutionary co-spectral method

    Directory of Open Access Journals (Sweden)

    Juan Li

    2015-04-01

    Full Text Available Purpose: This paper investigates the dynamic interaction between the real estate market and the macroeconomic environment of China by use of dynamic coherence function based on co-spectral analysis. Design/methodology/approach: Through a theoretical perspective, the dynamic interrelationship among economic variables at different time intervals (both long and short terms is analyzed. Findings: The empirical results show that China’s real estate market features a high coherence with the change of the long-term interest rate, employment rate and money supply, while there is a moderate coherence between the real estate market and the inflation rate and economic growth rate, and the coherence between the short-term rate of interest and the real estate market is the lowest. Research implications: Previous researches have some shortcomings. They do not consider the dependence between nonlinear series, but the latter is crucial to avoid the deviation of results. In this paper, we proposed a new method of experience to overcome these shortcomings. Originality/value: The paper provides a reasonable explanation accordingly to different coherences between the real estate market and the macroeconomic variables.

  19. Multi-Working Modes Product-Color Planning Based on Evolutionary Algorithms and Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Man Ding

    2010-01-01

    Full Text Available In order to assist designer in color planning during product development, a novel synthesized evaluation method is presented to evaluate color-combination schemes of multi-working modes products (MMPs. The proposed evaluation method considers color-combination images in different working modes as evaluating attributes, to which the corresponding weights are assigned for synthesized evaluation. Then a mathematical model is developed to search for optimal color-combination schemes of MMP based on the proposed evaluation method and two powerful search techniques known as Evolution Algorithms (EAs and Swarm Intelligence (SI. In the experiments, we present a comparative study for two EAs, namely, Genetic Algorithm (GA and Difference Evolution (DE, and one SI algorithm, namely, Particle Swarm Optimization (PSO, on searching for color-combination schemes of MMP problem. All of the algorithms are evaluated against a test scenario, namely, an Arm-type aerial work platform, which has two working modes. The results show that the DE obtains the superior solution than the other two algorithms for color-combination scheme searching problem in terms of optimization accuracy and computation robustness. Simulation results demonstrate that the proposed method is feasible and efficient.

  20. Integrated Data Base Program: a status report

    International Nuclear Information System (INIS)

    Notz, K.J.; Klein, J.A.

    1984-06-01

    The Integrated Data Base (IDB) Program provides official Department of Energy (DOE) data on spent fuel and radioactive waste inventories, projections, and characteristics. The accomplishments of FY 1983 are summarized for three broad areas: (1) upgrading and issuing of the annual report on spent fuel and radioactive waste inventories, projections, and characteristics, including ORIGEN2 applications and a quality assurance plan; (2) creation of a summary data file in user-friendly format for use on a personal computer and enhancing user access to program data; and (3) optimizing and documentation of the data handling methodology used by the IDB Program and providing direct support to other DOE programs and sites in data handling. Plans for future work in these three areas are outlined. 23 references, 11 figures

  1. Collaborative Communication in Work Based Learning Programs

    Science.gov (United States)

    Wagner, Stephen Allen

    2017-01-01

    This basic qualitative study, using interviews and document analysis, examined reflections from a Work Based Learning (WBL) program to understand how utilizing digital collaborative communication tools influence the educational experience. The Community of Inquiry (CoI) framework was used as a theoretical frame promoting the examination of the…

  2. School-Based Child Abuse Prevention Programs

    Science.gov (United States)

    Brassard, Marla R.; Fiorvanti, Christina M.

    2015-01-01

    Child abuse is a leading cause of emotional, behavioral, and health problems across the lifespan. It is also preventable. School-based abuse prevention programs for early childhood and elementary school children have been found to be effective in increasing student knowledge and protective behaviors. The purpose of this article is to help school…

  3. Asymmetric Evolutionary Games

    Science.gov (United States)

    McAvoy, Alex; Hauert, Christoph

    2015-01-01

    Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner’s Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. PMID:26308326

  4. Motion Learning Based on Bayesian Program Learning

    Directory of Open Access Journals (Sweden)

    Cheng Meng-Zhen

    2017-01-01

    Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

  5. Nuclear Power Reactor simulator - based training program

    International Nuclear Information System (INIS)

    Abdelwahab, S.A.S.

    2009-01-01

    nuclear power stations will continue playing a major role as an energy source for electric generation and heat production in the world. in this paper, a nuclear power reactor simulator- based training program will be presented . this program is designed to aid in training of the reactor operators about the principles of operation of the plant. also it could help the researchers and the designers to analyze and to estimate the performance of the nuclear reactors and facilitate further studies for selection of the proper controller and its optimization process as it is difficult and time consuming to do all experiments in the real nuclear environment.this program is written in MATLAB code as MATLAB software provides sophisticated tools comparable to those in other software such as visual basic for the creation of graphical user interface (GUI). moreover MATLAB is available for all major operating systems. the used SIMULINK reactor model for the nuclear reactor can be used to model different types by adopting appropriate parameters. the model of each component of the reactor is based on physical laws rather than the use of look up tables or curve fitting.this simulation based training program will improve acquisition and retention knowledge also trainee will learn faster and will have better attitude

  6. MS-SQL data base programming

    Energy Technology Data Exchange (ETDEWEB)

    Noh, Chang Bae; Kim, Nam Jung; Lee, Hyeong Gyo

    2002-07-15

    This is about MS-SQL data base programming which is divided into thirteen chapters. The contents of this book are to understand MS-SQL 2000 DBMS with its composition, new function and history of MS-SQL, to learn conception of data base, install, run and closing of MS-SQL 2000 DBMS, to deal with the basic of MS-SQL DBMS, to handle the intermediate level of MS-SQL DBMS, to deal with MS-SQL DBMS in advanced level, to practice query like changing data base and checking of data lists, function on its use and data diff, get date, date add, char, upper and system function, set-up of MS-SQL ODBC, constructing of web server of windows 2000, web programming using visual studio.net.making board and making reference room.

  7. MS-SQL data base programming

    International Nuclear Information System (INIS)

    Noh, Chang Bae; Kim, Nam Jung; Lee, Hyeong Gyo

    2002-07-01

    This is about MS-SQL data base programming which is divided into thirteen chapters. The contents of this book are to understand MS-SQL 2000 DBMS with its composition, new function and history of MS-SQL, to learn conception of data base, install, run and closing of MS-SQL 2000 DBMS, to deal with the basic of MS-SQL DBMS, to handle the intermediate level of MS-SQL DBMS, to deal with MS-SQL DBMS in advanced level, to practice query like changing data base and checking of data lists, function on its use and data diff, get date, date add, char, upper and system function, set-up of MS-SQL ODBC, constructing of web server of windows 2000, web programming using visual studio.net.making board and making reference room.

  8. A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration

    International Nuclear Information System (INIS)

    Niknam, Taher; Azadfarsani, Ehsan; Jabbari, Masoud

    2012-01-01

    Highlights: ► Network reconfiguration is a very important way to save the electrical energy. ► This paper proposes a new algorithm to solve the DFR. ► The algorithm combines NFAPSO with NM. ► The proposed algorithm is tested on two distribution test feeders. - Abstract: Network reconfiguration for loss reduction in distribution system is a very important way to save the electrical energy. This paper proposes a new hybrid evolutionary algorithm to solve the Distribution Feeder Reconfiguration problem (DFR). The algorithm is based on combination of a New Fuzzy Adaptive Particle Swarm Optimization (NFAPSO) and Nelder–Mead simplex search method (NM) called NFAPSO–NM. In the proposed algorithm, a new fuzzy adaptive particle swarm optimization includes two parts. The first part is Fuzzy Adaptive Binary Particle Swarm Optimization (FABPSO) that determines the status of tie switches (open or close) and second part is Fuzzy Adaptive Discrete Particle Swarm Optimization (FADPSO) that determines the sectionalizing switch number. In other side, due to the results of binary PSO(BPSO) and discrete PSO(DPSO) algorithms highly depends on the values of their parameters such as the inertia weight and learning factors, a fuzzy system is employed to adaptively adjust the parameters during the search process. Moreover, the Nelder–Mead simplex search method is combined with the NFAPSO algorithm to improve its performance. Finally, the proposed algorithm is tested on two distribution test feeders. The results of simulation show that the proposed method is very powerful and guarantees to obtain the global optimization.

  9. An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

    Directory of Open Access Journals (Sweden)

    Sergei L Kosakovsky Pond

    2009-11-01

    Full Text Available Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1 are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5% fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance

  10. Community-based radon education programs

    International Nuclear Information System (INIS)

    Laquatra, J.

    1990-01-01

    This paper reports that in the United States, educational programs about radon gas have been developed and implemented by federal and state government entities and other organizations, including the Cooperative Extension Service and affiliated land grant universities. Approaches have included the production of brochures, pamphlets, workshops for targeted audiences, and consumer telephone hotlines. In a free market for radon mitigation products and services, these efforts can be appropriate for their credibility, lack of bias, and individualized approaches. The purpose of this paper is to report on an educational program about radon undertaken by Cornell Cooperative Extension, including county-based workshops targeted to homeowners, housing professionals, high school teachers, and others. An analysis of survey data from program participants forms the basis for a discussion of the effectiveness of the Cooperative Extension Service in reaching the public about this topic

  11. A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers

    DEFF Research Database (Denmark)

    Tian, Yihui; Govindan, Kannan; Zhu, Qinghua

    2014-01-01

    In this study, a system dynamics (SD) model is developed to guide the subsidy policies to promote the diffusion of green supply chain management (GSCM) in China. The relationships of stakeholders such as government, enterprises and consumers are analyzed through evolutionary game theory. Finally...

  12. Saul: Towards Declarative Learning Based Programming.

    Science.gov (United States)

    Kordjamshidi, Parisa; Roth, Dan; Wu, Hao

    2015-07-01

    We present Saul , a new probabilistic programming language designed to address some of the shortcomings of programming languages that aim at advancing and simplifying the development of AI systems. Such languages need to interact with messy, naturally occurring data, to allow a programmer to specify what needs to be done at an appropriate level of abstraction rather than at the data level, to be developed on a solid theory that supports moving to and reasoning at this level of abstraction and, finally, to support flexible integration of these learning and inference models within an application program. Saul is an object-functional programming language written in Scala that facilitates these by (1) allowing a programmer to learn, name and manipulate named abstractions over relational data; (2) supporting seamless incorporation of trainable (probabilistic or discriminative) components into the program, and (3) providing a level of inference over trainable models to support composition and make decisions that respect domain and application constraints. Saul is developed over a declaratively defined relational data model, can use piecewise learned factor graphs with declaratively specified learning and inference objectives, and it supports inference over probabilistic models augmented with declarative knowledge-based constraints. We describe the key constructs of Saul and exemplify its use in developing applications that require relational feature engineering and structured output prediction.

  13. Darwinian foundations for evolutionary economics

    NARCIS (Netherlands)

    Stoelhorst, J.W.

    2008-01-01

    This paper engages with the methodological debate on the contribution of Darwinism to Veblen's (1898) evolutionary research program for economics. I argue that ontological continuity, generalized Darwinism, and multi-level selection are necessary building blocks for an explanatory framework that can

  14. Repository-based software engineering program

    Science.gov (United States)

    Wilson, James

    1992-01-01

    The activities performed during September 1992 in support of Tasks 01 and 02 of the Repository-Based Software Engineering Program are outlined. The recommendations and implementation strategy defined at the September 9-10 meeting of the Reuse Acquisition Action Team (RAAT) are attached along with the viewgraphs and reference information presented at the Institute for Defense Analyses brief on legal and patent issues related to software reuse.

  15. 45 CFR 1306.32 - Center-based program option.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Center-based program option. 1306.32 Section 1306... START PROGRAM HEAD START STAFFING REQUIREMENTS AND PROGRAM OPTIONS Head Start Program Options § 1306.32 Center-based program option. (a) Class size. (1) Head Start classes must be staffed by a teacher and an...

  16. Process Evaluation for a Prison-based Substance Abuse Program.

    Science.gov (United States)

    Staton, Michele; Leukefeld, Carl; Logan, T. K.; Purvis, Rick

    2000-01-01

    Presents findings from a process evaluation conducted in a prison-based substance abuse program in Kentucky. Discusses key components in the program, including a detailed program description, modifications in planned treatment strategies, program documentation, and perspectives of staff and clients. Findings suggest that prison-based programs have…

  17. The evolutionary psychology of hunger.

    Science.gov (United States)

    Al-Shawaf, Laith

    2016-10-01

    An evolutionary psychological perspective suggests that emotions can be understood as coordinating mechanisms whose job is to regulate various psychological and physiological programs in the service of solving an adaptive problem. This paper suggests that it may also be fruitful to approach hunger from this coordinating mechanism perspective. To this end, I put forward an evolutionary task analysis of hunger, generating novel a priori hypotheses about the coordinating effects of hunger on psychological processes such as perception, attention, categorization, and memory. This approach appears empirically fruitful in that it yields a bounty of testable new hypotheses. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. IPTV program recommendation based on combination strategies

    Directory of Open Access Journals (Sweden)

    Li Hao

    2018-01-01

    Full Text Available As a new interactive service technology, IPTV has been extensively studying in the field of TV pro-gram recommendation, but the sparse of the user-program rating matrix and the cold-start problem is a bottleneck that the program recommended accurately. In this paper, a flexible combination of two recommendation strategies proposed, which explored the sparse and cold-start problem as well as the issue of user interest change over time. This paper achieved content-based filtering section and collaborative filtering section according to the two combination strategies, which effectively solved the cold-start program and over the sparse problem and the problem of users interest change over time. The experimental results showed that this combinational recommendation system in optimal parameters compared by using any one of two combination strategies or not using any combination strategy at all, and the reducing range of MAE is [2.7%,3%].The increasing range of precision and recall is [13.8%95.5%] and [0,97.8%], respectively. The experiment showed better results when using combinational recommendation system in optimal parameters than using each combination strategies individually or not using any combination strategy.

  19. The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization.

    Science.gov (United States)

    Błażej, Paweł; Wnȩtrzak, Małgorzata; Mackiewicz, Paweł

    2016-12-01

    One of theories explaining the present structure of canonical genetic code assumes that it was optimized to minimize harmful effects of amino acid replacements resulting from nucleotide substitutions and translational errors. A way to testify this concept is to find the optimal code under given criteria and compare it with the canonical genetic code. Unfortunately, the huge number of possible alternatives makes it impossible to find the optimal code using exhaustive methods in sensible time. Therefore, heuristic methods should be applied to search the space of possible solutions. Evolutionary algorithms (EA) seem to be ones of such promising approaches. This class of methods is founded both on mutation and crossover operators, which are responsible for creating and maintaining the diversity of candidate solutions. These operators possess dissimilar characteristics and consequently play different roles in the process of finding the best solutions under given criteria. Therefore, the effective searching for the potential solutions can be improved by applying both of them, especially when these operators are devised specifically for a given problem. To study this subject, we analyze the effectiveness of algorithms for various combinations of mutation and crossover probabilities under three models of the genetic code assuming different restrictions on its structure. To achieve that, we adapt the position based crossover operator for the most restricted model and develop a new type of crossover operator for the more general models. The applied fitness function describes costs of amino acid replacement regarding their polarity. Our results indicate that the usage of crossover operators can significantly improve the quality of the solutions. Moreover, the simulations with the crossover operator optimize the fitness function in the smaller number of generations than simulations without this operator. The optimal genetic codes without restrictions on their structure

  20. Communicative automata based programming. Society Framework

    Directory of Open Access Journals (Sweden)

    Andrei Micu

    2015-10-01

    Full Text Available One of the aims of this paper is to present a new programming paradigm based on the new paradigms intensively used in IT industry. Implementation of these techniques can improve the quality of code through modularization, not only in terms of entities used by a program, but also in terms of states in which they pass. Another aspect followed in this paper takes into account that in the development of software applications, the transition from the design to the source code is a very expensive step in terms of effort and time spent. Diagrams can hide very important details for simplicity of understanding, which can lead to incorrect or incomplete implementations. To improve this process communicative automaton based programming comes with an intermediate step. We will see how it goes after creating modeling diagrams to communicative automata and then to writing code for each of them. We show how the transition from one step to another is much easier and intuitive.

  1. A New Evolutionary Algorithm Based on Bacterial Evolution and Its Application for Scheduling A Flexible Manufacturing System

    Directory of Open Access Journals (Sweden)

    Chandramouli Anandaraman

    2012-01-01

    Full Text Available A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs. AGVs are used for carrying jobs between the Load/Unload (L/U station and the machines. Experimental results indicate the efficiency of the proposed algorithm in its optimization performance in scheduling is noticeably superior to other evolutionary algorithms when compared to the best results reported in the literature for FMS Scheduling.

  2. Evolutionary agroecology

    DEFF Research Database (Denmark)

    Weiner, Jacob; Du, Yan-Lei; Zhang, Cong

    2017-01-01

    Although the importance of group selection in nature is highly controversial, several researchers have argued that plant breeding for agriculture should be based on group selection, because the goal in agriculture is to optimize population production, not individual fitness. A core hypothesis beh...

  3. 75 FR 67751 - Medicare Program: Community-Based Care Transitions Program (CCTP) Meeting

    Science.gov (United States)

    2010-11-03

    ...] Medicare Program: Community-Based Care Transitions Program (CCTP) Meeting AGENCY: Centers for Medicare... guidance and ask questions about the upcoming Community-based Care Transitions Program. The meeting is open... conference will also provide an overview of the Community-based Care Transitions Program (CCTP) and provide...

  4. Seca Coal-Based Systems Program

    International Nuclear Information System (INIS)

    Alinger, Matthew

    2008-01-01

    This report summarizes the progress made during the August 1, 2006 - May 31, 2008 award period under Cooperative Agreement DE-FC26-05NT42614 for the U. S. Department of Energy/National Energy Technology Laboratory (USDOE/NETL) entitled 'SECA Coal Based Systems'. The initial overall objective of this program was to design, develop, and demonstrate multi-MW integrated gasification fuel cell (IGFC) power plants with >50% overall efficiency from coal (HHV) to AC power. The focus of the program was to develop low-cost, high performance, modular solid oxide fuel cell (SOFC) technology to support coal gas IGFC power systems. After a detailed GE internal review of the SOFC technology, the program was de-scoped at GE's request. The primary objective of this program was then focused on developing a performance degradation mitigation path for high performing, cost-effective solid oxide fuel cells (SOFCs). There were two initial major objectives in this program. These were: (1) Develop and optimize a design of a >100 MWe integrated gasification fuel cell (IGFC) power plant; (2) Resolve identified barrier issues concerning the long-term economic performance of SOFC. The program focused on designing and cost estimating the IGFC system and resolving technical and economic barrier issues relating to SOFC. In doing so, manufacturing options for SOFC cells were evaluated, options for constructing stacks based upon various cell configurations identified, and key performance characteristics were identified. Key factors affecting SOFC performance degradation for cells in contact with metallic interconnects were be studied and a fundamental understanding of associated mechanisms was developed using a fixed materials set. Experiments and modeling were carried out to identify key processes/steps affecting cell performance degradation under SOFC operating conditions. Interfacial microstructural and elemental changes were characterized, and their relationships to observed degradation

  5. Seca Coal-Based Systems Program

    Energy Technology Data Exchange (ETDEWEB)

    Matthew Alinger

    2008-05-31

    This report summarizes the progress made during the August 1, 2006 - May 31, 2008 award period under Cooperative Agreement DE-FC26-05NT42614 for the U. S. Department of Energy/National Energy Technology Laboratory (USDOE/NETL) entitled 'SECA Coal Based Systems'. The initial overall objective of this program was to design, develop, and demonstrate multi-MW integrated gasification fuel cell (IGFC) power plants with >50% overall efficiency from coal (HHV) to AC power. The focus of the program was to develop low-cost, high performance, modular solid oxide fuel cell (SOFC) technology to support coal gas IGFC power systems. After a detailed GE internal review of the SOFC technology, the program was de-scoped at GE's request. The primary objective of this program was then focused on developing a performance degradation mitigation path for high performing, cost-effective solid oxide fuel cells (SOFCs). There were two initial major objectives in this program. These were: (1) Develop and optimize a design of a >100 MWe integrated gasification fuel cell (IGFC) power plant; (2) Resolve identified barrier issues concerning the long-term economic performance of SOFC. The program focused on designing and cost estimating the IGFC system and resolving technical and economic barrier issues relating to SOFC. In doing so, manufacturing options for SOFC cells were evaluated, options for constructing stacks based upon various cell configurations identified, and key performance characteristics were identified. Key factors affecting SOFC performance degradation for cells in contact with metallic interconnects were be studied and a fundamental understanding of associated mechanisms was developed using a fixed materials set. Experiments and modeling were carried out to identify key processes/steps affecting cell performance degradation under SOFC operating conditions. Interfacial microstructural and elemental changes were characterized, and their relationships to observed

  6. An Evidence-Based Assessment of Faith-Based Programs: Do Faith-Based Programs "Work" to Reduce Recidivism?

    Science.gov (United States)

    Dodson, Kimberly D.; Cabage, Leann N.; Klenowski, Paul M.

    2011-01-01

    Faith-based organizations administer many of the prison-based programs aimed at reducing recidivism. Many of these organizations also manage treatment programs for substance abusers, at-risk juveniles, and ex-offenders. Much of the research on religiosity and delinquency indicates that the two are inversely related. Therefore, it seems plausible…

  7. Attractive evolutionary equilibria

    NARCIS (Netherlands)

    Joosten, Reinoud A.M.G.; Roorda, Berend

    2011-01-01

    We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary

  8. Evolutionary Stable Strategy

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.

  9. Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems

    International Nuclear Information System (INIS)

    Yousefi, Moslem; Darus, Amer Nordin; Yousefi, Milad; Hooshyar, Danial

    2015-01-01

    The complicated task of design optimization of compact heat exchangers (CHEs) have been effectively performed by using evolutionary algorithms (EAs) in the recent years. However, mainly due to difficulties of handling extra variables, the design approach has been based on constant rates of heat duty in the available literature. In this paper, a new design strategy is presented where variable operating conditions, which better represent real-world problems, are considered. The proposed strategy is illustrated using a case study for design of a plate-fin heat exchanger though it can be employed for all types of heat exchangers without much change. Learning automata based particle swarm optimization (LAPSO), is employed for handling nine design variables while satisfying various equality and inequality constraints. For handling the constraints, a novel feasibility based ranking strategy (FBRS) is introduced. The numerical results indicate that the design based on variable heat duties yields in more cost savings and superior thermodynamics efficiency comparing to a conventional design approach. Furthermore, the proposed algorithm has shown a superior performance in finding the near-optimum solution for this task when it is compared to the most popular evolutionary algorithms in engineering applications, i.e. genetic algorithm (GA) and particle swarm optimization (PSO). - Highlights: • Multi-stage design of heat exchangers is presented. • Feasibility based ranking strategy is employed for constraint handling. • Learning abilities added to particle swarm optimization

  10. Mathematical programming solver based on local search

    CERN Document Server

    Gardi, Frédéric; Darlay, Julien; Estellon, Bertrand; Megel, Romain

    2014-01-01

    This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kind of mathematical programming solver, namely LocalSolver, based on neighborhood search. First, an iconoclast methodology is presented to design and engineer local search algorithms. The authors' concern about industrializing local search approaches is of particular interest for practitioners. This methodology is applied to solve two industrial problems with high economic stakes. Software based on local search induces ex...

  11. From the "Modern Synthesis" to cybernetics: Ivan Ivanovich Schmalhausen (1884-1963) and his research program for a synthesis of evolutionary and developmental biology.

    Science.gov (United States)

    Levit, Georgy S; Hossfeld, Uwe; Olsson, Lennart

    2006-03-15

    Ivan I. Schmalhausen was one of the central figures in the Russian development of the "Modern Synthesis" in evolutionary biology. He is widely cited internationally even today. Schmalhausen developed the main principles of his theory facing the danger of death in the totalitarian Soviet Union. His great services to evolutionary and theoretical biology are indisputable. However, the received view of Schmalhausen's contributions to evolutionary biology makes an unbiased reading of his texts difficult. Here we show that taking all of his works into consideration (including those only available in Russian) paints a much more dynamic and exciting picture of what he tried to achieve. Schmalhausen pioneered the integration of a developmental perspective into evolutionary thinking. A main tool for achieving this was his approach to living objects as complex multi-level self-regulating systems. Schmalhausen put enormous effort into bringing this idea into fruition during the final stages of his career by combining evolutionary theory with cybernetics. His results and ideas remain thought-provoking, and his texts are of more than just historical interest. Copyright 2006 Wiley-Liss, Inc.

  12. Evolutionary developmental perspective for the origin of turtles: the folding theory for the shell based on the developmental nature of the carapacial ridge.

    Science.gov (United States)

    Kuratani, Shigeru; Kuraku, Shigehiro; Nagashima, Hiroshi

    2011-01-01

    The body plan of the turtle represents an example of evolutionary novelty for acquisition of the shell. Unlike similar armors in other vertebrate groups, the turtle shell involves the developmental repatterning of the axial skeleton and exhibits an unusual topography of musculoskeletal elements. Thus, the turtle provides an ideal case study for understanding changes in the developmental program associated with the morphological evolution of vertebrates. In this article, the evolution of the turtle-specific body plan is reviewed and discussed. The key to understanding shell patterning lies in the modification of the ribs, for which the carapacial ridge (CR), a turtle-specific embryonic anlage, is assumed to be responsible. The growth of the ribs is arrested in the axial part of the body, allowing dorsal and lateral oriented growth to encapsulate the scapula. Although the CR does not appear to induce this axial arrest per se, it has been shown to support the fan-shaped patterning of the ribs, which occurs concomitant with marginal growth of the carapace along the line of the turtle-specific folding that takes place in the lateral body wall. During the process of the folding, some trunk muscles maintain their ancestral connectivities, whereas the limb muscles establish new attachments specific to the turtle. The turtle body plan can thus be explained with our knowledge of vertebrate anatomy and developmental biology, consistent with the evolutionary origin of the turtle suggested by the recently discovered fossil species, Odontochelys. © 2011 Wiley Periodicals, Inc.

  13. Evolutionary molecular medicine.

    Science.gov (United States)

    Nesse, Randolph M; Ganten, Detlev; Gregory, T Ryan; Omenn, Gilbert S

    2012-05-01

    Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

  14. 76 FR 39006 - Medicare Program; Hospital Inpatient Value-Based Purchasing Program; Correction

    Science.gov (United States)

    2011-07-05

    ... and 480 [CMS-3239-CN] RIN 0938-AQ55 Medicare Program; Hospital Inpatient Value-Based Purchasing... Value-Based Purchasing Program.'' DATES: Effective Date: These corrections are effective on July 1, 2011... for the hospital value-based purchasing program. Therefore, in section III. 6. and 7. of this notice...

  15. Evolutionary Aesthetics and Print Advertising

    Directory of Open Access Journals (Sweden)

    Kamil Luczaj

    2015-06-01

    Full Text Available The article analyzes the extent to which predictions based on the theory of evolutionary aesthetics are utilized by the advertising industry. The purpose of a comprehensive content analysis of print advertising is to determine whether the items indicated by evolutionists such as animals, flowers, certain types of landscapes, beautiful humans, and some colors are part of real advertising strategies. This article has shown that many evolutionary hypotheses (although not all of them are supported by empirical data. Along with these hypotheses, some inferences from Bourdieu’s cultural capital theory were tested. It turned out that advertising uses both biological schemata and cultural patterns to make an image more likable.

  16. IDEA: Interactive Display for Evolutionary Analyses.

    Science.gov (United States)

    Egan, Amy; Mahurkar, Anup; Crabtree, Jonathan; Badger, Jonathan H; Carlton, Jane M; Silva, Joana C

    2008-12-08

    The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood) suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. We have developed IDEA (Interactive Display for Evolutionary Analyses), an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

  17. IDEA: Interactive Display for Evolutionary Analyses

    Directory of Open Access Journals (Sweden)

    Carlton Jane M

    2008-12-01

    Full Text Available Abstract Background The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. Results We have developed IDEA (Interactive Display for Evolutionary Analyses, an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. Conclusion IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

  18. Evolutionary and Ecological Consequences of Interspecific Hybridization in Cladocerans

    NARCIS (Netherlands)

    Schwenk, K.; Spaak, P.

    1995-01-01

    The evolutionary process of interspecific hybridization in cladocerans is reviewed based on ecological and population genetic data. The evolutionary consequences of hybridization, biogeographic patterns and fitness comparisons are analyzed within the conceptual framework of theories on

  19. Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective

    Science.gov (United States)

    Xu, Chuanpei; Niu, Junhao; Ling, Jing; Wang, Suyan

    2018-03-01

    In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

  20. The ABCs of an evolutionary education science: The academic, behavioral, and cultural implications of an evolutionary approach to education theory and practice

    Science.gov (United States)

    Kauffman, Rick, Jr.

    Calls for improving research-informed policy in education are everywhere. Yet, while there is an increasing trend towards science-based practice, there remains little agreement over which of the sciences to consult and how to organize a collective effort between them. What Education lacks is a general theoretical framework through which policies can be constructed, implemented, and assessed. This dissertation submits that evolutionary theory can provide a suitable framework for coordinating educational policies and practice, and can provide the entire field of education with a clearer sense of how to better manage the learning environment. This dissertation explores two broad paths that outline the conceptual foundations for an Evolutionary Education Science: "Teaching Evolution" and "Using Evolution to Teach." Chapter 1 introduces both of these themes. After describing why evolutionary science is best suited for organizing education research and practice, Chapter 1 proceeds to "teach" an overview of the "evolutionary toolkit"---the mechanisms and principles that underlie the modern evolutionary perspective. The chapter then employs the "toolkit" in examining education from an evolutionary perspective, outlining the evolutionary precepts that can guide theorizing and research in education, describing how educators can "use evolution to teach.". Chapters 2-4 expand on this second theme. Chapters 2 and 3 describe an education program for at-risk 9th and 10th grade students, the Regents Academy, designed entirely with evolutionary principles in mind. The program was rigorously assessed in a randomized control design and has demonstrated success at improving students' academic performance (Chapter 2) and social & behavioral development (Chapter 3). Chapter 4 examines current teaching strategies that underlie effective curriculum-instruction-assessment practices and proposes a framework for organizing successful, evidence-based strategies for neural

  1. A taxonomic framework for emerging groups of ecologically important marine gammaproteobacteria based on the reconstruction of evolutionary relationships using genome-scale data

    Directory of Open Access Journals (Sweden)

    Stefan eSpring

    2015-04-01

    Full Text Available In recent years a large number of isolates were obtained from saline environments that are phylogenetically related to distinct clades of oligotrophic marine gammaproteobacteria, which were originally identified in seawater samples using cultivation independent methods and are characterized by high seasonal abundances in coastal environments. To date a sound taxonomic framework for the classification of these ecologically important isolates and related species in accordance with their evolutionary relationships is missing.In this study we demonstrate that a reliable allocation of members of the oligotrophic marine gammaproteobacteria (OMG group and related species to higher taxonomic ranks is possible by phylogenetic analyses of whole proteomes but also of the RNA polymerase beta subunit, whereas phylogenetic reconstructions based on 16S rRNA genes alone resulted in unstable tree topologies with only insignificant bootstrap support. The identified clades could be correlated with distinct phenotypic traits illustrating an adaptation to common environmental factors in their evolutionary history. Genome wide gene-content analyses revealed the existence of two distinct ecological guilds within the analyzed lineage of marine gammaproteobacteria which can be distinguished by their trophic strategies. Based on our results a novel order within the class Gammaproteobacteria is proposed, which is designated Cellvibrionales ord. nov. and comprises the five novel families Cellvibrionaceae fam. nov., Halieaceae fam. nov., Microbulbiferaceae fam. nov., Porticoccaceae fam. nov., and Spongiibacteraceae fam. nov.

  2. Evolutionary design assistants for architecture

    Directory of Open Access Journals (Sweden)

    N. Onur Sönmez

    2015-04-01

    Full Text Available In its parallel pursuit of an increased competitivity for design offices and more pleasurable and easier workflows for designers, artificial design intelligence is a technical, intellectual, and political challenge. While human-machine cooperation has become commonplace through Computer Aided Design (CAD tools, a more improved collaboration and better support appear possible only through an endeavor into a kind of artificial design intelligence, which is more sensitive to the human perception of affairs. Considered as part of the broader Computational Design studies, the research program of this quest can be called Artificial / Autonomous / Automated Design (AD. The current available level of Artificial Intelligence (AI for design is limited and a viable aim for current AD would be to develop design assistants that are capable of producing drafts for various design tasks. Thus, the overall aim of this thesis is the development of approaches, techniques, and tools towards artificial design assistants that offer a capability for generating drafts for sub-tasks within design processes. The main technology explored for this aim is Evolutionary Computation (EC, and the target design domain is architecture. The two connected research questions of the study concern, first, the investigation of the ways to develop an architectural design assistant, and secondly, the utilization of EC for the development of such assistants. While developing approaches, techniques, and computational tools for such an assistant, the study also carries out a broad theoretical investigation into the main problems, challenges, and requirements towards such assistants on a rather overall level. Therefore, the research is shaped as a parallel investigation of three main threads interwoven along several levels, moving from a more general level to specific applications. The three research threads comprise, first, theoretical discussions and speculations with regard to both

  3. Phylogenetic inference with weighted codon evolutionary distances.

    Science.gov (United States)

    Criscuolo, Alexis; Michel, Christian J

    2009-04-01

    We develop a new approach to estimate a matrix of pairwise evolutionary distances from a codon-based alignment based on a codon evolutionary model. The method first computes a standard distance matrix for each of the three codon positions. Then these three distance matrices are weighted according to an estimate of the global evolutionary rate of each codon position and averaged into a unique distance matrix. Using a large set of both real and simulated codon-based alignments of nucleotide sequences, we show that this approach leads to distance matrices that have a significantly better treelikeness compared to those obtained by standard nucleotide evolutionary distances. We also propose an alternative weighting to eliminate the part of the noise often associated with some codon positions, particularly the third position, which is known to induce a fast evolutionary rate. Simulation results show that fast distance-based tree reconstruction algorithms on distance matrices based on this codon position weighting can lead to phylogenetic trees that are at least as accurate as, if not better, than those inferred by maximum likelihood. Finally, a well-known multigene dataset composed of eight yeast species and 106 codon-based alignments is reanalyzed and shows that our codon evolutionary distances allow building a phylogenetic tree which is similar to those obtained by non-distance-based methods (e.g., maximum parsimony and maximum likelihood) and also significantly improved compared to standard nucleotide evolutionary distance estimates.

  4. A Theory Based Introductory Programming Course

    DEFF Research Database (Denmark)

    Hansen, Michael Reichhardt; Kristensen, Jens Thyge; Rischel, Hans

    1999-01-01

    This paper presents an introductory programming course designed to teach programming as an intellectual activity. The course emphasizes understandable concepts which can be useful in designing programs, while the oddities of today's technology are considered of secondary importance. An important...... goal is to fight the trial-and-error approach to programming which is a result of the students battles with horribly designed and documented systems and languages prior to their studies at university. Instead, the authors strive for giving the students a good experience of programming as a systematic......, intellectual activity where the solution of a programming problem can be described in an understandable way. The approach is illustrated by an example which is a commented solution of a problem posed to the students in the course....

  5. Adaptive Test Selection for Factorization-based Surrogate Fitness in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Krawiec Krzysztof

    2017-12-01

    Full Text Available Genetic programming (GP is a variant of evolutionary algorithm where the entities undergoing simulated evolution are computer programs. A fitness function in GP is usually based on a set of tests, each of which defines the desired output a correct program should return for an exemplary input. The outcomes of interactions between programs and tests in GP can be represented as an interaction matrix, with rows corresponding to programs in the current population and columns corresponding to tests. In previous work, we proposed SFIMX, a method that performs only a fraction of interactions and employs non-negative matrix factorization to estimate the outcomes of remaining ones, shortening GP’s runtime. In this paper, we build upon that work and propose three extensions of SFIMX, in which the subset of tests drawn to perform interactions is selected with respect to test difficulty. The conducted experiment indicates that the proposed extensions surpass the original SFIMX on a suite of discrete GP benchmarks.

  6. The role of duplications in the evolution of genomes highlights the need for evolutionary-based approaches in comparative genomics

    Directory of Open Access Journals (Sweden)

    Levasseur Anthony

    2011-02-01

    Full Text Available Abstract Understanding the evolutionary plasticity of the genome requires a global, comparative approach in which genetic events are considered both in a phylogenetic framework and with regard to population genetics and environmental variables. In the mechanisms that generate adaptive and non-adaptive changes in genomes, segmental duplications (duplication of individual genes or genomic regions and polyploidization (whole genome duplications are well-known driving forces. The probability of fixation and maintenance of duplicates depends on many variables, including population sizes and selection regimes experienced by the corresponding genes: a combination of stochastic and adaptive mechanisms has shaped all genomes. A survey of experimental work shows that the distinction made between fixation and maintenance of duplicates still needs to be conceptualized and mathematically modeled. Here we review the mechanisms that increase or decrease the probability of fixation or maintenance of duplicated genes, and examine the outcome of these events on the adaptation of the organisms. Reviewers This article was reviewed by Dr. Etienne Joly, Dr. Lutz Walter and Dr. W. Ford Doolittle.

  7. Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis

    Science.gov (United States)

    Fokas, Alexander S.; Cole, Daniel J.; Ahnert, Sebastian E.; Chin, Alex W.

    2016-01-01

    Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function. PMID:27623708

  8. Evolutionary search for new high-k dielectric materials: methodology and applications to hafnia-based oxides.

    Science.gov (United States)

    Zeng, Qingfeng; Oganov, Artem R; Lyakhov, Andriy O; Xie, Congwei; Zhang, Xiaodong; Zhang, Jin; Zhu, Qiang; Wei, Bingqing; Grigorenko, Ilya; Zhang, Litong; Cheng, Laifei

    2014-02-01

    High-k dielectric materials are important as gate oxides in microelectronics and as potential dielectrics for capacitors. In order to enable computational discovery of novel high-k dielectric materials, we propose a fitness model (energy storage density) that includes the dielectric constant, bandgap, and intrinsic breakdown field. This model, used as a fitness function in conjunction with first-principles calculations and the global optimization evolutionary algorithm USPEX, efficiently leads to practically important results. We found a number of high-fitness structures of SiO2 and HfO2, some of which correspond to known phases and some of which are new. The results allow us to propose characteristics (genes) common to high-fitness structures--these are the coordination polyhedra and their degree of distortion. Our variable-composition searches in the HfO2-SiO2 system uncovered several high-fitness states. This hybrid algorithm opens up a new avenue for discovering novel high-k dielectrics with both fixed and variable compositions, and will speed up the process of materials discovery.

  9. Effects of behavioral response and vaccination policy on epidemic spreading--an approach based on evolutionary-game dynamics.

    Science.gov (United States)

    Zhang, Hai-Feng; Wu, Zhi-Xi; Tang, Ming; Lai, Ying-Cheng

    2014-07-11

    How effective are governmental incentives to achieve widespread vaccination coverage so as to prevent epidemic outbreak? The answer largely depends on the complex interplay among the type of incentive, individual behavioral responses, and the intrinsic epidemic dynamics. By incorporating evolutionary games into epidemic dynamics, we investigate the effects of two types of incentives strategies: partial-subsidy policy in which certain fraction of the cost of vaccination is offset, and free-subsidy policy in which donees are randomly selected and vaccinated at no cost. Through mean-field analysis and computations, we find that, under the partial-subsidy policy, the vaccination coverage depends monotonically on the sensitivity of individuals to payoff difference, but the dependence is non-monotonous for the free-subsidy policy. Due to the role models of the donees for relatively irrational individuals and the unchanged strategies of the donees for rational individuals, the free-subsidy policy can in general lead to higher vaccination coverage. Our findings indicate that any disease-control policy should be exercised with extreme care: its success depends on the complex interplay among the intrinsic mathematical rules of epidemic spreading, governmental policies, and behavioral responses of individuals.

  10. Attractive evolutionary equilibria

    OpenAIRE

    Roorda, Berend; Joosten, Reinoud

    2011-01-01

    We present attractiveness, a refinement criterion for evolutionary equilibria. Equilibria surviving this criterion are robust to small perturbations of the underlying payoff system or the dynamics at hand. Furthermore, certain attractive equilibria are equivalent to others for certain evolutionary dynamics. For instance, each attractive evolutionarily stable strategy is an attractive evolutionarily stable equilibrium for certain barycentric ray-projection dynamics, and vice versa.

  11. Polymorphic Evolutionary Games.

    Science.gov (United States)

    Fishman, Michael A

    2016-06-07

    In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. What Is Sexual Orientation All About? Explaining an Evolutionary Paradox

    OpenAIRE

    Brad Bowins

    2015-01-01

    Numerous psychological, biological, and evolutionary theories have been proposed to explain sexual orientation. For a theory to be valid it must account for the evolutionary or Darwinian paradox of how homosexual behavior seemingly blocking evolutionary fitness could have evolved. Typically it is only evolutionary based theories that attempt to address this issue. All theories proposed to date have limitations, a major one being that they tend to be specific for male or female sexual orientat...

  13. Exercise, Affect, and Adherence: An Evolutionary Perspective

    Directory of Open Access Journals (Sweden)

    Harold Lee

    2016-08-01

    Full Text Available The low rates of regular exercise and overall physical activity (PA in the general population represent a significant public health challenge. Previous research suggests that, for many people, exercise leads to a negative affective response and, in turn, reduced likelihood of future exercise. The purpose of this paper is to examine this exercise-affect-adherence relationship from an evolutionary perspective. Specifically, we argue that low rates of physical exercise in the general population are a function of the evolved human tendency to avoid unnecessary physical exertion. This innate tendency evolved because it allowed our evolutionary ancestors to conserve energy for physical activities that had immediate adaptive utility such as pursuing prey, escaping predators, and engaging in social and reproductive behaviors. The commonly observed negative affective response to exercise is an evolved proximate psychological mechanism through which humans avoid unnecessary energy expenditure. The fact that the human tendencies toward negative affective response to and avoidance of unnecessary physical activities are innate does not mean that they are unchangeable. Indeed, it is only because of human-engineered changes in our environmental conditions (i.e., it is no longer necessary for us to work for our food that our predisposition to avoid unnecessary physical exertion has become a liability. Thus, it is well within our capabilities to reengineer our environments to once again make PA necessary or, at least, to serve an immediate functional purpose. We propose a two-pronged approach to PA promotion based on this evolutionary functional perspective: First, to promote exercise and other physical activities that are perceived to have an immediate purpose, and second, to instill greater perceived purpose for a wider range of physical activities. We posit that these strategies are more likely to result in more positive (or at least less negative affective

  14. O Programa Brasileiro de genética evolucionária de populações, de Theodosius Dobzhansky Theodosius Dobzhansky's Brazilian program of evolutionary population genetics

    Directory of Open Access Journals (Sweden)

    Thomas F. Glick

    2008-01-01

    Full Text Available Nas décadas de 1940 e 1950, a Fundação Rockefeller estabeleceu um programa para o desenvolvimento da genética de populações na Universidade de São Paulo, sob a direção do geneticista norte-americano Theodosius Dobzhansky, nascido na Rússia. O grande sucesso desse programa foi atribuído ao tipo de organização da pesquisa, realizada em grupos, prática introduzida por Dobzhansky. O presente artigo analisa essa conclusão, com base nas reminiscências do geneticista suíço Hans Burla, membro estrangeiro do grupo original de Dobzhansky.In the 1940s and 50s the Rockefeller Foundation established a program for the development of population genetics at the Universidade de São Paulo under the direction of the Russian/North American geneticist Theodosius Dobzhansky. The great success of this program was said to have been the result of the kind of research organization, in teams, that Dobzhansky introduced. An evaluation of this conclusion is analyzed, based on the reminiscence of the Swiss geneticist, Hans Burla, a foreign member of the original Dobzhansky group.

  15. Saul: Towards Declarative Learning Based Programming

    OpenAIRE

    Kordjamshidi, Parisa; Roth, Dan; Wu, Hao

    2015-01-01

    We present Saul, a new probabilistic programming language designed to address some of the shortcomings of programming languages that aim at advancing and simplifying the development of AI systems. Such languages need to interact with messy, naturally occurring data, to allow a programmer to specify what needs to be done at an appropriate level of abstraction rather than at the data level, to be developed on a solid theory that supports moving to and reasoning at this level of abstraction and,...

  16. Geometric Generalisation of Surrogate Model-Based Optimisation to Combinatorial and Program Spaces

    Directory of Open Access Journals (Sweden)

    Yong-Hyuk Kim

    2014-01-01

    Full Text Available Surrogate models (SMs can profitably be employed, often in conjunction with evolutionary algorithms, in optimisation in which it is expensive to test candidate solutions. The spatial intuition behind SMs makes them naturally suited to continuous problems, and the only combinatorial problems that have been previously addressed are those with solutions that can be encoded as integer vectors. We show how radial basis functions can provide a generalised SM for combinatorial problems which have a geometric solution representation, through the conversion of that representation to a different metric space. This approach allows an SM to be cast in a natural way for the problem at hand, without ad hoc adaptation to a specific representation. We test this adaptation process on problems involving binary strings, permutations, and tree-based genetic programs.

  17. Putative recombination events and evolutionary history of five economically important viruses of fruit trees based on coat protein-encoding gene sequence analysis.

    Science.gov (United States)

    Boulila, Moncef

    2010-06-01

    To enhance the knowledge of recombination as an evolutionary process, 267 accessions retrieved from GenBank were investigated, all belonging to five economically important viruses infecting fruit crops (Plum pox, Apple chlorotic leaf spot, Apple mosaic, Prune dwarf, and Prunus necrotic ringspot viruses). Putative recombinational events were detected in the coat protein (CP)-encoding gene using RECCO and RDP version 3.31beta algorithms. Based on RECCO results, all five viruses were shown to contain potential recombination signals in the CP gene. Reconstructed trees with modified topologies were proposed. Furthermore, RECCO performed better than the RDP package in detecting recombination events and exhibiting their evolution rate along the sequences of the five viruses. RDP, however, provided the possible major and minor parents of the recombinants. Thus, the two methods should be considered complementary.

  18. New PARSEC data base of α-enhanced stellar evolutionary tracks and isochrones - I. Calibration with 47 Tuc (NGC 104) and the improvement on RGB bump

    Science.gov (United States)

    Fu, Xiaoting; Bressan, Alessandro; Marigo, Paola; Girardi, Léo; Montalbán, Josefina; Chen, Yang; Nanni, Ambra

    2018-05-01

    Precise studies on the Galactic bulge, globular cluster, Galactic halo, and Galactic thick disc require stellar models with α enhancement and various values of helium content. These models are also important for extra-Galactic population synthesis studies. For this purpose, we complement the existing PARSEC models, which are based on the solar partition of heavy elements, with α-enhanced partitions. We collect detailed measurements on the metal mixture and helium abundance for the two populations of 47 Tuc (NGC 104) from the literature, and calculate stellar tracks and isochrones with these α-enhanced compositions. By fitting the precise colour-magnitude diagram with HST ACS/WFC data, from low main sequence till horizontal branch (HB), we calibrate some free parameters that are important for the evolution of low mass stars like the mixing at the bottom of the convective envelope. This new calibration significantly improves the prediction of the red giant branch bump (RGBB) brightness. Comparison with the observed RGB and HB luminosity functions also shows that the evolutionary lifetimes are correctly predicted. As a further result of this calibration process, we derive the age, distance modulus, reddening, and the RGB mass-loss for 47 Tuc. We apply the new calibration and α-enhanced mixtures of the two 47 Tuc populations ([α/Fe] ˜ 0.4 and 0.2) to other metallicities. The new models reproduce the RGB bump observations much better than previous models. This new PARSEC data base, with the newly updated α-enhanced stellar evolutionary tracks and isochrones, will also be a part of the new stellar products for Gaia.

  19. Protocol-Based Verification of Message-Passing Parallel Programs

    DEFF Research Database (Denmark)

    López-Acosta, Hugo-Andrés; Eduardo R. B. Marques, Eduardo R. B.; Martins, Francisco

    2015-01-01

    We present ParTypes, a type-based methodology for the verification of Message Passing Interface (MPI) programs written in the C programming language. The aim is to statically verify programs against protocol specifications, enforcing properties such as fidelity and absence of deadlocks. We develo...

  20. Optimization Research of Generation Investment Based on Linear Programming Model

    Science.gov (United States)

    Wu, Juan; Ge, Xueqian

    Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

  1. Phylogeny and evolutionary history of Leymus (Triticeae; Poaceae based on a single-copy nuclear gene encoding plastid acetyl-CoA carboxylase

    Directory of Open Access Journals (Sweden)

    Ding Cun-Bang

    2009-10-01

    Full Text Available Abstract Background Single- and low- copy genes are less likely subject to concerted evolution, thus making themselves ideal tools for studying the origin and evolution of polyploid taxa. Leymus is a polyploid genus with a diverse array of morphology, ecology and distribution in Triticeae. The genomic constitution of Leymus was assigned as NsXm, where Ns was presumed to be originated from Psathyrostachys, while Xm represented a genome of unknown origin. In addition, little is known about the evolutionary history of Leymus. Here, we investigate the phylogenetic relationship, genome donor, and evolutionary history of Leymus based on a single-copy nuclear Acc1 gene. Results Two homoeologues of the Acc1 gene were isolated from nearly all the sampled Leymus species using allele-specific primer and were analyzed with those from 35 diploid taxa representing 18 basic genomes in Triticeae. Sequence diversity patterns and genealogical analysis suggested that (1 Leymus is closely related to Psathyrostachys, Agropyron, and Eremopyrum; (2 Psathyrostachys juncea is an ancestral Ns-genome donor of Leymus species; (3 the Xm genome in Leymus may be originated from an ancestral lineage of Agropyron and Eremopyrum triticeum; (4 the Acc1 sequences of Leymus species from the Qinghai-Tibetan plateau are evolutionarily distinct; (5 North America Leymus species might originate from colonization via the Bering land bridge; (6 Leymus originated about 11-12MYA in Eurasia, and adaptive radiation might have occurred in Leymus during the period of 3.7-4.3 MYA and 1.7-2.1 MYA. Conclusion Leymus species have allopolyploid origin. It is hypothesized that the adaptive radiation of Leymus species might have been triggered by the recent upliftings of the Qinghai-Tibetan plateau and subsequent climatic oscillations. Adaptive radiation may have promoted the rapid speciation, as well as the fixation of unique morphological characters in Leymus. Our results shed new light on our

  2. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  3. A METHOD FOR SOLVING LINEAR PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS BASED ON MULTIOBJECTIVE LINEAR PROGRAMMING TECHNIQUE

    OpenAIRE

    M. ZANGIABADI; H. R. MALEKI

    2007-01-01

    In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...

  4. Programming languages and operating systems used in data base systems

    International Nuclear Information System (INIS)

    Radulescu, T.G.

    1977-06-01

    Some apsects of the use of the programming languages and operating systems in the data base systems are presented. There are four chapters in this paper. In the first chapter we present some generalities about the programming languages. In the second one we describe the use of the programming languages in the data base systems. A classification of the programming languages used in data base systems is presented in the third one. An overview of the operating systems is made in the last chapter. (author)

  5. Strategies for measuring evolutionary conservation of RNA secondary structures

    Directory of Open Access Journals (Sweden)

    Hofacker Ivo L

    2008-02-01

    Full Text Available Abstract Background Evolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential. Results We systematically assessed the ability of various measures to detect conserved RNA structures in multiple sequence alignments. We tested three existing and eight novel strategies that are based on metrics of folding energies, metrics of single optimal structure predictions, and metrics of structure ensembles. We find that the folding energy based SCI score used in the RNAz program and a simple base-pair distance metric are by far the most accurate. The use of more complex metrics like for example tree editing does not improve performance. A variant of the SCI performed particularly well on highly conserved alignments and is thus a viable alternative when only little evolutionary information is available. Surprisingly, ensemble based methods that, in principle, could benefit from the additional information contained in sub-optimal structures, perform particularly poorly. As a general trend, we observed that methods that include a consensus structure prediction outperformed equivalent methods that only consider pairwise comparisons. Conclusion Structural conservation can be measured accurately with relatively simple and intuitive metrics. They have the potential to form the basis of future RNA gene finders, that face new challenges like finding lineage specific structures or detecting mis-aligned sequences.

  6. Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

    Science.gov (United States)

    Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat

    2016-11-01

    There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  7. Passivity and Evolutionary Game Dynamics

    KAUST Repository

    Park, Shinkyu; Shamma, Jeff S.; Martins, Nuno C.

    2018-01-01

    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  8. Passivity and Evolutionary Game Dynamics

    KAUST Repository

    Park, Shinkyu

    2018-03-21

    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  9. Building Rural Communities through School-Based Agriculture Programs

    Science.gov (United States)

    Martin, Michael J.; Henry, Anna

    2012-01-01

    The purpose of this study was to develop a substantive theory for community development by school-based agriculture programs through grounded theory methodology. Data for the study included in-depth interviews and field observations from three school-based agriculture programs in three non-metropolitan counties across a Midwestern state. The…

  10. An evidence-based rehabilitation program for tracheoesophageal speakers

    NARCIS (Netherlands)

    Jongmans, P.; Rossum, M.; As-Brooks, C.; Hilgers, F.; Pols, L.; Hilgers, F.J.M.; Pols, L.C.W.; van Rossum, M.; van den Brekel, M.W.M.

    2008-01-01

    Objectives: to develop an evidence-based therapy program aimed at improving tracheoesophageal speech intelligibility. The therapy program is based on particular problems found for TE speakers in a previous study as performed by the authors. Patients/Materials and Methods: 9 male laryngectomized

  11. Evolutionary theory and the naturalist fallacy

    DEFF Research Database (Denmark)

    Grodal, Torben Kragh

    2008-01-01

    that great work of art are also automatically fitness-enhancing in the present day environment, at that there are simple correllations between whether a work of art has a high aesthetic value and whether it is fitness-enhancing or not.  Keywords :  Evolutionary aesthetics, film theory, literary theory......The article is an invited response to a target article by Joseph Carroll entitled "An evolutionary paradigm for literary study". It argues that the target article  misuse the fact that works of art are based on adaptations that were fitness-enhancing in the era of evolutionary adaptations to claim...

  12. Origins of evolutionary transitions

    Indian Academy of Sciences (India)

    2014-03-15

    Mar 15, 2014 ... ... of events: 'Entities that were capable of independent replication ... There have been many major evolutionary events that this definition of .... selection at level x to exclusive selection at x – will probably require a multiplicity ...

  13. Evolutionary relationships among Astroviridae

    NARCIS (Netherlands)

    Lukashov, Vladimir V.; Goudsmit, Jaap

    2002-01-01

    To study the evolutionary relationships among astroviruses, all available sequences for members of the family Astroviridae were collected. Phylogenetic analysis distinguished two deep-rooted groups: one comprising mammalian astroviruses, with ovine astrovirus being an outlier, and the other

  14. Finite Countermodel Based Verification for Program Transformation (A Case Study

    Directory of Open Access Journals (Sweden)

    Alexei P. Lisitsa

    2015-12-01

    Full Text Available Both automatic program verification and program transformation are based on program analysis. In the past decade a number of approaches using various automatic general-purpose program transformation techniques (partial deduction, specialization, supercompilation for verification of unreachability properties of computing systems were introduced and demonstrated. On the other hand, the semantics based unfold-fold program transformation methods pose themselves diverse kinds of reachability tasks and try to solve them, aiming at improving the semantics tree of the program being transformed. That means some general-purpose verification methods may be used for strengthening program transformation techniques. This paper considers the question how finite countermodels for safety verification method might be used in Turchin's supercompilation method. We extract a number of supercompilation sub-algorithms trying to solve reachability problems and demonstrate use of an external countermodel finder for solving some of the problems.

  15. A systematic review of school-based suicide prevention programs.

    Science.gov (United States)

    Katz, Cara; Bolton, Shay-Lee; Katz, Laurence Y; Isaak, Corinne; Tilston-Jones, Toni; Sareen, Jitender

    2013-10-01

    Suicide is one of the leading causes of death among youth today. Schools are a cost-effective way to reach youth, yet there is no conclusive evidence regarding the most effective prevention strategy. We conducted a systematic review of the empirical literature on school-based suicide prevention programs. Studies were identified through MEDLINE and Scopus searches, using keywords such as "suicide, education, prevention and program evaluation." Additional studies were identified with a manual search of relevant reference lists. Individual studies were rated for level of evidence, and the programs were given a grade of recommendation. Five reviewers rated all studies independently and disagreements were resolved through discussion. Sixteen programs were identified. Few programs have been evaluated for their effectiveness in reducing suicide attempts. Most studies evaluated the programs' abilities to improve students' and school staffs' knowledge and attitudes toward suicide. Signs of Suicide and the Good Behavior Game were the only programs found to reduce suicide attempts. Several other programs were found to reduce suicidal ideation, improve general life skills, and change gatekeeper behaviors. There are few evidence-based, school-based suicide prevention programs, a combination of which may be effective. It would be useful to evaluate the effectiveness of general mental health promotion programs on the outcome of suicide. The grades assigned in this review are reflective of the available literature, demonstrating a lack of randomized controlled trials. Further evaluation of programs examining suicidal behavior outcomes in randomized controlled trials is warranted. © 2013 Wiley Periodicals, Inc.

  16. Constraint-based verification of imperative programs

    OpenAIRE

    Beyene, Tewodros Awgichew

    2011-01-01

    work presented in the context of the European Master’s program in Computational Logic, as the partial requirement for obtaining Master of Science degree in Computational Logic The continuous reduction in the cost of computing ever since the first days of computers has resulted in the ubiquity of computing systems today; there is no any sphere of life in the daily routine of human beings that is not directly or indirectly influenced by computer systems anymore. But this high reliance ...

  17. Evolutionary Multiplayer Games

    OpenAIRE

    Gokhale, Chaitanya S.; Traulsen, Arne

    2014-01-01

    Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g.\\ increase less than linear wi...

  18. Schroedinger operators and evolutionary strategies

    International Nuclear Information System (INIS)

    Asselmeyer, T.

    1997-01-01

    First we introduce a simple model for the description of evolutionary algorithms, which is based on 2nd order partial differential equations for the distribution function of the individuals. Then we turn to the properties of Boltzmann's and Darwin's strategy. the next chapter is dedicated to the mathematical properties of Schroedinger operators. Both statements on the spectral density and their reproducibility during the simulation are summarized. The remaining of this chapter are dedicated to the analysis of the kernel as well as the dependence of the Schroedinger operator on the potential. As conclusion from the results of this chapter we obtain the classification of the strategies in dependence of the fitness. We obtain the classification of the evolutionary strategies, which are described by a 2nd order partial differential equation, in relation to their solution behaviour. Thereafter we are employed with the variation of the mutation distribution

  19. Preventive evolutionary medicine of cancers.

    Science.gov (United States)

    Hochberg, Michael E; Thomas, Frédéric; Assenat, Eric; Hibner, Urszula

    2013-01-01

    Evolutionary theory predicts that once an individual reaches an age of sufficiently low Darwinian fitness, (s)he will have reduced chances of keeping cancerous lesions in check. While we clearly need to better understand the emergence of precursor states and early malignancies as well as their mitigation by the microenvironment and tissue architecture, we argue that lifestyle changes and preventive therapies based in an evolutionary framework, applied to identified high-risk populations before incipient neoplasms become clinically detectable and chemoresistant lineages emerge, are currently the most reliable way to control or eliminate early tumours. Specifically, the relatively low levels of (epi)genetic heterogeneity characteristic of many if not most incipient lesions will mean a relatively limited set of possible adaptive traits and associated costs compared to more advanced cancers, and thus a more complete and predictable understanding of treatment options and outcomes. We propose a conceptual model for preventive treatments and discuss the many associated challenges.

  20. Incorporating Development Into Evolutionary Psychology

    Directory of Open Access Journals (Sweden)

    David F. Bjorklund

    2016-09-01

    Full Text Available Developmental thinking is gradually becoming integrated within mainstream evolutionary psychology. This is most apparent with respect to the role of parenting, with proponents of life history theory arguing that cognitive and behavioral plasticity early in life permits children to select different life history strategies, with such strategies being adaptive solutions to different fitness trade-offs. I argue that adaptations develop and are based on the highly plastic nature of infants’ and children’s behavior/cognition/brains. The concept of evolved probabilistic cognitive mechanisms is introduced, defined as information processing mechanisms evolved to solve recurrent problems faced by ancestral populations that are expressed in a probabilistic fashion in each individual in a generation and are based on the continuous and bidirectional interaction over time at all levels of organization, from the genetic through the cultural. Early perceptual/cognitive biases result in behavior that, when occurring in a species-typical environment, produce continuous adaptive changes in behavior (and cognition, yielding adaptive outcomes. Examples from social learning and tool use are provided, illustrating the development of adaptations via evolved probabilistic cognitive mechanisms. The integration of developmental concepts into mainstream evolutionary psychology (and evolutionary concepts into mainstream developmental psychology will provide a clearer picture of what it means to be human.

  1. Evolutionary Game Theory Analysis of Tumor Progression

    Science.gov (United States)

    Wu, Amy; Liao, David; Sturm, James; Austin, Robert

    2014-03-01

    Evolutionary game theory applied to two interacting cell populations can yield quantitative prediction of the future densities of the two cell populations based on the initial interaction terms. We will discuss how in a complex ecology that evolutionary game theory successfully predicts the future densities of strains of stromal and cancer cells (multiple myeloma), and discuss the possible clinical use of such analysis for predicting cancer progression. Supported by the National Science Foundation and the National Cancer Institute.

  2. Assessment of military population-based psychological resilience programs.

    Science.gov (United States)

    Morgan, Brenda J; Bibb, Sandra C Garmon

    2011-09-01

    Active duty service members' (ADSMs) seemingly poor adaptability to traumatic stressors is a risk to force health. Enhancing the psychological resilience of ADSMs has become a key focus of Department of Defense (DoD) leaders and the numbers of military programs for enhancing psychological resilience have increased. The purpose of this article is to describe the results of an assessment conducted to determine comprehensiveness of current psychological resilience building programs that target ADSMs. A modified six-step, population-based needs assessment was used to evaluate resilience programs designed to meet the psychological needs of the ADSM population. The assessment results revealed a gap in published literature regarding program outcomes. DoD leaders may benefit from targeted predictive research that assesses program effectiveness outcomes. The necessity of including preventive, evidence-based interventions in new programs, such as positive emotion interventions shown to enhance psychological resilience in civilian samples, is also recommended.

  3. Evolutionary algorithm based optimization of hydraulic machines utilizing a state-of-the-art block coupled CFD solver and parametric geometry and mesh generation tools

    Science.gov (United States)

    S, Kyriacou; E, Kontoleontos; S, Weissenberger; L, Mangani; E, Casartelli; I, Skouteropoulou; M, Gattringer; A, Gehrer; M, Buchmayr

    2014-03-01

    An efficient hydraulic optimization procedure, suitable for industrial use, requires an advanced optimization tool (EASY software), a fast solver (block coupled CFD) and a flexible geometry generation tool. EASY optimization software is a PCA-driven metamodel-assisted Evolutionary Algorithm (MAEA (PCA)) that can be used in both single- (SOO) and multiobjective optimization (MOO) problems. In MAEAs, low cost surrogate evaluation models are used to screen out non-promising individuals during the evolution and exclude them from the expensive, problem specific evaluation, here the solution of Navier-Stokes equations. For additional reduction of the optimization CPU cost, the PCA technique is used to identify dependences among the design variables and to exploit them in order to efficiently drive the application of the evolution operators. To further enhance the hydraulic optimization procedure, a very robust and fast Navier-Stokes solver has been developed. This incompressible CFD solver employs a pressure-based block-coupled approach, solving the governing equations simultaneously. This method, apart from being robust and fast, also provides a big gain in terms of computational cost. In order to optimize the geometry of hydraulic machines, an automatic geometry and mesh generation tool is necessary. The geometry generation tool used in this work is entirely based on b-spline curves and surfaces. In what follows, the components of the tool chain are outlined in some detail and the optimization results of hydraulic machine components are shown in order to demonstrate the performance of the presented optimization procedure.

  4. Evolutionary algorithm based optimization of hydraulic machines utilizing a state-of-the-art block coupled CFD solver and parametric geometry and mesh generation tools

    International Nuclear Information System (INIS)

    Kyriacou S; Kontoleontos E; Weissenberger S; Mangani L; Casartelli E; Skouteropoulou I; Gattringer M; Gehrer A; Buchmayr M

    2014-01-01

    An efficient hydraulic optimization procedure, suitable for industrial use, requires an advanced optimization tool (EASY software), a fast solver (block coupled CFD) and a flexible geometry generation tool. EASY optimization software is a PCA-driven metamodel-assisted Evolutionary Algorithm (MAEA (PCA)) that can be used in both single- (SOO) and multiobjective optimization (MOO) problems. In MAEAs, low cost surrogate evaluation models are used to screen out non-promising individuals during the evolution and exclude them from the expensive, problem specific evaluation, here the solution of Navier-Stokes equations. For additional reduction of the optimization CPU cost, the PCA technique is used to identify dependences among the design variables and to exploit them in order to efficiently drive the application of the evolution operators. To further enhance the hydraulic optimization procedure, a very robust and fast Navier-Stokes solver has been developed. This incompressible CFD solver employs a pressure-based block-coupled approach, solving the governing equations simultaneously. This method, apart from being robust and fast, also provides a big gain in terms of computational cost. In order to optimize the geometry of hydraulic machines, an automatic geometry and mesh generation tool is necessary. The geometry generation tool used in this work is entirely based on b-spline curves and surfaces. In what follows, the components of the tool chain are outlined in some detail and the optimization results of hydraulic machine components are shown in order to demonstrate the performance of the presented optimization procedure

  5. Controller design approach based on linear programming.

    Science.gov (United States)

    Tanaka, Ryo; Shibasaki, Hiroki; Ogawa, Hiromitsu; Murakami, Takahiro; Ishida, Yoshihisa

    2013-11-01

    This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor. © 2013 ISA. Published by ISA. All rights reserved.

  6. A model surveillance program based on regulatory experience

    International Nuclear Information System (INIS)

    Conte, R.J.

    1980-01-01

    A model surveillance program is presented based on regulatory experience. The program consists of three phases: Program Delineation, Data Acquistion and Data Analysis. Each phase is described in terms of key quality assurance elements and some current philosophies is the United States Licensing Program. Other topics include the application of these ideas to test equipment used in the surveillance progam and audits of the established program. Program Delineation discusses the establishment of administrative controls for organization and the description of responsibilities using the 'Program Coordinator' concept, with assistance from Data Acquisition and Analysis Teams. Ideas regarding frequency of surveillance testing are also presented. The Data Acquisition Phase discusses various methods for acquiring data including operator observations, test procedures, operator logs, and computer output, for trending equipment performance. The Data Analysis Phase discusses the process for drawing conclusions regarding component/equipment service life, proper application, and generic problems through the use of trend analysis and failure rate data. (orig.)

  7. Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences

    Science.gov (United States)

    Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence d...

  8. Modeling the milling tool wear by using an evolutionary SVM-based model from milling runs experimental data

    Science.gov (United States)

    Nieto, Paulino José García; García-Gonzalo, Esperanza; Vilán, José Antonio Vilán; Robleda, Abraham Segade

    2015-12-01

    The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on Particle Swarm Optimization (PSO) in combination with support vector machines (SVMs). This optimization mechanism involved kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, a PSO-SVM-based model, which is based on the statistical learning theory, was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. To accomplish the objective of this study, the experimental dataset represents experiments from runs on a milling machine under various operating conditions. In this way, data sampled by three different types of sensors (acoustic emission sensor, vibration sensor and current sensor) were acquired at several positions. A second aim is to determine the factors with the greatest bearing on the milling tool flank wear with a view to proposing milling machine's improvements. Firstly, this hybrid PSO-SVM-based regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the flank wear (output variable) and input variables (time, depth of cut, feed, etc.). Indeed, regression with optimal hyperparameters was performed and a determination coefficient of 0.95 was obtained. The agreement of this model with experimental data confirmed its good performance. Secondly, the main advantages of this PSO-SVM-based model are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, the main conclusions of this study are exposed.

  9. The International Coal Statistics Data Base program maintenance guide

    International Nuclear Information System (INIS)

    1991-06-01

    The International Coal Statistics Data Base (ICSD) is a microcomputer-based system which contains information related to international coal trade. This includes coal production, consumption, imports and exports information. The ICSD is a secondary data base, meaning that information contained therein is derived entirely from other primary sources. It uses dBase III+ and Lotus 1-2-3 to locate, report and display data. The system is used for analysis in preparing the Annual Prospects for World Coal Trade (DOE/EIA-0363) publication. The ICSD system is menu driven and also permits the user who is familiar with dBase and Lotus operations to leave the menu structure to perform independent queries. Documentation for the ICSD consists of three manuals -- the User's Guide, the Operations Manual, and the Program Maintenance Manual. This Program Maintenance Manual provides the information necessary to maintain and update the ICSD system. Two major types of program maintenance documentation are presented in this manual. The first is the source code for the dBase III+ routines and related non-dBase programs used in operating the ICSD. The second is listings of the major component database field structures. A third important consideration for dBase programming, the structure of index files, is presented in the listing of source code for the index maintenance program. 1 fig

  10. Risk-based Regulatory Evaluation Program methodology

    International Nuclear Information System (INIS)

    DuCharme, A.R.; Sanders, G.A.; Carlson, D.D.; Asselin, S.V.

    1987-01-01

    The objectives of this DOE-supported Regulatory Evaluation Progrwam are to analyze and evaluate the safety importance and economic significance of existing regulatory guidance in order to assist in the improvement of the regulatory process for current generation and future design reactors. A risk-based cost-benefit methodology was developed to evaluate the safety benefit and cost of specific regulations or Standard Review Plan sections. Risk-based methods can be used in lieu of or in combination with deterministic methods in developing regulatory requirements and reaching regulatory decisions

  11. Web-Based Programs Assess Cognitive Fitness

    Science.gov (United States)

    2009-01-01

    The National Space Biomedical Research Institute, based in Houston and funded by NASA, began funding research for Harvard University researchers to design Palm software to help astronauts monitor and assess their cognitive functioning. The MiniCog Rapid Assessment Battery (MRAB) was licensed by the Criteria Corporation in Los Angeles and adapted for Web-based employment testing. The test battery assesses nine different cognitive functions and can gauge the effect of stress-related deficits, such as fatigue, on various tasks. The MRAB can be used not only for pre-employment testing but also for repeat administrations to measure day-to-day job readiness in professions where alertness is critical.

  12. Analysis of School Food Safety Programs Based on HACCP Principles

    Science.gov (United States)

    Roberts, Kevin R.; Sauer, Kevin; Sneed, Jeannie; Kwon, Junehee; Olds, David; Cole, Kerri; Shanklin, Carol

    2014-01-01

    Purpose/Objectives: The purpose of this study was to determine how school districts have implemented food safety programs based on HACCP principles. Specific objectives included: (1) Evaluate how schools are implementing components of food safety programs; and (2) Determine foodservice employees food-handling practices related to food safety.…

  13. Permission-Based Separation Logic for Multithreaded Java Programs

    NARCIS (Netherlands)

    Haack, Christian; Huisman, Marieke; Hurlin, C.

    2011-01-01

    This paper motivates and presents a program logic for reasoning about multithreaded Java-like programs with concurrency primitives such as dynamic thread creation, thread joining and reentrant object monitors. The logic is based on concurrent separation logic. It is the first detailed adaptation of

  14. Connect: An Effective Community-Based Youth Suicide Prevention Program

    Science.gov (United States)

    Bean, Gretchen; Baber, Kristine M.

    2011-01-01

    Youth suicide prevention is an important public health issue. However, few prevention programs are theory driven or systematically evaluated. This study evaluated Connect, a community-based youth suicide prevention program. Analysis of pre and posttraining questionnaires from 648 adults and 204 high school students revealed significant changes in…

  15. Friendship Experiences of Participants in a University Based Transition Program

    Science.gov (United States)

    Nasr, Maya; Cranston-Gingras, Ann; Jang, Seung-Eun

    2015-01-01

    This study examined the nature of friendships of 14 students with intellectual and developmental disabilities participating in a university-based transition program in the United States. The transition program is a bridge between high school and adulthood, designed to foster students' self-esteem and self-confidence by providing them with training…

  16. Towards Separation of Concerns in Flow-Based Programming

    DEFF Research Database (Denmark)

    Zarrin, Bahram; Baumeister, Hubert

    2015-01-01

    Flow-Based Programming (FBP) is a programming paradigm that models software systems as a directed graph of predefined processes which run asynchronously and exchange data through input and output ports. FBP decomposes software systems into a network of processes. However there are concerns...

  17. A Program Based on Maslow's Hierarchy Helps Students in Trouble

    Science.gov (United States)

    Yates, Mary Ruth; Saunders, Ron; Watkins, J. Foster

    1980-01-01

    The article discusses the development of an "alternative school" in an urban school system for students having trouble in the regular secondary setting. The program was based upon "Maslow's Hierarchy of Needs" and is described in detail. The initial assessment of the program produced very positive results.

  18. Evolutionary Robotics: What, Why, and Where to

    Directory of Open Access Journals (Sweden)

    Stephane eDoncieux

    2015-03-01

    Full Text Available Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the whole robot at once, and enables the exploitation of robot features in a holistic manner. Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. The use of robots as a substrate can help address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. In this paper we consider the main achievements of evolutionary robotics, focusing particularly on its contributions to both engineering and biology. We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work.

  19. Mean-Potential Law in Evolutionary Games

    Science.gov (United States)

    Nałecz-Jawecki, Paweł; Miekisz, Jacek

    2018-01-01

    The Letter presents a novel way to connect random walks, stochastic differential equations, and evolutionary game theory. We introduce a new concept of a potential function for discrete-space stochastic systems. It is based on a correspondence between one-dimensional stochastic differential equations and random walks, which may be exact not only in the continuous limit but also in finite-state spaces. Our method is useful for computation of fixation probabilities in discrete stochastic dynamical systems with two absorbing states. We apply it to evolutionary games, formulating two simple and intuitive criteria for evolutionary stability of pure Nash equilibria in finite populations. In particular, we show that the 1 /3 law of evolutionary games, introduced by Nowak et al. [Nature, 2004], follows from a more general mean-potential law.

  20. A hybrid evolutionary algorithm for multi-objective anatomy-based dose optimization in high-dose-rate brachytherapy

    International Nuclear Information System (INIS)

    Lahanas, M; Baltas, D; Zamboglou, N

    2003-01-01

    Multiple objectives must be considered in anatomy-based dose optimization for high-dose-rate brachytherapy and a large number of parameters must be optimized to satisfy often competing objectives. For objectives expressed solely in terms of dose variances, deterministic gradient-based algorithms can be applied and a weighted sum approach is able to produce a representative set of non-dominated solutions. As the number of objectives increases, or non-convex objectives are used, local minima can be present and deterministic or stochastic algorithms such as simulated annealing either cannot be used or are not efficient. In this case we employ a modified hybrid version of the multi-objective optimization algorithm NSGA-II. This, in combination with the deterministic optimization algorithm, produces a representative sample of the Pareto set. This algorithm can be used with any kind of objectives, including non-convex, and does not require artificial importance factors. A representation of the trade-off surface can be obtained with more than 1000 non-dominated solutions in 2-5 min. An analysis of the solutions provides information on the possibilities available using these objectives. Simple decision making tools allow the selection of a solution that provides a best fit for the clinical goals. We show an example with a prostate implant and compare results obtained by variance and dose-volume histogram (DVH) based objectives

  1. Testing evolutionary convergence on Europa

    Energy Technology Data Exchange (ETDEWEB)

    Chela-Flores, Julian [Instituto de Estudios Avanzados, Caracas (Venezuela); [Abdus Salam International Centre for Theoretical Physics, Trieste (Italy)

    2002-11-01

    A major objective in solar system exploration is the insertion of appropriate biology-oriented experiments in future missions. We discuss various reasons for suggesting that this type of research be considered a high priority for feasibility studies and, subsequently, for technological development of appropriate melters and submersibles. Based on numerous examples, we argue in favour of the assumption that Darwin's theory is valid for the evolution of life anywhere in the universe. We have suggested how to obtain preliminary insights into the question of the distribution of life in the universe. Universal evolution of intelligent behaviour is at the end of an evolutionary pathway, in which evolution of ion channels in the membrane of microorganisms occurs in its early stages. Further, we have argued that a preliminary test of this conjecture is feasible with experiments on the Europan surface or ocean, involving evolutionary biosignatures (ion channels). This aspect of the exploration for life in the solar system should be viewed as a complement to the astronomical approach for the search of evidence of the later stages of the evolutionary pathways towards intelligent behaviour. (author)

  2. Building 4-H Program Capacity and Sustainability through Collaborative Fee-Based Programs

    Science.gov (United States)

    Pellien, Tamara

    2016-01-01

    Shrinking budgets and increased demands for services and programs are the norm for today's Extension professional. The tasks of procuring grants, developing fund raisers, and pursuing donors require a large investment of time and can lead to mission drift in the pursuit of funding. Implementing a collaborative fee-based program initiative can fund…

  3. 76 FR 2453 - Medicare Program; Hospital Inpatient Value-Based Purchasing Program

    Science.gov (United States)

    2011-01-13

    ... program based on conditions for coverage. This new program will necessarily be a fluid model, subject to... rewarding better value, outcomes, and innovations instead of merely volume. Use of Measures: Public....hospitalcompare.hhs.gov , after a 30-day preview period. An interactive Web tool, this Web site assists...

  4. Evolutionary patterns at the RNase based gametophytic self - incompatibility system in two divergent Rosaceae groups (Maloideae and Prunus).

    Science.gov (United States)

    Vieira, Jorge; Ferreira, Pedro G; Aguiar, Bruno; Fonseca, Nuno A; Vieira, Cristina P

    2010-06-28

    Within Rosaceae, the RNase based gametophytic self-incompatibility (GSI) system has been studied at the molecular level in Maloideae and Prunus species that have been diverging for, at least, 32 million years. In order to understand RNase based GSI evolution within this family, comparative studies must be performed, using similar methodologies. It is here shown that many features are shared between the two species groups such as levels of recombination at the S-RNase (the S-pistil component) gene, and the rate at which new specificities arise. Nevertheless, important differences are found regarding the number of ancestral lineages and the degree of specificity sharing between closely related species. In Maloideae, about 17% of the amino acid positions at the S-RNase protein are found to be positively selected, and they occupy about 30% of the exposed protein surface. Positively selected amino acid sites are shown to be located on either side of the active site cleft, an observation that is compatible with current models of specificity determination. At positively selected amino acid sites, non-conservative changes are almost as frequent as conservative changes. There is no evidence that at these sites the most drastic amino acid changes may be more strongly selected. Many similarities are found between the GSI system of Prunus and Maloideae that are compatible with the single origin hypothesis for RNase based GSI. The presence of common features such as the location of positively selected amino acid sites and lysine residues that may be important for ubiquitylation, raise a number of issues that, in principle, can be experimentally addressed in Maloideae. Nevertheless, there are also many important differences between the two Rosaceae GSI systems. How such features changed during evolution remains a puzzling issue.

  5. Evolutionary patterns at the RNase based gametophytic self - incompatibility system in two divergent Rosaceae groups (Maloideae and Prunus

    Directory of Open Access Journals (Sweden)

    Fonseca Nuno A

    2010-06-01

    Full Text Available Abstract Background Within Rosaceae, the RNase based gametophytic self-incompatibility (GSI system has been studied at the molecular level in Maloideae and Prunus species that have been diverging for, at least, 32 million years. In order to understand RNase based GSI evolution within this family, comparative studies must be performed, using similar methodologies. Result It is here shown that many features are shared between the two species groups such as levels of recombination at the S-RNase (the S-pistil component gene, and the rate at which new specificities arise. Nevertheless, important differences are found regarding the number of ancestral lineages and the degree of specificity sharing between closely related species. In Maloideae, about 17% of the amino acid positions at the S-RNase protein are found to be positively selected, and they occupy about 30% of the exposed protein surface. Positively selected amino acid sites are shown to be located on either side of the active site cleft, an observation that is compatible with current models of specificity determination. At positively selected amino acid sites, non-conservative changes are almost as frequent as conservative changes. There is no evidence that at these sites the most drastic amino acid changes may be more strongly selected. Conclusions Many similarities are found between the GSI system of Prunus and Maloideae that are compatible with the single origin hypothesis for RNase based GSI. The presence of common features such as the location of positively selected amino acid sites and lysine residues that may be important for ubiquitylation, raise a number of issues that, in principle, can be experimentally addressed in Maloideae. Nevertheless, there are also many important differences between the two Rosaceae GSI systems. How such features changed during evolution remains a puzzling issue.

  6. 78 FR 42788 - School-Based Health Center Program

    Science.gov (United States)

    2013-07-17

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Health Resources and Services Administration School-Based... Gadsden County. SUMMARY: HRSA will be transferring a School-Based Health Center Capital (SBHCC) Program... support the expansion of services at school-based health centers will continue. SUPPLEMENTARY INFORMATION...

  7. Introduction of the SAT based training programs at Paks NPP

    International Nuclear Information System (INIS)

    Kiss, I.

    1998-01-01

    An introduction of the SAT based training programs at Paks nuclear power plant is described in detail, including framework of project operation; project implementation; process of SAT applied at Paks NPP and the needs of its introduction

  8. Evolutionary history of the endangered fish Zoogoneticus quitzeoensis (Bean, 1898) (Cyprinodontiformes: Goodeidae) using a sequential approach to phylogeography based on mitochondrial and nuclear DNA data

    Science.gov (United States)

    2008-01-01

    Background Tectonic, volcanic and climatic events that produce changes in hydrographic systems are the main causes of diversification and speciation of freshwater fishes. Elucidate the evolutionary history of freshwater fishes permits to infer theories on the biotic and geological evolution of a region, which can further be applied to understand processes of population divergence, speciation and for conservation purposes. The freshwater ecosystems in Central Mexico are characterized by their genesis dynamism, destruction, and compartmentalization induced by intense geologic activity and climatic changes since the early Miocene. The endangered goodeid Zoogoneticus quitzeoensis is widely distributed across Central México, thus making it a good model for phylogeographic analyses in this area. Results We addressed the phylogeography, evolutionary history and genetic structure of populations of Z. quitzeoensis through a sequential approach, based on both microsatellite and mitochondrial cytochrome b sequences. Most haplotypes were private to particular locations. All the populations analysed showed a remarkable number of haplotypes. The level of gene diversity within populations was H¯d = 0.987 (0.714 – 1.00). However, in general the nucleotide diversity was low, π = 0.0173 (0.0015 – 0.0049). Significant genetic structure was found among populations at the mitochondrial and nuclear level (ΦST = 0.836 and FST = 0.262, respectively). We distinguished two well-defined mitochondrial lineages that were separated ca. 3.3 million years ago (Mya). The time since expansion was ca. 1.5 × 106 years ago for Lineage I and ca. 860,000 years ago for Lineage II. Also, genetic patterns of differentiation, between and within lineages, are described at different historical timescales. Conclusion Our mtDNA data indicates that the evolution of the different genetic groups is more related to ancient geological and climatic events (Middle Pliocene, ca. 3.3 Mya) than to the current

  9. Archaeogenetics in evolutionary medicine.

    Science.gov (United States)

    Bouwman, Abigail; Rühli, Frank

    2016-09-01

    Archaeogenetics is the study of exploration of ancient DNA (aDNA) of more than 70 years old. It is an important part of the wider studies of many different areas of our past, including animal, plant and pathogen evolution and domestication events. Hereby, we address specifically the impact of research in archaeogenetics in the broader field of evolutionary medicine. Studies on ancient hominid genomes help to understand even modern health patterns. Human genetic microevolution, e.g. related to abilities of post-weaning milk consumption, and specifically genetic adaptation in disease susceptibility, e.g. towards malaria and other infectious diseases, are of the upmost importance in contributions of archeogenetics on the evolutionary understanding of human health and disease. With the increase in both the understanding of modern medical genetics and the ability to deep sequence ancient genetic information, the field of archaeogenetic evolutionary medicine is blossoming.

  10. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  11. An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

    Science.gov (United States)

    Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

    2017-12-07

    Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

  12. Towards an agent-oriented programming language based on Scala

    Science.gov (United States)

    Mitrović, Dejan; Ivanović, Mirjana; Budimac, Zoran

    2012-09-01

    Scala and its multi-threaded model based on actors represent an excellent framework for developing purely reactive agents. This paper presents an early research on extending Scala with declarative programming constructs, which would result in a new agent-oriented programming language suitable for developing more advanced, BDI agent architectures. The main advantage the new language over many other existing solutions for programming BDI agents is a natural and straightforward integration of imperative and declarative programming constructs, fitted under a single development framework.

  13. Criteria to evaluate SAT-based training programs

    International Nuclear Information System (INIS)

    Arjona, O.; Venegas, M.; Rodriguez, L.; Lopez, M.

    1997-01-01

    This paper present some coefficients of error obtained to evaluate the quality of the design development and implementation of SAT-based personnel training programs. With the attainment of these coefficients, with the use of the GESAT system, is facilitated the continuos evaluation of training programs and the main deficiencies in the design, development and implementation of training programs are obtained, through the comparison between the program features and their standards or wanted features and doing an statistics analysis of the data kept in the GESAT system

  14. A recovery-based outreach program in rural Victoria.

    Science.gov (United States)

    Prabhu, Radha; Browne, Mark Oakley

    2007-04-01

    A recovery-based outreach program for people with severe mental illness in regional Victoria is described. The paper covers a description of the program, the services provided and outcomes achieved. The program emphasized active collaboration between patients and clinicians as outlined in the collaborative recovery model and recognized that recovery from mental illness is an individual, personal process. The program provided service to 108 people over 3 years and had a positive impact on clinicians, patients and carers. The benefits of recovery orientation, multidisciplinary teams, collaborative relationships and carer involvement are discussed. The paper highlights the need for a focus on recovery and comprehensive care for people with severe mental illness.

  15. Evolutionary conceptual analysis: faith community nursing.

    Science.gov (United States)

    Ziebarth, Deborah

    2014-12-01

    The aim of the study was to report an evolutionary concept analysis of faith community nursing (FCN). FCN is a source of healthcare delivery in the USA which has grown in comprehensiveness and complexity. With increasing healthcare cost and a focus on access and prevention, FCN has extended beyond the physical walls of the faith community building. Faith communities and healthcare organizations invest in FCN and standardized training programs exist. Using Rodgers' evolutionary analysis, the literature was examined for antecedents, attributes, and consequences of the concept. This design allows for understanding the historical and social nature of the concept and how it changes over time. A search of databases using the keywords FCN, faith community nurse, parish nursing, and parish nurse was done. The concept of FCN was explored using research and theoretical literature. A theoretical definition and model were developed with relevant implications. The search results netted a sample of 124 reports of research and theoretical articles from multiple disciplines: medicine, education, religion and philosophy, international health, and nursing. Theoretical definition: FCN is a method of healthcare delivery that is centered in a relationship between the nurse and client (client as person, family, group, or community). The relationship occurs in an iterative motion over time when the client seeks or is targeted for wholistic health care with the goal of optimal wholistic health functioning. Faith integrating is a continuous occurring attribute. Health promoting, disease managing, coordinating, empowering and accessing health care are other essential attributes. All essential attributes occur with intentionality in a faith community, home, health institution and other community settings with fluidity as part of a community, national, or global health initiative. A new theoretical definition and corresponding conceptual model of FCN provides a basis for future nursing

  16. A Trust-region-based Sequential Quadratic Programming Algorithm

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints.......This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints....

  17. LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

    OpenAIRE

    Rustan, Edhy

    2017-01-01

    The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

  18. New Comparative Analysis Based on the Secondary Structure of SSU-rRNA Gene Reveals the Evolutionary Trend and the Family-Genus Characters of Mobilida (Ciliophora, Peritrichia).

    Science.gov (United States)

    Zhang, Yong; Zhao, Yuan-Jun; Wang, Qin; Tang, Fa-Hui

    2015-08-01

    In order to reveal the structural evolutionary trend of Mobilida ciliates, twenty-six SSU-rRNA sequences of mobilid species, including seven ones newly sequenced in the present work, were used for comparative phylogenic analysis based on the RNA secondary structure. The research results indicate that all the secondary structures except domains Helix 10, Helix 12, and Helix 37 could be regarded as the criterions in classification between the family Trichodinidae and Urceolariida, and four regions including Helix E10-1, Helix 29, Helix 43, and Helix 45-Helix 46 could be as criterions in classification between the genus Trichodinella and Trichodina in family Trichodinidae. After the analysis of common structural feature within the Mobilida, it was found that the secondary structure of V6 could prove the family Urceolariidae primitive status. This research has further suggested that the genus Trichodina could be divergent earlier than Trichodinella in the family Trichodinidae. In addition, the relationship between the secondary structure and topology of phylogenic tree that the branching order of most clades corresponds with the secondary structure of species within each clade of phylogenetic tree was first uncovered and discussed in the present study.

  19. Complete genome sequence of a Chinese isolate of pepper vein yellows virus and evolutionary analysis based on the CP, MP and RdRp coding regions.

    Science.gov (United States)

    Liu, Maoyan; Liu, Xiangning; Li, Xun; Zhang, Deyong; Dai, Liangyin; Tang, Qianjun

    2016-03-01

    The genome sequence of pepper vein yellows virus (PeVYV) (PeVYV-HN, accession number KP326573), isolated from pepper plants (Capsicum annuum L.) grown at the Hunan Vegetables Institute (Changsha, Hunan, China), was determined by deep sequencing of small RNAs. The PeVYV-HN genome consists of 6244 nucleotides, contains six open reading frames (ORFs), and is similar to that of an isolate (AB594828) from Japan. Its genomic organization is similar to that of members of the genus Polerovirus. Sequence analysis revealed that PeVYV-HN shared 92% sequence identity with the Japanese PeVYV genome at both the nucleotide and amino acid levels. Evolutionary analysis based on the coat protein (CP), movement protein (MP), and RNA-dependent RNA polymerase (RdRP) showed that PeVYV could be divided into two major lineages corresponding to their geographical origins. The Asian isolates have a higher population expansion frequency than the African isolates. Negative selection and genetic drift (founder effect) were found to be the potential drivers of the molecular evolution of PeVYV. Moreover, recombination was not the distinct cause of PeVYV evolution. This is the first report of a complete genomic sequence of PeVYV in China.

  20. The island model for parallel implementation of evolutionary algorithm of Population-Based Incremental Learning (PBIL) optimization

    International Nuclear Information System (INIS)

    Lima, Alan M.M. de; Schirru, Roberto

    2000-01-01

    Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. The purpose of this work is to introduce a new parallelization method to be applied to the Population-Based Incremental Learning (PBIL) algorithm. PBIL combines standard genetic algorithm mechanisms with simple competitive learning and has ben successfully used in combinatorial optimization problems. The development of this algorithm aims its application to the reload optimization of PWR nuclear reactors. Tests have been performed with combinatorial optimization problems similar to the reload problem. Results are compared to the serial PBIL ones, showing the new method's superiority and its viability as a tool for the nuclear core reload problem solution. (author)

  1. A mission-based gifted and talented program

    Directory of Open Access Journals (Sweden)

    Yazdani Sh

    2004-07-01

    Full Text Available Background: Only in recent years has the concept of "Multiple intelligences" been acknowledged. Purpose: To develop a mission-based program to train gifted medical students on skills and sciences needed for sustainable development Methods: A two-armed program was developed for training medical students. The first arm of the program train students for management purposes. The second branch of the program educates medical students to enable them to contribute to scholar development in areas of health and medicine. Results: The Managerial pathway has been implemented since July 2003. More than 400 students from Shaheed Beheshti and elsewhere registered in the program as main members or guest members of the program. The level up exam was given on February 2004 with 13 students qualifying for C level. Conclusion: It may be to early to draw any conclusion in terms of fulfilment of the outcomes of the program but the dedication of the members to the program has been beyond imagination. Keywords: MISSION-BASED, PROGRAM, GIFTED, TALENTED STUDENTS, GIFTEDNESS IDENTIFICATION

  2. Designing an Elderly Assistance Program Based-on Home Care

    Science.gov (United States)

    Umusya'adah, L.; Juwaedah, A.; Jubaedah, Y.; Ratnasusanti, H.; Puspita, R. H.

    2018-02-01

    PKH (Program Keluarga Harapan) is a program of Indonesia’s Government through the ministry of social directorate to accelerate the poverty reduction and the achievement of Millennium Development Goals (MDGs) target as well as the policies development in social protection and social welfare domain or commonly referred to as Indonesian Conditional Cash Transfer (CCT) Program. This research is motivated that existing participants of the family expectation program (PKH) that already exist in Sumedang, Indoensia, especially in the South Sumedang on the social welfare components is only limited to the health checking, while for assisting the elderly based Home Care program there has been no structured and systematic, where as the elderly still need assistance, especially from the family and community environment. This study uses a method of Research and Development with Model Addie which include analysis, design, development, implementation and evaluation. Participants in this study using purposive sampling, where selected families of PKH who provide active assistance to the elderly with 82 participants. The program is designed consists of program components: objectives, goals, forms of assistance, organizing institutions and implementing the program, besides, program modules include assisting the elderly. Form of assistance the elderly cover physical, social, mental and spiritual. Recommended for families and companions PKH, the program can be implemented to meet the various needs of the elderly. For the elderly should introspect, especially in the health and follow the advice recommended by related parties

  3. Exergy, exergoeconomic and environmental analyses and evolutionary algorithm based multi-objective optimization of combined cycle power plants

    International Nuclear Information System (INIS)

    Ahmadi, Pouria; Dincer, Ibrahim; Rosen, Marc A.

    2011-01-01

    A comprehensive exergy, exergoeconomic and environmental impact analysis and optimization is reported of several combined cycle power plants (CCPPs). In the first part, thermodynamic analyses based on energy and exergy of the CCPPs are performed, and the effect of supplementary firing on the natural gas-fired CCPP is investigated. The latter step includes the effect of supplementary firing on the performance of bottoming cycle and CO 2 emissions, and utilizes the first and second laws of thermodynamics. In the second part, a multi-objective optimization is performed to determine the 'best' design parameters, accounting for exergetic, economic and environmental factors. The optimization considers three objective functions: CCPP exergy efficiency, total cost rate of the system products and CO 2 emissions of the overall plant. The environmental impact in terms of CO 2 emissions is integrated with the exergoeconomic objective function as a new objective function. The results of both exergy and exergoeconomic analyses show that the largest exergy destructions occur in the CCPP combustion chamber, and that increasing the gas turbine inlet temperature decreases the CCPP cost of exergy destruction. The optimization results demonstrates that CO 2 emissions are reduced by selecting the best components and using a low fuel injection rate into the combustion chamber. -- Highlights: → Comprehensive thermodynamic modeling of a combined cycle power plant. → Exergy, economic and environmental analyses of the system. → Investigation of the role of multiobjective exergoenvironmental optimization as a tool for more environmentally-benign design.

  4. EVOLUTIONARY FOUNDATIONS FOR MOLECULAR MEDICINE

    Science.gov (United States)

    Nesse, Randolph M.; Ganten, Detlev; Gregory, T. Ryan; Omenn, Gilbert S.

    2015-01-01

    Evolution has long provided a foundation for population genetics, but many major advances in evolutionary biology from the 20th century are only now being applied in molecular medicine. They include the distinction between proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are further transforming evolutionary biology and creating yet more opportunities for progress at the interface of evolution with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and others to speed the development of evolutionary molecular medicine. PMID:22544168

  5. GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.

    Directory of Open Access Journals (Sweden)

    Leonardo Bottolo

    Full Text Available Genome-wide association studies (GWAS yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s-trait(s associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS. Despite the relatively small size of GHS (n  =  3,175, when compared with the largest published meta-GWAS (n > 100,000, GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify

  6. Technical bases for the DWPF testing program

    International Nuclear Information System (INIS)

    Plodinec, M.J.

    1990-01-01

    The Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) will be the first production facility in the United States for the immobilization of high-level nuclear waste. Production of DWPF canistered wasteforms will begin prior to repository licensing, so decisions on facility startup will have to be made before the final decisions on repository design are made. The Department of Energy's Office of Civilian Radioactive Waste Management (RW) has addressed this discrepancy by defining a Waste Acceptance Process. This process provides assurance that the borosilicate-glass wasteform, in a stainless-steel canister, produced by the DWPF will be acceptable for permanent storage in a federal repository. As part of this process, detailed technical specifications have been developed for the DWPF product. SRS has developed detailed strategies for demonstrating compliance with each of the Waste Acceptance Process specifications. An important part of the compliance is the testing which will be carried out in the DWPF. In this paper, the bases for each of the tests to be performed in the DWPF to establish compliance with the specifications are described, and the tests are detailed. The results of initial tests relating to characterization of sealed canisters are reported

  7. Evolutionary trends in Heteroptera

    NARCIS (Netherlands)

    Cobben, R.H.

    1968-01-01

    1. This work, the first volume of a series dealing with evolutionary trends in Heteroptera, is concerned with the egg system of about 400 species. The data are presented systematically in chapters 1 and 2 with a critical review of the literature after each family.

    2. Chapter 3 evaluates facts

  8. Evolutionary mysteries in meiosis

    NARCIS (Netherlands)

    Lenormand, Thomas; Engelstädter, Jan; Johnston, Susan E.; Wijnker, Erik; Haag, Christoph R.

    2016-01-01

    Meiosis is a key event of sexual life cycles in eukaryotes. Its mechanistic details have been uncovered in several model organisms, and most of its essential features have received various and often contradictory evolutionary interpretations. In this perspective, we present an overview of these

  9. Applications of Evolutionary Computation

    NARCIS (Netherlands)

    Mora, Antonio M.; Squillero, Giovanni; Di Chio, C; Agapitos, Alexandros; Cagnoni, Stefano; Cotta, Carlos; Fernández De Vega, F; Di Caro, G A; Drechsler, R.; Ekárt, A; Esparcia-Alcázar, Anna I.; Farooq, M; Langdon, W B; Merelo-Guervós, J.J.; Preuss, M; Richter, O.-M.H.; Silva, Sara; Sim$\\$~oes, A; Squillero, Giovanni; Tarantino, Ernesto; Tettamanzi, Andrea G B; Togelius, J; Urquhart, Neil; Uyar, A S; Yannakakis, G N; Smith, Stephen L; Caserta, Marco; Ramirez, Adriana; Voß, Stefan; Squillero, Giovanni; Burelli, Paolo; Mora, Antonio M.; Squillero, Giovanni; Jan, Mathieu; Matthias, M; Di Chio, C; Agapitos, Alexandros; Cagnoni, Stefano; Cotta, Carlos; Fernández De Vega, F; Di Caro, G A; Drechsler, R.; Ekárt, A; Esparcia-Alcázar, Anna I.; Farooq, M; Langdon, W B; Merelo-Guervós, J.J.; Preuss, M; Richter, O.-M.H.; Silva, Sara; Sim$\\$~oes, A; Squillero, Giovanni; Tarantino, Ernesto; Tettamanzi, Andrea G B; Togelius, J; Urquhart, Neil; Uyar, A S; Yannakakis, G N; Caserta, Marco; Ramirez, Adriana; Voß, Stefan; Squillero, Giovanni; Burelli, Paolo; Esparcia-Alcazar, Anna I; Silva, Sara; Agapitos, Alexandros; Cotta, Carlos; De Falco, Ivanoe; Cioppa, Antonio Della; Diwold, Konrad; Ekart, Aniko; Tarantino, Ernesto; Vega, Francisco Fernandez De; Burelli, Paolo; Sim, Kevin; Cagnoni, Stefano; Simoes, Anabela; Merelo, J.J.; Urquhart, Neil; Haasdijk, Evert; Zhang, Mengjie; Squillero, Giovanni; Eiben, A E; Tettamanzi, Andrea G B; Glette, Kyrre; Rohlfshagen, Philipp; Schaefer, Robert; Caserta, Marco; Ramirez, Adriana; Voß, Stefan

    2015-01-01

    The application of genetic and evolutionary computation to problems in medicine has increased rapidly over the past five years, but there are specific issues and challenges that distinguish it from other real-world applications. Obtaining reliable and coherent patient data, establishing the clinical

  10. Evolutionary perspectives on ageing.

    Science.gov (United States)

    Reichard, Martin

    2017-10-01

    From an evolutionary perspective, ageing is a decrease in fitness with chronological age - expressed by an increase in mortality risk and/or decline in reproductive success and mediated by deterioration of functional performance. While this makes ageing intuitively paradoxical - detrimental to individual fitness - evolutionary theory offers answers as to why ageing has evolved. In this review, I first briefly examine the classic evolutionary theories of ageing and their empirical tests, and highlight recent findings that have advanced our understanding of the evolution of ageing (condition-dependent survival, positive pleiotropy). I then provide an overview of recent theoretical extensions and modifications that accommodate those new discoveries. I discuss the role of indeterminate (asymptotic) growth for lifetime increases in fecundity and ageing trajectories. I outline alternative views that challenge a universal existence of senescence - namely the lack of a germ-soma distinction and the ability of tissue replacement and retrogression to younger developmental stages in modular organisms. I argue that rejuvenation at the organismal level is plausible, but includes a return to a simple developmental stage. This may exempt a particular genotype from somatic defects but, correspondingly, removes any information acquired during development. A resolution of the question of whether a rejuvenated individual is the same entity is central to the recognition of whether current evolutionary theories of ageing, with their extensions and modifications, can explain the patterns of ageing across the Tree of Life. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Editorial overview: Evolutionary psychology

    NARCIS (Netherlands)

    Gangestad, S.W.; Tybur, J.M.

    2016-01-01

    Functional approaches in psychology - which ask what behavior is good for - are almost as old as scientific psychology itself. Yet sophisticated, generative functional theories were not possible until developments in evolutionary biology in the mid-20th century. Arising in the last three decades,

  12. Biochemistry and evolutionary biology

    Indian Academy of Sciences (India)

    Biochemical information has been crucial for the development of evolutionary biology. On the one hand, the sequence information now appearing is producing a huge increase in the amount of data available for phylogenetic analysis; on the other hand, and perhaps more fundamentally, it allows understanding of the ...

  13. Evolutionary Biology Today

    Indian Academy of Sciences (India)

    Hindi and English. Port 1. Resonance, Vo1.7 ... they use. Of course, many evolutionary biologists do work with fossils or DNA, or both, but there are also large numbers of ... The first major division that I like to make is between studies focussed ...

  14. Learning: An Evolutionary Analysis

    Science.gov (United States)

    Swann, Joanna

    2009-01-01

    This paper draws on the philosophy of Karl Popper to present a descriptive evolutionary epistemology that offers philosophical solutions to the following related problems: "What happens when learning takes place?" and "What happens in human learning?" It provides a detailed analysis of how learning takes place without any direct transfer of…

  15. Complex systems, evolutionary planning?

    NARCIS (Netherlands)

    Bertolini, L.; de Roo, G.; Silva, E.A.

    2010-01-01

    Coping with uncertainty is a defining challenge for spatial planners. Accordingly, most spatial planning theories and methods are aimed at reducing uncertainty. However, the question is what should be done when this seems impossible? This chapter proposes an evolutionary interpretation of spatial

  16. Molluscan Evolutionary Development

    DEFF Research Database (Denmark)

    Wanninger, Andreas Wilhelm Georg; Koop, Damien; Moshel-Lynch, Sharon

    2008-01-01

    Brought together by Winston F. Ponder and David R. Lindberg, thirty-six experts on the evolution of the Mollusca provide an up-to-date review of its evolutionary history. The Mollusca are the second largest animal phylum and boast a fossil record of over 540 million years. They exhibit remarkable...

  17. A new evolutionary system for evolving artificial neural networks.

    Science.gov (United States)

    Yao, X; Liu, Y

    1997-01-01

    This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

  18. Exploring Tradeoffs in Demand-Side and Supply-Side Management of Urban Water Resources Using Agent-Based Modeling and Evolutionary Computation

    Directory of Open Access Journals (Sweden)

    Lufthansa Kanta

    2015-11-01

    Full Text Available Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger: (1 increases in the volume of water pumped through inter-basin transfers from an external reservoir; and (2 drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use.

  19. Feminist Encounters with Evolutionary Psychology

    OpenAIRE

    O'Neill, Rachel

    2016-01-01

    This Section of Australian Feminist Studies is the product of an event that took place at King’s College London in January 2015, hosted as part of the UK-based ‘Critical Sexology’ seminar series. Participants at this event – feminist scholars working across the fields of lin- guistics, cultural studies, sociology, and psychology – were invited to reflect on their encounters with evolutionary psychology (EP). As the event organiser, I was interested to prompt a discussion about how EP shapes t...

  20. Program Transformation to Identify List-Based Parallel Skeletons

    Directory of Open Access Journals (Sweden)

    Venkatesh Kannan

    2016-07-01

    Full Text Available Algorithmic skeletons are used as building-blocks to ease the task of parallel programming by abstracting the details of parallel implementation from the developer. Most existing libraries provide implementations of skeletons that are defined over flat data types such as lists or arrays. However, skeleton-based parallel programming is still very challenging as it requires intricate analysis of the underlying algorithm and often uses inefficient intermediate data structures. Further, the algorithmic structure of a given program may not match those of list-based skeletons. In this paper, we present a method to automatically transform any given program to one that is defined over a list and is more likely to contain instances of list-based skeletons. This facilitates the parallel execution of a transformed program using existing implementations of list-based parallel skeletons. Further, by using an existing transformation called distillation in conjunction with our method, we produce transformed programs that contain fewer inefficient intermediate data structures.

  1. Agent Programming Languages and Logics in Agent-Based Simulation

    DEFF Research Database (Denmark)

    Larsen, John

    2018-01-01

    and social behavior, and work on verification. Agent-based simulation is an approach for simulation that also uses the notion of agents. Although agent programming languages and logics are much less used in agent-based simulation, there are successful examples with agents designed according to the BDI...

  2. Dementia caregivers' responses to 2 Internet-based intervention programs.

    Science.gov (United States)

    Marziali, Elsa; Garcia, Linda J

    2011-02-01

    The aim of this study was to examine the impact on dementia caregivers' experienced stress and health status of 2 Internet-based intervention programs. Ninety-one dementia caregivers were given the choice of being involved in either an Internet-based chat support group or an Internet-based video conferencing support group. Pre-post outcome measures focused on distress, health status, social support, and service utilization. In contrast to the Chat Group, the Video Group showed significantly greater improvement in mental health status. Also, for the Video Group, improvements in self-efficacy, neuroticism, and social support were associated with lower stress response to coping with the care recipient's cognitive impairment and decline in function. The results show that, of 2 Internet-based intervention programs for dementia caregivers, the video conferencing intervention program was more effective in improving mental health status and improvement in personal characteristics were associated with lower caregiver stress response.

  3. Home-based intermediate care program vs hospitalization

    Science.gov (United States)

    Armstrong, Catherine Deri; Hogg, William E.; Lemelin, Jacques; Dahrouge, Simone; Martin, Carmel; Viner, Gary S.; Saginur, Raphael

    2008-01-01

    OBJECTIVE To explore whether a home-based intermediate care program in a large Canadian city lowers the cost of care and to look at whether such home-based programs could be a solution to the increasing demands on Canadian hospitals. DESIGN Single-arm study with historical controls. SETTING Department of Family Medicine at the Ottawa Hospital (Civic campus) in Ontario. PARTICIPANTS Patients requiring hospitalization for acute care. Participants were matched with historical controls based on case-mix, most responsible diagnosis, and level of complexity. INTERVENTIONS Placement in the home-based intermediate care program. Daily home visits from the nurse practitioner and 24-hour access to care by telephone. MAIN OUTCOME MEASURES Multivariate regression models were used to estimate the effect of the program on 5 outcomes: length of stay in hospital, cost of care substituted for hospitalization (Canadian dollars), readmission for a related diagnosis, readmission for any diagnosis, and costs incurred by community home-care services for patients following discharge from hospital. RESULTS The outcomes of 43 hospital admissions were matched with those of 363 controls. Patients enrolled in the program stayed longer in hospital (coefficient 3.3 days, P costs of home-based care were not significantly different from the costs of hospitalization (coefficient -$501, P = .11). CONCLUSION While estimated cost savings were not statistically significant, the limitations of our study suggest that we underestimated these savings. In particular, the economic inefficiencies of a small immature program and the inability to control for certain factors when selecting historical controls affected our results. Further research is needed to determine the economic effect of mature home-based programs. PMID:18208958

  4. A Census of Prison-Based Drug Treatment Programs: Implications for Programming, Policy, and Evaluation

    Science.gov (United States)

    Welsh, Wayne N.; Zajac, Gary

    2004-01-01

    Despite a growing realization that unmeasured programmatic differences influence prison-based drug treatment effectiveness, few attempts to systematically measure such differences have been made. To improve program planning and evaluation in this area, we developed a census instrument to collect descriptive information about 118 prison-based drug…

  5. Constraint-based scheduling applying constraint programming to scheduling problems

    CERN Document Server

    Baptiste, Philippe; Nuijten, Wim

    2001-01-01

    Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

  6. Visual Programming of Subsumption-Based Reactive Behaviour

    Directory of Open Access Journals (Sweden)

    Omid Banyasad

    2008-11-01

    Full Text Available General purpose visual programming languages (VPLs promote the construction of programs that are more comprehensible, robust, and maintainable by enabling programmers to directly observe and manipulate algorithms and data. However, they usually do not exploit the visual representation of entities in the problem domain, even if those entities and their interactions have obvious visual representations, as is the case in the robot control domain. We present a formal control model for autonomous robots, based on subsumption, and use it as the basis for a VPL in which reactive behaviour is programmed via interactions with a simulation.

  7. Comprehensive Outpatient Rehabilitation Program: Hospital-Based Stroke Outpatient Rehabilitation.

    Science.gov (United States)

    Rice, Danielle; Janzen, Shannon; McIntyre, Amanda; Vermeer, Julianne; Britt, Eileen; Teasell, Robert

    2016-05-01

    Few studies have considered the effectiveness of outpatient rehabilitation programs for stroke patients. The objective of this study was to assess the effectiveness of a hospital-based interdisciplinary outpatient stroke rehabilitation program with respect to physical functioning, mobility, and balance. The Comprehensive Outpatient Rehabilitation Program provides a hospital-based interdisciplinary approach to stroke rehabilitation in Southwestern Ontario. Outcome measures from physiotherapy and occupational therapy sessions were available at intake and discharge from the program. A series of paired sample t-tests were performed to assess patient changes between time points for each outcome measure. A total of 271 patients met the inclusion criteria for analysis (56.1% male; mean age = 62.9 ± 13.9 years). Significant improvements were found between admission and discharge for the Functional Independence Measure, grip strength, Chedoke-McMaster Stroke Assessment, two-minute walk test, maximum walk test, Timed Up and Go, Berg Balance Scale, and one-legged stance (P rehabilitation program was effective at improving the physical functioning, mobility, and balance of individuals after a stroke. A hospital-based, stroke-specific rehabilitation program should be considered when patients continue to experience deficits after inpatient rehabilitation. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  8. An efficient model for auxiliary diagnosis of hepatocellular carcinoma based on gene expression programming.

    Science.gov (United States)

    Zhang, Li; Chen, Jiasheng; Gao, Chunming; Liu, Chuanmiao; Xu, Kuihua

    2018-03-16

    Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The early diagnosis of HCC is greatly helpful to achieve long-term disease-free survival. However, HCC is usually difficult to be diagnosed at an early stage. The aim of this study was to create the prediction model to diagnose HCC based on gene expression programming (GEP). GEP is an evolutionary algorithm and a domain-independent problem-solving technique. Clinical data show that six serum biomarkers, including gamma-glutamyl transferase, C-reaction protein, carcinoembryonic antigen, alpha-fetoprotein, carbohydrate antigen 153, and carbohydrate antigen 199, are related to HCC characteristics. In this study, the prediction of HCC was made based on these six biomarkers (195 HCC patients and 215 non-HCC controls) by setting up optimal joint models with GEP. The GEP model discriminated 353 out of 410 subjects, representing a determination coefficient of 86.28% (283/328) and 85.37% (70/82) for training and test sets, respectively. Compared to the results from the support vector machine, the artificial neural network, and the multilayer perceptron, GEP showed a better outcome. The results suggested that GEP modeling was a promising and excellent tool in diagnosis of hepatocellular carcinoma, and it could be widely used in HCC auxiliary diagnosis. Graphical abstract The process to establish an efficient model for auxiliary diagnosis of hepatocellular carcinoma.

  9. Evaluation of a Secure Laptop-Based Testing Program in an Undergraduate Nursing Program: Students' Perspective.

    Science.gov (United States)

    Tao, Jinyuan; Gunter, Glenda; Tsai, Ming-Hsiu; Lim, Dan

    2016-01-01

    Recently, the many robust learning management systems, and the availability of affordable laptops, have made secure laptop-based testing a reality on many campuses. The undergraduate nursing program at the authors' university began to implement a secure laptop-based testing program in 2009, which allowed students to use their newly purchased laptops to take quizzes and tests securely in classrooms. After nearly 5 years' secure laptop-based testing program implementation, a formative evaluation, using a mixed method that has both descriptive and correlational data elements, was conducted to seek constructive feedback from students to improve the program. Evaluation data show that, overall, students (n = 166) believed the secure laptop-based testing program helps them get hands-on experience of taking examinations on the computer and gets them prepared for their computerized NCLEX-RN. Students, however, had a lot of concerns about laptop glitches and campus wireless network glitches they experienced during testing. At the same time, NCLEX-RN first-time passing rate data were analyzed using the χ2 test, and revealed no significant association between the two testing methods (paper-and-pencil testing and the secure laptop-based testing) and students' first-time NCLEX-RN passing rate. Based on the odds ratio, however, the odds of students passing NCLEX-RN the first time was 1.37 times higher if they were taught with the secure laptop-based testing method than if taught with the traditional paper-and-pencil testing method in nursing school. It was recommended to the institution that better quality of laptops needs to be provided to future students, measures needed to be taken to further stabilize the campus wireless Internet network, and there was a need to reevaluate the Laptop Initiative Program.

  10. Risk-based technical specifications program: Site interview results

    International Nuclear Information System (INIS)

    Andre, G.R.; Baker, A.J.; Johnson, R.L.

    1991-08-01

    The Electric Power Research Institute and Pacific Gas and Electric Company are sponsoring a program directed at improving Technical Specifications using risk-based methods. The major objectives of the program are to develop risk-based approaches to improve Technical Specifications and to develop an Interactive Risk Advisor (IRA) prototype. The IRA is envisioned as an interactive system that is available to plant personnel to assist in controlling plant operation. Use of an IRA is viewed as a method to improve plant availability while maintaining or improving plant safety. In support of the program, interviews were conducted at several PWR and BWR plant sites, to elicit opinions and information concerning risk-based approaches to Technical Specifications and IRA requirements. This report presents the results of these interviews, including the functional requirements of an IRA. 2 refs., 6 figs., 2 tabs

  11. Evaluation of a case-based urology learning program.

    Science.gov (United States)

    Mishra, Kirtishri; Snow-Lisy, Devon C; Ross, Jonathan; Goldfarb, David A; Goldman, Howard; Campbell, Steven C

    2013-12-01

    To address the challenges that today's trainees encounter, such as information overload and reduced immersion in the field, and recognizing their preference for novel educational resources, an electronic case-based urology learning program was developed. Each case was designed to illustrate the basic principles of the disease process and the fundamentals of evaluation and management using the Socratic method, recapitulating a prototypical patient encounter. A 21-question survey was developed after review of published reports of classroom and clinical learning environment surveys. The target group was 2 pilot urology training programs (the Cleveland Clinic and University Hospitals-Case Medical Center). The responses were entirely anonymous. A total of 32 trainees participated (8 fellows and 24 residents), representing a 53% response rate. Most trainees (79%) were able to process cases within an average of ≤ 10 minutes. Of the trainees, 91% reported referring back to particular cases for patient care, to review for examinations, or for studying. Most trainees believed a case-based urology learning program would be a potentially important resource for clinical practice (69%) and for preparing for the in-service (63%) or board (69%) examinations. Most trainees believed the program met its goals of illustrating the basics principles of the disease process (88%), outlining the fundamentals of evaluation and management (94%), and improving the trainees' knowledge base (91%). An electronic case-based urology learning program is feasible and useful and stimulates learning at all trainee levels. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Evolutionary history of the endangered fish Zoogoneticus quitzeoensis (Bean, 1898 (Cyprinodontiformes: Goodeidae using a sequential approach to phylogeography based on mitochondrial and nuclear DNA data

    Directory of Open Access Journals (Sweden)

    García-Garitagoitia José

    2008-05-01

    Full Text Available Abstract Background Tectonic, volcanic and climatic events that produce changes in hydrographic systems are the main causes of diversification and speciation of freshwater fishes. Elucidate the evolutionary history of freshwater fishes permits to infer theories on the biotic and geological evolution of a region, which can further be applied to understand processes of population divergence, speciation and for conservation purposes. The freshwater ecosystems in Central Mexico are characterized by their genesis dynamism, destruction, and compartmentalization induced by intense geologic activity and climatic changes since the early Miocene. The endangered goodeid Zoogoneticus quitzeoensis is widely distributed across Central México, thus making it a good model for phylogeographic analyses in this area. Results We addressed the phylogeography, evolutionary history and genetic structure of populations of Z. quitzeoensis through a sequential approach, based on both microsatellite and mitochondrial cytochrome b sequences. Most haplotypes were private to particular locations. All the populations analysed showed a remarkable number of haplotypes. The level of gene diversity within populations was H¯ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGafmisaGKbaebaaaa@2D06@d = 0.987 (0.714 – 1.00. However, in general the nucleotide diversity was low, π = 0.0173 (0.0015 – 0.0049. Significant genetic structure was found among populations at the mitochondrial and nuclear level (ΦST = 0.836 and FST = 0.262, respectively. We distinguished two well-defined mitochondrial lineages that were separated ca. 3.3 million years ago (Mya. The time since expansion was ca. 1.5 × 106 years ago for Lineage I and ca. 860,000 years ago for Lineage II. Also, genetic patterns of

  13. Mutually unbiased bases and semi-definite programming

    Energy Technology Data Exchange (ETDEWEB)

    Brierley, Stephen; Weigert, Stefan, E-mail: steve.brierley@ulb.ac.be, E-mail: stefan.weigert@york.ac.uk

    2010-11-01

    A complex Hilbert space of dimension six supports at least three but not more than seven mutually unbiased bases. Two computer-aided analytical methods to tighten these bounds are reviewed, based on a discretization of parameter space and on Groebner bases. A third algorithmic approach is presented: the non-existence of more than three mutually unbiased bases in composite dimensions can be decided by a global optimization method known as semidefinite programming. The method is used to confirm that the spectral matrix cannot be part of a complete set of seven mutually unbiased bases in dimension six.

  14. Mutually unbiased bases and semi-definite programming

    International Nuclear Information System (INIS)

    Brierley, Stephen; Weigert, Stefan

    2010-01-01

    A complex Hilbert space of dimension six supports at least three but not more than seven mutually unbiased bases. Two computer-aided analytical methods to tighten these bounds are reviewed, based on a discretization of parameter space and on Groebner bases. A third algorithmic approach is presented: the non-existence of more than three mutually unbiased bases in composite dimensions can be decided by a global optimization method known as semidefinite programming. The method is used to confirm that the spectral matrix cannot be part of a complete set of seven mutually unbiased bases in dimension six.

  15. Infrastructure system restoration planning using evolutionary algorithms

    Science.gov (United States)

    Corns, Steven; Long, Suzanna K.; Shoberg, Thomas G.

    2016-01-01

    This paper presents an evolutionary algorithm to address restoration issues for supply chain interdependent critical infrastructure. Rapid restoration of infrastructure after a large-scale disaster is necessary to sustaining a nation's economy and security, but such long-term restoration has not been investigated as thoroughly as initial rescue and recovery efforts. A model of the Greater Saint Louis Missouri area was created and a disaster scenario simulated. An evolutionary algorithm is used to determine the order in which the bridges should be repaired based on indirect costs. Solutions were evaluated based on the reduction of indirect costs and the restoration of transportation capacity. When compared to a greedy algorithm, the evolutionary algorithm solution reduced indirect costs by approximately 12.4% by restoring automotive travel routes for workers and re-establishing the flow of commodities across the three rivers in the Saint Louis area.

  16. Introduction to Evolutionary Algorithms

    CERN Document Server

    Yu, Xinjie

    2010-01-01

    Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm opti

  17. River-Based Experiential Learning: the Bear River Fellows Program

    Science.gov (United States)

    Rosenberg, D. E.; Shirley, B.; Roark, M. F.

    2012-12-01

    The Department of Civil and Environmental Engineering, Outdoor Recreation, and Parks and Recreation programs at Utah State University (USU) have partnered to offer a new, unique river-based experiential learning opportunity for undergraduates called the Bear River Fellows Program. The program allows incoming freshmen Fellows to experience a river first hand during a 5-day/4-night river trip on the nearby Bear River two weeks before the start of their first Fall semester. As part of the program, Fellows will navigate the Bear River in canoes, camp along the banks, interact with local water and environmental managers, collect channel cross section, stream flow, vegetation cover, and topological complexity data, meet other incoming freshmen, interact with faculty and graduate students, develop boating and leadership skills, problem solve, and participate as full members of the trip team. Subsequently, Fellows will get paid as undergraduate researchers during their Fall and Spring Freshman semesters to analyze, synthesize, and present the field data they collect. The program is a collaborative effort between two USU academic units and the (non-academic) division of Student Services and supports a larger National Science Foundation funded environmental modelling and management project for the lower Bear River, Utah watershed. We have advertised the program via Facebook and emails to incoming USU freshmen, received 35 applications (60% women), and accepted 5 Fellows into the program (3 female and 2 male). The river trip departs August 14, 2012. The poster will overview the Bear River Fellows Program and present qualitative and preliminary outcomes emerging from the trip and Fellows' work through the Fall semester with the field data they collect. We will also undertake more rigorous and longer longitudinal quantitative evaluation of Program outcomes (for example, in problem-solving and leadership) both in Spring 2013 and in subsequent 2013 and 2014 offerings of the

  18. Evolutionary games on graphs

    Science.gov (United States)

    Szabó, György; Fáth, Gábor

    2007-07-01

    Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

  19. Evolutionary mysteries in meiosis.

    Science.gov (United States)

    Lenormand, Thomas; Engelstädter, Jan; Johnston, Susan E; Wijnker, Erik; Haag, Christoph R

    2016-10-19

    Meiosis is a key event of sexual life cycles in eukaryotes. Its mechanistic details have been uncovered in several model organisms, and most of its essential features have received various and often contradictory evolutionary interpretations. In this perspective, we present an overview of these often 'weird' features. We discuss the origin of meiosis (origin of ploidy reduction and recombination, two-step meiosis), its secondary modifications (in polyploids or asexuals, inverted meiosis), its importance in punctuating life cycles (meiotic arrests, epigenetic resetting, meiotic asymmetry, meiotic fairness) and features associated with recombination (disjunction constraints, heterochiasmy, crossover interference and hotspots). We present the various evolutionary scenarios and selective pressures that have been proposed to account for these features, and we highlight that their evolutionary significance often remains largely mysterious. Resolving these mysteries will likely provide decisive steps towards understanding why sex and recombination are found in the majority of eukaryotes.This article is part of the themed issue 'Weird sex: the underappreciated diversity of sexual reproduction'. © 2016 The Author(s).

  20. Repository-based software engineering program: Concept document

    Science.gov (United States)

    1992-01-01

    This document provides the context for Repository-Based Software Engineering's (RBSE's) evolving functional and operational product requirements, and it is the parent document for development of detailed technical and management plans. When furnished, requirements documents will serve as the governing RBSE product specification. The RBSE Program Management Plan will define resources, schedules, and technical and organizational approaches to fulfilling the goals and objectives of this concept. The purpose of this document is to provide a concise overview of RBSE, describe the rationale for the RBSE Program, and define a clear, common vision for RBSE team members and customers. The document also provides the foundation for developing RBSE user and system requirements and a corresponding Program Management Plan. The concept is used to express the program mission to RBSE users and managers and to provide an exhibit for community review.

  1. Parallel evolutionary computation in bioinformatics applications.

    Science.gov (United States)

    Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

    2013-05-01

    A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  2. Using scenario based programming to develop embedded control software

    NARCIS (Netherlands)

    Bettiol, F.

    2015-01-01

    A new paradigm to develop embedded software is waking up the interest of companies. Its name is Scenario Based Programming and it claims to be a good approach to develop embedded software. Live Sequence Charts (LSC), a visual language supporting the paradigm, enables the developers to specify a

  3. MENO-II: An AI-Based Programming Tutor.

    Science.gov (United States)

    Soloway, Elliot; And Others

    This report examines the features and performance of the BUG-FINDing component of MENO-II, a computer-based tutor for beginning PASCAL programming students. A discussion of the use of artificial intelligence techniques is followed by a summary of the system status and objectives. The two main components of MENO-II are described, beginning with the…

  4. Dynamic Frames Based Verification Method for Concurrent Java Programs

    NARCIS (Netherlands)

    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

  5. Ethical Decisions in Experience-Based Training and Development Programs.

    Science.gov (United States)

    Gass, Michael A.; Wurdinger, Scott

    1993-01-01

    Illustrates how principle and virtue ethics can be applied to decision-making processes in experience-based training and development programs. Principle ethics is guided by predetermined rules and assumes that issues being examined are somewhat similar in context, whereas virtue ethics assumes that "correct behavior" is determined from…

  6. Evaluation of a Spiritually Based Child Maltreatment Prevention Training Program

    Science.gov (United States)

    Baker, Louisa K.; Rigazio-DiGilio, Sandra A.

    2013-01-01

    The authors empirically evaluated a spiritually based 1-day child maltreatment training program. Pretest, posttest, and follow-up results indicated that participants' recognition of hypothetical maltreatment did not increase after training. Furthermore, although participants decreased their use of items known to dissuade decisions to report, they…

  7. A Spreadsheet-Based, Matrix Formulation Linear Programming Lesson

    DEFF Research Database (Denmark)

    Harrod, Steven

    2009-01-01

    The article focuses on the spreadsheet-based, matrix formulation linear programming lesson. According to the article, it makes a higher level of theoretical mathematics approachable by a wide spectrum of students wherein many may not be decision sciences or quantitative methods majors. Moreover...

  8. Scenario-Based Programming, Usability-Oriented Perception

    Science.gov (United States)

    Alexandron, Giora; Armoni, Michal; Gordon, Michal; Harel, David

    2014-01-01

    In this article, we discuss the possible connection between the programming language and the paradigm behind it, and programmers' tendency to adopt an external or internal perspective of the system they develop. Based on a qualitative analysis, we found that when working with the visual, interobject language of live sequence charts (LSC),…

  9. Effects of a school-based pediatric obesity prevention program

    Science.gov (United States)

    The purpose of this study was to evaluate a school-based pediatric obesity program for elementary children. Children (n = 782) were between the ages of 7 and 9 and in the 2nd grade. A total of 323 (189 males) children who exceeded the 85th percentile for BMI were randomized into an integrated health...

  10. Shuttle Program Information Management System (SPIMS) data base

    Science.gov (United States)

    1983-01-01

    The Shuttle Program Information Management System (SPIMS) is a computerized data base operations system. The central computer is the CDC 170-730 located at Johnson Space Center (JSC), Houston, Texas. There are several applications which have been developed and supported by SPIMS. A brief description is given.

  11. Improved Sorting-Based Procedure for Integer Programming

    DEFF Research Database (Denmark)

    Dantchev, Stefan

    2002-01-01

    Recently, Cornuéjols and Dawande have considered a special class of 0-1 programs that turns out to be hard for existing IP solvers. One of them is a sorting-based algorithm, based on an idea of Wolsey. In this paper, we show how to improve both the running time and the space requirements...... of this algorithm. The drastic reduction of space needed allows us to solve much larger instances than was possible before using this technique....

  12. Applied Research of Enterprise Cost Control Based on Linear Programming

    Directory of Open Access Journals (Sweden)

    Yu Shuo

    2015-01-01

    This paper researches the enterprise cost control through the linear programming model, and analyzes the restriction factors of the labor of enterprise production, raw materials, processing equipment, sales price, and other factors affecting the enterprise income, so as to obtain an enterprise cost control model based on the linear programming. This model can calculate rational production mode in the case of limited resources, and acquire optimal enterprise income. The production guiding program and scheduling arrangement of the enterprise can be obtained through calculation results, so as to provide scientific and effective guidance for the enterprise production. This paper adds the sensitivity analysis in the linear programming model, so as to learn about the stability of the enterprise cost control model based on linear programming through the sensitivity analysis, and verify the rationality of the model, and indicate the direction for the enterprise cost control. The calculation results of the model can provide a certain reference for the enterprise planning in the market economy environment, which have strong reference and practical significance in terms of the enterprise cost control.

  13. Community Based Educational Model on Water Conservation Program

    Science.gov (United States)

    Sudiajeng, L.; Parwita, I. G. L.; Wiraga, I. W.; Mudhina, M.

    2018-01-01

    The previous research showed that there were indicators of water crisis in the northern and eastern part of Denpasar city and most of coastal area experienced on seawater intrusion. The recommended water conservation programs were rainwater harvesting and educate the community to develop a water saving and environmentally conscious culture. This research was conducted to built the community based educational model on water conservation program through ergonomics SHIP approach which placed the human aspect as the first consideration, besides the economic and technically aspects. The stakeholders involved in the program started from the problem analyses to the implementation and the maintenance as well. The model was built through three main steps, included determination of accepted design; building the recharge wells by involving local communities; guidance and assistance in developing a water saving and environmentally conscious culture for early childhood, elementary and junior high school students, community and industry. The program was implemented based on the “TRIHITA KARANA” concept, which means the relationship between human to God, human-to-human, and human to environment. Through the development of the model, it is expected to grow a sense of belonging and awareness from the community to maintain the sustainability of the program.

  14. A rural, community-based suicide awareness and intervention program.

    Science.gov (United States)

    Jones, Sharon; Walker, Coralanne; Miles, Alison C J; De Silva, Eve; Zimitat, Craig

    2015-01-01

    Suicide is a prominent public health issue in rural Australia and specifically in Tasmania, which has one of the highest suicide rates in the country. The Community Response to Eliminating Suicide (CORES) program was developed in rural Tasmania in response to a significant number of suicides over a short period of time. CORES is unique in that it is both a community-based and gatekeeper education model. CORES aims to build and empower communities to take ownership of suicide prevention strategies. It also aims to increase the individual community member's interpersonal skills and awareness of suicide risks, while building peer support and awareness of suicide prevention support services within the community itself. Pre- and post-test surveys after the CORES 1-day suicide awareness and intervention program (SAIP) showed significant increases in levels of comfort and confidence in discussing suicide with those who may be contemplating that action. CORES builds community capital through establishing new connections within communities. Establishment of local executive groups, funding and SAIP are key activities of successful CORES programs in communities around Australia. Over half of the initial leaders are still actively involved after a decade, which reflects positively on the quality and outcomes of the program. This study supports CORES as a beneficial and feasible community-based suicide intervention program for rural communities.

  15. Evaluation of a Hospital-Based Pneumonia Nurse Navigator Program.

    Science.gov (United States)

    Seldon, Lisa E; McDonough, Kelly; Turner, Barbara; Simmons, Leigh Ann

    2016-12-01

    The aim of this study is to evaluate the effectiveness of a hospital-based pneumonia nurse navigator program. This study used a retrospective, formative evaluation. Data of patients admitted from January 2012 through December 2014 to a large community hospital with a primary or secondary diagnosis of pneumonia, excluding aspiration pneumonia, were used. Data included patient demographics, diagnoses, insurance coverage, core measures, average length of stay (ALOS), disposition, readmission rate, financial outcomes, and patient barriers to care were collected. Descriptive statistics and parametric testing were used to analyze data. Core measure performance was sustained at the 90th percentile 2 years after the implementation of the navigator program. The ALOS did not decrease to established benchmarks; however, the SD for ALOS decreased by nearly half after implementation of the navigator program, suggesting the program decreased the number and length of extended stays. Charges per case decreased by 21% from 2012 to 2014. Variable costs decreased by 4% over a 2-year period, which increased net profit per case by 5%. Average readmission payments increased by 8% from 2012 to 2014, and the net revenue per case increased by 8.3%. The pneumonia nurse navigator program may improve core measures, reduce ALOS, and increase net revenue. Future evaluations are necessary to substantiate these findings and optimize the cost and quality performance of navigator programs.

  16. Evolutionary stability concepts in a stochastic environment

    Science.gov (United States)

    Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

    2017-09-01

    Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

  17. Evolutionary Sound Synthesis Controlled by Gestural Data

    Directory of Open Access Journals (Sweden)

    Jose Fornari

    2011-05-01

    Full Text Available This article focuses on the interdisciplinary research involving Computer Music and Generative Visual Art. We describe the implementation of two interactive artistic systems based on principles of Gestural Data (WILSON, 2002 retrieval and self-organization (MORONI, 2003, to control an Evolutionary Sound Synthesis method (ESSynth. The first implementation uses, as gestural data, image mapping of handmade drawings. The second one uses gestural data from dynamic body movements of dance. The resulting computer output is generated by an interactive system implemented in Pure Data (PD. This system uses principles of Evolutionary Computation (EC, which yields the generation of a synthetic adaptive population of sound objects. Considering that music could be seen as “organized sound” the contribution of our study is to develop a system that aims to generate "self-organized sound" – a method that uses evolutionary computation to bridge between gesture, sound and music.

  18. Prospective Algorithms for Quantum Evolutionary Computation

    OpenAIRE

    Sofge, Donald A.

    2008-01-01

    This effort examines the intersection of the emerging field of quantum computing and the more established field of evolutionary computation. The goal is to understand what benefits quantum computing might offer to computational intelligence and how computational intelligence paradigms might be implemented as quantum programs to be run on a future quantum computer. We critically examine proposed algorithms and methods for implementing computational intelligence paradigms, primarily focused on ...

  19. Convex hull ranking algorithm for multi-objective evolutionary algorithms

    NARCIS (Netherlands)

    Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.

    2012-01-01

    Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity

  20. Cooperation or Competition: An Evolutionary Game Study between Commercial Banks and Big Data-Based E-Commerce Financial Institutions in China

    Directory of Open Access Journals (Sweden)

    Yi Zhao

    2015-01-01

    Full Text Available On the premise of participants’ bounded rationality and information asymmetry, this paper focuses on the cooperation or competition relationship between Chinese e-commerce financial institutions and commercial banks from the perspective of dynamic game. Theoretical mathematical model is built to analyze an evolutionary stable strategy under different conditions. We adopt real-life data set collected in Alibaba’s network credit loan business case and Jingdong’s supply chain financing business case to verify the evolution process of cooperation and competition relationship. The results show that (cooperation, cooperation is bound to be the evolutionary stable strategy (ESS and cooperation tends to be increasingly in-depth and expansive for commercial banks as well as e-commerce financial institutions in China. The complementarity of participants’ core competitiveness is explored as the root of cooperation. Finally, strategic suggestions are put forward on cooperation between e-commerce financial institutions and commercial banks.

  1. Hybrid Projected Gradient-Evolutionary Search Algorithm for Mixed Integer Nonlinear Optimization Problems

    National Research Council Canada - National Science Library

    Homaifar, Abdollah; Esterline, Albert; Kimiaghalam, Bahram

    2005-01-01

    The Hybrid Projected Gradient-Evolutionary Search Algorithm (HPGES) algorithm uses a specially designed evolutionary-based global search strategy to efficiently create candidate solutions in the solution space...

  2. Evidence-Based Programming within Cooperative Extension: How Can We Maintain Program Fidelity While Adapting to Meet Local Needs?

    Science.gov (United States)

    Olson, Jonathan R.; Welsh, Janet A.; Perkins, Daniel F.

    2015-01-01

    In this article, we describe how the recent movement towards evidence-based programming has impacted Extension. We review how the emphasis on implementing such programs with strict fidelity to an underlying program model may be at odds with Extension's strong history of adapting programming to meet the unique needs of children, youth, families,…

  3. Community-Based Global Health Program for Maltreated Children and Adolescents in Brazil: The Equilibrium Program.

    Science.gov (United States)

    Marques, Andrea Horvath; Oliveira, Paula Approbato; Scomparini, Luciana Burim; Silva, Uiara Maria Rêgo E; Silva, Angelica Cristine; Doretto, Victoria; de Medeiros Filho, Mauro Victor; Scivoletto, Sandra

    2015-01-01

    The maltreatment of children and adolescents is a global public health problem that affects high- and low-middle income countries ("LMICs"). In the United States, around 1.2 million children suffer from abuse, while in LMICs, such as Brazil, these rates are much higher (an estimated 28 million children). Exposition to early environmental stress has been associated with suboptimal physical and brain development, persistent cognitive impairment, and behavioral problems. Studies have reported that children exposed to maltreatment are at high risk of behavioral problems, learning disabilities, communication and psychiatric disorders, and general clinical conditions, such as obesity and systemic inflammation later in life. The aim of this paper is to describe The Equilibrium Program ("TEP"), a community-based global health program implemented in São Paulo, Brazil to serve traumatized and neglected children and adolescents. We will describe and discuss TEP's implementation, highlighting its innovation aspects, research projects developed within the program as well as its population profile. Finally, we will discuss TEP's social impact, challenges, and limitations. The program's goal is to promote the social and family reintegration of maltreated children and adolescents through an interdisciplinary intervention program that provides multi-dimensional bio-psycho-social treatment integrated with the diverse services needed to meet the unique demands of this population. The program's cost effectiveness is being evaluated to support the development of more effective treatments and to expand similar programs in other areas of Brazil. Policy makers should encourage early evidence-based interventions for disadvantaged children to promote healthier psychosocial environments and provide them opportunities to become healthy and productive adults. This approach has already shown itself to be a cost-effective strategy to prevent disease and promote health.

  4. Cooperation or Competition: An Evolutionary Game Study between Commercial Banks and Big Data-Based E-Commerce Financial Institutions in China

    OpenAIRE

    Yi Zhao; Dong Li; Liqiang Pan

    2015-01-01

    On the premise of participants’ bounded rationality and information asymmetry, this paper focuses on the cooperation or competition relationship between Chinese e-commerce financial institutions and commercial banks from the perspective of dynamic game. Theoretical mathematical model is built to analyze an evolutionary stable strategy under different conditions. We adopt real-life data set collected in Alibaba’s network credit loan business case and Jingdong’s supply chain financing business ...

  5. Model-based automated testing of critical PLC programs.

    CERN Document Server

    Fernández Adiego, B; Tournier, J-C; González Suárez, V M; Bliudze, S

    2014-01-01

    Testing of critical PLC (Programmable Logic Controller) programs remains a challenging task for control system engineers as it can rarely be automated. This paper proposes a model based approach which uses the BIP (Behavior, Interactions and Priorities) framework to perform automated testing of PLC programs developed with the UNICOS (UNified Industrial COntrol System) framework. This paper defines the translation procedure and rules from UNICOS to BIP which can be fully automated in order to hide the complexity of the underlying model from the control engineers. The approach is illustrated and validated through the study of a water treatment process.

  6. A Competence-Based Curriculum Design for Entrepreneurship Study Program

    Directory of Open Access Journals (Sweden)

    Priska J.R. Siagian

    2011-08-01

    Full Text Available Indonesia is affected by global crisis. Increasing the number of entrepreneurs is one of many solutions to increase the economic growth in Indonesia. The number of entrepreneurs in Indonesia to leverage the economic growth is still limited. Entrepreneurs can be prepared through an Entrepreneurship Study Program. Entrepreneurship Study Program attempts to create qualified entrepreneurs who have relevant competences. In order to create a qualified entrepreneurs, the Entrepreneurial Studies Program requires a competency-based curriculum that will support the educational process and provide all the necessary to become future entrepreneurs who can survive through a global challenge. This research aims to design a competence-based curriculum for entrepreneurial study and uses Quality Function Deployment (QFD as the major tool to design the competence-based curriculum. From the QFD process, this research finds core and elective courses for the Entrepreneurship Study Program. The result shows the competences covered by the courses and sequence, credits, and teaching methods for each course. The competences prepared the potential entrepreneurs can be achieved through specific courses which can be acquired within 8 semesters.

  7. Studies in evolutionary agroecology

    DEFF Research Database (Denmark)

    Wille, Wibke

    of population performance will increase in frequency. Yield, one of the fundamental agronomic variables, is not an individual, but a population characteristic. A farmer wants a high yield per hectare; he is not interested in the performance of individual plants. When individual selection and population...... of Evolutionary Agroecology that the highest yielding individuals do not necessarily perform best as a population. The investment of resources into strategies and structures increasing individual competitive ability carries a cost. If a whole population consists of individuals investing resources to compete...

  8. Towards Adaptive Evolutionary Architecture

    DEFF Research Database (Denmark)

    Bak, Sebastian HOlt; Rask, Nina; Risi, Sebastian

    2016-01-01

    This paper presents first results from an interdisciplinary project, in which the fields of architecture, philosophy and artificial life are combined to explore possible futures of architecture. Through an interactive evolutionary installation, called EvoCurtain, we investigate aspects of how...... to the development of designs tailored to the individual preferences of inhabitants, changing the roles of architects and designers entirely. Architecture-as-it-could-be is a philosophical approach conducted through artistic methods to anticipate the technological futures of human-centered development within...

  9. KNOWLEDGE BASE AND EFL TEACHER EDUCATION PROGRAMS: A COLOMBIAN PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    Yamith Fandiño

    2013-04-01

    Full Text Available In the 21st century, Colombian pre-service EFL Teacher Education Programs (TEPs should study what constitutes the core knowledge base for language teachers to be effective in their profession. These programs must refrain from simply conceptualizing knowledge base as the acquisition of the basic skills required for teaching, the competency of educators in their subject matter area, and the use of pedagogical skills. Instead, they should strive to reflect on what Colombian language teachers need to know about teaching and learning, and study how their knowledge, beliefs, and attitudes inform their practices. A starting point to do so is to interpret the variety of proposals that have been generated through the years in the field. This paperoffers a review of what teacher knowledge base is, presents an overview of how Colombian EFL TEPs are working on teacher knowledge,and suggests some strategies to envision a more complete framework of reference for teacher formation in Colombia.

  10. A Program to Protect Integrity of Body-Mind-Spirit: Mindfulness Based Stress Reduction Program

    Directory of Open Access Journals (Sweden)

    Oznur Korukcu

    2015-03-01

    Full Text Available Mindfulness-based applications allow health care staffs to understand themselves as well as other individuals. Awareness based applications are not only stress reduction techniques but also a way of understanding the life and human existence, and it should not be only used to cope with the diseases. Emotions, thoughts and judgments of people might give direction to their life sometimes. Accessing a life without judgment and negative feelings brings a peaceful and happy life together. Mindfulness based stress reduction exercises may help to enjoy the present time, to cope with the challenges, stress and diseases and accept the negative life experiences rather than to question their reasons. About three decades ago, Kabat-Zin conducted the first investigation of Mindfulness-Based Stress Reduction program which is used commonly all around the world. The 8-weeks program, which contains mindful living exercises (such as eating, walking, cooking, etc., yoga, body scan and meditation practices, requires doing daily life activity and meditation with attention, openness and acceptance. The aim of this review article is to give information about Mindfulness Based Stress Reduction program and to emphasize its importance. [Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry 2015; 7(1: 68-80

  11. Embedded design based virtual instrument program for positron beam automation

    International Nuclear Information System (INIS)

    Jayapandian, J.; Gururaj, K.; Abhaya, S.; Parimala, J.; Amarendra, G.

    2008-01-01

    Automation of positron beam experiment with a single chip embedded design using a programmable system on chip (PSoC) which provides easy interfacing of the high-voltage DC power supply is reported. Virtual Instrument (VI) control program written in Visual Basic 6.0 ensures the following functions (i) adjusting of sample high voltage by interacting with the programmed PSoC hardware, (ii) control of personal computer (PC) based multi channel analyzer (MCA) card for energy spectroscopy, (iii) analysis of the obtained spectrum to extract the relevant line shape parameters, (iv) plotting of relevant parameters and (v) saving the file in the appropriate format. The present study highlights the hardware features of the PSoC hardware module as well as the control of MCA and other units through programming in Visual Basic

  12. Physical security technology base programs for physical security

    International Nuclear Information System (INIS)

    Jacobs, J.

    1986-01-01

    Sandia National Laboratories is the US Department of Energy's lead laboratory for physical security research and development (R and D). In support of this mission, Sandia has maintained for several years an R and D program in each of the following technology areas: Intrusion Detection, Entry Control, CCTV Assessment, Access Delay, Alarm Display, and Guard Equipment and Training. The purpose of the technology base programs is to maintain cognizance of the capabilities of the commercial market, identify improvements and transfer technology to industry and facilities. The output of these programs supports the development of new equipment and advanced system concepts, demonstrations of proof-of-principles and system implementation. This paper will review the status of current developments and discuss trends in new technologies which are being explored for future applications, i.e., artificial intelligence, expert systems, robotics, and more automated systems

  13. Evaluation of a Workplace-Based Migraine Education Program.

    Science.gov (United States)

    Burton, Wayne N; Chen, Chin-Yu; Li, Xingquan; McCluskey, Maureen; Erickson, Denise; Schultz, Alyssa B

    2016-08-01

    Migraine affects approximately 10% of working-age adults and is associated with increased health care costs, absenteeism, and presenteeism in the workplace. A migraine education program was offered to United States employees of a global financial services organization. Two hundred forty three employees (46% response rate) completed both a baseline and 6-month follow-up migraine questionnaire. The program included webinars, E-mailed educational tips, and intranet-based resources. No change was found in the frequency of migraines but improvements were observed in the severity, workdays missed, effectiveness at work during migraine, and work/activity limitations. Participants reported taking action to identify and reduce migraine triggers. A worksite disease education program for migraine headache has the potential to significantly impact lost productivity and absenteeism for migraineurs.

  14. A backtracking evolutionary algorithm for power systems

    Directory of Open Access Journals (Sweden)

    Chiou Ji-Pyng

    2017-01-01

    Full Text Available This paper presents a backtracking variable scaling hybrid differential evolution, called backtracking VSHDE, for solving the optimal network reconfiguration problems for power loss reduction in distribution systems. The concepts of the backtracking, variable scaling factor, migrating, accelerated, and boundary control mechanism are embedded in the original differential evolution (DE to form the backtracking VSHDE. The concepts of the backtracking and boundary control mechanism can increase the population diversity. And, according to the convergence property of the population, the scaling factor is adjusted based on the 1/5 success rule of the evolution strategies (ESs. A larger population size must be used in the evolutionary algorithms (EAs to maintain the population diversity. To overcome this drawback, two operations, acceleration operation and migrating operation, are embedded into the proposed method. The feeder reconfiguration of distribution systems is modelled as an optimization problem which aims at achieving the minimum loss subject to voltage and current constraints. So, the proper system topology that reduces the power loss according to a load pattern is an important issue. Mathematically, the network reconfiguration system is a nonlinear programming problem with integer variables. One three-feeder network reconfiguration system from the literature is researched by the proposed backtracking VSHDE method and simulated annealing (SA. Numerical results show that the perfrmance of the proposed method outperformed the SA method.

  15. Literary study and evolutionary theory : A review essay.

    Science.gov (United States)

    Carroll, J

    1998-09-01

    Several recent books have claimed to integrate literary study with evolutionary biology. All of the books here considered, except Robert Storey's, adopt conceptions of evolutionary theory that are in some way marginal to the Darwinian adaptationist program. All the works attempt to connect evolutionary study with various other disciplines or methodologies: for example, with cultural anthropology, cognitive psychology, the psychology of emotion, neurobiology, chaos theory, or structuralist linguistics. No empirical paradigm has yet been established for this field, but important steps have been taken, especially by Storey, in formulating basic principles, identifying appropriate disciplinary connections, and marking out lines of inquiry. Reciprocal efforts are needed from biologists and social scientists.

  16. Knowledge based system for control rod programming of BWRs

    International Nuclear Information System (INIS)

    Fukuzaki, Takaharu; Yoshida, Ken-ichi; Kobayashi, Yasuhiro

    1988-01-01

    A knowledge based system has been developed to support designers in control rod programming of BWRs. The programming searches through optimal control rod patterns to realize safe and effective burning of nuclear fuel. Knowledge of experienced designers plays the main role in minimizing the number of calculations by the core performance evaluation code. This code predicts power distibution and thermal margins of the nuclear fuel. This knowledge is transformed into 'if-then' type rules and subroutines, and is stored in a knowledge base of the knowledge based system. The system consists of working area, an inference engine and the knowledge base. The inference engine can detect those data which have to be regenerated, call those subroutine which control the user's interface and numerical computations, and store competitive sets of data in different parts of the working area. Using this system, control rod programming of a BWR plant was traced with about 500 rules and 150 subroutines. Both the generation of control rod patterns for the first calculation of the code and the modification of a control rod pattern to reflect the calculation were completed more effectively than in a conventional method. (author)

  17. INPO JTA application: developing a competency-based training program

    International Nuclear Information System (INIS)

    Patrick, P.W.

    1985-01-01

    Developing a competency-based training program requires the support of a strong curriculum development program. The major thrust of Arkansas Power and Light Company's competency-based curriculum development program is the identification of competencies using position task analysis data, panels, and INPO JTA data. Eight steps in the curriculum development approach provide the logic and rationale of the process: (1) establish competencies, (2) conduct competency verification, (3) develop competency tests, (4) develop curriculum, (5) develop instructional media, (6) validate curriculum and conduct field testing, (7) perform training effectiveness evaluation, and (8) revise the curriculum as needed. The processes describe how INPO JTA's and NRC procedures are cross-referenced to show that standards and requirements imposed or sanctioned by NRC and INPO are met. The competency-based approach to curriculum and training development eliminates the traditional scatterload approach to training and focuses on training to the competency. The primary benefits of competency-based training include accountability, minimal job training to meet job or position requirements, and a process to document an individual's job proficiency

  18. Research Based Science Education: An Exemplary Program for Broader Impacts

    Science.gov (United States)

    Walker, C. E.; Pompea, S. M.

    2016-12-01

    Broader impacts are most effective when standing on the shoulders of successful programs. The Research Based Science Education (RBSE) program was such a successful program and played a major role in activating effective opportunities beyond the scope of its program. NSF funded the National Optical Astronomy Observatory (NOAO) to oversee the project from 1996-2008. RBSE provided primarily high school teachers with on-site astronomy research experiences and their students with astronomy research projects that their teachers could explain with confidence. The goal of most student research projects is to inspire and motivate students to go into STEM fields. The authors of the original NSF proposal felt that for students to do research in the classroom, a foundational research experience for teachers must first be provided. The key components of the program consisted of 16 teachers/year on average; a 15-week distance learning course covering astronomy content, research, mentoring and leadership skills; a subsequent 10-day summer workshop with half the time on Kitt Peak on research-class telescopes; results presented on the 9th day; research brought back to the classroom; more on-site observing opportunities for students and teachers; data placed on-line to reach a wider audience; opportunities to submit research articles to the project's refereed journal; and travel for teachers (and the 3 teachers they each mentored) to a professional meeting. In 2004, leveraging on the well-established RBSE program, the NOAO/NASA Spitzer Space Telescope Research began. Between 2005 and 2008, metrics included 32 teachers (mostly from RBSE), 10 scientists, 15 Spitzer Director Discretionary proposals, 31 AAS presentations and many Intel ISEF winners. Under new funding in 2009, the NASA/IPAC Teacher Archive Research Program was born with similar goals and thankfully still runs today. Broader impacts, lessons learned and ideas for future projects will be discussed in this presentation.

  19. SIP: A Web-Based Astronomical Image Processing Program

    Science.gov (United States)

    Simonetti, J. H.

    1999-12-01

    I have written an astronomical image processing and analysis program designed to run over the internet in a Java-compatible web browser. The program, Sky Image Processor (SIP), is accessible at the SIP webpage (http://www.phys.vt.edu/SIP). Since nothing is installed on the user's machine, there is no need to download upgrades; the latest version of the program is always instantly available. Furthermore, the Java programming language is designed to work on any computer platform (any machine and operating system). The program could be used with students in web-based instruction or in a computer laboratory setting; it may also be of use in some research or outreach applications. While SIP is similar to other image processing programs, it is unique in some important respects. For example, SIP can load images from the user's machine or from the Web. An instructor can put images on a web server for students to load and analyze on their own personal computer. Or, the instructor can inform the students of images to load from any other web server. Furthermore, since SIP was written with students in mind, the philosophy is to present the user with the most basic tools necessary to process and analyze astronomical images. Images can be combined (by addition, subtraction, multiplication, or division), multiplied by a constant, smoothed, cropped, flipped, rotated, and so on. Statistics can be gathered for pixels within a box drawn by the user. Basic tools are available for gathering data from an image which can be used for performing simple differential photometry, or astrometry. Therefore, students can learn how astronomical image processing works. Since SIP is not part of a commercial CCD camera package, the program is written to handle the most common denominator image file, the FITS format.

  20. The Design of Model-Based Training Programs

    Science.gov (United States)

    Polson, Peter; Sherry, Lance; Feary, Michael; Palmer, Everett; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

    1997-01-01

    This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

  1. Core principles of evolutionary medicine

    Science.gov (United States)

    Grunspan, Daniel Z; Nesse, Randolph M; Barnes, M Elizabeth; Brownell, Sara E

    2018-01-01

    Abstract Background and objectives Evolutionary medicine is a rapidly growing field that uses the principles of evolutionary biology to better understand, prevent and treat disease, and that uses studies of disease to advance basic knowledge in evolutionary biology. Over-arching principles of evolutionary medicine have been described in publications, but our study is the first to systematically elicit core principles from a diverse panel of experts in evolutionary medicine. These principles should be useful to advance recent recommendations made by The Association of American Medical Colleges and the Howard Hughes Medical Institute to make evolutionary thinking a core competency for pre-medical education. Methodology The Delphi method was used to elicit and validate a list of core principles for evolutionary medicine. The study included four surveys administered in sequence to 56 expert panelists. The initial open-ended survey created a list of possible core principles; the three subsequent surveys winnowed the list and assessed the accuracy and importance of each principle. Results Fourteen core principles elicited at least 80% of the panelists to agree or strongly agree that they were important core principles for evolutionary medicine. These principles over-lapped with concepts discussed in other articles discussing key concepts in evolutionary medicine. Conclusions and implications This set of core principles will be helpful for researchers and instructors in evolutionary medicine. We recommend that evolutionary medicine instructors use the list of core principles to construct learning goals. Evolutionary medicine is a young field, so this list of core principles will likely change as the field develops further. PMID:29493660

  2. Practical advantages of evolutionary computation

    Science.gov (United States)

    Fogel, David B.

    1997-10-01

    Evolutionary computation is becoming a common technique for solving difficult, real-world problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as their ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.

  3. School-Based First Aid Training Programs: A Systematic Review.

    Science.gov (United States)

    Reveruzzi, Bianca; Buckley, Lisa; Sheehan, Mary

    2016-04-01

    This review examines the breadth of first aid training delivered to school students and the components that are age appropriate to adolescents. Eligible studies included school-based first aid interventions targeting students aged between 10 and 18 years. Online databases were searched, for peer-reviewed publications available as at August 2014. A total of 20 journal articles were relevant to the review. Research supported programs with longer durations (3 hours or more). Most programs taught resuscitation alone and few included content that was context-specific and relevant to the target group. The training experience of the facilitator did not appear to impact on student outcomes. Incorporating both practical and didactic components was found to be an important factor in delivering material and facilitating the retention of knowledge. Educational resources and facilitator training were found to be common features of effective programs. The review supports first aid in school curriculum and provides details of key components pertinent to design of school-based first aid programs. The findings suggest that first aid training may have benefits wider than the uptake and retention of knowledge and skills. There is a need for future research, particularly randomized controlled trials to aid in identifying best practice approaches. © 2016, American School Health Association.

  4. ANALISIS KESIAPAN PROGRAM STUDI DALAM PRODUCTION BASED EDUCATION: STUDI PADA PROGRAM STUDI D3 AKUNTANSI POLINES

    Directory of Open Access Journals (Sweden)

    Muhammad Noor Ardiansah

    2015-03-01

    Full Text Available There has been no clear studies to identify, verify and analyze readiness program resources in order to study the implementation of PBE resulted in initial position (existing point is not clear that the priority programs and activities that are carried out per year tend to be responsive and not directed priorities. These conditions resulted in analysis of resource readiness courses in the management of production-based learning pattern PBE draw conducted This study aims to identify and verify and analyze readiness resources management courses in the pattern of production based learning, particularly in the Accounting Studies Program. This research is expected to be used to increase the effectiveness of learning and vocational education to improve the quality and relevance of polytechnic graduates. Total score was 33 the existence of resources from the scale of 12-60. The average score is 2.75. The average score was shown the position of Prodi's resources have been used, but its role is unclear (repeatable tend to have clearly defined functions, communicated and documented (defined. Resources have been managed, monitored and evaluated well (managed are: curriculum resources, networking courses, lab facilities, ISO-based management. Resources have been used but not optimal role: resources module practice, the formulation of an internship, practice material / TA, the performance of IC-based lecturer

  5. ANALISIS KESIAPAN PROGRAM STUDI DALAM PRODUCTION BASED EDUCATION: STUDI PADA PROGRAM STUDI D3 AKUNTANSI POLINES

    Directory of Open Access Journals (Sweden)

    Muhammad Noor Ardiansah

    2014-06-01

    Full Text Available There has been no clear studies to identify, verify and analyze readiness program resources in order to study the implementation of PBE resulted in initial position (existing point is not clear that the priority programs and activities that are carried out per year tend to be responsive and not directed priorities. These conditions resulted in analysis of resource readiness courses in the management of production-based learning pattern PBE draw conducted This study aims to identify and verify and analyze readiness resources management courses in the pattern of production based learning, particularly in the Accounting Studies Program. This research is expected to be used to increase the effectiveness of learning and vocational education to improve the quality and relevance of polytechnic graduates. Total score was 33 the existence of resources from the scale of 12-60. The average score is 2.75. The average score was shown the position of Prodi's resources have been used, but its role is unclear (repeatable tend to have clearly defined functions, communicated and documented (defined. Resources have been managed, monitored and evaluated well (managed are: curriculum resources, networking courses, lab facilities, ISO-based management. Resources have been used but not optimal role: resources module practice, the formulation of an internship, practice material / TA, the performance of IC-based lecturer

  6. On Reciprocal Causation in the Evolutionary Process.

    Science.gov (United States)

    Svensson, Erik I

    2018-01-01

    Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause-effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist . Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach

  7. Evolutionary dynamics of incubation periods.

    Science.gov (United States)

    Ottino-Loffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

    2017-12-21

    The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.

  8. Markov Networks in Evolutionary Computation

    CERN Document Server

    Shakya, Siddhartha

    2012-01-01

    Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs).  EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current researc...

  9. An evolutionary framework for cultural change: Selectionism versus communal exchange

    Science.gov (United States)

    Gabora, Liane

    2013-06-01

    Dawkins' replicator-based conception of evolution has led to widespread mis-application of selectionism across the social sciences because it does not address the paradox that necessitated the theory of natural selection in the first place: how do organisms accumulate change when traits acquired over their lifetime are obliterated? This is addressed by von Neumann's concept of a self-replicating automaton (SRA). A SRA consists of a self-assembly code that is used in two distinct ways: (1) actively deciphered during development to construct a self-similar replicant, and (2) passively copied to the replicant to ensure that it can reproduce. Information that is acquired over a lifetime is not transmitted to offspring, whereas information that is inherited during copying is transmitted. In cultural evolution there is no mechanism for discarding acquired change. Acquired change can accumulate orders of magnitude faster than, and quickly overwhelm, inherited change due to differential replication of variants in response to selection. This prohibits a selectionist but not an evolutionary framework for culture and the creative processes that fuel it. The importance non-Darwinian processes in biological evolution is increasingly recognized. Recent work on the origin of life suggests that early life evolved through a non-Darwinian process referred to as communal exchange that does not involve a self-assembly code, and that natural selection emerged from this more haphazard, ancestral evolutionary process. It is proposed that communal exchange provides an evolutionary framework for culture that enables specification of cognitive features necessary for a (real or artificial) societies to evolve culture. This is supported by a computational model of cultural evolution and a conceptual network based program for documenting material cultural history, and it is consistent with high levels of human cooperation.

  10. A monitoring program of the histograms based on ROOT package

    International Nuclear Information System (INIS)

    Zhou Yongzhao; Liang Hao; Chen Yixin; Xue Jundong; Yang Tao; Gong Datao; Jin Ge; Yu Xiaoqi

    2002-01-01

    KHBOOK is a histogram monitor and browser based on ROOT package, which reads the histogram file in HBOOK format from Physmon, converts it into ROOT format, and browses the histograms in Repeat and Overlap modes to monitor and trace the quality of the data from DAQ. KHBOOK is a program of small memory, easy maintenance and fast running as well, using mono-behavior classes and a communication class of C ++

  11. Systems and methods for interpolation-based dynamic programming

    KAUST Repository

    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.

  12. Systems and methods for interpolation-based dynamic programming

    KAUST Repository

    Rockwood, Alyn

    2013-01-01

    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.

  13. Trauma Center Based Youth Violence Prevention Programs: An Integrative Review.

    Science.gov (United States)

    Mikhail, Judy Nanette; Nemeth, Lynne Sheri

    2016-12-01

    Youth violence recidivism remains a significant public health crisis in the United States. Violence prevention is a requirement of all trauma centers, yet little is known about the effectiveness of these programs. Therefore, this systematic review summarizes the effectiveness of trauma center-based youth violence prevention programs. A systematic review of articles from MEDLINE, CINAHL, and PsychINFO databases was performed to identify eligible control trials or observational studies. Included studies were from 1970 to 2013, describing and evaluating an intervention, were trauma center based, and targeted youth injured by violence (tertiary prevention). The social ecological model provided the guiding framework, and findings are summarized qualitatively. Ten studies met eligibility requirements. Case management and brief intervention were the primary strategies, and 90% of the studies showed some improvement in one or more outcome measures. These results held across both social ecological level and setting: both emergency department and inpatient unit settings. Brief intervention and case management are frequent and potentially effective trauma center-based violence prevention interventions. Case management initiated as an inpatient and continued beyond discharge was the most frequently used intervention and was associated with reduced rearrest or reinjury rates. Further research is needed, specifically longitudinal studies using experimental designs with high program fidelity incorporating uniform direct outcome measures. However, this review provides initial evidence that trauma centers can intervene with the highest of risk patients and break the youth violence recidivism cycle. © The Author(s) 2015.

  14. Nonlinear Knowledge in Kernel-Based Multiple Criteria Programming Classifier

    Science.gov (United States)

    Zhang, Dongling; Tian, Yingjie; Shi, Yong

    Kernel-based Multiple Criteria Linear Programming (KMCLP) model is used as classification methods, which can learn from training examples. Whereas, in traditional machine learning area, data sets are classified only by prior knowledge. Some works combine the above two classification principle to overcome the defaults of each approach. In this paper, we propose a model to incorporate the nonlinear knowledge into KMCLP in order to solve the problem when input consists of not only training example, but also nonlinear prior knowledge. In dealing with real world case breast cancer diagnosis, the model shows its better performance than the model solely based on training data.

  15. Recommendation System of Program Based on REST Style

    Directory of Open Access Journals (Sweden)

    Song Jin Bao

    2016-01-01

    Full Text Available With the popularity of digital TV, TV programs have been on the increase no matter in both the number and species, which brought many choice to the users. Although the digital TV has increased largely in the selectivity, it has become a fussy process that users search for programs which they are interested in. So there is need to have an efficient program recommendation system to solve the problem that is “information overload” for users. It can not only help users to get the program which they require, but also bring convenience to people’s life. The program recommendation system named MyView is planned and designed, aimed to providing an efficient information platform. The system also involves intelligent recommendation. The information guide will trigger the recommendation engine after users registering information, the engine will accord to the data in the guide information to make the personalized program recommendation. The system was deployed in the Tomcat and Apache integration servers on my localhost, so it also belongs to the Web application based on J2EE platform. AJAX is used that can achieve a good user experience to develop web presentation layer on MyView PC browser with flexible interface performance. The background of business services uses the hierarchical form. MyView System uses the CXF framework and Hibernate to equip controller and data persistence layer in the Spring container. The overall framework of the system uses the REST style, in order to extend the performance and function later. Background service layer with uniform interface, marked by the URI resource. At the same time, HTTP requestion is submitted by the AJAX to obtain services provided by resources. Finally, we can analyze and summary the features of MyView System.

  16. Outcomes in a Community-Based Intensive Cardiac Rehabilitation Program: Comparison with Hospital-Based and Academic Programs.

    Science.gov (United States)

    Katzenberg, Charles; Silva, Edna; Young, M Jean; Gilles, Greg

    2018-04-13

    The purpose of this study was to test the hypothesis that a community-based intensive cardiac rehabilitation program could produce positive changes in risk factor profile and outcomes in an at-risk population. Participants seeking either primary or secondary coronary artery disease prevention voluntarily enrolled in the 12-week intensive cardiac rehabilitation program. Data were obtained at baseline and 6-12 months after completion of the program. A total of 142 individuals, mean age 69 years, completed the Heart Series between 2012 and 2016. Follow-up data were available in 105 participants (74%). Participants showed statistically significant improvements in mean weight (165 to 162 lbs, P = .0005), body mass index (26 to 25 kg/m 2 , P = .001), systolic blood pressure (126 to 122 mm Hg, P = .01), diastolic blood pressure (73 to 70 mm Hg, P = .0005), total cholesterol (175 to 168 mg/dL, P = .03), low-density lipoprotein cholesterol (LDL-C) (100 to 93 mg/dL, P = .005), LDL-C/high-density lipoprotein cholesterol (HDL-C) ratio (1.8 to 1.6, P = .005), and cholesterol/HDL-C ratio (3.2 to 3.0, P = .003). Changes in HDL-C, triglycerides, and fasting blood glucose did not reach statistical significance, but all trended in favorable directions. Adverse cardiovascular disease outcomes were rare (one stent placement, no deaths). A total of 105 participants completed our 12-week community-based intensive cardiac rehabilitation program and showed significant positive changes in several measures of cardiac risk, with only 1 adverse event. These results compare favorably with those of hospital-based and academic institutional programs. Copyright © 2018 Elsevier Inc. All rights reserved.

  17. Complexity in Evolutionary Processes

    International Nuclear Information System (INIS)

    Schuster, P.

    2010-01-01

    Darwin's principle of evolution by natural selection is readily casted into a mathematical formalism. Molecular biology revealed the mechanism of mutation and provides the basis for a kinetic theory of evolution that models correct reproduction and mutation as parallel chemical reaction channels. A result of the kinetic theory is the existence of a phase transition in evolution occurring at a critical mutation rate, which represents a localization threshold for the population in sequence space. Occurrence and nature of such phase transitions depend critically on fitness landscapes. The fitness landscape being tantamount to a mapping from sequence or genotype space into phenotype space is identified as the true source of complexity in evolution. Modeling evolution as a stochastic process is discussed and neutrality with respect to selection is shown to provide a major challenge for understanding evolutionary processes (author)

  18. Spore: Spawning Evolutionary Misconceptions?

    Science.gov (United States)

    Bean, Thomas E.; Sinatra, Gale M.; Schrader, P. G.

    2010-10-01

    The use of computer simulations as educational tools may afford the means to develop understanding of evolution as a natural, emergent, and decentralized process. However, special consideration of developmental constraints on learning may be necessary when using these technologies. Specifically, the essentialist (biological forms possess an immutable essence), teleological (assignment of purpose to living things and/or parts of living things that may not be purposeful), and intentionality (assumption that events are caused by an intelligent agent) biases may be reinforced through the use of computer simulations, rather than addressed with instruction. We examine the video game Spore for its depiction of evolutionary content and its potential to reinforce these cognitive biases. In particular, we discuss three pedagogical strategies to mitigate weaknesses of Spore and other computer simulations: directly targeting misconceptions through refutational approaches, targeting specific principles of scientific inquiry, and directly addressing issues related to models as cognitive tools.

  19. Evolutionary games under incompetence.

    Science.gov (United States)

    Kleshnina, Maria; Filar, Jerzy A; Ejov, Vladimir; McKerral, Jody C

    2018-02-26

    The adaptation process of a species to a new environment is a significant area of study in biology. As part of natural selection, adaptation is a mutation process which improves survival skills and reproductive functions of species. Here, we investigate this process by combining the idea of incompetence with evolutionary game theory. In the sense of evolution, incompetence and training can be interpreted as a special learning process. With focus on the social side of the problem, we analyze the influence of incompetence on behavior of species. We introduce an incompetence parameter into a learning function in a single-population game and analyze its effect on the outcome of the replicator dynamics. Incompetence can change the outcome of the game and its dynamics, indicating its significance within what are inherently imperfect natural systems.

  20. Community-Based Global Health Program for Maltreated Children and Adolescents in Brazil: The Equilibrium Program

    Science.gov (United States)

    Marques, Andrea Horvath; Oliveira, Paula Approbato; Scomparini, Luciana Burim; Silva, Uiara Maria Rêgo e; Silva, Angelica Cristine; Doretto, Victoria; de Medeiros Filho, Mauro Victor; Scivoletto, Sandra

    2015-01-01

    The maltreatment of children and adolescents is a global public health problem that affects high- and low-middle income countries (“LMICs”). In the United States, around 1.2 million children suffer from abuse, while in LMICs, such as Brazil, these rates are much higher (an estimated 28 million children). Exposition to early environmental stress has been associated with suboptimal physical and brain development, persistent cognitive impairment, and behavioral problems. Studies have reported that children exposed to maltreatment are at high risk of behavioral problems, learning disabilities, communication and psychiatric disorders, and general clinical conditions, such as obesity and systemic inflammation later in life. The aim of this paper is to describe The Equilibrium Program (“TEP”), a community-based global health program implemented in São Paulo, Brazil to serve traumatized and neglected children and adolescents. We will describe and discuss TEP’s implementation, highlighting its innovation aspects, research projects developed within the program as well as its population profile. Finally, we will discuss TEP’s social impact, challenges, and limitations. The program’s goal is to promote the social and family reintegration of maltreated children and adolescents through an interdisciplinary intervention program that provides multi-dimensional bio-psycho-social treatment integrated with the diverse services needed to meet the unique demands of this population. The program’s cost effectiveness is being evaluated to support the development of more effective treatments and to expand similar programs in other areas of Brazil. Policy makers should encourage early evidence-based interventions for disadvantaged children to promote healthier psychosocial environments and provide them opportunities to become healthy and productive adults. This approach has already shown itself to be a cost-effective strategy to prevent disease and promote health. PMID

  1. Interactive, Computer-Based Training Program for Radiological Workers

    International Nuclear Information System (INIS)

    Trinoskey, P.A.; Camacho, P.I.; Wells, L.

    2000-01-01

    Lawrence Livermore National Laboratory (LLNL) is redesigning its Computer-Based Training (CBT) program for radiological workers. The redesign represents a major effort to produce a single, highly interactive and flexible CBT program that will meet the training needs of a wide range of radiological workers--from researchers and x-ray operators to individuals working in tritium, uranium, plutonium, and accelerator facilities. The new CBT program addresses the broad diversity of backgrounds found at a national laboratory. When a training audience is homogeneous in terms of education level and type of work performed, it is difficult to duplicate the effectiveness of a flexible, technically competent instructor who can tailor a course to the express needs and concerns of a course's participants. Unfortunately, such homogeneity is rare. At LLNL, they have a diverse workforce engaged in a wide range of radiological activities, from the fairly common to the quite exotic. As a result, the Laboratory must offer a wide variety of radiological worker courses. These include a general contamination-control course in addition to radioactive-material-handling courses for both low-level laboratory (i.e., bench-top) activities as well as high-level work in tritium, uranium, and plutonium facilities. They also offer training courses for employees who work with radiation-generating devices--x-ray, accelerator, and E-beam operators, for instance. However, even with the number and variety of courses the Laboratory offers, they are constrained by the diversity of backgrounds (i.e., knowledge and experience) of those to be trained. Moreover, time constraints often preclude in-depth coverage of site- and/or task-specific details. In response to this situation, several years ago LLNL began moving toward computer-based training for radiological workers. Today, that CBT effort includes a general radiological safety course developed by the Department of Energy's Hanford facility and a

  2. Interactive computer-based training program for radiological workers

    International Nuclear Information System (INIS)

    Trinoskey, P.A.; Camacho, P.I.; Wells, L.

    2000-01-01

    Lawrence Livermore National Laboratory is redesigning its existing Computer-Based Training (CBT) programs for radiological workers. The redesign represents a major effort that is aimed at producing a single highly interactive and flexible CBT program. The new CBT program is designed to address a variety of radiological workers, including researchers, x-ray operators, and individuals working in tritium, uranium, plutonium, and accelerator facilities. The program addresses the diversity of backgrounds found at a national laboratory. The CBT program includes photographs, line drawings and illustrations, sound, video, and simulations, and it allows for easy insertion and replacement of text, graphics, sound, and video. The new design supports timely updates and customization for use at other University of California sites. The CBT program is divided into ten basic modules. Introduction and Lessons Learned, History and Uses, Fundamentals, Background Radiation, Biological Effects of Radiation, Characteristics of Radionuclides, Radiological Controls, Monitoring, Emergency Response, Responsibilities. Some of the main modules features as many as seven or eight submodules. For example, the module on Characteristics of Radionuclides features submodules on common radionuclides, tritium uranium, plutonium, x-ray machines, E-beam devices, radiographic devices, and accelerators. Required submodules are tailored to an individual's type of work and facility, and they are determined by the answers to an onscreen questionnaire given at the outset of training. Individuals can challenge most individual modules, but certain submodules will be mandatory based on the initial survey. For example, individuals working in the uranium facility will be required to complete the submodule on 'History and Uses of Uranium'. However, all other submodules under the main module, 'History and Uses', will be available if selected for preview. For each module, an opportunity is provided for further

  3. Synthesis of logic circuits with evolutionary algorithms

    Energy Technology Data Exchange (ETDEWEB)

    JONES,JAKE S.; DAVIDSON,GEORGE S.

    2000-01-26

    In the last decade there has been interest and research in the area of designing circuits with genetic algorithms, evolutionary algorithms, and genetic programming. However, the ability to design circuits of the size and complexity required by modern engineering design problems, simply by specifying required outputs for given inputs has as yet eluded researchers. This paper describes current research in the area of designing logic circuits using an evolutionary algorithm. The goal of the research is to improve the effectiveness of this method and make it a practical aid for design engineers. A novel method of implementing the algorithm is introduced, and results are presented for various multiprocessing systems. In addition to evolving standard arithmetic circuits, work in the area of evolving circuits that perform digital signal processing tasks is described.

  4. Evolutionary economics and industry location

    NARCIS (Netherlands)

    Boschma, R.A.; Frenken, K.

    2003-01-01

    This paper aims to provide the outlines of an evolutionary economic geography of industry location. We discuss two evolutionary explanations of industry location, that is, one that concentrates on spin-offs, and one that focuses attention on knowledge and agglomeration economies. We claim that both

  5. Contemporary issues in evolutionary biology

    Indian Academy of Sciences (India)

    We are delighted to bring to the readers, a set of peer-reviewed papers on evolutionary biology, published as a special issue of the Journal of Genetics. These papers emanated from ruminations upon and discussions at the Foundations of. Evolutionary Theory: the Ongoing Synthesis meeting at Coorg, India, in February ...

  6. Fixation Time for Evolutionary Graphs

    Science.gov (United States)

    Nie, Pu-Yan; Zhang, Pei-Ai

    Evolutionary graph theory (EGT) is recently proposed by Lieberman et al. in 2005. EGT is successful for explaining biological evolution and some social phenomena. It is extremely important to consider the time of fixation for EGT in many practical problems, including evolutionary theory and the evolution of cooperation. This study characterizes the time to asymptotically reach fixation.

  7. Applications of evolutionary economic geography

    NARCIS (Netherlands)

    Boschma, R.A.; Frenken, K.; Puranam, Krishna Kishore; Ravi Kumar Jain B., xx

    2008-01-01

    This paper is written as the first chapter of an edited volume on evolutionary economics and economic geography (Frenken, K., editor, Applied Evolutionary Economics and Economic Geography, Cheltenham: Edward Elgar, expected publication date February 2007). The paper reviews empirical applications of

  8. Train Repathing in Emergencies Based on Fuzzy Linear Programming

    Directory of Open Access Journals (Sweden)

    Xuelei Meng

    2014-01-01

    Full Text Available Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

  9. Train repathing in emergencies based on fuzzy linear programming.

    Science.gov (United States)

    Meng, Xuelei; Cui, Bingmou

    2014-01-01

    Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.

  10. Differential Programming Needs of College Students Preferring Web-Based Versus In-Person Physical Activity Programs.

    Science.gov (United States)

    Goldstein, Stephanie P; Forman, Evan M; Butryn, Meghan L; Herbert, James D

    2017-09-21

    College students report several barriers to exercise, highlighting a need for university-based programs that address these challenges. In contrast to in-person interventions, several web-based programs have been developed to enhance program engagement by increasing ease of access and lowering the necessary level of commitment to participate. Unfortunately, web-based programs continue to struggle with engagement and less-than-ideal outcomes. One explanation for this discrepancy is that different intervention modalities may attract students with distinctive activity patterns, motivators, barriers, and program needs. However, no studies have formally evaluated intervention modality preference (e.g., web-based or in-person) among college students. The current study sought to examine the relationship between intervention modality preference and physical activity programming needs. Undergraduate students (n = 157) enrolled in psychology courses at an urban university were asked to complete an online survey regarding current activity patterns and physical activity program preferences. Participants preferring web-based physical activity programs exercised less (p = .05), were less confident in their abilities to exercise (p = .01), were less likely to endorse the maintenance stage of change (p web-based programming may require programs that enhance self-efficacy by fostering goal-setting and problem-solving skills. A user-centered design approach may enhance the engagement (and therefore effectiveness) of physical activity promotion programs for college students.

  11. Motivating programming students by Problem Based Learning and LEGO robots

    DEFF Research Database (Denmark)

    Lykke, Marianne; Coto Chotto, Mayela; Mora, Sonia

    2014-01-01

    . For this reason the school is focusing on different teaching methods to help their students master these skills. This paper introduces an experimental, controlled comparison study of three learning designs, involving a problem based learning (PBL) approach in connection with the use of LEGO Mindstorms to improve...... students programming skills and motivation for learning in an introductory programming course. The paper reports the results related with one of the components of the study - the experiential qualities of the three learning designs. The data were collected through a questionnaire survey with 229 students...... from three groups exposed to different learning designs and through six qualitative walk-alongs collecting data from these groups by informal interviews and observations. Findings from the three studies were discussed in three focus group interviews with 10 students from the three experimental groups....

  12. An iconic programming language for sensor-based robots

    Science.gov (United States)

    Gertz, Matthew; Stewart, David B.; Khosla, Pradeep K.

    1993-01-01

    In this paper we describe an iconic programming language called Onika for sensor-based robotic systems. Onika is both modular and reconfigurable and can be used with any system architecture and real-time operating system. Onika is also a multi-level programming environment wherein tasks are built by connecting a series of icons which, in turn, can be defined in terms of other icons at the lower levels. Expert users are also allowed to use control block form to define servo tasks. The icons in Onika are both shape and color coded, like the pieces of a jigsaw puzzle, thus providing a form of error control in the development of high level applications.

  13. A reference standard-based quality assurance program for radiology.

    Science.gov (United States)

    Liu, Patrick T; Johnson, C Daniel; Miranda, Rafael; Patel, Maitray D; Phillips, Carrie J

    2010-01-01

    The authors have developed a comprehensive radiology quality assurance (QA) program that evaluates radiology interpretations and procedures by comparing them with reference standards. Performance metrics are calculated and then compared with benchmarks or goals on the basis of published multicenter data and meta-analyses. Additional workload for physicians is kept to a minimum by having trained allied health staff members perform the comparisons of radiology reports with the reference standards. The performance metrics tracked by the QA program include the accuracy of CT colonography for detecting polyps, the false-negative rate for mammographic detection of breast cancer, the accuracy of CT angiography detection of coronary artery stenosis, the accuracy of meniscal tear detection on MRI, the accuracy of carotid artery stenosis detection on MR angiography, the accuracy of parathyroid adenoma detection by parathyroid scintigraphy, the success rate for obtaining cortical tissue on ultrasound-guided core biopsies of pelvic renal transplants, and the technical success rate for peripheral arterial angioplasty procedures. In contrast with peer-review programs, this reference standard-based QA program minimizes the possibilities of reviewer bias and erroneous second reviewer interpretations. The more objective assessment of performance afforded by the QA program will provide data that can easily be used for education and management conferences, research projects, and multicenter evaluations. Additionally, such performance data could be used by radiology departments to demonstrate their value over nonradiology competitors to referring clinicians, hospitals, patients, and third-party payers. Copyright 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  14. PERMUTATION-BASED POLYMORPHIC STEGO-WATERMARKS FOR PROGRAM CODES

    Directory of Open Access Journals (Sweden)

    Denys Samoilenko

    2016-06-01

    Full Text Available Purpose: One of the most actual trends in program code protection is code marking. The problem consists in creation of some digital “watermarks” which allow distinguishing different copies of the same program codes. Such marks could be useful for authority protection, for code copies numbering, for program propagation monitoring, for information security proposes in client-server communication processes. Methods: We used the methods of digital steganography adopted for program codes as text objects. The same-shape symbols method was transformed to same-semantic element method due to codes features which makes them different from ordinary texts. We use dynamic principle of marks forming making codes similar to be polymorphic. Results: We examined the combinatorial capacity of permutations possible in program codes. As a result it was shown that the set of 5-7 polymorphic variables is suitable for the most modern network applications. Marks creation and restoration algorithms where proposed and discussed. The main algorithm is based on full and partial permutations in variables names and its declaration order. Algorithm for partial permutation enumeration was optimized for calculation complexity. PHP code fragments which realize the algorithms were listed. Discussion: Methodic proposed in the work allows distinguishing of each client-server connection. In a case if a clone of some network resource was found the methodic could give information about included marks and thereby data on IP, date and time, authentication information of client copied the resource. Usage of polymorphic stego-watermarks should improve information security indexes in network communications.

  15. A Randomised Controlled Trial of Two Early Intervention Programs for Young Children with Autism: Centre-Based with Parent Program and Home-Based

    Science.gov (United States)

    Roberts, Jacqueline; Williams, Katrina; Carter, Mark; Evans, David; Parmenter, Trevor; Silove, Natalie; Clark, Trevor; Warren, Anthony

    2011-01-01

    This study compares outcomes of early intervention programs for young children with autism; an individualised home-based program (HB), a small group centre-based program for children combined with a parent training and support group (CB) and a non-treatment comparison group (WL). Outcome measures of interest include social and communication skill…

  16. BEAST: Bayesian evolutionary analysis by sampling trees

    Directory of Open Access Journals (Sweden)

    Drummond Alexei J

    2007-11-01

    Full Text Available Abstract Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.

  17. Evolutionary rate variation and RNA secondary structure prediction

    DEFF Research Database (Denmark)

    Knudsen, B.; Andersen, E.S.; Damgaard, C.

    2004-01-01

    Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type...... by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions...

  18. The SUPER Program: A Research-based Undergraduate Experience

    Science.gov (United States)

    Ernakovich, J. G.; Boone, R. B.; Boot, C. M.; Denef, K.; Lavallee, J. M.; Moore, J. C.; Wallenstein, M. D.

    2014-12-01

    Producing undergraduates capable of broad, independent thinking is one of the grand challenges in science education. Experience-based learning, specifically hands-on research, is one mechanism for increasing students' ability to think critically. With this in mind, we created a two-semester long research program called SUPER (Skills for Undergraduate Participation in Ecological Research) aimed at teaching students to think like scientists and enhancing the student research experience through instruction and active-learning about the scientific method. Our aim was for students to gain knowledge, skills, and experience, and to conduct their own research. In the first semester, we hosted active-learning workshops on "Forming Hypotheses", "Experimental Design", "Collecting and Managing Data", "Analysis of Data", "Communicating to a Scientific Audience", "Reading Literature Effectively", and "Ethical Approaches". Each lesson was taught by different scientists from one of many ecological disciplines so that students were exposed to the variation in approach that scientists have. In the second semester, students paired with a scientific mentor and began doing research. To ensure the continued growth of the undergraduate researcher, we continued the active-learning workshops and the students attended meetings with their mentors. Thus, the students gained technical and cognitive skills in parallel, enabling them to understand both "the how" and "the why" of what they were doing in their research. The program culminated with a research poster session presented by the students. The interest in the program has grown beyond our expectations, and we have now run the program successfully for two years. Many of the students have gone on to campus research jobs, internships and graduate school, and have attributed part of their success in obtaining their positions to their experience with the SUPER program. Although common in other sciences, undergraduate research experiences are

  19. Food Safety Programs Based on HACCP Principles in School Nutrition Programs: Implementation Status and Factors Related to Implementation

    Science.gov (United States)

    Stinson, Wendy Bounds; Carr, Deborah; Nettles, Mary Frances; Johnson, James T.

    2011-01-01

    Purpose/Objectives: The objectives of this study were to assess the extent to which school nutrition (SN) programs have implemented food safety programs based on Hazard Analysis and Critical Control Point (HACCP) principles, as well as factors, barriers, and practices related to implementation of these programs. Methods: An online survey was…

  20. Unifying Model-Based and Reactive Programming within a Model-Based Executive

    Science.gov (United States)

    Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

    1999-01-01

    Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

  1. The Resilience Program: Preliminary evaluation of a mentalization-based education program.

    Directory of Open Access Journals (Sweden)

    Poul Lundgaard Bak

    2015-06-01

    Full Text Available In order to manage with the burden of mental health problems in the world we need to develop cost-effective and safe preventive interventions. Education about resilience to support the ability to cope with life challenges in general, may be a useful strategy. We consider the concepts of Theory of Mind and Mentalization to be relevant in this context. In this paper we describe a simple modular intervention program based on these concepts which can be tailored to specific needs and situations in individual therapy as well as group levels. The program has shown promising results in pilot studies and is now tested in controlled trials in settings such as schools and educational institutions, adults diagnosed with ADHD and children in foster care.

  2. Marine Dispersal Scales Are Congruent over Evolutionary and Ecological Time

    KAUST Repository

    Pinsky, Malin L.; Saenz-Agudelo, Pablo; Salles, Océ ane C.; Almany, Glenn R.; Bode, Michael; Berumen, Michael L.; André fouë t, Serge; Thorrold, Simon R.; Jones, Geoffrey P.; Planes, Serge

    2016-01-01

    -distance dispersal are based on direct ecological observations of dispersing individuals, while indirect evolutionary estimates often suggest substantially greater homogeneity among populations. Reconciling these two approaches and their seemingly competing

  3. Accountability for Community-Based Programs for the Seriously Ill.

    Science.gov (United States)

    Teno, Joan M; Montgomery, Russ; Valuck, Tom; Corrigan, Janet; Meier, Diane E; Kelley, Amy; Curtis, J Randall; Engelberg, Ruth

    2018-03-01

    Innovation is needed to improve care of the seriously ill, and there are important opportunities as we transition from a volume- to value-based payment system. Not all seriously ill are dying; some recover, while others are persistently functionally impaired. While we innovate in service delivery and payment models for the seriously ill, it is important that we concurrently develop accountability that ensures a focus on high-quality care rather than narrowly focusing on cost containment. The Gordon and Betty Moore Foundation convened a meeting of 45 experts to arrive at guiding principles for measurement, create a starter measurement set, specify a proposed definition of the denominator and its refinement, and identify research priorities for future implementation of the accountability system. A series of articles written by experts provided the basis for debate and guidance in formulating a path forward to develop an accountability system for community-based programs for the seriously ill, outlined in this article. As we innovate in existing population-based payment programs such as Medicare Advantage and develop new alternative payment models, it is important and urgent that we develop the foundation for accountability along with actionable measures so that the healthcare system ensures high-quality person- and family-centered care for persons who are seriously ill.

  4. Gamma ray shielding: a web based interactive program

    International Nuclear Information System (INIS)

    Subbaiah, K.V.; Senthi Kumar, C.; Sarangapani, R.

    2005-01-01

    A web based interactive computing program is developed using java for quick assessment of Gamma Ray shielding problems. The program addresses usually encountered source geometries like POINT, LINE, CYLINDRICAL, ANNULAR, SPHERICAL, BOX, followed by 'SLAB' shield configurations. The calculation is based on point kernel technique. The source points are randomly sampled within the source volume. From each source point, optical path traversed in the source and shield media up to the detector location is estimated to calculate geometrical and material attenuations, and then corresponding buildup factor is obtained, which accounts for scattered contribution. Finally, the dose rate for entire source is obtained by summing over all sampled points. The application allows the user to select one of the seven regular geometrical bodies and provision exist to give source details such as emission energies, intensities, physical dimensions and material composition. Similar provision is provided to specify shield slab details. To aid the user, atomic numbers, densities, standard build factor materials and isotope list with respective emission energies and intensity for ready reference are given in dropdown combo boxes. Typical results obtained from this program are validated against existing point kernel gamma ray shielding codes. Additional facility is provided to compute fission product gamma ray source strengths based on the fuel type, burn up and cooling time. Plots of Fission product gamma ray source strengths, Gamma ray cross-sections and buildup factors can be optionally obtained, which enable the user to draw inference on the computed results. It is expected that this tool will be handy to all health physicists and radiological safety officers as it will be available on the internet. (author)

  5. Energy Economic Data Base (EEDB) Program. Technical Reference Book

    International Nuclear Information System (INIS)

    Allen, R.E.; Benedict, R.G.; Hodson, J.S.

    1983-09-01

    Purpose of the program is to develop current technical and cost information for nuclear and comparison electric power generating stations. Purpose of this Technical Reference Book is to provide the current technical design bases for each of the technical data models updated in the Sixth Update (1983). It contains a set of detailed system design descriptions for these technical data models, which are supplemented with engineering drawings. The system design descriptions reflect regulatory and industry practice and experience for nuclear and coal-fired power generating stations that are current for January 1, 1983

  6. Awareness programs and change in taste-based caste prejudice

    DEFF Research Database (Denmark)

    Banerjee, Ritwik; Datta Gupta, Nabanita

    ) in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find......Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Becker (1971...

  7. Where Evolutionary Psychology Meets Cognitive Neuroscience: A Précis to Evolutionary Cognitive Neuroscience1

    Directory of Open Access Journals (Sweden)

    Austen L. Krill

    2007-01-01

    Full Text Available Cognitive neuroscience, the study of brain-behavior relationships, has long attempted to map the brain. The discipline is flourishing, with an increasing number of functional neuroimaging studies appearing in the scientific literature daily. Unlike biology and even psychology, the cognitive neurosciences have only recently begun to apply evolutionary meta-theory and methodological guidance. Approaching cognitive neuroscience from an evolutionary perspective allows scientists to apply biologically based theoretical guidance to their investigations and can be conducted in both humans and nonhuman animals. In fact, several investigations of this sort are underway in laboratories around the world. This paper and two new volumes (Platek, Keenan, and Shackelford [Eds.], 2007; Platek and Shackelford [Eds.], under contract represent the first formal attempts to document the burgeoning field of evolutionary cognitive neuroscience. Here, we briefly review the current state of the science of evolutionary cognitive neuroscience, the methods available to the evolutionary cognitive neuroscientist, and what we foresee as the future directions of the discipline.

  8. Probabilistic dual heuristic programming-based adaptive critic

    Science.gov (United States)

    Herzallah, Randa

    2010-02-01

    Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.

  9. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    Science.gov (United States)

    Xiang, Lin

    incomplete and many relationships among the model ideas had not been well established by the end of the study. Most of them did not treat the natural selection model as a whole but only focused on some ideas within the model. Very few of them could scientifically apply the natural selection model to interpret other evolutionary phenomena. The findings about participating students' programming processes revealed these processes were composed of consecutive programming cycles. The cycle typically included posing a task, constructing and running program codes, and examining the resulting simulation. Students held multiple ideas and applied various programming strategies in these cycles. Students were involved in MBI at each step of a cycle. Three types of ideas, six programming strategies and ten MBI actions were identified out of the processes. The relationships among these ideas, strategies and actions were also identified and described. Findings suggested that ABPM activities could support MBI by (1) exposing students' personal models and understandings, (2) provoking and supporting a series of model-based inquiry activities, such as elaborating target phenomena, abstracting patterns, and revising conceptual models, and (3) provoking and supporting tangible and productive conversations among students, as well as between the instructor and students. Findings also revealed three programming behaviors that appeared to impede productive MBI, including (1) solely phenomenon-orientated programming, (2) transplanting program codes, and (3) blindly running procedures. Based on the findings, I propose a general modeling process in ABPM activities, summarize the ways in which MBI can be supported in ABPM activities and constrained by multiple factors, and suggest the implications of this study in the future ABPM-assisted science instructional design and research.

  10. Verification and Planning Based on Coinductive Logic Programming

    Science.gov (United States)

    Bansal, Ajay; Min, Richard; Simon, Luke; Mallya, Ajay; Gupta, Gopal

    2008-01-01

    Coinduction is a powerful technique for reasoning about unfounded sets, unbounded structures, infinite automata, and interactive computations [6]. Where induction corresponds to least fixed point's semantics, coinduction corresponds to greatest fixed point semantics. Recently coinduction has been incorporated into logic programming and an elegant operational semantics developed for it [11, 12]. This operational semantics is the greatest fix point counterpart of SLD resolution (SLD resolution imparts operational semantics to least fix point based computations) and is termed co- SLD resolution. In co-SLD resolution, a predicate goal p( t) succeeds if it unifies with one of its ancestor calls. In addition, rational infinite terms are allowed as arguments of predicates. Infinite terms are represented as solutions to unification equations and the occurs check is omitted during the unification process. Coinductive Logic Programming (Co-LP) and Co-SLD resolution can be used to elegantly perform model checking and planning. A combined SLD and Co-SLD resolution based LP system forms the common basis for planning, scheduling, verification, model checking, and constraint solving [9, 4]. This is achieved by amalgamating SLD resolution, co-SLD resolution, and constraint logic programming [13] in a single logic programming system. Given that parallelism in logic programs can be implicitly exploited [8], complex, compute-intensive applications (planning, scheduling, model checking, etc.) can be executed in parallel on multi-core machines. Parallel execution can result in speed-ups as well as in larger instances of the problems being solved. In the remainder we elaborate on (i) how planning can be elegantly and efficiently performed under real-time constraints, (ii) how real-time systems can be elegantly and efficiently model- checked, as well as (iii) how hybrid systems can be verified in a combined system with both co-SLD and SLD resolution. Implementations of co-SLD resolution

  11. Chemical evolutionary games.

    Science.gov (United States)

    Aristotelous, Andreas C; Durrett, Richard

    2014-05-01

    Inspired by the use of hybrid cellular automata in modeling cancer, we introduce a generalization of evolutionary games in which cells produce and absorb chemicals, and the chemical concentrations dictate the death rates of cells and their fitnesses. Our long term aim is to understand how the details of the interactions in a system with n species and m chemicals translate into the qualitative behavior of the system. Here, we study two simple 2×2 games with two chemicals and revisit the two and three species versions of the one chemical colicin system studied earlier by Durrett and Levin (1997). We find that in the 2×2 examples, the behavior of our new spatial model can be predicted from that of the mean field differential equation using ideas of Durrett and Levin (1994). However, in the three species colicin model, the system with diffusion does not have the coexistence which occurs in the lattices model in which sites interact with only their nearest neighbors. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Evolutionary and developmental modules.

    Science.gov (United States)

    Lacquaniti, Francesco; Ivanenko, Yuri P; d'Avella, Andrea; Zelik, Karl E; Zago, Myrka

    2013-01-01

    The identification of biological modules at the systems level often follows top-down decomposition of a task goal, or bottom-up decomposition of multidimensional data arrays into basic elements or patterns representing shared features. These approaches traditionally have been applied to mature, fully developed systems. Here we review some results from two other perspectives on modularity, namely the developmental and evolutionary perspective. There is growing evidence that modular units of development were highly preserved and recombined during evolution. We first consider a few examples of modules well identifiable from morphology. Next we consider the more difficult issue of identifying functional developmental modules. We dwell especially on modular control of locomotion to argue that the building blocks used to construct different locomotor behaviors are similar across several animal species, presumably related to ancestral neural networks of command. A recurrent theme from comparative studies is that the developmental addition of new premotor modules underlies the postnatal acquisition and refinement of several different motor behaviors in vertebrates.

  13. The four cornerstones of Evolutionary Toxicology.

    Science.gov (United States)

    Bickham, John W

    2011-05-01

    Evolutionary Toxicology is the study of the effects of chemical pollutants on the genetics of natural populations. Research in Evolutionary Toxicology uses experimental designs familiar to the ecotoxicologist with matched reference and contaminated sites and the selection of sentinel species. It uses the methods of molecular genetics and population genetics, and is based on the theories and concepts of evolutionary biology and conservation genetics. Although it is a relatively young field, interest is rapidly growing among ecotoxicologists and more and more field studies and even controlled laboratory experiments are appearing in the literature. A number of population genetic impacts have been observed in organisms exposed to pollutants which I refer to here as the four cornerstones of Evolutionary Toxicology. These include (1) genome-wide changes in genetic diversity, (2) changes in allelic or genotypic frequencies caused by contaminant-induced selection acting at survivorship loci, (3) changes in dispersal patterns or gene flow which alter the genetic relationships among populations, and (4) changes in allelic or genotypic frequencies caused by increased mutation rates. It is concluded that population genetic impacts of pollution exposure are emergent effects that are not necessarily predictable from the mode of toxicity of the pollutant. Thus, to attribute an effect to a particular contaminant requires a careful experimental design which includes selection of appropriate reference sites, detailed chemistry analyses of environmental samples and tissues, and the use of appropriate biomarkers to establish exposure and effect. This paper describes the field of Evolutionary Toxicology and discusses relevant field studies and their findings. © Springer Science+Business Media, LLC 2011

  14. Team sponsors in community-based health leadership programs.

    Science.gov (United States)

    Patterson, Tracy Enright; Dinkin, Donna R; Champion, Heather

    2017-05-02

    Purpose The purpose of this article is to share the lessons learned about the role of team sponsors in action-learning teams as part of community-based health leadership development programs. Design/methodology/approach This case study uses program survey results from fellow participants, action learning coaches and team sponsors to understand the value of sponsors to the teams, the roles they most often filled and the challenges they faced as team sponsors. Findings The extent to which the sponsors were perceived as having contributed to the work of the action learning teams varied greatly from team to team. Most sponsors agreed that they were well informed about their role. The roles sponsors most frequently played were to provide the teams with input and support, serve as a liaison to the community and serve as a sounding board, motivator and cheerleader. The most common challenges or barriers team sponsors faced in this role were keeping engaged in the process, adjusting to the role and feeling disconnected from the program. Practical implications This work provides insights for program developers and community foundations who are interested in building the capacity for health leadership by linking community sponsors with emerging leaders engaged in an action learning experience. Originality/value This work begins to fill a gap in the literature. The role of team sponsors has been studied for single organization work teams but there is a void of understanding about the role of sponsors with multi-organizational teams working to improve health while also learning about leadership.

  15. Conceptual bases of Christian, faith-based substance abuse rehabilitation programs: qualitative analysis of staff interviews.

    Science.gov (United States)

    McCoy, Lisa K; Hermos, John A; Bokhour, Barbara G; Frayne, Susan M

    2004-09-01

    Faith-based substance abuse rehabilitation programs provide residential treatment for many substance abusers. To determine key governing concepts of such programs, we conducted semi-structured interviews with sample of eleven clinical and administrative staff referred to us by program directors at six, Evangelical Christian, faith-based, residential rehabilitation programs representing two large, nationwide networks. Qualitative analysis using grounded theory methods examined how spirituality is incorporated into treatment and elicited key theories of addiction and recovery. Although containing comprehensive secular components, the core activities are strongly rooted in a Christian belief system that informs their understanding of addiction and recovery and drives the treatment format. These governing conceptions, that addiction stems from attempts to fill a spiritual void through substance use and recovery through salvation and a long-term relationship with God, provide an explicit, theory-driven model upon which they base their core treatment activities. Knowledge of these core concepts and practices should be helpful to clinicians in considering referrals to faith-based recovery programs.

  16. Industrial Applications of Evolutionary Algorithms

    CERN Document Server

    Sanchez, Ernesto; Tonda, Alberto

    2012-01-01

    This book is intended as a reference both for experienced users of evolutionary algorithms and for researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, and advice on solving issues related to fitness computation, modeling and setting appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of all evolutionary algorithms exploited to solve different problems. The book could fill the gap between the

  17. Awareness Programs and Change in Taste-based Caste Prejudice

    DEFF Research Database (Denmark)

    Banerjee, Ritwik; Gupta, Nabanita Datta

    2015-01-01

    Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker...... in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste...... and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution - the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit...

  18. Awareness programs and change in taste-based caste prejudice.

    Directory of Open Access Journals (Sweden)

    Ritwik Banerjee

    Full Text Available Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution--the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste.

  19. Awareness programs and change in taste-based caste prejudice.

    Science.gov (United States)

    Banerjee, Ritwik; Datta Gupta, Nabanita

    2015-01-01

    Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution--the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste.

  20. An academic program for experience-based seismic evaluation

    International Nuclear Information System (INIS)

    Nix, S.J.; Meyer, W.; Clemence, S.P.

    1990-01-01

    The authors have been involved in a project, sponsored by the Niagara Mohawk Power Corporation, to develop knowledge-based expert systems to aid in the implementation of the Seismic Qualification Utility Group (SQUG) approach for the seismic qualification of equipment in operating nuclear power plants. This approach, being founded on the use of engineering judgment in the application of prior earthquake experience data, requires comprehensive training. There seems to be general consensus that the experience-based approach is a more cost-effective means of qualifying nuclear power plant equipment when compared to the more traditional analytical methods. The experience-based approach has a number of potential applications in civil engineering, including bridge evaluation and design, seismic adequacy of general structures, foundation design, and water and wastewater treatment plant design and operation. The objective of this paper is to outline an academic curriculum, at the master's level, to educate structural engineers to use and further develop the experience-based approach for seismic evaluation. In the long term, this could lead to the development of academic programs in experience-based assessment and design for a wide range of applications in maintaining the nation's infrastructure

  1. An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Yushan Zhang

    2015-01-01

    Full Text Available Although there have been many studies on the runtime of evolutionary algorithms in discrete optimization, relatively few theoretical results have been proposed on continuous optimization, such as evolutionary programming (EP. This paper proposes an analysis of the runtime of two EP algorithms based on Gaussian and Cauchy mutations, using an absorbing Markov chain. Given a constant variation, we calculate the runtime upper bound of special Gaussian mutation EP and Cauchy mutation EP. Our analysis reveals that the upper bounds are impacted by individual number, problem dimension number n, searching range, and the Lebesgue measure of the optimal neighborhood. Furthermore, we provide conditions whereby the average runtime of the considered EP can be no more than a polynomial of n. The condition is that the Lebesgue measure of the optimal neighborhood is larger than a combinatorial calculation of an exponential and the given polynomial of n.

  2. Evolutionary Medicine: The Ongoing Evolution of Human Physiology and Metabolism.

    Science.gov (United States)

    Rühli, Frank; van Schaik, Katherine; Henneberg, Maciej

    2016-11-01

    The field of evolutionary medicine uses evolutionary principles to understand changes in human anatomy and physiology that have occurred over time in response to environmental changes. Through this evolutionary-based approach, we can understand disease as a consequence of anatomical and physiological "trade-offs" that develop to facilitate survival and reproduction. We demonstrate how diachronic study of human anatomy and physiology is fundamental for an increased understanding of human health and disease. ©2016 Int. Union Physiol. Sci./Am. Physiol. Soc.

  3. Evolutionary disarmament in interspecific competition.

    Science.gov (United States)

    Kisdi, E; Geritz, S A

    2001-12-22

    Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races.

  4. Evolutionary computation for reinforcement learning

    NARCIS (Netherlands)

    Whiteson, S.; Wiering, M.; van Otterlo, M.

    2012-01-01

    Algorithms for evolutionary computation, which simulate the process of natural selection to solve optimization problems, are an effective tool for discovering high-performing reinforcement-learning policies. Because they can automatically find good representations, handle continuous action spaces,

  5. Evolutionary genetics: the Drosophila model

    Indian Academy of Sciences (India)

    Unknown

    Evolutionary genetics straddles the two fundamental processes of life, ... of the genus Drosophila have been used extensively as model systems in experimental ... issue will prove interesting, informative and thought-provoking for both estab-.

  6. Integrating genomics into evolutionary medicine.

    Science.gov (United States)

    Rodríguez, Juan Antonio; Marigorta, Urko M; Navarro, Arcadi

    2014-12-01

    The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Evolutionary robotics – A review

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    a need for a technique by which the robot is able to acquire new behaviours automatically .... Evolutionary robotics is a comparatively new field of robotics research, which seems to ..... Technical Report: PCIA-94-04, Institute of Psychology,.

  8. Evolutionary Game Theory: A Renaissance

    Directory of Open Access Journals (Sweden)

    Jonathan Newton

    2018-05-01

    Full Text Available Economic agents are not always rational or farsighted and can make decisions according to simple behavioral rules that vary according to situation and can be studied using the tools of evolutionary game theory. Furthermore, such behavioral rules are themselves subject to evolutionary forces. Paying particular attention to the work of young researchers, this essay surveys the progress made over the last decade towards understanding these phenomena, and discusses open research topics of importance to economics and the broader social sciences.

  9. Freud: the first evolutionary psychologist?

    Science.gov (United States)

    LeCroy, D

    2000-04-01

    An evolutionary perspective on attachment theory and psychoanalytic theory brings these two fields together in interesting ways. Application of the evolutionary principle of parent-offspring conflict to attachment theory suggests that attachment styles represent context-sensitive, evolved (adaptive) behaviors. In addition, an emphasis on offspring counter-strategies to adult reproductive strategies leads to consideration of attachment styles as overt manifestations of psychodynamic mediating processes, including the defense mechanisms of repression and reaction formation.

  10. An evolutionary cascade model for sauropod dinosaur gigantism--overview, update and tests.

    Directory of Open Access Journals (Sweden)

    P Martin Sander

    Full Text Available Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM. This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades ("Reproduction", "Feeding", "Head and neck", "Avian-style lung", and "Metabolism". Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait "Very high body mass". Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size.

  11. An Evolutionary Cascade Model for Sauropod Dinosaur Gigantism - Overview, Update and Tests

    Science.gov (United States)

    Sander, P. Martin

    2013-01-01

    Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades (“Reproduction”, “Feeding”, “Head and neck”, “Avian-style lung”, and “Metabolism”). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait “Very high body mass”. Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size. PMID:24205267

  12. An evolutionary cascade model for sauropod dinosaur gigantism--overview, update and tests.

    Science.gov (United States)

    Sander, P Martin

    2013-01-01

    Sauropod dinosaurs are a group of herbivorous dinosaurs which exceeded all other terrestrial vertebrates in mean and maximal body size. Sauropod dinosaurs were also the most successful and long-lived herbivorous tetrapod clade, but no abiological factors such as global environmental parameters conducive to their gigantism can be identified. These facts justify major efforts by evolutionary biologists and paleontologists to understand sauropods as living animals and to explain their evolutionary success and uniquely gigantic body size. Contributions to this research program have come from many fields and can be synthesized into a biological evolutionary cascade model of sauropod dinosaur gigantism (sauropod gigantism ECM). This review focuses on the sauropod gigantism ECM, providing an updated version based on the contributions to the PLoS ONE sauropod gigantism collection and on other very recent published evidence. The model consist of five separate evolutionary cascades ("Reproduction", "Feeding", "Head and neck", "Avian-style lung", and "Metabolism"). Each cascade starts with observed or inferred basal traits that either may be plesiomorphic or derived at the level of Sauropoda. Each trait confers hypothetical selective advantages which permit the evolution of the next trait. Feedback loops in the ECM consist of selective advantages originating from traits higher in the cascades but affecting lower traits. All cascades end in the trait "Very high body mass". Each cascade is linked to at least one other cascade. Important plesiomorphic traits of sauropod dinosaurs that entered the model were ovipary as well as no mastication of food. Important evolutionary innovations (derived traits) were an avian-style respiratory system and an elevated basal metabolic rate. Comparison with other tetrapod lineages identifies factors limiting body size.

  13. Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

    Science.gov (United States)

    Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

    2014-01-16

    To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high

  14. The evolutionary rate dynamically tracks changes in HIV-1 epidemics

    Energy Technology Data Exchange (ETDEWEB)

    Maljkovic-berry, Irina [Los Alamos National Laboratory; Athreya, Gayathri [Los Alamos National Laboratory; Daniels, Marcus [Los Alamos National Laboratory; Bruno, William [Los Alamos National Laboratory; Korber, Bette [Los Alamos National Laboratory; Kuiken, Carla [Los Alamos National Laboratory; Ribeiro, Ruy M [Los Alamos National Laboratory

    2009-01-01

    Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.

  15. Efficient classification of complete parameter regions based on semidefinite programming

    Directory of Open Access Journals (Sweden)

    Parrilo Pablo A

    2007-01-01

    Full Text Available Abstract Background Current approaches to parameter estimation are often inappropriate or inconvenient for the modelling of complex biological systems. For systems described by nonlinear equations, the conventional approach is to first numerically integrate the model, and then, in a second a posteriori step, check for consistency with experimental constraints. Hence, only single parameter sets can be considered at a time. Consequently, it is impossible to conclude that the "best" solution was identified or that no good solution exists, because parameter spaces typically cannot be explored in a reasonable amount of time. Results We introduce a novel approach based on semidefinite programming to directly identify consistent steady state concentrations for systems consisting of mass action kinetics, i.e., polynomial equations and inequality constraints. The duality properties of semidefinite programming allow to rigorously certify infeasibility for whole regions of parameter space, thus enabling the simultaneous multi-dimensional analysis of entire parameter sets. Conclusion Our algorithm reduces the computational effort of parameter estimation by several orders of magnitude, as illustrated through conceptual sample problems. Of particular relevance for systems biology, the approach can discriminate between structurally different candidate models by proving inconsistency with the available data.

  16. Discovery of Boolean metabolic networks: integer linear programming based approach.

    Science.gov (United States)

    Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

    2018-04-11

    Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".

  17. A community-based program evaluation of community competency trainings.

    Science.gov (United States)

    Hanssmann, Christoph; Morrison, Darius; Russian, Ellery; Shiu-Thornton, Sharyne; Bowen, Deborah

    2010-01-01

    Transgender and gender-nonconforming individuals encounter a multitude of barriers to accessing clinically and culturally competent health care. One strategy to increase the quality and competence of care delivery is workplace trainings. This study describes a community-based program for the evaluation of this type of training. Using a mixed-methods approach, the research team assessed the effectiveness of three competency trainings administered by a local nonprofit organization in the Northwest United States. Quantitative data indicated a significant shift in self-assessed knowledge associated with completion of the training. Qualitative data confirmed this result and revealed a number of important themes about the effect of the trainings on providers and their ability to implement knowledge and skills in practice. Clinical considerations are proposed for providers who seek similar trainings and who aim to increase clinical and cultural competency in delivering care to transgender and gender-nonconforming patients and clients.

  18. DEMO development strategy based on China FPP program

    International Nuclear Information System (INIS)

    Pan Chuanhong; Feng, K.M.; Wu, W.C.; Liu, S.L.

    2007-01-01

    The DEMO in China is to demonstrate the safety, reliability and environment feasibility of the fusion power plants, while to demonstrate the prospective economic feasibility of the commercial fusion power plants. Considering that there is still a long way to go towards an economically competitive commercial power plant, DEMO in China should be an indispensable step prior to the commercial one. Two options of breeding blanket with ceramic and lead lithium breeders might be chosen as DEMO concepts under the conditions of meeting the requirement of the neutronics, thermal-hydraulics and mechanics aspects. The DEMO development strategy, related R and D activities, based on China fusion power plant (FPP) program are presented. (orig.)

  19. Model-Based Systems Engineering Pilot Program at NASA Langley

    Science.gov (United States)

    Vipavetz, Kevin G.; Murphy, Douglas G.; Infeld, Samatha I.

    2012-01-01

    NASA Langley Research Center conducted a pilot program to evaluate the benefits of using a Model-Based Systems Engineering (MBSE) approach during the early phase of the Materials International Space Station Experiment-X (MISSE-X) project. The goal of the pilot was to leverage MBSE tools and methods, including the Systems Modeling Language (SysML), to understand the net gain of utilizing this approach on a moderate size flight project. The System Requirements Review (SRR) success criteria were used to guide the work products desired from the pilot. This paper discusses the pilot project implementation, provides SysML model examples, identifies lessons learned, and describes plans for further use on MBSE on MISSE-X.

  20. The sequence relay selection strategy based on stochastic dynamic programming

    Science.gov (United States)

    Zhu, Rui; Chen, Xihao; Huang, Yangchao

    2017-07-01

    Relay-assisted (RA) network with relay node selection is a kind of effective method to improve the channel capacity and convergence performance. However, most of the existing researches about the relay selection did not consider the statically channel state information and the selection cost. This shortage limited the performance and application of RA network in practical scenarios. In order to overcome this drawback, a sequence relay selection strategy (SRSS) was proposed. And the performance upper bound of SRSS was also analyzed in this paper. Furthermore, in order to make SRSS more practical, a novel threshold determination algorithm based on the stochastic dynamic program (SDP) was given to work with SRSS. Numerical results are also presented to exhibit the performance of SRSS with SDP.