WorldWideScience

Sample records for hierarchical adaptive multiple

  1. Adaptive Sampling in Hierarchical Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R

    2007-07-09

    We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.

  2. 分层递阶多模型自适应解耦控制器%Multivariable Adaptive Decoupling Controller Using Hierarchical Multiple Models

    Institute of Scientific and Technical Information of China (English)

    王昕; 李少远; 岳恒

    2005-01-01

    To solve the problem such as too many models, long computing time and so on, a hierarchical multiple models direct adaptive decoupling controller is designed. It consists of multiple levels. In the upper level, the best model is chosen according to the switching index. Then multiple fixed models are constructed on line to cover the region which the above chosen fixed model lies in.In the last level, one free-running and one re-initialized adaptive model are added to guarantee the stability and improve the transient response. By selection of the weighting polynomial matrix, it not only eliminates the steady output error and places the poles of the closed loop system arbitrarily, but also decouples the system dynamically. At last, for this multiple models switching system, global convergence is obtained under common assumptions. Compared with the conventional multiple models adaptive controller, it reduces the number of the fixed models greatly. If the same number of the fixed models is used, the system transient response and decoupling result are improved. The simulation example illustrates the power of the derived controller.

  3. Hierarchical Control for Multiple DC Microgrids Clusters

    DEFF Research Database (Denmark)

    Shafiee, Qobad; Dragicevic, Tomislav; Vasquez, Juan Carlos;

    2014-01-01

    This paper presents a distributed hierarchical control framework to ensure reliable operation of dc Microgrid (MG) clusters. In this hierarchy, primary control is used to regulate the common bus voltage inside each MG locally. An adaptive droop method is proposed for this level which determines....... Another distributed policy is employed then to regulate the power flow among the MGs according to their local SOCs. The proposed distributed controllers on each MG communicate with only the neighbor MGs through a communication infrastructure. Finally, the small signal model is expanded for dc MG clusters...

  4. Adaptive mobility management scheme in hierarchical mobile IPv6

    Science.gov (United States)

    Fang, Bo; Song, Junde

    2004-04-01

    Hierarchical mobile IPv6 makes the mobility management localized. Registration with HA is only needed while MN moving between MAP domains. This paper proposed an adaptive mobility management scheme based on the hierarchical mobile IPv6. The scheme focuses on the MN operation as well as MAP operation during the handoff. Adaptive MAP selection algorithm can be used to select a suitable MAP to register with once MN moves into a new subnet while MAP can thus adaptively changing his management domain. Furthermore, MAP can also adaptively changes its level in the hierarchical referring on the service load or other related information. Detailed handoff algorithm is also discussed in this paper.

  5. OBSERVATIONS OF HIERARCHICAL SOLAR-TYPE MULTIPLE STAR SYSTEMS

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, Lewis C. Jr. [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena CA 91109 (United States); Tokovinin, Andrei [Cerro Tololo Inter-American Observatory, Casilla 603, La Serena (Chile); Mason, Brian D.; Hartkopf, William I. [U.S. Naval Observatory, 3450 Massachusetts Avenue, NW, Washington, DC 20392-5420 (United States); Riddle, Reed L., E-mail: lewis.c.roberts@jpl.nasa.gov [Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena, CA 91125 (United States)

    2015-10-15

    Twenty multiple stellar systems with solar-type primaries were observed at high angular resolution using the PALM-3000 adaptive optics system at the 5 m Hale telescope. The goal was to complement the knowledge of hierarchical multiplicity in the solar neighborhood by confirming recent discoveries by the visible Robo-AO system with new near-infrared observations with PALM-3000. The physical status of most, but not all, of the new pairs is confirmed by photometry in the Ks band and new positional measurements. In addition, we resolved for the first time five close sub-systems: the known astrometric binary in HIP 17129AB, companions to the primaries of HIP 33555, and HIP 118213, and the companions to the secondaries in HIP 25300 and HIP 101430. We place the components on a color–magnitude diagram and discuss each multiple system individually.

  6. Observations of Hierarchical Solar-Type Multiple Star Systems

    CERN Document Server

    Roberts,, Lewis C; Mason, Brian D; Hartkopf, William I; Riddle, Reed L

    2015-01-01

    Twenty multiple stellar systems with solar-type primaries were observed at high angular resolution using the PALM-3000 adaptive optics system at the 5 m Hale telescope. The goal was to complement the knowledge of hierarchical multiplicity in the solar neighborhood by confirming recent discoveries by the visible Robo-AO system with new near-infrared observations with PALM-3000. The physical status of most, but not all, of the new pairs is confirmed by photometry in the Ks band and new positional measurements. In addition, we resolved for the first time five close sub-systems: the known astrometric binary in HIP 17129AB, companions to the primaries of HIP 33555, and HIP 118213, and the companions to the secondaries in HIP 25300 and HIP 101430. We place the components on a color-magnitude diagram and discuss each multiple system individually.

  7. Adaptations in a hierarchical food web of southeastern Lake Michigan

    Science.gov (United States)

    Krause, Ann E.; Frank, Ken A.; Jones, Michael L.; Nalepa, Thomas F.; Barbiero, Richard P.; Madenjian, Charles P.; Agy, Megan; Evans, Marlene S.; Taylor, William W.; Mason, Doran M.; Leonard, Nancy J.

    2009-01-01

    Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more

  8. Multiple comparisons in genetic association studies: a hierarchical modeling approach.

    Science.gov (United States)

    Yi, Nengjun; Xu, Shizhong; Lou, Xiang-Yang; Mallick, Himel

    2014-02-01

    Multiple comparisons or multiple testing has been viewed as a thorny issue in genetic association studies aiming to detect disease-associated genetic variants from a large number of genotyped variants. We alleviate the problem of multiple comparisons by proposing a hierarchical modeling approach that is fundamentally different from the existing methods. The proposed hierarchical models simultaneously fit as many variables as possible and shrink unimportant effects towards zero. Thus, the hierarchical models yield more efficient estimates of parameters than the traditional methods that analyze genetic variants separately, and also coherently address the multiple comparisons problem due to largely reducing the effective number of genetic effects and the number of statistically "significant" effects. We develop a method for computing the effective number of genetic effects in hierarchical generalized linear models, and propose a new adjustment for multiple comparisons, the hierarchical Bonferroni correction, based on the effective number of genetic effects. Our approach not only increases the power to detect disease-associated variants but also controls the Type I error. We illustrate and evaluate our method with real and simulated data sets from genetic association studies. The method has been implemented in our freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/).

  9. Entrepreneurial intention modeling using hierarchical multiple regression

    Directory of Open Access Journals (Sweden)

    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  10. Adaptive color visualization for dichromats using a customized hierarchical palette

    Science.gov (United States)

    Rodríguez-Pardo, Carlos E.; Sharma, Gaurav

    2011-01-01

    We propose a user-centric methodology for displaying digital color documents, that optimizes color representations in an observer specific and adaptive fashion. We apply our framework to situations involving viewers with common dichromatic color vision deficiencies, who face challenges in perceiving information presented in color images and graphics designed for color normal individuals. For situations involving qualitative data visualization, we present a computationally efficient solution that combines a customized observer-specific hierarchical palette with "display time" selection of the number of colors to generate renderings with colors that are easily discriminated by the intended viewer. The palette design is accomplished via a clustering algorithm, that arranges colors in a hierarchical tree based on their perceived differences for the intended viewer. A desired number of highly discriminable colors are readily obtained from the hierarchical palette via a simple truncation. As an illustration, we demonstrate the application of the methodology to Ishihara style images.

  11. Hierarchical decomposition considered inconvenient: self-adaptation across abstraction layers

    Science.gov (United States)

    Gallagher, John C.

    2012-06-01

    Hierarchy may be difficult, if not impossible, to avoid either in natural or artificially engineered systems. Nevertheless, hierarchical decomposition can be considered inconvenient in a number of ways that interfere with the construction of adaptive systems capable of full exploitation of unexpected opportunities in an operational environment. This paper will briefly review some of those inconveniences and suggest principles by which to circumvent them while maintaining the obviously beneficial, and perhaps inevitable, paradigm of hierarchical decomposition of engineering designs. The paper will illustrate the introduced principles by appeal to an example auto-adaptive flight controller for an insect-scale flapping-wing micro air vehicle. The paper will conclude with discussion of possible future applications and methodological extensions.

  12. Hierarchical Participation Constraints for Adaptive Learning and Coordination

    DEFF Research Database (Denmark)

    Yi, Sangyoon; Stieglitz, Nils; Knudsen, Thorbjørn

    From the knowledge-based view of competence, firms exist as an institution where knowledge accumulation and knowledge application are facilitated by organizing principles that markets cannot provide. While scholars perceive that these two interdependent knowledge processes could be influenced...... by formal aspects of organizations, the underlying mechanisms still need to be unpacked. As such an organizing principle, we suggest in this study that hierarchical participation constraints promote both adaptive learning at the individual level and dynamic coordination at the organization level...

  13. Adaptive object recognition model using incremental feature representation and hierarchical classification.

    Science.gov (United States)

    Jeong, Sungmoon; Lee, Minho

    2012-01-01

    This paper presents an adaptive object recognition model based on incremental feature representation and a hierarchical feature classifier that offers plasticity to accommodate additional input data and reduces the problem of forgetting previously learned information. The incremental feature representation method applies adaptive prototype generation with a cortex-like mechanism to conventional feature representation to enable an incremental reflection of various object characteristics, such as feature dimensions in the learning process. A feature classifier based on using a hierarchical generative model recognizes various objects with variant feature dimensions during the learning process. Experimental results show that the adaptive object recognition model successfully recognizes single and multiple-object classes with enhanced stability and flexibility.

  14. Maximizing Adaptivity in Hierarchical Topological Models Using Cancellation Trees

    Energy Technology Data Exchange (ETDEWEB)

    Bremer, P; Pascucci, V; Hamann, B

    2008-12-08

    We present a highly adaptive hierarchical representation of the topology of functions defined over two-manifold domains. Guided by the theory of Morse-Smale complexes, we encode dependencies between cancellations of critical points using two independent structures: a traditional mesh hierarchy to store connectivity information and a new structure called cancellation trees to encode the configuration of critical points. Cancellation trees provide a powerful method to increase adaptivity while using a simple, easy-to-implement data structure. The resulting hierarchy is significantly more flexible than the one previously reported. In particular, the resulting hierarchy is guaranteed to be of logarithmic height.

  15. Adapting playware to multiple players

    DEFF Research Database (Denmark)

    Þorsteinsson, Arnar Tumi; Lund, Henrik Hautop; Mastorakis, Nikos

    2011-01-01

    With the creation of playware as intelligent hardware and software that creates play, it is possible to adapt the play tool to the individual user, and even to multiple users playing at the same time with the play tool. In this paper, we show how it is possible to implement adaptivity in modular...... to such differences, and argues that adaptivity is needed to make games fit to the individual users in both single-player games and multi-player games. As a case study, we implemented such adaptivity on modular interactive tiles for the single-user game ColorTimer, and for the multiple-user games PingPong, in which...

  16. Hierarchical method of task assignment for multiple cooperating UAV teams

    Institute of Scientific and Technical Information of China (English)

    Xiaoxuan Hu; Huawei Ma; Qingsong Ye; He Luo

    2015-01-01

    The problem of task assignment for multiple cooperat-ing unmanned aerial vehicle (UAV) teams is considered. Multiple UAVs forming several smal teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: tar-get clustering, cluster al ocation and target assignment. The first two sub-problems are central y solved by using clustering algo-rithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and paral el manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem con-siderably, especial y when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasi-ble and more efficient than non-hierarchical methods.

  17. Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

    Science.gov (United States)

    Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

    2014-09-30

    This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Research and application of hierarchical model for multiple fault diagnosis

    Institute of Scientific and Technical Information of China (English)

    An Ruoming; Jiang Xingwei; Song Zhengji

    2005-01-01

    Computational complexity of complex system multiple fault diagnosis is a puzzle at all times. Based on the well-known Mozetic's approach, a novel hierarchical model-based diagnosis methodology is put forward for improving efficiency of multi-fault recognition and localization. Structural abstraction and weighted fault propagation graphs are combined to build diagnosis model. The graphs have weighted arcs with fault propagation probabilities and propagation strength. For solving the problem of coupled faults, two diagnosis strategies are used: one is the Lagrangian relaxation and the primal heuristic algorithms; another is the method of propagation strength. Finally, an applied example shows the applicability of the approach and experimental results are given to show the superiority of the presented technique.

  19. Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform.

    Science.gov (United States)

    De Queiroz, Ricardo; Chou, Philip A

    2016-06-01

    In free-viewpoint video, there is a recent trend to represent scene objects as solids rather than using multiple depth maps. Point clouds have been used in computer graphics for a long time and with the recent possibility of real time capturing and rendering, point clouds have been favored over meshes in order to save computation. Each point in the cloud is associated with its 3D position and its color. We devise a method to compress the colors in point clouds which is based on a hierarchical transform and arithmetic coding. The transform is a hierarchical sub-band transform that resembles an adaptive variation of a Haar wavelet. The arithmetic encoding of the coefficients assumes Laplace distributions, one per sub-band. The Laplace parameter for each distribution is transmitted to the decoder using a custom method. The geometry of the point cloud is encoded using the well-established octtree scanning. Results show that the proposed solution performs comparably to the current state-of-the-art, in many occasions outperforming it, while being much more computationally efficient. We believe this work represents the state-of-the-art in intra-frame compression of point clouds for real-time 3D video.

  20. Improving Measurement Precision of Hierarchical Latent Traits Using Adaptive Testing

    Science.gov (United States)

    Wang, Chun

    2014-01-01

    Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order factors directly govern the actual item responses.…

  1. A Distributed and Adaptive Location Management Scheme for Hierarchical Mobility Management

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Hierarchical mobility management is sensitive to the failure of gateway mobility agents and prone to degrade performance on heavy loads. This paper proposes a distributed and adaptive location management scheme based on Hierarchical Mobile IPv6. This scheme can balance the loads of mobility anchor points and increase the robustness of the hierarchical structure to certain extents. In this scheme, the optimized IP paging scheme is adopted to reduce the paging signaling cost and improve the scalability of the hierarchical mobility management. We implement the distributed and adaptive location management scheme in a simulation platform and compare its performance with that of two other location management schemes. Our simulation results show that our scheme is capable of balancing the signaling and traffic loads of mobility ancher points, decreasing the average handover latency, and increasing the throughout of the visited networks.

  2. Hierarchical Control for Multiple DC-Microgrids Clusters

    DEFF Research Database (Denmark)

    Shafiee, Qobad; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2014-01-01

    DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed in this p......DC microgrids (MGs) have gained research interest during the recent years because of many potential advantages as compared to the ac system. To ensure reliable operation of a low-voltage dc MG as well as its intelligent operation with the other DC MGs, a hierarchical control is proposed...

  3. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Directory of Open Access Journals (Sweden)

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  4. Coevolution of Information Processing and Topology in Hierarchical Adaptive Random Boolean Networks

    CERN Document Server

    Gorski, Piotr J; Holyst, Janusz A

    2015-01-01

    Random Boolean networks (RBNs) are frequently employed for modelling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive RBN (HARBN) as a system consisting of distinct adaptive RBNs - subnetworks - connected by a set of permanent interlinks. Information measures and internal subnetworks topology of HARBN coevolve and reach steady-states that are specific for a given network structure. We investigate mean node information, mean edge information as well as a mean node degree as functions of model parameters and demonstrate HARBN's ability to describe complex hierarchical systems.

  5. A hierarchical model for optimal supplier selection in multiple sourcing contexts

    OpenAIRE

    Dotoli, Mariagrazia; Falagario, Marco

    2011-01-01

    Abstract The paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e., optimal supplier selection. We present a hierarchical extension of the Data Envelopment Analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier acco...

  6. Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

    Science.gov (United States)

    Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

    2016-09-01

    In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

  7. A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates

    Science.gov (United States)

    Huang, Weizhang; Kamenski, Lennard; Lang, Jens

    2010-03-01

    A new anisotropic mesh adaptation strategy for finite element solution of elliptic differential equations is presented. It generates anisotropic adaptive meshes as quasi-uniform ones in some metric space, with the metric tensor being computed based on hierarchical a posteriori error estimates. A global hierarchical error estimate is employed in this study to obtain reliable directional information of the solution. Instead of solving the global error problem exactly, which is costly in general, we solve it iteratively using the symmetric Gauß-Seidel method. Numerical results show that a few GS iterations are sufficient for obtaining a reasonably good approximation to the error for use in anisotropic mesh adaptation. The new method is compared with several strategies using local error estimators or recovered Hessians. Numerical results are presented for a selection of test examples and a mathematical model for heat conduction in a thermal battery with large orthotropic jumps in the material coefficients.

  8. Analysis of stability of community structure across multiple hierarchical levels

    CERN Document Server

    Li, Hui-Jia

    2015-01-01

    The analysis of stability of community structure is an important problem for scientists from many fields. Here, we propose a new framework to reveal hidden properties of community structure by quantitatively analyzing the dynamics of Potts model. Specifically we model the Potts procedure of community structure detection by a Markov process, which has a clear mathematical explanation. Critical topological information regarding to multivariate spin configuration could also be inferred from the spectral significance of the Markov process. We test our framework on some example networks and find it doesn't have resolute limitation problem at all. Results have shown the model we proposed is able to uncover hierarchical structure in different scales effectively and efficiently.

  9. Multiple models adaptive feedforward decoupling controller

    Institute of Scientific and Technical Information of China (English)

    Wang Xin; Li Shaoyuan; Wang Zhongjie

    2005-01-01

    When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

  10. Adaptive stochastic Galerkin FEM with hierarchical tensor representations

    KAUST Repository

    Eigel, Martin

    2016-01-08

    PDE with stochastic data usually lead to very high-dimensional algebraic problems which easily become unfeasible for numerical computations because of the dense coupling structure of the discretised stochastic operator. Recently, an adaptive stochastic Galerkin FEM based on a residual a posteriori error estimator was presented and the convergence of the adaptive algorithm was shown. While this approach leads to a drastic reduction of the complexity of the problem due to the iterative discovery of the sparsity of the solution, the problem size and structure is still rather limited. To allow for larger and more general problems, we exploit the tensor structure of the parametric problem by representing operator and solution iterates in the tensor train (TT) format. The (successive) compression carried out with these representations can be seen as a generalisation of some other model reduction techniques, e.g. the reduced basis method. We show that this approach facilitates the efficient computation of different error indicators related to the computational mesh, the active polynomial chaos index set, and the TT rank. In particular, the curse of dimension is avoided.

  11. Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities

    CERN Document Server

    Eriksson, Brian; Singh, Aarti; Nowak, Robert

    2011-01-01

    Hierarchical clustering based on pairwise similarities is a common tool used in a broad range of scientific applications. However, in many problems it may be expensive to obtain or compute similarities between the items to be clustered. This paper investigates the hierarchical clustering of N items based on a small subset of pairwise similarities, significantly less than the complete set of N(N-1)/2 similarities. First, we show that if the intracluster similarities exceed intercluster similarities, then it is possible to correctly determine the hierarchical clustering from as few as 3N log N similarities. We demonstrate this order of magnitude savings in the number of pairwise similarities necessitates sequentially selecting which similarities to obtain in an adaptive fashion, rather than picking them at random. We then propose an active clustering method that is robust to a limited fraction of anomalous similarities, and show how even in the presence of these noisy similarity values we can resolve the hierar...

  12. HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

    Directory of Open Access Journals (Sweden)

    V. T. Nguyen

    2016-05-01

    Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

  13. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    HOU XueLiang; LU Mei

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction en-gineering projects,a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model.By this new algorithm,local solutions to the first-order transformation of co-adaptability for conflict events can be ob-tained,based upon which,a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction de-gree of local solutions.The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently,but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  14. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction engineering projects, a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model. By this new algorithm, local solutions to the first-order transformation of co-adaptability for conflict events can be obtained, based upon which, a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction degree of local solutions. The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently, but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  15. Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree

    Science.gov (United States)

    Chen, Wei-Bang

    2012-01-01

    The purpose of this research is to develop a new visual information analysis, representation, and retrieval framework for automatic discovery of salient objects of user's interest in large-scale image databases. In particular, this dissertation describes a content-based image retrieval framework which supports multiple-object retrieval. The…

  16. Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree

    Science.gov (United States)

    Chen, Wei-Bang

    2012-01-01

    The purpose of this research is to develop a new visual information analysis, representation, and retrieval framework for automatic discovery of salient objects of user's interest in large-scale image databases. In particular, this dissertation describes a content-based image retrieval framework which supports multiple-object retrieval. The…

  17. The use of multiple hierarchically independent gene ontology terms in gene function prediction and genome annotation

    NARCIS (Netherlands)

    Kourmpetis, Y.I.A.; Burgt, van der A.; Bink, M.C.A.M.; Braak, ter C.J.F.; Ham, van R.C.H.J.

    2007-01-01

    The Gene Ontology (GO) is a widely used controlled vocabulary for the description of gene function. In this study we quantify the usage of multiple and hierarchically independent GO terms in the curated genome annotations of seven well-studied species. In most genomes, significant proportions (6 -

  18. Hierarchical Direct Time Integration Method and Adaptive Procedure for Dynamic Analysis

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    New hierarchical direct time integration method for structural dynamic analysis is developed by using Taylor series expansions in each time step. Very accurate results can be obtained by increasing the order of the Taylor series. Furthermore, the local error can be estimated by simply comparing the solutions obtained by the proposed method with the higher order solutions. This local estimate is then used to develop an adaptive order-control technique. Numerical examples are given to illustrate the performance of the present method and its adaptive procedure.

  19. Hierarchical prediction and context adaptive coding for lossless color image compression.

    Science.gov (United States)

    Kim, Seyun; Cho, Nam Ik

    2014-01-01

    This paper presents a new lossless color image compression algorithm, based on the hierarchical prediction and context-adaptive arithmetic coding. For the lossless compression of an RGB image, it is first decorrelated by a reversible color transform and then Y component is encoded by a conventional lossless grayscale image compression method. For encoding the chrominance images, we develop a hierarchical scheme that enables the use of upper, left, and lower pixels for the pixel prediction, whereas the conventional raster scan prediction methods use upper and left pixels. An appropriate context model for the prediction error is also defined and the arithmetic coding is applied to the error signal corresponding to each context. For several sets of images, it is shown that the proposed method further reduces the bit rates compared with JPEG2000 and JPEG-XR.

  20. Multiple Source Adaptation and the Renyi Divergence

    CERN Document Server

    Mansour, Yishay; Rostamizadeh, Afshin

    2012-01-01

    This paper presents a novel theoretical study of the general problem of multiple source adaptation using the notion of Renyi divergence. Our results build on our previous work [12], but significantly broaden the scope of that work in several directions. We extend previous multiple source loss guarantees based on distribution weighted combinations to arbitrary target distributions P, not necessarily mixtures of the source distributions, analyze both known and unknown target distribution cases, and prove a lower bound. We further extend our bounds to deal with the case where the learner receives an approximate distribution for each source instead of the exact one, and show that similar loss guarantees can be achieved depending on the divergence between the approximate and true distributions. We also analyze the case where the labeling functions of the source domains are somewhat different. Finally, we report the results of experiments with both an artificial data set and a sentiment analysis task, showing the p...

  1. Adaptive Integral Method for Higher-Order Hierarchical Method of Moments

    DEFF Research Database (Denmark)

    Kim, Oleksiy S.; Meincke, Peter

    2006-01-01

    The Adaptive Integral Method (AIM) is applied to solve the volume integral equation in conjunction with the higher-order Method of Moments (MoM). The classical AIM is modified for larger discretization cells to take advantage of higher-order MoM. The technique combines the low computational...... complexity and memory requirements of AIM with the reduced number of unknowns and higher-order convergence of higher-order hierarchical Legendre basis functions. Numerical examples given show the advantages of the proposed technique over AIM based on low-order basis functions in terms of memory...

  2. Multiple-Morphs Adaptive Stream Architecture

    Institute of Scientific and Technical Information of China (English)

    Mei Wen; Nan Wu; Hai-Yan Li; Chun-Yuan Zhang

    2005-01-01

    In modern VLSI technology, hundreds of thousands of arithmetic units fit on a 1cm2 chip. The challenge is supplying them with instructions and data. Stream architecture is able to solve the problem well. However, the applications suited for typical stream architecture are limited. This paper presents the definition of regular stream and irregular stream,and then describes MASA (Multiple-morphs Adaptive Stream Architecture) prototype system which supports different execution models according to applications' stream characteristics. This paper first discusses MASA architecture and stream model, and then explores the features and advantages of MASA through mapping stream applications to hardware.Finally MASA is evaluated by ten benchmarks. The result is encouraging.

  3. An Adaptive Method for Mining Hierarchical Spatial Co-location Patterns

    Directory of Open Access Journals (Sweden)

    CAI Jiannan

    2016-04-01

    Full Text Available Mining spatial co-location patterns plays a key role in spatial data mining. Spatial co-location patterns refer to subsets of features whose objects are frequently located in close geographic proximity. Due to spatial heterogeneity, spatial co-location patterns are usually not the same across geographic space. However, existing methods are mainly designed to discover global spatial co-location patterns, and not suitable for detecting regional spatial co-location patterns. On that account, an adaptive method for mining hierarchical spatial co-location patterns is proposed in this paper. Firstly, global spatial co-location patterns are detected and other non-prevalent co-location patterns are identified as candidate regional co-location patterns. Then, for each candidate pattern, adaptive spatial clustering method is used to delineate localities of that pattern in the study area, and participation ratio is utilized to measure the prevalence of the candidate co-location pattern. Finally, an overlap operation is developed to deduce localities of (k+1-size co-location patterns from localities of k-size co-location patterns. Experiments on both simulated and real-life datasets show that the proposed method is effective for detecting hierarchical spatial co-location patterns.

  4. An Isogeometric Design-through-analysis Methodology based on Adaptive Hierarchical Refinement of NURBS, Immersed Boundary Methods, and T-spline CAD Surfaces

    Science.gov (United States)

    2012-01-22

    ICES REPORT 12-05 January 2012 An Isogeometric Design-through-analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed...M.J. Borden, E. Rank, T.J.R. Hughes, An Isogeometric Design-through-analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed...analysis Methodology based on Adaptive Hierarchical Refinement of NURBS , Immersed Boundary Methods, and T-spline CAD Surfaces 5a. CONTRACT NUMBER 5b

  5. Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms

    KAUST Repository

    Hasanov, Khalid

    2014-03-04

    © 2014, Springer Science+Business Media New York. Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix–matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms.

  6. Hierarchical multiple informants models: examining food environment contributions to the childhood obesity epidemic.

    Science.gov (United States)

    Baek, Jonggyu; Sánchez, Brisa N; Sanchez-Vaznaugh, Emma V

    2014-02-20

    Methods for multiple informants help to estimate the marginal effect of each multiple source predictor and formally compare the strength of their association with an outcome. We extend multiple informant methods to the case of hierarchical data structures to account for within cluster correlation. We apply the proposed method to examine the relationship between features of the food environment near schools and children's body mass index z-scores (BMIz). Specifically, we compare the associations between two different features of the food environment (fast food restaurants and convenience stores) with BMIz and investigate how the association between the number of fast food restaurants or convenience stores and child's BMIz varies across distance from a school. The newly developed methodology enhances the types of research questions that can be asked by investigators studying effects of environment on childhood obesity and can be applied to other fields.

  7. Highly Stretchable Superhydrophobic Composite Coating Based on Self-Adaptive Deformation of Hierarchical Structures.

    Science.gov (United States)

    Hu, Xin; Tang, Changyu; He, Zhoukun; Shao, Hong; Xu, Keqin; Mei, Jun; Lau, Woon-Ming

    2017-05-01

    With the rapid development of stretchable electronics, functional textiles, and flexible sensors, water-proof protection materials are required to be built on various highly flexible substrates. However, maintaining the antiwetting of superhydrophobic surface under stretching is still a big challenge since the hierarchical structures at hybridized micro-nanoscales are easily damaged following large deformation of the substrates. This study reports a highly stretchable and mechanically stable superhydrophobic surface prepared by a facile spray coating of carbon black/polybutadiene elastomeric composite on a rubber substrate followed by thermal curing. The resulting composite coating can maintain its superhydrophobic property (water contact angle ≈170° and sliding angle superhydrophobic property. Furthermore, the experimental observation and modeling analysis reveal that the stable superhydrophobic properties of the composite coating are attributed to the unique self-adaptive deformation ability of 3D hierarchical roughness of the composite coating, which delays the Cassie-Wenzel transition of surface wetting. In addition, it is first observed that the damaged coating can automatically recover its superhydrophobicity via a simple stretching treatment without incorporating additional hydrophobic materials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

    Directory of Open Access Journals (Sweden)

    KwangHee Choi

    2014-10-01

    Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.

  9. Coevolution of information processing and topology in hierarchical adaptive random Boolean networks

    Science.gov (United States)

    Górski, Piotr J.; Czaplicka, Agnieszka; Hołyst, Janusz A.

    2016-02-01

    Random Boolean Networks (RBNs) are frequently used for modeling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive random Boolean Network (HARBN) as a system consisting of distinct adaptive RBNs (ARBNs) - subnetworks - connected by a set of permanent interlinks. We investigate mean node information, mean edge information as well as mean node degree. Information measures and internal subnetworks topology of HARBN coevolve and reach steady-states that are specific for a given network structure. The main natural feature of ARBNs, i.e. their adaptability, is preserved in HARBNs and they evolve towards critical configurations which is documented by power law distributions of network attractor lengths. The mean information processed by a single node or a single link increases with the number of interlinks added to the system. The mean length of network attractors and the mean steady-state connectivity possess minima for certain specific values of the quotient between the density of interlinks and the density of all links in networks. It means that the modular network displays extremal values of its observables when subnetworks are connected with a density a few times lower than a mean density of all links.

  10. Adaptive Hierarchical Voltage Control of a DFIG-Based Wind Power Plant for a Grid Fault

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jinho; Muljadi, Eduard; Park, Jung-Wook; Kang, Yong Cheol

    2016-11-01

    This paper proposes an adaptive hierarchical voltage control scheme of a doubly-fed induction generator (DFIG)-based wind power plant (WPP) that can secure more reserve of reactive power (Q) in the WPP against a grid fault. To achieve this, each DFIG controller employs an adaptive reactive power to voltage (Q-V) characteristic. The proposed adaptive Q-V characteristic is temporally modified depending on the available Q capability of a DFIG; it is dependent on the distance from a DFIG to the point of common coupling (PCC). The proposed characteristic secures more Q reserve in the WPP than the fixed one. Furthermore, it allows DFIGs to promptly inject up to the Q limit, thereby improving the PCC voltage support. To avert an overvoltage after the fault clearance, washout filters are implemented in the WPP and DFIG controllers; they can prevent a surplus Q injection after the fault clearance by eliminating the accumulated values in the proportional-integral controllers of both controllers during the fault. Test results demonstrate that the scheme can improve the voltage support capability during the fault and suppress transient overvoltage after the fault clearance under scenarios of various system and fault conditions; therefore, it helps ensure grid resilience by supporting the voltage stability.

  11. AH-MAC: Adaptive Hierarchical MAC Protocol for Low-Rate Wireless Sensor Network Applications

    Directory of Open Access Journals (Sweden)

    Adnan Ismail Al-Sulaifanie

    2017-01-01

    Full Text Available This paper proposes an adaptive hierarchical MAC protocol (AH-MAC with cross-layer optimization for low-rate and large-scale wireless sensor networks. The main goal of the proposed protocol is to combine the strengths of LEACH and IEEE 802.15.4 while offsetting their weaknesses. The predetermined cluster heads are supported with an energy harvesting circuit, while the normal nodes are battery-operated. To prolong the network’s operational lifetime, the proposed protocol transfers most of the network’s activities to the cluster heads while minimizing the node’s activity. Some of the main features of this protocol include energy efficiency, self-configurability, scalability, and self-healing. The simulation results showed great improvement of the AH-MAC over LEACH protocol in terms of energy consumption and throughput. AH-MAC consumes eight times less energy while improving throughput via acknowledgment support.

  12. Using Hierarchical Adaptive Neuro Fuzzy Systems And Design Two New Edge Detectors In Noisy Images

    Directory of Open Access Journals (Sweden)

    M. H. Olyaee

    2013-10-01

    Full Text Available One of the most important topics in image processing is edge detection. Many methods have been proposed for this end but most of them have weak performance in noisy images because noise pixels are determined as edge. In this paper, two new methods are represented based on Hierarchical Adaptive Neuro Fuzzy Systems (HANFIS. Each method consists of desired number of HANFIS operators that receive the value of some neighbouring pixels and decide central pixel is edge or not. Simple train images are used in order to set internal parameters of each HANFIS operator. The presented methods are evaluated by some test images and compared with several popular edge detectors. The experimental results show that these methods are robust against impulse noise and extract edge pixels exactly.

  13. Hierarchical multilevel authentication system for multiple-image based on phase retrieval and basic vector operations

    Science.gov (United States)

    Li, Xianye; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Peng, Xiang; He, Wenqi; Pan, Xuemei; Dong, Guoyan; Chen, Hongyi

    2017-02-01

    A hierarchical multilevel authentication system for multiple-image based on phase retrieval and basic vector operations in the Fresnel domain is proposed, by which more certification images are iteratively encoded into multiple cascaded phase masks according to different hierarchical levels. Based on the secret sharing algorithm by basic vector decomposition and composition operations, the iterated phase distributions are split into n pairs of shadow images keys (SIKs), and then distributed to n different participants (the authenticators). During each level in the high authentication process, any 2 or more participants can be gathered to reconstruct the original meaningful certification images. While in the case of each level in the low authentication process, only one authenticator who possesses a correct pair of SIKs, will gain no significant information of certification image; however, it can result in a remarkable peak output in the nonlinear correlation coefficient of the recovered image and the standard certification image, which can successfully provide an additional authentication layer for the high-level authentication. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

  14. Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

    Science.gov (United States)

    Benaskeur, Abder R.; Roy, Jean

    2001-08-01

    Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

  15. Three-dimensional hierarchical cultivation of human skin cells on bio-adaptive hybrid fibers.

    Science.gov (United States)

    Planz, Viktoria; Seif, Salem; Atchison, Jennifer S; Vukosavljevic, Branko; Sparenberg, Lisa; Kroner, Elmar; Windbergs, Maike

    2016-07-11

    The human skin comprises a complex multi-scale layered structure with hierarchical organization of different cells within the extracellular matrix (ECM). This supportive fiber-reinforced structure provides a dynamically changing microenvironment with specific topographical, mechanical and biochemical cell recognition sites to facilitate cell attachment and proliferation. Current advances in developing artificial matrices for cultivation of human cells concentrate on surface functionalizing of biocompatible materials with different biomolecules like growth factors to enhance cell attachment. However, an often neglected aspect for efficient modulation of cell-matrix interactions is posed by the mechanical characteristics of such artificial matrices. To address this issue, we fabricated biocompatible hybrid fibers simulating the complex biomechanical characteristics of native ECM in human skin. Subsequently, we analyzed interactions of such fibers with human skin cells focusing on the identification of key fiber characteristics for optimized cell-matrix interactions. We successfully identified the mediating effect of bio-adaptive elasto-plastic stiffness paired with hydrophilic surface properties as key factors for cell attachment and proliferation, thus elucidating the synergistic role of these parameters to induce cellular responses. Co-cultivation of fibroblasts and keratinocytes on such fiber mats representing the specific cells in dermis and epidermis resulted in a hierarchical organization of dermal and epidermal tissue layers. In addition, terminal differentiation of keratinocytes at the air interface was observed. These findings provide valuable new insights into cell behaviour in three-dimensional structures and cell-material interactions which can be used for rational development of bio-inspired functional materials for advanced biomedical applications.

  16. Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms

    KAUST Repository

    Quintin, Jean-Noel

    2013-10-01

    Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon\\'s algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon\\'s algorithm as it can be used on a nonsquare number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores. © 2013 IEEE.

  17. Accelerated Multiplicative Updates and Hierarchical ALS Algorithms for Nonnegative Matrix Factorization

    CERN Document Server

    Gillis, Nicolas

    2011-01-01

    Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety of applications such as text mining, image processing, hyperspectral data analysis, computational biology, and clustering. In this paper, we consider two well-known algorithms designed to solve NMF problems, namely the multiplicative updates of Lee and Seung and the hierarchical alternating least squares of Cichocki et al. We propose a simple way to significantly accelerate their convergence, based on a careful analysis of the computational cost needed at each iteration. This acceleration technique can also be applied to other algorithms, which we illustrate on the projected gradient method of Lin. The efficiency of the accelerated algorithms is empirically demonstrated on image and text datasets, and compares favorably with a state-of-the-art alternating nonnegative least squares algorithm. Finally, we provide a theoretical argument based on the properties of NMF and its solutions that explains in particular the very ...

  18. Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

    Science.gov (United States)

    Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.

    2017-01-01

    A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

  19. A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model

    Energy Technology Data Exchange (ETDEWEB)

    Koniges, A E; Masters, N D; Fisher, A C; Anderson, R W; Eder, D C; Benson, D; Kaiser, T B; Gunney, B T; Wang, P; Maddox, B R; Hansen, J F; Kalantar, D H; Dixit, P; Jarmakani, H; Meyers, M A

    2009-03-03

    Fragmentation is a fundamental material process that naturally spans spatial scales from microscopic to macroscopic. We developed a mathematical framework using an innovative combination of hierarchical material modeling (HMM) and adaptive mesh refinement (AMR) to connect the continuum to microstructural regimes. This framework has been implemented in a new multi-physics, multi-scale, 3D simulation code, NIF ALE-AMR. New multi-material volume fraction and interface reconstruction algorithms were developed for this new code, which is leading the world effort in hydrodynamic simulations that combine AMR with ALE (Arbitrary Lagrangian-Eulerian) techniques. The interface reconstruction algorithm is also used to produce fragments following material failure. In general, the material strength and failure models have history vector components that must be advected along with other properties of the mesh during remap stage of the ALE hydrodynamics. The fragmentation models are validated against an electromagnetically driven expanding ring experiment and dedicated laser-based fragmentation experiments conducted at the Jupiter Laser Facility. As part of the exit plan, the NIF ALE-AMR code was applied to a number of fragmentation problems of interest to the National Ignition Facility (NIF). One example shows the added benefit of multi-material ALE-AMR that relaxes the requirement that material boundaries must be along mesh boundaries.

  20. Multiple-Model Adaptive Switching Control for Uncertain Multivariable Systems

    NARCIS (Netherlands)

    Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro

    2011-01-01

    This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl

  1. Control Strategies for Islanded Microgrid using Enhanced Hierarchical Control Structure with Multiple Current-Loop Damping Schemes

    DEFF Research Database (Denmark)

    Han, Yang; Shen, Pan; Zhao, Xin

    2017-01-01

    In this paper, the modeling, controller design, and stability analysis of the islanded microgrid (MG) using enhanced hierarchical control structure with multiple current loop damping schemes is proposed. The islanded MG is consisted of the parallel-connected voltage source inverters using LCL...

  2. Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

    Science.gov (United States)

    Graves, T.A.; Kendall, K.C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

    2011-01-01

    Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system. ?? 2011 The Authors. Animal Conservation ?? 2011 The Zoological Society of London.

  3. Ordered assembly of NiCo₂O₄ multiple hierarchical structures for high-performance pseudocapacitors.

    Science.gov (United States)

    Zhou, Qingwen; Xing, Jiachao; Gao, Yanfang; Lv, Xiaojun; He, Yongmei; Guo, Zihan; Li, Yueming

    2014-07-23

    The design and development of nanomaterials has become central to the advancement of pseudocapacitive performance. Many one-dimensional nanostructures (1D NSs), two-dimensional nanostructures (2D NSs), and three-dimensional hierarchical structures (3D HSs) composed of these building blocks have been synthesized as pseudocapacitive materials via different methods. However, due to the unclear assembly mechanism of these NSs, reports of HSs simultaneously assembled from two or more types of NSs are rare. In this article, NiCo2O4 multiple hierarchical structures (MHSs) composed of 1D nanowires and 2D nanosheets are simply grown on Ni foam using an ordered two-step hydrothermal synthesis followed by annealing processing. The low-dimensional nanowire is found to hold priority in the growth order, rather than the high-dimensional nanosheet, thus effectively promoting the integration of these different NSs in the assembly of the NiCo2O4 MHSs. With vast electroactive surface area and favorable mesoporous architecture, the NiCo2O4 MHSs exhibit a high specific capacitance of up to 2623.3 F g(-1), scaled to the active mass of the NiCo2O4 sample at a current density of 1 A g(-1). A nearly constant rate performance of 68% is achieved at a current density ranging from 1 to 40 A g(-1), and the sample retains approximately 94% of its maximum capacitance even after 3000 continuous charge-discharge cycles at a consistently high current density of 10 A g(-1).

  4. Accelerating Matrix-Vector Multiplication on Hierarchical Matrices Using Graphical Processing Units

    KAUST Repository

    Boukaram, W.

    2015-03-25

    Large dense matrices arise from the discretization of many physical phenomena in computational sciences. In statistics very large dense covariance matrices are used for describing random fields and processes. One can, for instance, describe distribution of dust particles in the atmosphere, concentration of mineral resources in the earth\\'s crust or uncertain permeability coefficient in reservoir modeling. When the problem size grows, storing and computing with the full dense matrix becomes prohibitively expensive both in terms of computational complexity and physical memory requirements. Fortunately, these matrices can often be approximated by a class of data sparse matrices called hierarchical matrices (H-matrices) where various sub-blocks of the matrix are approximated by low rank matrices. These matrices can be stored in memory that grows linearly with the problem size. In addition, arithmetic operations on these H-matrices, such as matrix-vector multiplication, can be completed in almost linear time. Originally the H-matrix technique was developed for the approximation of stiffness matrices coming from partial differential and integral equations. Parallelizing these arithmetic operations on the GPU has been the focus of this work and we will present work done on the matrix vector operation on the GPU using the KSPARSE library.

  5. Adaptive Hierarchical Sliding Mode Control with Input Saturation for Attitude Regulation of Multi-satellite Tethered System

    Science.gov (United States)

    Ma, Zhiqiang; Sun, Guanghui

    2017-06-01

    This paper proposes a novel adaptive hierarchical sliding mode control for the attitude regulation of the multi-satellite inline tethered system, where the input saturation is taken into account. The governing equations for the attitude dynamics of the three-satellite inline tethered system are derived firstly by utilizing Lagrangian mechanics theory. Considering the fact that the attitude of the central satellite can be adjusted by using the simple exponential stabilization scheme, the decoupling of the central satellite and the terminal ones is presented, and in addition, the new adaptive sliding mode control law is applied to stabilize the attitude dynamics of the two terminal satellites based on the synchronization and partial contraction theory. In the adaptive hierarchical sliding mode control design, the input is modeled as saturated input due to the fact that the flywheel torque is bounded, and meanwhile, an adaptive update rate is introduced to eliminate the effect of the saturated input and the external perturbation. The proposed control scheme can be applied on the two-satellite system to achieve fixed-point rotation. Numerical results validate the effectiveness of the proposed method.

  6. Adaptive Hierarchical Sliding Mode Control with Input Saturation for Attitude Regulation of Multi-satellite Tethered System

    Science.gov (United States)

    Ma, Zhiqiang; Sun, Guanghui

    2016-11-01

    This paper proposes a novel adaptive hierarchical sliding mode control for the attitude regulation of the multi-satellite inline tethered system, where the input saturation is taken into account. The governing equations for the attitude dynamics of the three-satellite inline tethered system are derived firstly by utilizing Lagrangian mechanics theory. Considering the fact that the attitude of the central satellite can be adjusted by using the simple exponential stabilization scheme, the decoupling of the central satellite and the terminal ones is presented, and in addition, the new adaptive sliding mode control law is applied to stabilize the attitude dynamics of the two terminal satellites based on the synchronization and partial contraction theory. In the adaptive hierarchical sliding mode control design, the input is modeled as saturated input due to the fact that the flywheel torque is bounded, and meanwhile, an adaptive update rate is introduced to eliminate the effect of the saturated input and the external perturbation. The proposed control scheme can be applied on the two-satellite system to achieve fixed-point rotation. Numerical results validate the effectiveness of the proposed method.

  7. HiCoDG: A Hierarchical Data-Gathering Scheme Using Cooperative Multiple Mobile Elements †

    Science.gov (United States)

    Van Le, Duc; Oh, Hoon; Yoon, Seokhoon

    2014-01-01

    In this paper, we study mobile element (ME)-based data-gathering schemes in wireless sensor networks. Due to the physical speed limits of mobile elements, the existing data-gathering schemes that use mobile elements can suffer from high data-gathering latency. In order to address this problem, this paper proposes a new hierarchical and cooperative data-gathering (HiCoDG) scheme that enables multiple mobile elements to cooperate with each other to collect and relay data. In HiCoDG, two types of mobile elements are used: the mobile collector (MC) and the mobile relay (MR). MCs collect data from sensors and forward them to the MR, which will deliver them to the sink. In this work, we also formulated an integer linear programming (ILP) optimization problem to find the optimal trajectories for MCs and the MR, such that the traveling distance of MEs is minimized. Two variants of HiCoDG, intermediate station (IS)-based and cooperative movement scheduling (CMS)-based, are proposed to facilitate cooperative data forwarding from MCs to the MR. An analytical model for estimating the average data-gathering latency in HiCoDG was also designed. Simulations were performed to compare the performance of the IS and CMS variants, as well as a multiple traveling salesman problem (mTSP)-based approach. The simulation results show that HiCoDG outperforms mTSP in terms of latency. The results also show that CMS can achieve the lowest latency with low energy consumption. PMID:25526356

  8. HiCoDG: A Hierarchical Data-Gathering Scheme Using Cooperative Multiple Mobile Elements

    Directory of Open Access Journals (Sweden)

    Duc Van Le

    2014-12-01

    Full Text Available In this paper, we study mobile element (ME-based data-gathering schemes in wireless sensor networks. Due to the physical speed limits of mobile elements, the existing data-gathering schemes that usemobile elements can suffer from high data-gathering latency. In order to address this problem, this paper proposes a new hierarchical and cooperative data-gathering (HiCoDG scheme that enables multiple mobile elements to cooperate with each other to collect and relay data. In HiCoDG, two types of mobile elements are used: the mobile collector (MC and the mobile relay (MR. MCs collect data from sensors and forward them to the MR, which will deliver them to the sink. In this work, we also formulated an integer linear programming (ILP optimization problem to find the optimal trajectories for MCs and the MR, such that the traveling distance of MEs is minimized. Two variants of HiCoDG, intermediate station (IS-based and cooperative movement scheduling (CMS-based, are proposed to facilitate cooperative data forwarding from MCs to theMR. An analytical model for estimating the average data-gathering latency in HiCoDG was also designed. Simulations were performed to compare the performance of the IS and CMS variants, as well as a multiple traveling salesman problem (mTSP-based approach. The simulation results show that HiCoDG outperformsmTSP in terms of latency. The results also show that CMS can achieve the lowest latency with low energy consumption.

  9. Hierarchal Variable Switching Sets of Interacting Multiple Model for Tracking Maneuvering Targets in Sensor Network

    Directory of Open Access Journals (Sweden)

    Seham Moawoud Ay Ebrahim

    2013-01-01

    Full Text Available Tracking maneuvering targets introduce two major directions to improve the Multiple Model (MM approach: Develop a better MM algorithm and design a better model set. The Interacting Multiple Model (IMM estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is the ability to estimate the state of a dynamic system with several behavior modes which can "switch" from one to another. In particular, the use of too many models is performance-wise as bad as that of too few models. In this paper we show that the use of too many models is performance-wise as bad as that of too few models. To overcome this we divide the models into a small number of sets, tuning these sets during operation at the right operating set. We proposed Hierarchal Switching sets of IMM (HSIMM. The state space of the nonlinear variable is divided into sets each set has its own IMM. The connection between them is the switching algorithm which manages the activation and termination of sets. Also the re-initialization process overcomes the error accumulation due to the targets changes from one model to another. This switching can introduce a number of different models while no restriction on their number. The activation of sets depends on the threshold value of set likely hood. As the likely hood of the set is higher than threshold it is active otherwise it is minimized. The result is the weighted sum of the output of active sets. The computational time is minimum than introduced by IMM and VIMM. HSIMM introduces less error as the noise increase and there is no need for re adjustment to the Covariance as the noise increase so it is more robust against noise and introduces minimum computational time.

  10. Hierarchical folding of multiple sequence alignments for the prediction of structures and RNA-RNA interactions

    Directory of Open Access Journals (Sweden)

    Gorodkin Jan

    2010-05-01

    Full Text Available Abstract Background Many regulatory non-coding RNAs (ncRNAs function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting these RNA interactions is essential for functional studies of putative ncRNAs or for the design of artificial RNAs. Many ncRNAs show clear signs of undergoing compensating base changes over evolutionary time. Here, we postulate that a non-negligible part of the existing RNA-RNA interactions contain preserved but covarying patterns of interactions. Methods We present a novel method that takes compensating base changes across the binding sites into account. The algorithm works in two steps on two pre-generated multiple alignments. In the first step, individual base pairs with high reliability are found using the PETfold algorithm, which includes evolutionary and thermodynamic properties. In step two (where high reliability base pairs from step one are constrained as unpaired, the principle of cofolding is combined with hierarchical folding. The final prediction of intra- and inter-molecular base pairs consists of the reliabilities computed from the constrained expected accuracy scoring, which is an extended version of that used for individual multiple alignments. Results We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNA-RNA interaction prediction methods is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach.

  11. HiCoDG: a hierarchical data-gathering scheme using cooperative multiple mobile elements.

    Science.gov (United States)

    Van Le, Duc; Oh, Hoon; Yoon, Seokhoon

    2014-12-17

    In this paper, we study mobile element (ME)-based data-gathering schemes in wireless sensor networks. Due to the physical speed limits of mobile elements, the existing data-gathering schemes that use mobile elements can suffer from high data-gathering latency. In order to address this problem, this paper proposes a new hierarchical and cooperative data-gathering (HiCoDG) scheme that enables multiple mobile elements to cooperate with each other to collect and relay data. In HiCoDG, two types of mobile elements are used: the mobile collector (MC) and the mobile relay (MR). MCs collect data from sensors and forward them to the MR, which will deliver them to the sink. In this work, we also formulated an integer linear programming (ILP) optimization problem to find the optimal trajectories for MCs and the MR, such that the traveling distance of MEs is minimized. Two variants of HiCoDG, intermediate station (IS)-based and cooperative movement scheduling (CMS)-based, are proposed to facilitate cooperative data forwarding from MCs to the MR. An analytical model for estimating the average data-gathering latency in HiCoDG was also designed. Simulations were performed to compare the performance of the IS and CMS variants, as well as a multiple traveling salesman problem (mTSP)-based approach. The simulation results show that HiCoDG outperforms mTSP in terms of latency. The results also show that CMS can achieve the lowest latency with low energy consumption.

  12. Continued Kinematic and Photometric Investigations of Hierarchical Solar-type Multiple Star Systems

    Science.gov (United States)

    Roberts, Lewis C., Jr.; Tokovinin, Andrei; Mason, Brian D.; Marinan, Anne D.

    2017-03-01

    We observed 15 of the solar-type binaries within 67 pc of the Sun previously observed by the Robo-AO system in the visible, with the PHARO near-infrared camera and the PALM-3000 adaptive optics system on the 5 m Hale telescope. The physical status of the binaries is confirmed through common proper motion and detection of orbital motion. In the process, we detected a new candidate companion to HIP 95309. We also resolved the primary of HIP 110626 into a close binary, making that system a triple. These detections increase the completeness of the multiplicity survey of the solar-type stars within 67 pc of the Sun. Combining our observations of HIP 103455 with archival astrometric measurements and RV measurements, we are able to compute the first orbit of HIP 103455, showing that the binary has a 68 year period. We place the components on a color–magnitude diagram and discuss each multiple system individually.

  13. Object naming at multiple hierarchical levels: a comparison of preschoolers with and without word-finding deficits.

    Science.gov (United States)

    McGregor, K K; Waxman, S R

    1998-06-01

    According to the storage hypothesis (Kail & Leonard, 1986), word-finding deficits in young children are not the direct results of deficient retrieval strategies; they are a manifestation of a general delay in language development that affects lexical storage. In the current study, we explored one aspect of lexical storage, the hierarchical organization of the semantic system, in 13 preschoolers with word-finding deficits (WF) and 13 preschoolers with normal language abilities (ND), ranging in age from 3;3 to 6;7. The children named a series of objects at multiple levels of the noun hierarchy in response to contrast questions (e.g. for rose they were asked, 'Is this an animal?' to elicit plant [superordinate]; 'Is this a tree?' to elicit flower [basic]; 'Is this a dandelion?' to elicit rose [subordinate]). Both groups readily named at multiple levels, providing evidence of hierarchical organization of the lexicon. However, there were several differences between WF and ND groups that suggested that WF children did not have enough stored information to discriminate between similar semantic neighbours. We conclude (1) that hierarchical organization of the semantic lexicon is a robust developmental phenomenon, apparent in both ND and WF preschoolers and (2) that the word-finding deficits of preschoolers appear to reflect insufficient depth and breadth of storage elaboration rather than deficits in hierarchical semantic organization.

  14. Time and temperature dependent multiple hierarchical NiCo2O4 for high-performance supercapacitors.

    Science.gov (United States)

    Wang, Shen; Sun, Shumin; Li, Shaodan; Gong, Feilong; Li, Yannan; Wu, Qiong; Song, Pei; Fang, Shaoming; Wang, Peiyuan

    2016-05-07

    A multiple hierarchical NiCo2O4 (denoted as P-100), which was constructed of nanosheets covered with nanowires, was obtained by a facial hydrothermal method in combination with annealing treatment at 300 °C. The hydrothermal temperature and reaction time play key roles in the formation of the unique hierarchical NiCo2O4 based on the morphology evolution. As a supercapacitor electrode material, the obtained P-100 displays a high specific capacitance of 1393 F g(-1) at 0.5 A g(-1). Furthermore, the assembled P-100//AC asymmetric supercapacitor demonstrates a high energy density (21.4 Wh kg(-1)) at a power density of 350 W kg(-1) and remarkable cycling stability. The good electrochemical performances of the P-100 are mainly due to its three dimensional hierarchical porous nanostructure and high specific surface area as well as the synergetic effect of the nanosheets and nanowires in NiCo2O4. The experimental results demonstrated that the multiple hierarchical NiCo2O4 is a promising electrode material for high-performance supercapacitors.

  15. Beyond Adapting to Climate Change: Embedding Adaptation in Responses to Multiple Threats and Stresses

    Energy Technology Data Exchange (ETDEWEB)

    Wilbanks, Thomas J [ORNL; Kates, Dr. Robert W. [Independent Scholar, Bangor, Maine

    2010-01-01

    Climate change impacts are already being experienced in every region of the United States and every part of the world most severely in Arctic regions and adaptation is needed now. Although climate change adaptation research is still in its infancy, significant adaptation planning in the United States has already begun in a number of localities. This article seeks to broaden the adaptation effort by integrating it with broader frameworks of hazards research, sustainability science, and community and regional resilience. To extend the range of experience, we draw from ongoing case studies in the Southeastern United States and the environmental history of New Orleans to consider the multiple threats and stresses that all communities and regions experience. Embedding climate adaptation in responses to multiple threats and stresses helps us to understand climate change impacts, themselves often products of multiple stresses, to achieve community acceptance of needed adaptations as co-benefits of addressing multiple threats, and to mainstream the process of climate adaptation through the larger envelope of social relationships, communication channels, and broad-based awareness of needs for risk management that accompany community resilience.

  16. Multiple dynamical time-scales in networks with hierarchically nested modular organization

    Indian Academy of Sciences (India)

    Sitabhra Sinha; Swarup Poria

    2011-11-01

    Many natural and engineered complex networks have intricate mesoscopic organization, e.g., the clustering of the constituent nodes into several communities or modules. Often, such modularity is manifested at several different hierarchical levels, where the clusters defined at one level appear as elementary entities at the next higher level. Using a simple model of a hierarchical modular network, we show that such a topological structure gives rise to characteristic time-scale separation between dynamics occurring at different levels of the hierarchy. This generalizes our earlier result for simple modular networks, where fast intramodular and slow intermodular processes were clearly distinguished. Investigating the process of synchronization of oscillators in a hierarchical modular network, we show the existence of as many distinct time-scales as there are hierarchical levels in the system. This suggests a possible functional role of such mesoscopic organization principle in natural systems, viz., in the dynamical separation of events occurring at different spatial scales.

  17. A High-Transmission, Multiple Antireflective Surface Inspired from Bilayer 3D Ultrafine Hierarchical Structures in Butterfly Wing Scales.

    Science.gov (United States)

    Han, Zhiwu; Mu, Zhengzhi; Li, Bo; Niu, Shichao; Zhang, Junqiu; Ren, Luquan

    2016-02-10

    A high-transmission, multiple antireflective surface inspired by bilayer 3D ultrafine hierarchical structures in butterfly wing scales is fabricated on a glass substrate using wet chemical biomimetic fabrication. Interestingly, the biomimetic antireflective surface exhibits excellent antireflective properties and high transmission, which provides better characteristics than the butterfly wings and can significantly reduce reflection without losing transparency. These findings offer a new path for generating nanostructured antireflectors with high transmission properties.

  18. A new adaptive filtering algorithm for systems with multiplicative noise

    Institute of Scientific and Technical Information of China (English)

    WANG Hui-li; CHEN Xi-xin; LU Qian-hao

    2005-01-01

    Presented here is a new adaptive state filtering algorithm for systems with multiplicative noise. This algorithm estimates the vector state of the system and the statistics of noise when all the statistics of noise are unknown. This filtering algorithm is a simple recursive structure. A simulation example is presented which demonstrates the effectiveness of this filtering algorithm.

  19. Combining Adaptive Coding and Modulation with Hierarchical Modulation in Satcom Systems

    CERN Document Server

    Meric, Hugo; Arnal, Fabrice; Lesthievent, Guy; Boucheret, Marie-Laure

    2011-01-01

    We investigate the design of a broadcast system in order to maximise the throughput. This task is usually challenging due to the channel variability. Forty years ago, Cover introduced and compared two schemes: time sharing and superposition coding. Even if the second scheme was proved to be optimal for some channels, modern satellite communications systems such as DVB-SH and DVB-S2 mainly rely on time sharing strategy to optimize the throughput. They consider hierarchical modulation, a practical implementation of superposition coding, but only for unequal error protection or backward compatibility purposes. We propose in this article to combine time sharing and hierarchical modulation together and show how this scheme can improve the performance in terms of available rate. We introduce the hierarchical 16-APSK to boost the performance of the DVB-S2 standard. We also evaluate various strategies to group the receivers in pairs when using hierarchical modulation. Finally, we show in a realistic use case based on...

  20. Hierarchical adaptive nanostructured PVD coatings for extreme tribological applications: the quest for nonequilibrium states and emergent behavior

    Directory of Open Access Journals (Sweden)

    German S Fox-Rabinovich, Kenji Yamamoto, Ben D Beake, Iosif S Gershman, Anatoly I Kovalev, Stephen C Veldhuis, Myram H Aguirre, Goulnara Dosbaeva and Jose L Endrino

    2012-01-01

    Full Text Available Adaptive wear-resistant coatings produced by physical vapor deposition (PVD are a relatively new generation of coatings which are attracting attention in the development of nanostructured materials for extreme tribological applications. An excellent example of such extreme operating conditions is high performance machining of hard-to-cut materials. The adaptive characteristics of such coatings develop fully during interaction with the severe environment. Modern adaptive coatings could be regarded as hierarchical surface-engineered nanostructural materials. They exhibit dynamic hierarchy on two major structural scales: (a nanoscale surface layers of protective tribofilms generated during friction and (b an underlying nano/microscaled layer. The tribofilms are responsible for some critical nanoscale effects that strongly impact the wear resistance of adaptive coatings. A new direction in nanomaterial research is discussed: compositional and microstructural optimization of the dynamically regenerating nanoscaled tribofilms on the surface of the adaptive coatings during friction. In this review we demonstrate the correlation between the microstructure, physical, chemical and micromechanical properties of hard coatings in their dynamic interaction (adaptation with environment and the involvement of complex natural processes associated with self-organization during friction. Major physical, chemical and mechanical characteristics of the adaptive coating, which play a significant role in its operating properties, such as enhanced mass transfer, and the ability of the layer to provide dissipation and accumulation of frictional energy during operation are presented as well. Strategies for adaptive nanostructural coating design that enhance beneficial natural processes are outlined. The coatings exhibit emergent behavior during operation when their improved features work as a whole. In this way, as higher-ordered systems, they achieve multifunctionality

  1. Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects.

    Directory of Open Access Journals (Sweden)

    Nengjun Yi

    2011-12-01

    Full Text Available Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The proposed hierarchical generalized linear models introduce a group effect and a genetic score (i.e., a linear combination of main-effect predictors for genetic variants for each group of variants, and jointly they estimate the group effects and the weights of the genetic scores. This framework includes various previous methods as special cases, and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance. Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models, leading to the development of stable and flexible tools. The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/.

  2. Hierarchical Generalized Linear Models for Multiple Groups of Rare and Common Variants: Jointly Estimating Group and Individual-Variant Effects

    Science.gov (United States)

    Yi, Nengjun; Liu, Nianjun; Zhi, Degui; Li, Jun

    2011-01-01

    Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The proposed hierarchical generalized linear models introduce a group effect and a genetic score (i.e., a linear combination of main-effect predictors for genetic variants) for each group of variants, and jointly they estimate the group effects and the weights of the genetic scores. This framework includes various previous methods as special cases, and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance. Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models, leading to the development of stable and flexible tools. The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). PMID:22144906

  3. Evaluation by hierarchical clustering of multiple cytokine expression after phytohemagglutinin stimulation

    Directory of Open Access Journals (Sweden)

    Yang Chunhe

    2016-01-01

    Full Text Available The hierarchical clustering method has been used for exploration of gene expression and proteomic profiles; however, little research into its application in the examination of expression of multiplecytokine/chemokine responses to stimuli has been reported. Thus, little progress has been made on how phytohemagglutinin(PHA affects cytokine expression profiling on a large scale in the human hematological system. To investigate the characteristic expression pattern under PHA stimulation, Luminex, a multiplex bead-based suspension array, was performed. The data set collected from human peripheral blood mononuclear cells (PBMC was analyzed using the hierarchical clustering method. It was revealed that two specific chemokines (CCL3 andCCL4 underwent significantly greater quantitative changes during induction of expression than other tested cytokines/chemokines after PHA stimulation. This result indicates that hierarchical clustering is a useful tool for detecting fine patterns during exploration of biological data, and that it can play an important role in comparative studies.

  4. ADAPTIVE HIERARCHICAL DENSE MATCHING OF MULTI-VIEW AIRBORNE OBLIQUE IMAGERY

    Directory of Open Access Journals (Sweden)

    Z. C. Zhang

    2015-03-01

    Full Text Available Traditional single-lens vertical photogrammetry can obtain object images from the air with rare lateral information of tall buildings. Multi-view airborne photogrammetry can get rich lateral texture of buildings, while the common area-based matching for oblique images may lose efficacy because of serious geometric distortion. A hierarchical dense matching algorithm is put forward here to match two oblique airborne images of different perspectives. Based on image hierarchical strategy and matching constraints, this algorithm delivers matching results from the upper layer of the pyramid to the below and implements per-pixel dense matching in the local Delaunay triangles between the original images. Experimental results show that the algorithm can effectively overcome the geometric distortion between different perspectives and achieve pixel-level dense matching entirely based on the image space.

  5. Improved Multiple Descriptions Sinusoidal Coder Adaptive to Packet Loss Rate

    Institute of Scientific and Technical Information of China (English)

    LANG Yue; WANG Jing; ZHAO Sheng-hui; KUANG Jing-ming

    2008-01-01

    To make the multiple descriptions codec adaptive to the packet loss rate, which can minimize the final distortion, a novel adaptive multiple descriptions sinusoidal coder (AMDSC) is proposed, which is based on a sinusoidal model and a noise model. Firstly, the sinusoidal parameters are extracted in the sinusoidal model, and ordered in a decrease manner. Odd indexed and even indexed parameters are divided into two descriptions. Secondly, the output vector from the noise model is split vector quantized. And the two sub-vectors are placed into two descriptions too. Finally, the number of the extracted parameters and the redundancy between the two descriptions are adjusted according to the packet loss rate of the network. Analytical and experimental results show that the proposed AMDSC outperforms existing MD speech coders by taking network loss characteristics into account. Therefore, it is very suitable for unreliable channels.

  6. Adaptive Threshold Median Filter for Multiple-Impulse Noise

    Institute of Scientific and Technical Information of China (English)

    JIANG Bo; HUANG Wei

    2007-01-01

    Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter(ATMF) has been developed by combining the adaptive median filter (AMF) and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed Filter.

  7. Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

    Science.gov (United States)

    Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

  8. Hierarchical Multiple Regression in Counseling Research: Common Problems and Possible Remedies.

    Science.gov (United States)

    Petrocelli, John V.

    2003-01-01

    A brief content analysis was conducted on the use of hierarchical regression in counseling research published in the "Journal of Counseling Psychology" and the "Journal of Counseling & Development" during the years 1997-2001. Common problems are cited and possible remedies are described. (Contains 43 references and 3 tables.) (Author)

  9. Nonstationary Interference Excision in Time-Frequency Domain Using Adaptive Hierarchical Lapped Orthogonal Transform for Direct Sequence Spread Spectrum Communications

    Directory of Open Access Journals (Sweden)

    Zhu Yi-Sheng

    2003-01-01

    Full Text Available An adaptive hierarchical lapped orthogonal transform (HLOT exciser is proposed for tracking, localizing, and rejecting the nonstationary interference in direct sequence spread spectrum (DSSS communications. The method is based on HLOT. It utilizes a fast dynamic programming algorithm to search for the best basis, which matches the interference structure best, in a library of lapped orthogonal bases. The adaptive HLOT differs from conventional block transform and the more advanced modulated lapped transform (MLT in that the former produces arbitrary time-frequency tiling, which can be adapted to the signal structure, while the latter yields fixed tilings. The time-frequency tiling of the adaptive HLOT can be time varying, so it is also able to track the variations of the signal time-frequency structure. Simulation results show that the proposed exciser brings significant performance improvement in the presence of nonstationary time-localized interference with or without instantaneous frequency (IF information compared with the existing block transform domain excisers. Also, the proposed exciser is effective in suppressing narrowband interference and combined narrowband and time-localized impulsive interference.

  10. Adaptive Hierarchical B-spline Surface Representation of Large-Scale Scattered Data

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The representation of large scale scattered data is a difficult problem, especially when various features of the representation, such as C2-continuity, are required. This paper describes a fast algorithm for large scale scattered data approximation and interpolation. The interpolation algorithm uses a coarse-to-fine hierarchical control lattice to fit the scattered data. The refinement process is only used in the regions where the error between the scattered data and the result in a surface is greater than a specified tolerance. A method to ensure C2-continuity is introduced to calculate the control lattice under constrained conditions. Experimental results show that this method can quickly represent large scale scattered data set.

  11. Adaptive synchronization of asymmetric coupled networks with multiple coupling delays

    Science.gov (United States)

    Sun, Weiwei; Hao, Fei; Chen, Xia

    2012-05-01

    The synchronization problem of asymmetric networks with multiple coupled delays is investigated in this paper. By using Lyapunov stability theory and Lasalle's invariance principle, several synchronization criteria are deduced for both asymmetric networks with and without norm uncertainties. Furthermore, the synchronization problem of a special complex network with each node being a Lurie system is studied. The main results show that the states of all nodes of networks globally asymptotically synchronize to a desired synchronization state by designing suitable adaptive controllers, and these controllers have strong robustness against the uncertain coupling matrixes. Finally, several illustrative examples with numerical simulations are given to show the feasibility and efficiency of theoretical results.

  12. Phylo-mLogo: an interactive and hierarchical multiple-logo visualization tool for alignment of many sequences

    Directory of Open Access Journals (Sweden)

    Lee DT

    2007-02-01

    Full Text Available Abstract Background When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences. Results A multiple-logo alignment visualization tool, called Phylo-mLogo, is presented in this paper. Phylo-mLogo calculates the variabilities and homogeneities of alignment sequences by base frequencies or entropies. Different from the traditional representations of sequence logos, Phylo-mLogo not only displays the global logo patterns of the whole alignment of multiple sequences, but also demonstrates their local homologous logos for each clade hierarchically. In addition, Phylo-mLogo also allows the user to focus only on the analysis of some important, structurally or functionally constrained sites in the alignment selected by the user or by built-in automatic calculation. Conclusion With Phylo-mLogo, the user can symbolically and hierarchically visualize hundreds of aligned sequences simultaneously and easily check the changes of their amino acid sites when analyzing many homologous/orthologous or influenza virus sequences. More information of Phylo-mLogo can be found at URL http://biocomp.iis.sinica.edu.tw/phylomlogo.

  13. Globular cluster formation with multiple stellar populations from hierarchical star cluster complexes

    Science.gov (United States)

    Bekki, Kenji

    2017-01-01

    Most old globular clusters (GCs) in the Galaxy are observed to have internal chemical abundance spreads in light elements. We discuss a new GC formation scenario based on hierarchical star formation within fractal molecular clouds. In the new scenario, a cluster of bound and unbound star clusters (`star cluster complex', SCC) that have a power-law cluster mass function with a slope (β) of 2 is first formed from a massive gas clump developed in a dwarf galaxy. Such cluster complexes and β = 2 are observed and expected from hierarchical star formation. The most massive star cluster (`main cluster'), which is the progenitor of a GC, can accrete gas ejected from asymptotic giant branch (AGB) stars initially in the cluster and other low-mass clusters before the clusters are tidally stripped or destroyed to become field stars in the dwarf. The SCC is initially embedded in a giant gas hole created by numerous supernovae of the SCC so that cold gas outside the hole can be accreted onto the main cluster later. New stars formed from the accreted gas have chemical abundances that are different from those of the original SCC. Using hydrodynamical simulations of GC formation based on this scenario, we show that the main cluster with the initial mass as large as [2 - 5] × 105M⊙ can accrete more than 105M⊙ gas from AGB stars of the SCC. We suggest that merging of hierarchical star cluster complexes can play key roles in stellar halo formation around GCs and self-enrichment processes in the early phase of GC formation.

  14. Multiple centroid method to evaluate the adaptability of alfalfa genotypes

    Directory of Open Access Journals (Sweden)

    Moysés Nascimento

    2015-02-01

    Full Text Available This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.. In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data. In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.

  15. Adaptive mixture observation models for multiple object tracking

    Institute of Scientific and Technical Information of China (English)

    CUI Peng; SUN LiFeng; YANG ShiQiang

    2009-01-01

    Multiple object tracking (MOT) poses many difficulties to conventional well-studied single object track-ing (SOT) algorithms, such as severe expansion of configuration space, high complexity of motion con-ditions, and visual ambiguities among nearby targets, among which the visual ambiguity problem is the central challenge. In this paper, we address this problem by embedding adaptive mixture observation models (AMOM) into a mixture tracker which is implemented in Particle Filter framework. In AMOM, the extracted multiple features for appearance description are combined according to their discriminative power between ambiguity prone objects, where the discriminability of features are evaluated by online entropy-based feature selection techniques. The induction of AMOM can help to surmount the Incapa-bility of conventional mixture tracker in handling object occlusions, and meanwhile retain its merits of flexibility and high efficiency. The final experiments show significant improvement in MOT scenarios compared with other methods.

  16. RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations.

    Science.gov (United States)

    Castro, Mauro A A; Wang, Xin; Fletcher, Michael N C; Meyer, Kerstin B; Markowetz, Florian

    2012-04-24

    Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html.

  17. Keck Adaptive Optics Imaging of Nearby Young Stars: Detection of Close Multiple Systems

    CERN Document Server

    Brandeker, A; Najita, J R; Brandeker, Alexis; Jayawardhana, Ray; Najita, Joan

    2003-01-01

    Using adaptive optics on the Keck II 10-meter telescope on Mauna Kea, we have surveyed 24 of the nearest young stars known in search of close companions. Our sample includes members of the MBM 12 and TW Hydrae young associations and the classical T Tauri binary UY Aurigae in the Taurus star-forming region. We present relative photometry and accurate astrometry for 10 close multiple systems. The multiplicity frequency in the TW Hydrae and MBM 12 groups are high in comparison to other young regions, though the significance of this result is low because of the small number statistics. We resolve S 18 into a triple system including a tight 63 mas (projected separation of 17 AU at a distance of 275 pc) binary for the first time, with a hierarchical configuration reminiscent of VW Chamaeleontis and T Tauri. Another tight binary in our sample -- TWA 5Aab (54 mas or 3 AU at 55 pc) -- offers the prospect of dynamical mass measurement using astrometric observations within a few years, and thus could be important for te...

  18. Adaptive Hierarchical Control for the Muscle Strength Training of Stroke Survivors in Robot-aided Upper-limb Rehabilitation

    Directory of Open Access Journals (Sweden)

    Guozheng Xu

    2012-10-01

    Full Text Available Muscle strength training for stroke patients is of vital importance for helping survivors to progressively restore muscle strength and improve the performance of their activities in daily living (ADL. An adaptive hierarchical therapy control framework which integrates the patient’s real biomechanical state estimation with task‐performance quantitative evaluation is proposed. Firstly, a high‐level progressive resistive supervisory controller is designed to determine the resistive force base for each training session based on the patient’s online task‐performance evaluation. Then, a low‐level adaptive resistive force triggered controller is presented to further regulate the interactive resistive force corresponding to the patient’s real‐time biomechanical state ‐ characterized by the patient’s bio‐damping and bio‐stiffness in the course of one training session, so that the patient is challenged in a moderate but engaging and motivating way. Finally, a therapeutic robot system using a Barrett WAMTM compliant manipulator is set up. We recruited eighteen inpatient and outpatient stroke participants who were randomly allocated in experimental (robot‐aided and control (conventional physical therapy groups and enrolled for sixteen weeks of progressive resistance training. The preliminary results show that the proposed therapy control strategies can enhance the recovery of strength and motor control ability.

  19. Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming

    Institute of Scientific and Technical Information of China (English)

    Ming BAI; Yan ZHUANG; Wei WANG

    2009-01-01

    An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points(GCPs) is presented.To decrease time complexity without losing matching precision,using a multilevel search scheme,the coarse matching is processed in typical disparity space image,while the fine matching is processed in disparity-offset space image.In the upper level,GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint.Under the supervision of the highly reliable GCPs,bidirec-tional dynamic programming framework is employed to solve the inconsistency in the optimization path.In the lower level,to reduce running time,disparity-offset space is proposed to efficiently achieve the dense disparity image.In addition,an adaptive dual support-weight strategy is presented to aggregate matching cost,which considers photometric and geomet-ric information.Further,post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm,where missing stereo information is substituted from surrounding re-gions.To demonstrate the effectiveness of the algorithm,we present the two groups of experimental results for four widely used standard stereo data sets,including discussion on performance and comparison with other methods,which show that the algorithm has not only a fast speed,but also significantly improves the efficiency of holistic optimization.

  20. Adaptive social recommendation in a multiple category landscape

    CERN Document Server

    Chen, Duanbing; Cimini, Giulio; Zhang, Yi-Cheng

    2012-01-01

    People in the Internet era have to cope with the information overload, striving to find what they are interested in, and usually face this situation by following a limited number of sources or friends that best match their interests. A recent line of research, namely adaptive social recommendation, has therefore emerged to optimize the information propagation in social networks and provide users with personalized recommendations. Validation of these methods by agent-based simulations often assumes that the tastes of users and can be represented by binary vectors, with entries denoting users' preferences. In this work we introduce a more realistic assumption that users' tastes are modeled by multiple vectors. We show that within this framework the social recommendation process has a poor outcome. Accordingly, we design novel measures of users' taste similarity that can substantially improve the precision of the recommender system. Finally, we discuss the issue of enhancing the recommendations' diversity while ...

  1. Classification of multiple sclerosis lesions using adaptive dictionary learning.

    Science.gov (United States)

    Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

    2015-12-01

    This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification.

  2. Multiple Computing Task Scheduling Method Based on Dynamic Data Replication and Hierarchical Strategy

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    2014-02-01

    Full Text Available As for the problem of how to carry out task scheduling and data replication effectively in the grid and to reduce task’s execution time, this thesis proposes the task scheduling algorithm and the optimum dynamic data replication algorithm and builds a scheme to effectively combine these two algorithms. First of all, the scheme adopts the ISS algorithm considering the number of tasks waiting queue, the location of task demand data and calculation capacity of site by adopting the method of network structure’s hierarchical scheduling to calculate the cost of comprehensive task with the proper weight efficiency and search out the best compute node area. And then the algorithm of ODHRA is adopted to analyze the data transmission time, memory access latency, waiting copy requests in the queue and the distance between nodes, choose out the best replications location in many copies combined with copy placement and copy management to reduce the file access time. The simulation results show that the proposed scheme compared with other algorithm has better performance in terms of average task execution time. 

  3. Multiple representations and mechanisms for visuomotor adaptation in young children.

    Science.gov (United States)

    Tahej, Pierre-Karim; Ferrel-Chapus, Carole; Olivier, Isabelle; Ginhac, Dominique; Rolland, Jean-Pierre

    2012-12-01

    In this study, we utilized transformed spatial mappings to perturb visuomotor integration in 5-yr-old children and adults. The participants were asked to perform pointing movements under five different conditions of visuomotor rotation (from 0° to 180°), which were designed to reveal explicit vs. implicit representations as well as the mechanisms underlying the visual-motor mapping. Several tests allowed us to separately evaluate sensorimotor (i.e., the dynamic dimension of movement) and cognitive (i.e., the explicit representations of target position and the strategies used by the participants) representations of visuo-proprioceptive distortion. Our results indicate that children do not establish representations in the same manner as adults and that children exhibit multiple visuomotor representations. Sensorimotor representations were relatively precise, presumably due to the recovery of proprioceptive information and efferent copy. Furthermore, a bidirectional mechanism was used to re-map visual and motor spaces. In contrast, cognitive representations were supplied with visual information and followed a unidirectional visual-motor mapping. Therefore, it appears that sensorimotor mechanisms develop before the use of explicit strategies during development, and young children showed impaired visuomotor adaptation when confronted with large distortions.

  4. Adaptive multiple subtraction with wavelet-based complex unary Wiener filters

    CERN Document Server

    Ventosa, Sergi; Huard, Irène; Pica, Antonio; Rabeson, Hérald; Ricarte, Patrice; Duval, Laurent

    2011-01-01

    Multiple attenuation is a crucial task in seismic data processing because multiples usually cover primaries from fundamental reflectors. Predictive multiple suppression methods remove these multiples by building an adapted model, aiming at being subtracted from the original signal. However, before the subtraction is applied, a matching filter is required to minimize amplitude differences and misalignments between actual multiples and their prediction, and thus to minimize multiples in the input dataset after the subtraction. In this work we focus on the subtraction element. We propose an adaptive multiple removal technique in a 1-D complex wavelet frame combined with a non-stationary adaptation performed via single-sample (unary) Wiener filters, consistently estimated on overlapping windows in the transformed domain. This approach greatly simplifies the matching filter estimation and, despite its simplicity, compares promisingly with standard adaptive 2-D methods, both in terms of results and retained speed a...

  5. A hierarchical model to estimate fish abundance in alpine streams by using removal sampling data from multiple locations.

    Science.gov (United States)

    Laplanche, Christophe

    2010-04-01

    The author compares 12 hierarchical models in the aim of estimating the abundance of fish in alpine streams by using removal sampling data collected at multiple locations. The most expanded model accounts for (i) variability of the abundance among locations, (ii) variability of the catchability among locations, and (iii) residual variability of the catchability among fish. Eleven model reductions are considered depending which variability is included in the model. The more restrictive model considers none of the aforementioned variabilities. Computations of the latter model can be achieved by using the algorithm presented by Carle and Strub (Biometrics 1978, 34, 621-630). Maximum a posteriori and interval estimates of the parameters as well as the Akaike and the Bayesian information criterions of model fit are computed by using samples simulated by a Markov chain Monte Carlo method. The models are compared by using a trout (Salmo trutta fario) parr (0+) removal sampling data set collected at three locations in the Pyrénées mountain range (Haute-Garonne, France) in July 2006. Results suggest that, in this case study, variability of the catchability is not significant, either among fish or locations. Variability of the abundance among locations is significant. 95% interval estimates of the abundances at the three locations are [0.15, 0.24], [0.26, 0.36], and [0.45, 0.58] parrs per m(2). Such differences are likely the consequence of habitat variability.

  6. Structuring Climate Adaptation through Multiple Perspectives: Framework and Case Study on Flood Risk Management

    Directory of Open Access Journals (Sweden)

    Mohanasundar Radhakrishnan

    2017-02-01

    Full Text Available Adaptation to climate change is being addressed in many domains. This means that there are multiple perspectives on adaptation; often with differing visions resulting in disconnected responses and outcomes. Combining singular perspectives into coherent, combined perspectives that include multiple needs and visions can help to deepen the understanding of various aspects of adaptation and provide more effective responses. Such combinations of perspectives can help to increase the range and variety of adaptation measures available for implementation or avoid maladaptation compared with adaptations derived from a singular perspective. The objective of this paper is to present and demonstrate a framework for structuring the local adaptation responses using the inputs from multiple perspectives. The adaptation response framing has been done by: (i contextualizing climate change adaptation needs; (ii analyzing drivers of change; (iii characterizing measures of adaptation; and (iv establishing links between the measures with a particular emphasis on taking account of multiple perspectives. This framework was demonstrated with reference to the management of flood risks in a case study Can Tho, Vietnam. The results from the case study show that framing of adaptation responses from multiple perspectives can enhance the understanding of adaptation measures, thereby helping to bring about more flexible implementation practices.

  7. Fibrin Networks Support Recurring Mechanical Loads by Adapting their Structure across Multiple Scales.

    Science.gov (United States)

    Kurniawan, Nicholas A; Vos, Bart E; Biebricher, Andreas; Wuite, Gijs J L; Peterman, Erwin J G; Koenderink, Gijsje H

    2016-09-06

    Tissues and cells sustain recurring mechanical loads that span a wide range of loading amplitudes and timescales as a consequence of exposure to blood flow, muscle activity, and external impact. Both tissues and cells derive their mechanical strength from fibrous protein scaffolds, which typically have a complex hierarchical structure. In this study, we focus on a prototypical hierarchical biomaterial, fibrin, which is one of the most resilient naturally occurring biopolymers and forms the structural scaffold of blood clots. We show how fibrous networks composed of fibrin utilize irreversible changes in their hierarchical structure at different scales to maintain reversible stress stiffening up to large strains. To trace the origin of this paradoxical resilience, we systematically tuned the microstructural parameters of fibrin and used a combination of optical tweezers and fluorescence microscopy to measure the interactions of single fibrin fibers for the first time, to our knowledge. We demonstrate that fibrin networks adapt to moderate strains by remodeling at the network scale through the spontaneous formation of new bonds between fibers, whereas they adapt to high strains by plastic remodeling of the fibers themselves. This multiscale adaptation mechanism endows fibrin gels with the remarkable ability to sustain recurring loads due to shear flows and wound stretching. Our findings therefore reveal a microscopic mechanism by which tissues and cells can balance elastic nonlinearity and plasticity, and thus can provide microstructural insights into cell-driven remodeling of tissues.

  8. Adaptive switching control of discrete time nonlinear systems based on multiple models

    Institute of Scientific and Technical Information of China (English)

    Rui KAN

    2004-01-01

    We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.

  9. MI-ANFIS: A Multiple Instance Adaptive Neuro-Fuzzy Inference System

    Science.gov (United States)

    2015-08-02

    16. SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6...Instance AdaptiveNeuro-Fuzzy Inference System We introduce a novel adaptive neuro -fuzzy architecture based on the framework of Multiple Instance Fuzzy...Inference. The new architecture called Multiple Instance-ANFIS (MI-ANFIS), is an extension of the standard Adaptive Neuro Fuzzy Inference System (ANFIS

  10. Generating a Style-Adaptive Trajectory from Multiple Demonstrations

    Directory of Open Access Journals (Sweden)

    Yue Zhao

    2014-07-01

    Full Text Available Trajectory learning and generation from demonstration have been widely discussed in recent years, with promising progress made. Existing approaches, including the Gaussian Mixture Model (GMM, affine functions and Dynamic Movement Primitives (DMPs have proven their applicability to learning the features and styles of existing trajectories and generating similar trajectories that can adapt to different dynamic situations. However, in many applications, such as grasping an object, shooting a ball, etc., different goals require trajectories of different styles. An issue that must be resolved is how to reproduce a trajectory with a suitable style. In this paper, we propose a style-adaptive trajectory generation approach based on DMPs, by which the style of the reproduced trajectories can change smoothly as the new goal changes. The proposed approach first adopts a Point Distribution Model (PDM to get the principal trajectories for different styles, then learns the model of each principal trajectory independently using DMPs, and finally adapts the parameters of the trajectory model smoothly according to the new goal using an adaptive goal-to-style mechanism. This paper further discusses the application of the approach on small-sized robots for an adaptive shooting task and on a humanoid robot arm to generate motions for table tennis-playing with different styles.

  11. Generating a Style-adaptive Trajectory from Multiple Demonstrations

    Directory of Open Access Journals (Sweden)

    Yue Zhao

    2014-07-01

    Full Text Available Trajectory learning and generation from demonstration have been widely discussed in recent years, with promising progress made. Existing approaches, including the Gaussian Mixture Model (GMM, affine functions and Dynamic Movement Primitives (DMPs have proven their applicability to learning the features and styles of existing trajectories and generating similar trajectories that can adapt to different dynamic situations. However, in many applications, such as grasping an object, shooting a ball, etc., different goals require trajectories of different styles. An issue that must be resolved is how to reproduce a trajectory with a suitable style. In this paper, we propose a style-adaptive trajectory generation approach based on DMPs, by which the style of the reproduced trajectories can change smoothly as the new goal changes. The proposed approach first adopts a Point Distribution Model (PDM to get the principal trajectories for different styles, then learns the model of each principal trajectory independently using DMPs, and finally adapts the parameters of the trajectory model smoothly according to the new goal using an adaptive goal-to-style mechanism. This paper further discusses the application of the approach on small-sized robots for an adaptive shooting task and on a humanoid robot arm to generate motions for table tennis-playing with different styles.

  12. Reflections on multiple personality disorder as a developmentally complex adaptation.

    Science.gov (United States)

    Armstrong, J G

    1994-01-01

    Recent advances in the understanding of multiple personality disorder provide the groundwork for its creative reconciliation with psychoanalysis. This paper uses psychoanalytic, modern developmental, and psychological assessment perspectives to conceptualize multiple personality disorder as a developmentally protective response to chronic childhood trauma. Implications of this theory for clinical work with these patients are discussed.

  13. Multiple sites of adaptation lead to contrast encoding in the Drosophila olfactory system.

    Science.gov (United States)

    Cafaro, Jon

    2016-04-01

    Animals often encounter large increases in odor intensity that can persist for many seconds. These increases in the background odor are often accompanied by increases in the variance of the odor stimulus. Previous studies have shown that a persistent odor stimulus (odor background) results in a decrease in the response to brief odor pulses in the olfactory receptor neurons (ORNs). However, the contribution of adapting mechanisms beyond theORNs is not clear. Thus, it is unclear how adaptive mechanisms are distributed within the olfactory circuit and what impact downstream adaptation may have on the encoding of odor stimuli. In this study, adaptation to the same odor stimulus is examined at multiple levels in the well studied and accessibleDrosophilaolfactory system. The responses of theORNs are compared to the responses of the second order, projection neurons (PNs), directly connected to them. Adaptation inPNspike rate was found to be much greater than adaptation in theORNspike rate. This greater adaptation allowsPNs to encode odor contrast (ratio of pulse intensity to background intensity) with little ambiguity. Moreover, distinct neural mechanisms contribute to different aspects of adaptation; adaptation to the background odor is dominated by adaptation in spike generation in bothORNs andPNs, while adaptation to the odor pulse is dominated by changes within olfactory transduction and the glomerulus. These observations suggest that the olfactory system adapts at multiple sites to better match its response gain to stimulus statistics.

  14. Adaptive Image Processing and Implementation by Multiple Microcomputer System.

    Science.gov (United States)

    1980-12-01

    C.R. Jr., " SHARF - An Algorithm for Adapting IIR Digital Filters," IEEE Trans. on Acoustics. Speech and Signal Processing, 1979. 44. Rickard, John T...Postgraduate School Monterey, California 93940 14. Mrs. Atara Rozic 2 6040 Glenarms Drive Oakland, California 94611 15. Mr. Richard Wooten 1 6860 Worth

  15. Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control

    Directory of Open Access Journals (Sweden)

    Simone Baldi

    2013-05-01

    Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.

  16. Adaptive sliding mode formation control of multiple underwater robots

    Directory of Open Access Journals (Sweden)

    Das Bikramaditya

    2014-12-01

    Full Text Available This paper proposes a new adaptive sliding mode control scheme for achieving coordinated motion control of a group of autonomous underwater vehicles with variable added mass. The control law considers the communication constraints in the acoustic medium. A common reference frame for velocity is assigned to a virtual leader dynamically. The performances of the proposed adaptive SMC were compared with that of a passivity based controller. To save the time and traveling distance for reaching the FRP by the follower AUVs, a sliding mode controller is proposed in this paper that drives the state trajectory of the AUV into a switching surface in the state space. It is observed from the obtained results that the proposed SMC provides improved performance in terms of accurately tracking the desired trajectory within less time compared to the passivity based controller. A communication consensus is designed ensuring the transfer of information among the AUVs so that they move collectively as a group. The stability of the overall closed-loop systems are analysed using Lyapunov theory and simulation results confirmed the robustness and efficiency of proposed controller.

  17. Vibrio Iron Transport: Evolutionary Adaptation to Life in Multiple Environments.

    Science.gov (United States)

    Payne, Shelley M; Mey, Alexandra R; Wyckoff, Elizabeth E

    2016-03-01

    Iron is an essential element for Vibrio spp., but the acquisition of iron is complicated by its tendency to form insoluble ferric complexes in nature and its association with high-affinity iron-binding proteins in the host. Vibrios occupy a variety of different niches, and each of these niches presents particular challenges for acquiring sufficient iron. Vibrio species have evolved a wide array of iron transport systems that allow the bacteria to compete for this essential element in each of its habitats. These systems include the secretion and uptake of high-affinity iron-binding compounds (siderophores) as well as transport systems for iron bound to host complexes. Transporters for ferric and ferrous iron not complexed to siderophores are also common to Vibrio species. Some of the genes encoding these systems show evidence of horizontal transmission, and the ability to acquire and incorporate additional iron transport systems may have allowed Vibrio species to more rapidly adapt to new environmental niches. While too little iron prevents growth of the bacteria, too much can be lethal. The appropriate balance is maintained in vibrios through complex regulatory networks involving transcriptional repressors and activators and small RNAs (sRNAs) that act posttranscriptionally. Examination of the number and variety of iron transport systems found in Vibrio spp. offers insights into how this group of bacteria has adapted to such a wide range of habitats.

  18. Plant Adaptation to Multiple Stresses during Submergence and Following Desubmergence

    Directory of Open Access Journals (Sweden)

    Bishal Gole Tamang

    2015-12-01

    Full Text Available Plants require water for growth and development, but excessive water negatively affects their productivity and viability. Flash floods occasionally result in complete submergence of plants in agricultural and natural ecosystems. When immersed in water, plants encounter multiple stresses including low oxygen, low light, nutrient deficiency, and high risk of infection. As floodwaters subside, submerged plants are abruptly exposed to higher oxygen concentration and greater light intensity, which can induce post-submergence injury caused by oxidative stress, high light, and dehydration. Recent studies have emphasized the significance of multiple stress tolerance in the survival of submergence and prompt recovery following desubmergence. A mechanistic understanding of acclimation responses to submergence at molecular and physiological levels can contribute to the deciphering of the regulatory networks governing tolerance to other environmental stresses that occur simultaneously or sequentially in the natural progress of a flood event.

  19. A multiple access communication network based on adaptive arrays

    Science.gov (United States)

    Zohar, S.

    1981-01-01

    A single frequency communication system is considered consisting of K possibly moving users distributed in space simultaneously communicating with a central station equipped with a computationally adapted array of n = or K antennas. Such a configuration could result if K spacecraft were to be simultaneously tracked by a single DSN complex consisting of an n antennas array. The array employs K sets of n weights to segregate the signals received from the K users. The weights are determined by direct computation based on known position information of the K users. Currently known techniques require (for n = K) about (4/3)K to the 4th power computer operations (multiply and add) to perform such computations. A technique that accomplishes this same goal in 8 K to the 3rd power operations, yielding a reduction by a factor K/6, was developed.

  20. Sparse Signal Reconstruction with Multiple Side Information using Adaptive Weights for Multiview Sources

    DEFF Research Database (Denmark)

    Luong, Huynh Van; Seiler, Jürgen; Kaup, André

    2016-01-01

    This work considers reconstructing a target signal in a context ofdistributed sparse sources. We propose an efficient reconstruction algorithmwith the aid of other given sources as multiple side information (SI). Theproposed algorithm takes advantage of compressive sensing (CS) with SI andadaptive...... the proposedreconstruction algorithm with multiple SI using adaptive weights (RAMSIA) torobustly exploit the multiple SIs with different qualities. We experimentallyperform our algorithm on generated sparse signals and also correlated featurehistograms as multiview sparse sources from a multiview image database. Theresults...

  1. 3D hierarchical computational model of wood as a cellular material with fibril reinforced, heterogeneous multiple layers

    DEFF Research Database (Denmark)

    Qing, Hai; Mishnaevsky, Leon

    2009-01-01

    A 3D hierarchical computational model of deformation and stiffness of wood, which takes into account the structures of wood at several scale levels (cellularity, multilayered nature of cell walls, composite-like structures of the wall layers) is developed. At the mesoscale, the softwood cell...... is presented as a 3D hexagon-shape-tube with multilayered walls. The layers in the softwood cell are considered as considered as composite reinforced by microfibrils (celluloses). The elastic properties of the layers are determined with Halpin–Tsai equations, and introduced into mesoscale finite element...... cellular model. With the use of the developed hierarchical model, the influence of the microstructure, including microfibril angles (MFAs, which characterizes the orientation of the cellulose fibrils with respect to the cell axis), the thickness of the cell wall, the shape of the cell cross...

  2. Repairing Multiple Failures with Coordinated and Adaptive Regenerating Codes

    CERN Document Server

    Kermarrec, Anne-Marie; Scouarnec, Nicolas Le

    2011-01-01

    Erasure correcting codes are widely used to ensure data persistence in distributed storage systems. This paper addresses the repair of such codes in the presence of simultaneous failures. It is crucial to maintain the required redundancy over time to prevent permanent data losses. We go beyond existing work (i.e., regenerating codes by Dimakis et al.) and propose coordinated regenerating codes allowing devices to coordinate during simultaneous repairs thus reducing the costs further. We provide closed form expressions of the communication costs of our new codes depending on the number of live devices and the number of devices being repaired. We prove that deliberately delaying repairs does not bring additional gains in itself. This means that regenerating codes are optimal as long as each failure can be repaired before a second one occurs. Yet, when multiple failures are detected simultaneously, we prove that our coordinated regenerating codes are optimal and outperform uncoordinated repairs (with respect to ...

  3. Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

  4. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

    Science.gov (United States)

    Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

    2016-08-01

    The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

  5. Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    With an aim at the job-shop scheduling problem of multiple resource constraints, this paper presents mixed self-adapting Genetic Algorithm (GA), and establishes a job-shop optimal scheduling model of multiple resource constraints based on the effect of priority scheduling rules in the heuristic algorithm upon the scheduling target. New coding regulations or rules are designed. The sinusoidal function is adopted as the self-adapting factor, thus making cross probability and variable probability automatically change with group adaptability in such a way as to overcome the shortcoming in the heuristic algorithm and common GA, so that the operation efficiency is improved. The results from real example simulation and comparison with other algorithms indicate that the mixed self-adapting GA algorithm can well solve the job-shop optimal scheduling problem under the constraints of various kinds of production resources such as machine-tools and cutting tools.

  6. Benchmark on Adaptive Regulation - Rejection ofunknown/time-varying multiple narrow band disturbances

    OpenAIRE

    Landau, Ioan Doré; Castellanos Silva, Abraham; Airimitoaie, Tudor-Bogdan; Buche, Gabriel; Noe, Mathieu

    2013-01-01

    International audience; The adaptive regulation is an important issue with a lot of potential for applications in active suspension, active vibration control, disc drives control and active noise control. One of the basic problems from the " control system " point of view is the rejection of multiple unknown and time varying narrow band disturbances without using an additional transducer for getting information upon the disturbances. An adaptive feedback approach has to be considered for this...

  7. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    Science.gov (United States)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  8. An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies

    OpenAIRE

    Li, Jia; Tseng, George C

    2011-01-01

    Global expression analyses using microarray technologies are becoming more common in genomic research, therefore, new statistical challenges associated with combining information from multiple studies must be addressed. In this paper we will describe our proposal for an adaptively weighted (AW) statistic to combine multiple genomic studies for detecting differentially expressed genes. We will also present our results from comparisons of our proposed AW statistic to Fisher...

  9. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  10. Multivariable direct adaptive decoupling controller using multiple models and a case study

    Institute of Scientific and Technical Information of China (English)

    WANG Xin; YANG Hui; ZHENG YiHui

    2009-01-01

    In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system.

  11. Robust adaptive synchronization of general dynamical networks with multiple delays and uncertainties

    Indian Academy of Sciences (India)

    LU YIMING; HE PING; MA SHU-HUA; LI GUO-ZHI; MOBAYBEN SALEH

    2016-06-01

    In this article, a general complex dynamical network which contains multiple delays and uncertainties is introduced, which contains time-varying coupling delays, time-varying node delay, and uncertainties of both the inner- and outer-coupling matrices. A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose some suitable adaptive synchronization controllers to ensure the robust synchronization of this dynamical network. The numerical simulations of the time-delay Lorenz chaotic system as local dynamical node are provided to observe and verify the viability and productivity of the theoretical research in this paper. Compared to the achievement of previous research, theresearch in this paper seems quite comprehensive and universal.

  12. Functional adaptation to loading of a single bone is neuronally regulated and involves multiple bones.

    Science.gov (United States)

    Sample, Susannah J; Behan, Mary; Smith, Lesley; Oldenhoff, William E; Markel, Mark D; Kalscheur, Vicki L; Hao, Zhengling; Miletic, Vjekoslav; Muir, Peter

    2008-09-01

    Regulation of load-induced bone formation is considered a local phenomenon controlled by osteocytes, although it has also been hypothesized that functional adaptation may be neuronally regulated. The aim of this study was to examine bone formation in multiple bones, in response to loading of a single bone, and to determine whether adaptation may be neuronally regulated. Load-induced responses in the left and right ulnas and humeri were determined after loading of the right ulna in male Sprague-Dawley rats (69 +/- 16 days of age). After a single period of loading at -760-, -2000-, or -3750-microepsilon initial peak strain, rats were given calcein to label new bone formation. Bone formation and bone neuropeptide concentrations were determined at 10 days. In one group, temporary neuronal blocking was achieved by perineural anesthesia of the brachial plexus with bupivicaine during loading. We found right ulna loading induces adaptive responses in other bones in both thoracic limbs compared with Sham controls and that neuronal blocking during loading abrogated bone formation in the loaded ulna and other thoracic limb bones. Skeletal adaptation was more evident in distal long bones compared with proximal long bones. We also found that the single period of loading modulated bone neuropeptide concentrations persistently for 10 days. We conclude that functional adaptation to loading of a single bone in young rapidly growing rats is neuronally regulated and involves multiple bones. Persistent changes in bone neuropeptide concentrations after a single loading period suggest that plasticity exists in the innervation of bone.

  13. An Hierarchical Approach to Big Data

    CERN Document Server

    Allen, M G; Boch, T; Durand, D; Oberto, A; Merin, B; Stoehr, F; Genova, F; Pineau, F-X; Salgado, J

    2016-01-01

    The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. We highlight the decisions and approaches that have been taken to make this scheme a practical solution for managing large volumes of heterogeneous data. Early implementors of this system have formed a network of HiPS nodes, with some 250 diverse data sets currently available, with multiple mirror implementations for important data sets. This hierarchical approach can be adapted to expose Big Data in different ways. We describe how the ease of implementation, and local customisation of the Aladin Lite embeddable HiPS visualiser have been keys for promoting collaboration on HiPS.

  14. SAMPLING ADAPTIVE STRATEGY AND SPATIAL ORGANISATION ESTIMATION OF SOIL ANIMAL COMMUNITIES AT VARIOUS HIERARCHICAL LEVELS OF URBANISED TERRITORIES

    Directory of Open Access Journals (Sweden)

    Baljuk J.A.

    2014-12-01

    Full Text Available In work the algorithm of adaptive strategy of optimum spatial sampling for studying of the spatial organisation of communities of soil animals in the conditions of an urbanization have been presented. As operating variables the principal components obtained as a result of the analysis of the field data on soil penetration resistance, soils electrical conductivity and density of a forest stand, collected on a quasiregular grid have been used. The locations of experimental polygons have been stated by means of program ESAP. The sampling has been made on a regular grid within experimental polygons. The biogeocoenological estimation of experimental polygons have been made on a basis of A.L.Belgard's ecomorphic analysis. The spatial configuration of biogeocoenosis types has been established on the basis of the data of earth remote sensing and the analysis of digital elevation model. The algorithm was suggested which allows to reveal the spatial organisation of soil animal communities at investigated point, biogeocoenosis, and landscape.

  15. Global adaptive exponential stabilisation for nonlinear systems with multiple unknown control directions

    Science.gov (United States)

    Sun, Xifang; Chen, Weisheng; Wu, Jian

    2016-12-01

    In this paper, we address the global generalised exponential stabilisation problem for a class of lower-triangular systems with multiple unknown directions. Instead of the well-known Nussbaum-gain adaptive rule, a Lyapunov-based adaptive logic switching rule is proposed to seek the correct control directions for such systems. The main advantage of the proposed controller is that it can guarantee the global generalised exponential stability of closed-loop systems. Simulation examples are given to verify the effectiveness of the developed control approach.

  16. Adaptive radio resource allocation for multiple traffic OFDMA broadband wireless access system

    Institute of Scientific and Technical Information of China (English)

    LU Yan-hui; LUO Tao; YIN Chang-chuan; YUE Guang-xin

    2006-01-01

    In this article, an adaptive radio resource allocation algorithm applied to multiple traffic orthogonal frequency division multiple access (OFDMA) system is proposed, which distributes subcarriers and bits among users according to their different quality of service requirements and traffic type. By classifying and prioritizing the users based on their traffic characteristic and ensuring resource for higher priority users, the new scheme decreases tremendously the outage probability of the users requiting a real-time transmission without impact on the spectrum efficiency of system, as well as the outage probability of data users is not increased compared with the radio resource allocation methods published.

  17. Adaptive management of applications across multiple clouds: The SeaClouds Approach

    Directory of Open Access Journals (Sweden)

    Antonio Brogi

    2015-04-01

    Full Text Available How to deploy and manage, in an efficient and adaptive way, complex applications across multiple heterogeneous cloud platforms is one of the problems that have emerged with the cloud revolution. In this paper we present context, motivations and objectives of the EU research project SeaClouds, which aims at enabling a seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and migration of application modules over multiple heterogeneous cloud platforms. After positioning SeaClouds with respect to related cloud initiatives, we present the SeaClouds architecture and discuss some of its aspect, such as the use of the OASIS standard TOSCA and the compatibility with the OASIS CAMP initiative.

  18. 一种新型无线网络自适应分层覆盖系统研究%Research on an adaptive hierarchical coverage scheme of wireless networks

    Institute of Scientific and Technical Information of China (English)

    赵兆

    2011-01-01

    First, a utility function was proposed to evaluate the performance of hierarchical cellular system. Both the blocking probability and handover times were considered in the function. Second, an adaptive hierarchical cellular system was proposed which allows the mobile equipments in macrocells to communicate with any base station in the system. Simulation results indicate that the adaptive hierarchical cellular system performances better than hierarchical cellular system in blocking probability, handover times and utility function.%首先提出一种衡量分层覆盖系统性能的效用函数,该效用函数综合考虑了阻塞率和切换次数;然后,提出了一种自适应分层覆盖系统,该系统允许接入宏蜂窝的移动台可以与任何基站通信.仿真结果表明:在阻塞率、切换次数、效用函数等方面自适应分层覆盖系统优于传统分层覆盖系统.

  19. h-ADAPTIVITY ANALYSIS BASED ON MULTIPLE SCALE REPRODUCING KERNEL PARTICLE METHOD

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhi-qian; ZHOU Jin-xiong; WANG Xue-ming; ZHANG Yan-fen; ZHANG Ling

    2005-01-01

    An h-adaptivity analysis scheme based on multiple scale reproducing kernel particle method was proposed, and two node refinement strategies were constructed using searching-neighbor-nodes(SNN) and local-Delaunay-triangulation(LDT) techniques, which were suitable and effective for h-adaptivity analysis on 2-D problems with the regular or irregular distribution of the nodes. The results of multiresolution and hadaptivity analyses on 2-D linear elastostatics and bending plate problems demonstrate that the improper high-gradient indicator will reduce the convergence property of the hadaptivity analysis, and that the efficiency of the LDT node refinement strategy is better than SNN, and that the presented h-adaptivity analysis scheme is provided with the validity, stability and good convergence property.

  20. An efficient algorithm for finding optimal gain-ratio multiple-split tests on hierarchical attributes in decision tree learning

    Energy Technology Data Exchange (ETDEWEB)

    Almuallim, H. [King Fahd Univ. of Petroleum & Minerals, Dhahran (Saudi Arabia); Akiba, Yasuhiro; Kaneda, Shigeo [NTT Communication Science Labs., Kanagawa (Japan)

    1996-12-31

    Given a set of training examples S and a tree-structured attribute x, the goal in this work is to find a multiple-split test defined on x that maximizes Quinlan`s gain-ratio measure. The number of possible such multiple-split tests grows exponentially in the size of the hierarchy associated with the attribute. It is, therefore, impractical to enumerate and evaluate all these tests in order to choose the best one. We introduce an efficient algorithm for solving this problem that guarantees maximizing the gain-ratio over all possible tests. For a training set of m examples and an attribute hierarchy of height d, our algorithm runs in time proportional to dm, which makes it efficient enough for practical use.

  1. Adaptive Personalized Training Games for Individual and Collaborative Rehabilitation of People with Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Johanna Renny Octavia

    2014-01-01

    Full Text Available Any rehabilitation involves people who are unique individuals with their own characteristics and rehabilitation needs, including patients suffering from Multiple Sclerosis (MS. The prominent variation of MS symptoms and the disease severity elevate a need to accommodate the patient diversity and support adaptive personalized training to meet every patient’s rehabilitation needs. In this paper, we focus on integrating adaptivity and personalization in rehabilitation training for MS patients. We introduced the automatic adjustment of difficulty levels as an adaptation that can be provided in individual and collaborative rehabilitation training exercises for MS patients. Two user studies have been carried out with nine MS patients to investigate the outcome of this adaptation. The findings showed that adaptive personalized training trajectories have been successfully provided to MS patients according to their individual training progress, which was appreciated by the patients and the therapist. They considered the automatic adjustment of difficulty levels to provide more variety in the training and to minimize the therapists involvement in setting up the training. With regard to social interaction in the collaborative training exercise, we have observed some social behaviors between the patients and their training partner which indicated the development of social interaction during the training.

  2. Adaptive personalized training games for individual and collaborative rehabilitation of people with multiple sclerosis.

    Science.gov (United States)

    Octavia, Johanna Renny; Coninx, Karin

    2014-01-01

    Any rehabilitation involves people who are unique individuals with their own characteristics and rehabilitation needs, including patients suffering from Multiple Sclerosis (MS). The prominent variation of MS symptoms and the disease severity elevate a need to accommodate the patient diversity and support adaptive personalized training to meet every patient's rehabilitation needs. In this paper, we focus on integrating adaptivity and personalization in rehabilitation training for MS patients. We introduced the automatic adjustment of difficulty levels as an adaptation that can be provided in individual and collaborative rehabilitation training exercises for MS patients. Two user studies have been carried out with nine MS patients to investigate the outcome of this adaptation. The findings showed that adaptive personalized training trajectories have been successfully provided to MS patients according to their individual training progress, which was appreciated by the patients and the therapist. They considered the automatic adjustment of difficulty levels to provide more variety in the training and to minimize the therapists involvement in setting up the training. With regard to social interaction in the collaborative training exercise, we have observed some social behaviors between the patients and their training partner which indicated the development of social interaction during the training.

  3. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  4. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  5. Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

    Science.gov (United States)

    Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

    2017-09-01

    It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus

  6. Consideration of multiple load cases is critical in modelling orthotropic bone adaptation in the femur.

    Science.gov (United States)

    Geraldes, Diogo M; Modenese, Luca; Phillips, Andrew T M

    2016-10-01

    Functional adaptation of the femur has been investigated in several studies by embedding bone remodelling algorithms in finite element (FE) models, with simplifications often made to the representation of bone's material symmetry and mechanical environment. An orthotropic strain-driven adaptation algorithm is proposed in order to predict the femur's volumetric material property distribution and directionality of its internal structures within a continuum. The algorithm was applied to a FE model of the femur, with muscles, ligaments and joints included explicitly. Multiple load cases representing distinct frames of two activities of daily living (walking and stair climbing) were considered. It is hypothesised that low shear moduli occur in areas of bone that are simply loaded and high shear moduli in areas subjected to complex loading conditions. In addition, it is investigated whether material properties of different femoral regions are stimulated by different activities. The loading and boundary conditions were considered to provide a physiological mechanical environment. The resulting volumetric material property distribution and directionalities agreed with ex vivo imaging data for the whole femur. Regions where non-orthogonal trabecular crossing has been documented coincided with higher values of predicted shear moduli. The topological influence of the different activities modelled was analysed. The influence of stair climbing on the properties of the femoral neck region is highlighted. It is recommended that multiple load cases should be considered when modelling bone adaptation. The orthotropic model of the complete femur is released with this study.

  7. Robust Adaptive Beamforming for Multiple Signals of Interest with Cycle Frequency Error

    Directory of Open Access Journals (Sweden)

    Huang Chia-Cheng

    2010-01-01

    Full Text Available This paper deals with the problem of robust adaptive array beamforming by exploiting the signal cyclostationarity. Recently, a novel cyclostationarity-exploiting beamforming method has been proposed by J.-H. Lee and C.-C. Huang (2009 for dealing with the situation of multiple signals of interest (SOI based on the LS-SCORE algorithm. This method is referred to as the multiple LS-SCORE (MLS-SCORE algorithm. However, the MLS-SCORE algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequencies of the SOIs. In this paper, we evaluate the performance of the MLS-SCORE algorithm in the presence of cycle frequency error (CFE. The output SINR of an adaptive beamforming using the MLS-SCORE algorithm deteriorates like a function as the number of data snapshots increases. To tackle this difficulty, we present an efficient method to find an appropriate estimate for each of the cycle frequencies of the SOIs iteratively to achieve robust adaptive beamforming against the CFE. Simulation results for showing the effectiveness of the proposed method are provided.

  8. Mean deviation coupling synchronous control for multiple motors via second-order adaptive sliding mode control.

    Science.gov (United States)

    Li, Lebao; Sun, Lingling; Zhang, Shengzhou

    2016-05-01

    A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme.

  9. Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

    Science.gov (United States)

    Abdallah, Muhammad E. (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor)

    2013-01-01

    A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

  10. Speed tracking and synchronization of multiple motors using ring coupling control and adaptive sliding mode control.

    Science.gov (United States)

    Li, Le-Bao; Sun, Ling-Ling; Zhang, Sheng-Zhou; Yang, Qing-Quan

    2015-09-01

    A new control approach for speed tracking and synchronization of multiple motors is developed, by incorporating an adaptive sliding mode control (ASMC) technique into a ring coupling synchronization control structure. This control approach can stabilize speed tracking of each motor and synchronize its motion with other motors' motion so that speed tracking errors and synchronization errors converge to zero. Moreover, an adaptive law is exploited to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort and attenuate chattering. Performance comparisons with parallel control, relative coupling control and conventional PI control are investigated on a four-motor synchronization control system. Extensive simulation results show the effectiveness of the proposed control scheme.

  11. Improving the performance of link prediction by adaptively exploiting multiple structural features of networks

    CERN Document Server

    Ma, Chuang; Zhang, Hai-Feng

    2016-01-01

    So far, many network-structure-based link prediction methods have been proposed. However, these traditional methods were proposed by highlighting one or two structural features of networks, and then use the methods to implement link prediction in different networks. In many cases, the performance is not ideal since each network has its unique underlying structural features. In this article, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same networks, their inner structural features are utterly different. Inspired by these facts, an \\emph{adaptive} link prediction method is proposed to incorporate multiple structural features from the perspective of combination optimization. In the model, the weight of each structural feature is \\emph{adaptively } determined by logistic regression but not be artificially given in advance. According to our experimental results, we find that the logistic regression based link ...

  12. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    Satellite tracking is a challenging task for marine applications due to the disturbance from ocean waves. An Attitude Heading and Reference System (AHRS) for measuring ship attitude, based on Microelectromechanical Systems (MEMS) sensors, is a key part for satellite tracking. In this paper......, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  13. Comparison of Multiple-Microphone and Single-Loudspeaker Adaptive Feedback/Echo Cancellation Systems

    DEFF Research Database (Denmark)

    Guo, Meng; Elmedyb, Thomas Bo; Jensen, Søren Holdt;

    2011-01-01

    Recently, we introduced a frequency domain measure - the power transfer function - to predict the convergence rate, system stability bound and the steady-state behavior across time and frequency of a least mean square based feedback/echo cancellation algorithm in a general multiple......-microphone and single-loudspeaker system. In this work, we extend the theoretical analysis to the normalized least mean square and recursive least squares algorithms. Furthermore, we compare and discuss the system behaviors in terms of the power transfer function for all three adaptive algorithms....

  14. Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles

    Science.gov (United States)

    Yang, Tzu-Chi; Hwang, Gwo-Jen; Yang, Stephen Jen-Hwa

    2013-01-01

    In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An…

  15. Hierarchical nanostructure and synergy of multimolecular signalling complexes

    Science.gov (United States)

    Sherman, Eilon; Barr, Valarie A.; Merrill, Robert K.; Regan, Carole K.; Sommers, Connie L.; Samelson, Lawrence E.

    2016-01-01

    Signalling complexes are dynamic, multimolecular structures and sites for intracellular signal transduction. Although they play a crucial role in cellular activation, current research techniques fail to resolve their structure in intact cells. Here we present a multicolour, photoactivated localization microscopy approach for imaging multiple types of single molecules in fixed and live cells and statistical tools to determine the nanoscale organization, topology and synergy of molecular interactions in signalling complexes downstream of the T-cell antigen receptor. We observe that signalling complexes nucleated at the key adapter LAT show a hierarchical topology. The critical enzymes PLCγ1 and VAV1 localize to the centre of LAT-based complexes, and the adapter SLP-76 and actin molecules localize to the periphery. Conditional second-order statistics reveal a hierarchical network of synergic interactions between these molecules. Our results extend our understanding of the nanostructure of signalling complexes and are relevant to studying a wide range of multimolecular complexes. PMID:27396911

  16. Hierarchical nanostructure and synergy of multimolecular signalling complexes

    Science.gov (United States)

    Sherman, Eilon; Barr, Valarie A.; Merrill, Robert K.; Regan, Carole K.; Sommers, Connie L.; Samelson, Lawrence E.

    2016-07-01

    Signalling complexes are dynamic, multimolecular structures and sites for intracellular signal transduction. Although they play a crucial role in cellular activation, current research techniques fail to resolve their structure in intact cells. Here we present a multicolour, photoactivated localization microscopy approach for imaging multiple types of single molecules in fixed and live cells and statistical tools to determine the nanoscale organization, topology and synergy of molecular interactions in signalling complexes downstream of the T-cell antigen receptor. We observe that signalling complexes nucleated at the key adapter LAT show a hierarchical topology. The critical enzymes PLCγ1 and VAV1 localize to the centre of LAT-based complexes, and the adapter SLP-76 and actin molecules localize to the periphery. Conditional second-order statistics reveal a hierarchical network of synergic interactions between these molecules. Our results extend our understanding of the nanostructure of signalling complexes and are relevant to studying a wide range of multimolecular complexes.

  17. Image classification with densely sampled image windows and generalized adaptive multiple kernel learning.

    Science.gov (United States)

    Yan, Shengye; Xu, Xinxing; Xu, Dong; Lin, Stephen; Li, Xuelong

    2015-03-01

    We present a framework for image classification that extends beyond the window sampling of fixed spatial pyramids and is supported by a new learning algorithm. Based on the observation that fixed spatial pyramids sample a rather limited subset of the possible image windows, we propose a method that accounts for a comprehensive set of windows densely sampled over location, size, and aspect ratio. A concise high-level image feature is derived to effectively deal with this large set of windows, and this higher level of abstraction offers both efficient handling of the dense samples and reduced sensitivity to misalignment. In addition to dense window sampling, we introduce generalized adaptive l(p)-norm multiple kernel learning (GA-MKL) to learn a robust classifier based on multiple base kernels constructed from the new image features and multiple sets of prelearned classifiers from other classes. With GA-MKL, multiple levels of image features are effectively fused, and information is shared among different classifiers. Extensive evaluation on benchmark datasets for object recognition (Caltech256 and Caltech101) and scene recognition (15Scenes) demonstrate that the proposed method outperforms the state-of-the-art under a broad range of settings.

  18. Application of Multiple Description Coding for Adaptive QoS Mechanism for Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Ilan Sadeh

    2014-02-01

    Full Text Available Multimedia transmission over cloud infrastructure is a hot research topic worldwide. It is very strongly related to video streaming, VoIP, mobile networks, and computer networks. The goal is a reliable integration of telephony, video and audio transmission, computing and broadband transmission based on cloud computing. One right approach to pave the way for mobile multimedia and cloud computing is Multiple Description Coding (MDC, i.e. the solution would be: TCP/IP and similar protocols to be used for transmission of text files, and Multiple Description Coding “Send and Forget” algorithm to be used as transmission method for Multimedia over the cloud. Multiple Description Coding would improve the Quality of Service and would provide new service of rate adaptive streaming. This paper presents a new approach for improving the quality of multimedia and other services in the cloud, by using Multiple Description Coding (MDC. Firsty MDC Send and Forget Algorithm is compared with the existing protocols such as TCP/IP, UDP, RTP, etc. Then the Achievable Rate Region for MDC system is evaluated. Finally, a new subset of Quality of Service that considers the blocking in multi-terminal multimedia network and fidelity losses is considered.

  19. The Multiple Use of Tropical Forests by Indigenous Peoples in Mexico: a Case of Adaptive Management

    Directory of Open Access Journals (Sweden)

    Víctor M. Toledo

    2003-12-01

    Full Text Available The quest for an appropriate system of management for tropical ecosystems necessitates that ecologists consider the accumulated experiences of indigenous peoples in their long-term management of local resources, a subject of current ethnoecology. This paper provides data and empirical evidence of an indigenous multiple-use strategy (MUS of tropical forest management existing in Mexico, that can be considered a case of adaptive management. This conclusion is based on the observation that some indigenous communities avoid common modernization routes toward specialized, unsustainable, and ecologically disruptive systems of production, and yet probably achieve the most successful tropical forest utilization design, in terms of biodiversity conservation, resilience, and sustainability. This analysis relies on an exhaustive review of the literature and the authors' field research. Apparently, this MUS represents an endogenous reaction of indigenous communities to the intensification of natural resource use, responding to technological, demographic, cultural, and economic changes in the contemporary world. This transforms traditional shifting cultivators into multiple-use strategists. Based on a case study, three main features (biodiversity, resilience, and permanence considered relevant to achieving adaptive and sustainable management of tropical ecosystems are discussed.

  20. A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

    Directory of Open Access Journals (Sweden)

    Yepeng Ni

    2016-01-01

    Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

  1. A new adaptive control scheme based on the interacting multiple model (IMM) estimation

    Energy Technology Data Exchange (ETDEWEB)

    Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid [McMaster University, Hamilton (Canada)

    2016-06-15

    In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.

  2. Adaptive radiation in extremophilic Dorvilleidae (Annelida): diversification of a single colonizer or multiple independent lineages?

    Science.gov (United States)

    Thornhill, Daniel J; Struck, Torsten H; Ebbe, Brigitte; Lee, Raymond W; Mendoza, Guillermo F; Levin, Lisa A; Halanych, Kenneth M

    2012-08-01

    Metazoan inhabitants of extreme environments typically evolved from forms found in less extreme habitats. Understanding the prevalence with which animals move into and ultimately thrive in extreme environments is critical to elucidating how complex life adapts to extreme conditions. Methane seep sediments along the Oregon and California margins have low oxygen and very high hydrogen sulfide levels, rendering them inhospitable to many life forms. Nonetheless, several closely related lineages of dorvilleid annelids, including members of Ophryotrocha, Parougia, and Exallopus, thrive at these sites in association with bacterial mats and vesicomyid clam beds. These organisms are ideal for examining adaptive radiations in extreme environments. Did dorvilleid annelids invade these extreme environments once and then diversify? Alternatively, did multiple independent lineages adapt to seep conditions? To address these questions, we examined the evolutionary history of methane-seep dorvilleids using 16S and Cyt b genes in an ecological context. Our results indicate that dorvilleids invaded these extreme habitats at least four times, implying preadaptation to life at seeps. Additionally, we recovered considerably more dorvilleid diversity than is currently recognized. A total of 3 major clades (designated "Ophryotrocha," "Mixed Genera" and "Parougia") and 12 terminal lineages or species were encountered. Two of these lineages represented a known species, Parougia oregonensis, whereas the remaining 10 lineages were newly discovered species. Certain lineages exhibited affinity to geography, habitat, sediment depth, and/or diet, suggesting that dorvilleids at methane seeps radiated via specialization and resource partitioning.

  3. Optimizing the passenger air bag of an adaptive restraint system for multiple size occupants.

    Science.gov (United States)

    Bai, Zhonghao; Jiang, Binhui; Zhu, Feng; Cao, Libo

    2014-01-01

    The development of the adaptive occupant restraint system (AORS) has led to an innovative way to optimize such systems for multiple size occupants. An AORS consists of multiple units such as adaptive air bags, seat belts, etc. During a collision, as a supplemental protective device, air bags can provide constraint force and play a role in dissipating the crash energy of the occupants' head and thorax. This article presents an investigation into an adaptive passenger air bag (PAB). The purpose of this study is to develop a base shape of a PAB for different size occupants using an optimization method. Four typical base shapes of a PAB were designed based on geometric data on the passenger side. Then 4 PAB finite element (FE) models and a validated sled with different size dummy models were developed in MADYMO (TNO, Rijswijk, The Netherlands) to conduct the optimization to obtain the best baseline PAB that would be used in the AORS. The objective functions-that is, the minimum total probability of injuries (∑Pcomb) of the 5th percentile female and 50th and 95th percentile male dummies-were adopted to evaluate the optimal configurations. The injury probability (Pcomb) for each dummy was adopted from the U.S. New Car Assessment Program (US-NCAP). The parameters of the AORS were first optimized for different types of PAB base shapes in a frontal impact. Then, contact time duration and force between the PAB and dummy head/chest were optimized by adjusting the parameters of the PAB, such as the number and position of tethers, lower the Pcomb of the 95th percentile male dummy. According to the optimization results, 4 typical PABs could provide effective protection to 5th and 50th percentile dummies. However, due to the heavy and large torsos of the 95th percentile occupants, the current occupant restraint system does not demonstrate satisfactory protective function, particularly for the thorax.

  4. Accelerated parabolic Radon domain 2D adaptive multiple subtraction with fast iterative shrinkage thresholding algorithm and its application in parabolic Radon domain hybrid demultiple method

    Science.gov (United States)

    Li, Zhong-xiao; Li, Zhen-chun

    2017-08-01

    Adaptive multiple subtraction is an important step for successfully conducting surface-related multiple elimination in marine seismic exploration. 2D adaptive multiple subtraction conducted in the parabolic Radon domain has been proposed to better separate primaries and multiples than 2D adaptive multiple subtraction conducted in the time-offset domain. Additionally, the parabolic Radon domain hybrid demultiple method combining parabolic Radon filtering and parabolic Radon domain 2D adaptive multiple subtraction can better remove multiples than the cascaded demultiple method using time-offset domain 2D adaptive multiple subtraction and the parabolic Radon transform method sequentially. To solve the matching filter in the optimization problem with L1 norm minimization constraint of primaries, traditional parabolic Radon domain 2D adaptive multiple subtraction uses the iterative reweighted least squares (IRLS) algorithm, which is computationally expensive for solving a weighted LS inversion in each iteration. In this paper we introduce the fast iterative shrinkage thresholding algorithm (FISTA) as a faster alternative to the IRLS algorithm for parabolic Radon domain 2D adaptive multiple subtraction. FISTA uses the shrinkage-thresholding operator to promote the sparsity of estimated primaries and solves the 2D matching filter with iterative steps. FISTA based parabolic Radon domain 2D adaptive multiple subtraction reduces the computation time effectively while achieving similar accuracy compared with IRLS based parabolic Radon domain 2D adaptive multiple subtraction. Additionally, the provided examples show that FISTA based parabolic Radon domain 2D adaptive multiple subtraction can better separate primaries and multiples than FISTA based time-offset domain 2D adaptive multiple subtraction. Furthermore, we introduce FISTA based parabolic Radon domain 2D adaptive multiple subtraction into the parabolic Radon domain hybrid demultiple method to improve its computation

  5. [And if it happened to children? Adapting medical care during terrorist attacks with multiple pediatric victims].

    Science.gov (United States)

    Alix-Séguin, L; Lodé, N; Orliaguet, G; Chamorro, E; Kerroué, F; Lorge, C; Moreira, A

    2017-03-01

    In light of the recent terrorist attacks in Europe, we need to reconsider the organization of rescue and medical management and plan for an attack involving multiple pediatric victims. To ensure quick surgical management, but also to minimize risk for on-site teams (direct threats from secondary terrorist attacks targeting deployed emergency services), it is crucial to evacuate patients in a swift but orderly fashion. Children are vulnerable targets in terrorist attacks. Their anatomical and physiological characteristics make it likely that pediatric victims will suffer more brain injuries and require more, often advanced, airway management. Care of multiple pediatric victims would also prove to be a difficult emotional challenge. Civilian medical teams have adapted the military-medicine principles of damage control in their medical practice using the MARCHE algorithm (Massive hemorrhage, Airway, Respiration [breathing], Circulation, Head/Hypothermia, Evacuation). They have also learned to adapt the level of care to the level of safety at the scene. Prehospital damage control principles should now be tailored to the treatment of pediatric patients in extraordinary circumstances. Priorities are given to hemorrhage control and preventing the lethal triad (coagulopathy, hypothermia, and acidosis). Managing hemorrhagic shock involves quickly controlling external bleeding (tourniquets, hemostatic dressing), using small volumes for fluid resuscitation (10-20ml/kg of normal saline), quickly introducing a vasopressor (noradrenaline 0.1μg/kg/min then titrate) after one or two fluid boluses, and using tranexamic acid (15mg/kg over 10min for loading dose, maximum 1g over 10min). Prehospital resources specifically dedicated to children are limited, and it is therefore important that everyone be trained and prepared for a scene with multiple pediatric patients.

  6. An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.

    Science.gov (United States)

    Kim, Junghi; Bai, Yun; Pan, Wei

    2015-12-01

    We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods.

  7. Sex, horizontal transmission, and multiple hosts prevent local adaptation of Crithidia bombi, a parasite of bumblebees (Bombus spp.).

    Science.gov (United States)

    Erler, Silvio; Popp, Mario; Wolf, Stephan; Lattorff, H Michael G

    2012-05-01

    Local adaptation within host-parasite systems can evolve by several non-exclusive drivers (e.g., host species-genetic adaptation; ecological conditions-ecological adaptation, and time-temporal adaptation). Social insects, especially bumblebees, with an annual colony life history not only provide an ideal system to test parasite transmission within and between different host colonies, but also parasite adaptation to specific host species and environments. Here, we study local adaptation in a multiple-host parasite characterized by high levels of horizontal transmission. Crithidia bombi occurs as a gut parasite in several bumblebee species. Parasites were sampled from five different host species in two subsequent years. Population genetic tools were used to test for the several types of adaptation. Although we found no evidence for local adaptation of the parasite toward host species, there was a slight temporal differentiation of the parasite populations, which might have resulted from severe bottlenecks during queen hibernation. Parasite populations were in Hardy-Weinberg equilibrium and showed no signs of linkage disequilibrium suggesting that sexual reproduction is an alternative strategy in this otherwise clonal parasite. Moreover, high levels of multiple infections were found, which might facilitate sexual genetic exchange. The detection of identical clones in different host species suggested that horizontal transmission occurs between host species and underpins the lack of host-specific adaptation.

  8. Adaptive Double Threshold with Multiple Energy Detection Technique in Cognitive Radio

    Directory of Open Access Journals (Sweden)

    J. Avila

    2015-08-01

    Full Text Available The Cognitive Radio (CR network is a system which lends help at the time of scarcity in spectrum. One of the process by which CR senses the spectrum is energy detection method with a fixed single threshold. When energy levels fall below the threshold, secondary user is permitted to use the spectrum of the primary user. It is shown by simulation results that having two levels of threshold i.e., double threshold improves performance by giving importance to one of the major aspects of CR, reducing the confliction of the primary and the secondary user. For enhanced performance under noise conditions, dynamic allocation or adaptive threshold is employed with the two levels of threshold. The system is made better by the use of multiple energy detectors on the reception end.

  9. Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

    Science.gov (United States)

    Yoo, Sung Jin

    2016-11-01

    This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

  10. Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

    Science.gov (United States)

    Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

    2015-03-01

    Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.

  11. Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

    Directory of Open Access Journals (Sweden)

    Mustafa Rahimie

    2017-01-01

    Full Text Available The method of least mean square (LMS is the commonly used algorithm in Adaptive filter due to its simplicity and robustness in implementation. In Active Noise Control application, a filtered reference signal is used prior to LMS algorithm to overcome the constraint on stability and convergence performance of the system due to the existence of the auxiliary path. This is known as Filtered-X LMS algorithm. In conventional Filtered-X LMS algorithm, each filter weight is updated once on every audio sample. This paper proposes the improved version of Filtered-X LMS algorithm with the use of multiple iteration of filter weight on every sample of audio signal. The proposed work uses field programmable gate arrays to realize real-time simulation on hardware for the noise signal of 500 Hz. Results from the real-time hardware simulations have shown much faster error convergence and better adaptation performance for different selections of learning constant μ, as compared with the conventional method.

  12. Multiple-objective response-adaptive repeated measurement designs in clinical trials for binary responses.

    Science.gov (United States)

    Liang, Yuanyuan; Li, Yin; Wang, Jing; Carriere, Keumhee C

    2014-02-20

    A multiple-objective allocation strategy was recently proposed for constructing response-adaptive repeated measurement designs for continuous responses. We extend the allocation strategy to constructing response-adaptive repeated measurement designs for binary responses. The approach with binary responses is quite different from the continuous case, as the information matrix is a function of responses, and it involves nonlinear modeling. To deal with these problems, we first build the design on the basis of success probabilities. Then we illustrate how various models can accommodate carryover effects on the basis of logits of response profiles as well as any correlation structure. Through computer simulations, we find that the allocation strategy developed for continuous responses also works well for binary responses. As expected, design efficiency in terms of mean squared error drops sharply, as more emphasis is placed on increasing treatment benefit than estimation precision. However, we find that it can successfully allocate more patients to better treatment sequences without sacrificing much estimation precision.

  13. Adaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded Channel

    Directory of Open Access Journals (Sweden)

    P. Sivakumar

    2011-01-01

    Full Text Available Problem statement: Digital transmission over band-limited communication channel largely suffers from ISIS and various noise sources. The presence of ISI and noise causes bit errors in the received signal. Equalization is necessary at the receiver to overcome these channel impairment to recover the original transmitted sequence. Traditionally equalization is considered as equivalent to inverse filtering and implemented using linear-perform under severe distortion conditions when Signal to Noise Ratio (SNR is poor. Equalization can be considered as a non-linear classification problem and optimum solution is given by Bayesian solution. Non-linear techniques like Artificial Neutral Networks (ANN are very good choice for non-linear classification problems. Several non-lines are equalizers have been implemented using ANN which outperformed LTE and solved the problem of equalization to the varying degree of sources. Approach: Forward neural network architecture with optimum number of nodes was used to achieve adaptive channel equalization. Summation at each node was replaced by multiplications which result in powerful mapping. The equalizer was tested on Rayleigh fading channel with a BPSK signal. Results: Results showed that proposed equalizer provides simplified architecture and improvement in the bit error rate at various levels of signal to noise ratio for Rayleigh faded channel. Conclusion: A high order feed forward network equalizer with multiplicative neuron is proposed in this study. Use of Multiplication allows direct computing of polynomial inputs and approximation with fewer nodes. Performance comparison in terms of network architecture and BER performance suggest the better classification capability of the proposed MNN equalizer over RRBF.

  14. Multiple recent co-options of Optix associated with novel traits in adaptive butterfly wing radiations

    Science.gov (United States)

    2014-01-01

    Background While the ecological factors that drive phenotypic radiations are often well understood, less is known about the generative mechanisms that cause the emergence and subsequent diversification of novel features. Heliconius butterflies display an extraordinary diversity of wing patterns due in part to mimicry and sexual selection. Identifying the genetic drivers of this crucible of evolution is now within reach, as it was recently shown that cis-regulatory variation of the optix transcription factor explains red pattern differences in the adaptive radiations of the Heliconius melpomene and Heliconius erato species groups. Results Here, we compare the developmental expression of the Optix protein across a large phylogenetic sample of butterflies and infer that its color patterning role originated at the base of the neotropical passion-vine butterfly clade (Lepidoptera, Nymphalidae, Tribe: Heliconiini), shortly predating multiple Optix-driven wing pattern radiations in the speciose Heliconius and Eueides genera. We also characterize novel Optix and Doublesex expression in the male-specific pheromone wing scales of the basal heliconiines Dryas and Agraulis, thus illustrating that within the Heliconinii lineage, Optix has been evolutionarily redeployed in multiple contexts in association with diverse wing features. Conclusions Our findings reveal that the repeated co-option of Optix into various aspects of wing scale specification was associated with multiple evolutionary novelties over a relatively short evolutionary time scale. In particular, the recruitment of Optix expression in colored scale cell precursors was a necessary condition to the explosive diversification of passion-vine butterfly wing patterns. The novel deployment of a gene followed by spatial modulation of its expression in a given cell type could be a common mode of developmental innovation for triggering phenotypic radiations. PMID:24499528

  15. Adaptation of a Counseling Intervention to Address Multiple Cancer Risk Factors among Overweight/Obese Latino Smokers

    Science.gov (United States)

    Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Hernandez Robles, Eden; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W.

    2015-01-01

    More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social…

  16. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition

    Directory of Open Access Journals (Sweden)

    Mohammad Subhi Al-batah

    2014-01-01

    Full Text Available To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL and high-grade squamous intraepithelial lesion (HSIL. The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy.

  17. An Adaptive Time-Spread Multiple-Access Policy for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Konstantinos Oikonomou

    2007-05-01

    Full Text Available Sensor networks require a simple and efficient medium access control policy achieving high system throughput with no or limited control overhead in order to increase the network lifetime by minimizing the energy consumed during transmission attempts. Time-spread multiple-access (TSMA policies that have been proposed for ad hoc network environments, can also be employed in sensor networks, since no control overhead is introduced. However, they do not take advantage of any cross-layer information in order to exploit the idiosyncrasies of the particular sensor network environment such as the presence of typically static nodes and a common destination for the forwarded data. An adaptive probabilistic TSMA-based policy, that is proposed and analyzed in this paper, exploits these idiosyncrasies and achieves higher system throughput than the existing TSMA-based policies without any need for extra control overhead. As it is analytically shown in this paper, the proposed policy always outperforms the existing TSMA-based policies, if certain parameter values are properly set; the analysis also provides for these proper values. It is also shown that the proposed policy is characterized by a certain convergence period and that high system throughput is achieved for long convergence periods. The claims and expectations of the provided analysis are supported by simulation results presented in this paper.

  18. The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

    Science.gov (United States)

    Elfes, Alberto; Podnar, Gregg W.; Dolan, John M.; Stancliff, Stephen; Lin, Ellie; Hosler, Jeffrey C.; Ames, Troy J.; Higinbotham, John; Moisan, John R.; Moisan, Tiffany A.; Kulczycki, Eric A.

    2008-01-01

    Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

  19. Adaptive behaviour and multiple equilibrium states in a predator-prey model.

    Science.gov (United States)

    Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii

    2015-05-01

    There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point.

  20. Research on non-uniform sampling problem when adapting wavenumber algorithm to multiple-receiver synthetic aperture sonar

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The azimuth sampling of multiple-receiver SAS systems is non-uniform,which causes standard wavenumber algorithm(ω—κ) can't be applied to multiple-receiver SAS image reconstruction.To solve the problem,two methods are presented,which can adapt the standardω—κalgorithm to multiple-receiver SAS system.One method named Non-uniform Separate Fourier Transform(NSFFT) converts the Fourier Transform(FT) of the non-uniform samples in azimuth direction into several uniform FTs on the assumption that the sonar array...

  1. 基于递阶遗传算法的一类多旅行商问题优化%Optimization of multiple traveling salesman problem based on hierarchical genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    周辉仁; 唐万生; 牛犇

    2009-01-01

    针对最小化单个旅行商路程的多旅行商问题,提出了一种递阶遗传算法和矩阵解码方法.该算法根据问题的特点,采用一种递阶编码方案,此编码与多旅行商问题一一对应.用递阶遗传算法优化多旅行商问题不需设计专门的遗传算子,操作简单,并且解码方法适于求解距离对称和距离非对称的多旅行商问题.计算结果表明,递阶遗传算法是有效的,能适用于优化多旅行商问题.%In order to solve a kind of longest-path-shortest multiple traveling salesman problem, a hierarchi-cal genetic algorithm and decoding method with matrix is proposed. Its coding method is simple and can effec-tively reflect the traveling policy, and the methods of crossover and mutation are not special to design. By this method, symmetric and asymmetric multiple traveling salesman problems can be easily solved. The computa-tional results show that the hierarchical genetic algorithm is efficient and fits for multiple traveling salesman problems.

  2. Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model

    NARCIS (Netherlands)

    Bohte, S.M.

    2012-01-01

    Neural adaptation underlies the ability of neurons to maximize encoded informa- tion over a wide dynamic range of input stimuli. While adaptation is an intrinsic feature of neuronal models like the Hodgkin-Huxley model, the challenge is to in- tegrate adaptation in models of neural computation. Rece

  3. Hierarchical low-rank approximation for high dimensional approximation

    KAUST Repository

    Nouy, Anthony

    2016-01-07

    Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

  4. Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

    Science.gov (United States)

    Li, Zhijun; Su, Chun-Yi

    2013-09-01

    In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

  5. Adapting hierarchical bidirectional inter prediction on a GPU-based platform for 2D and 3D H.264 video coding

    Science.gov (United States)

    Rodríguez-Sánchez, Rafael; Martínez, José Luis; Cock, Jan De; Fernández-Escribano, Gerardo; Pieters, Bart; Sánchez, José L.; Claver, José M.; de Walle, Rik Van

    2013-12-01

    The H.264/AVC video coding standard introduces some improved tools in order to increase compression efficiency. Moreover, the multi-view extension of H.264/AVC, called H.264/MVC, adopts many of them. Among the new features, variable block-size motion estimation is one which contributes to high coding efficiency. Furthermore, it defines a different prediction structure that includes hierarchical bidirectional pictures, outperforming traditional Group of Pictures patterns in both scenarios: single-view and multi-view. However, these video coding techniques have high computational complexity. Several techniques have been proposed in the literature over the last few years which are aimed at accelerating the inter prediction process, but there are no works focusing on bidirectional prediction or hierarchical prediction. In this article, with the emergence of many-core processors or accelerators, a step forward is taken towards an implementation of an H.264/AVC and H.264/MVC inter prediction algorithm on a graphics processing unit. The results show a negligible rate distortion drop with a time reduction of up to 98% for the complete H.264/AVC encoder.

  6. Meeting multiple demands: Water transaction opportunities for environmental benefits promoting adaptation to climate change

    Science.gov (United States)

    McCoy, Amy

    2015-04-01

    In arid regions, the challenge of balancing water use among a diversity of sectors expands in lock step with conditions of water stress that are exacerbated by climate variability, prolonged drought, and growing water-use demands. The elusiveness of achieving a sustainable balance under conditions of environmental change in the southwestern United States is evidenced by reductions in both overall water availability and freshwater ecosystem health, as well as by recent projections of shortages on the Colorado River within the next five years. The water sustainability challenge in this region, as well as drylands throughout the world, can therefore be viewed through the lens of water stress, a condition wherein demands on land and water -- including the needs of freshwater ecosystems -- exceed reliable supplies, and the full range of water needs cannot be met without tradeoffs across multiple uses. Water stress influences not only ecosystems, but a region's economy, land management, quality of life, and cultural heritage -- each of which requires water to thrive. With respect to promoting successful adaptation to climate change, achieving full water sustainability would allow for water to be successfully divided among water users -- including municipalities, agriculture, and freshwater ecosystems -- at a level that meets the goals of water users and the governing body. Over the last ten to fifteen years, the use of transactional approaches in the western U.S., Mexico, and Australia has proven to be a viable management tool for achieving stream flow and shallow aquifer restoration. By broad definition, environmental water transactions are an equitable and adaptable tool that brings diverse stakeholders to the table to facilitate a fair-market exchange of rights to use water in a manner that benefits both water users and the environment. This talk will present a basic framework of necessary stakeholder engagement, hydrologic conditions, enabling laws and policies

  7. Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

    Science.gov (United States)

    Principe, Jose C.

    2007-01-01

    We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a

  8. Hierarchical DSE for multi-ASIP platforms

    DEFF Research Database (Denmark)

    Micconi, Laura; Corvino, Rosilde; Gangadharan, Deepak;

    2013-01-01

    This work proposes a hierarchical Design Space Exploration (DSE) for the design of multi-processor platforms targeted to specific applications with strict timing and area constraints. In particular, it considers platforms integrating multiple Application Specific Instruction Set Processors (ASIPs...

  9. Hierarchical rendering of trees from precomputed multi-layer z-buffers

    Energy Technology Data Exchange (ETDEWEB)

    Max, N. [California Univ., Davis, CA (United States)

    1996-02-01

    Chen and Williams show how precomputed z-buffer images from different fixed viewing positions can be reprojected to produce an image for a new viewpoint. Here images are precomputed for twigs and branches at various levels in the hierarchical structure of a tree, and adaptively combined, depending on the position of the new viewpoint. The precomputed images contain multiple z levels to avoid missing pixels in the reconstruction, subpixel masks for anti-aliasing, and colors and normals for shading after reprojection.

  10. Enhancement of Innate and Adaptive Immune Functions by Multiple Echinacea Species

    Science.gov (United States)

    Zhai, Zili; Liu, Yi; Wu, Lankun; Senchina, David S.; Wurtele, Eve S.; Murphy, Patricia A.; Kohut, Marian L.; Cunnick, Joan E.

    2008-01-01

    Echinacea preparations are commonly used as nonspecific immunomodulatory agents. Alcohol extracts from three widely used Echinacea species, Echinacea angustifolia, Echinacea pallida, and Echinacea purpurea, were investigated for immunomodulating properties. The three Echinacea species demonstrated a broad difference in concentrations of individual lipophilic amides and hydrophilic caffeic acid derivatives. Mice were gavaged once a day (for 7 days) with one of the Echinacea extracts (130 mg/kg) or vehicle and immunized with sheep red blood cells (sRBC) 4 days prior to collection of immune cells for multiple immunological assays. The three herb extracts induced similar, but differential, changes in the percentage of immune cell populations and their biological functions, including increased percentages of CD49+ and CD19+ lymphocytes in spleen and natural killer cell cytotoxicity. Antibody response to sRBC was significantly increased equally by extracts of all three Echinacea species. Concanavalin A-stimulated splenocytes from E. angustifolia- and E. pallida-treated mice demonstrated significantly higher T cell proliferation. In addition, the Echinacea treatment significantly altered the cytokine production by mitogen-stimulated splenic cells. The three herbal extracts significantly increased interferon-γ production, but inhibited the release of tumor necrosis factor-α and interleukin (IL)-1β. Only E. angustifolia- and E. pallida-treated mice demonstrated significantly higher production of IL-4 and increased IL-10 production. Taken together, these findings demonstrated that Echinacea is a wide-spectrum immunomodulator that modulates both innate and adaptive immune responses. In particular, E. angustifolia or E. pallida may have more anti-inflammatory potential. PMID:17887935

  11. Multiple Decoupled CPGs with Local Sensory Feedback for Adaptive Locomotion Behaviors of Bio-inspired Walking Robots

    DEFF Research Database (Denmark)

    Shaker Barikhan, Subhi; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    Walking animals show versatile locomotion. They can also adapt their movement according to the changes of their morphology and the environmental conditions. These emergent properties are realized by biomechanics, distributed central pattern generators (CPGs), local sensory feedback, and their int...... of the front legs, to deal with morphological change, and to synchronize its movement with another robot during a collaborative task....... and the environment through local sensory feedback of each leg. Simulation results show that this bio-inspired approach generates self-organizing emergent locomotion allowing the robot to adaptively form regular patterns, to stably walk while pushing an object with its front legs or performing multiple stepping...

  12. General solution to diagonal model matching control of multiple-output-delay systems and its applications in adaptive scheme

    Institute of Scientific and Technical Information of China (English)

    Yingmin Jia

    2009-01-01

    This paper mainly studies the model matching problem of multiple-output-delay systems in which the reference model is assigned to a diagonal transfer function matrix.A new model matching controller structure is first developed,and then,it is shown that the controller is feasible if and only if the sets of Diophantine equations have common solutions.The obtained controller allows a parametric representation,which shows that an adaptive scheme can be used to tolerate parameter variations in the plants.The resulting adaptive law can guarantee the global stability of the closed-loop systems and the convergence of the output error.

  13. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls....... We introduce an example language and prove the existence of a sound requirement which preserves static correctness while allowing hierarchical procedures. This requirement is further shown to be optimal, in the sense that it imposes as few restrictions as possible. This establishes the theoretical...... basis for a general type hierarchy with static type checking, which enables first-order polymorphism combined with multiple inheritance and specialization in a language with assignments. We extend the results to include opaque types. An opaque version of a type is different from the original but has...

  14. Multiple-model-and-neural-network-based nonlinear multivariable adaptive control

    Institute of Scientific and Technical Information of China (English)

    Yue FU; Tianyou CHAI

    2007-01-01

    A multivariable adaptive controller feasible for implementation on distributed computer systems (DCS) is presented for a class of uncertain nonlinear multivariable discrete time systems. The adaptive controller is composed of a linear adaptive controller, a neural network nonlinear adaptive controller and a switching mechanism. The linear controller can provide boundedness of the input and output signals, and the nonlinear controller can improve the performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method.

  15. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  16. Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction

    Science.gov (United States)

    Hirschi, Andreas

    2009-01-01

    This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on…

  17. Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction

    Science.gov (United States)

    Hirschi, Andreas

    2009-01-01

    This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on…

  18. Advancing adaptive governance of social-ecological systems through theoretical multiplicity

    NARCIS (Netherlands)

    Karpouzoglou, T.D.; Dewulf, A.R.P.J.; Clark, J.

    2016-01-01

    In recent years there has been rising scientific and policy interest in the adaptive governance of social ecological systems. A systematic literature review of adaptive governance research during the period 2005–2014, demonstrates a vibrant debate taking place that spans a variety of empirical and t

  19. Influence of Stellar Multiplicity On Planet Formation. IV. Adaptive Optics Imaging of Kepler Stars With Multiple Transiting Planet Candidates

    CERN Document Server

    Wang, Ji; Xie, Ji-Wei; Ciardi, David R

    2015-01-01

    The Kepler mission provides a wealth of multiple transiting planet systems (MTPS). The formation and evolution of multi-planet systems are likely to be influenced by companion stars given the abundance of multi stellar systems. We study the influence of stellar companions by measuring the stellar multiplicity rate of MTPS. We select 138 bright (KP < 13.5) Kepler MTPS and search for stellar companions with AO imaging data and archival radial velocity (RV) data. We obtain new AO images for 73 MTPS. Other MTPS in the sample have archival AO imaging data from the Kepler Community Follow-up Observation Program (CFOP). From these imaging data, we detect 42 stellar companions around 35 host stars. For stellar separation 1 AU < a < 100 AU, the stellar multiplicity rate is 5.2 $\\pm$ 5.0% for MTPS, which is 2.8{\\sigma} lower than 21.1 $\\pm$ 2.8% for the control sample, i.e., the field stars in the solar neighborhood. We identify two origins for the deficit of stellar companions within 100 AU to MTPS: (1) a sup...

  20. Multiple Time Courses of Vestibular Set-Point Adaptation Revealed by Sustained Magnetic Field Stimulation of the Labyrinth.

    Science.gov (United States)

    Jareonsettasin, Prem; Otero-Millan, Jorge; Ward, Bryan K; Roberts, Dale C; Schubert, Michael C; Zee, David S

    2016-05-23

    A major focus in neurobiology is how the brain adapts its motor behavior to changes in its internal and external environments [1, 2]. Much is known about adaptively optimizing the amplitude and direction of eye and limb movements, for example, but little is known about another essential form of learning, "set-point" adaptation. Set-point adaptation balances tonic activity so that reciprocally acting, agonist and antagonist muscles have a stable platform from which to launch accurate movements. Here, we use the vestibulo-ocular reflex-a simple behavior that stabilizes the position of the eye while the head is moving-to investigate how tonic activity is adapted toward a new set point to prevent eye drift when the head is still [3, 4]. Set-point adaptation was elicited with magneto-hydrodynamic vestibular stimulation (MVS) by placing normal humans in a 7T MRI for 90 min. MVS is ideal for prolonged labyrinthine activation because it mimics constant head acceleration and induces a sustained nystagmus similar to natural vestibular lesions [5, 6]. The MVS-induced nystagmus diminished slowly but incompletely over multiple timescales. We propose a new adaptation hypothesis, using a cascade of imperfect mathematical integrators, that reproduces the response to MVS (and more natural chair rotations), including the gradual decrease in nystagmus as the set point changes over progressively longer time courses. MVS set-point adaptation is a biological model with applications to basic neurophysiological research into all types of movements [7], functional brain imaging [8], and treatment of vestibular and higher-level attentional disorders by introducing new biases to counteract pathological ones [9].

  1. Design of artificial genetic regulatory networks with multiple delayed adaptive responses

    CERN Document Server

    Kaluza, Pablo

    2016-01-01

    Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways.

  2. Kathoey, un genre multiple Kathoey, Multiple Gender : Identity Adaptation and Negotiation Process among Thai MTF Transsexuals in Thailand

    Directory of Open Access Journals (Sweden)

    Cheera Thongkrajai

    2010-07-01

    Full Text Available Les kathoey, transgenres et transsexuels Male-to-Female thaïlandais s’adaptent pour trouver le rôle ou la présentation identitaire convenant aux contextes et aux interactions auxquels elles doivent faire face. Elles peuvent adopter une apparence ou un rôle plus masculin lorsque la situation dans laquelle elles se trouvent ne leur permet pas d’affirmer leur féminité ou que celle-ci pourrait leur nuire socialement. Elles peuvent également accentuer leur féminité pour exprimer leur sentiment identitaire. Les kathoey négocient leur place en faisant preuve de leurs qualités personnelles et de leurs compétences et en mettant également en évidence leurs autres privilèges : statut socio-économique, beauté, etc. pour gagner une reconnaissance sociale. Malgré leur marginalité due à leur différence de genre, elles tentent de s’intégrer dans leurs milieux sociaux en adaptant leur image identitaire, en assumant leurs responsabilités et en réussissant leur vie familiale et professionnelle.Thai male-to-female transsexuals, “kathoey” adapt themselves and adjust their roles and their physical identity i.e., their appearances to different interactional situations. They can adopt their appearance and play masculine roles in the situation in which revealing femininity would be inacceptable or would cause them problem socially. Occasionally, in some situations, they can do the opposite by showing off their femininity they confirm to others who they really are. Kathoey negotiate their identity and their social position by proving and emphasizing on their personal qualities, capacities and others privileges such as social and economical status, beauty, professional competency etc. to gain social acceptation and admiration. Even though they have been marginalized by the society, they tend to reintegrate themselves in their social environment by using different strategies of such as personal identities, showing of their professional

  3. Frequency-adaptive grid-virtual-flux synchronization by multiple second-order generalized integrators under distorted grid conditions

    OpenAIRE

    2015-01-01

    With some of the intermittent new energy and large nonlinear loads, grid voltage unbalance, harmonics, and frequency deviation are increasing year by year. The voltage source converter (VSC) is seriously affected by the various unexpected factors, and the presence of grid impedance makes the situation worse. In order to make the VSC track the nonideal grid quickly and accurately, this paper proposes a frequency-adaptive grid-virtual-flux synchronization by multiple second-order generalized in...

  4. Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

    Directory of Open Access Journals (Sweden)

    Alireza Taravat

    2014-12-01

    Full Text Available Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR, as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM and MultiLayer Perceptron (MLP neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN model generates poor accuracies.

  5. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  6. Adaptive aspirations and performance heterogeneity : Attention allocation among multiple reference points

    NARCIS (Netherlands)

    Blettner, D.P.; He, Z.; Hu, S.; Bettis, R.

    2015-01-01

    Organizations learn and adapt their aspiration levels based on reference points (prior aspiration, prior performance, and prior performance of reference groups). The relative attention that organizations allocate to these reference points impacts organizational search and strategic decisions. Howeve

  7. An adaptive time step scheme for a system of stochastic differential equations with multiple multiplicative noise: chemical Langevin equation, a proof of concept.

    Science.gov (United States)

    Sotiropoulos, Vassilios; Kaznessis, Yiannis N

    2008-01-07

    Models involving stochastic differential equations (SDEs) play a prominent role in a wide range of applications where systems are not at the thermodynamic limit, for example, biological population dynamics. Therefore there is a need for numerical schemes that are capable of accurately and efficiently integrating systems of SDEs. In this work we introduce a variable size step algorithm and apply it to systems of stiff SDEs with multiple multiplicative noise. The algorithm is validated using a subclass of SDEs called chemical Langevin equations that appear in the description of dilute chemical kinetics models, with important applications mainly in biology. Three representative examples are used to test and report on the behavior of the proposed scheme. We demonstrate the advantages and disadvantages over fixed time step integration schemes of the proposed method, showing that the adaptive time step method is considerably more stable than fixed step methods with no excessive additional computational overhead.

  8. Career adaptability development in adolescence: Multiple predictors and effect on sense of power and life satisfaction

    OpenAIRE

    Hirschi, Andreas

    2009-01-01

    This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on Motivational Systems Theory four groups of predictors were assessed: positive emotional disposition, goal decidedness, capability beliefs and socia...

  9. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-11-01

    This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  10. Hierarchically nanostructured materials for sustainable environmental applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-01-01

    This review presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions, and multiple functionalities toward water remediation, biosensing, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing, and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology. PMID:24790946

  11. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Directory of Open Access Journals (Sweden)

    Zheng eRen

    2013-11-01

    Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  12. Influence of Stellar Multiplicity On Planet Formation. III. Adaptive Optics Imaging of Kepler Stars With Gas Giant Planets

    CERN Document Server

    Wang, Ji; Horch, Elliott P; Xie, Ji-Wei

    2015-01-01

    As hundreds of gas giant planets have been discovered, we study how these planets form and evolve in different stellar environments, specifically in multiple stellar systems. In such systems, stellar companions may have a profound influence on gas giant planet formation and evolution via several dynamical effects such as truncation and perturbation. We select 84 Kepler Objects of Interest (KOIs) with gas giant planet candidates. We obtain high-angular resolution images using telescopes with adaptive optics (AO) systems. Together with the AO data, we use archival radial velocity data and dynamical analysis to constrain the presence of stellar companions. We detect 59 stellar companions around 40 KOIs for which we develop methods of testing their physical association. These methods are based on color information and galactic stellar population statistics. We find evidence of suppressive planet formation within 20 AU by comparing stellar multiplicity. The stellar multiplicity rate for planet host stars is 0$^{+5...

  13. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  14. 基于分级规划策略的 A*算法多航迹规划%Multiple routes planning for A* algorithm based on hierarchical planning

    Institute of Scientific and Technical Information of China (English)

    李枭扬; 周德云; 冯琦

    2015-01-01

    In order to avoid setting operating parameters and generate multiple routes steadily,a multiple routes planning for the A* algorithm based on hierarchical planning is proposed.The hierarchical planning is in-troduced to divide the planning process into two parts,the initial route planning and the fine route planning.In the initial route planning,many feasible routes are obtained by setting the middle route point and the A* algo-rithm,then the hierarchical clustering method is presented to obtain the initial reference route so as to avoid the weakness of K-means clustering sensitive to the initial clustering center.In the fine route planning,a variable width path planning channel is designed,and the final multiple routes are obtained by planning in the channel. Simulation results prove the feasibility of the algorithm.%为了避免设置运行参数,稳定地生成多条航迹,提出一种基于分级规划策略的 A*算法多航迹规划技术。采用分级规划策略将规划过程分成初始航迹规划和精细航迹规划两部分。在初始航迹规划中,通过设置中间航迹点并利用 A*算法得到多条初始可行航迹,然后为了避免 K 均值算法对初始聚类中心敏感的问题,提出采用层次聚类法对所得到的初始可行航迹进行聚类,得到初始参考航迹。在精细航迹规划中,设计了一种变宽度的航迹规划通道,并在通道内进行航迹规划以得到最终的多条航迹。仿真实验证明了算法的可行性。

  15. A decision analysis approach to climate adaptation: comparing multiple pathways for multi-decadal decision making

    Science.gov (United States)

    Lin, B. B.; Little, L.

    2013-12-01

    Policy planners around the world are required to consider the implications of adapting to climatic change across spatial contexts and decadal timeframes. However, local level information for planning is often poorly defined, even though climate adaptation decision-making is made at this scale. This is especially true when considering sea level rise and coastal impacts of climate change. We present a simple approach using sea level rise simulations paired with adaptation scenarios to assess a range of adaptation options available to local councils dealing with issues of beach recession under present and future sea level rise and storm surge. Erosion and beach recession pose a large socioeconomic risk to coastal communities because of the loss of key coastal infrastructure. We examine the well-known adaptation technique of beach nourishment and assess various timings and amounts of beach nourishment at decadal time spans in relation to beach recession impacts. The objective was to identify an adaptation strategy that would allow for a low frequency of management interventions, the maintenance of beach width, and the ability to minimize variation in beach width over the 2010 to 2100 simulation period. 1000 replications of each adaptation option were produced against the 90 year simulation in order to model the ability each adaptation option to achieve the three key objectives. Three sets of adaptation scenarios were identified. Within each scenario, a number of adaptation options were tested. The three scenarios were: 1) Fixed periodic beach replenishment of specific amounts at 20 and 50 year intervals, 2) Beach replenishment to the initial beach width based on trigger levels of recession (5m, 10m, 20m), and 3) Fixed period beach replenishment of a variable amount at decadal intervals (every 10, 20, 30, 40, 50 years). For each adaptation option, we show the effectiveness of each beach replenishment scenario to maintain beach width and consider the implications of more

  16. Design of artificial genetic regulatory networks with multiple delayed adaptive responses*

    Science.gov (United States)

    Kaluza, Pablo; Inoue, Masayo

    2016-06-01

    Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways. Supplementary material in the form of one nets file available from the Journal web page at http://dx.doi.org/10.1140/epjb/e2016-70172-9

  17. Climate change adaptation and forests in South Asia: Policy for multiple stakeholders

    Energy Technology Data Exchange (ETDEWEB)

    Deshingkar, P.

    1997-12-31

    Moving from a general understanding of the potential dangers of climate change to real policy and investment requires changes in priorities at the level of government as well as the individual. Information should be disseminated through regional technical co-operation as well as improved communication between relevant institutions within countries. Besides fulfilling scientific and economic criteria for sustainability, forest adaption strategies in South asian countries should aim to be participatory and low cost. In the short term, maximizing the utility of existing institutions and skills may be more practical. The removal of market distortions will also enhance adaptive capacity. Continued research and technological innovation must accompany efforts to change management practices. The immediate priority for donor assistance in this area is to conduct vulnerability assessments, evaluate the constraints and develop a menu of adaption options based on multi criteria analysis of different objectives

  18. Climate change adaptation and forests in South Asia: Policy for multiple stakeholders

    Energy Technology Data Exchange (ETDEWEB)

    Deshingkar, P.

    1997-12-31

    Moving from a general understanding of the potential dangers of climate change to real policy and investment requires changes in priorities at the level of government as well as the individual. Information should be disseminated through regional technical co-operation as well as improved communication between relevant institutions within countries. Besides fulfilling scientific and economic criteria for sustainability, forest adaption strategies in South asian countries should aim to be participatory and low cost. In the short term, maximizing the utility of existing institutions and skills may be more practical. The removal of market distortions will also enhance adaptive capacity. Continued research and technological innovation must accompany efforts to change management practices. The immediate priority for donor assistance in this area is to conduct vulnerability assessments, evaluate the constraints and develop a menu of adaption options based on multi criteria analysis of different objectives

  19. Multiple adaptive losses of alanine-glyoxylate aminotransferase mitochondrial targeting in fruit-eating bats.

    Science.gov (United States)

    Liu, Yang; Xu, Huihui; Yuan, Xinpu; Rossiter, Stephen J; Zhang, Shuyi

    2012-06-01

    The enzyme alanine-glyoxylate aminotransferase 1 (AGT) functions to detoxify glyoxylate before it is converted into harmful oxalate. In mammals, mitochondrial targeting of AGT in carnivorous species versus peroxisomal targeting in herbivores is controlled by two signal peptides that correspond to these respective organelles. Differential expression of the mitochondrial targeting sequence (MTS) is considered an adaptation to diet-specific subcellular localization of glyoxylate precursors. Bats are an excellent group in which to study adaptive changes in dietary enzymes; they show unparalleled mammalian dietary diversification as well as independent origins of carnivory, frugivory, and nectarivory. We studied the AGT gene in bats and other mammals with diverse diets and found that the MTS has been lost in unrelated lineages of frugivorous bats. Conversely, species exhibiting piscivory, carnivory, insectivory, and sanguinivory possessed intact MTSs. Detected positive selection in the AGT of ancestral fruit bats further supports adaptations related to evolutionary changes in diet.

  20. Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.

    Science.gov (United States)

    Wang, Wei; Tong, Shaocheng

    2017-01-10

    This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.

  1. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  2. Hierarchical multiple bit clusters and patterned media enabled by novel nanofabrication techniques -- High resolution electron beam lithography and block polymer self assembly

    Science.gov (United States)

    Xiao, Qijun

    This thesis discusses the full scope of a project exploring the physics of hierarchical clusters of interacting nanomagnets. These clusters may be relevant for novel applications such as multilevel data storage devices. The work can be grouped into three main activities: micromagnetic simulation, fabrication and characterization of proof-of-concept prototype devices, and efforts to scale down the structures by creating the hierarchical structures with the aid of diblock copolymer self assembly. Theoretical micromagnetic studies and simulations based on Landau-Lifshitz-Gilbert (LLG) equation were conducted on nanoscale single domain magnetic entities. For the simulated nanomagnet clusters with perpendicular uniaxial anisotropy, the simulation showed the switching field distributions, the stability of the magnetostatic states with distinctive total cluster perpendicular moments, and the stepwise magnetic switching curves. For simulated nanomagnet clusters with in-plane shape anisotropy, the simulation showed the stepwise switching behaviors governed by thermal agitation and cluster configurations. Proof-of-concept cluster devices with three interacting Co nanomagnets were fabricated by e-beam lithography (EBL) and pulse-reverse electrochemical deposition (PRECD). EBL patterning on a suspended 100 nm SiN membrane showed improved lateral lithography resolution to 30 nm. The Co nanomagnets deposited using the PRECD method showed perpendicular anisotropy. The switching experiments with external applied fields were able to switch the Co nanomagnets through the four magnetostatic states with distinctive total perpendicular cluster magnetization, and proved the feasibility of multilevel data storage devices based on the cluster concept. Shrinking the structures size was experimented by the aid of diblock copolymer. Thick poly(styrene)-b-poly(methyl methacrylate) (PS-b-PMMA) diblock copolymer templates aligned with external electrical field were used to fabricate long Ni

  3. Digital adaptive coronagraphy using SLMs: promising prospects of a novel approach, including high-contrast imaging of multiple stars systems

    Science.gov (United States)

    Kühn, Jonas; Patapis, Polychronis

    2016-07-01

    We introduce a new technological framework for high-contrast coronagraphy, namely digital adaptive coronagraphy (DAC) using spatial light modulators (SLMs), taking advantage of recent advances in this technology. We present proof-of-principle experimental results in the visible, using a transmissive twisted nematic liquid crystal SLM display to show that SLMs can be successfully implemented as focal-plane phase-mask coronagraphs (4QPM, 8OPM,...), and that the technology is essentially in place to address realistic instrumental configurations. We explore a specific application where SLM-based adaptive coronagraphy might be particularly competitive, which is direct imaging of multiple stars systems, by simultaneously nulling multiple point sources in the field. Using a simple approach to compute a brightness-weighted synthetized coronagraphic phase map, we show that in the case of binaries the contrast gain over using a regular phase map can exceed 4 stellar magnitudes for a 1:1 binaries down to separation as close as 1 λ/D. Thanks to video-rate update frequency of the SLM, the technique is in principle compatible with sky rotation in the case of altitude-azimuth telescope mounts, and can address multiple target configurations with no actual mechanical or hardware change.

  4. Architecture for an Adaptive and Intelligent Tutoring System That Considers the Learner's Multiple Intelligences

    Science.gov (United States)

    Hafidi, Mohamed; Bensebaa, Taher

    2015-01-01

    The majority of adaptive and intelligent tutoring systems (AITS) are dedicated to a specific domain, allowing them to offer accurate models of the domain and the learner. The analysis produced from traces left by the users is didactically very precise and specific to the domain in question. It allows one to guide the learner in case of difficulty…

  5. A Primal-Dual Proximal Algorithm for Sparse Template-Based Adaptive Filtering: Application to Seismic Multiple Removal

    CERN Document Server

    Pham, Mai Quyen; Chaux, Caroline; Pesquet, Jean-Christophe

    2014-01-01

    Unveiling meaningful geophysical information from seismic data requires to deal with both random and structured "noises". As their amplitude may be greater than signals of interest (primaries), additional prior information is especially important in performing efficient signal separation. We address here the problem of multiple reflections, caused by wave-field bouncing between layers. Since only approximate models of these phenomena are available, we propose a flexible framework for time-varying adaptive filtering of seismic signals, using sparse representations, based on inaccurate templates. We recast the joint estimation of adaptive filters and primaries in a new convex variational formulation. This approach allows us to incorporate plausible knowledge about noise statistics, data sparsity and slow filter variation in parsimony-promoting wavelet frames. The designed primal-dual algorithm solves a constrained minimization problem that alleviates standard regularization issues in finding hyperparameters. Th...

  6. Analysis of Adaptive Feedback and Echo Cancelation Algorithms in A General Multiple-Microphone and Single-Loudspeaker System

    DEFF Research Database (Denmark)

    Guo, Meng; Elmedyb, Thomas Bo; Jensen, Søren Holdt;

    2011-01-01

    In this paper, we analyze a general multiple-microphone and single-loudspeaker system, where an adaptive algorithm is used to cancel acoustic feedback/echo and a beamformer processes the feedback/echo canceled signals. This system can be viewed as part of a typical hearing aid system and....../or a traditional acoustic echo cancelation system. We introduce and derive an approximation of a useful frequency domain measure - the power transfer function - and show how to predict the system stability bound, convergence rate and the steady-state behavior across time and frequency. Furthermore, we show how...... the derived expressions can be used to determine e.g. the step size parameter in the adaptive algorithms to achieve a desired system property e.g. convergence rate at a specific frequency....

  7. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  8. Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

    Science.gov (United States)

    Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

    2016-06-01

    Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

  9. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  10. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  11. Prediction of Rotor Spun Yarn Strength Using Adaptive Neuro-fuzzy Inference System and Linear Multiple Regression Methods

    Institute of Scientific and Technical Information of China (English)

    NURWAHA Deogratias; WANG Xin-hou

    2008-01-01

    This paper presents a comparison study of two models for predicting the strength of rotor spun cotton yarns from fiber properties. The adaptive neuro-fuzzy system inference (ANFIS) and Multiple Linear Regression models are used to predict the rotor spun yarn strength. Fiber properties and yarn count are used as inputs to train the two models and the count-strength-product (CSP) was the target. The predictive performances of the two models are estimated and compared. We found that the ANFIS has a better predictive power in comparison with linear multipleregression model. The impact of each fiber property is also illustrated.

  12. On-line Multiple-model Based Adaptive Control Reconfiguration for a Class of Non-linear Control Systems

    DEFF Research Database (Denmark)

    Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2000-01-01

    Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets...... of LTI models are employed to approximate the faulty, reconfigured and nominal nonlinear systems respectively with respect to the on-line information of the operating system, and a set of compensating modules are proposed and designed so as to make the local LTI model approximating to the reconfigured...

  13. On-line Multiple-model Based Adaptive Control Reconfiguration for a Class of Non-linear Control Systems

    DEFF Research Database (Denmark)

    Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2000-01-01

    Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets of ...... corresponding to the updating of local LTI models, which validations are determined by the model approximation errors and the optimal index of local design. The test on a nonlinear ship propulsion system shows the promising potential of this method for system reconfiguration...

  14. Spectral Efficiency of Multiple Access Fading Channels with Adaptive Interference Cancellation

    CERN Document Server

    Shakya, Indu L

    2012-01-01

    Reliable estimation of users' channels and data in rapidly time varying fading environments is a very challenging task of multiuser detection (MUD) techniques that promise impressive capacity gains for interference limited systems such as non-orthogonal CDMA and spatial multiplexing MIMO based LTE. This paper analyzes relative channel estimation error performances of conventional single user and multiuser receivers for an uplink of DS-CDMA and shows their impact on output signal to interference and noise ratio (SINR) performances. Mean squared error (MSE) of channel estimation and achievable spectral efficiencies of these receivers obtained from the output SINR calculations are then compared with that achieved with new adaptive interference canceling receivers. It is shown that the adaptive receivers using successive (SIC) and parallel interference cancellation (PIC) methods offer much improved channel estimation and SINR performances, and hence significant increase in achievable sum date rates.

  15. A Microswitch-Cluster Program to Foster Adaptive Responses and Head Control in Students with Multiple Disabilities: Replication and Validation Assessment

    Science.gov (United States)

    Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Oliva, Doretta; Gatti, Michela; Manfredi, Francesco; Megna, Gianfranco; La Martire, Maria L.; Tota, Alessia; Smaldone, Angela; Groeneweg, Jop

    2008-01-01

    A program relying on microswitch clusters (i.e., combinations of microswitches) and preferred stimuli was recently developed to foster adaptive responses and head control in persons with multiple disabilities. In the last version of this program, preferred stimuli (a) are scheduled for adaptive responses occurring in combination with head control…

  16. Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision-Making Framework for Climate Change Adaptation.

    Science.gov (United States)

    Shortridge, Julie E; Guikema, Seth D

    2016-12-01

    There is increasing concern over deep uncertainty in the risk analysis field as probabilistic models of uncertainty cannot always be confidently determined or agreed upon for many of our most pressing contemporary risk challenges. This is particularly true in the climate change adaptation field, and has prompted the development of a number of frameworks aiming to characterize system vulnerabilities and identify robust alternatives. One such methodology is robust decision making (RDM), which uses simulation models to assess how strategies perform over many plausible conditions and then identifies and characterizes those where the strategy fails in a process termed scenario discovery. While many of the problems to which RDM has been applied are characterized by multiple objectives, research to date has provided little insight into how treatment of multiple criteria impacts the failure scenarios identified. In this research, we compare different methods for incorporating multiple objectives into the scenario discovery process to evaluate how they impact the resulting failure scenarios. We use the Lake Tana basin in Ethiopia as a case study, where climatic and environmental uncertainties could impact multiple planned water infrastructure projects, and find that failure scenarios may vary depending on the method used to aggregate multiple criteria. Common methods used to convert multiple attributes into a single utility score can obscure connections between failure scenarios and system performance, limiting the information provided to support decision making. Applying scenario discovery over each performance metric separately provides more nuanced information regarding the relative sensitivity of the objectives to different uncertain parameters, leading to clearer insights on measures that could be taken to improve system robustness and areas where additional research might prove useful. © 2016 Society for Risk Analysis.

  17. Disability-Aware Adaptive and Personalised Learning for Students with Multiple Disabilities

    Science.gov (United States)

    Nganji, Julius T.; Brayshaw, Mike

    2017-01-01

    Purpose: The purpose of this paper is to address how virtual learning environments (VLEs) can be designed to include the needs of learners with multiple disabilities. Specifically, it employs AI to show how specific learning materials from a huge repository of learning materials can be recommended to learners with various disabilities. This is…

  18. Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure

    Science.gov (United States)

    Yoo, Yun Joo; Sun, Lei; Poirier, Julia G.; Paterson, Andrew D.

    2016-01-01

    ABSTRACT By jointly analyzing multiple variants within a gene, instead of one at a time, gene‐based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster‐specific effects in a quadratic sum of squares and cross‐products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well‐powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P‐value, variance‐component, and principal‐component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene‐specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome‐wide analysis. The cluster construction of the MLC test statistics helps reveal within‐gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations. PMID:27885705

  19. Adaptive Subspace-based Inverse Projections via Division into Multiple Sub-problems for Missing Image Data Restoration.

    Science.gov (United States)

    Ogawa, Takahiro; Haseyama, Miki

    2016-10-10

    This paper presents adaptive subspace-based inverse projections via division into multiple sub-problems (ASIP-DIMS) for missing image data restoration. In the proposed method, a target problem for estimating missing image data is divided into multiple sub-problems, and each sub-problem is iteratively solved with constraints of other known image data. By projection into a subspace model of image patches, the solution of each subproblem is calculated, where we call this procedure "subspacebased inverse projection" for simplicity. The proposed method can use higher-dimensional subspaces for finding unique solutions in each sub-problem, and successful restoration becomes feasible since a high level of image representation performance can be preserved. This is the biggest contribution of this paper. Furthermore, the proposed method generates several subspaces from known training examples and enables derivation of a new criterion in the above framework to adaptively select the optimal subspace for each target patch. In this way, the proposed method realizes missing image data restoration using ASIP-DIMS. Since our method can estimate any kind of missing image data, its potential in two image restoration tasks, image inpainting and super-resolution, based on several methods for multivariate analysis is also shown in this paper.

  20. High-resolution adaptive optics scanning laser ophthalmoscope with multiple deformable mirrors

    Science.gov (United States)

    Chen, Diana C.; Olivier, Scot S.; Jones; Steven M.

    2010-02-23

    An adaptive optics scanning laser ophthalmoscopes is introduced to produce non-invasive views of the human retina. The use of dual deformable mirrors improved the dynamic range for correction of the wavefront aberrations compared with the use of the MEMS mirror alone, and improved the quality of the wavefront correction compared with the use of the bimorph mirror alone. The large-stroke bimorph deformable mirror improved the capability for axial sectioning with the confocal imaging system by providing an easier way to move the focus axially through different layers of the retina.

  1. Peripheral NK cell phenotypes: multiple changing of faces of an adapting, developing cell.

    Science.gov (United States)

    Perussia, Bice; Chen, Yingying; Loza, Matthew J

    2005-02-01

    We have defined the existence of developmental relationships among human peripheral NK cells with distinct phenotypic and functional characteristics. These findings closely parallel the changes that occur in vivo during NK cell development, and in vitro in experimental culture systems supporting NK cell generation from hematopoietic progenitors. These new insights provide a simplified framework to understand NK cell immunobiology and the cellular bases for their roles in innate immunity, initiation and maintenance of immune responses via regulation of adaptive and accessory cell functions, and immune pathologies.

  2. Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata

    Science.gov (United States)

    Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.

    2016-01-01

    It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345

  3. Regressão múltipla stepwise e hierárquica em Psicologia Organizacional: aplicações, problemas e soluções Stepwise and hierarchical multiple regression in organizational psychology: Applications, problemas and solutions

    Directory of Open Access Journals (Sweden)

    Gardênia Abbad

    2002-01-01

    Full Text Available Este artigo discute algumas aplicações das técnicas de análise de regressão múltipla stepwise e hierárquica, as quais são muito utilizadas em pesquisas da área de Psicologia Organizacional. São discutidas algumas estratégias de identificação e de solução de problemas relativos à ocorrência de erros do Tipo I e II e aos fenômenos de supressão, complementaridade e redundância nas equações de regressão múltipla. São apresentados alguns exemplos de pesquisas nas quais esses padrões de associação entre variáveis estiveram presentes e descritas as estratégias utilizadas pelos pesquisadores para interpretá-los. São discutidas as aplicações dessas análises no estudo de interação entre variáveis e na realização de testes para avaliação da linearidade do relacionamento entre variáveis. Finalmente, são apresentadas sugestões para lidar com as limitações das análises de regressão múltipla (stepwise e hierárquica.This article discusses applications of stepwise and hierarchical multiple regression analyses to research in organizational psychology. Strategies for identifying type I and II errors, and solutions to potential problems that may arise from such errors are proposed. In addition, phenomena such as suppression, complementarity, and redundancy are reviewed. The article presents examples of research where these phenomena occurred, and the manner in which they were explained by researchers. Some applications of multiple regression analyses to studies involving between-variable interactions are presented, along with tests used to analyze the presence of linearity among variables. Finally, some suggestions are provided for dealing with limitations implicit in multiple regression analyses (stepwise and hierarchical.

  4. Multiple symbiont acquisition strategies as an adaptive mechanism in the coral Stylophora pistillata.

    Science.gov (United States)

    Byler, Kristen A; Carmi-Veal, Maya; Fine, Maoz; Goulet, Tamar L

    2013-01-01

    In obligate symbioses, the host's survival relies on the successful acquisition and maintenance of symbionts. Symbionts can either be transferred from parent to offspring via direct inheritance (vertical transmission) or acquired anew each generation from the environment (horizontal transmission). With vertical symbiont transmission, progeny benefit by not having to search for their obligate symbionts, and, with symbiont inheritance, a mechanism exists for perpetuating advantageous symbionts. But, if the progeny encounter an environment that differs from that of their parent, they may be disadvantaged if the inherited symbionts prove suboptimal. Conversely, while in horizontal symbiont acquisition host survival hinges on an unpredictable symbiont source, an individual host may acquire genetically diverse symbionts well suited to any given environment. In horizontal acquisition, however, a potentially advantageous symbiont will not be transmitted to subsequent generations. Adaptation in obligate symbioses may require mechanisms for both novel symbiont acquisition and symbiont inheritance. Using denaturing-gradient gel electrophoresis and real-time PCR, we identified the dinoflagellate symbionts (genus Symbiodinium) hosted by the Red Sea coral Stylophora pistillata throughout its ontogenesis and over depth. We present evidence that S. pistillata juvenile colonies may utilize both vertical and horizontal symbiont acquisition strategies. By releasing progeny with maternally derived symbionts, that are also capable of subsequent horizontal symbiont acquisition, coral colonies may acquire physiologically advantageous novel symbionts that are then perpetuated via vertical transmission to subsequent generations. With symbiont inheritance, natural selection can act upon the symbiotic variability, providing a mechanism for coral adaptation.

  5. Multiple symbiont acquisition strategies as an adaptive mechanism in the coral Stylophora pistillata.

    Directory of Open Access Journals (Sweden)

    Kristen A Byler

    Full Text Available In obligate symbioses, the host's survival relies on the successful acquisition and maintenance of symbionts. Symbionts can either be transferred from parent to offspring via direct inheritance (vertical transmission or acquired anew each generation from the environment (horizontal transmission. With vertical symbiont transmission, progeny benefit by not having to search for their obligate symbionts, and, with symbiont inheritance, a mechanism exists for perpetuating advantageous symbionts. But, if the progeny encounter an environment that differs from that of their parent, they may be disadvantaged if the inherited symbionts prove suboptimal. Conversely, while in horizontal symbiont acquisition host survival hinges on an unpredictable symbiont source, an individual host may acquire genetically diverse symbionts well suited to any given environment. In horizontal acquisition, however, a potentially advantageous symbiont will not be transmitted to subsequent generations. Adaptation in obligate symbioses may require mechanisms for both novel symbiont acquisition and symbiont inheritance. Using denaturing-gradient gel electrophoresis and real-time PCR, we identified the dinoflagellate symbionts (genus Symbiodinium hosted by the Red Sea coral Stylophora pistillata throughout its ontogenesis and over depth. We present evidence that S. pistillata juvenile colonies may utilize both vertical and horizontal symbiont acquisition strategies. By releasing progeny with maternally derived symbionts, that are also capable of subsequent horizontal symbiont acquisition, coral colonies may acquire physiologically advantageous novel symbionts that are then perpetuated via vertical transmission to subsequent generations. With symbiont inheritance, natural selection can act upon the symbiotic variability, providing a mechanism for coral adaptation.

  6. Fuzzy Analytical Hierarchical Process and Spatially Explicit Uncertainty Analysis Approach for Multiple Forest Fire Risk Mapping. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

    OpenAIRE

    2016-01-01

    Uncertainty is associated with GIS- Multi Criteria Decision Analysis (GIS-MCDA) when applied to disaster modeling. Technically speaking, GIS-MCDA model outcomes are prone to multiple types of uncertainty and error. In order to minimize the inherent uncertainty, within this research we introduced a novel approach of spatial explicit uncertainty and sensitivity analysis for GIS-MCDA models. This novel approach is developed based on early works published by FEZIZADEH et al. 2014a, 2014b and make...

  7. Sensory extinction and sensory reinforcement principles for programming multiple adaptive behavior change.

    Science.gov (United States)

    Rincover, A; Cook, R; Peoples, A; Packard, D

    1979-01-01

    The role of sensory reinforcement was examined in programming multiple treatment gains in self-stimulation and spontaneous play for developmentally disabled children. Two phases were planned. First, we attempted to identify reinforcers maintaining self-stimulation. Sensory Extinction procedures were implemented in which auditory, proprioceptive, or visual sensory consequences of self-stimulatory behavior were systematically removed and reintroduced in a reversal design. When self-stimulation was decreased or eliminated as a result of removing one of these sensory consequences, the functional sensory consequence was designated as a child's preferred sensory reinforcer. In Phase 2, we assessed whether children would play selectively with toys producing the preferred kind of sensory stimulation. The results showed the following. (1) Self-stimulatory behavior was found to be maintained by sensory reinforcement. When the sensory reinforcer was removed, self-stimulation extinguished. (2) The sensory reinforcers identified for self-stimulatory behavior also served as reinforcers for new, appropriate toy play. (3) The multiple treatment gains observed appeared to be relatively durable in the absence of external reinforcers for play or restraints on self-stimulation. These results illustrate one instance in which multiple behavior change may be programmed in a predictable, lawful fashion by using "natural communities of sensory reinforcement."

  8. Immunomodulatory effects and adaptive immune response to daratumumab in multiple myeloma

    DEFF Research Database (Denmark)

    Krejcik, Jakub; Casneuf, T.; Nijhof, I.

    2015-01-01

    .048) in responders compared to nonresponders. Increased antiviral T-cell responses were observed post-DARA treatment, particularly in responders. Interestingly, a novel subpopulation of regulatory T cells was identified that expressed high levels of CD38. These cells comprised ~10% of all Tregs and were depleted...... by one DARA infusion. In ex vivo analyses, CD38+ Tregs appeared to be highly immune suppressive compared to CD38-Tregs. Conclusions: Robust T cell increases, increased CD8+: CD4+ ratios, increased antiviral responses, and increased T cell clonality were all observed after DARA treatment in a heavily...... including increased antigen presentation through phagocytosis, targeting of immune suppressive Tregs, and increased adaptive immune responses....

  9. Emerging hierarchies in dynamically adapting webs

    Science.gov (United States)

    Katifori, Eleni; Graewer, Johannes; Magnasco, Marcelo; Modes, Carl

    Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. We quantify the hierarchical organization of the networks by developing an algorithm that decomposes the architecture to multiple scales and analyzes how the organization in each scale relates to that of the scale above and below it. The methodologies developed in this work are applicable to a wide range of systems including the slime mold physarum polycephalum, human microvasculature, and force chains in granular media.

  10. Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems

    Directory of Open Access Journals (Sweden)

    Chen Jiang

    2017-06-01

    Full Text Available The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS and the Inertial Navigation System (INS integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.

  11. A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

    Science.gov (United States)

    Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

    2017-05-01

    Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Resolving the Multiple Outflows in the Egg Nebula with Keck II Laser Guide Star Adaptive Optics

    CERN Document Server

    Mignant, D Le; Bouchez, A; Campbell, R; van Dam, M; Chin, J; Johansson, E; Hartman, S; Lafon, R; Lyke, J; Stomski, P; Summers, D; Wizinowich, P

    2007-01-01

    The Egg Nebula has been regarded as the archetype of bipolar proto-planetary nebulae, yet we lack a coherent model that can explain the morphology and kinematics of the nebular and dusty components observed at high-spatial and spectral resolution. Here, we report on two sets of observations obtained with the Keck Adaptive Optics Laser Guide Star: H to M-band NIRC2 imaging, and narrow bandpath K-band OSIRIS 3-D imaging-spectroscopy (through the H2 2.121micron emission line). While the central star or engine remains un-detected at all bands, we clearly resolve the dusty components in the central region and confirm that peak A is not a companion star. The spatially-resolved spectral analysis provide kinematic information of the H_2 emission regions in the eastern and central parts of the nebula and show projected velocities for the H_2 emission higher than 100 km/s. We discuss these observations against a possible formation scenario for the nebular components.

  13. Adaptive Optics Simulation for the World's Largest Telescope on Multicore Architectures with Multiple GPUs

    KAUST Repository

    Ltaief, Hatem

    2016-06-02

    We present a high performance comprehensive implementation of a multi-object adaptive optics (MOAO) simulation on multicore architectures with hardware accelerators in the context of computational astronomy. This implementation will be used as an operational testbed for simulating the de- sign of new instruments for the European Extremely Large Telescope project (E-ELT), the world\\'s biggest eye and one of Europe\\'s highest priorities in ground-based astronomy. The simulation corresponds to a multi-step multi-stage pro- cedure, which is fed, near real-time, by system and turbulence data coming from the telescope environment. Based on the PLASMA library powered by the OmpSs dynamic runtime system, our implementation relies on a task-based programming model to permit an asynchronous out-of-order execution. Using modern multicore architectures associated with the enormous computing power of GPUS, the resulting data-driven compute-intensive simulation of the entire MOAO application, composed of the tomographic reconstructor and the observing sequence, is capable of coping with the aforementioned real-time challenge and stands as a reference implementation for the computational astronomy community.

  14. Outline of a multiple-access communication network based on adaptive arrays

    Science.gov (United States)

    Zohar, S.

    1982-01-01

    Attention is given to a narrow-band communication system consisting of a central station trying to receive signals simultaneously from K spatially distinct mobile users sharing the same frequencies. One example of such a system is a group of aircraft and ships transmitting messages to a communication satellite. A reasonable approach to such a multiple access system may be based on equipping the central station with an n-element antenna array where n is equal to or greater than K. The array employs K sets of n weights to segregate the signals received from the K users. The weights are determined by direct computation based on position information transmitted by the users. A description is presented of an improved technique which makes it possible to reduce significantly the number of required computer operations in comparison to currently known techniques.

  15. Treatment Protocols as Hierarchical Structures

    Science.gov (United States)

    Ben-Bassat, Moshe; Carlson, Richard W.; Puri, Vinod K.; Weil, Max Harry

    1978-01-01

    We view a treatment protocol as a hierarchical structure of therapeutic modules. The lowest level of this structure consists of individual therapeutic actions. Combinations of individual actions define higher level modules, which we call routines. Routines are designed to manage limited clinical problems, such as the routine for fluid loading to correct hypovolemia. Combinations of routines and additional actions, together with comments, questions, or precautions organized in a branching logic, in turn, define the treatment protocol for a given disorder. Adoption of this modular approach may facilitate the formulation of treatment protocols, since the physician is not required to prepare complex flowcharts. This hierarchical approach also allows protocols to be updated and modified in a flexible manner. By use of such a standard format, individual components may be fitted together to create protocols for multiple disorders. The technique is suited for computer implementation. We believe that this hierarchical approach may facilitate standarization of patient care as well as aid in clinical teaching. A protocol for acute pancreatitis is used to illustrate this technique.

  16. DOA Estimation of Low Altitude Target Based on Adaptive Step Glowworm Swarm Optimization-multiple Signal Classification Algorithm

    Directory of Open Access Journals (Sweden)

    Zhou Hao

    2015-06-01

    Full Text Available The traditional MUltiple SIgnal Classification (MUSIC algorithm requires significant computational effort and can not be employed for the Direction Of Arrival (DOA estimation of targets in a low-altitude multipath environment. As such, a novel MUSIC approach is proposed on the basis of the algorithm of Adaptive Step Glowworm Swarm Optimization (ASGSO. The virtual spatial smoothing of the matrix formed by each snapshot is used to realize the decorrelation of the multipath signal and the establishment of a fullorder correlation matrix. ASGSO optimizes the function and estimates the elevation of the target. The simulation results suggest that the proposed method can overcome the low altitude multipath effect and estimate the DOA of target readily and precisely without radar effective aperture loss.

  17. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    KAUST Repository

    Hwang, Kyusung

    2011-02-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  18. Adaptive control using multiple models in a field bus network; Controle adaptativo utilizando multiplos modelos em uma rede Fieldbus

    Energy Technology Data Exchange (ETDEWEB)

    Uberti, Rafael Carvalho; Santos, Ricardo Souza; Plucenio, Agustinho [Santa Catarina Univ., Florianopolis, SC (Brazil). Dept. de Automacao e Sistemas]. E-mail: uberti, rsantos, plucenio@das.ufsc.br

    2003-07-01

    The majority of the oil industry processes are characterized by a nonlinear behavior. For this class of systems traditional controllers based on a linear feedback structure with constant gains cannot achieve a good performance in a wide range of operation, rejecting disturbances. Then, it is necessary to apply new design of control strategies. The proposal of this work is to apply an adaptive controller adopting a multiple model structure using elements of fuzzy logic, allowing a smooth transition between different regions of operation. The proposed approach is based on Field bus Networks, due to the increased utilization of this technology in the oil and gas industry. To clarify the application a controller is designed for a level control problem of an educational plant based on Foundation Field bus. (author)

  19. Adaptable User Interface Based on the Ecological Interface Design Concept for Multiple Robots Operating Works with Uncertainty

    Directory of Open Access Journals (Sweden)

    Hiroshi Furukawa

    2010-01-01

    Full Text Available Problem statement: When supervising a team of semi-autonomous robots, the operator’s task is not only the manipulation of each robot but also achievement of the top goal that is assigned to the entire team of humans and robots. The operators are demanded to comprehend highly complex states and make appropriate decisions in dynamic environment using the limited cognitive resources. The Ecological Interface Design (EID is a design approach based on visualization of constraints in study environment onto the interface to reduce the cognitive workload. Our research question was “How should we design Human-Robot Interface (HRI that allows operators to understand states of multiple robots systems working in environment with uncertainty?” Approach: Our proposed method was Adaptable User Interface (AUI with EID. The interface is a framework that allowed the operators to take selectable use of displays indicating different types of functional information. Two types of expressions of functions were defined for indicating states of functions: indication of functional disposition and of effectiveness. Three cognitive experiments were conducted to reveal potential efficacy of the method using an experimental test-bed simulation. Results: The results of the first and second experiments showed that usefulness of functional indications is different from different works, tasks and operators. The third experiment demonstrated that operators could select and use appropriate information among a set of indicators with different types and levels of functional information, which are adaptive for tasks, their strategies, their skills and available information and knowledge about the tasks. Conclusion: From the remarks, it can be concluded that the proposed method (AUI+EID is a useful and feasible HRI method for multiple robot operations, even knowledge about the work is not sufficient to build a set of dedicated indicators each has only necessary information for a

  20. MULTIPASS, a rice R2R3-type MYB transcription factor, regulates adaptive growth by integrating multiple hormonal pathways.

    Science.gov (United States)

    Schmidt, Romy; Schippers, Jos H M; Mieulet, Delphine; Obata, Toshihiro; Fernie, Alisdair R; Guiderdoni, Emmanuel; Mueller-Roeber, Bernd

    2013-10-01

    Growth regulation is an important aspect of plant adaptation during environmental perturbations. Here, the role of MULTIPASS (OsMPS), an R2R3-type MYB transcription factor of rice, was explored. OsMPS is induced by salt stress and expressed in vegetative and reproductive tissues. Over-expression of OsMPS reduces growth under non-stress conditions, while knockdown plants display increased biomass. OsMPS expression is induced by abscisic acid and cytokinin, but is repressed by auxin, gibberellin and brassinolide. Growth retardation caused by OsMPS over-expression is partially restored by auxin application. Expression profiling revealed that OsMPS negatively regulates the expression of EXPANSIN (EXP) and cell-wall biosynthesis as well as phytohormone signaling genes. Furthermore, the expression of OsMPS-dependent genes is regulated by auxin, cytokinin and abscisic acid. Moreover, we show that OsMPS is a direct upstream regulator of OsEXPA4, OsEXPA8, OsEXPB2, OsEXPB3, OsEXPB6 and the endoglucanase genes OsGLU5 and OsGLU14. The multiple responses of OsMPS and its target genes to various hormones suggest an integrative function of OsMPS in the cross-talk between phytohormones and the environment to regulate adaptive growth.

  1. The collapsed cone algorithm for (192)Ir dosimetry using phantom-size adaptive multiple-scatter point kernels.

    Science.gov (United States)

    Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc

    2015-07-07

    /phantom for which low doses at phantom edges can be overestimated by 2-5 %. It would be possible to improve the situation by using a point kernel for multiple-scatter dose adapted to the patient/phantom dimensions at hand.

  2. The collapsed cone algorithm for 192Ir dosimetry using phantom-size adaptive multiple-scatter point kernels

    Science.gov (United States)

    Carlsson Tedgren, Åsa; Plamondon, Mathieu; Beaulieu, Luc

    2015-07-01

    /phantom for which low doses at phantom edges can be overestimated by 2-5 %. It would be possible to improve the situation by using a point kernel for multiple-scatter dose adapted to the patient/phantom dimensions at hand.

  3. Multiple Sclerosis Walking Scale-12, translation, adaptation and validation for the Persian language population.

    Science.gov (United States)

    Nakhostin Ansari, Noureddin; Naghdi, Soofia; Mohammadi, Roghaye; Hasson, Scott

    2015-02-01

    The Multiple Sclerosis Walking Scale-12 (MSWS-12) is a multi-item rating scale used to assess the perspectives of patients about the impact of MS on their walking ability. The aim of this study was to examine the reliability and validity of the MSWS-12 in Persian speaking patients with MS. The MSWS-12 questionnaire was translated into Persian language according to internationally adopted standards involving forward-backward translation, reviewed by an expert committee and tested on the pre-final version. In this cross-sectional study, 100 participants (50 patients with MS and 50 healthy subjects) were included. The MSWS-12 was administered twice 7 days apart to 30 patients with MS for test and retest reliability. Internal consistency reliability was Cronbach's α 0.96 for test and 0.97 for retest. There were no significant floor or ceiling effects. Test-retest reliability was excellent (intraclass correlation coefficient [ICC] agreement of 0.98, 95% CI, 0.95-0.99) confirming the reproducibility of the Persian MSWS-12. Construct validity using known group methods was demonstrated through a significant difference in the Persian MSWS-12 total score between the patients with MS and healthy subjects. Factor analysis extracted 2 latent factors (79.24% of the total variance). A second factor analysis suggested the 9-item Persian MSWS as a unidimensional scale for patients with MS. The Persian MSWS-12 was found to be valid and reliable for assessing walking ability in Persian speaking patients with MS.

  4. Evolution of urea transporters in vertebrates: adaptation to urea's multiple roles and metabolic sources.

    Science.gov (United States)

    LeMoine, Christophe M R; Walsh, Patrick J

    2015-06-01

    In the two decades since the first cloning of the mammalian kidney urea transporter (UT-A), UT genes have been identified in a plethora of organisms, ranging from single-celled bacteria to metazoans. In this review, focusing mainly on vertebrates, we first reiterate the multiple catabolic and anabolic pathways that produce urea, then we reconstruct the phylogenetic history of UTs, and finally we examine the tissue distribution of UTs in selected vertebrate species. Our analysis reveals that from an ancestral UT, three homologues evolved in piscine lineages (UT-A, UT-C and UT-D), followed by a subsequent reduction to a single UT-A in lobe-finned fish and amphibians. A later internal tandem duplication of UT-A occurred in the amniote lineage (UT-A1), followed by a second tandem duplication in mammals to give rise to UT-B. While the expected UT expression is evident in excretory and osmoregulatory tissues in ureotelic taxa, UTs are also expressed ubiquitously in non-ureotelic taxa, and in tissues without a complete ornithine-urea cycle (OUC). We posit that non-OUC production of urea from arginine by arginase, an important pathway to generate ornithine for synthesis of molecules such as polyamines for highly proliferative tissues (e.g. testis, embryos), and neurotransmitters such as glutamate for neural tissues, is an important evolutionary driving force for the expression of UTs in these taxa and tissues.

  5. Robust central pattern generators for embodied hierarchical reinforcement learning

    NARCIS (Netherlands)

    Snel, M.; Whiteson, S.; Kuniyoshi, Y.

    2011-01-01

    Hierarchical organization of behavior and learning is widespread in animals and robots, among others to facilitate dealing with multiple tasks. In hierarchical reinforcement learning, agents usually have to learn to recombine or modulate low-level behaviors when facing a new task, which costs time t

  6. Hierarchical Nanoceramics for Industrial Process Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

    2011-07-15

    This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

  7. A Novel Architecture for Adaptive Traffic Control in Network on Chip using Code Division Multiple Access Technique

    Directory of Open Access Journals (Sweden)

    Fatemeh. Dehghani

    2016-08-01

    Full Text Available Network on chip has emerged as a long-term and effective method in Multiprocessor System-on-Chip communications in order to overcome the bottleneck in bus based communication architectures. Efficiency and performance of network on chip is so dependent on the architecture and structure of the network. In this paper a new structure and architecture for adaptive traffic control in network on chip using Code Division Multiple Access technique is presented. To solve the problem of synchronous access to bus based interconnection the code division multiple access technique was applied. In the presented structure that is based upon mesh topology and simple routing method we attempted to increase the exchanged data bandwidth rate among different cores. Also an attempt has been made to increase the performance by isolating the target address transfer path from data transfer path. The main goal of this paper is presenting a new structure to improve energy consumption, area and maximum frequency in network on chip systems using information coding and decoding techniques. The presented structure is simulated using Xilinx ISE software and the results show effectiveness of this architecture.

  8. Muscles-Specific MicroRNA-206 Targets Multiple Components in Dystrophic Skeletal Muscle Representing Beneficial Adaptations.

    Science.gov (United States)

    Amirouche, Adel; Jahnke, Vanessa E; Lunde, John A; Koulmann, Nathalie; Freyssenet, Damien G; Jasmin, Bernard J

    2016-12-21

    Over the last several years, converging lines of evidence have indicated that miR-206 plays a pivotal role in promoting muscle differentiation and regeneration, thereby potentially impacting positively on the progression of neuromuscular disorders including Duchenne muscular dystrophy (DMD). Despite several studies showing the regulatory function of miR-206 on target mRNAs in skeletal muscle cells, the effects of overexpression of miR-206 in dystrophic muscles remain to be established. Here, we found that miR-206 overexpression in mdx mouse muscles simultaneously targets multiple mRNAs and proteins implicated in satellite cell differentiation, muscle regeneration, and at the neuromuscular junction. Overexpression of miR-206 also increased the levels of several muscle-specific mRNAs/proteins while enhancing utrophin A expression at the sarcolemma. Finally, we also observed that the increase expression of miR-206 in dystrophin-deficient mouse muscle decreased the production of pro-inflammatory cytokines and infiltration of macrophages. Taken together, our results show that miR-206 acts as a pleiotropic regulator that targets multiple key mRNAs and proteins expected to provide beneficial adaptations in dystrophic muscle, thus highlighting its therapeutic potential for DMD.

  9. Time course of strength adaptations following high-intensity resistance training in individuals with multiple sclerosis.

    Science.gov (United States)

    Manca, A; Dvir, Z; Dragone, D; Mureddu, G; Bua, G; Deriu, Franca

    2017-04-01

    No evidence exists regarding the time course and clinical relevance of muscle strength improvements following resistance training in people with multiple sclerosis (PwMS). The purpose of this study was to investigate the temporal course and the clinical meaningfulness of the changes in strength induced by high-intensity resistance training and whether these changes impact on muscle endurance to fatigue and functional outcomes. PwMS with predominantly unilateral hyposthenia of the ankle dorsiflexors underwent a 6-week isokinetic training of the more affected ankle dorsiflexion muscles. Maximal strength was measured at baseline, during the training on a weekly basis, at the end of the intervention (POST) and at the 12-week follow-up. Muscle endurance to fatigue, mobility and walking outcomes were assessed at baseline, POST and follow-up. Reproducibility and responsiveness analyses were performed. Significant gains in muscle strength were already detected after 3 weeks of training with no further improvements in the following weeks. These improvements exceeded the cutoff values for relevant changes and were also positively correlated to improved muscle endurance to fatigue and mobility measures. None of the observed changes in muscle performance and functional outcomes was retained at the follow-up. Preliminary evidence showed that 3 weeks of high-intensity resistance training induces consistent and meaningful improvements in muscle performance of the ankle dorsiflexors in PwMS. These findings may have practical dose-response and cost-effectiveness implications in the management of MS-induced muscle weakness, potentially enhancing the understanding of the response to training exhibited by PwMS. ClinicalTrials.gov identifier NCT02010398; December 2013.

  10. Adaptations of a Yucatec Maya Multiple-Use Ecological Management Strategy to Ecotourism

    Directory of Open Access Journals (Sweden)

    Eduardo García-Frapolli

    2008-12-01

    Full Text Available Over the last 40 years, the Yucatan Peninsula has experienced the implementation and promotion of development programs that have economically and ecologically shaped this region of Mexico. Nowadays, tourist development has become the principal catalyst of social, economic, and ecological changes in the region. All these programs, which are based on a specialization rationale, have historically clashed with traditional Yucatec Maya management of natural resources. Using participant observation, informal and semi-structured interviews, and life-history interviews, we carried out an assessment of a Yucatec Maya natural resources management system implemented by three indigenous communities located within a natural protected area. The assessment, intended as an examination of the land-use practices and productive strategies currently implemented by households, was framed within an ecological-economic approach to ecosystems appropriation. To examine the influence of tourism on the multiple-use strategy, we contrasted productive activities among households engaged primarily in ecotourism with those more oriented toward traditional agriculture. Results show that households from these communities allocated an annual average of 586 work days to implement a total of 15 activities in five different land-use units, and that those figures vary significantly in accordance with households' productive strategy (agriculture oriented or service oriented. As the region is quickly becoming an important tourist destination and ecotourism is replacing many traditional activities, we discuss the need for a balance between traditional and alternative economic activities that will allow Yucatec Maya communities to diversify their economic options without compromising existing local management practices.

  11. GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

    CERN Document Server

    Miki, Yohei

    2016-01-01

    The tree method is a widely implemented algorithm for collisionless $N$-body simulations in astrophysics well suited for GPU(s). Adopting hierarchical time stepping can accelerate $N$-body simulations; however, it is infrequently implemented and its potential remains untested in GPU implementations. We have developed a Gravitational Oct-Tree code accelerated by HIerarchical time step Controlling named \\texttt{GOTHIC}, which adopts both the tree method and the hierarchical time step. The code adopts some adaptive optimizations by monitoring the execution time of each function on-the-fly and minimizes the time-to-solution by balancing the measured time of multiple functions. Results of performance measurements with realistic particle distribution performed on NVIDIA Tesla M2090, K20X, and GeForce GTX TITAN X, which are representative GPUs of the Fermi, Kepler, and Maxwell generation of GPUs, show that the hierarchical time step achieves a speedup by a factor of around 3--5 times compared to the shared time step...

  12. GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

    Science.gov (United States)

    Miki, Yohei; Umemura, Masayuki

    2017-04-01

    The tree method is a widely implemented algorithm for collisionless N-body simulations in astrophysics well suited for GPU(s). Adopting hierarchical time stepping can accelerate N-body simulations; however, it is infrequently implemented and its potential remains untested in GPU implementations. We have developed a Gravitational Oct-Tree code accelerated by HIerarchical time step Controlling named GOTHIC, which adopts both the tree method and the hierarchical time step. The code adopts some adaptive optimizations by monitoring the execution time of each function on-the-fly and minimizes the time-to-solution by balancing the measured time of multiple functions. Results of performance measurements with realistic particle distribution performed on NVIDIA Tesla M2090, K20X, and GeForce GTX TITAN X, which are representative GPUs of the Fermi, Kepler, and Maxwell generation of GPUs, show that the hierarchical time step achieves a speedup by a factor of around 3-5 times compared to the shared time step. The measured elapsed time per step of GOTHIC is 0.30 s or 0.44 s on GTX TITAN X when the particle distribution represents the Andromeda galaxy or the NFW sphere, respectively, with 224 = 16,777,216 particles. The averaged performance of the code corresponds to 10-30% of the theoretical single precision peak performance of the GPU.

  13. Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

    Science.gov (United States)

    Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

    2016-02-01

    Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  14. Learning Hierarchical User Interest Models from Web Pages

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuum. In some sense, specific interests correspond to short-term interests, while general interests correspond to long-term interests. So this representation more really reflects the users' interests. The algorithm can automatically model a user's multiple interest domains, dynamically generate the interest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.

  15. Cultural adaptation and validation of a peninsular Spanish version of the MSTCQ(©) (Multiple Sclerosis Treatment Concerns Questionnaire).

    Science.gov (United States)

    Muntéis Olivas, E; Navarro Mascarell, G; Meca Lallana, J; Maestre Martínez, A; Pérez Sempere, Á; Gracia Gil, J; Pato Pato, A

    Although subcutaneous treatments for multiple sclerosis (MS) have been shown to be effective, adverse reactions and pain may adversely affect treatment satisfaction and adherence. This study presents an adapted and validated Spanish version of the Multiple Sclerosis Treatment Concerns Questionnaire(©) (MSTCQ), which evaluates satisfaction with the injection device (ID) across 4 domains: injection system (A), side effects (B) (flu-like symptoms, reactions, and satisfaction), experience with treatment (C) and benefits (D). Two study phases: 1) Cultural adaptation process with input from experts (n=6) and patients (n=30). 2) Validation obtained by means of an observational, cross-sectional, multi-centre study evaluating 143 adult MS patients using an ID. Tools employed: MSTCQ(©), Patient-Reported Indices for Multiple Sclerosis (PRIMUS(©)), and Treatment Satisfaction Questionnaire for Medication (TSQM(©)). Psychometric properties: Feasibility (percentage of valid cases and floor/ceiling effects); Reliability (Cronbach α) and test-retest correlation (n=41, intraclass correlation coefficient, ICC); and construct validity (factor analysis of domains A and B) and convergent validity (Spearman rank-order correlation for MSTCQ(©) vs TSQM(©)). Mean age (SD) was 41.94 (10.47) years, 63% of the group were women, and 88.11% presented relapsing-remitting MS. Mean (SD) EDSS score was 2.68 (1.82) points. MSTCQ(©) completion was high (0%-2.80% missing data). Internal consistency was high at α=0.89 for the total score (A+B) and α=0.76, 0.89, and 0.92 for domains A, B, and C, respectively. The version demonstrated excellent test-retest reliability for the total (ICC=0.98) and for domains A, B, and C: ICC=0.82, 0.97, and 0.89, respectively. Factor analysis corroborated the internal structure of the original questionnaire. The association between total and domain scores on both the MSTCQ(©) and the TSQM(©) was moderately strong (Rho=0.42-0.74) and significant (P<.05 and P

  16. Implementation of Adaptive Multiple Bit Mutation Genetic Algorithm%自适应多位变异遗传算法的实现

    Institute of Scientific and Technical Information of China (English)

    王基一; 吴燕仙

    2003-01-01

    Genetic algorithm is a widely used optimization method. Crossover and mutation are two Basicl operatorsof the genetic algorithm. On the basis of analyzing the principles of simple genetic algorithm and discussing its exist-ing problems of crossover point and mutation bit, this paper presents a way of the adaptive multiple bit mutation ge-netic algorithm , which not only can keep the population diversity but also has quicker convergence speed. The resultsof the multi-modal function optimization show that the adaptive multiple bit mutation genetic algorithm is practicaland efficient.

  17. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  18. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  19. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  20. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  1. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  2. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  3. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  4. Adaption of Ulva pertusa to multiple-contamination of heavy metals and nutrients: Biological mechanism of outbreak of Ulva sp. green tide.

    Science.gov (United States)

    Ge, Changzi; Yu, Xiru; Kan, Manman; Qu, Chunfeng

    2017-08-18

    The multiple-contamination of heavy metals and nutrients worsens increasingly and Ulva sp. green tide occurs almost simultaneously. To reveal the biological mechanism for outbreak of the green tide, Ulva pertusa was exposed to seven-day-multiple-contamination. The relation between pH variation (VpH), Chl a content, ratio of (Chl a content)/(Chl b content) (Rchla/chlb), SOD activity of U. pertusa (ASOD) and contamination concentration is [Formula: see text] (pcontamination concentrations of seawaters where Ulva sp. green tide occurred and the contamination concentrations set in the present work, U. pertusa can adapt to multiple-contaminations in these waters. Thus, the adaption to multiple-contamination may be one biological mechanism for the outbreak of Ulva sp. green tide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

    Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

  6. The halophilic alkalithermophile Natranaerobius thermophilus adapts to multiple environmental extremes using a large repertoire of Na(K)/H antiporters.

    Science.gov (United States)

    Mesbah, Noha M; Cook, Gregory M; Wiegel, Juergen

    2009-10-01

    Natranaerobius thermophilus is an unusual extremophile because it is halophilic, alkaliphilic and thermophilic, growing optimally at 3.5 M Na(+), pH(55 degrees C) 9.5 and 53 degrees C. Mechanisms enabling this tripartite lifestyle are essential for understanding how microorganisms grow under inhospitable conditions, but remain unknown, particularly in extremophiles growing under multiple extremes. We report on the response of N. thermophilus to external pH at high salt and elevated temperature and identify mechanisms responsible for this adaptation. N. thermophilus exhibited cytoplasm acidification, maintaining an unanticipated transmembrane pH gradient of 1 unit over the entire extracellular pH range for growth. N. thermophilus uses two distinct mechanisms for cytoplasm acidification. At extracellular pH values at and below the optimum, N. thermophilus utilizes at least eight electrogenic Na(+)(K(+))/H(+) antiporters for cytoplasm acidification. Characterization of these antiporters in antiporter-deficient Escherichia coli KNabc showed overlapping pH profiles (pH 7.8-10.0) and Na(+) concentrations for activity (K(0.5) values 1.0-4.4 mM), properties that correlate with intracellular conditions of N. thermophilus. As the extracellular pH increases beyond the optimum, electrogenic antiport activity ceases, and cytoplasm acidification is achieved by energy-independent physiochemical effects (cytoplasmic buffering) potentially mediated by an acidic proteome. The combination of these strategies allows N. thermophilus to grow over a range of extracellular pH and Na(+) concentrations and protect biomolecules under multiple extreme conditions.

  7. Building Algebra Testlets: A Comparison of Hierarchical and Linear Structures.

    Science.gov (United States)

    Wainer, Howard; And Others

    1991-01-01

    Hierarchical (adaptive) and linear methods of testlet construction were compared. The performance of 2,080 ninth and tenth graders on a 4-item testlet was used to predict performance on the entire test. The adaptive test was slightly superior as a predictor, but the cost of obtaining that superiority was considerable. (SLD)

  8. Building Algebra Testlets: A Comparison of Hierarchical and Linear Structures.

    Science.gov (United States)

    Wainer, Howard; And Others

    1991-01-01

    Hierarchical (adaptive) and linear methods of testlet construction were compared. The performance of 2,080 ninth and tenth graders on a 4-item testlet was used to predict performance on the entire test. The adaptive test was slightly superior as a predictor, but the cost of obtaining that superiority was considerable. (SLD)

  9. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  10. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  11. Fractal image perception provides novel insights into hierarchical cognition.

    Science.gov (United States)

    Martins, M J; Fischmeister, F P; Puig-Waldmüller, E; Oh, J; Geissler, A; Robinson, S; Fitch, W T; Beisteiner, R

    2014-08-01

    Hierarchical structures play a central role in many aspects of human cognition, prominently including both language and music. In this study we addressed hierarchy in the visual domain, using a novel paradigm based on fractal images. Fractals are self-similar patterns generated by repeating the same simple rule at multiple hierarchical levels. Our hypothesis was that the brain uses different resources for processing hierarchies depending on whether it applies a "fractal" or a "non-fractal" cognitive strategy. We analyzed the neural circuits activated by these complex hierarchical patterns in an event-related fMRI study of 40 healthy subjects. Brain activation was compared across three different tasks: a similarity task, and two hierarchical tasks in which subjects were asked to recognize the repetition of a rule operating transformations either within an existing hierarchical level, or generating new hierarchical levels. Similar hierarchical images were generated by both rules and target images were identical. We found that when processing visual hierarchies, engagement in both hierarchical tasks activated the visual dorsal stream (occipito-parietal cortex, intraparietal sulcus and dorsolateral prefrontal cortex). In addition, the level-generating task specifically activated circuits related to the integration of spatial and categorical information, and with the integration of items in contexts (posterior cingulate cortex, retrosplenial cortex, and medial, ventral and anterior regions of temporal cortex). These findings provide interesting new clues about the cognitive mechanisms involved in the generation of new hierarchical levels as required for fractals.

  12. Speech recognition in reverberant and noisy environments employing multiple feature extractors and i-vector speaker adaptation

    Science.gov (United States)

    Alam, Md Jahangir; Gupta, Vishwa; Kenny, Patrick; Dumouchel, Pierre

    2015-12-01

    The REVERB challenge provides a common framework for the evaluation of feature extraction techniques in the presence of both reverberation and additive background noise. State-of-the-art speech recognition systems perform well in controlled environments, but their performance degrades in realistic acoustical conditions, especially in real as well as simulated reverberant environments. In this contribution, we utilize multiple feature extractors including the conventional mel-filterbank, multi-taper spectrum estimation-based mel-filterbank, robust mel and compressive gammachirp filterbank, iterative deconvolution-based dereverberated mel-filterbank, and maximum likelihood inverse filtering-based dereverberated mel-frequency cepstral coefficient features for speech recognition with multi-condition training data. In order to improve speech recognition performance, we combine their results using ROVER (Recognizer Output Voting Error Reduction). For two- and eight-channel tasks, to get benefited from the multi-channel data, we also use ROVER, instead of the multi-microphone signal processing method, to reduce word error rate by selecting the best scoring word at each channel. As in a previous work, we also apply i-vector-based speaker adaptation which was found effective. In speech recognition task, speaker adaptation tries to reduce mismatch between the training and test speakers. Speech recognition experiments are conducted on the REVERB challenge 2014 corpora using the Kaldi recognizer. In our experiments, we use both utterance-based batch processing and full batch processing. In the single-channel task, full batch processing reduced word error rate (WER) from 10.0 to 9.3 % on SimData as compared to utterance-based batch processing. Using full batch processing, we obtained an average WER of 9.0 and 23.4 % on the SimData and RealData, respectively, for the two-channel task, whereas for the eight-channel task on the SimData and RealData, the average WERs found were 8

  13. A Hierarchical Sensor Network Based on Voronoi Diagram

    Institute of Scientific and Technical Information of China (English)

    SHANG Rui-qiang; ZHAO Jian-li; SUN Qiu-xia; WANG Guang-xing

    2006-01-01

    A hierarchical sensor network is proposed which places the sensing and routing capacity at different layer nodes.It thus simplifies the hardware design and reduces cost. Adopting Voronoi diagram in the partition of backbone network,a mathematical model of data aggregation based on hierarchical architecture is given. Simulation shows that the number of transmission data packages is sharply cut down in the network, thus reducing the needs in the bandwidth and energy resources and is thus well adapted to sensor networks.

  14. Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning.

    Science.gov (United States)

    Chalmers, Eric; Luczak, Artur; Gruber, Aaron J

    2016-01-01

    The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL) to guide "goal-directed" behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals' ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, "forward sweeps" through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort) required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.

  15. Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Eric Chalmers

    2016-12-01

    Full Text Available The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL to guide goal-directed behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals’ ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, forward sweeps through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.

  16. Mechanisms of adaptation from a multiple to a single step recovery strategy following repeated exposure to forward loss of balance in older adults.

    Directory of Open Access Journals (Sweden)

    Christopher P Carty

    Full Text Available When released from an initial, static, forward lean angle and instructed to recover with a single step, some older adults are able to meet the task requirements, whereas others either stumble or fall. The purpose of the present study was to use the concept of margin of stability (MoS to investigate balance recovery responses in the anterior-posterior direction exhibited by older single steppers, multiple steppers and those that are able to adapt from multiple to single steps following exposure to repeated forward loss of balance. One hundred and fifty-one healthy, community dwelling, older adults, aged 65-80 years, participated in the study. Participants performed four trials of the balance recovery task from each of three initial lean angles. Balance recovery responses in the anterior-posterior direction were quantified at three events; cable release (CR, toe-off (TO and foot contact (FC, for trials performed at the intermediate lean angle. MoS was computed as the anterior-posterior distance between the forward boundary of the Base of Support (BoS and the vertical projection of the velocity adjusted centre of mass position (XCoM. Approximately one-third of participants adapted from a multiple to a single step recovery strategy following repeated exposure to the task. MoS at FC for the single and multiple step trials in the adaptation group were intermediate between the exclusively single step group and the exclusively multiple step group, with the single step trials having a significant, 3.7 times higher MoS at FC than the multiple step trials. Consistent with differences between single and multiple steppers, adaptation from multiple to single steps was attributed to an increased BoS at FC, a reduced XCoM at FC and an increased rate of BoS displacement from TO to FC. Adaptations occurred within a single test session and suggest older adults that are close to the threshold of successful recovery can rapidly improve dynamic stability following

  17. Predicting strength of recycled aggregate concrete using Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System and Multiple Linear Regression

    Directory of Open Access Journals (Sweden)

    Faezehossadat Khademi

    2016-12-01

    Full Text Available Compressive strength of concrete, recognized as one of the most significant mechanical properties of concrete, is identified as one of the most essential factors for the quality assurance of concrete. In the current study, three different data-driven models, i.e., Artificial Neural Network (ANN, Adaptive Neuro-Fuzzy Inference System (ANFIS, and Multiple Linear Regression (MLR were used to predict the 28 days compressive strength of recycled aggregate concrete (RAC. Recycled aggregate is the current need of the hour owing to its environmental pleasant aspect of re-using the wastes due to construction. 14 different input parameters, including both dimensional and non-dimensional parameters, were used in this study for predicting the 28 days compressive strength of concrete. The present study concluded that estimation of 28 days compressive strength of recycled aggregate concrete was performed better by ANN and ANFIS in comparison to MLR. In other words, comparing the test step of all the three models, it can be concluded that the MLR model is better to be utilized for preliminary mix design of concrete, and ANN and ANFIS models are suggested to be used in the mix design optimization and in the case of higher accuracy necessities. In addition, the performance of data-driven models with and without the non-dimensional parameters is explored. It was observed that the data-driven models show better accuracy when the non-dimensional parameters were used as additional input parameters. Furthermore, the effect of each non-dimensional parameter on the performance of each data-driven model is investigated. Finally, the effect of number of input parameters on 28 days compressive strength of concrete is examined.

  18. The Swedish version of the Acceptance of Chronic Health Conditions Scale for people with multiple sclerosis: Translation, cultural adaptation and psychometric properties.

    Science.gov (United States)

    Forslin, Mia; Kottorp, Anders; Kierkegaard, Marie; Johansson, Sverker

    2016-11-11

    To translate and culturally adapt the Acceptance of Chronic Health Conditions (ACHC) Scale for people with multiple sclerosis into Swedish, and to analyse the psychometric properties of the Swedish version. Ten people with multiple sclerosis participated in translation and cultural adaptation of the ACHC Scale; 148 people with multiple sclerosis were included in evaluation of the psychometric properties of the scale. Translation and cultural adaptation were carried out through translation and back-translation, by expert committee evaluation and pre-test with cognitive interviews in people with multiple sclerosis. The psychometric properties of the Swedish version were evaluated using Rasch analysis. The Swedish version of the ACHC Scale was an acceptable equivalent to the original version. Seven of the original 10 items fitted the Rasch model and demonstrated ability to separate between groups. A 5-item version, including 2 items and 3 super-items, demonstrated better psychometric properties, but lower ability to separate between groups. The Swedish version of the ACHC Scale with the original 10 items did not fit the Rasch model. Two solutions, either with 7 items (ACHC-7) or with 2 items and 3 super-items (ACHC-5), demonstrated acceptable psychometric properties. Use of the ACHC-5 Scale with super-items is recommended, since this solution adjusts for local dependency among items.

  19. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  20. Application of Bayesian hierarchical models for phase I/II clinical trials in oncology.

    Science.gov (United States)

    Yada, Shinjo; Hamada, Chikuma

    2017-03-01

    Treatment during cancer clinical trials sometimes involves the combination of multiple drugs. In addition, in recent years there has been a trend toward phase I/II trials in which a phase I and a phase II trial are combined into a single trial to accelerate drug development. Methods for the seamless combination of phases I and II parts are currently under investigation. In the phase II part, adaptive randomization on the basis of patient efficacy outcomes allocates more patients to the dose combinations considered to have higher efficacy. Patient toxicity outcomes are used for determining admissibility to each dose combination and are not used for selection of the dose combination itself. In cases where the objective is not to find the optimum dose combination solely for efficacy but regarding both toxicity and efficacy, the need exists to allocate patients to dose combinations with consideration of the balance of existing trade-offs between toxicity and efficacy. We propose a Bayesian hierarchical model and an adaptive randomization with consideration for the relationship with toxicity and efficacy. Using the toxicity and efficacy outcomes of patients, the Bayesian hierarchical model is used to estimate the toxicity probability and efficacy probability in each of the dose combinations. Here, we use Bayesian moving-reference adaptive randomization on the basis of desirability computed from the obtained estimator. Computer simulations suggest that the proposed method will likely recommend a higher percentage of target dose combinations than a previously proposed method.

  1. Robot manipulator identification based on adaptive multiple-input and multiple-output neural model optimized by advanced differential evolution algorithm

    Directory of Open Access Journals (Sweden)

    Nguyen Ngoc Son

    2016-12-01

    Full Text Available This article proposes a novel advanced differential evolution method which combines the differential evolution with the modified back-propagation algorithm. This new proposed approach is applied to train an adaptive enhanced neural model for approximating the inverse model of the industrial robot arm. Experimental results demonstrate that the proposed modeling procedure using the new identification approach obtains better convergence and more precision than the traditional back-propagation method or the lonely differential evolution approach. Furthermore, the inverse model of the industrial robot arm using the adaptive enhanced neural model performs outstanding results.

  2. Hierarchical beamformer and cross-talk reduction in electroneurography

    Science.gov (United States)

    Calvetti, Daniela; Wodlinger, Brian; Durand, Dominique M.; Somersalo, Erkki

    2011-10-01

    Electroneurography (ENG) is a method of recording neural activity within nerves. Using nerve electrodes with multiple contacts the activation patterns of individual neuronal fascicles can be estimated by measuring the surface voltages induced by the intraneural activity. The information about neuronal activation can be used for functional electric stimulation (FES) of patients suffering from spinal chord injury, or to control a robotic prosthetic limb of an amputee. However, the ENG signal estimation is a severely ill-posed inverse problem due to uncertainties in the model, low resolution due to limitations of the data, geometric constraints and the difficulty in separating the signal from biological and exogenous noise. In this paper, a reduced computational model for the forward problem is proposed, and the ENG problem is addressed by using beamformer techniques. Furthermore, we show that using a hierarchical statistical model, it is possible to develop an adaptive beamformer algorithm that estimates directly the source variances rather than the voltage source itself. The advantage of this new algorithm, e.g., over a traditional adaptive beamformer algorithm, is that it allows a very stable noise reduction by averaging over a time window. In addition, a new projection technique for separating sources and reducing cross-talk between different fascicle signals is proposed. The algorithms are tested on a computer model of realistic nerve geometry and time series signals.

  3. Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

    Science.gov (United States)

    Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

    2017-05-01

    In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

  4. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  5. Hierarchical manifold learning.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

    2012-01-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

  6. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  7. HDS: Hierarchical Data System

    Science.gov (United States)

    Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

    2015-02-01

    The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

  8. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  9. Hierarchical Robot Control In A Multisensor Environment

    Science.gov (United States)

    Bhanu, Bir; Thune, Nils; Lee, Jih Kun; Thune, Mari

    1987-03-01

    Automatic recognition, inspection, manipulation and assembly of objects will be a common denominator in most of tomorrow's highly automated factories. These tasks will be handled by intelligent computer controlled robots with multisensor capabilities which contribute to desired flexibility and adaptability. The control of a robot in such a multisensor environment becomes of crucial importance as the complexity of the problem grows exponentially with the number of sensors, tasks, commands and objects. In this paper we present an approach which uses CAD (Computer-Aided Design) based geometric and functional models of objects together with action oriented neuroschemas to recognize and manipulate objects by a robot in a multisensor environment. The hierarchical robot control system is being implemented on a BBN Butterfly multi processor. Index terms: CAD, Hierarchical Control, Hypothesis Generation and Verification, Parallel Processing, Schemas

  10. Cache related pre-emption delays in hierarchical scheduling

    NARCIS (Netherlands)

    Lunniss, W.; Altmeyer, S.; Lipari, G.; Davis, R.I.

    2016-01-01

    Hierarchical scheduling provides a means of composing multiple real-time applications onto a single processor such that the temporal requirements of each application are met. This has become a popular technique in industry as it allows applications from multiple vendors as well as legacy application

  11. Complex adaptive responses during antagonistic coevolution between Tribolium castaneum and its natural parasite Nosema whitei revealed by multiple fitness components

    Directory of Open Access Journals (Sweden)

    Bérénos Camillo

    2012-01-01

    Full Text Available Abstract Background Host-parasite coevolution can lead to local adaptation of either parasite or host if there is specificity (GxG interactions and asymmetric evolutionary potential between host and parasite. This has been demonstrated both experimentally and in field studies, but a substantial proportion of studies fail to detect such clear-cut patterns. One explanation for this is that adaptation can be masked by counter-adaptation by the antagonist. Additionally, genetic architecture underlying the interaction is often highly complex thus preventing specific adaptive responses. Here, we have employed a reciprocal cross-infection experiment to unravel the adaptive responses of two components of fitness affecting both parties with different complexities of the underlying genetic architecture (i.e. mortality and spore load. Furthermore, our experimental coevolution of hosts (Tribolium castaneum and parasites (Nosema whitei included paired replicates of naive hosts from identical genetic backgrounds to allow separation between host- and parasite-specific responses. Results In hosts, coevolution led to higher resistance and altered resistance profiles compared to paired control lines. Host genotype × parasite genotype interactions (GH × GP were observed for spore load (the trait of lower genetic complexity, but not for mortality. Overall parasite performance correlated with resistance of its matching host coevolution background reflecting a directional and unspecific response to strength of selection during coevolution. Despite high selective pressures exerted by the obligatory killing parasite, and host- and parasite-specific mortality profiles, no general pattern of local adaptation was observed, but one case of parasite maladaptation was consistently observed on both coevolved and control host populations. In addition, the use of replicate control host populations in the assay revealed one case of host maladaptation and one case of parasite

  12. Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

    Science.gov (United States)

    Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

    2011-01-01

    Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

  13. Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

    Science.gov (United States)

    Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

    2011-01-01

    Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

  14. Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems

    DEFF Research Database (Denmark)

    Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung

    2015-01-01

    The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...

  15. Adapting the Unique Minds Program: Exploring the Feasibility of a Multiple Family Intervention for Children with Learning Disabilities in the Context of Spain.

    Science.gov (United States)

    López-Larrosa, Silvia; González-Seijas, Rosa M; Carpenter, John S W

    2017-06-01

    The Unique Minds Program (Stern, Unique Minds Program, 1999) addresses the socio-emotional needs of children with learning disabilities (LD) and their families. Children and their parents work together in a multiple family group to learn more about LD and themselves as people with the capacity to solve problems in a collaborative way, including problems in family school relationships. This article reports the cultural adaptation of the program for use in Spain and findings from a feasibility study involving three multiple family groups and a total of 15 children and 15 mothers, using a pre-post design. This Spanish adaptation of the program is called "Mentes Únicas". Standardized outcome measures indicated an overall statistically significant decrease in children's self-rated maladjustment and relationship difficulties by the end of the program. Improvements were endorsed by most mothers, although they were not always recognized by the children's teachers. The program had a high level of acceptability: Mothers and children felt safe, understood, and helped throughout the sessions. The efficacy of the adapted intervention for the context of Spain remains to be tested in a more rigorous study. © 2016 Family Process Institute.

  16. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2012-01-01

    a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure......Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  17. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  18. Therapy for Relapsed Multiple Myeloma: Guidelines From the Mayo Stratification for Myeloma and Risk-Adapted Therapy.

    Science.gov (United States)

    Dingli, David; Ailawadhi, Sikander; Bergsagel, P Leif; Buadi, Francis K; Dispenzieri, Angela; Fonseca, Rafael; Gertz, Morie A; Gonsalves, Wilson I; Hayman, Susan R; Kapoor, Prashant; Kourelis, Taxiarchis; Kumar, Shaji K; Kyle, Robert A; Lacy, Martha Q; Leung, Nelson; Lin, Yi; Lust, John A; Mikhael, Joseph R; Reeder, Craig B; Roy, Vivek; Russell, Stephen J; Sher, Taimur; Stewart, A Keith; Warsame, Rahma; Zeldenrust, Stephen R; Rajkumar, S Vincent; Chanan Khan, Asher A

    2017-04-01

    Life expectancy in patients with multiple myeloma is increasing because of the availability of an increasing number of novel agents with various mechanisms of action against the disease. However, the disease remains incurable in most patients because of the emergence of resistant clones, leading to repeated relapses of the disease. In 2015, 5 novel agents were approved for therapy for relapsed multiple myeloma. This surfeit of novel agents renders management of relapsed multiple myeloma more complex because of the occurrence of multiple relapses, the risk of cumulative and emergent toxicity from previous therapies, as well as evolution of the disease during therapy. A group of physicians at Mayo Clinic with expertise in the care of patients with multiple myeloma regularly evaluates the evolving literature on the biology and therapy for multiple myeloma and issues guidelines on the optimal care of patients with this disease. In this article, the latest recommendations on the diagnostic evaluation of relapsed multiple myeloma and decision trees on how to treat patients at various stages of their relapse (off study) are provided together with the evidence to support them. Copyright © 2017 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

  19. Object tracking with hierarchical multiview learning

    Science.gov (United States)

    Yang, Jun; Zhang, Shunli; Zhang, Li

    2016-09-01

    Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

  20. Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network.

    Science.gov (United States)

    Balaguer, Jan; Spiers, Hugo; Hassabis, Demis; Summerfield, Christopher

    2016-05-18

    Planning allows actions to be structured in pursuit of a future goal. However, in natural environments, planning over multiple possible future states incurs prohibitive computational costs. To represent plans efficiently, states can be clustered hierarchically into "contexts". For example, representing a journey through a subway network as a succession of individual states (stations) is more costly than encoding a sequence of contexts (lines) and context switches (line changes). Here, using functional brain imaging, we asked humans to perform a planning task in a virtual subway network. Behavioral analyses revealed that humans executed a hierarchically organized plan. Brain activity in the dorsomedial prefrontal cortex and premotor cortex scaled with the cost of hierarchical plan representation and unique neural signals in these regions signaled contexts and context switches. These results suggest that humans represent hierarchical plans using a network of caudal prefrontal structures. VIDEO ABSTRACT.

  1. Fast multiple run_before decoding method for efficient implementation of an H.264/advanced video coding context-adaptive variable length coding decoder

    Science.gov (United States)

    Ki, Dae Wook; Kim, Jae Ho

    2013-07-01

    We propose a fast new multiple run_before decoding method in context-adaptive variable length coding (CAVLC). The transform coefficients are coded using CAVLC, in which the run_before symbols are generated for a 4×4 block input. To speed up the CAVLC decoding, the run_before symbols need to be decoded in parallel. We implemented a new CAVLC table for simultaneous decoding of up to three run_befores. The simulation results show a Total Speed-up Factor of 205%˜144% over various resolutions and quantization steps.

  2. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritization of polluted sites is given.

  3. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  4. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  5. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  6. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  7. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L; Bod, Rens; Christiansen, Morten H

    2012-11-22

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

  8. Confidentiality Protection of User Data and Adaptive Resource Allocation for Managing Multiple Workflow Performance in Service-Based Systems

    Science.gov (United States)

    An, Ho

    2012-01-01

    In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in…

  9. Confidentiality Protection of User Data and Adaptive Resource Allocation for Managing Multiple Workflow Performance in Service-Based Systems

    Science.gov (United States)

    An, Ho

    2012-01-01

    In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in…

  10. Three Layer Hierarchical Model for Chord

    Directory of Open Access Journals (Sweden)

    Waqas A. Imtiaz

    2012-12-01

    Full Text Available Increasing popularity of decentralized Peer-to-Peer (P2P architecture emphasizes on the need to come across an overlay structure that can provide efficient content discovery mechanism, accommodate high churn rate and adapt to failures in the presence of heterogeneity among the peers. Traditional p2p systems incorporate distributed client-server communication, which finds the peer efficiently that store a desires data item, with minimum delay and reduced overhead. However traditional models are not able to solve the problems relating scalability and high churn rates. Hierarchical model were introduced to provide better fault isolation, effective bandwidth utilization, a superior adaptation to the underlying physical network and a reduction of the lookup path length as additional advantages. It is more efficient and easier to manage than traditional p2p networks. This paper discusses a further step in p2p hierarchy via 3-layers hierarchical model with distributed database architecture in different layer, each of which is connected through its root. The peers are divided into three categories according to their physical stability and strength. They are Ultra Super-peer, Super-peer and Ordinary Peer and we assign these peers to first, second and third level of hierarchy respectively. Peers in a group in lower layer have their own local database which hold as associated super-peer in middle layer and access the database among the peers through user queries. In our 3-layer hierarchical model for DHT algorithms, we used an advanced Chord algorithm with optimized finger table which can remove the redundant entry in the finger table in upper layer that influences the system to reduce the lookup latency. Our research work finally resulted that our model really provides faster search since the network lookup latency is decreased by reducing the number of hops. The peers in such network then can contribute with improve functionality and can perform well in

  11. The rice OsNAC6 transcription factor orchestrates multiple molecular mechanisms involving root structural adaptions and nicotianamine biosynthesis for drought tolerance.

    Science.gov (United States)

    Lee, Dong-Keun; Chung, Pil Joong; Jeong, Jin Seo; Jang, Geupil; Bang, Seung Woon; Jung, Harin; Kim, Youn Shic; Ha, Sun-Hwa; Choi, Yang Do; Kim, Ju-Kon

    2016-11-28

    Drought has a serious impact on agriculture worldwide. A plant's ability to adapt to rhizosphere drought stress requires reprogramming of root growth and development. Although physiological studies have documented the root adaption for tolerance to the drought stress, underlying molecular mechanisms is still incomplete, which is essential for crop engineering. Here, we identified OsNAC6-mediated root structural adaptations, including increased root number and root diameter, which enhanced drought tolerance. Multiyear drought field tests demonstrated that the grain yield of OsNAC6 root-specific overexpressing transgenic rice lines was less affected by drought stress than were nontransgenic controls. Genome-wide analyses of loss- and gain-of-function mutants revealed that OsNAC6 up-regulates the expression of direct target genes involved in membrane modification, nicotianamine (NA) biosynthesis, glutathione relocation, 3'-phophoadenosine 5'-phosphosulphate accumulation and glycosylation, which represent multiple drought tolerance pathways. Moreover, overexpression of NICOTIANAMINE SYNTHASE genes, direct targets of OsNAC6, promoted the accumulation of the metal chelator NA and, consequently, drought tolerance. Collectively, OsNAC6 orchestrates novel molecular drought tolerance mechanisms and has potential for the biotechnological development of high-yielding crops under water-limiting conditions.

  12. On the geostatistical characterization of hierarchical media

    Science.gov (United States)

    Neuman, Shlomo P.; Riva, Monica; Guadagnini, Alberto

    2008-02-01

    The subsurface consists of porous and fractured materials exhibiting a hierarchical geologic structure, which gives rise to systematic and random spatial and directional variations in hydraulic and transport properties on a multiplicity of scales. Traditional geostatistical moment analysis allows one to infer the spatial covariance structure of such hierarchical, multiscale geologic materials on the basis of numerous measurements on a given support scale across a domain or "window" of a given length scale. The resultant sample variogram often appears to fit a stationary variogram model with constant variance (sill) and integral (spatial correlation) scale. In fact, some authors, who recognize that hierarchical sedimentary architecture and associated log hydraulic conductivity fields tend to be nonstationary, nevertheless associate them with stationary "exponential-like" transition probabilities and variograms, respectively, the latter being a consequence of the former. We propose that (1) the apparent ability of stationary spatial statistics to characterize the covariance structure of nonstationary hierarchical media is an artifact stemming from the finite size of the windows within which geologic and hydrologic variables are ubiquitously sampled, and (2) the artifact is eliminated upon characterizing the covariance structure of such media with the aid of truncated power variograms, which represent stationary random fields obtained upon sampling a nonstationary fractal over finite windows. To support our opinion, we note that truncated power variograms arise formally when a hierarchical medium is sampled jointly across all geologic categories and scales within a window; cite direct evidence that geostatistical parameters (variance and integral scale) inferred on the basis of traditional variograms vary systematically with support and window scales; demonstrate the ability of truncated power models to capture these variations in terms of a few scaling parameters

  13. MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

    2014-06-15

    Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method.

  14. Resilient 3D hierarchical architected metamaterials.

    Science.gov (United States)

    Meza, Lucas R; Zelhofer, Alex J; Clarke, Nigel; Mateos, Arturo J; Kochmann, Dennis M; Greer, Julia R

    2015-09-15

    Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic-polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥ 50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property.

  15. Semantic Image Segmentation with Contextual Hierarchical Models.

    Science.gov (United States)

    Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-05-01

    Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

  16. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

  17. Contribution of Multiple Inter-kingdom Horizontal Gene Transfers to Evolution and Adaptation of Amphibian-killing Chytrid, Batrachochytrium dendrobatidis

    Directory of Open Access Journals (Sweden)

    Baofa Sun

    2016-08-01

    Full Text Available Amphibian populations are experiencing catastrophic declines driven by the fungal pathogen Batrachochytrium dendrobatidis (Bd. Although horizontal gene transfer (HGT facilitates the evolution and adaptation in many fungi by conferring novel function genes to the recipient fungi, inter-kingdom HGT in Bd remains largely unexplored. In this study, our investigation detects 19 bacterial genes transferred to Bd, including metallo-beta-lactamase and arsenate reductase that play important roles in the resistance to antibiotics and arsenates. Moreover, three probable HGT gene families in Bd are from plants and one gene family coding the ankyrin repeat-containing protein appears to come from oomycetes. The observed multi-copy gene families associated with HGT are probably due to the independent transfer events or gene duplications. Five HGT genes with extracellular locations may relate to infection, and some other genes may participate in a variety of metabolic pathways, and in doing so add important metabolic traits to the recipient. The evolutionary analysis indicates that all the transferred genes evolved under purifying selection, suggesting that their functions in Bd are similar to those of the donors. Collectively, our results indicate that HGT from diverse donors may be an important evolutionary driver of Bd, and improve its adaptations for infecting and colonizing host amphibians.

  18. Adaptation of ovarian cancer cells to the peritoneal environment: Multiple mechanisms of the developmental patterning gene HOXA9

    Science.gov (United States)

    Ko, Song Yi; Naora, Honami

    2015-01-01

    The lethality of ovarian cancer stems from its propensity to involve the peritoneal cavity. However, the mechanisms that enable ovarian cancer cells to readily adapt to the peritoneal environment are not well understood. Here, we describe our recent studies in which we identified the mechanisms by which the transcription factor encoded by the patterning gene HOXA9 promotes the aggressive behavior of ovarian cancer. Firstly, we identified that HOXA9 promotes ovarian tumor growth and angiogenesis by activating the gene encoding transforming growth factor-β2 (TGF-β2), which in turn stimulates peritoneal fibroblasts and mesenchymal stem cells to acquire features of cancer-associated fibroblasts. Secondly, by inducing TGF-β2 and chemokine (C-C motif) ligand 2, HOXA9 stimulates peritoneal macrophages to acquire an immunosuppressive phenotype. Thirdly, HOXA9 stimulates attachment of ovarian cancer cells to peritoneal mesothelial cells by inducing expression of P-cadherin. By inducing P-cadherin, HOXA9 also enables floating cancer cells in the peritoneal cavity to form aggregates and escape anoikis. Together, our studies demonstrate that HOXA9 enables ovarian cancer cells to adapt to the peritoneal environment and ‘educates’ different types of stromal cells to become permissive for tumor growth. Our studies provide new insights into the regulation of tumor-stroma interactions in ovarian cancer and implicate several key effector molecules as candidate therapeutic targets. PMID:26000332

  19. Contribution of Multiple Inter-Kingdom Horizontal Gene Transfers to Evolution and Adaptation of Amphibian-Killing Chytrid, Batrachochytrium dendrobatidis

    Science.gov (United States)

    Sun, Baofa; Li, Tong; Xiao, Jinhua; Liu, Li; Zhang, Peng; Murphy, Robert W.; He, Shunmin; Huang, Dawei

    2016-01-01

    Amphibian populations are experiencing catastrophic declines driven by the fungal pathogen Batrachochytrium dendrobatidis (Bd). Although horizontal gene transfer (HGT) facilitates the evolution and adaptation in many fungi by conferring novel function genes to the recipient fungi, inter-kingdom HGT in Bd remains largely unexplored. In this study, our investigation detects 19 bacterial genes transferred to Bd, including metallo-beta-lactamase and arsenate reductase that play important roles in the resistance to antibiotics and arsenates. Moreover, three probable HGT gene families in Bd are from plants and one gene family coding the ankyrin repeat-containing protein appears to come from oomycetes. The observed multi-copy gene families associated with HGT are probably due to the independent transfer events or gene duplications. Five HGT genes with extracellular locations may relate to infection, and some other genes may participate in a variety of metabolic pathways, and in doing so add important metabolic traits to the recipient. The evolutionary analysis indicates that all the transferred genes evolved under purifying selection, suggesting that their functions in Bd are similar to those of the donors. Collectively, our results indicate that HGT from diverse donors may be an important evolutionary driver of Bd, and improve its adaptations for infecting and colonizing host amphibians. PMID:27630622

  20. Adaptation of AMO-FBMC-OQAM in optical access network for accommodating asynchronous multiple access in OFDM-based uplink transmission

    Science.gov (United States)

    Jung, Sun-Young; Jung, Sang-Min; Han, Sang-Kook

    2015-01-01

    Exponentially expanding various applications in company with proliferation of mobile devices make mobile traffic exploded annually. For future access network, bandwidth efficient and asynchronous signals converged transmission technique is required in optical network to meet a huge bandwidth demand, while integrating various services and satisfying multiple access in perceived network resource. Orthogonal frequency division multiplexing (OFDM) is highly bandwidth efficient parallel transmission technique based on orthogonal subcarriers. OFDM has been widely studied in wired-/wireless communication and became a Long term evolution (LTE) standard. Consequently, OFDM also has been actively researched in optical network. However, OFDM is vulnerable frequency and phase offset essentially because of its sinc-shaped side lobes, therefore tight synchronism is necessary to maintain orthogonality. Moreover, redundant cyclic prefix (CP) is required in dispersive channel. Additionally, side lobes act as interference among users in multiple access. Thus, it practically hinders from supporting integration of various services and multiple access based on OFDM optical transmission In this paper, adaptively modulated optical filter bank multicarrier system with offset QAM (AMO-FBMC-OQAM) is introduced and experimentally investigated in uplink optical transmission to relax multiple access interference (MAI), while improving bandwidth efficiency. Side lobes are effectively suppressed by using FBMC, therefore the system becomes robust to path difference and imbalance among optical network units (ONUs), which increase bandwidth efficiency by reducing redundancy. In comparison with OFDM, a signal performance and an efficiency of frequency utilization are improved in the same experimental condition. It enables optical network to effectively support heterogeneous services and multiple access.

  1. Protocol for a randomized controlled trial on risk adapted damage control orthopedic surgery of femur shaft fractures in multiple trauma patients

    Directory of Open Access Journals (Sweden)

    Rixen Dieter

    2009-08-01

    Full Text Available Abstract Background Fractures of the long bones and femur fractures in particular are common in multiple trauma patients, but the optimal management of femur fractures in these patients is not yet resolved. Although there is a trend towards the concept of "Damage Control Orthopedics" (DCO in the management of multiple trauma patients with long bone fractures as reflected by a significant increase in primary external fixation of femur fractures, current literature is insufficient. Thus, in the era of "evidence-based medicine", there is the need for a more specific, clarifying trial. Methods/Design The trial is designed as a randomized controlled open-label multicenter study. Multiple trauma patients with femur shaft fractures and a calculated probability of death between 20 and 60% will be randomized to either temporary fracture fixation with fixateur externe and defined secondary definitive treatment (DCO or primary reamed nailing (early total care. The primary objective is to reduce the extent of organ failure as measured by the maximum sepsis-related organ failure assessment (SOFA score. Discussion The Damage Control Study is the first to evaluate the risk adapted damage control orthopedic surgery concept of femur shaft fractures in multiple trauma patients in a randomized controlled design. The trial investigates the differences in clinical outcome of two currently accepted different ways of treating multiple trauma patients with femoral shaft fractures. This study will help to answer the question whether the "early total care" or the „damage control” concept is associated with better outcome. Trial registration Current Controlled Trials ISRCTN10321620

  2. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    OpenAIRE

    Jelonek, Magdalena

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...

  3. Climate information based streamflow and rainfall forecasts for Huai River Basin using Hierarchical Bayesian Modeling

    Directory of Open Access Journals (Sweden)

    X. Chen

    2013-09-01

    Full Text Available A Hierarchal Bayesian model for forecasting regional summer rainfall and streamflow season-ahead using exogenous climate variables for East Central China is presented. The model provides estimates of the posterior forecasted probability distribution for 12 rainfall and 2 streamflow stations considering parameter uncertainty, and cross-site correlation. The model has a multilevel structure with regression coefficients modeled from a common multivariate normal distribution results in partial-pooling of information across multiple stations and better representation of parameter and posterior distribution uncertainty. Covariance structure of the residuals across stations is explicitly modeled. Model performance is tested under leave-10-out cross-validation. Frequentist and Bayesian performance metrics used include Receiver Operating Characteristic, Reduction of Error, Coefficient of Efficiency, Rank Probability Skill Scores, and coverage by posterior credible intervals. The ability of the model to reliably forecast regional summer rainfall and streamflow season-ahead offers potential for developing adaptive water risk management strategies.

  4. Evaluation of anthelmintic resistance in livestock parasites using observational data and hierarchical models

    DEFF Research Database (Denmark)

    Nielsen, Martin Krarup; Vidyashankar, Anand N.; Hanlon, Bret

    contribute to cause this high variability and these must be taken into account to accurately identify a reduction in anthelmintic efficacy. To address this problem, we developed a hierarchical statistical model for analysis of FECRT data from multiple farms. The model includes animal effect and farm clusters...... to handle FECRT data obtained from other livestock species, drug types, and parasite species........93 %) farms as pyrantel resistant, 5 (7.81 %) as suspect resistant and the remainder of farms (81.25%) as not resistant. In comparison with unadjusted LCLs, the model provided a more stable classification of farms with a 1.1 % 12 false discovery rate. The statistical model presented here can be adapted...

  5. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  6. Onboard hierarchical network

    Science.gov (United States)

    Tunesi, Luca; Armbruster, Philippe

    2004-02-01

    The objective of this paper is to demonstrate a suitable hierarchical networking solution to improve capabilities and performances of space systems, with significant recurrent costs saving and more efficient design & manufacturing flows. Classically, a satellite can be split in two functional sub-systems: the platform and the payload complement. The platform is in charge of providing power, attitude & orbit control and up/down-link services, whereas the payload represents the scientific and/or operational instruments/transponders and embodies the objectives of the mission. One major possibility to improve the performance of payloads, by limiting the data return to pertinent information, is to process data on board thanks to a proper implementation of the payload data system. In this way, it is possible to share non-recurring development costs by exploiting a system that can be adopted by the majority of space missions. It is believed that the Modular and Scalable Payload Data System, under development by ESA, provides a suitable solution to fulfil a large range of future mission requirements. The backbone of the system is the standardised high data rate SpaceWire network http://www.ecss.nl/. As complement, a lower speed command and control bus connecting peripherals is required. For instance, at instrument level, there is a need for a "local" low complexity bus, which gives the possibility to command and control sensors and actuators. Moreover, most of the connections at sub-system level are related to discrete signals management or simple telemetry acquisitions, which can easily and efficiently be handled by a local bus. An on-board hierarchical network can therefore be defined by interconnecting high-speed links and local buses. Additionally, it is worth stressing another important aspect of the design process: Agencies and ESA in particular are frequently confronted with a big consortium of geographically spread companies located in different countries, each one

  7. Hierarchical Reverberation Mapping

    CERN Document Server

    Brewer, Brendon J

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large amount of data needed to measure $\\tau$. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow fo...

  8. Hierarchical prisoner’s dilemma in hierarchical game for resource competition

    Science.gov (United States)

    Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

    2017-07-01

    Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

  9. Higher-Order Hierarchical Legendre Basis Functions in Applications

    DEFF Research Database (Denmark)

    Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter;

    2007-01-01

    degree of orthogonality. The basis functions are well-suited for solution of complex electromagnetic problems involving multiple homogeneous or inhomogeneous dielectric regions, metallic surfaces, layered media, etc. This paper presents real-life complex antenna radiation problems modeled...... with electromagnetic simulation tools based on the higher-order hierarchical Legendre basis functions....

  10. Hierarchical surfaces for enhanced self-cleaning applications

    Science.gov (United States)

    Fernández, Ariadna; Francone, Achille; Thamdrup, Lasse H.; Johansson, Alicia; Bilenberg, Brian; Nielsen, Theodor; Guttmann, Markus; Sotomayor Torres, Clivia M.; Kehagias, Nikolaos

    2017-04-01

    In this study we present a flexible and adaptable fabrication method to create complex hierarchical structures over inherently hydrophobic resist materials. We have tested these surfaces for their superhydrophobic behaviour and successfully verified their self-cleaning properties. The followed approach allow us to design and produce superhydrophobic surfaces in a reproducible manner. We have analysed different combination of hierarchical micro-nanostructures for their application to self-cleaning surfaces. A static contact angle value of 170° with a hysteresis of 4° was achieved without the need of any additional chemical treatment on the fabricated hierarchical structures. Dynamic effects were analysed on these surfaces, obtaining a remarkable self-cleaning effect as well as a good robustness over impacting droplets.

  11. Prostaglandin E2 Exerts Multiple Regulatory Actions on Human Obese Adipose Tissue Remodeling, Inflammation, Adaptive Thermogenesis and Lipolysis.

    Directory of Open Access Journals (Sweden)

    Verónica García-Alonso

    Full Text Available Obesity induces white adipose tissue (WAT dysfunction characterized by unremitting inflammation and fibrosis, impaired adaptive thermogenesis and increased lipolysis. Prostaglandins (PGs are powerful lipid mediators that influence the homeostasis of several organs and tissues. The aim of the current study was to explore the regulatory actions of PGs in human omental WAT collected from obese patients undergoing laparoscopic bariatric surgery. In addition to adipocyte hypertrophy, obese WAT showed remarkable inflammation and total and pericellular fibrosis. In this tissue, a unique molecular signature characterized by altered expression of genes involved in inflammation, fibrosis and WAT browning was identified by microarray analysis. Targeted LC-MS/MS lipidomic analysis identified increased PGE2 levels in obese fat in the context of a remarkable COX-2 induction and in the absence of changes in the expression of terminal prostaglandin E synthases (i.e. mPGES-1, mPGES-2 and cPGES. IPA analysis established PGE2 as a common top regulator of the fibrogenic/inflammatory process present in this tissue. Exogenous addition of PGE2 significantly reduced the expression of fibrogenic genes in human WAT explants and significantly down-regulated Col1α1, Col1α2 and αSMA in differentiated 3T3 adipocytes exposed to TGF-β. In addition, PGE2 inhibited the expression of inflammatory genes (i.e. IL-6 and MCP-1 in WAT explants as well as in adipocytes challenged with LPS. PGE2 anti-inflammatory actions were confirmed by microarray analysis of human pre-adipocytes incubated with this prostanoid. Moreover, PGE2 induced expression of brown markers (UCP1 and PRDM16 in WAT and adipocytes, but not in pre-adipocytes, suggesting that PGE2 might induce the trans-differentiation of adipocytes towards beige/brite cells. Finally, PGE2 inhibited isoproterenol-induced adipocyte lipolysis. Taken together, these findings identify PGE2 as a regulator of the complex network of

  12. Prostaglandin E2 Exerts Multiple Regulatory Actions on Human Obese Adipose Tissue Remodeling, Inflammation, Adaptive Thermogenesis and Lipolysis

    Science.gov (United States)

    García-Alonso, Verónica; Titos, Esther; Alcaraz-Quiles, Jose; Rius, Bibiana; Lopategi, Aritz; López-Vicario, Cristina; Jakobsson, Per-Johan; Delgado, Salvadora; Lozano, Juanjo; Clària, Joan

    2016-01-01

    Obesity induces white adipose tissue (WAT) dysfunction characterized by unremitting inflammation and fibrosis, impaired adaptive thermogenesis and increased lipolysis. Prostaglandins (PGs) are powerful lipid mediators that influence the homeostasis of several organs and tissues. The aim of the current study was to explore the regulatory actions of PGs in human omental WAT collected from obese patients undergoing laparoscopic bariatric surgery. In addition to adipocyte hypertrophy, obese WAT showed remarkable inflammation and total and pericellular fibrosis. In this tissue, a unique molecular signature characterized by altered expression of genes involved in inflammation, fibrosis and WAT browning was identified by microarray analysis. Targeted LC-MS/MS lipidomic analysis identified increased PGE2 levels in obese fat in the context of a remarkable COX-2 induction and in the absence of changes in the expression of terminal prostaglandin E synthases (i.e. mPGES-1, mPGES-2 and cPGES). IPA analysis established PGE2 as a common top regulator of the fibrogenic/inflammatory process present in this tissue. Exogenous addition of PGE2 significantly reduced the expression of fibrogenic genes in human WAT explants and significantly down-regulated Col1α1, Col1α2 and αSMA in differentiated 3T3 adipocytes exposed to TGF-β. In addition, PGE2 inhibited the expression of inflammatory genes (i.e. IL-6 and MCP-1) in WAT explants as well as in adipocytes challenged with LPS. PGE2 anti-inflammatory actions were confirmed by microarray analysis of human pre-adipocytes incubated with this prostanoid. Moreover, PGE2 induced expression of brown markers (UCP1 and PRDM16) in WAT and adipocytes, but not in pre-adipocytes, suggesting that PGE2 might induce the trans-differentiation of adipocytes towards beige/brite cells. Finally, PGE2 inhibited isoproterenol-induced adipocyte lipolysis. Taken together, these findings identify PGE2 as a regulator of the complex network of interactions

  13. Prostaglandin E2 Exerts Multiple Regulatory Actions on Human Obese Adipose Tissue Remodeling, Inflammation, Adaptive Thermogenesis and Lipolysis.

    Science.gov (United States)

    García-Alonso, Verónica; Titos, Esther; Alcaraz-Quiles, Jose; Rius, Bibiana; Lopategi, Aritz; López-Vicario, Cristina; Jakobsson, Per-Johan; Delgado, Salvadora; Lozano, Juanjo; Clària, Joan

    2016-01-01

    Obesity induces white adipose tissue (WAT) dysfunction characterized by unremitting inflammation and fibrosis, impaired adaptive thermogenesis and increased lipolysis. Prostaglandins (PGs) are powerful lipid mediators that influence the homeostasis of several organs and tissues. The aim of the current study was to explore the regulatory actions of PGs in human omental WAT collected from obese patients undergoing laparoscopic bariatric surgery. In addition to adipocyte hypertrophy, obese WAT showed remarkable inflammation and total and pericellular fibrosis. In this tissue, a unique molecular signature characterized by altered expression of genes involved in inflammation, fibrosis and WAT browning was identified by microarray analysis. Targeted LC-MS/MS lipidomic analysis identified increased PGE2 levels in obese fat in the context of a remarkable COX-2 induction and in the absence of changes in the expression of terminal prostaglandin E synthases (i.e. mPGES-1, mPGES-2 and cPGES). IPA analysis established PGE2 as a common top regulator of the fibrogenic/inflammatory process present in this tissue. Exogenous addition of PGE2 significantly reduced the expression of fibrogenic genes in human WAT explants and significantly down-regulated Col1α1, Col1α2 and αSMA in differentiated 3T3 adipocytes exposed to TGF-β. In addition, PGE2 inhibited the expression of inflammatory genes (i.e. IL-6 and MCP-1) in WAT explants as well as in adipocytes challenged with LPS. PGE2 anti-inflammatory actions were confirmed by microarray analysis of human pre-adipocytes incubated with this prostanoid. Moreover, PGE2 induced expression of brown markers (UCP1 and PRDM16) in WAT and adipocytes, but not in pre-adipocytes, suggesting that PGE2 might induce the trans-differentiation of adipocytes towards beige/brite cells. Finally, PGE2 inhibited isoproterenol-induced adipocyte lipolysis. Taken together, these findings identify PGE2 as a regulator of the complex network of interactions

  14. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  15. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  16. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  17. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  18. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  19. Advanced hierarchical distance sampling

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

  20. Multiple parameter synchronous monitor system for human adaptability in altiplano%人体高原适应性多参数同步监测系统

    Institute of Scientific and Technical Information of China (English)

    杨雷; 王磊; 欧燕; 蔡尧钟

    2009-01-01

    To aim at altitude sickness, this multiple parameter synchronous monitor system for human adaptability in alti-plano is excogitated. The change of physiological parameters(SPO2 HR, ECG, pulse wave, breath wave)of human in alti-plano and the environment parameters(altitude, air pressure, temperature, direction, GPS positioning)are monitored via no injury method. The intuitionist estimation is given by the analysis of the multiple parameters using the arithmetic of the adaptability in altiplano. The data can be transmitted by wireless communication module.%针对急性高原反应,研发了相关的人体高原适应性多参数同步监测系统.通过无创的方法来监测人体在高海拔环境下相关生理参数(血氧饱和度、心率、心电、脉搏波、呼吸)的变化,同时监测人体所处外界环境参数(海拔、气压、温度、方向、GPS定位).通过基于无创多参数同步测量系统之上的高原适应性分析算法,对多种参数综合分析,给出人体在高海拔下的高原适应状况的直观判断,通过通讯模块实现数据远距离无线传输.

  1. Motivation and drives in bottom-up developments in natural hazards management: multiple-use of adaptation strategies in Austria

    Science.gov (United States)

    Thaler, Thomas; Fuchs, Sven

    2015-04-01

    Losses from extreme hydrological events, such as recently experienced in Europe have focused the attention of policymakers as well as researchers on vulnerability to natural hazards. In parallel, the context of changing flood risks under climate and societal change is driving transformation in the role of the state in responsibility sharing and individual responsibilities for risk management and precaution. The new policy agenda enhances the responsibilities of local authorities and private citizens in hazard management and reduces the role of central governments. Within the objective is to place added responsibility on local organisations and citizens to determine locally-based strategies for risk reduction. A major challenge of modelling adaptation is to represent the complexity of coupled human-environmental systems and particularly the feedback loops between environmental dynamics and human decision-making processes on different scales. This paper focuses on bottom-up initiatives to flood risk management which are, by definition, different from the mainstream. These initiatives are clearly influenced (positively or negatively) by a number of factors, where the combination of these interdependences can create specific conditions that alter the opportunity for effective governance arrangements in a local scheme approach. In total, this study identified six general drivers which encourage the implementation of flood storages, such as direct relation to recent major flood frequency and history, the initiative of individual stakeholders (promoters), political pressures from outside (e.g. business companies, private households) and a strong solidarity attitude of municipalities and the stakeholders involved. Although partnership approach may be seen as an 'optimal' solution for flood risk management, in practice there are many limitations and barriers in establishing these collaborations and making them effective (especially in the long term) with the consequences

  2. Learning emergent behaviours for a hierarchical Bayesian framework for active robotic perception.

    Science.gov (United States)

    Ferreira, João Filipe; Tsiourti, Christiana; Dias, Jorge

    2012-08-01

    In this research work, we contribute with a behaviour learning process for a hierarchical Bayesian framework for multimodal active perception, devised to be emergent, scalable and adaptive. This framework is composed by models built upon a common spatial configuration for encoding perception and action that is naturally fitting for the integration of readings from multiple sensors, using a Bayesian approach devised in previous work. The proposed learning process is shown to reproduce goal-dependent human-like active perception behaviours by learning model parameters (referred to as "attentional sets") for different free-viewing and active search tasks. Learning was performed by presenting several 3D audiovisual virtual scenarios using a head-mounted display, while logging the spatial distribution of fixations of the subject (in 2D, on left and right images, and in 3D space), data which are consequently used as the training set for the framework. As a consequence, the hierarchical Bayesian framework adequately implements high-level behaviour resulting from low-level interaction of simpler building blocks by using the attentional sets learned for each task, and is able to change these attentional sets "on the fly," allowing the implementation of goal-dependent behaviours (i.e., top-down influences).

  3. Urban pattern: Layout design by hierarchical domain splitting

    KAUST Repository

    Yang, Yongliang

    2013-11-01

    We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

  4. Information diffusion on adaptive network

    Institute of Scientific and Technical Information of China (English)

    Hu Ke; Tang Yi

    2008-01-01

    Based on the adaptive network,the feedback mechanism and interplay between the network topology and the diffusive process of information are studied.The results reveal that the adaptation of network topology can drive systems into the scale-free one with the assortative or disassortative degree correlations,and the hierarchical clustering.Meanwhile,the processes of the information diffusion are extremely speeded up by the adaptive changes of network topology.

  5. Adaptive Immune Responses in a Multiple Sclerosis Patient with Acute Varicella-Zoster Virus Reactivation during Treatment with Fingolimod

    Directory of Open Access Journals (Sweden)

    Andrea Harrer

    2015-09-01

    Full Text Available Fingolimod, an oral sphingosine 1-phosphate (S1P receptor modulator, is approved for the treatment of relapsing forms of multiple sclerosis (MS. The interference with S1P signaling leads to retention particularly of chemokine receptor-7 (CCR7 expressing T cells in lymph nodes. The immunological basis of varicella zoster virus (VZV infections during fingolimod treatment is unclear. Here, we studied the dynamics of systemic and intrathecal immune responses associated with symptomatic VZV reactivation including cessation of fingolimod and initiation of antiviral therapy. Key features in peripheral blood were an about two-fold increase of VZV-specific IgG at diagnosis of VZV reactivation as compared to the previous months, a relative enrichment of effector CD4+ T cells (36% versus mean 12% in controls, and an accelerated reconstitution of absolute lymphocytes counts including a normalized CD4+/CD8+ ratio and reappearance of CCR7+ T cells. In cerebrospinal fluid (CSF the lymphocytic pleocytosis and CD4+/CD8+ ratios at diagnosis of reactivation and after nine days of fingolimod discontinuation remained unchanged. During this time CCR7+ T cells were not observed in CSF. Further research into fingolimod-associated VZV reactivation and immune reconstitution is mandatory to prevent morbidity and mortality associated with this potentially life-threatening condition.

  6. Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay

    Science.gov (United States)

    McGowan, Conor P.; Lyons, James E.; Smith, David

    2015-01-01

    Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.

  7. HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

    Science.gov (United States)

    Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

    2017-02-09

    In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

  8. Online state of charge and model parameters estimation of the LiFePO4 battery in electric vehicles using multiple adaptive forgetting factors recursive least-squares

    Science.gov (United States)

    Duong, Van-Huan; Bastawrous, Hany Ayad; Lim, KaiChin; See, Khay Wai; Zhang, Peng; Dou, Shi Xue

    2015-11-01

    This paper deals with the contradiction between simplicity and accuracy of the LiFePO4 battery states estimation in the electric vehicles (EVs) battery management system (BMS). State of charge (SOC) and state of health (SOH) are normally obtained from estimating the open circuit voltage (OCV) and the internal resistance of the equivalent electrical circuit model of the battery, respectively. The difficulties of the parameters estimation arise from their complicated variations and different dynamics which require sophisticated algorithms to simultaneously estimate multiple parameters. This, however, demands heavy computation resources. In this paper, we propose a novel technique which employs a simplified model and multiple adaptive forgetting factors recursive least-squares (MAFF-RLS) estimation to provide capability to accurately capture the real-time variations and the different dynamics of the parameters whilst the simplicity in computation is still retained. The validity of the proposed method is verified through two standard driving cycles, namely Urban Dynamometer Driving Schedule and the New European Driving Cycle. The proposed method yields experimental results that not only estimated the SOC with an absolute error of less than 2.8% but also characterized the battery model parameters accurately.

  9. Efficient scalable algorithms for hierarchically semiseparable matrices

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de

    2011-09-14

    Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.

  10. Farmer responses to multiple stresses in the face of global change: Assessing five case studies to enhance adaptation

    Science.gov (United States)

    Nicholas, K. A.; Feola, G.; Lerner, A. M.; Jain, M.; Montefrio, M.

    2013-12-01

    The global challenge of sustaining agricultural livelihoods and yields in the face of growing populations and increasing climate change is the topic of intense research. The role of on-the-ground decision-making by individual farmers actually producing food, fuel, and fiber is often studied in individual cases to determine its environmental, economic, and social effects. However, there are few efforts to link across studies in a way that provides opportunities to better understand empirical farmer behavior, design effective policies, and be able to aggregate from case studies to a broader scale. Here we synthesize existing literature to identify four general factors affecting farmer decision-making: local technical and socio-cultural contexts; actors and institutions involved in decision-making; multiple stressors at broader scales; and the temporal gradient of decision-making. We use these factors to compare five cases that illustrate agricultural decision-making and its impacts: cotton and castor farming in Gujarat, India; swidden cultivation of upland rice in the Philippines; potato cultivation in Andean Colombia; winegrowing in Northern California; and maize production in peri-urban central Mexico. These cases span a geographic and economic range of production systems, but we find that we are able to make valid comparisons and draw lessons common across all cases by using the four factors as an organizing principle. We also find that our understanding of why farmers make the decisions they do changes if we neglect to examine even one of the four general factors guiding decision-making. This suggests that these four factors are important to understanding farmer decision-making, and can be used to guide the design and interpretation of future studies, as well as be the subject of further research in and of themselves to promote an agricultural system that is resilient to climate and other global environmental changes.

  11. Muscular strength adaptations and hormonal responses after two different multiple-set protocols of resistance training in postmenopausal women.

    Science.gov (United States)

    Nunes, Paulo Ricardo P; Barcelos, Larissa C; Oliveira, Anselmo A; Júnior, Roberto Furlanetto; Martins, Fernanda M; Resende, Elizabete Ap M R; Orsatti, Fábio L

    2017-01-20

    We studied the effects of two different resistance training (RT) multiple-set protocols (three and six sets) on muscle strength and basal hormones concentrations in postmenopausal women (PW). Thirty-four PW were randomly allocated into three groups: control (CT, n=12), low RT volume (LV = three sets for each exercise, n=10) and high RT volume (HV = six sets for each exercise, n=12). The LV and HV groups performed eight exercises of a total body RT protocol three times a week, at 70 % of one repetition maximum (1RM) for 16 weeks. The muscle strength and basal hormones concentration were measured before and after the RT. Our findings show that three sets or six sets at 70% of 1RM protocol increased muscular strength similarly after 16 weeks (sum of all exercises, LV: 37.7% and HV: 34.1% vs. CT: 2.1%, p < 0.001). Moreover, the RT volume does not affect basal levels of testosterone (TT) (LV: 0.02%, HV: -0.12% and CT: 0.006%, p = 0.233), cortisol (C) (LV: 72.4%, HV: 36.8% and CT: 16.8%, p = 0.892), insulin-like growth factor-1 (LV: 6.7%, HV: 7.3% and CT: 4.1%, p = 0.802), dehydroepiandrosterone sulfate (LV: 0.1%, HV: -4.5% and CT: -6.7%, p = 0.885) and TT:C ratio (LV: -0.9%, HV: -1.6% and CT: -0.4%, p = 0.429). Our results suggest that three sets and six sets at 70% of 1RM seem to promote similar muscle strength gain. Thus, three set RT is a time efficient protocol for strength gain after 16 weeks in PW.

  12. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  13. Power Efficient Hierarchical Scheduling for DSP Transformations

    Directory of Open Access Journals (Sweden)

    P. K. Merakos

    2002-01-01

    Full Text Available In this paper, the problem of scheduling the computation of partial products in transformational Digital Signal Processing (DSP algorithms, aiming at the minimization of the switching activity in data and address buses, is addressed. The problem is stated as a hierarchical scheduling problem. Two different optimization algorithms, which are based on the Travelling Salesman Problem (TSP, are defined. The proposed optimization algorithms are independent on the target architecture and can be adapted to take into account it. Experimental results obtained from the application of the proposed algorithms in various widely used DSP transformations, like Discrete Cosine Transform (DCT and Discrete Fourier Transform (DFT, show that significant switching activity savings in data and address buses can be achieved, resulting in corresponding power savings. In addition, the differences between the two proposed methods are underlined, providing envisage for their suitable selection for implementation, in particular transformational algorithms and architectures.

  14. Hierarchical Codebook Design for Massive MIMO

    Directory of Open Access Journals (Sweden)

    Xin Su

    2015-02-01

    Full Text Available The Research of Massive MIMO is an emerging area, since the more antennas the transmitters or receivers equipped with, the higher spectral efficiency and link reliability the system can provide. Due to the limited feedback channel, precoding and codebook design are important to exploit the performance of massive MIMO. To improve the precoding performance, we propose a novel hierarchical codebook with the Fourier-based perturbation matrices as the subcodebook and the Kerdock codebook as the main codebook, which could reduce storage and search complexity due to the finite a lphabet. Moreover, t o f urther r educe t he search complexity and feedback overhead without noticeable performance degradation, we use an adaptive selection algorithm to decide whether to use the subcodebook. Simulation results show that the proposed codebook has remarkable performance gain compared to the conventional Kerdock codebook, without significant increase in feedback overhead and search complexity.

  15. Replanning Using Hierarchical Task Network and Operator-Based Planning

    Science.gov (United States)

    Wang, X.; Chien, S.

    1997-01-01

    In order to scale-up to real-world problems, planning systems must be able to replan in order to deal with changes in problem context. In this paper we describe hierarchical task network and operatorbased re-planning techniques which allow adaptation of a previous plan to account for problems associated with executing plans in real-world domains with uncertainty, concurrency, changing objectives.

  16. Hierarchical Overlapping Clustering of Network Data Using Cut Metrics

    CERN Document Server

    Gama, Fernando; Ribeiro, Alejandro

    2016-01-01

    A novel method to obtain hierarchical and overlapping clusters from network data -i.e., a set of nodes endowed with pairwise dissimilarities- is presented. The introduced method is hierarchical in the sense that it outputs a nested collection of groupings of the node set depending on the resolution or degree of similarity desired, and it is overlapping since it allows nodes to belong to more than one group. Our construction is rooted on the facts that a hierarchical (non-overlapping) clustering of a network can be equivalently represented by a finite ultrametric space and that a convex combination of ultrametrics results in a cut metric. By applying a hierarchical (non-overlapping) clustering method to multiple dithered versions of a given network and then convexly combining the resulting ultrametrics, we obtain a cut metric associated to the network of interest. We then show how to extract a hierarchical overlapping clustering structure from the aforementioned cut metric. Furthermore, the so-called overlappi...

  17. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    Purpose This paper aims to present that deliberate change is strongly associated with formal structures and top-down influence. Hierarchical configurations have been used to structure processes, overcome resistance and get things done. But is deliberate change also possible without formal...... reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  18. Multiple hypothesis tracking with adaptive association depth%关联深度自适应的多假设跟踪研究

    Institute of Scientific and Technical Information of China (English)

    陈杭; 张伯彦; 陈映

    2016-01-01

    多假设跟踪(multiple hypothesis tracking,MHT)方法是一种在多个扫描上评价关联假设并由此做出决策的贝叶斯型关联跟踪方法,此方法能够在信噪比低10~100倍的状况下获得与单扫描方法相当的性能,但同时会带来相当大的计算量。本文研究了面向航迹 MHT 中的关键算法,包括航迹得分计算与航迹树的生成、将航迹聚类和假设生成建模为图论问题并求解、N 扫描回溯剪枝等,特别关注了这些算法过程的实现;提出了一种关联深度自适应(adaptive association depth,AAD)方法,使关联深度随关联场景的复杂程度自适应变化;仿真研究了本文提出的 AAD-MHT 跟踪密集目标的性能,结果和分析表明,与深度值固定为6的 MHT 相比,最大深度为6的 AAD-MHT 既能保证性能又有效降低了计算量。%Multiple hypothesis tracking(MHT)is a Bayesian association method that evaluates association hypotheses among multiple scans and makes evaluation-based decisions.Comparing with the single hypothesis method,MHT can work reasonably under 10 ~ 100 times lower signal-noise ratio (SNR)but it needs much more computational load.The implementation of track-oriented MHT (TOMHT)is studied and some key points are investigated,include calculating the track score,generating the track tree,modeling track clustering, hypotheses generating as problems in graph theory and N-scan pruning,etc.In the TOMHT framework,an a-daptive association depth (AAD)method is proposed.This method makes the association depth change adap-tively with the complexity of scenarios.Its performance is investigated by several simulation experiments on tracking closely targets.The results and analysis show that the performance of AAD-MHT is nearly the same as MHT but the computational load is much lower.

  19. Structural integrity of hierarchical composites

    Directory of Open Access Journals (Sweden)

    Marco Paggi

    2012-01-01

    Full Text Available Interface mechanical problems are of paramount importance in engineering and materials science. Traditionally, due to the complexity of modelling their mechanical behaviour, interfaces are often treated as defects and their features are not explored. In this study, a different approach is illustrated, where the interfaces play an active role in the design of innovative hierarchical composites and are fundamental for their structural integrity. Numerical examples regarding cutting tools made of hierarchical cellular polycrystalline materials are proposed, showing that tailoring of interface properties at the different scales is the way to achieve superior mechanical responses that cannot be obtained using standard materials

  20. Hierarchical Training Mode for Market Demand Oriented Outstanding Seed Industry Talents

    Institute of Scientific and Technical Information of China (English)

    Xuechun; WANG; Hongni; WANG; Shishun; TAO

    2014-01-01

    This paper analyzed the trend of seed industry development in-depth and studied changes in quantity and quality of demands for seed industry talents. To adapt to " breeding,propagating and selling" integration and internationalized trend of seed industry,it stated that hierarchical training mode is an ideal mode for training outstanding seed industry talents. Finally,it elaborated specific objectives and requirements of the hierarchical training mode,i. e. undergraduate- master- doctor.

  1. Sensory Hierarchical Organization and Reading.

    Science.gov (United States)

    Skapof, Jerome

    The purpose of this study was to judge the viability of an operational approach aimed at assessing response styles in reading using the hypothesis of sensory hierarchical organization. A sample of 103 middle-class children from a New York City public school, between the ages of five and seven, took part in a three phase experiment. Phase one…

  2. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  3. When to Use Hierarchical Linear Modeling

    Directory of Open Access Journals (Sweden)

    Veronika Huta

    2014-04-01

    Full Text Available Previous publications on hierarchical linear modeling (HLM have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis: Does HLM apply to one’s data and research question? And if it does apply, how does one choose between HLM and other methods sometimes used in these circumstances, including multiple regression, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis? The purpose of this tutorial is to briefly introduce HLM and then to review some of the considerations that are helpful in answering these questions, including the nature of the data, the model to be tested, and the information desired on the output. Some examples of how the same analysis could be performed in HLM, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis are also provided. .

  4. Learning a hierarchical deformable template for rapid deformable object parsing.

    Science.gov (United States)

    Zhu, Long Leo; Chen, Yuanhao; Yuille, Alan

    2010-06-01

    In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical deformable template (HDT). The HDT represents the object by state variables defined over a hierarchy (with typically five levels). The hierarchy is built recursively by composing elementary structures to form more complex structures. A probability distribution--a parameterized exponential model--is defined over the hierarchy to quantify the variability in shape and appearance of the object at multiple scales. To perform inference--to estimate the most probable states of the hierarchy for an input image--we use a bottom-up algorithm called compositional inference. This algorithm is an approximate version of dynamic programming where approximations are made (e.g., pruning) to ensure that the algorithm is fast while maintaining high performance. We adapt the structure-perceptron algorithm to estimate the parameters of the HDT in a discriminative manner (simultaneously estimating the appearance and shape parameters). More precisely, we specify an exponential distribution for the HDT using a dictionary of potentials, which capture the appearance and shape cues. This dictionary can be large and so does not require handcrafting the potentials. Instead, structure-perceptron assigns weights to the potentials so that less important potentials receive small weights (this is like a "soft" form of feature selection). Finally, we provide experimental evaluation of HDTs on different visual tasks, including detection, segmentation, matching (alignment), and parsing. We show that HDTs achieve state-of-the-art performance for these different tasks when evaluated on data sets with groundtruth (and when compared to alternative algorithms, which are typically specialized to each task).

  5. Goleman's Leadership styles at different hierarchical levels in medical education.

    Science.gov (United States)

    Saxena, Anurag; Desanghere, Loni; Stobart, Kent; Walker, Keith

    2017-09-19

    With current emphasis on leadership in medicine, this study explores Goleman's leadership styles of medical education leaders at different hierarchical levels and gain insight into factors that contribute to the appropriateness of practices. Forty two leaders (28 first-level with limited formal authority, eight middle-level with wider program responsibility and six senior- level with higher organizational authority) rank ordered their preferred Goleman's styles and provided comments. Eight additional senior leaders were interviewed in-depth. Differences in ranked styles within groups were determined by Friedman tests and Wilcoxon tests. Based upon style descriptions, confirmatory template analysis was used to identify Goleman's styles for each interviewed participant. Content analysis was used to identify themes that affected leadership styles. There were differences in the repertoire and preferred styles at different leadership levels. As a group, first-level leaders preferred democratic, middle-level used coaching while the senior leaders did not have one preferred style and used multiple styles. Women and men preferred democratic and coaching styles respectively. The varied use of styles reflected leadership conceptualizations, leader accountabilities, contextual adaptations, the situation and its evolution, leaders' awareness of how they themselves were situated, and personal preferences and discomfort with styles. The not uncommon use of pace-setting and commanding styles by senior leaders, who were interviewed, was linked to working with physicians and delivering quickly on outcomes. Leaders at different levels in medical education draw from a repertoire of styles. Leadership development should incorporate learning of different leadership styles, especially at first- and mid-level positions.

  6. ECoS, a framework for modelling hierarchical spatial systems.

    Science.gov (United States)

    Harris, John R W; Gorley, Ray N

    2003-10-01

    A general framework for modelling hierarchical spatial systems has been developed and implemented as the ECoS3 software package. The structure of this framework is described, and illustrated with representative examples. It allows the set-up and integration of sets of advection-diffusion equations representing multiple constituents interacting in a spatial context. Multiple spaces can be defined, with zero, one or two-dimensions and can be nested, and linked through constituent transfers. Model structure is generally object-oriented and hierarchical, reflecting the natural relations within its real-world analogue. Velocities, dispersions and inter-constituent transfers, together with additional functions, are defined as properties of constituents to which they apply. The resulting modular structure of ECoS models facilitates cut and paste model development, and template model components have been developed for the assembly of a range of estuarine water quality models. Published examples of applications to the geochemical dynamics of estuaries are listed.

  7. Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

    CERN Document Server

    Fujimoto, Yuma; Kaneko, Kunihiko

    2016-01-01

    The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical d...

  8. Comparison of Two Hierarchical Routing Protocols for Heterogeneous MANET

    Science.gov (United States)

    2007-10-01

    protocols (e.g. Ad-Hoc On-Demand Distance Vector routing protocol , AODV ) search for and maintain routes to destination nodes upon demand from...the time it takes to find a route when data needs to be sent. Protocols such as OLSR and AODV support nodes having multiple interfaces. However they...hierarchical ad hoc routing protocols are derived from a “flat” ad routing protocol . For instance, H- AODV [8] and H-DSR [11] are examples

  9. Hierarchical Control of Thermostatically Controller Loads for Primary Frequency Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun

    2016-01-01

    This paper proposes a hierarchical control of Thermostatically Controlled Loads (TCLs) to provide primary frequency control support. The control architecture is comprised of three levels. At the high level, an aggregator coordinates multiple distribution substations and dispatches the primary...... respond to the frequency event autonomously. Case studies show that the proposed controller can efficiently respond to frequency events and fulfill the requirement specified by the system operator. The users’ comforts are not compromised and the short cycling of TCLs is largely reduced. Due...

  10. Inference in HIV dynamics models via hierarchical likelihood

    OpenAIRE

    2010-01-01

    HIV dynamical models are often based on non-linear systems of ordinary differential equations (ODE), which do not have analytical solution. Introducing random effects in such models leads to very challenging non-linear mixed-effects models. To avoid the numerical computation of multiple integrals involved in the likelihood, we propose a hierarchical likelihood (h-likelihood) approach, treated in the spirit of a penalized likelihood. We give the asymptotic distribution of the maximum h-likelih...

  11. Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

    Science.gov (United States)

    Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

    2014-12-01

    This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

  12. Hierarchical structure of biological systems

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  13. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  14. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  15. Hierarchical Formation of Galactic Clusters

    CERN Document Server

    Elmegreen, B G

    2006-01-01

    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  16. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

  17. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.

  18. Effect of multiple stress factors (thermal, nutritional and pregnancy type) on adaptive capability of native ewes under semi-arid environment.

    Science.gov (United States)

    Dias E Silva, Tairon Pannunzio; Costa Torreão, Jacira Neves da; Torreão Marques, Carlo Aldrovandi; de Araújo, Marcos Jácome; Bezerra, Leílson Rocha; Kumar Dhanasekaran, Dinesh; Sejian, Veerasamy

    2016-07-01

    This study was conducted to evaluate the effect of multiple stress factors (thermal, nutritional and pregnancy type) on two different native track breeds of ewes as reflected by their adaptive capability under semi-arid environment. The multiple stressor experiment was conducted in twenty-four ewes (12 Santa Inês and 12 Morada Nova ewes). Both heat stress and pregnancy stress was common to all four groups. However, the animals were divided into further two groups within each breed on the basis of nutrition regimen. According the groupings were: Group 1 (Six Santa Ines ewes; heat stress; nutrition at 0.5% of BW; single pregnancy); Group 2 (Six Santa Ines ewes; heat stress; nutrition at 1.5% BW; twin pregnancy); groups Group 3 (Six Morada Nova ewes; heat stress; nutrition at 0.5% of BW; single pregnancy); Group 4 (Six Morada Nova ewes; heat stress; nutrition at 1.5% BW; twin pregnancy). All the animals in the experiment were pregnant. Heat stress was induced by exposing all animals to summer heat stress in outside environment while the nutritional regimen followed was at 0.5% and 1.5% level of body weight (BW) respectively in each breed. The experiment was conducted in a completely randomized design with two breeds, two nutritional treatments and two pregnancy types, 10 repetitions for physiological parameters and six for blood parameters, with repeated measures over time. Physiological parameters (respiratory rate, pulse rate and rectal temperature) were measured with the animals at rest in the morning and afternoon, 0600-0700 and 1300-1400h, respectively, every seven days. Blood samples were collected every 14d for determination of serum glucose, triglycerides, cholesterol, urea and creatinine. We found interaction effect between breed and pregnancy type on respiratory rate and rectal temperature with greater values in Santa Inês ewes than Morada Nova ewes. However, there was no significant fixed effect of pregnancy type and supplementation level on physiological

  19. Hierarchical Clustering and Active Galaxies

    CERN Document Server

    Hatziminaoglou, E; Manrique, A

    2000-01-01

    The growth of Super Massive Black Holes and the parallel development of activity in galactic nuclei are implemented in an analytic code of hierarchical clustering. The evolution of the luminosity function of quasars and AGN will be computed with special attention paid to the connection between quasars and Seyfert galaxies. One of the major interests of the model is the parallel study of quasar formation and evolution and the History of Star Formation.

  20. Hybrid and hierarchical composite materials

    CERN Document Server

    Kim, Chang-Soo; Sano, Tomoko

    2015-01-01

    This book addresses a broad spectrum of areas in both hybrid materials and hierarchical composites, including recent development of processing technologies, structural designs, modern computer simulation techniques, and the relationships between the processing-structure-property-performance. Each topic is introduced at length with numerous  and detailed examples and over 150 illustrations.   In addition, the authors present a method of categorizing these materials, so that representative examples of all material classes are discussed.

  1. Etk/Bmx mediates expression of stress-induced adaptive genes VEGF, PAI-1, and iNOS via multiple signaling cascades in different cell systems.

    Science.gov (United States)

    Chau, Cindy H; Clavijo, Carlos A; Deng, Hong-Tao; Zhang, Qunzhou; Kim, Kwang-Jin; Qiu, Yun; Le, Anh D; Ann, David K

    2005-08-01

    We recently showed that Etk/Bmx, a member of the Tec family of nonreceptor protein tyrosine kinases, promotes tight junction formation during chronic hypoxic exposure and augments normoxic VEGF expression via a feedforward mechanism. Here we further characterized Etk's role in potentiating hypoxia-induced gene expression in salivary epithelial Pa-4 cells. Using transient transfection in conditionally activated Etk (DeltaEtk:ER) cells, we demonstrated that Etk enhances hypoxia-response element-dependent reporter activation in normoxia and hypoxia. This Etk-driven reporter activation is ameliorated by treatment with wortmannin or LFM-A13. Using lentivirus-mediated gene delivery and small interfering RNA, we provided direct evidence that hypoxia leads to transient Etk and Akt activation and hypoxia-mediated Akt activation is Etk dependent. Northern blot analyses confirmed that Etk activation led to induction of steady-state mRNA levels of endogenous VEGF and plasminogen activator inhibitor (PAI)-1, a hallmark of hypoxia-mediated gene regulation. We also demonstrated that Etk utilizes a phosphatidylinositol 3-kinase/Akt pathway to promote reporter activation driven by NF-kappaB, another oxygen-sensitive transcription factor, and to augment cytokine-induced inducible nitric oxide synthase expression in endothelial cells. To establish the clinical relevance of Etk-induced, hypoxia-mediated gene regulation, we examined Etk expression in keloid, which has elevated VEGF and PAI-1. We found that Etk is overexpressed in keloid (but not normal skin) tissues. The differential steady-state Etk protein levels were further confirmed in primary fibroblast cultures derived from these tissues, suggesting an Etk role in tissue fibrosis. Our results provide further understanding of Etk function within multiple signaling cascades to govern adaptive cytoprotection against extracellular stress in different cell systems, salivary epithelial cells, brain endothelial cells, and dermal

  2. Study on Hierarchical Structure of Detailed Control Planning

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Using case studies,this paper analyzes the characteristics of detailed control planning and its hierarchical controls,the form and composition of plan content,and methodological innovations.It then suggests improvements to the planning structure that are oriented at adaptability,fairness,centrality,and scientific principles with regard to the content,methods,and results of the planning.Regarding the hierarchical control system,the paper suggests that the detailed control plan should be composed of "block planning" and "plot planning".It is believed that through a combination of block and plot planning,the problem of joining long-term and short-term planning will be solved and it will be possible to address the need for adjustment and revision of detailed control plan.

  3. Cooperative mechanism of self-regulation in hierarchical living systems

    CERN Document Server

    Lubashevsky, I A

    1998-01-01

    We study the problem of how a ``living'' system complex in structure can respond perfectly to local changes in the environment. Such a system is assumed to consist of a distributed ``living'' medium and a hierarchical ``supplying'' network that provides this medium with ``nutritious'' products. Because of the hierarchical organization each element of the supplying network has to behave in a self-consistent way for the system can adapt to changes in the environment. We propose a cooperative mechanism of self-regulation by which the system as a whole can react perfectly. This mechanism is based on an individual response of each element to the corresponding small piece of the information on the state of the ``living'' medium. The conservation of flux through the supplying network gives rise to a certain processing of information and the self-consistent behavior of the elements, leading to the perfect self-regulation. The corresponding equations governing the ``living'' medium state are obtained.

  4. Hierarchical Cellular Structures in High-Capacity Cellular Communication Systems

    CERN Document Server

    Jain, R K; Agrawal, N K

    2011-01-01

    In the prevailing cellular environment, it is important to provide the resources for the fluctuating traffic demand exactly in the place and at the time where and when they are needed. In this paper, we explored the ability of hierarchical cellular structures with inter layer reuse to increase the capacity of mobile communication network by applying total frequency hopping (T-FH) and adaptive frequency allocation (AFA) as a strategy to reuse the macro and micro cell resources without frequency planning in indoor pico cells [11]. The practical aspects for designing macro- micro cellular overlays in the existing big urban areas are also explained [4]. Femto cells are inducted in macro / micro / pico cells hierarchical structure to achieve the required QoS cost effectively.

  5. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    DEFF Research Database (Denmark)

    Custer, Rocco

    Societies around the world are faced with flood risk, prompting authorities and decision makers to manage risk to protect population and assets. With climate change, urbanisation and population growth, flood risk changes constantly, requiring flood risk management strategies that are flexible...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...... measures, allows identifying flexible and robust flood risk management strategies. Based on it, this thesis investigates hierarchical flood protection systems, which encompass two, or more, hierarchically integrated flood protection structures on different spatial scales (e.g. dikes, local flood barriers...

  6. Accounting for Cache Related Pre-emption Delays in Hierarchical Scheduling

    NARCIS (Netherlands)

    Lunniss, W.; Altmeyer, S.; Lipari, G.; Davis, R.I.

    2014-01-01

    Hierarchical scheduling provides a means of composing multiple real-time applications onto a single processor such that the temporal requirements of each application are met. This has become a popular technique in industry as it allows applications from multiple vendors as well as legacy application

  7. Accounting for Cache Related Pre-emption Delays in Hierarchical Scheduling with Local EDF Scheduler

    NARCIS (Netherlands)

    Lunniss, W.; Altmeyer, S.; Davis, R.I.

    2014-01-01

    Hierarchical scheduling provides a means of composing multiple real-time applications onto a single processor such that the temporal requirements of each application are met. This has become a popular technique in industry as it allows applications from multiple vendors as well as legacy application

  8. An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

    Directory of Open Access Journals (Sweden)

    Yunqing Rao

    2013-01-01

    Full Text Available For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

  9. SafeZone: A Hierarchical Inter-Domain Authenticated Source Address Validation Solution

    CERN Document Server

    Li, Jie; Xu, Ke

    2011-01-01

    Next generation Internet is highly concerned about the issue of reliability. Principally, the foundation of reliability is authentication of the source IP address. With the signature-and-verification based defense mechanisms available today, unfortunately, there is a lack of hierarchical architecture, which makes the structure of the trust alliance excessively flat and single. Moreover, with the increasing scale of the trust alliance, costs of validation grow so quickly that they do not adapt to incremental deployment. Via comparison with traditional solutions, this article proposes a hierarchical, inter-domain authenticated source address validation solution named SafeZone. SafeZone employs two intelligent designs, lightweight tag replacement and a hierarchical partitioning scheme, each of which helps to ensure that SafeZone can construct trustworthy and hierarchical trust alliances without the negative influences and complex operations on de facto networks. Extensive experiments also indicate that SafeZone ...

  10. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Clinical time series prediction: towards a hierarchical dynamical system framework

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  12. Bayesian Analysis of Multiple Populations I: Statistical and Computational Methods

    CERN Document Server

    Stenning, D C; Robinson, E; van Dyk, D A; von Hippel, T; Sarajedini, A; Stein, N

    2016-01-01

    We develop a Bayesian model for globular clusters composed of multiple stellar populations, extending earlier statistical models for open clusters composed of simple (single) stellar populations (vanDyk et al. 2009, Stein et al. 2013). Specifically, we model globular clusters with two populations that differ in helium abundance. Our model assumes a hierarchical structuring of the parameters in which physical properties---age, metallicity, helium abundance, distance, absorption, and initial mass---are common to (i) the cluster as a whole or to (ii) individual populations within a cluster, or are unique to (iii) individual stars. An adaptive Markov chain Monte Carlo (MCMC) algorithm is devised for model fitting that greatly improves convergence relative to its precursor non-adaptive MCMC algorithm. Our model and computational tools are incorporated into an open-source software suite known as BASE-9. We use numerical studies to demonstrate that our method can recover parameters of two-population clusters, and al...

  13. Hierarchical Participation Constraints for Adaptive Learning and Coordination

    DEFF Research Database (Denmark)

    Yi, Sangyoon; Stieglitz, Nils; Knudsen, Thorbjørn

    From the knowledge-based view of competence, firms exist as an institution where knowledge accumulation and knowledge application are facilitated by organizing principles that markets cannot provide. While scholars perceive that these two interdependent knowledge processes could be influenced...

  14. Optimism and adaptation to chronic disease: the role of optimism in relation to self-care options of type I diabetes mellitus, rheumatoid arthritis and multiple sclerosis.

    NARCIS (Netherlands)

    Fournier, M.; Ridder, D. de; Bensing, J.

    2002-01-01

    OBJECTIVES: To determine the role of optimistic beliefs in adaptation processes of three chronic diseases different in controllability by self-care. It was expected that optimism towards the future would relate to adaptation independently of the controllability of disease. Optimism regarding one's c

  15. MULTILEVEL RECURRENT MODEL FOR HIERARCHICAL CONTROL OF COMPLEX REGIONAL SECURITY

    Directory of Open Access Journals (Sweden)

    Andrey V. Masloboev

    2014-11-01

    Full Text Available Subject of research. The research goal and scope are development of methods and software for mathematical and computer modeling of the regional security information support systems as multilevel hierarchical systems. Such systems are characterized by loosely formalization, multiple-aspect of descendent system processes and their interconnectivity, high level dynamics and uncertainty. The research methodology is based on functional-target approach and principles of multilevel hierarchical system theory. The work considers analysis and structural-algorithmic synthesis problem-solving of the multilevel computer-aided systems intended for management and decision-making information support in the field of regional security. Main results. A hierarchical control multilevel model of regional socio-economic system complex security has been developed. The model is based on functional-target approach and provides both formal statement and solving, and practical implementation of the automated information system structure and control algorithms synthesis problems of regional security management optimal in terms of specified criteria. An approach for intralevel and interlevel coordination problem-solving in the multilevel hierarchical systems has been proposed on the basis of model application. The coordination is provided at the expense of interconnection requirements satisfaction between the functioning quality indexes (objective functions, which are optimized by the different elements of multilevel systems. That gives the possibility for sufficient coherence reaching of the local decisions, being made on the different control levels, under decentralized decision-making and external environment high dynamics. Recurrent model application provides security control mathematical models formation of regional socioeconomic systems, functioning under uncertainty. Practical relevance. The model implementation makes it possible to automate synthesis realization of

  16. A hierarchical model of the evolution of human brain specializations.

    Science.gov (United States)

    Barrett, H Clark

    2012-06-26

    The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised.

  17. Hierarchical traits distances explain grassland Fabaceae species’ ecological niches distances

    Directory of Open Access Journals (Sweden)

    Florian eFort

    2015-02-01

    Full Text Available Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e. ecological niches. We measured a wide range of functional traits (root traits, leaf traits and whole plant traits in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species’ ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

  18. Evaluation and mechanism for outcomes exploration of providing public health care in contract service in rural China: a multiple-case study with complex adaptive systems design.

    Science.gov (United States)

    Zhou, Huixuan; Zhang, Shengfa; Zhang, Weijun; Wang, Fugang; Zhong, You; Gu, Linni; Qu, Zhiyong; Tian, Donghua

    2015-02-27

    The Chinese government has increased the funding for public health in 2009 and experimentally applied a contract service policy (could be seen as a counterpart to family medicine) in 15 counties to promote public health services in the rural areas in 2013. The contract service aimed to convert village doctors, who had privately practiced for decades, into general practitioners under the government management, and better control the rampant chronic diseases. This study made a rare attempt to assess the effectiveness of public health services delivered under the contract service policy, explore the influencing mechanism and draw the implications for the policy extension in the future. Three pilot counties and a non-pilot one with heterogeneity in economic and health development from east to west of China were selected by a purposive sampling method. The case study methods by document collection, non-participant observation and interviews (including key informant interview and focus group interview) with 84 health providers and 20 demanders in multiple level were applied in this study. A thematic approach was used to compare diverse outcomes and analyze mechanism in the complex adaptive systems framework. Without sufficient incentives, the public health services were not conducted effectively, regardless of the implementation of the contract policy. To appropriately increase the funding for public health by local finance and properly allocate subsidy to village doctors was one of the most effective approaches to stimulate health providers and demanders' positivity and promote the policy implementation. County health bureaus acted as the most crucial agents among the complex public health systems. Their mental models influenced by the compound and various environments around them led to the diverse outcomes. If they could provide extra incentives and make the contexts of the systems ripe enough for change, the health providers and demanders would be receptive to the

  19. The icmF3 locus is involved in multiple adaptation- and virulence-related characteristics in Pseudomonas aeruginosa PAO1

    Directory of Open Access Journals (Sweden)

    Jinshui eLin

    2015-10-01

    Full Text Available The type VI secretion system (T6SS is widely distributed in Gram-negative bacteria. Three separate T6SSs called H1-, H2-, and H3-T6SS have been discovered in Pseudomonas aeruginosa PAO1. Recent studies suggest that, in contrast to the H1-T6SS that targets prokaryotic cells, H2-T6SS and H3-T6SS are involved in interactions with both prokaryotic and eukaryotic cells. However, the detailed functions of T6SS components are still uncharacterized. The intracellular multiplication factor (IcmF protein is conserved in type VI secretion systems (T6SS of all different bacterial pathogens. Bioinformatic analysis revealed that IcmF3 in P. aeruginosa PAO1 is different from other IcmF homologues and may represent a new branch of these proteins with distinct functions. Herein, we have investigated the function of IcmF3 in this strain. We have shown that deletion of the icmF3 gene in P. aeruginosa PAO1 is associated with pleiotropic phenotypes. The icmF3 mutant has variant colony morphology and an hypergrowth phenotype in iron-limiting medium. Surprisingly, this mutant is also defective for the production of pyoverdine, as well as defects in swimming motility and virulence in a C. elegans worm model. The icmF3 mutant exhibits higher conjugation frequency than the wild type and increased biofilm formation on abiotic surfaces. Additionally, expression of two phenazine biosynthetic loci is increased in the icmF3 mutant, leading to the overproduction of pyocyanin. Finally, the mutant exhibits decreased susceptibility to aminoglycosides such as tobramycin and gentamicin. And the detected phenotypes can be restored completely or partially by trans complementation of wild type icmF3 gene. The pleiotropic effects observed upon icmF3 deletion demonstrate that icmF3 plays critical roles in both pathogenesis and environmental adaptation in P. aeruginosa PAO1.

  20. Integrated optimization of management cost of hierarchical mobile IPv6 and its performance simulation

    Science.gov (United States)

    Peng, Xue-hai; Zhang, Hong-ke; Zhang, Si-dong

    2004-04-01

    Mobile IPv6 was designed to enable an IPv6 terminal to continue communications seamlessly while changing its access to network. Decreasing communication and management cost is a key issue of the research of the Internet mobility management. Hierarchical Mobile IPv6 was proposed to reduce the number of management messages in backbone network. However, the resources consumptions inside a hierarchical domain are increased as expense according to our cost models. Based on the idea of integrated optimization, adaptive mobility management scheme (AMMS) is proposed in this paper, which decreases the total cost of delivering management messages and data payload on the viewpoint of entire network resources by selecting a suitable mobility management scheme adaptively for a mobile node. The results of simulation show that AMMS has better performance than unmixed Mobile IPv6 and Hierarchical Mobile IPv6.

  1. Hierarchical Control for Smart Grids

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2011-01-01

    This paper deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high level MPC controller, a second level of so-called aggregators, which reduces the computational and communication-related load on the high-level control, and a lower level...... of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The objective is to accommodate the load variation on the grid, arising...

  2. Hierarchical Picture Coding Using Quadtree Decomposition

    Science.gov (United States)

    Buhler, Yves; Fortier, Michel

    1987-10-01

    A new hierarchical encoding scheme for grey-level pictures is presented here. The picture field is split by a modified quadtree algorithm into blocks of size 32 x 32, 16 x 16, 8 x 8 and 4 x 4 pels, according to their subjective importance in the picture. The larger cells, of size 32 x 32, 16 x 16 and 8 x 8 pels, corresponding to uniform or low-detailed areas, are coded at a very low rates by block truncation in the Discrete Cosine Transform field. The smallest blocks, representing mainly high-detailed areas of the like edges or textures are coded with a multi-codebook vector quantization scheme. Due to its structure, such an encoding scheme is especially well adapted for coding "head and shoulders" pictures, mostly encountered in videophone or videoconference application, where large areas of background may appear. Concerning the vector quantization, several techniques were investigated in order to improve the subjective quality and to reduce the search time through the codebooks. This permits a faster elaboration of the codebooks. Results are presented with bit-rates ranging from 0.4 to 0.8 bits/pel depending on the picture complexity.

  3. Create and Publish a Hierarchical Progressive Survey (HiPS)

    Science.gov (United States)

    Fernique, P.; Boch, T.; Pineau, F.; Oberto, A.

    2014-05-01

    Since 2009, the CDS promotes a method for visualizing based on the HEALPix sky tessellation. This method, called “Hierarchical Progressive Survey" or HiPS, allows one to display a survey progressively. It is particularly suited for all-sky surveys or deep fields. This visualization method is now integrated in several applications, notably Aladin, the SiTools/MIZAR CNES framework, and the recent HTML5 “Aladin Lite". Also, more than one hundred surveys are already available in this view mode. In this article, we will present the progress concerning this method and its recent adaptation to the astronomical catalogs such as the GAIA simulation.

  4. Understanding the unusual adsorption behavior in hierarchical zeolite nanosheets.

    Science.gov (United States)

    Bai, Peng; Olson, David H; Tsapatsis, Michael; Siepmann, J Ilja

    2014-08-04

    Hierarchical zeolites are advanced materials possessing the catalytic and adsorption properties of conventional zeolites while eliminating their transport limitations through the introduction of mesopores. Recent experiments comparing the adsorption in hierarchical self-pillared pentasils (SPP) and silicalite-1 (MFI) revealed an interesting crossover in sorbate loading for branched or long-chain alkanes but not for shorter linear alkanes, but an explanation for this behavior is not readily available through experimental probes due to the complications arising from the presence of multiple adsorption sites. Here we present a molecular simulation study on the adsorption of alkane isomers and show that a multi-step mechanism, found here for all molecules, is responsible for the observed phenomena. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Hierarchical supramolecules and organization using boronic acid building blocks.

    Science.gov (United States)

    Kubo, Yuji; Nishiyabu, Ryuhei; James, Tony D

    2015-02-07

    Current progress on hierarchical supramolecules using boronic acids has been highlighted in this feature article. Boronic acids can participate in "click reactions" with diols and their congeners with dynamic covalent functionality. By comprehensively exploring versatile sequential boronate esterification linkages between plural boronic acid-appended molecules and multiple hydroxyl counterparts, not only versatile supramolecular polymers but also structurally well-defined network nanostructures have been developed. In addition orthogonal interactions such as dative bonds of the boron center with Lewis bases have led to the formation of hierarchical nano/microstructures. Boronate systems have the potential to be used as materials for smart gels, chemosensors, active architectures for electronics, heterogeneous catalysts, chemical-stimulus responsive systems for drug delivery, etc. Here, we fully discuss the feasibility of the structure-directing ability of boronic acids from the standpoint of the generation of new smart materials.

  6. Hierarchical Structures in Hypertext Learning Environments

    NARCIS (Netherlands)

    Bezdan, Eniko; Kester, Liesbeth; Kirschner, Paul A.

    2011-01-01

    Bezdan, E., Kester, L., & Kirschner, P. A. (2011, 9 September). Hierarchical Structures in Hypertext Learning Environments. Presentation for the visit of KU Leuven, Open University, Heerlen, The Netherlands.

  7. HIERARCHICAL FRAGMENTATION OF THE ORION MOLECULAR FILAMENTS

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Satoko; Ho, Paul T. P.; Su, Yu-Nung [Academia Sinica Institute of Astronomy and Astrophysics, P.O. Box 23-141, Taipei 10617, Taiwan (China); Teixeira, Paula S. [Institut fuer Astrophysik, Universitaet Wien, Tuerkenschanzstrasse 17, A-1180, Wien (Austria); Zapata, Luis A., E-mail: satoko_t@asiaa.sinica.edu.tw [Centro de Radioastronomia y Astrofisica, Universidad Nacional Autonoma de Mexico, Morelia, Michoacan 58090 (Mexico)

    2013-01-20

    We present a high angular resolution map of the 850 {mu}m continuum emission of the Orion Molecular Cloud-3 (OMC 3) obtained with the Submillimeter Array (SMA); the map is a mosaic of 85 pointings covering an approximate area of 6.'5 Multiplication-Sign 2.'0 (0.88 Multiplication-Sign 0.27 pc). We detect 12 spatially resolved continuum sources, each with an H{sub 2} mass between 0.3-5.7 M {sub Sun} and a projected source size between 1400-8200 AU. All the detected sources are on the filamentary main ridge (n{sub H{sub 2}}{>=}10{sup 6} cm{sup -3}), and analysis based on the Jeans theorem suggests that they are most likely gravitationally unstable. Comparison of multi-wavelength data sets indicates that of the continuum sources, 6/12 (50%) are associated with molecular outflows, 8/12 (67%) are associated with infrared sources, and 3/12 (25%) are associated with ionized jets. The evolutionary status of these sources ranges from prestellar cores to protostar phase, confirming that OMC-3 is an active region with ongoing embedded star formation. We detect quasi-periodical separations between the OMC-3 sources of Almost-Equal-To 17''/0.035 pc. This spatial distribution is part of a large hierarchical structure that also includes fragmentation scales of giant molecular cloud ( Almost-Equal-To 35 pc), large-scale clumps ( Almost-Equal-To 1.3 pc), and small-scale clumps ( Almost-Equal-To 0.3 pc), suggesting that hierarchical fragmentation operates within the Orion A molecular cloud. The fragmentation spacings are roughly consistent with the thermal fragmentation length in large-scale clumps, while for small-scale cores it is smaller than the local fragmentation length. These smaller spacings observed with the SMA can be explained by either a helical magnetic field, cloud rotation, or/and global filament collapse. Finally, possible evidence for sequential fragmentation is suggested in the northern part of the OMC-3 filament.

  8. Is Echo a complex adaptive system?

    Science.gov (United States)

    Smith, R M; Bedau, M A

    2000-01-01

    We evaluate whether John Holland's Echo model exemplifies his theory of complex adaptive systems. After reviewing Holland's theory of complex adaptive systems and describing his Escho model, we describe and explain the characteristic evolutionary behavior observed in a series of Echo model runs. We conclude that Echo lacks the diversity of hierarchically organized aggregates that typify complex adaptive systems, and we explore possible explanations for this failure.

  9. Symptom structure of PTSD: support for a hierarchical model separating core PTSD symptoms from dysphoria

    NARCIS (Netherlands)

    Rademaker, A.R.; Minnen, A. van; Ebberink, F.; Zuiden, M. van; Geuze, E.

    2012-01-01

    Background: As of yet, no collective agreement has been reached regarding the precise factor structure of posttraumatic stress disorder (PTSD). Several alternative factor-models have been proposed in the last decades. Objective: The current study examined the fit of a hierarchical adaptation of the

  10. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios

    National Research Council Canada - National Science Library

    Petkova, Elisaveta P; Vink, Jan K; Horton, Radley M; Gasparrini, Antonio; Bader, Daniel A; Francis, Joe D; Kinney, Patrick L

    2017-01-01

    ...: The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound...

  11. Dynamic Organization of Hierarchical Memories.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2016-01-01

    In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a "dynamic categorization"; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity.

  12. Learning curve estimation in medical devices and procedures: hierarchical modeling.

    Science.gov (United States)

    Govindarajulu, Usha S; Stillo, Marco; Goldfarb, David; Matheny, Michael E; Resnic, Frederic S

    2017-07-30

    In the use of medical device procedures, learning effects have been shown to be a critical component of medical device safety surveillance. To support their estimation of these effects, we evaluated multiple methods for modeling these rates within a complex simulated dataset representing patients treated by physicians clustered within institutions. We employed unique modeling for the learning curves to incorporate the learning hierarchy between institution and physicians and then modeled them within established methods that work with hierarchical data such as generalized estimating equations (GEE) and generalized linear mixed effect models. We found that both methods performed well, but that the GEE may have some advantages over the generalized linear mixed effect models for ease of modeling and a substantially lower rate of model convergence failures. We then focused more on using GEE and performed a separate simulation to vary the shape of the learning curve as well as employed various smoothing methods to the plots. We concluded that while both hierarchical methods can be used with our mathematical modeling of the learning curve, the GEE tended to perform better across multiple simulated scenarios in order to accurately model the learning effect as a function of physician and hospital hierarchical data in the use of a novel medical device. We found that the choice of shape used to produce the 'learning-free' dataset would be dataset specific, while the choice of smoothing method was negligibly different from one another. This was an important application to understand how best to fit this unique learning curve function for hierarchical physician and hospital data. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Modeling place field activity with hierarchical slow feature analysis

    Directory of Open Access Journals (Sweden)

    Fabian eSchoenfeld

    2015-05-01

    Full Text Available In this paper we present six experimental studies from the literature on hippocampal place cells and replicate their main results in a computational framework based on the principle of slowness. Each of the chosen studies first allows rodents to develop stable place field activity and then examines a distinct property of the established spatial encoding, namely adaptation to cue relocation and removal; directional firing activity in the linear track and open field; and results of morphing and stretching the overall environment. To replicate these studies we employ a hierarchical Slow Feature Analysis (SFA network. SFA is an unsupervised learning algorithm extracting slowly varying information from a given stream of data, and hierarchical application of SFA allows for high dimensional input such as visual images to be processed efficiently and in a biologically plausible fashion. Training data for the network is produced in ratlab, a free basic graphics engine designed to quickly set up a wide range of 3D environments mimicking real life experimental studies, simulate a foraging rodent while recording its visual input, and training & sampling a hierarchical SFA network.

  14. A Review on the Fabrication of Hierarchical ZnO Nanostructures for Photocatalysis Application

    Directory of Open Access Journals (Sweden)

    Yi Xia

    2016-11-01

    Full Text Available Semiconductor photocatalysis provides potential solutions for many energy and environmental-related issues. Recently, various semiconductors with hierarchical nanostructures have been fabricated to achieve efficient photocatalysts owing to their multiple advantages, such as high surface area, porous structures, as well as enhanced light harvesting. ZnO has been widely investigated and considered as the most promising alternative photocatalyst to TiO2. Herein, we present a review on the fabrication methods, growth mechanisms and photocatalytic applications of hierarchical ZnO nanostructures. Various synthetic strategies and growth mechanisms, including multistep sequential growth routes, template-based synthesis, template-free self-organization and precursor or self-templating strategies, are highlighted. In addition, the fabrication of multicomponent ZnO-based nanocomposites with hierarchical structures is also included. Finally, the application of hierarchical ZnO nanostructures and nanocomposites in typical photocatalytic reactions, such as pollutant degradation and H2 evolution, is reviewed.

  15. E-Learning, Multiple Intelligences Theory (MI) and Learner-Centred Instruction: Adapting MI Learning Theoretical Principles to the Instruction of Health and Safety to Construction Managers

    Science.gov (United States)

    McNamee, Paul; Madden, Dave; McNamee, Frank; Wall, John; Hurst, Alan; Vrasidas, Charalambos; Chanquoy, Lucile; Baccino, Thierry; Acar, Emrah; Onwy-Yazici, Ela; Jordan, Ann

    2009-01-01

    This paper describes an ongoing EU project concerned with developing an instructional design framework for virtual classes (VC) that is based on the theory of Multiple Intelligences (MI) (1983). The psychological theory of Multiple Intelligences (Gardner 1983) has received much credence within instructional design since its inception and has been…

  16. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

    2014-01-01

    Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non-param...

  17. Discursive Hierarchical Patterning in Economics Cases

    Science.gov (United States)

    Lung, Jane

    2011-01-01

    This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

  18. A Model of Hierarchical Key Assignment Scheme

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhigang; ZHAO Jing; XU Maozhi

    2006-01-01

    A model of the hierarchical key assignment scheme is approached in this paper, which can be used with any cryptography algorithm. Besides, the optimal dynamic control property of a hierarchical key assignment scheme will be defined in this paper. Also, our scheme model will meet this property.

  19. How protein materials balance strength, robustness, and adaptability

    Science.gov (United States)

    Buehler, Markus J.; Yung, Yu Ching

    2010-01-01

    Proteins form the basis of a wide range of biological materials such as hair, skin, bone, spider silk, or cells, which play an important role in providing key functions to biological systems. The focus of this article is to discuss how protein materials are capable of balancing multiple, seemingly incompatible properties such as strength, robustness, and adaptability. To illustrate this, we review bottom-up materiomics studies focused on the mechanical behavior of protein materials at multiple scales, from nano to macro. We focus on alpha-helix based intermediate filament proteins as a model system to explain why the utilization of hierarchical structural features is vital to their ability to combine strength, robustness, and adaptability. Experimental studies demonstrating the activation of angiogenesis, the growth of new blood vessels, are presented as an example of how adaptability of structure in biological tissue is achieved through changes in gene expression that result in an altered material structure. We analyze the concepts in light of the universality and diversity of the structural makeup of protein materials and discuss the findings in the context of potential fundamental evolutionary principles that control their nanoscale structure. We conclude with a discussion of multiscale science in biology and de novo materials design. PMID:20676305

  20. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  1. Galaxy formation through hierarchical clustering

    Science.gov (United States)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  2. Groups possessing extensive hierarchical decompositions

    CERN Document Server

    Januszkiewicz, T; Leary, I J

    2009-01-01

    Kropholler's class of groups is the smallest class of groups which contains all finite groups and is closed under the following operator: whenever $G$ admits a finite-dimensional contractible $G$-CW-complex in which all stabilizer groups are in the class, then $G$ is itself in the class. Kropholler's class admits a hierarchical structure, i.e., a natural filtration indexed by the ordinals. For example, stage 0 of the hierarchy is the class of all finite groups, and stage 1 contains all groups of finite virtual cohomological dimension. We show that for each countable ordinal $\\alpha$, there is a countable group that is in Kropholler's class which does not appear until the $\\alpha+1$st stage of the hierarchy. Previously this was known only for $\\alpha= 0$, 1 and 2. The groups that we construct contain torsion. We also review the construction of a torsion-free group that lies in the third stage of the hierarchy.

  3. Quantum transport through hierarchical structures.

    Science.gov (United States)

    Boettcher, S; Varghese, C; Novotny, M A

    2011-04-01

    The transport of quantum electrons through hierarchical lattices is of interest because such lattices have some properties of both regular lattices and random systems. We calculate the electron transmission as a function of energy in the tight-binding approximation for two related Hanoi networks. HN3 is a Hanoi network with every site having three bonds. HN5 has additional bonds added to HN3 to make the average number of bonds per site equal to five. We present a renormalization group approach to solve the matrix equation involved in this quantum transport calculation. We observe band gaps in HN3, while no such band gaps are observed in linear networks or in HN5. We provide a detailed scaling analysis near the edges of these band gaps.

  4. Hierarchical networks of scientific journals

    CERN Document Server

    Palla, Gergely; Mones, Enys; Pollner, Péter; Vicsek, Tamás

    2015-01-01

    Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied ...

  5. Multicollinearity in hierarchical linear models.

    Science.gov (United States)

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model.

  6. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

    Energy Technology Data Exchange (ETDEWEB)

    Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

    2016-04-01

    In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  7. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  8. Hierarchical Identity-Based Lossy Trapdoor Functions

    CERN Document Server

    Escala, Alex; Libert, Benoit; Rafols, Carla

    2012-01-01

    Lossy trapdoor functions, introduced by Peikert and Waters (STOC'08), have received a lot of attention in the last years, because of their wide range of applications in theoretical cryptography. The notion has been recently extended to the identity-based scenario by Bellare et al. (Eurocrypt'12). We provide one more step in this direction, by considering the notion of hierarchical identity-based lossy trapdoor functions (HIB-LTDFs). Hierarchical identity-based cryptography generalizes identitybased cryptography in the sense that identities are organized in a hierarchical way; a parent identity has more power than its descendants, because it can generate valid secret keys for them. Hierarchical identity-based cryptography has been proved very useful both for practical applications and to establish theoretical relations with other cryptographic primitives. In order to realize HIB-LTDFs, we first build a weakly secure hierarchical predicate encryption scheme. This scheme, which may be of independent interest, is...

  9. Adaptive versus maladaptive coping and beliefs and their relation to chronic pain adjustment.

    Science.gov (United States)

    Tan, Gabriel; Teo, Irene; Anderson, Karen O; Jensen, Mark P

    2011-01-01

    Coping and beliefs are cornerstones to our understanding of adjustment to chronic pain. This study sought to test the hypothesis that maladaptive pain-related coping and beliefs are more strongly related to measures of patient adjustment than are adaptive coping and beliefs. A sample of 106 veterans with mixed chronic pain diagnoses in a multidisciplinary pain treatment program were administered measures of pain beliefs and pain coping, and composite scores were computed to reflect adaptive and maladaptive responses. Correlations between the composite scores and outcomes (pain intensity, pain interference, depression) were examined. Hierarchical multiple regressions were also conducted to estimate the independent contributions of adaptive and maladaptive responses. The maladaptive response composite score was found to be significantly related to pain interference and depression, whereas both adaptive and maladaptive response composite scores were found to be significantly related to pain intensity. The maladaptive response composite showed stronger independent associations with pain interference and depression after controlling for demographic variables, pain intensity, and adaptive responses. Contrary to expectations, only the adaptive response composite showed an independent association with pain intensity. The findings suggest that the relative importance of adaptive versus maladaptive beliefs and coping may differ as a function of the outcome domain in question. The findings support current cognitive-behavioral interventions that focus on reducing the frequency of maladaptive coping responses and beliefs as a way to improve patient functioning.

  10. Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

    DEFF Research Database (Denmark)

    He, W.; Min, D.D.; Zhang, X.D.

    2014-01-01

    Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...

  11. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    CERN Document Server

    Perotti, Juan Ignacio; Caldarelli, Guido

    2015-01-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical ...

  12. Hierarchical Interference Mitigation for Massive MIMO Cellular Networks

    Science.gov (United States)

    Liu, An; Lau, Vincent

    2014-09-01

    We propose a hierarchical interference mitigation scheme for massive MIMO cellular networks. The MIMO precoder at each base station (BS) is partitioned into an inner precoder and an outer precoder. The inner precoder controls the intra-cell interference and is adaptive to local channel state information (CSI) at each BS (CSIT). The outer precoder controls the inter-cell interference and is adaptive to channel statistics. Such hierarchical precoding structure reduces the number of pilot symbols required for CSI estimation in massive MIMO downlink and is robust to the backhaul latency. We study joint optimization of the outer precoders, the user selection, and the power allocation to maximize a general concave utility which has no closed-form expression. We first apply random matrix theory to obtain an approximated problem with closed-form objective. We show that the solution of the approximated problem is asymptotically optimal with respect to the original problem as the number of antennas per BS grows large. Then using the hidden convexity of the problem, we propose an iterative algorithm to find the optimal solution for the approximated problem. We also obtain a low complexity algorithm with provable convergence. Simulations show that the proposed design has significant gain over various state-of-the-art baselines.

  13. A hierarchical instrumental decision theory of nicotine dependence.

    Science.gov (United States)

    Hogarth, Lee; Troisi, Joseph R

    2015-01-01

    It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.

  14. Power margin improvement for OFDMA-PON using hierarchical modulation.

    Science.gov (United States)

    Cao, Pan; Hu, Xiaofeng; Zhuang, Zhiming; Zhang, Liang; Chang, Qingjiang; Yang, Qi; Hu, Rong; Su, Yikai

    2013-04-08

    We propose and experimentally demonstrate a hierarchical modulation scheme to improve power margin for orthogonal frequency division multiple access-passive optical networks (OFDMA-PONs). In a PON system, under the same launched optical power, optical network units (ONUs) have different power margins due to unequal distribution fiber lengths. The power margin of the PON system is determined by the ONU with the lowest power margin. In our proposed scheme, ONUs with long and short distribution fibers are grouped together, and downstream signals for the paired ONUs are mapped onto the same OFDM subcarriers using hierarchical modulation. In a pair of ONUs, part of the power margin of the ONU with short distribution fiber is re-allocated to the ONU with long distribution fiber. Therefore, the power margin of the ONU with the longest distribution fiber can be increased, leading to the power margin improvement of the PON system. Experimental results show that the hierarchical modulation scheme improves the power margin by 2.7 dB for an OFDMA-PON system, which can be used to support more users or extend transmission distance.

  15. Bayesian response-adaptive designs for basket trials.

    Science.gov (United States)

    Ventz, Steffen; Barry, William T; Parmigiani, Giovanni; Trippa, Lorenzo

    2017-02-17

    We develop a general class of response-adaptive Bayesian designs using hierarchical models, and provide open source software to implement them. Our work is motivated by recent master protocols in oncology, where several treatments are investigated simultaneously in one or multiple disease types, and treatment efficacy is expected to vary across biomarker-defined subpopulations. Adaptive trials such as I-SPY-2 (Barker et al., 2009) and BATTLE (Zhou et al., 2008) are special cases within our framework. We discuss the application of our adaptive scheme to two distinct research goals. The first is to identify a biomarker subpopulation for which a therapy shows evidence of treatment efficacy, and to exclude other subpopulations for which such evidence does not exist. This leads to a subpopulation-finding design. The second is to identify, within biomarker-defined subpopulations, a set of cancer types for which an experimental therapy is superior to the standard-of-care. This goal leads to a subpopulation-stratified design. Using simulations constructed to faithfully represent ongoing cancer sequencing projects, we quantify the potential gains of our proposed designs relative to conventional non-adaptive designs.

  16. Multiple arithmetic operations in a single neuron: the recruitment of adaptation processes in the cricket auditory pathway depends on sensory context.

    Science.gov (United States)

    Hildebrandt, K Jannis; Benda, Jan; Hennig, R Matthias

    2011-10-01

    Sensory pathways process behaviorally relevant signals in various contexts and therefore have to adapt to differing background conditions. Depending on changes in signal statistics, this adjustment might be a combination of two fundamental computational operations: subtractive adaptation shifting a neuron's threshold and divisive gain control scaling its sensitivity. The cricket auditory system has to deal with highly stereotyped conspecific songs at low carrier frequencies, and likely much more variable predator signals at high frequencies. We proposed that due to the differences between the two signal classes, the operation that is implemented by adaptation depends on the carrier frequency. We aimed to identify the biophysical basis underlying the basic computational operations of subtraction and division. We performed in vivo intracellular and extracellular recordings in a first-order auditory interneuron (AN2) that is active in both mate recognition and predator avoidance. We demonstrated subtractive shifts at the carrier frequency of conspecific songs and division at the predator-like carrier frequency. Combined application of current injection and acoustic stimuli for each cell allowed us to demonstrate the subtractive effect of cell-intrinsic adaptation currents. Pharmacological manipulation enabled us to demonstrate that presynaptic inhibition is most likely the source of divisive gain control. We showed that adjustment to the sensory context can depend on the class of signals that are relevant to the animal. We further revealed that presynaptic inhibition is a simple mechanism for divisive operations. Unlike other proposed mechanisms, it is widely available in the sensory periphery of both vertebrates and invertebrates.

  17. Neuromuscular adaptations to long-term progressive resistance training translates to improved functional capacity for people with multiple sclerosis and is maintained at follow-up

    DEFF Research Database (Denmark)

    Kjølhede, Tue; Vissing, Kristian; de Place, Line;

    2015-01-01

    BACKGROUND: Progressive resistance training (PRT) is acknowledged to effectively improve muscle strength for people with multiple sclerosis (PwMS), but diverging results exist regarding whether such improvements translates to improved functional capacity, possibly relating to insufficient duration...

  18. Towards More Comprehensive Projections of Urban Heat-Related Mortality: Estimates for New York City Under Multiple Population, Adaptation, and Climate Scenarios

    Science.gov (United States)

    Petkova, Elisaveta P.; Vink, Jan K.; Horton, Radley M.; Gasparrini, Antonio; Bader, Daniel A.; Francis, Joe D.; Kinney, Patrick L.

    2016-01-01

    High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information necessary to formulate hypotheses about population sensitivity to high temperatures and future demographics. This study has derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on future health burdens. We adopt a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projects heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporate a range of new scenarios for population change until the end of the 21st century. We then estimate future heat-related deaths in New York City by combining the changing temperature-mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs).The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3331 in the 2080s compared to 638 heat-related deaths annually between 2000 and 2006.These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York, and highlight the importance of both demographic change and adaptation responses in modifying future risks.

  19. Understanding pitch perception as a hierarchical process with top-down modulation.

    Directory of Open Access Journals (Sweden)

    Emili Balaguer-Ballester

    2009-03-01

    Full Text Available Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing.

  20. EMIR: a configurable hierarchical system for event monitoring and incident response

    Science.gov (United States)

    Deich, William T. S.

    2014-07-01

    The Event Monitor and Incident Response system (emir) is a flexible, general-purpose system for monitoring and responding to all aspects of instrument, telescope, and general facility operations, and has been in use at the Automated Planet Finder telescope for two years. Responses to problems can include both passive actions (e.g. generating alerts) and active actions (e.g. modifying system settings). Emir includes a monitor-and-response daemon, plus graphical user interfaces and text-based clients that automatically configure themselves from data supplied at runtime by the daemon. The daemon is driven by a configuration file that describes each condition to be monitored, the actions to take when the condition is triggered, and how the conditions are aggregated into hierarchical groups of conditions. Emir has been implemented for the Keck Task Library (KTL) keyword-based systems used at Keck and Lick Observatories, but can be readily adapted to many event-driven architectures. This paper discusses the design and implementation of Emir , and the challenges in balancing the competing demands for simplicity, flexibility, power, and extensibility. Emir 's design lends itself well to multiple purposes, and in addition to its core monitor and response functions, it provides an effective framework for computing running statistics, aggregate values, and summary state values from the primitive state data generated by other subsystems, and even for creating quick-and-dirty control loops for simple systems.

  1. Bayesian hierarchical modeling for detecting safety signals in clinical trials.

    Science.gov (United States)

    Xia, H Amy; Ma, Haijun; Carlin, Bradley P

    2011-09-01

    Detection of safety signals from clinical trial adverse event data is critical in drug development, but carries a challenging statistical multiplicity problem. Bayesian hierarchical mixture modeling is appealing for its ability to borrow strength across subgroups in the data, as well as moderate extreme findings most likely due merely to chance. We implement such a model for subject incidence (Berry and Berry, 2004 ) using a binomial likelihood, and extend it to subject-year adjusted incidence rate estimation under a Poisson likelihood. We use simulation to choose a signal detection threshold, and illustrate some effective graphics for displaying the flagged signals.

  2. Hierarchical clustering techniques for image database organization and summarization

    Science.gov (United States)

    Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    This paper investigates clustering techniques as a method of organizing image databases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglomerative clustering techniques are studied as a method of organizing features space as well as summarizing image groups by the selection of a few appropriate representatives. Retrieval performance using both single and multiple level hierarchies are experimented with and the algorithms show an interesting relationship between the top k correct retrievals and the number of comparisons required. Some arguments are given to support the use of such cluster-based techniques for managing distributed image databases.

  3. Hierarchical Non-linear Image Registration Integrating Deformable Segmentation

    Institute of Scientific and Technical Information of China (English)

    RAN Xin; QI Fei-hu

    2005-01-01

    A hierarchical non-linear method for image registration was presented, which integrates image segmentation and registration under a variational framework. An improved deformable model is used to simultaneously segment and register feature from multiple images. The objects in the image pair are segmented by evolving a single contour and meanwhile the parameters of affine registration transformation are found out. After that, a contour-constrained elastic registration is applied to register the images correctly. The experimental results indicate that the proposed approach is effective to segment and register medical images.

  4. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

    Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

    2015-01-01

    The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

  5. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    Science.gov (United States)

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  6. Final Report of Optimization Algorithms for Hierarchical Problems, with Applications to Nanoporous Materials

    Energy Technology Data Exchange (ETDEWEB)

    Nash, Stephen G.

    2013-11-11

    The research focuses on the modeling and optimization of nanoporous materials. In systems with hierarchical structure that we consider, the physics changes as the scale of the problem is reduced and it can be important to account for physics at the fine level to obtain accurate approximations at coarser levels. For example, nanoporous materials hold promise for energy production and storage. A significant issue is the fabrication of channels within these materials to allow rapid diffusion through the material. One goal of our research is to apply optimization methods to the design of nanoporous materials. Such problems are large and challenging, with hierarchical structure that we believe can be exploited, and with a large range of important scales, down to atomistic. This requires research on large-scale optimization for systems that exhibit different physics at different scales, and the development of algorithms applicable to designing nanoporous materials for many important applications in energy production, storage, distribution, and use. Our research has two major research thrusts. The first is hierarchical modeling. We plan to develop and study hierarchical optimization models for nanoporous materials. The models have hierarchical structure, and attempt to balance the conflicting aims of model fidelity and computational tractability. In addition, we analyze the general hierarchical model, as well as the specific application models, to determine their properties, particularly those properties that are relevant to the hierarchical optimization algorithms. The second thrust was to develop, analyze, and implement a class of hierarchical optimization algorithms, and apply them to the hierarchical models we have developed. We adapted and extended the optimization-based multigrid algorithms of Lewis and Nash to the optimization models exemplified by the hierarchical optimization model. This class of multigrid algorithms has been shown to be a powerful tool for

  7. Closed testing procedure for multiplicity control. An application on oxidative stress parameters in Hashimoto's Thyroiditis

    Directory of Open Access Journals (Sweden)

    Angela Alibrandi

    2017-03-01

    Full Text Available Closed Testing procedures represent an effective solution to the need to make inferences on multiple aspects at the same time, controlling the Familywise Error Rate (FWER, that is the error rate of the hierarchical family. Closed Testing procedures have a high degree of adaptability to a wide range of experimental situations, both in parametric than in non-parametric ambit. The attention is focused on the  Bonferroni-Holm method, frequently used to counteract the problem of multiple comparisons. The present paper aims to show an original application of the Closed Testing procedures for multiplicity control in medical research, with reference to the oxidative stress; in particular the Min-P Bonferrroni-Holm method was applied to the p-value adjustment, related to three parameters (BAP, D-ROMS, AGEs of oxidative stress in Hashimoto’s thyroidytis.

  8. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong

    2017-08-03

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

  9. A Model for Slicing JAVA Programs Hierarchically

    Institute of Scientific and Technical Information of China (English)

    Bi-Xin Li; Xiao-Cong Fan; Jun Pang; Jian-Jun Zhao

    2004-01-01

    Program slicing can be effectively used to debug, test, analyze, understand and maintain objectoriented software. In this paper, a new slicing model is proposed to slice Java programs based on their inherent hierarchical feature. The main idea of hierarchical slicing is to slice programs in a stepwise way, from package level, to class level, method level, and finally up to statement level. The stepwise slicing algorithm and the related graph reachability algorithms are presented, the architecture of the Java program Analyzing Tool (JATO) based on hierarchical slicing model is provided, the applications and a small case study are also discussed.

  10. Hierarchical analysis of acceptable use policies

    Directory of Open Access Journals (Sweden)

    P. A. Laughton

    2008-01-01

    Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

  11. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  12. Two new Bent-toed Geckos of the Cyrtodactylus pulchellus complex from Peninsular Malaysia and multiple instances of convergent adaptation to limestone forest ecosystems.

    Science.gov (United States)

    Grismer, L Lee; Wood, Perry L; Anuar, Shahrul; Grismer, Marta S; Quah, Evan S H; Murdoch, Matthew L; Muin, Mohd Abdul; Davis, Hayden R; Aguilar, César; Klabacka, Randy; Cobos, Anthony J; Aowphol, Anchalee; Sites, Jack W

    2016-04-25

    A new species of limestone cave-adapted gecko of the Cyrtodactylus pulchellus complex, C. hidupselamanya sp. nov., is described from an isolated karst formation at Felda Chiku 7, Kelantan, Peninsular Malaysia. This formation is scheduled to be completely quarried for its mineral content. From what we know about the life history of C. hidupselamanya sp. nov., this will result in its extinction. A new limestone forest-adapted species, C. lenggongensis sp. nov., from the Lenggong Valley, Perak was previously considered to be conspecific with C. bintangrendah but a re-evaluation of morphological, color pattern, molecular, and habitat preference indicates that it too is a unique lineage worthy of specific recognition. Fortunately C. lenggongensis sp. nov. is not facing extinction because its habitat is protected by the UNESCO Archaeological Heritage of the Lenggong Valley due to the archaeological significance of that region. Both new species can be distinguished from all other species of Cyrtodactylus based on molecular evidence from the mitochondrial gene ND2 and its flanking tRNAs as well as having unique combinations of morphological and color pattern characteristics. Using a time-calibrated BEAST analysis we inferred that the evolution of a limestone habitat preference and its apparently attendant morphological and color pattern adaptations evolved independently at least four times in the C. pulchellus complex between 26.1 and 0.78 mya.

  13. Hierarchical Representation of Time-Varying Volume Data with Fourth-Root-of-Two Subdivision and Quadrilinear B-Spline Wavelets

    Energy Technology Data Exchange (ETDEWEB)

    Linsen, L; Pascucci, V; Duchaineau, M A; Hamann, B; Joy, K I

    2002-11-19

    Multiresolution methods for representing data at multiple levels of detail are widely used for large-scale two- and three-dimensional data sets. We present a four-dimensional multiresolution approach for time-varying volume data. This approach supports a hierarchy with spatial and temporal scalability. The hierarchical data organization is based on 4{radical}2 subdivision. The n{radical}2-subdivision scheme only doubles the overall number of grid points in each subdivision step. This fact leads to fine granularity and high adaptivity, which is especially desirable in the spatial dimensions. For high-quality data approximation on each level of detail, we use quadrilinear B-spline wavelets. We present a linear B-spline wavelet lighting scheme based on n{radical}2 subdivision to obtain narrow masks for the update rules. Narrow masks provide a basis for out-of-core data exploration techniques and view-dependent visualization of sequences of time steps.

  14. Glatiramer Acetate in Treatment of Multiple Sclerosis: A Toolbox of Random Co-Polymers for Targeting Inflammatory Mechanisms of both the Innate and Adaptive Immune System?

    Directory of Open Access Journals (Sweden)

    Thomas Vorup-Jensen

    2012-11-01

    Full Text Available Multiple sclerosis is a disease of the central nervous system, resulting in the demyelination of neurons, causing mild to severe symptoms. Several anti-inflammatory treatments now play a significant role in ameliorating the disease. Glatiramer acetate (GA is a formulation of random polypeptide copolymers for the treatment of relapsing-remitting MS by limiting the frequency of attacks. While evidence suggests the influence of GA on inflammatory responses, the targeted molecular mechanisms remain poorly understood. Here, we review the multiple pharmacological modes-of-actions of glatiramer acetate in treatment of multiple sclerosis. We discuss in particular a newly discovered interaction between the leukocyte-expressed integrin αMβ2 (also called Mac-1, complement receptor 3, or CD11b/CD18 and perspectives on the GA co-polymers as an influence on the function of the innate immune system.

  15. Image meshing via hierarchical optimization

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONG‡

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., defi nition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to fi nd a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to fi nd a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to fi ner ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  16. Image meshing via hierarchical optimization*

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONGS

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., definition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to find a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to find a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to finer ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  17. Hierarchical Bayes Ensemble Kalman Filtering

    CERN Document Server

    Tsyrulnikov, Michael

    2015-01-01

    Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...

  18. Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling

    Science.gov (United States)

    Wei Wu; James Clark; James Vose

    2010-01-01

    Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model – GR4J – by coherently assimilating the uncertainties from the...

  19. Augmenting Visual Analysis in Single-Case Research with Hierarchical Linear Modeling

    Science.gov (United States)

    Davis, Dawn H.; Gagne, Phill; Fredrick, Laura D.; Alberto, Paul A.; Waugh, Rebecca E.; Haardorfer, Regine

    2013-01-01

    The purpose of this article is to demonstrate how hierarchical linear modeling (HLM) can be used to enhance visual analysis of single-case research (SCR) designs. First, the authors demonstrated the use of growth modeling via HLM to augment visual analysis of a sophisticated single-case study. Data were used from a delayed multiple baseline…

  20. A Real-Time PCR Array for Hierarchical Identification of Francisella Isolates

    NARCIS (Netherlands)

    Svensson, Kerstin; Granberg, Malin; Karlsson, Linda; Neubauerova, Vera; Forsman, Mats; Johansson, Anders

    2009-01-01

    A robust, rapid and flexible real-time PCR assay for hierarchical genetic typing of clinical and environmental isolates of Francisella is presented. Typing markers were found by multiple genome and gene comparisons, from which 23 canonical single nucleotide polymorphisms (canSNPs) and 11 canonical i

  1. Single photon in hierarchical architecture for physical reinforcement learning: Photon intelligence

    CERN Document Server

    Naruse, Makoto; Drezet, Aurélien; Huant, Serge; Hori, Hirokazu; Kim, Song-Ju

    2016-01-01

    Understanding and using natural processes for intelligent functionalities, referred to as natural intelligence, has recently attracted interest from a variety of fields, including post-silicon computing for artificial intelligence and decision making in the behavioural sciences. In a past study, we successfully used the wave-particle duality of single photons to solve the two-armed bandit problem, which constitutes the foundation of reinforcement learning and decision making. In this study, we propose and confirm a hierarchical architecture for single-photon-based reinforcement learning and decision making that verifies the scalability of the principle. Specifically, the four-armed bandit problem is solved given zero prior knowledge in a two-layer hierarchical architecture, where polarization is autonomously adapted in order to effect adequate decision making using single-photon measurements. In the hierarchical structure, the notion of layer-dependent decisions emerges. The optimal solutions in the coarse la...

  2. Hierarchical Route Optimization By Using Memetic Algorithm In A Mobile Networks

    Directory of Open Access Journals (Sweden)

    K .K. Gautam

    2011-02-01

    Full Text Available The networks Mobility (NEMO Protocol is a way of managing the mobility of an entire network, and mobile internet protocol is the basic solution for networks Mobility. A hierarchical route optimization system for mobile network is proposed to solve management of hierarchical route optimization problems. In present paper we study hierarchical Route Optimization scheme using memetic algorithm(HROSMA The concept of optimization- finding the extreme of a function that maps candidate ‘solution’ to scalar values of ‘quality’ – is an extremely general and useful idea. For solving this problem, we use a few salient adaptations, and we also extend HROSMA perform routing between the mobile networks.

  3. Fuzzy hierarchical model for risk assessment principles, concepts, and practical applications

    CERN Document Server

    Chan, Hing Kai

    2013-01-01

    Risk management is often complicated by situational uncertainties and the subjective preferences of decision makers. Fuzzy Hierarchical Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and quantitative criteria to tackle imprecise information.   This approach is illustrated through number of case studies using examples from the food, fashion and electronics sectors to cover a range of applications including supply chain management, green product design and green initiatives. These practical examples explore how this method can be adapted and fine tuned to fit other industries as well.   Supported by an extensive literature review, Fuzzy Hierarchical Model for Risk Assessment  comprehensively introduces a new method for project managers across all industries as well as researchers in risk management.

  4. Robust Real-Time Music Transcription with a Compositional Hierarchical Model

    Science.gov (United States)

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model’s structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model’s performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks. PMID:28046074

  5. An Automatic Hierarchical Delay Analysis Tool

    Institute of Scientific and Technical Information of China (English)

    FaridMheir-El-Saadi; BozenaKaminska

    1994-01-01

    The performance analysis of VLSI integrated circuits(ICs) with flat tools is slow and even sometimes impossible to complete.Some hierarchical tools have been developed to speed up the analysis of these large ICs.However,these hierarchical tools suffer from a poor interaction with the CAD database and poorly automatized operations.We introduce a general hierarchical framework for performance analysis to solve these problems.The circuit analysis is automatic under the proposed framework.Information that has been automatically abstracted in the hierarchy is kept in database properties along with the topological information.A limited software implementation of the framework,PREDICT,has also been developed to analyze the delay performance.Experimental results show that hierarchical analysis CPU time and memory requirements are low if heuristics are used during the abstraction process.

  6. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau

    2017-08-03

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures extending from the HNWs.

  7. Generation of hierarchically correlated multivariate symbolic sequences

    CERN Document Server

    Tumminello, Mi; Mantegna, R N

    2008-01-01

    We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering procedure as applied to an empirical matrix of Hamming distances. The algorithm can be interpreted as the finite alphabet equivalent of the recently introduced hierarchically nested factor model (M. Tumminello et al. EPL 78 (3) 30006 (2007)). The algorithm is based on a generating mechanism that is different from the one used in the mutation rate approach. We apply the proposed methodology for investigating the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny.

  8. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  9. HIERARCHICAL ORGANIZATION OF INFORMATION, IN RELATIONAL DATABASES

    Directory of Open Access Journals (Sweden)

    Demian Horia

    2008-05-01

    Full Text Available In this paper I will present different types of representation, of hierarchical information inside a relational database. I also will compare them to find the best organization for specific scenarios.

  10. Hierarchical Network Design Using Simulated Annealing

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Clausen, Jens

    2002-01-01

    The hierarchical network problem is the problem of finding the least cost network, with nodes divided into groups, edges connecting nodes in each groups and groups ordered in a hierarchy. The idea of hierarchical networks comes from telecommunication networks where hierarchies exist. Hierarchical...... networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

  11. When to Use Hierarchical Linear Modeling

    National Research Council Canada - National Science Library

    Veronika Huta

    2014-01-01

    Previous publications on hierarchical linear modeling (HLM) have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis...

  12. An introduction to hierarchical linear modeling

    National Research Council Canada - National Science Library

    Woltman, Heather; Feldstain, Andrea; MacKay, J. Christine; Rocchi, Meredith

    2012-01-01

    This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis...

  13. Conservation Laws in the Hierarchical Model

    NARCIS (Netherlands)

    Beijeren, H. van; Gallavotti, G.; Knops, H.

    1974-01-01

    An exposition of the renormalization-group equations for the hierarchical model is given. Attention is drawn to some properties of the spin distribution functions which are conserved under the action of the renormalization group.

  14. αB-crystallin is a target for adaptive immune responses and a trigger of innate responses in preactive multiple sclerosis lesions

    NARCIS (Netherlands)

    Noort, J.M. van; Bsibsi, M.; Gerritsen, W.H.; Valk, P. van der; Bajramovic, J.J.; Steinman, L.; Amor, S.

    2010-01-01

    We present the first comparative analysis of serum immunoglobulinG reactivity profiles against the full spectrum of human myelin-associated proteins in multiple sclerosis patients and healthy control subjects. In both groups, serum antibodies display a consistent and prominent reaction to αB-crystal

  15. Parental distress, parenting practices, and child adaptive outcomes following traumatic brain injury.

    Science.gov (United States)

    Micklewright, Jackie L; King, Tricia Z; O'Toole, Kathleen; Henrich, Chris; Floyd, Frank J

    2012-03-01

    Moderate and severe pediatric traumatic brain injuries (TBI) are associated with significant familial distress and child adaptive sequelae. Our aim was to examine the relationship between parental psychological distress, parenting practices (authoritarian, permissive, authoritative), and child adaptive functioning 12-36 months following TBI or orthopedic injury (OI). Injury type was hypothesized to moderate the relationship between parental distress and child adaptive functioning, demonstrating a significantly stronger relationship in the TBI relative to OI group. Authoritarian parenting practices were hypothesized to mediate relationship between parental distress and child adaptive functioning across groups. Groups (TBI n = 21, OI n = 23) did not differ significantly on age at injury, time since injury, sex, race, or SES. Parents completed the Brief Symptom Inventory, Parenting Practices Questionnaire, and Vineland-II. Moderation and mediation hypotheses were tested using hierarchical multiple regression and a bootstrapping approach, respectively. Results supported moderation and revealed that higher parental psychological distress was associated with lower child adaptive functioning in the TBI group only. Mediation results indicated that higher parental distress was associated with authoritarian parenting practices and lower adaptive functioning across groups. Results suggest that parenting practices are an important area of focus for studies attempting to elucidate the relationship between parent and child functioning following TBI.

  16. A Hierarchical Multi-Unidimensional IRT Approach for Analyzing Sparse, Multi-Group Data for Integrative Data Analysis.

    Science.gov (United States)

    Huo, Yan; de la Torre, Jimmy; Mun, Eun-Young; Kim, Su-Young; Ray, Anne E; Jiao, Yang; White, Helene R

    2015-09-01

    The present paper proposes a hierarchical, multi-unidimensional two-parameter logistic item response theory (2PL-MUIRT) model extended for a large number of groups. The proposed model was motivated by a large-scale integrative data analysis (IDA) study which combined data (N = 24,336) from 24 independent alcohol intervention studies. IDA projects face unique challenges that are different from those encountered in individual studies, such as the need to establish a common scoring metric across studies and to handle missingness in the pooled data. To address these challenges, we developed a Markov chain Monte Carlo (MCMC) algorithm for a hierarchical 2PL-MUIRT model for multiple groups in which not only were the item parameters and latent traits estimated, but the means and covariance structures for multiple dimensions were also estimated across different groups. Compared to a few existing MCMC algorithms for multidimensional IRT models that constrain the item parameters to facilitate estimation of the covariance matrix, we adapted an MCMC algorithm so that we could directly estimate the correlation matrix for the anchor group without any constraints on the item parameters. The feasibility of the MCMC algorithm and the validity of the basic calibration procedure were examined using a simulation study. Results showed that model parameters could be adequately recovered, and estimated latent trait scores closely approximated true latent trait scores. The algorithm was then applied to analyze real data (69 items across 20 studies for 22,608 participants). The posterior predictive model check showed that the model fit all items well, and the correlations between the MCMC scores and original scores were overall quite high. An additional simulation study demonstrated robustness of the MCMC procedures in the context of the high proportion of missingness in data. The Bayesian hierarchical IRT model using the MCMC algorithms developed in the current study has the potential to

  17. Fast and Adaptive Bidimensional Empirical Mode Decomposition Using Order-Statistics Filter Based Envelope Estimation

    Directory of Open Access Journals (Sweden)

    Jesmin F. Khan

    2008-08-01

    Full Text Available A novel approach for bidimensional empirical mode decomposition (BEMD is proposed in this paper. BEMD decomposes an image into multiple hierarchical components known as bidimensional intrinsic mode functions (BIMFs. In each iteration of the process, two-dimensional (2D interpolation is applied to a set of local maxima (minima points to form the upper (lower envelope. But, 2D scattered data interpolation methods cause huge computation time and other artifacts in the decomposition. This paper suggests a simple, but effective, method of envelope estimation that replaces the surface interpolation. In this method, order statistics filters are used to get the upper and lower envelopes, where filter size is derived from the data. Based on the properties of the proposed approach, it is considered as fast and adaptive BEMD (FABEMD. Simulation results demonstrate that FABEMD is not only faster and adaptive, but also outperforms the original BEMD in terms of the quality of the BIMFs.

  18. Hierarchical organization versus self-organization

    OpenAIRE

    Busseniers, Evo

    2014-01-01

    In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

  19. Hierarchical decision making for flood risk reduction

    DEFF Research Database (Denmark)

    Custer, Rocco; Nishijima, Kazuyoshi

    2013-01-01

    . In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...

  20. Hierarchical self-organization of tectonic plates

    OpenAIRE

    2010-01-01

    The Earth's surface is subdivided into eight large tectonic plates and many smaller ones. We reconstruct the plate tessellation history and demonstrate that both large and small plates display two distinct hierarchical patterns, described by different power-law size-relationships. While small plates display little organisational change through time, the structure of the large plates oscillate between minimum and maximum hierarchical tessellations. The organization of large plates rapidly chan...