A hierarchical spatial framework for forest landscape planning.

Science.gov (United States)

Pete Bettinger; Marie Lennette; K. Norman Johnson; Thomas A. Spies

2005-01-01

A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian...

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-01-01

matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p

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.

Gas generation matrix depletion quality assurance project plan

International Nuclear Information System (INIS)

1998-01-01

The Los Alamos National Laboratory (LANL) is to provide the necessary expertise, experience, equipment and instrumentation, and management structure to: Conduct the matrix depletion experiments using simulated waste for quantifying matrix depletion effects; and Conduct experiments on 60 cylinders containing simulated TRU waste to determine the effects of matrix depletion on gas generation for transportation. All work for the Gas Generation Matrix Depletion (GGMD) experiment is performed according to the quality objectives established in the test plan and under this Quality Assurance Project Plan (QAPjP)

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-26

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-24

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\mathcal{H}$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Decision support in hierarchical planning systems: The case of procurement planning in oil refining industries

DEFF Research Database (Denmark)

Kallestrup, Kasper Bislev; Lynge, Lasse Hadberg; Akkerman, Renzo

2014-01-01

In this paper, we discuss the development of decision support systems for hierarchically structured planning approaches, such as commercially available advanced planning systems. We develop a framework to show how such a decision support system can be designed with the existing organization in mind...... and from the perspective of the organizational aspects involved. To exemplify and develop our framework, we use a case study of crude oil procurement planning in the refining industry. The results of the case study indicate an improved organizational embedding of the DSS, leading to significant savings...... in terms of planning efforts and procurement costs. In general, our framework aims to support the continuous improvement of advanced planning systems, increasing planning quality in complex supply chain settings....

Hierarchical spatial segregation of two Mediterranean vole species: the role of patch-network structure and matrix composition.

Science.gov (United States)

Pita, Ricardo; Lambin, Xavier; Mira, António; Beja, Pedro

2016-09-01

According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e., many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from within-patches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.

Parallel hierarchical radiosity rendering

Energy Technology Data Exchange (ETDEWEB)

Carter, Michael [Iowa State Univ., Ames, IA (United States)

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.

Statistical dynamics of ultradiffusion in hierarchical systems

International Nuclear Information System (INIS)

Gardner, S.

1987-01-01

In many types of disordered systems which exhibit frustration and competition, an ultrametric topology is found to exist in the space of allowable states. This ultrametric topology of states is associated with a hierarchical relaxation process called ultradiffusion. Ultradiffusion occurs in hierarchical non-linear (HNL) dynamical systems when constraints cause large scale, slow modes of motion to be subordinated to small scale, fast modes. Examples of ultradiffusion are found throughout condensed matter physics and critical phenomena (e.g. the states of spin glasses), in biophysics (e.g. the states of Hopfield networks) and in many other fields including layered computing based upon nonlinear dynamics. The statistical dynamics of ultradiffusion can be treated as a random walk on an ultrametric space. For reversible bifurcating ultrametric spaces the evolution equation governing the probability of a particle being found at site i at time t has a highly degenerate transition matrix. This transition matrix has a fractal geometry similar to the replica form proposed for spin glasses. The authors invert this fractal matrix using a recursive quad-tree (QT) method. Possible applications of hierarchical systems to communications and symbolic computing are discussed briefly

Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

Science.gov (United States)

Fu, QiMing

2016-01-01

To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

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 ...

Technique for fast and efficient hierarchical clustering

Science.gov (United States)

Stork, Christopher

2013-10-08

A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

Science.gov (United States)

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies

Robust and scalable hierarchical matrix-based fast direct solver and preconditioner for the numerical solution of elliptic partial differential equations

KAUST Repository

Chavez Chavez, Gustavo Ivan

2017-01-01

Numerical experiments corroborate the robustness, accuracy, and complexity claims and provide a baseline of the performance and memory footprint by comparisons with competing approaches such as the multigrid solver hypre, and the STRUMPACK implementation of the multifrontal factorization with hierarchically semi-separable matrices. The companion implementation can utilize many thousands of cores of Shaheen, KAUST's Haswell-based Cray XC-40 supercomputer, and compares favorably with other implementations of hierarchical solvers in terms of time-to-solution and memory consumption.

Novel nitrogen-doped hierarchically porous coralloid carbon materials as host matrixes for lithium–sulfur batteries

International Nuclear Information System (INIS)

Yang, Jing; Wang, Shuyuan; Ma, Zhipeng; Du, Zhiling; Li, Chunying; Song, Jianjun; Wang, Guiling; Shao, Guangjie

2015-01-01

Highlights: • Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites were prepared • Nitrogen atoms were introduced to improve electrochemical properties • The intriguing structural features benefited discharge capacity and cycling stability - Abstract: Nitrogen-doped hierarchically porous coralloid carbon/sulfur composites (N-HPCC/S) served as attractive cathode materials for lithium–sulfur (Li–S) batteries were fabricated for the first time. The nitrogen-doped hierarchically porous coralloid carbon (N-HPCC) with an appropriate nitrogen content (1.29 wt%) was synthesized via a facile hydrothermal approach, combined with subsequent carbonization–activation. The N-HPCC/S composites prepared by a simple melt–diffusion method displayed an excellent electrochemical performance. With a high sulfur content (58 wt%) in the total electrode weight, the N-HPCC/S cathode delivered a high initial discharge capacity of 1626.8 mA h g −1 and remained high up to 1086.3 mA h g −1 after 50 cycles at 100 mA g −1 , which is about 1.86 times as that of activated carbon. Particularly, the reversible discharge capacity still maintained 607.2 mA h g −1 after 200 cycles even at a higher rate of 800 mA g −1 . The enhanced electrochemical performance was attributed to the synergetic effect between the intriguing hierarchically porous coralloid structure and appropriate nitrogen doping, which could effectively trap polysulfides, alleviate the volume expansion, enhance the electronic conductivity and improve the surface interaction between the carbon matrix and polysulfides

Novel hierarchically porous carbon materials obtained from natural biopolymer as host matrixes for lithium-sulfur battery applications.

Science.gov (United States)

Zhang, Bin; Xiao, Min; Wang, Shuanjin; Han, Dongmei; Song, Shuqin; Chen, Guohua; Meng, Yuezhong

2014-08-13

Novel hierarchically porous carbon materials with very high surface areas, large pore volumes and high electron conductivities were prepared from silk cocoon by carbonization with KOH activation. The prepared novel porous carbon-encapsulated sulfur composites were fabricated by a simple melting process and used as cathodes for lithium sulfur batteries. Because of the large surface area and hierarchically porous structure of the carbon material, soluble polysulfide intermediates can be trapped within the cathode and the volume expansion can be alleviated effectively. Moreover, the electron transport properties of the carbon materials can provide an electron conductive network and promote the utilization rate of sulfur in cathode. The prepared carbon-sulfur composite exhibited a high specific capacity and excellent cycle stability. The results show a high initial discharge capacity of 1443 mAh g(-1) and retain 804 mAh g(-1) after 80 discharge/charge cycles at a rate of 0.5 C. A Coulombic efficiency retained up to 92% after 80 cycles. The prepared hierarchically porous carbon materials were proven to be an effective host matrix for sulfur encapsulation to improve the sulfur utilization rate and restrain the dissolution of polysulfides into lithium-sulfur battery electrolytes.

Multi person detection and tracking based on hierarchical level-set method

Science.gov (United States)

Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

2018-04-01

In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

OD Matrix Acquisition Based on Mobile Phone Positioning Data

Directory of Open Access Journals (Sweden)

Xiaoqing ZUO

2014-06-01

Full Text Available Dynamic OD matrix is basic data of traffic travel guidance, traffic control, traffic management and traffic planning, and reflects the basic needs of travelers on the traffic network. With the rising popularity of positioning technology and the communication technology and the generation of huge mobile phone users, the mining and use of mobile phone positioning data, can get more traffic intersections and import and export data. These data will be integrated into obtaining the regional OD matrix, which is bound to bring convenience. In this article, mobile phone positioning data used in the data acquisition of intelligent transportation system, research a kind of regional dynamic OD matrix acquisition method based on the mobile phone positioning data. The method based on purpose of transportation, using time series similarity classification algorithm based on piecewise linear representation of the corner point (CP-PLR, mapping each base station cell to traffic zone of different traffic characteristics, and through a series of mapping optimization of base station cell to traffic zone to realize city traffic zone division based on mobile phone traffic data, on the basis, adjacency matrix chosen as the physical data structure of OD matrix storage, the principle of obtaining regional dynamic OD matrix based on the mobile phone positioning data are expounded, and the algorithm of obtaining regional dynamic OD matrix based on mobile phone positioning data are designed and verified.

Multiscale experimental mechanics of hierarchical carbon-based materials.

Science.gov (United States)

Espinosa, Horacio D; Filleter, Tobin; Naraghi, Mohammad

2012-06-05

Investigation of the mechanics of natural materials, such as spider silk, abalone shells, and bone, has provided great insight into the design of materials that can simultaneously achieve high specific strength and toughness. Research has shown that their emergent mechanical properties are owed in part to their specific self-organization in hierarchical molecular structures, from nanoscale to macroscale, as well as their mixing and bonding. To apply these findings to manmade materials, researchers have devoted significant efforts in developing a fundamental understanding of multiscale mechanics of materials and its application to the design of novel materials with superior mechanical performance. These efforts included the utilization of some of the most promising carbon-based nanomaterials, such as carbon nanotubes, carbon nanofibers, and graphene, together with a variety of matrix materials. At the core of these efforts lies the need to characterize material mechanical behavior across multiple length scales starting from nanoscale characterization of constituents and their interactions to emerging micro- and macroscale properties. In this report, progress made in experimental tools and methods currently used for material characterization across multiple length scales is reviewed, as well as a discussion of how they have impacted our current understanding of the mechanics of hierarchical carbon-based materials. In addition, insight is provided into strategies for bridging experiments across length scales, which are essential in establishing a multiscale characterization approach. While the focus of this progress report is in experimental methods, their concerted use with theoretical-computational approaches towards the establishment of a robust material by design methodology is also discussed, which can pave the way for the development of novel materials possessing unprecedented mechanical properties. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Page Layout Analysis of the Document Image Based on the Region Classification in a Decision Hierarchical Structure

Directory of Open Access Journals (Sweden)

Hossein Pourghassem

2010-10-01

Full Text Available The conversion of document image to its electronic version is a very important problem in the saving, searching and retrieval application in the official automation system. For this purpose, analysis of the document image is necessary. In this paper, a hierarchical classification structure based on a two-stage segmentation algorithm is proposed. In this structure, image is segmented using the proposed two-stage segmentation algorithm. Then, the type of the image regions such as document and non-document image is determined using multiple classifiers in the hierarchical classification structure. The proposed segmentation algorithm uses two algorithms based on wavelet transform and thresholding. Texture features such as correlation, homogeneity and entropy that extracted from co-occurrenc matrix and also two new features based on wavelet transform are used to classifiy and lable the regions of the image. The hierarchical classifier is consisted of two Multilayer Perceptron (MLP classifiers and a Support Vector Machine (SVM classifier. The proposed algorithm is evaluated on a database consisting of document and non-document images that provides from Internet. The experimental results show the efficiency of the proposed approach in the region segmentation and classification. The proposed algorithm provides accuracy rate of 97.5% on classification of the regions.

An Efficient, Hierarchical Viewpoint Planning Strategy for Terrestrial Laser Scanner Networks

Science.gov (United States)

Jia, F.; Lichti, D. D.

2018-05-01

Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the "optimality" of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a "brute force" search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the "brute force" strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.

Topology-based hierarchical scheduling using deficit round robin

DEFF Research Database (Denmark)

Yu, Hao; Yan, Ying; Berger, Michael Stubert

2009-01-01

according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

Hierarchical video summarization based on context clustering

Science.gov (United States)

Tseng, Belle L.; Smith, John R.

2003-11-01

A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

Priority-Based Hierarchical Operational Management for Multiagent-Based Microgrids

Directory of Open Access Journals (Sweden)

Takumi Kato

2014-03-01

Full Text Available Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters.

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...

Introduction into Hierarchical Matrices

KAUST Repository

Litvinenko, Alexander

2013-01-01

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.

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.

Runtime Concepts of Hierarchical Software Components

Czech Academy of Sciences Publication Activity Database

Bureš, Tomáš; Hnětynka, P.; Plášil, František

2007-01-01

Roč. 8, special (2007), s. 454-463 ISSN 1525-9293 R&D Projects: GA AV ČR 1ET400300504 Institutional research plan: CEZ:AV0Z10300504 Keywords : component-based development * hierarchical components * connectors * controlers * runtime environment Subject RIV: JC - Computer Hardware ; Software

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.

2017-09-07

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.; Keyes, David E.; Turkiyyah, George

2017-01-01

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

The effects of governance modes on the energy matrix of Andean countries

International Nuclear Information System (INIS)

Fontaine, Guillaume

2011-01-01

This article addresses the consequences of different modes of energy governance on the energy matrix. Energy governance is understood as a regulation system of the energy related interplays between the State, the society and the economy. The energy matrix is a useful instrument for comparative policy analysis, since it informs us about production and consumption trends, by sources and sectors. Our central argument is that energy governance follows two different patterns, one hierarchical and the other cooperative, that are not necessarily determined by the initial factors allocation, and produce different effects on the energy matrix. Hierarchical governance is based on centralized decision-making and State-centered development, while co-governance is based on decentralized decision-making and market-oriented development. To develop this argument, we compare the energy matrix from the five Andean countries (Venezuela, Colombia, Ecuador, Peru and Bolivia).

The effects of governance modes on the energy matrix of Andean countries

Energy Technology Data Exchange (ETDEWEB)

Fontaine, Guillaume, E-mail: gfontaine@flacso.org.e [Latin American Faculty for Social Sciences (FLACSO), Research Laboratory on Governance, Quito (Ecuador)

2011-05-15

This article addresses the consequences of different modes of energy governance on the energy matrix. Energy governance is understood as a regulation system of the energy related interplays between the State, the society and the economy. The energy matrix is a useful instrument for comparative policy analysis, since it informs us about production and consumption trends, by sources and sectors. Our central argument is that energy governance follows two different patterns, one hierarchical and the other cooperative, that are not necessarily determined by the initial factors allocation, and produce different effects on the energy matrix. Hierarchical governance is based on centralized decision-making and State-centered development, while co-governance is based on decentralized decision-making and market-oriented development. To develop this argument, we compare the energy matrix from the five Andean countries (Venezuela, Colombia, Ecuador, Peru and Bolivia).

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang; Wang, Jun; Vouga, Etienne; Wonka, Peter

2013-01-01

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.

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang

2013-11-06

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.

The Realized Hierarchical Archimedean Copula in Risk Modelling

Directory of Open Access Journals (Sweden)

Ostap Okhrin

2017-06-01

Full Text Available This paper introduces the concept of the realized hierarchical Archimedean copula (rHAC. The proposed approach inherits the ability of the copula to capture the dependencies among financial time series, and combines it with additional information contained in high-frequency data. The considered model does not suffer from the curse of dimensionality, and is able to accurately predict high-dimensional distributions. This flexibility is obtained by using a hierarchical structure in the copula. The time variability of the model is provided by daily forecasts of the realized correlation matrix, which is used to estimate the structure and the parameters of the rHAC. Extensive simulation studies show the validity of the estimator based on this realized correlation matrix, and its performance, in comparison to the benchmark models. The application of the estimator to one-day-ahead Value at Risk (VaR prediction using high-frequency data exhibits good forecasting properties for a multivariate portfolio.

A hierarchical lattice spring model to simulate the mechanics of 2-D materials-based composites

Directory of Open Access Journals (Sweden)

Lucas eBrely

2015-07-01

Full Text Available In the field of engineering materials, strength and toughness are typically two mutually exclusive properties. Structural biological materials such as bone, tendon or dentin have resolved this conflict and show unprecedented damage tolerance, toughness and strength levels. The common feature of these materials is their hierarchical heterogeneous structure, which contributes to increased energy dissipation before failure occurring at different scale levels. These structural properties are the key to exceptional bioinspired material mechanical properties, in particular for nanocomposites. Here, we develop a numerical model in order to simulate the mechanisms involved in damage progression and energy dissipation at different size scales in nano- and macro-composites, which depend both on the heterogeneity of the material and on the type of hierarchical structure. Both these aspects have been incorporated into a 2-dimensional model based on a Lattice Spring Model, accounting for geometrical nonlinearities and including statistically-based fracture phenomena. The model has been validated by comparing numerical results to continuum and fracture mechanics results as well as finite elements simulations, and then employed to study how structural aspects impact on hierarchical composite material properties. Results obtained with the numerical code highlight the dependence of stress distributions on matrix properties and reinforcement dispersion, geometry and properties, and how failure of sacrificial elements is directly involved in the damage tolerance of the material. Thanks to the rapidly developing field of nanocomposite manufacture, it is already possible to artificially create materials with multi-scale hierarchical reinforcements. The developed code could be a valuable support in the design and optimization of these advanced materials, drawing inspiration and going beyond biological materials with exceptional mechanical properties.

HAUTO: Automated composition of convergent services based in HTN planning

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Armando Ordoñez

2014-01-01

Full Text Available This paper presents HAUTO, a framework able to compose convergent services automatically. HAUTO is based in HTN (hierarchical task networks Automated Planning and is composed of three modules: a request processing module that transforms natural language and context information into a planning instance, the automated composition module based on HTN planning and the execution environment for convergent (Web and telecom services. The integration of a planning component provides two basic functionalities: the possibility of customizing the composition of services using the user context information and a middleware level that integrates the execution of services in high performance telecom environments. Finally, a prototype in environmental early warning management is presented as a test case.

Surface-based test plan, Deaf Smith County, Texas Site: Draft

International Nuclear Information System (INIS)

1985-01-01

The Surface-Based Test Plan (SBTP) is the plan which accounts for all surface-based site field work to be conducted at the Permian salt site selected for characterization. The SBTP relates data needs from program requirement documents and presents plans to satisfy the data needs. The SBTP excludes plans for construction of the Exploratory Shaft Facility (ESF) and plans for the in situ testing. The SBTP is a hierarchical plan stemming from the Technical Program Plan. The SBTP describes in detail the process by which surface-based study plans are defined, developed, and controlled. The plans hierarchy extends downward thru subordinate Site Study Plans (SSPs), which describe in detail elements of field work to be done, to detailed Procedures which document the exact methodologies to be employed in the conduct of field work. The plan is a QA level S document, although some of its elements are at lower QA levels. The plan is a controlled document, and any proposed amendments to the plan or subordinate documents can only be implemented through the specified change control procedure

Road Network Selection Based on Road Hierarchical Structure Control

Directory of Open Access Journals (Sweden)

HE Haiwei

2015-04-01

Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

Three-dimensional hierarchical porous tubular carbon as a host matrix for long-term lithium-selenium batteries

Science.gov (United States)

Jia, Min; Lu, Shiyu; Chen, Yuming; Liu, Ting; Han, Jin; Shen, Bolei; Wu, Xiaoshuai; Bao, Shu-Juan; Jiang, Jian; Xu, Maowen

2017-11-01

Lithium-selenium (Li-Se) batteries are of great interest as a representative family of electrochemical energy storage systems because of their high theoretical volumetric capacity and considerable electronic conductivity. However, the main drawback of Se electrodes is the rapid capacity fading caused by the dissolution of polyselenides upon cycling. Here, we report a simple, economical, and effective method for the synthesis of three-dimensional (3D) hierarchical porous carbon with a hollow tubular structure as a host matrix for loading Se and trapping polyselenides. The as-obtained porous tubular carbon shows a superior specific surface area of 1786 m2 g-1, a high pore volume of 0.79 cm3 g-1, and many nanostructured pores. Benefiting from the unique structural characteristics, the resulting hierarchical porous carbon/Se composite exhibits a high capacity of 515 mAh g-1 at 0.2 C. More importantly, a remarkable cycling stability over 900 cycles at 2 C with a capacity fading rate of merely 0.02% per cycle can be achieved. The 3D hollow porous tubular carbon can be also used for other high-performance electrodes of electrochemical energy storage.

Detailed Sponge City Planning Based on Hierarchical Fuzzy Decision-Making: A Case Study on Yangchen Lake

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Junyu Zhang

2017-11-01

Full Text Available We proposed a Hierarchical Fuzzy Inference System (HFIS framework to offer better decision supports with fewer user-defined data (uncertainty. The framework consists two parts: a fuzzified Geographic Information System (GIS and a HFIS system. The former provides comprehensive information on the criterion unit and the latter helps in making more robust decisions. The HFIS and the traditional Multi-Criteria Decision Making (MCDM method were applied to a case study and compared. The fuzzified GIS maps maintained a majority of the dominant characteristics of the criterion unit but also revealed some non-significant information according to the surrounding environment. The urban planning map generated by the two methods shares similar strategy choices (6% difference, while the spatial distribution of strategies shares 69.7% in common. The HFIS required fewer subjective decisions than the MCDM (34 user-defined decision rules vs. 141 manual evaluations.

Study on the correlation between the hierarchical urban system and high-speed railway network planning in China

Directory of Open Access Journals (Sweden)

Hong Sun

2016-09-01

Full Text Available This study examines the interrelatedness between the hierarchical structure of China׳s urban system and high-speed railway (HSR network planning at the national level. As a multi-layered system, the Chinese HSR can be categorized into three sub-networks, namely, the national HSR trunk network, the national HSR extensional network, and the intercity HSR network. By examining the direct HSR network connection, HSR nodal connection, and HSR operational frequency of 287 prefecture-level cities, this study demonstrates that the hierarchies of China׳s administrative, demographic, and economic urban systems strongly influence HSR network planning. The national HSR trunk network prioritizes the connection of top-level central cities, whereas the extensional network prioritizes cities at the lower level of the urban system. Moreover, the national HSR system forms the backbone of the HSR network structure based on a national scale, whereas the intercity HSR system satisfies the travel needs within urban agglomerations based on the regional level.

Knowledge-based computer systems for radiotherapy planning.

Science.gov (United States)

Kalet, I J; Paluszynski, W

1990-08-01

Radiation therapy is one of the first areas of clinical medicine to utilize computers in support of routine clinical decision making. The role of the computer has evolved from simple dose calculations to elaborate interactive graphic three-dimensional simulations. These simulations can combine external irradiation from megavoltage photons, electrons, and particle beams with interstitial and intracavitary sources. With the flexibility and power of modern radiotherapy equipment and the ability of computer programs that simulate anything the machinery can do, we now face a challenge to utilize this capability to design more effective radiation treatments. How can we manage the increased complexity of sophisticated treatment planning? A promising approach will be to use artificial intelligence techniques to systematize our present knowledge about design of treatment plans, and to provide a framework for developing new treatment strategies. Far from replacing the physician, physicist, or dosimetrist, artificial intelligence-based software tools can assist the treatment planning team in producing more powerful and effective treatment plans. Research in progress using knowledge-based (AI) programming in treatment planning already has indicated the usefulness of such concepts as rule-based reasoning, hierarchical organization of knowledge, and reasoning from prototypes. Problems to be solved include how to handle continuously varying parameters and how to evaluate plans in order to direct improvements.

Embedding nano-Li{sub 4}Ti{sub 5}O{sub 12} in hierarchical porous carbon matrixes derived from water soluble polymers for ultra-fast lithium ion batteries anodic materials

Energy Technology Data Exchange (ETDEWEB)

Lan, Chun-Kai; Bao, Qi; Huang, Yao-Hui; Duh, Jenq-Gong, E-mail: jgd@mx.nthu.edu.tw

2016-07-15

Li{sub 4}Ti{sub 5}O{sub 12}/hierarchical porous carbon matrixes composites are successfully prepared by a facile and fast polymers assisted sol–gel method, aiming to promote both electronic and ionic conductivity. As indicated by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy analysis, three less expensive cost and available water soluble polymers (e.g. PAA, CMC, and SA) can homogeneously react with Li–Ti–O precursor to incorporate into interior of nano-scale lithium titanate and provide a continues conductive network after pyrolysis. In addition, the results of scanning electron microscopy and transmission electron microscopy also prove that the Li{sub 4}Ti{sub 5}O{sub 12} nanoparticles are firmly embedded in porous carbon matrix with no obvious agglomeration. EIS measurement and cyclic voltammetry further reveal that the facilitated electrode kinetics and better ionic transport of Li{sub 4}Ti{sub 5}O{sub 12}/hierarchical porous carbon matrixes composites than that of Li{sub 4}Ti{sub 5}O{sub 12}. The c-CMC-LTO exhibits a superior capacity of 92 mAh g{sup −1} and retains its initial value with no obviously capacity decay over 200 cycles under an ultra-high C rate (50 C). - Graphical abstract: Schematic illustrations of the formation process of embedding LTO into Carbon matrixes derived from water soluable polymers (upper) and the electrochemical reaction paths in LTO/Carbon composites during charging/discharging processes (lower). - Highlights: • Hierarchical porous carbon matrixes were used to improve the Li{sub 4}Ti{sub 5}O{sub 12} anodes. • Carbon matrixes could suppress the agglomeration of Li{sub 4}Ti{sub 5}O{sub 12} nanoparticles. • meso-nanoporous carbon structure was beneficial for filtration of electrolyte. • The c-CMC-LTO exhibited superior high rate capability and cycling durability.

Hierarchical MAS based control strategy for microgrid

Energy Technology Data Exchange (ETDEWEB)

Xiao, Z.; Li, T.; Huang, M.; Shi, J.; Yang, J.; Yu, J. [School of Information Science and Engineering, Yunnan University, Kunming 650091 (China); Xiao, Z. [School of Electrical and Electronic Engineering, Nanyang Technological University, Western Catchment Area, 639798 (Singapore); Wu, W. [Communication Branch of Yunnan Power Grid Corporation, Kunming, Yunnan 650217 (China)

2010-09-15

Microgrids have become a hot topic driven by the dual pressures of environmental protection concerns and the energy crisis. In this paper, a challenge for the distributed control of a modern electric grid incorporating clusters of residential microgrids is elaborated and a hierarchical multi-agent system (MAS) is proposed as a solution. The issues of how to realize the hierarchical MAS and how to improve coordination and control strategies are discussed. Based on MATLAB and ZEUS platforms, bilateral switching between grid-connected mode and island mode is performed under control of the proposed MAS to enhance and support its effectiveness. (authors)

RELAP-7 Software Verification and Validation Plan: Requirements Traceability Matrix (RTM) Part 1 – Physics and numerical methods

Energy Technology Data Exchange (ETDEWEB)

Choi, Yong Joon [Idaho National Lab. (INL), Idaho Falls, ID (United States); Yoo, Jun Soo [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-09-01

This INL plan comprehensively describes the Requirements Traceability Matrix (RTM) on main physics and numerical method of the RELAP-7. The plan also describes the testing-based software verification and validation (SV&V) process—a set of specially designed software models used to test RELAP-7.

Microwave induced hierarchical nanostructures on aramid fibers and their influence on adhesion properties in a rubber matrix

Energy Technology Data Exchange (ETDEWEB)

Palola, S., E-mail: sarianna.palola@tut.fi [Laboratory of Materials Science, Tampere University of Technology, P.O. Box 589, 33101, Tampere (Finland); Institute for Materials and Processes, School of Engineering, The University of Edinburgh, The King' s Buildings, Robert Stevenson Road, EH9 3FB Edinburgh (United Kingdom); Sarlin, E. [Laboratory of Materials Science, Tampere University of Technology, P.O. Box 589, 33101, Tampere (Finland); Kolahgar Azari, S.; Koutsos, V. [Institute for Materials and Processes, School of Engineering, The University of Edinburgh, The King' s Buildings, Robert Stevenson Road, EH9 3FB Edinburgh (United Kingdom); Vuorinen, J. [Laboratory of Materials Science, Tampere University of Technology, P.O. Box 589, 33101, Tampere (Finland)

2017-07-15

Highlights: • A novel method for creating nanostructures to aramid fiber surface is proposed. • The nanostructures enable mechanical interlocking at fiber-matrix interface. • A ∼250% increase in adhesion can be created with this method. - Abstract: Several commercial surface treatments are used to increase the adhesion between aramid fibers and the matrix material in composite structures but each of these has some limitations. The aim of this study is to address some of these limitations by developing a surface treatment method for aramid fibers that would not affect mechanical properties of the fibers negatively, could be used with any matrix material and that could withstand handling of the fibers and ageing. The method used is microwave assisted surface treatment that uses microwave radiation together with dry reactive chemicals to create hierarchical structures to the fiber surface and so makes it possible to control the adhesion properties of the fibers. SEM and AFM imaging, fiber tensile tests and modified bundle pull-out test were used to investigate the outcome of the surface treatment and measure adhesion between aramid fiber bundles and rubber. SEM and AFM imaging revealed that nanoscale deposits are formed on to the fiber surface which enable mechanical interlocking between the fiber and the matrix material. Fiber tensile tests showed that the surface treatment does not influence the tensile properties of the fiber negatively. Results from the bundle pull-out tests confirmed that this kind of method can lead up to 259% improvement in adhesion when compared to untreated aramid fibers in the rubber matrix.

Microwave induced hierarchical nanostructures on aramid fibers and their influence on adhesion properties in a rubber matrix

International Nuclear Information System (INIS)

Palola, S.; Sarlin, E.; Kolahgar Azari, S.; Koutsos, V.; Vuorinen, J.

2017-01-01

Highlights: • A novel method for creating nanostructures to aramid fiber surface is proposed. • The nanostructures enable mechanical interlocking at fiber-matrix interface. • A ∼250% increase in adhesion can be created with this method. - Abstract: Several commercial surface treatments are used to increase the adhesion between aramid fibers and the matrix material in composite structures but each of these has some limitations. The aim of this study is to address some of these limitations by developing a surface treatment method for aramid fibers that would not affect mechanical properties of the fibers negatively, could be used with any matrix material and that could withstand handling of the fibers and ageing. The method used is microwave assisted surface treatment that uses microwave radiation together with dry reactive chemicals to create hierarchical structures to the fiber surface and so makes it possible to control the adhesion properties of the fibers. SEM and AFM imaging, fiber tensile tests and modified bundle pull-out test were used to investigate the outcome of the surface treatment and measure adhesion between aramid fiber bundles and rubber. SEM and AFM imaging revealed that nanoscale deposits are formed on to the fiber surface which enable mechanical interlocking between the fiber and the matrix material. Fiber tensile tests showed that the surface treatment does not influence the tensile properties of the fiber negatively. Results from the bundle pull-out tests confirmed that this kind of method can lead up to 259% improvement in adhesion when compared to untreated aramid fibers in the rubber matrix.

Hierarchical graphs for rule-based modeling of biochemical systems

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Hu Bin

2011-02-01

Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

Communication Base Station Log Analysis Based on Hierarchical Clustering

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Zhang Shao-Hua

2017-01-01

Full Text Available Communication base stations generate massive data every day, these base station logs play an important value in mining of the business circles. This paper use data mining technology and hierarchical clustering algorithm to group the scope of business circle for the base station by recording the data of these base stations.Through analyzing the data of different business circle based on feature extraction and comparing different business circle category characteristics, which can choose a suitable area for operators of commercial marketing.

Matrix effective theories of the fractional quantum Hall effect

International Nuclear Information System (INIS)

Cappelli, Andrea; Rodriguez, Ivan D

2009-01-01

The present understanding of nonperturbative ground states in the fractional quantum Hall effect is based on effective theories of the Jain 'composite fermion' excitations. We review the approach based on matrix variables, i.e. D0 branes, originally introduced by Susskind and Polychronakos. We show that the Maxwell-Chern-Simons matrix gauge theory provides a matrix generalization of the quantum Hall effect, where the composite-fermion construction naturally follows from gauge invariance. The matrix ground states obtained by suitable projections of higher Landau levels are found to be in one-to-one correspondence with the Laughlin and Jain hierarchical states. The matrix theory possesses a physical limit for commuting matrices that could be reachable while staying in the same phase.

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

Science.gov (United States)

Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

Mini-lecture course: Introduction into hierarchical matrix technique

KAUST Repository

Litvinenko, Alexander

2017-12-14

The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations (mesh points). The H-matrix technique allows us to work with general class of matrices (not only structured or Toeplits or sparse). H-matrices can keep the H-matrix data format during linear algebra operations (inverse, update, Schur complement).

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

Science.gov (United States)

Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

2018-01-01

In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

Directory of Open Access Journals (Sweden)

Yoshinobu Hagiwara

2018-03-01

Full Text Available In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA. Object recognition results using convolutional neural network (CNN, hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL, and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

From Nano to Macro: Studying the Hierarchical Structure of the Corneal Extracellular Matrix

Science.gov (United States)

Quantock, Andrew J.; Winkler, Moritz; Parfitt, Geraint J.; Young, Robert D.; Brown, Donald J.; Boote, Craig; Jester, James V.

2014-01-01

In this review, we discuss current methods for studying ocular extracellular matrix (ECM) assembly from the ‘nano’ to the ‘macro’ levels of hierarchical organization. Since collagen is the major structural protein in the eye, providing mechanical strength and controlling ocular shape, the methods presented focus on understanding the molecular assembly of collagen at the nanometer level using x-ray scattering through to the millimeter to centimeter level using nonlinear optical (NLO) imaging of second harmonic generated (SHG) signals. Three-dimensional analysis of ECM structure is also discussed, including electron tomography, serial block face scanning electron microscopy (SBF-SEM) and digital image reconstruction. Techniques to detect non-collagenous structural components of the ECM are also presented, and these include immunoelectron microscopy and staining with cationic dyes. Together, these various approaches are providing new insights into the structural blueprint of the ocular ECM, and in particular that of the cornea, which impacts upon our current understanding of the control of corneal shape, pathogenic mechanisms underlying ectatic disorders of the cornea and the potential for corneal tissue engineering. PMID:25819457

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.

2017-01-01

algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H

Family-Centered Early Intervention Visual Impairment Services through Matrix Session Planning

Science.gov (United States)

Ely, Mindy S.; Gullifor, Kateri; Hollinshead, Tara

2017-01-01

Early intervention visual impairment services are built on a model that values family. Matrix session planning pulls together parent priorities, family routines, and identified strategies in a way that helps families and early intervention professionals outline a plan that can both highlight long-term goals and focus on what can be done today.…

Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

OpenAIRE

Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

2012-01-01

The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

Directory of Open Access Journals (Sweden)

Rui Sun

2016-08-01

Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

An evolving systems-based methodology for healthcare planning.

Science.gov (United States)

Warwick, Jon; Bell, Gary

2007-01-01

Healthcare planning seems beset with problems at all hierarchical levels. These are caused by the 'soft' nature of many of the issues present in healthcare planning and the high levels of complexity inherent in healthcare services. There has, in recent years, been a move to utilize systems thinking ideas in an effort to gain a better understanding of the forces at work within the healthcare environment and these have had some success. This paper argues that systems-based methodologies can be further enhanced by metrication and modeling which assist in exploring the changed emergent behavior of a system resulting from management intervention. The paper describes the Holon Framework as an evolving systems-based approach that has been used to help clients understand complex systems (in the education domain) that would have application in the analysis of healthcare problems.

Structural Group-based Auditing of Missing Hierarchical Relationships in UMLS

Science.gov (United States)

Chen, Yan; Gu, Huanying(Helen); Perl, Yehoshua; Geller, James

2009-01-01

The Metathesaurus of the UMLS was created by integrating various source terminologies. The inter-concept relationships were either integrated into the UMLS from the source terminologies or specially generated. Due to the extensive size and inherent complexity of the Metathesaurus, the accidental omission of some hierarchical relationships was inevitable. We present a recursive procedure which allows a human expert, with the support of an algorithm, to locate missing hierarchical relationships. The procedure starts with a group of concepts with exactly the same (correct) semantic type assignments. It then partitions the concepts, based on child-of hierarchical relationships, into smaller, singly rooted, hierarchically connected subgroups. The auditor only needs to focus on the subgroups with very few concepts and their concepts with semantic type reassignments. The procedure was evaluated by comparing it with a comprehensive manual audit and it exhibits a perfect error recall. PMID:18824248

Decomposition of the Strategic Plan for Restructuring a Machine-Building Enterprise in View of Continuity of the Plans for Adjacent Periods

Directory of Open Access Journals (Sweden)

Kozyr-Chepurna Mariia A.

2017-09-01

Full Text Available The aim of the article is to practically approve the authors’ multi-level hierarchical approach to the strategic planning of industrial enterprise restructuring using the example of solving the problem of disaggregating the strategic plan for restructuring a machine-building enterprise of the electrical industry providing for organization of production of railroad freight cars at the enterprise. Besides, there demonstrated the effectiveness of the mechanisms of coordinating the plans for adjacent hierarchical and time periods included in the corresponding mathematical support. In the course of the practical approval, different variants of formulating the problem of decomposing the strategic plan into plans of lower hierarchical levels differing in terms of coordination of the plans of adjacent hierarchical levels and adjacent planning periods are considered, and the solutions of corresponding optimal planning problems are analyzed. It is shown that the developed methodological approach, which is based on the methods of statistical optimization, demonstrates quite satisfactory performance characteristics in solving the problem of coordinating the plans of adjacent time periods in the mode of sliding planning in the process of decomposition of the strategic plan into lower-level plans.

Research on English course based on career planning

Directory of Open Access Journals (Sweden)

Ying Shi

2017-02-01

Full Text Available For the current higher vocational English education way, this paper researches English course on the basis of the need of English competence in career planning, and determines four main objectives to be accomplished in English teaching through the research of the need of English in career planning, and establishes the principle of course design. This paper proposes four kinds of teaching mode according to the career development and career demands, and establishes the hierarchical analysis structure on the basis of the teaching objectives as criteria, analyzes the weight of four objectives, and gives out the quantifiable results for matching with the teaching programs. The results show that, the way of theory and practice education is the most effective, and the academic language competence in career planning is the most important demand. The optimization ratio of English course teaching way based on career planning is 0.26: 0.29: 0.22: 0.23.

Evolution of project planning tools in a matrix organization

Energy Technology Data Exchange (ETDEWEB)

Furaus, J.P.; Figueroa-McInteer, C.; McKeever, P.S.; Wisler, D.B. [Sandia National Labs., Albuquerque, NM (United States); Zavadil, J.T. [Infomatrix (United States)

1996-10-01

Until recently, the Corporate Construction Program at Sandia was experiencing difficulties in managing projects: poor planning and cost estimating caused schedule and budget problems. The first step taken was a Microsoft {reg_sign} Project schedule that provides a standard template for scheduling individual construction projects. It is broken down according to the life cycle of the project and prevents the project team from leaving out an important item. A WBS (work breakdown structure) dictionary was also developed that describes how capital and operating funds are used to develop, design, construct, equip, and manage projects. We also developed a matrix chart that maps the planning guide against the major types of construction projects at Sandia. The guide, dictionary, and matrix chart offer enough flexibility that the project manager can make choices about how to structure work, yet ensure that all work rolls up to the cost categories and key DOE WBS elements. As requirements change, the tools can be updated; they also serve as training tools for new project team members.

Treatment plan modification using voxel-based weighting factors/dose prescription

International Nuclear Information System (INIS)

Wu Chuan; Olivera, Gustavo H; Jeraj, Robert; Keller, Harry; Mackie, Thomas R

2003-01-01

Under various clinical situations, it is desirable to modify the original treatment plan to better suit the clinical goals. In this work, a method to help physicians modify treatment plans based on their clinical preferences is proposed. The method uses a weighted quadratic dose objective function. The commonly used organ-/ROI-based weighting factors are expanded to a set of voxel-based weighting factors in order to obtain greater flexibility in treatment plan modification. Two different but equivalent modification schemes based on Rustem's quadratic programming algorithms -modification of a weighting matrix and modification of prescribed doses - are presented. Case studies demonstrated the effectiveness of the two methods with regard to their capability to fine-tune treatment plans

Binary Hierarchical Porous Graphene/Pyrolytic Carbon Nanocomposite Matrix Loaded with Sulfur as a High-Performance Li-S Battery Cathode.

Science.gov (United States)

Zhang, Hang; Gao, Qiuming; Qian, Weiwei; Xiao, Hong; Li, Zeyu; Ma, Li; Tian, Xuehui

2018-06-06

A N,O-codoped hierarchical porous nanocomposite consisting of binary reduced graphene oxide and pyrolytic carbon (rGO/PC) from chitosan is fabricated. The optimized rGO/PC possesses micropores with size distribution concentrated around 1.1 nm and plenty of meso/macropores. The Brunauer-Emmett-Teller specific surface area is 480.8 m 2 g -1 , and it possesses impressively large pore volume of 2.14 cm 3 g -1 . On the basis of the synergistic effects of the following main factors: (i) the confined space effect in the hierarchical porous binary carbonaceous matrix; (ii) the anchor effects by strong chemical bonds with codoped N and O atoms; and (iii) the good flexibility and conductivity of rGO, the rGO/PC/S holding 75 wt % S exhibits high performance as Li-S battery cathode. Specific capacity of 1625 mA h g -1 can be delivered at 0.1 C (1 C = 1675 mA g -1 ), whereas 848 mA h g -1 can be maintained after 300 cycles at 1 C. Even at high rate of 5 C, 412 mA h g -1 can be restrained after 1000 cycles.

A new simple form of quark mixing matrix

Energy Technology Data Exchange (ETDEWEB)

Qin Nan [School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871 (China); Ma Boqiang, E-mail: mabq@pku.edu.c [School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871 (China); Center for High Energy Physics, Peking University, Beijing 100871 (China)

2011-01-10

Although different parametrizations of quark mixing matrix are mathematically equivalent, the consequences of experimental analysis may be distinct. Based on the triminimal expansion of Kobayashi-Maskawa matrix around the unit matrix, we propose a new simple parametrization. Compared with the Wolfenstein parametrization, we find that the new form is not only consistent with the original one in the hierarchical structure, but also more convenient for numerical analysis and measurement of the CP-violating phase. By discussing the relation between our new form and the unitarity boomerang, we point out that along with the unitarity boomerang, this new parametrization is useful in hunting for new physics.

A new simple form of quark mixing matrix

International Nuclear Information System (INIS)

Qin Nan; Ma Boqiang

2011-01-01

Although different parametrizations of quark mixing matrix are mathematically equivalent, the consequences of experimental analysis may be distinct. Based on the triminimal expansion of Kobayashi-Maskawa matrix around the unit matrix, we propose a new simple parametrization. Compared with the Wolfenstein parametrization, we find that the new form is not only consistent with the original one in the hierarchical structure, but also more convenient for numerical analysis and measurement of the CP-violating phase. By discussing the relation between our new form and the unitarity boomerang, we point out that along with the unitarity boomerang, this new parametrization is useful in hunting for new physics.

Hierarchical structure for audio-video based semantic classification of sports video sequences

Science.gov (United States)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

Hierarchical fiber-optic-based sensing system: impact damage monitoring of large-scale CFRP structures

International Nuclear Information System (INIS)

Minakuchi, Shu; Banshoya, Hidehiko; Takeda, Nobuo; Tsukamoto, Haruka

2011-01-01

This study proposes a novel fiber-optic-based hierarchical sensing concept for monitoring randomly induced damage in large-scale composite structures. In a hierarchical system, several kinds of specialized devices are hierarchically combined to form a sensing network. Specifically, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with an optical fiber network through transducing mechanisms. The distributed devices detect damage, and the fiber-optic network gathers the damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of a hierarchical sensing system through comparison with existing fiber-optic-based systems, and an impact damage detection system was then proposed to validate the new concept. The sensor devices were developed based on comparative vacuum monitoring (CVM), and Brillouin-based distributed strain measurement was utilized to identify damaged areas. Verification tests were conducted step-by-step, beginning with a basic test using a single sensor unit, and, finally, the proposed monitoring system was successfully verified using a carbon fiber reinforced plastic (CFRP) fuselage demonstrator. It was clearly confirmed that the hierarchical system has better repairability, higher robustness, and a wider monitorable area compared to existing systems

Eigenspaces of networks reveal the overlapping and hierarchical community structure more precisely

International Nuclear Information System (INIS)

Ma, Xiaoke; Gao, Lin; Yong, Xuerong

2010-01-01

Identifying community structure is fundamental for revealing the structure–functionality relationship in complex networks, and spectral algorithms have been shown to be powerful for this purpose. In a traditional spectral algorithm, each vertex of a network is embedded into a spectral space by making use of the eigenvectors of the adjacency matrix or Laplacian matrix of the graph. In this paper, a novel spectral approach for revealing the overlapping and hierarchical community structure of complex networks is proposed by not only using the eigenvalues and eigenvectors but also the properties of eigenspaces of the networks involved. This gives us a better characterization of community. We first show that the communicability between a pair of vertices can be rewritten in term of eigenspaces of a network. An agglomerative clustering algorithm is then presented to discover the hierarchical communities using the communicability matrix. Finally, these overlapping vertices are discovered with the corresponding eigenspaces, based on the fact that the vertices more densely connected amongst one another are more likely to be linked through short cycles. Compared with the traditional spectral algorithms, our algorithm can identify both the overlapping and hierarchical community without increasing the time complexity O(n 3 ), where n is the size of the network. Furthermore, our algorithm can also distinguish the overlapping vertices from bridges. The method is tested by applying it to some computer-generated and real-world networks. The experimental results indicate that our algorithm can reveal community structure more precisely than the traditional spectral approaches

SU-E-T-395: Multi-GPU-Based VMAT Treatment Plan Optimization Using a Column-Generation Approach

International Nuclear Information System (INIS)

Tian, Z; Shi, F; Jia, X; Jiang, S; Peng, F

2014-01-01

Purpose: GPU has been employed to speed up VMAT optimizations from hours to minutes. However, its limited memory capacity makes it difficult to handle cases with a huge dose-deposition-coefficient (DDC) matrix, e.g. those with a large target size, multiple arcs, small beam angle intervals and/or small beamlet size. We propose multi-GPU-based VMAT optimization to solve this memory issue to make GPU-based VMAT more practical for clinical use. Methods: Our column-generation-based method generates apertures sequentially by iteratively searching for an optimal feasible aperture (referred as pricing problem, PP) and optimizing aperture intensities (referred as master problem, MP). The PP requires access to the large DDC matrix, which is implemented on a multi-GPU system. Each GPU stores a DDC sub-matrix corresponding to one fraction of beam angles and is only responsible for calculation related to those angles. Broadcast and parallel reduction schemes are adopted for inter-GPU data transfer. MP is a relatively small-scale problem and is implemented on one GPU. One headand- neck cancer case was used for test. Three different strategies for VMAT optimization on single GPU were also implemented for comparison: (S1) truncating DDC matrix to ignore its small value entries for optimization; (S2) transferring DDC matrix part by part to GPU during optimizations whenever needed; (S3) moving DDC matrix related calculation onto CPU. Results: Our multi-GPU-based implementation reaches a good plan within 1 minute. Although S1 was 10 seconds faster than our method, the obtained plan quality is worse. Both S2 and S3 handle the full DDC matrix and hence yield the same plan as in our method. However, the computation time is longer, namely 4 minutes and 30 minutes, respectively. Conclusion: Our multi-GPU-based VMAT optimization can effectively solve the limited memory issue with good plan quality and high efficiency, making GPUbased ultra-fast VMAT planning practical for real clinical use

SU-E-T-395: Multi-GPU-Based VMAT Treatment Plan Optimization Using a Column-Generation Approach

Energy Technology Data Exchange (ETDEWEB)

Tian, Z; Shi, F; Jia, X; Jiang, S [UT Southwestern Medical Ctr at Dallas, Dallas, TX (United States); Peng, F [Carnegie Mellon University, Pittsburgh, PA (United States)

2014-06-01

Purpose: GPU has been employed to speed up VMAT optimizations from hours to minutes. However, its limited memory capacity makes it difficult to handle cases with a huge dose-deposition-coefficient (DDC) matrix, e.g. those with a large target size, multiple arcs, small beam angle intervals and/or small beamlet size. We propose multi-GPU-based VMAT optimization to solve this memory issue to make GPU-based VMAT more practical for clinical use. Methods: Our column-generation-based method generates apertures sequentially by iteratively searching for an optimal feasible aperture (referred as pricing problem, PP) and optimizing aperture intensities (referred as master problem, MP). The PP requires access to the large DDC matrix, which is implemented on a multi-GPU system. Each GPU stores a DDC sub-matrix corresponding to one fraction of beam angles and is only responsible for calculation related to those angles. Broadcast and parallel reduction schemes are adopted for inter-GPU data transfer. MP is a relatively small-scale problem and is implemented on one GPU. One headand- neck cancer case was used for test. Three different strategies for VMAT optimization on single GPU were also implemented for comparison: (S1) truncating DDC matrix to ignore its small value entries for optimization; (S2) transferring DDC matrix part by part to GPU during optimizations whenever needed; (S3) moving DDC matrix related calculation onto CPU. Results: Our multi-GPU-based implementation reaches a good plan within 1 minute. Although S1 was 10 seconds faster than our method, the obtained plan quality is worse. Both S2 and S3 handle the full DDC matrix and hence yield the same plan as in our method. However, the computation time is longer, namely 4 minutes and 30 minutes, respectively. Conclusion: Our multi-GPU-based VMAT optimization can effectively solve the limited memory issue with good plan quality and high efficiency, making GPUbased ultra-fast VMAT planning practical for real clinical use.

Hierarchical quark mass matrices

International Nuclear Information System (INIS)

Rasin, A.

1998-02-01

I define a set of conditions that the most general hierarchical Yukawa mass matrices have to satisfy so that the leading rotations in the diagonalization matrix are a pair of (2,3) and (1,2) rotations. In addition to Fritzsch structures, examples of such hierarchical structures include also matrices with (1,3) elements of the same order or even much larger than the (1,2) elements. Such matrices can be obtained in the framework of a flavor theory. To leading order, the values of the angle in the (2,3) plane (s 23 ) and the angle in the (1,2) plane (s 12 ) do not depend on the order in which they are taken when diagonalizing. We find that any of the Cabbibo-Kobayashi-Maskawa matrix parametrizations that consist of at least one (1,2) and one (2,3) rotation may be suitable. In the particular case when the s 13 diagonalization angles are sufficiently small compared to the product s 12 s 23 , two special CKM parametrizations emerge: the R 12 R 23 R 12 parametrization follows with s 23 taken before the s 12 rotation, and vice versa for the R 23 R 12 R 23 parametrization. (author)

Heuristic hybrid game approach for fleet condition-based maintenance planning

International Nuclear Information System (INIS)

Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

2017-01-01

The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

Matrix Management: An Organizational Alternative for Libraries.

Science.gov (United States)

Johnson, Peggy

1990-01-01

Describes various organizational structures and models, presents matrix management as an alternative to traditional hierarchical structures, and suggests matrix management as an appropriate organizational alternative for academic libraries. Benefits that are discussed include increased flexibility, a higher level of professional independence, and…

Intensity-based hierarchical elastic registration using approximating splines.

Science.gov (United States)

Serifovic-Trbalic, Amira; Demirovic, Damir; Cattin, Philippe C

2014-01-01

We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces. The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cramér-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model. The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method. The proposed hierarchical elastic image registration approach incorporates the GEBS

Road network safety evaluation using Bayesian hierarchical joint model.

Science.gov (United States)

Wang, Jie; Huang, Helai

2016-05-01

Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ferritic Alloys with Extreme Creep Resistance via Coherent Hierarchical Precipitates.

Science.gov (United States)

Song, Gian; Sun, Zhiqian; Li, Lin; Xu, Xiandong; Rawlings, Michael; Liebscher, Christian H; Clausen, Bjørn; Poplawsky, Jonathan; Leonard, Donovan N; Huang, Shenyan; Teng, Zhenke; Liu, Chain T; Asta, Mark D; Gao, Yanfei; Dunand, David C; Ghosh, Gautam; Chen, Mingwei; Fine, Morris E; Liaw, Peter K

2015-11-09

There have been numerous efforts to develop creep-resistant materials strengthened by incoherent particles at high temperatures and stresses in response to future energy needs for steam turbines in thermal-power plants. However, the microstructural instability of the incoherent-particle-strengthened ferritic steels limits their application to temperatures below 900 K. Here, we report a novel ferritic alloy with the excellent creep resistance enhanced by coherent hierarchical precipitates, using the integrated experimental (transmission-electron microscopy/scanning-transmission-electron microscopy, in-situ neutron diffraction, and atom-probe tomography) and theoretical (crystal-plasticity finite-element modeling) approaches. This alloy is strengthened by nano-scaled L21-Ni2TiAl (Heusler phase)-based precipitates, which themselves contain coherent nano-scaled B2 zones. These coherent hierarchical precipitates are uniformly distributed within the Fe matrix. Our hierarchical structure material exhibits the superior creep resistance at 973 K in terms of the minimal creep rate, which is four orders of magnitude lower than that of conventional ferritic steels. These results provide a new alloy-design strategy using the novel concept of hierarchical precipitates and the fundamental science for developing creep-resistant ferritic alloys. The present research will broaden the applications of ferritic alloys to higher temperatures.

Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

Science.gov (United States)

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

Stress generation and hierarchical fracturing in reactive systems

Science.gov (United States)

Jamtveit, B.; Iyer, K.; Royne, A.; Malthe-Sorenssen, A.; Mathiesen, J.; Feder, J.

2007-12-01

Hierarchical fracture patterns are the result of a slowly driven fracturing process that successively divides the rocks into smaller domains. In quasi-2D systems, such fracture patterns are characterized by four sided domains, and T-junctions where new fractures stop at right angles to pre-existing fractures. We describe fracturing of mm to dm thick enstatite layers in a dunite matrix from the Leka ophiolite complex in Norway. The fracturing process is driven by expansion of the dunite matrix during serpentinization. The cumulative distributions of fracture lengths show a scaling behavior that lies between a log - normal and power law (fractal) distribution. This is consistent with a simple fragmentation model in which domains are divided according to a 'top hat' distribution of new fracture positions within unfractured domains. Reaction-assisted hierarchical fracturing is also likely to be responsible for other (3-D) structures commonly observed in serpentinized ultramafic rocks, including the mesh-textures observed in individual olivine grains, and the high abundance of rectangular domains at a wide range of scales. Spectacular examples of 3-D hierarchical fracture patterns also form during the weathering of basaltic intrusions (dolerites). Incipient chemical weathering of dolerites in the Karoo Basin in South Africa occurs around water- filled fractures, originally produced by thermal contraction or by externally imposed stresses. This chemical weathering causes local expansion of the rock matrix and generates elastic stresses. On a mm to cm scale, these stresses lead to mechanical layer-by-layer spalling, producing the characteristic spheroidal weathering patterns. However, our field observations and computer simulations demonstrate that in confined environments, the spalling process alone is unable to relieve the elastic stresses. In such cases, chemical weathering drives a much larger scale hierarchical fracturing process in which fresh dolerite undergoes a

Applying macromolecular crowding to 3D bioprinting: fabrication of 3D hierarchical porous collagen-based hydrogel constructs.

Science.gov (United States)

Ng, Wei Long; Goh, Min Hao; Yeong, Wai Yee; Naing, May Win

2018-02-27

Native tissues and/or organs possess complex hierarchical porous structures that confer highly-specific cellular functions. Despite advances in fabrication processes, it is still very challenging to emulate the hierarchical porous collagen architecture found in most native tissues. Hence, the ability to recreate such hierarchical porous structures would result in biomimetic tissue-engineered constructs. Here, a single-step drop-on-demand (DOD) bioprinting strategy is proposed to fabricate hierarchical porous collagen-based hydrogels. Printable macromolecule-based bio-inks (polyvinylpyrrolidone, PVP) have been developed and printed in a DOD manner to manipulate the porosity within the multi-layered collagen-based hydrogels by altering the collagen fibrillogenesis process. The experimental results have indicated that hierarchical porous collagen structures could be achieved by controlling the number of macromolecule-based bio-ink droplets printed on each printed collagen layer. This facile single-step bioprinting process could be useful for the structural design of collagen-based hydrogels for various tissue engineering applications.

Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

Directory of Open Access Journals (Sweden)

Lianbo Ma

2014-01-01

Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

Science.gov (United States)

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

Directory of Open Access Journals (Sweden)

Ntombizodwa J. Matsoma

2017-10-01

Full Text Available Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. Findings: The results revealed that both hierarchical and optimal approaches should be considered in clothing manufacturing. Managerial implications: In order to improve demand planning practices in the clothing industry, managers are recommended to apply hierarchical and optimal demand planning approaches, which might bring about improvements to demand planning in the Gauteng clothing industry. Conclusion: It is recommended that clothing manufacturers consider the types of product offering before making decisions about adopting the hierarchical or optimal demand planning approaches. When planning for basic clothes, manufacturers should consider a hierarchical demand planning approach, whereas the optimal demand planning approach is recommended for fashion clothes.

A reward optimization method based on action subrewards in hierarchical reinforcement learning.

Science.gov (United States)

Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

2014-01-01

Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

Agent-based distributed hierarchical control of dc microgrid systems

DEFF Research Database (Denmark)

Meng, Lexuan; Vasquez, Juan Carlos; Guerrero, Josep M.

2014-01-01

In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken as ....... Standard genetic algorithm is applied in each local control system in order to search for a global optimum. Hardware-in-Loop simulation results are shown to demonstrate the effectiveness of the method.......In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken...... as a case study. The objective is to enhance the system efficiency by finding the optimal sharing ratio of load current. Virtual resistances in local control systems are taken as decision variables. Consensus algorithms are applied for global information discovery and local control systems coordination...

Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets.

Directory of Open Access Journals (Sweden)

Woosang Lim

Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.

Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation

Science.gov (United States)

Jung, Dongwon

2007-12-01

problem is formulated by setting up geometric linear constraints as well as boundary conditions. Subsequently, we construct B-spline path templates by solving a set of distinct optimization problems. For application in UAV motion planning, the path templates are incorporated to replace parts of the entire path by the smooth B-spline paths. Each path segment is stitched together while preserving continuity to obtain a final smooth reference path to be used for path following control. The path following control for a small fixed-wing UAV to track the prescribed smooth reference path is also addressed. Assuming the UAV is equipped with an autopilot for low level control, we adopt a kinematic error model with respect to the moving Serret-Frenet frame attached to a path for tracking controller design. A kinematic path following control law that commands heading rate is presented. Backstepping is applied to derive the roll angle command by taking into account the approximate closed-loop roll dynamics. A parameter adaptation technique is employed to account for the inaccurate time constant of the closed-loop roll dynamics during actual implementation. Finally, we implement the proposed hierarchical path control of a small UAV on the actual hardware platform, which is based on an 1/5 scale R/C model airframe (Decathlon) and the autopilot hardware and software. Based on the hardware-in-the-loop (HIL) simulation environment, the proposed hierarchical path control algorithm has been validated through on-line, real-time implementation on a small micro-controller. By a seamless integration of the control algorithms for path planning, path smoothing, and path following, it has been demonstrated that the UAV equipped with a small autopilot having limited computational resources manages to accomplish the path control objective to reach the goal while avoiding obstacles with minimal human intervention.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying

2015-01-01

We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-11-30

We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.

Hierarchical control system of advanced robot manipulator

International Nuclear Information System (INIS)

Oomichi, Takeo; Okino, Akihisa; Nishihara, Masatoshi; Sakamoto, Taizou; Matsuda, Koichi; Ohnishi, Ken

1990-01-01

We introduce a double arm with 4-finger's manipulator system which process the large volume of information at high speed. This is under research/development many type of works in the harsh condition. Namely, hierarchization of instruction unit in which motion control system as real time processing unit, and task planning unit as non-real time processing unit, interface with operation through the task planning unit has been made. Also, high speed processing of large volume information has been realized by decentralizing the motion control unit by function, hierarchizing the high speed processing unit, and developing high speed transmission, IC which does not depend on computer OS to avoid the delay in transmission. (author)

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-01-05

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul

2015-01-01

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.

LSTM-Based Hierarchical Denoising Network for Android Malware Detection

Directory of Open Access Journals (Sweden)

Jinpei Yan

2018-01-01

Full Text Available Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN, a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequences are too long for LSTM to train due to the gradient vanishing problem. Hence, HDN uses a hierarchical structure, whose first-level LSTM parallelly computes on opcode subsequences (we called them method blocks to learn the dense representations; then the second-level LSTM can learn and detect malware through method block sequences. Considering that malicious behavior only appears in partial sequence segments, HDN uses method block denoise module (MBDM for data denoising by adaptive gradient scaling strategy based on loss cache. We evaluate and compare HDN with the latest mainstream researches on three datasets. The results show that HDN outperforms these Android malware detection methods,and it is able to capture longer sequence features and has better detection efficiency than N-gram-based malware detection which is similar to our method.

MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization

Directory of Open Access Journals (Sweden)

Kellermann Walter

2007-01-01

Full Text Available We address the problem of underdetermined BSS. While most previous approaches are designed for instantaneous mixtures, we propose a time-frequency-domain algorithm for convolutive mixtures. We adopt a two-step method based on a general maximum a posteriori (MAP approach. In the first step, we estimate the mixing matrix based on hierarchical clustering, assuming that the source signals are sufficiently sparse. The algorithm works directly on the complex-valued data in the time-frequency domain and shows better convergence than algorithms based on self-organizing maps. The assumption of Laplacian priors for the source signals in the second step leads to an algorithm for estimating the source signals. It involves the -norm minimization of complex numbers because of the use of the time-frequency-domain approach. We compare a combinatorial approach initially designed for real numbers with a second-order cone programming (SOCP approach designed for complex numbers. We found that although the former approach is not theoretically justified for complex numbers, its results are comparable to, or even better than, the SOCP solution. The advantage is a lower computational cost for problems with low input/output dimensions.

LSTM-Based Hierarchical Denoising Network for Android Malware Detection

OpenAIRE

Yan, Jinpei; Qi, Yong; Rao, Qifan

2018-01-01

Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN), a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequence...

Mini-lecture course: Introduction into hierarchical matrix technique

KAUST Repository

Litvinenko, Alexander

2017-01-01

allows us to work with general class of matrices (not only structured or Toeplits or sparse). H-matrices can keep the H-matrix data format during linear algebra operations (inverse, update, Schur complement).

Hierarchical layered and semantic-based image segmentation using ergodicity map

Science.gov (United States)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects

Hierarchical polypyrrole based composites for high performance asymmetric supercapacitors

Science.gov (United States)

Chen, Gao-Feng; Liu, Zhao-Qing; Lin, Jia-Ming; Li, Nan; Su, Yu-Zhi

2015-06-01

An advanced asymmetric supercapacitor with high energy density, exploiting hierarchical polypyrrole (PPy) based composites as both the anode [three dimensional (3D) chuzzle-like Ni@PPy@MnO2] and (3D cochleate-like Ni@MnO2@PPy) cathode, has been developed. The ultrathin PPy and flower-like MnO2 orderly coating on the high-conductivity 3D-Ni enhance charge storage while the unique 3D chuzzle-like and 3D cochleate-like structures provide storage chambers and fast ion transport pathways for benefiting the transport of electrolyte ions. The 3D cochleate-like Ni@MnO2@PPy possesses excellent pseudocapacitance with a relatively negative voltage window while preserved EDLC and free transmission channels conducive to hold the high power, providing an ideal cathode for the asymmetric supercapacitor. It is the first report of assembling hierarchical PPy based composites as both the anode and cathode for asymmetric supercapacitor, which exhibits wide operation voltage of 1.3-1.5 V with maximum energy and power densities of 59.8 Wh kg-1 and 7500 W kg-1.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-01-07

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul

2015-01-01

We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design

Hierarchical Controlled Grid-Connected Microgrid based on a Novel Autonomous Current Sharing Controller

DEFF Research Database (Denmark)

Guan, Yajuan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

2015-01-01

In this paper, a hierarchical control system based on a novel autonomous current sharing controller for grid-connected microgrids (MGs) is presented. A three-level hierarchical control system is implemented to guarantee the power sharing performance among voltage controlled parallel inverters......, while providing the required active and reactive power to the utility grid. A communication link is used to transmit the control signal from the tertiary and secondary control levels to the primary control. Simulation results from a MG based on two grid-connected parallel inverters are shown in order...

Application of hierarchical matrices for partial inverse

KAUST Repository

Litvinenko, Alexander

2013-11-26

In this work we combine hierarchical matrix techniques (Hackbusch, 1999) and domain decomposition methods to obtain fast and efficient algorithms for the solution of multiscale problems. This combination results in the hierarchical domain decomposition (HDD) method, which can be applied for solution multi-scale problems. Multiscale problems are problems that require the use of different length scales. Using only the finest scale is very expensive, if not impossible, in computational time and memory. Domain decomposition methods decompose the complete problem into smaller systems of equations corresponding to boundary value problems in subdomains. Then fast solvers can be applied to each subdomain. Subproblems in subdomains are independent, much smaller and require less computational resources as the initial problem.

Depletion of atmospheric muon-neutrino fluxes and structure of Majorana mass matrix

International Nuclear Information System (INIS)

Tanimoto, Morimitsu; Matsuda, Masahisa

1993-01-01

We study the structures of the Dirac and Majorana mass matrices which give rise to the large lepton mixing expected from the depleted atmospheric muonneutrino flux. In the case that the Majorana mass matrix has a hierarchy for generations, a certain kind of the neutrino Dirac mass matrix with the hierarchical structure leads to the large lepton mixing between the second generation and the third one. Our model-independent analyses serve the model-building of the mass matrices based on the quark-lepton unified theory. (orig.)

IMPLEMENTASI DISTRIBUSI REQUIREMENT PLANNING DAN SAVING MATRIX UNTUK MEMINIMASI TOTAL BIAYA DISTRIBUSI DI INDUSTRI BAHAN KIMIA

Directory of Open Access Journals (Sweden)

Johan Oscar Ong

2013-12-01

Full Text Available Planning and scheduling of the distribution of goods in PT. Senatama Laboranusa are not well coordinated, so the demand for each product is out of control, which results in deficiency or excess of inventories in both of the factories and each warehouse. This problem will affect the distribution cost incurred by the company. In this study, the distribution data process is done by using Distribution Requirement Planning method and route distribution processing by using Saving Matrix, in which both of these methods can group the delivery schedule and flow of distribution route regularly. PO Release, which contains time, order amount of each area, and lot size EOQ (Economic Order Quantity method used; will be generated from the calculation of DRP. From the calculation of Saving Matrix, route order sequence is applied by using Nearest Neighbor method. After the implementation of Distribution Requirement Planning, the cost reduction resulted is 29.75% and the difference in distance after the application of Saving Matrix is 983.3 Km. With a good distribution activity planning and scheduling, the success rate in meeting the customer demand would be more optimal, while sales performance increases in fulfilling orders in a timely manner and  appropriate amount, hence the distribution costs can be kept as minimum as possible.

Biomedical application of hierarchically built structures based on metal oxides

Science.gov (United States)

Korovin, M. S.; Fomenko, A. N.

2017-12-01

Nowadays, the use of hierarchically built structures in biology and medicine arouses much interest. The aim of this work is to review and summarize the available literature data about hierarchically organized structures in biomedical application. Nanoparticles can serve as an example of such structures. Medicine holds a special place among various application methods of similar systems. Special attention is paid to inorganic nanoparticles based on different metal oxides and hydroxides, such as iron, zinc, copper, and aluminum. Our investigations show that low-dimensional nanostructures based on aluminum oxides and hydroxides have an inhibitory effect on tumor cells and possess an antimicrobial activity. At the same time, it is obvious that the large-scale use of nanoparticles by humans needs to thoroughly study their properties. Special attention should be paid to the study of nanoparticle interaction with living biological objects. The numerous data show that there is no clear understanding of interaction mechanisms between nanoparticles and various cell types.

AHP-ENHANCED SWOT MATRIX TEACHING STRATEGY

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Mario Chipoco Quevedo

2015-12-01

Full Text Available ABSTRACT The SWOT matrix is the quintessential analysis tool for business purposes, and is taught both in undergraduate and postgraduate courses. However, it is widely understood that the selection of the critical success factors (CSFs that are included for analysis in the matrix is a very subjective and unstructured process, leaving room for bias and arbitrariness. One way to give a better foundation and support to the analysis results is by utilizing Analytic Hierarchical Process (AHP in order to weigh the importance of CSFs in the SWOT matrix and increase reliability of the output. This paper contains the design of a strategy to teach this topic in a marketing planning course, with the addition of a useful technique to overcome the limitations of the tool. RESUMEN La matriz FODA es la herramienta de análisis por excelencia para fines de negocios, y se enseña en cursos de pregrado y postgrado. Sin embargo, se entiende que la elección de los factores críticos de éxito (FCEs que se incluyen en la matriz para el análisis es un proceso muy subjetivo y no estructurado, que da cabida a sesgos y arbitrariedad. Una forma de dar una mejor base y respaldo a los resultados del análisis es mediante la utilización del Proceso Jerárquico Analítico (AHP con el fin de ponderar la importancia de los FCEs en la matriz FODA y aumentar la fiabilidad de los resultados. Este documento contiene el diseño de una estrategia para enseñar este tema en un curso de planificación de marketing, con la adición de una técnica útil para superar las limitaciones de la herramienta.

Macroscopic Rock Texture Image Classification Using a Hierarchical Neuro-Fuzzy Class Method

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Laercio B. Gonçalves

2010-01-01

Full Text Available We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning (NFHB-Class Method for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguistically interpretable, thus explaining the obtained data structure. The presented image classification for macroscopic rocks is based on texture descriptors, such as spatial variation coefficient, Hurst coefficient, entropy, and cooccurrence matrix. Four rock classes have been evaluated by the NFHB-Class Method: gneiss (two subclasses, basalt (four subclasses, diabase (five subclasses, and rhyolite (five subclasses. These four rock classes are of great interest in the evaluation of oil boreholes, which is considered a complex task by geologists. We present a computer method to solve this problem. In order to evaluate system performance, we used 50 RGB images for each rock classes and subclasses, thus producing a total of 800 images. For all rock classes, the NFHB-Class Method achieved a percentage of correct hits over 73%. The proposed method converged for all tests presented in the case study.

Determinants of falls in community-dwelling elderly: hierarchical analysis.

Science.gov (United States)

Brito, Thais Alves; Coqueiro, Raildo da Silva; Fernandes, Marcos Henrique; de Jesus, Cleber Souza

2014-01-01

To analyze the fall-related factors in community-dwelling elderly. Epidemiologic cross-sectional population-based household study with hierarchical interrelationships among the potential risk factors. The sample was made up of noninstitutionalized individuals over age 60, who were resident of a city in Brazil's Northeast Region. The dependent variable was fall occurrence in the last 12 months; independent variables were sociodemographic, behavioral, health, and functional status factors. Multivariate hierarchical Poisson regression analysis was used based on a proposed theoretic model. Three hundred and sixteen (89.0%) elderly participated of the survey, average age 74.2 years; the majority was female, with limited literacy and had low-medium family income. The fall prevalence was of 25.8%; occurrence was related to depression symptoms (PR = 1.55) and balance limitation (PR = 1.56). The high fall prevalence among elderly necessitates the identification of fall-related factors for action planning prevention programs with this group. © 2014 Wiley Periodicals, Inc.

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

KAUST Repository

Hasanov, Khalid; Quintin, Jean-Noë l; Lastovetsky, Alexey

2014-01-01

-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

Implementation of a Matrix Organizational Structure: A Case Study.

Science.gov (United States)

Whorton, David M.

The implementation of a matrix structure as an alternative to the traditional collegial/bureaucratic form at a college of education in a medium-size state university is described. Matrix organizational structures are differentiated from hierarchical bureaucratic structures by dividing the organization's tasks into functional units across which an…

Unsupervised active learning based on hierarchical graph-theoretic clustering.

Science.gov (United States)

Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

2009-10-01

Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

Constructing storyboards based on hierarchical clustering analysis

Science.gov (United States)

Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

2005-07-01

There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

Directory of Open Access Journals (Sweden)

Nabil Sabor

2017-01-01

Full Text Available Introducing mobility to Wireless Sensor Networks (WSNs puts new challenges particularly in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink node in the network. Many routing protocols have been developed to support the mobility of WSNs. These protocols are divided depending on the routing structure into hierarchical-based, flat-based, and location-based routing protocols. However, the hierarchical-based routing protocols outperform the other routing types in saving energy, scalability, and extending lifetime of Mobile WSNs (MWSNs. Selecting an appropriate hierarchical routing protocol for specific applications is an important and difficult task. Therefore, this paper focuses on reviewing some of the recently hierarchical-based routing protocols that are developed in the last five years for MWSNs. This survey divides the hierarchical-based routing protocols into two broad groups, namely, classical-based and optimized-based routing protocols. Also, we present a detailed classification of the reviewed protocols according to the routing approach, control manner, mobile element, mobility pattern, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated in this survey depending on delay, network size, energy-efficiency, and scalability while mentioning the advantages and drawbacks of each protocol. Finally, we summarize and conclude the paper with future directions.

A Planning Approach of Engineering Characteristics Based on QFD-TRIZ Integrated

Science.gov (United States)

Liu, Shang; Shi, Dongyan; Zhang, Ying

Traditional QFD planning method compromises contradictions between engineering characteristics to achieve higher customer satisfaction. However, this compromise trade-off can not eliminate the contradictions existing among the engineering characteristics which limited the overall customer satisfaction. QFD (Quality function deployment) integrated with TRIZ (the Russian acronym of the Theory of Inventive Problem Solving) becomes hot research recently for TRIZ can be used to solve contradictions between engineering characteristics which construct the roof of HOQ (House of quality). But, the traditional QFD planning approach is not suitable for QFD integrated with TRIZ for that TRIZ requires emphasizing the contradictions between engineering characteristics at problem definition stage instead of compromising trade-off. So, a new planning approach based on QFD / TRIZ integration is proposed in this paper, which based on the consideration of the correlation matrix of engineering characteristics and customer satisfaction on the basis of cost. The proposed approach suggests that TRIZ should be applied to solve contradictions at the first step, and the correlation matrix of engineering characteristics should be amended at the second step, and at next step IFR (ideal final result) must be validated, then planning execute. An example is used to illustrate the proposed approach. The application indicated that higher customer satisfaction can be met and the contradictions between the characteristic parameters are eliminated.

Morphology-controlled hydrothermal synthesis of MnCO3 hierarchical superstructures with Schiff base as stabilizer

International Nuclear Information System (INIS)

Hu, He; Xu, Jie-yan; Yang, Hong; Liang, Jie; Yang, Shiping; Wu, Huixia

2011-01-01

Graphical abstract: MnCO3 microcrystals with hierarchical superstructures were synthesized by using the CO2 in atmosphere as carbonate ions source and Schiff base as shape guiding-agent in water/ethanol system under hydrothermal condition. Highlights: → The most interesting in this work is the use of the greenhouse gases CO 2 in atmosphere as carbonate ions source to precipitate with Mn 2+ for producing MnCO 3 crystals. → This work is the first report related to the small organic molecule Schiff base as shape guiding-agent to produce different MnCO 3 hierarchical superstructures. → We are controllable synthesis of the MnCO 3 hierarchical superstructures such as chrysanthemum, straw-bundle, dumbbell and sphere-like microcrystals. → The as-prepared MnCO 3 could be used precursor to fabricate the Mn 2 O 3 hierarchical superstructures after thermal decomposition at high temperature. -- Abstract: MnCO 3 with hierarchical superstructures such as chrysanthemum, straw-bundle, dumbbell and sphere-like were synthesized in water/ethanol system under environment-friendly hydrothermal condition. In the synthesis process, the CO 2 in atmosphere was used as the source of carbonate ions and Schiff base was used as shape guiding-agent. The different superstructures of MnCO 3 could be obtained by controlling the hydrothermal temperature, the molar ratio of manganous ions to the Schiff base, or the volume ratio of water to ethanol. A tentative growth mechanism for the generation of MnCO 3 superstructures was proposed based on the rod-dumbbell-sphere model. Furthermore, the MnCO 3 as precursor could be further successfully transferred to Mn 2 O 3 microstructure after heating in the atmosphere at 500 o C, and the morphology of the Mn 2 O 3 was directly determined by that of the MnCO 3 precursor.

Large νμ-ντ mixing and the structure of right-handed Majorana mass matrix

International Nuclear Information System (INIS)

Matsuda, Masahisa

1993-01-01

Recent solar neutrino and atmospheric neutrino experiment suggest the existence of the large lepton mixing among 2nd and 3rd generation neutrino. This fact gives the important information on the structure of right-handed Majorana neutrino. It is shown that, if we assume that the neutrino Dirac mass matrix is similar to the mass matrix of the up-quark sector, the large lepton mixing among the 2nd and the 3rd generation requires the hierarchical structure of the Majorana mass matrix. This model-independent analyses serve the model-building of the mass matrices based on the quark-lepton unified theory. (author)

APPLICATION OF RESTART COVARIANCE MATRIX ADAPTATION EVOLUTION STRATEGY (RCMA-ES TO GENERATION EXPANSION PLANNING PROBLEM

Directory of Open Access Journals (Sweden)

K. Karthikeyan

2012-10-01

Full Text Available This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMA-ES to the Generation Expansion Planning (GEP problem. RCMA-ES is a class of continuous Evolutionary Algorithm (EA derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP. The GEP problem of a synthetic test systems for 6-year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.

ELIMINATION OF THE DISADVANTAGES OF SCHEDULING-NETWORK PLANNING BY APPLYING THE MATRIX OF KEY PROJECT EVENTS

Directory of Open Access Journals (Sweden)

Morozenko Andrey Aleksandrovich

2017-07-01

Full Text Available The article discusses the current disadvantages of the scheduling-network planning in the management of the terms of investment-construction project. Problems associated with the construction of the schedule and the definitions of the duration of the construction project are being studied. The problems of project management for the management apparatus are shown, which consists in the absence of mechanisms for prompt response to deviations in the parameters of the scheduling-network diagram. A new approach to planning the implementation of an investment-construction project based on a matrix of key events and a rejection of the current practice of determining the duration based on inauthentic regulatory data. An algorithm for determining the key events of the project is presented. For increase the reliability of the organizational structure, the load factor of the functional block in the process of achieving the key event is proposed. Recommendations for improving the interaction of the participants in the investment-construction project are given.

INFLUENCE OF THE SKELETON HIERARCHICAL ORGANIZATION ON ELECTRONIC STATE OF IONS IN BONE MATRIX

Directory of Open Access Journals (Sweden)

A. S. Avrunin

2016-01-01

Full Text Available The authors suggested the 3D-superlattice (3DSL model to describe the effect of coplanar assembly of the hydroxyapatite (HA nanocrystallites on local electronic state of ions in mineralized bone. This model is based on the main structural and functional relationships between adjacent levels of the hierarchical organization of bone tissue. In the framework of the 3DSL model the authors predicted the distinct assembly-to-crystal red shift of the unoccupied electronic states located near the bottom of the conduction band in HA and dependence of this shift on the ratio of the thickness of the hydrated layer to the crystallite size. To check these predictions the experimental X-ray absorption studies of native bone are performed near the Ca2р1/2,3/2-, P2р1/2,3/2- и O1s edges. Comparison of the measured spectra with the known spectra of the reference compounds has confirmed appearance of the distinct assembly-to-crystal red shift. The observed effect is the ground for development of new diagnostic methods for bone status and imaging changes in the local electronic structure of bone tissue by using ultrasoft X-ray absorption spectroscopy and measuring the assembly-tocrystal shifts. The experimental data analysis proved the applicability of the 3DSL model for better understanding of the hierarchical organization of bone at nanolevel.

Trigonometric bases for matrix weighted Lp-spaces

DEFF Research Database (Denmark)

Nielsen, Morten

2010-01-01

We give a complete characterization of 2π-periodic matrix weights W for which the vector-valued trigonometric system forms a Schauder basis for the matrix weighted space Lp(T;W). Then trigonometric quasi-greedy bases for Lp(T;W) are considered. Quasi-greedy bases are systems for which the simple...

Topology of foreign exchange markets using hierarchical structure methods

Science.gov (United States)

Naylor, Michael J.; Rose, Lawrence C.; Moyle, Brendan J.

2007-08-01

This paper uses two physics derived hierarchical techniques, a minimal spanning tree and an ultrametric hierarchical tree, to extract a topological influence map for major currencies from the ultrametric distance matrix for 1995-2001. We find that these two techniques generate a defined and robust scale free network with meaningful taxonomy. The topology is shown to be robust with respect to method, to time horizon and is stable during market crises. This topology, appropriately used, gives a useful guide to determining the underlying economic or regional causal relationships for individual currencies and to understanding the dynamics of exchange rate price determination as part of a complex network.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

Science.gov (United States)

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Efficiently dense hierarchical graphene based aerogel electrode for supercapacitors

Science.gov (United States)

Wang, Xin; Lu, Chengxing; Peng, Huifen; Zhang, Xin; Wang, Zhenkun; Wang, Gongkai

2016-08-01

Boosting gravimetric and volumetric capacitances simultaneously at a high rate is still a discrepancy in development of graphene based supercapacitors. We report the preparation of dense hierarchical graphene/activated carbon composite aerogels via a reduction induced self-assembly process coupled with a drying post treatment. The compact and porous structures of composite aerogels could be maintained. The drying post treatment has significant effects on increasing the packing density of aerogels. The introduced activated carbons play the key roles of spacers and bridges, mitigating the restacking of adjacent graphene nanosheets and connecting lateral and vertical graphene nanosheets, respectively. The optimized aerogel with a packing density of 0.67 g cm-3 could deliver maximum gravimetric and volumetric capacitances of 128.2 F g-1 and 85.9 F cm-3, respectively, at a current density of 1 A g-1 in aqueous electrolyte, showing no apparent degradation to the specific capacitance at a current density of 10 A g-1 after 20000 cycles. The corresponding gravimetric and volumetric capacitances of 116.6 F g-1 and 78.1 cm-3 with an acceptable cyclic stability are also achieved in ionic liquid electrolyte. The results show a feasible strategy of designing dense hierarchical graphene based aerogels for supercapacitors.

A hierarchical fuzzy rule-based approach to aphasia diagnosis.

Science.gov (United States)

Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

2007-10-01

Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

Contribution of matrix converter in microgeneration for a sustainable energy planning; Contribuicao do conversor matricial na microgeracao para um planejamento energetico sustentavel

Energy Technology Data Exchange (ETDEWEB)

Romero, Javier Alexis Andrade; Romero, Jesus Franklin Andrade [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil). Programa de Pos-Graduacao em Energia], emails: javier.romero@ufabc.edu.br, jesus.romero@ufabc.edu.br

2010-07-01

Once microturbine (MT) based generation systems present suitable and short term application conditions in distributed generation, a rigorous sustainability evaluation is necessary. In this work a Two Stage Matrix Converter (CM2E) that improves the energy efficiency performance is evaluated. In this sense, an analysis based on technological indicators regarding a sustainable energy planning is presented in technological, economic, social and environmental dimensions (author)

High Temperature Deformation Mechanism in Hierarchical and Single Precipitate Strengthened Ferritic Alloys by In Situ Neutron Diffraction Studies.

Science.gov (United States)

Song, Gian; Sun, Zhiqian; Li, Lin; Clausen, Bjørn; Zhang, Shu Yan; Gao, Yanfei; Liaw, Peter K

2017-04-07

The ferritic Fe-Cr-Ni-Al-Ti alloys strengthened by hierarchical-Ni 2 TiAl/NiAl or single-Ni 2 TiAl precipitates have been developed and received great attentions due to their superior creep resistance, as compared to conventional ferritic steels. Although the significant improvement of the creep resistance is achieved in the hierarchical-precipitate-strengthened ferritic alloy, the in-depth understanding of its high-temperature deformation mechanisms is essential to further optimize the microstructure and mechanical properties, and advance the development of the creep resistant materials. In the present study, in-situ neutron diffraction has been used to investigate the evolution of elastic strain of constitutive phases and their interactions, such as load-transfer/load-relaxation behavior between the precipitate and matrix, during tensile deformation and stress relaxation at 973 K, which provide the key features in understanding the governing deformation mechanisms. Crystal-plasticity finite-element simulations were employed to qualitatively compare the experimental evolution of the elastic strain during tensile deformation at 973 K. It was found that the coherent elastic strain field in the matrix, created by the lattice misfit between the matrix and precipitate phases for the hierarchical-precipitate-strengthened ferritic alloy, is effective in reducing the diffusional relaxation along the interface between the precipitate and matrix phases, which leads to the strong load-transfer capability from the matrix to precipitate.

Parallel iterative solvers and preconditioners using approximate hierarchical methods

Energy Technology Data Exchange (ETDEWEB)

Grama, A.; Kumar, V.; Sameh, A. [Univ. of Minnesota, Minneapolis, MN (United States)

1996-12-31

In this paper, we report results of the performance, convergence, and accuracy of a parallel GMRES solver for Boundary Element Methods. The solver uses a hierarchical approximate matrix-vector product based on a hybrid Barnes-Hut / Fast Multipole Method. We study the impact of various accuracy parameters on the convergence and show that with minimal loss in accuracy, our solver yields significant speedups. We demonstrate the excellent parallel efficiency and scalability of our solver. The combined speedups from approximation and parallelism represent an improvement of several orders in solution time. We also develop fast and paralellizable preconditioners for this problem. We report on the performance of an inner-outer scheme and a preconditioner based on truncated Green`s function. Experimental results on a 256 processor Cray T3D are presented.

SETH: A Hierarchical, Agent-based Architecture for Smart Spaces

OpenAIRE

Marsá Maestre, Iván

2008-01-01

The ultimate goal of any smart environment is to release users from the tasks they usually perform to achieve comfort, efficiency, and service personalization. To achieve this goal, we propose to use multiagent systems. In this report we describe the SETH architectur: a hierarchical, agent-based solution intended to be applicable to different smart space scenarios, ranging from small environments, like smart homes or smart offices, to large smart spaces like cities.

Hierarchical composites: Analysis of damage evolution based on fiber bundle model

DEFF Research Database (Denmark)

Mishnaevsky, Leon

2011-01-01

A computational model of multiscale composites is developed on the basis of the fiber bundle model with the hierarchical load sharing rule, and employed to study the effect of the microstructures of hierarchical composites on their damage resistance. Two types of hierarchical materials were consi...

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

Science.gov (United States)

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

Ontological Planning

Directory of Open Access Journals (Sweden)

Ahmet Alkan

2017-12-01

• Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

A new intrusion prevention model using planning knowledge graph

Science.gov (United States)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

Science.gov (United States)

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.

2017-01-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-11-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

Science.gov (United States)

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius

2017-07-03

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

Nested and Hierarchical Archimax copulas

KAUST Repository

Hofert, Marius; Huser, Raphaë l; Prasad, Avinash

2017-01-01

The class of Archimax copulas is generalized to nested and hierarchical Archimax copulas in several ways. First, nested extreme-value copulas or nested stable tail dependence functions are introduced to construct nested Archimax copulas based on a single frailty variable. Second, a hierarchical construction of d-norm generators is presented to construct hierarchical stable tail dependence functions and thus hierarchical extreme-value copulas. Moreover, one can, by itself or additionally, introduce nested frailties to extend Archimax copulas to nested Archimax copulas in a similar way as nested Archimedean copulas extend Archimedean copulas. Further results include a general formula for the density of Archimax copulas.

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

Science.gov (United States)

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

Biomineralization of a Self-assembled, Soft-Matrix Precursor: Enamel

Science.gov (United States)

Snead, Malcolm L.

2015-04-01

Enamel is the bioceramic covering of teeth, a composite tissue composed of hierarchical organized hydroxyapatite crystallites fabricated by cells under physiologic pH and temperature. Enamel material properties resist wear and fracture to serve a lifetime of chewing. Understanding the cellular and molecular mechanisms for enamel formation may allow a biology-inspired approach to material fabrication based on self-assembling proteins that control form and function. A genetic understanding of human diseases exposes insight from nature's errors by exposing critical fabrication events that can be validated experimentally and duplicated in mice using genetic engineering to phenocopy the human disease so that it can be explored in detail. This approach led to an assessment of amelogenin protein self-assembly that, when altered, disrupts fabrication of the soft enamel protein matrix. A misassembled protein matrix precursor results in loss of cell-to-matrix contacts essential to fabrication and mineralization.

Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

Directory of Open Access Journals (Sweden)

Parvin Jeffrey

2010-12-01

Full Text Available Abstract Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2 were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM. A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes and targeted TFs (25% of common TFs. The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to

Analysis of Scattering by Inhomogeneous Dielectric Objects Using Higher-Order Hierarchical MoM

DEFF Research Database (Denmark)

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

2003-01-01

An efficient technique for the analysis of electromagnetic scattering by arbitrary shaped inhomogeneous dielectric objects is presented. The technique is based on a higher-order method of moments (MoM) solution of the volume integral equation. This higher-order MoM solution comprises recently...... that the condition number of the resulting MoM matrix is reduced by several orders of magnitude in comparison to existing higher-order hierarchical basis functions and, consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement...

A prototype knowledge-based system for material selection of ceramic matrix composites of automotive engine components

Energy Technology Data Exchange (ETDEWEB)

Sapuan, S.M.; Jacob, M.S.D.; Mustapha, F.; Ismail, N

2002-12-15

A prototype knowledge based system (KBS) for material selection of ceramic matrix composites (CMC) for engine components such as piston, connecting rod and piston ring is proposed in this paper. The main aim of this research work is to select the most suitable material for the automotive engine components. The selection criteria are based upon the pre-defined constraint value. The constraint values are mechanical, physical properties and manufacturing techniques. The constraint values are the safety values for the product design. The constraint values are selected from the product design specification. The product design specification values are selected from the past design calculation and some values are calculated by the help of past design data. The knowledge-based system consists of several modules such as knowledge acquisition module, inference module and user interface module. The domains of the knowledge-based system are defined as objects and linked together by hierarchical graph. The system is capable of selecting the most suitable materials and ranks the materials with respect to their properties. The design engineers can choose the required materials related to the materials property.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-09-03

We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian log-likelihood function. To overcome cubic complexity in the linear algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H-matrix technique allows us to work with general covariance matrices in an efficient way, since H-matrices can approximate inhomogeneous covariance functions, with a fairly general mesh that is not necessarily axes-parallel, and neither the covariance matrix itself nor its inverse have to be sparse. We demonstrate our method with Monte Carlo simulations and an application to soil moisture data. The C, C++ codes and data are freely available.

Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

2010-11-15

There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

Hierarchical screening for multiple mental disorders.

Science.gov (United States)

Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

2013-10-01

There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

Matrix-based introduction to multivariate data analysis

CERN Document Server

Adachi, Kohei

2016-01-01

This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter. This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on ...

Systems View on Spatial Planning and Perception Based on Invariants in Agent-Environment Dynamics

Directory of Open Access Journals (Sweden)

Berenice eMettler

2015-01-01

Full Text Available Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs, capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes.

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

RELAP-7 Code Assessment Plan and Requirement Traceability Matrix

Energy Technology Data Exchange (ETDEWEB)

Yoo, Junsoo; Choi, Yong-joon; Smith, Curtis L.

2016-10-01

The RELAP-7, a safety analysis code for nuclear reactor system, is under development at Idaho National Laboratory (INL). Overall, the code development is directed towards leveraging the advancements in computer science technology, numerical solution methods and physical models over the last decades. Recently, INL has also been putting an effort to establish the code assessment plan, which aims to ensure an improved final product quality through the RELAP-7 development process. The ultimate goal of this plan is to propose a suitable way to systematically assess the wide range of software requirements for RELAP-7, including the software design, user interface, and technical requirements, etc. To this end, we first survey the literature (i.e., international/domestic reports, research articles) addressing the desirable features generally required for advanced nuclear system safety analysis codes. In addition, the V&V (verification and validation) efforts as well as the legacy issues of several recently-developed codes (e.g., RELAP5-3D, TRACE V5.0) are investigated. Lastly, this paper outlines the Requirement Traceability Matrix (RTM) for RELAP-7 which can be used to systematically evaluate and identify the code development process and its present capability.

Hierarchical control of a photovoltaic/battery based DC microgrid including electric vehicle wireless charging station

DEFF Research Database (Denmark)

Xiao, Zhao xia; Fan, Haodong; Guerrero, Josep M.

2017-01-01

In this paper, the hierarchical control strategy of a photovoltaic/battery based dc microgrid is presented for electric vehicle (EV) wireless charging. Considering irradiance variations, battery charging/discharging requirements, wireless power transmission characteristics, and onboard battery...... coils, receiving coils and compensation capacitors, the wireless power transmission system is designed to be resonant when it is operating at the rated power, with the aim to achieve the optimum transmission system efficiency. Simulation and experimental results of the hierarchical control...... charging power change and other factors, the possible operation states are obtained. A hierarchical control strategy is established, which includes central and local controllers. The central controller is responsible for the selection and transfer of operation states and the management of the local...

In-situ formation of nanoparticles within a silicon-based matrix

Science.gov (United States)

Thoma, Steven G [Albuquerque, NM; Wilcoxon, Jess P [Albuquerque, NM; Abrams, Billie L [Albuquerque, NM

2008-06-10

A method for encapsulating nanoparticles with an encapsulating matrix that minimizes aggregation and maintains favorable properties of the nanoparticles. The matrix comprises silicon-based network-forming compounds such as ormosils and polysiloxanes. The nanoparticles are synthesized from precursors directly within the silicon-based matrix.

Newborn screening by matrix-assisted laser desorption/ionization mass spectrometry based on parylene-matrix chip.

Science.gov (United States)

Kim, Jo-Il; Noh, Joo-Yoon; Kim, Mira; Park, Jong-Min; Song, Hyun-Woo; Kang, Min-Jung; Pyun, Jae-Chul

2017-08-01

Newborn screening for diagnosis of phenylketonuria, homocystinuria, and maple syrup urine disease have been conducted by analyzing the concentration of target amino acids using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) based on parylene-matrix chip. Parylene-matrix chip was applied to MALDI-ToF MS analysis reducing the matrix peaks significantly at low mass-to-charge ratio range (m/z  0.98) and the LODs were ranging from 9.0 to 22.9 μg/mL. Effect of proteins in serum was estimated by comparing MALDI-ToF mass spectra of amino acids-spiked serum before and after the methanol extraction. Interference of other amino acids on analysis of target analyte was determined to be insignificant. From these results, MALDI-ToF MS based on parylene-matrix chip could be applicable to medical diagnosis of neonatal metabolic disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

A hierarchical approach to multi-project planning under uncertainty

NARCIS (Netherlands)

Hans, Elias W.; Herroelen, W.; Wullink, Gerhard; Leus, R.

2007-01-01

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. Based on these viewpoints we propose a positioning framework to distinguish between different types of project-driven organisations. This framework is meant to aid project

The Inquiry Matrix: A Tool for Assessing and Planning Inquiry in Biology and Beyond

Science.gov (United States)

Grady, Julie

2010-01-01

One way to advance inquiry in the classroom is to establish a systematic strategy for reflecting on our practice and our students' readiness to engage in increasingly complex scientific reasoning. The Matrix for Assessing and Planning Scientific Inquiry (MAPSI) is a tool that promotes this valuable reflection so that we, as teachers, are better…

The Impact of Standards-Based Reform: Applying Brantlinger's Critique of "Hierarchical Ideologies"

Science.gov (United States)

Bacon, Jessica; Ferri, Beth

2013-01-01

Brantlinger's [2004b. "Ideologies Discerned, Values Determined: Getting past the Hierarchies of Special Education." In "Ideology and the Politics of (in)Exclusion," edited by L. Ware, 11-31. New York: Peter Lang Publishing] critique of hierarchical ideologies lays bare the logics embedded in standards-based reform. Drawing on…

Hierarchical architecture of active knits

International Nuclear Information System (INIS)

Abel, Julianna; Luntz, Jonathan; Brei, Diann

2013-01-01

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. (paper)

Parallel content-based sub-image retrieval using hierarchical searching.

Science.gov (United States)

Yang, Lin; Qi, Xin; Xing, Fuyong; Kurc, Tahsin; Saltz, Joel; Foran, David J

2014-04-01

The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/.

Mean deformation metrics for quantifying 3D cell–matrix interactions without requiring information about matrix material properties

Science.gov (United States)

Stout, David A.; Bar-Kochba, Eyal; Estrada, Jonathan B.; Toyjanova, Jennet; Kesari, Haneesh; Reichner, Jonathan S.; Franck, Christian

2016-01-01

Mechanobiology relates cellular processes to mechanical signals, such as determining the effect of variations in matrix stiffness with cell tractions. Cell traction recorded via traction force microscopy (TFM) commonly takes place on materials such as polyacrylamide- and polyethylene glycol-based gels. Such experiments remain limited in physiological relevance because cells natively migrate within complex tissue microenvironments that are spatially heterogeneous and hierarchical. Yet, TFM requires determination of the matrix constitutive law (stress–strain relationship), which is not always readily available. In addition, the currently achievable displacement resolution limits the accuracy of TFM for relatively small cells. To overcome these limitations, and increase the physiological relevance of in vitro experimental design, we present a new approach and a set of associated biomechanical signatures that are based purely on measurements of the matrix's displacements without requiring any knowledge of its constitutive laws. We show that our mean deformation metrics (MDM) approach can provide significant biophysical information without the need to explicitly determine cell tractions. In the process of demonstrating the use of our MDM approach, we succeeded in expanding the capability of our displacement measurement technique such that it can now measure the 3D deformations around relatively small cells (∼10 micrometers), such as neutrophils. Furthermore, we also report previously unseen deformation patterns generated by motile neutrophils in 3D collagen gels. PMID:26929377

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.

A proposal for a global task planning architecture using the RoboEarth cloud based framework

OpenAIRE

Janssen, R.J.M.; Molengraft, van de, M.J.G.; Steinbuch, M.; Di Marco, D.; Zweigle, O.; Levi, P.; Py, F.; Musliner, D.

2012-01-01

As robotic systems become more and more capable of assisting in human domains, methods are sought to compose robot executable plans from abstract human instructions. To cope with the semantically rich and highly expressive nature of human instructions, Hierarchical Task Network planning is often being employed along with domain knowledge to solve planning problems in a pragmatic way. Commonly, the domain knowledge is specific to the planning problem at hand, impeding re-use. Therefore this pa...

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

Science.gov (United States)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Hierarchical three-dimensional porous SnS{sub 2}/carbon cloth anode for high-performance lithium ion batteries

Energy Technology Data Exchange (ETDEWEB)

Chao, Junfeng, E-mail: chchjjff@163.com [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China); Zhang, Xiutai [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China); Xing, Shumin [College of Mathematics and Physics, Anyang Institute of Technology, Anyang 455000 (China); Fan, Qiufeng; Yang, Junping; Zhao, Luhua; Li, Xiang [College of Electronic Information and Electric Engineering, Anyang Institute of Technology, Anyang 455000 (China)

2016-08-15

Graphical abstract: Hierarchical 3D porous SnS{sub 2}/carbon cloth, good electrochemical performance. - Highlights: • Hierarchical 3D porous SnS{sub 2}/carbon cloth has been firstly synthesized. • The SnS{sub 2}/carbon clothes were good candidates for excellent lithium ion batteries. • The SnS{sub 2}/carbon cloth exhibits improved capacity compared to pure SnS{sub 2}. - Abstract: Hierarchical three-dimension (3D) porous SnS{sub 2}/carbon clothes were synthesized via a facile polyol refluxing process. The as-synthesized samples were characterized by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmet–Teller (BET) and UV–vis diffuse reflectance spectrometer (UV–vis DRS). The 3D porous SnS{sub 2}/carbon clothes-based lithium ion batteries exhibited high reversible capacity and good rate capability as anode materials. The good electrochemical performance for lithium ion storage could be attributed to the special nanostructure, leading to high-rate transportation of electrolyte ion and electrons throughout the electrode matrix.

Acid-base-driven matrix-assisted mass spectrometry for targeted metabolomics

Czech Academy of Sciences Publication Activity Database

Shroff, R.; Rulíšek, Lubomír; Doubský, J.; Svatoš, Aleš

2009-01-01

Roč. 106, č. 25 (2009), s. 10092-10096 ISSN 0027-8424 R&D Projects: GA MŠk LC512 Institutional research plan: CEZ:AV0Z40550506 Keywords : clinical diagnostic * matrix design * positive/negative ions * MALDI Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 9.432, year: 2009

The ground based plan

International Nuclear Information System (INIS)

1989-01-01

The paper presents a report of ''The Ground Based Plan'' of the United Kingdom Science and Engineering Research Council. The ground based plan is a plan for research in astronomy and planetary science by ground based techniques. The contents of the report contains a description of:- the scientific objectives and technical requirements (the basis for the Plan), the present organisation and funding for the ground based programme, the Plan, the main scientific features and the further objectives of the Plan. (U.K.)

The Mission Operations Planning Assistant

Science.gov (United States)

Schuetzle, James G.

1987-01-01

The Mission Operations Planning Assistant (MOPA) is a knowledge-based system developed to support the planning and scheduling of instrument activities on the Upper Atmospheric Research Satellite (UARS). The MOPA system represents and maintains instrument plans at two levels of abstraction in order to keep plans comprehensible to both UARS Principal Investigators and Command Management personnel. The hierarchical representation of plans also allows MOPA to automatically create detailed instrument activity plans from which spacecraft command loads may be generated. The MOPA system was developed on a Symbolics 3640 computer using the ZetaLisp and ART languages. MOPA's features include a textual and graphical interface for plan inspection and modification, recognition of instrument operational constraint violations during the planning process, and consistency maintenance between the different planning levels. This paper describes the current MOPA system.

Flexible supercapacitors with high areal capacitance based on hierarchical carbon tubular nanostructures

Science.gov (United States)

Zhang, Haitao; Su, Hai; Zhang, Lei; Zhang, Binbin; Chun, Fengjun; Chu, Xiang; He, Weidong; Yang, Weiqing

2016-11-01

Hierarchical structure design can greatly enhance the unique properties of primary material(s) but suffers from complicated preparation process and difficult self-assembly of materials with different dimensionalities. Here we report on the growth of single carbon tubular nanostructures with hierarchical structure (hCTNs) through a simple method based on direct conversion of carbon dioxide. Resorting to in-situ transformation and self-assembly of carbon micro/nano-structures, the obtained hCTNs are blood-like multichannel hierarchy composed of one large channel across the hCTNs and plenty of small branches connected to each other. Due to the unique pore structure and high surface area, these hCTN-based flexible supercapacitors possess the highest areal capacitance of ∼320 mF cm-2, as well as good rate-capability and excellent cycling stability (95% retention after 2500 cycles). It was established that this method can control the morphology, size, and density of hCTNs and effectively construct hCTNs well anchored to the various substrates. Our work unambiguously demonstrated the potential of hCTNs for large flexible supercapacitors and integrated energy management electronics.

Fabrication and biocompatibility of poly(L-lactic acid) and chitosan composite scaffolds with hierarchical microstructures

Energy Technology Data Exchange (ETDEWEB)

Lou, Tao, E-mail: taolou72@aliyun.com [College of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071 (China); Wang, Xuejun [College of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071 (China); Yan, Xu [College of Physics & Collaborative Innovation Center for Low-Dimensional Nanomaterials and Optoelectronic Devices, Qingdao University, Qingdao 266071 (China); Miao, Yu [Department of Mechanical Engineering, Columbia University, New York, NY 10027 (United States); Long, Yun-Ze, E-mail: yunzelong@163.com [College of Physics & Collaborative Innovation Center for Low-Dimensional Nanomaterials and Optoelectronic Devices, Qingdao University, Qingdao 266071 (China); Yin, Hai-Lei [Department of Osteology, No. 401 Hospital of P. L. A., Qingdao 266071 (China); Sun, Bin [College of Physics & Collaborative Innovation Center for Low-Dimensional Nanomaterials and Optoelectronic Devices, Qingdao University, Qingdao 266071 (China); Song, Guojun [College of Chemistry and Chemical Engineering, Qingdao University, Qingdao 266071 (China)

2016-07-01

The scaffold microstructure is crucial to reconstruct tissue normal functions. In this article, poly(L-lactic acid) and chitosan fiber (PLLA/CTSF) composite scaffolds with hierarchical microstructures both in fiber and pore sizes were successfully fabricated by combining thermal induced phase separation and salt leaching techniques. The composite scaffolds consisted of a nanofibrous PLLA matrix with diameter of 50–500 nm, and chitosan fibers with diameter of about 20 μm were homogenously distributed in the PLLA matrix as a microsized reinforcer. The composite scaffolds also had high porosity (> 94%) and hierarchical pore size, which were consisted of both micropores (50 nm–10 μm) and macropores (50–300 μm). By tailoring the microstructure and chemical composition, the mechanical property, pH buffer and protein adsorption capacity of the composite scaffold were improved significantly compared with those of PLLA scaffold. Cell culture results also revealed that the PLLA/CTSF composite scaffolds supported MG-63 osteoblast proliferation and penetration. - Highlights: • Composite scaffolds fabricated by combining thermal induced phase separation and salt leaching techniques • Hierarchical microstructure both in fiber and pore sizes • The scaffold microenvironment facilitates the protein adsorption, cell proliferation and penetration.

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

Science.gov (United States)

Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

2018-05-01

Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets

Directory of Open Access Journals (Sweden)

Janusz Dudczyk

2016-01-01

Full Text Available More advanced recognition methods, which may recognize particular copies of radars of the same type, are called identification. The identification process of radar devices is a more specialized task which requires methods based on the analysis of distinctive features. These features are distinguished from the signals coming from the identified devices. Such a process is called Specific Emitter Identification (SEI. The identification of radar emission sources with the use of classic techniques based on the statistical analysis of basic measurable parameters of a signal such as Radio Frequency, Amplitude, Pulse Width, or Pulse Repetition Interval is not sufficient for SEI problems. This paper presents the method of hierarchical data clustering which is used in the process of radar identification. The Hierarchical Agglomerative Clustering Algorithm (HACA based on Generalized Agglomerative Scheme (GAS implemented and used in the research method is parameterized; therefore, it is possible to compare the results. The results of clustering are presented in dendrograms in this paper. The received results of grouping and identification based on HACA are compared with other SEI methods in order to assess the degree of their usefulness and effectiveness for systems of ESM/ELINT class.

Refractive index inversion based on Mueller matrix method

Science.gov (United States)

Fan, Huaxi; Wu, Wenyuan; Huang, Yanhua; Li, Zhaozhao

2016-03-01

Based on Stokes vector and Jones vector, the correlation between Mueller matrix elements and refractive index was studied with the result simplified, and through Mueller matrix way, the expression of refractive index inversion was deduced. The Mueller matrix elements, under different incident angle, are simulated through the expression of specular reflection so as to analyze the influence of the angle of incidence and refractive index on it, which is verified through the measure of the Mueller matrix elements of polished metal surface. Research shows that, under the condition of specular reflection, the result of Mueller matrix inversion is consistent with the experiment and can be used as an index of refraction of inversion method, and it provides a new way for target detection and recognition technology.

Aerial surveillance based on hierarchical object classification for ground target detection

Science.gov (United States)

Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

2015-03-01

Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

Hierarchical finite element modeling of SiCp/Al2124 T4 composites with dislocation plasticity and size dependent failure

International Nuclear Information System (INIS)

Suh, Yeong Sung; Kim, Yong Bae

2012-01-01

The strength of particle reinforced metal matrix composites is, in general, known to be increased by the geometrically necessary dislocations punched around a particle that form during cooling after consolidation because of coefficient of thermal expansion (CTE) mismatch between the particle and the matrix. An additional strength increase may also be observed, since another type of geometrically necessary dislocation can be formed during extensive deformation as a result of the strain gradient plasticity due to the elastic plastic mismatch between the particle and the matrix. In this paper, the magnitudes of these two types of dislocations are calculated based on the dislocation plasticity. The dislocations are then converted to the respective strengths and allocated hierarchically to the matrix around the particle in the axisymmetric finite element unit cell model. the proposed method is shown to be very effective by performing finite element strength analysis of SiC p /Al2124 T4 composites that included ductile in the matrix and particle matrix decohesion. The predicted results for different particle sizes and volume fractions show that the length scale effect of the particle size obviously affects the strength and failure behavior of the particle reinforced metal matrix composites

Hierarchical and successive approximate registration of the non-rigid medical image based on thin-plate splines

Science.gov (United States)

Hu, Jinyan; Li, Li; Yang, Yunfeng

2017-06-01

The hierarchical and successive approximate registration method of non-rigid medical image based on the thin-plate splines is proposed in the paper. There are two major novelties in the proposed method. First, the hierarchical registration based on Wavelet transform is used. The approximate image of Wavelet transform is selected as the registered object. Second, the successive approximation registration method is used to accomplish the non-rigid medical images registration, i.e. the local regions of the couple images are registered roughly based on the thin-plate splines, then, the current rough registration result is selected as the object to be registered in the following registration procedure. Experiments show that the proposed method is effective in the registration process of the non-rigid medical images.

Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis

Science.gov (United States)

Krozel, James A.

1988-01-01

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

Hierarchical virtual screening approaches in small molecule drug discovery.

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Matrix-based image reconstruction methods for tomography

International Nuclear Information System (INIS)

Llacer, J.; Meng, J.D.

1984-10-01

Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

Hierarchical Co-based Porous Layered Double Hydroxide Arrays Derived via Alkali Etching for High-performance Supercapacitors

Science.gov (United States)

Abushrenta, Nasser; Wu, Xiaochao; Wang, Junnan; Liu, Junfeng; Sun, Xiaoming

2015-08-01

Hierarchical nanoarchitecture and porous structure can both provide advantages for improving the electrochemical performance in energy storage electrodes. Here we report a novel strategy to synthesize new electrode materials, hierarchical Co-based porous layered double hydroxide (PLDH) arrays derived via alkali etching from Co(OH)2@CoAl LDH nanoarrays. This structure not only has the benefits of hierarchical nanoarrays including short ion diffusion path and good charge transport, but also possesses a large contact surface area owing to its porous structure which lead to a high specific capacitance (23.75 F cm-2 or 1734 F g-1 at 5 mA cm-2) and excellent cycling performance (over 85% after 5000 cycles). The enhanced electrode material is a promising candidate for supercapacitors in future application.

Research on a Hierarchical Dynamic Automatic Voltage Control System Based on the Discrete Event-Driven Method

Directory of Open Access Journals (Sweden)

Yong Min

2013-06-01

Full Text Available In this paper, concepts and methods of hybrid control systems are adopted to establish a hierarchical dynamic automatic voltage control (HD-AVC system, realizing the dynamic voltage stability of power grids. An HD-AVC system model consisting of three layers is built based on the hybrid control method and discrete event-driven mechanism. In the Top Layer, discrete events are designed to drive the corresponding control block so as to avoid solving complex multiple objective functions, the power system’s characteristic matrix is formed and the minimum amplitude eigenvalue (MAE is calculated through linearized differential-algebraic equations. MAE is applied to judge the system’s voltage stability and security and construct discrete events. The Middle Layer is responsible for management and operation, which is also driven by discrete events. Control values of the control buses are calculated based on the characteristics of power systems and the sensitivity method. Then control values generate control strategies through the interface block. In the Bottom Layer, various control devices receive and implement the control commands from the Middle Layer. In this way, a closed-loop power system voltage control is achieved. Computer simulations verify the validity and accuracy of the HD-AVC system, and verify that the proposed HD-AVC system is more effective than normal voltage control methods.

Biased trapping issue on weighted hierarchical networks

Indian Academy of Sciences (India)

archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

Recurrence quantity analysis based on matrix eigenvalues

Science.gov (United States)

Yang, Pengbo; Shang, Pengjian

2018-06-01

Recurrence plots is a powerful tool for visualization and analysis of dynamical systems. Recurrence quantification analysis (RQA), based on point density and diagonal and vertical line structures in the recurrence plots, is considered to be alternative measures to quantify the complexity of dynamical systems. In this paper, we present a new measure based on recurrence matrix to quantify the dynamical properties of a given system. Matrix eigenvalues can reflect the basic characteristics of the complex systems, so we show the properties of the system by exploring the eigenvalues of the recurrence matrix. Considering that Shannon entropy has been defined as a complexity measure, we propose the definition of entropy of matrix eigenvalues (EOME) as a new RQA measure. We confirm that EOME can be used as a metric to quantify the behavior changes of the system. As a given dynamical system changes from a non-chaotic to a chaotic regime, the EOME will increase as well. The bigger EOME values imply higher complexity and lower predictability. We also study the effect of some factors on EOME,including data length, recurrence threshold, the embedding dimension, and additional noise. Finally, we demonstrate an application in physiology. The advantage of this measure lies in a high sensitivity and simple computation.

LANDSCAPE PLANNING IN UKRAINE: THE FIRST LANDSCAPE-PLANNING PROGRAM

Directory of Open Access Journals (Sweden)

Leonid Rudenko

2013-01-01

Full Text Available The paper presents the results of the first, in Ukraine; project on landscape planning widely accepted in European countries. Under the project implemented in 2010–2013, a landscape-planning program has been developed for the Cherkassy oblast. This is the first document of this kind in Ukraine. The program is mainly based on the experience of the German and Russian schools of landscape planning and on research and assessment conducted by the authors, which allowed identifying approaches to landscape planning, principles of the national policy, and characteristics and potential of environmentally friendly planning in Ukraine. The paper discusses the main phases of the work on the development of the landscape program for the oblast. It also identifies the main stages and key concepts and principles of landscape planning. The paper presents the results of integrated research on the identification and classification of conflicts in land use and the integral concept of the developmental goals for the oblast. The results can be the foundation for adopting management decisions and development of action plans for the lower hierarchal branches.

Hierarchical and Non-Hierarchical Linear and Non-Linear Clustering Methods to “Shakespeare Authorship Question”

Directory of Open Access Journals (Sweden)

Refat Aljumily

2015-09-01

Full Text Available A few literary scholars have long claimed that Shakespeare did not write some of his best plays (history plays and tragedies and proposed at one time or another various suspect authorship candidates. Most modern-day scholars of Shakespeare have rejected this claim, arguing that strong evidence that Shakespeare wrote the plays and poems being his name appears on them as the author. This has caused and led to an ongoing scholarly academic debate for quite some long time. Stylometry is a fast-growing field often used to attribute authorship to anonymous or disputed texts. Stylometric attempts to resolve this literary puzzle have raised interesting questions over the past few years. The following paper contributes to “the Shakespeare authorship question” by using a mathematically-based methodology to examine the hypothesis that Shakespeare wrote all the disputed plays traditionally attributed to him. More specifically, the mathematically based methodology used here is based on Mean Proximity, as a linear hierarchical clustering method, and on Principal Components Analysis, as a non-hierarchical linear clustering method. It is also based, for the first time in the domain, on Self-Organizing Map U-Matrix and Voronoi Map, as non-linear clustering methods to cover the possibility that our data contains significant non-linearities. Vector Space Model (VSM is used to convert texts into vectors in a high dimensional space. The aim of which is to compare the degrees of similarity within and between limited samples of text (the disputed plays. The various works and plays assumed to have been written by Shakespeare and possible authors notably, Sir Francis Bacon, Christopher Marlowe, John Fletcher, and Thomas Kyd, where “similarity” is defined in terms of correlation/distance coefficient measure based on the frequency of usage profiles of function words, word bi-grams, and character triple-grams. The claim that Shakespeare authored all the disputed

Discovering hierarchical structure in normal relational data

DEFF Research Database (Denmark)

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

2014-01-01

-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional...

Maslow and Motherboards: Taking a Hierarchical View of Technology Planning.

Science.gov (United States)

Johnson, Doug

2003-01-01

Presents a planning model for educational uses of technology that is based on Maslow's hierarchy of needs. Topics include established infrastructure; effective administration; extensive resources; enhanced teaching, including creating distance learning opportunities; empowered students, including evaluation methods and information literacy skills;…

Titanium-Phosphonate-Based Metal-Organic Frameworks with Hierarchical Porosity for Enhanced Photocatalytic Hydrogen Evolution

KAUST Repository

Li, Hui

2018-02-01

Photocatalytic hydrogen production is crucial for solar-to-chemical conversion process, wherein high-efficiency photocatalysts lie in the heart of this area. Herein a new photocatalyst of hierarchically mesoporous titanium-phosphonate-based metal-organic frameworks, featuring well-structured spheres, periodic mesostructure and large secondary mesoporosity, are rationally designed with the complex of polyelectrolyte and cathodic surfactant serving as the template. The well-structured hierarchical porosity and homogeneously incorporated phosphonate groups can favor the mass transfer and strong optical absorption during the photocatalytic reactions. Correspondingly, the titanium phosphonates exhibit significantly improved photocatalytic hydrogen evolution rate along with impressive stability. This work can provide more insights into designing advanced photocatalysts for energy conversion and render a tunable platform in photoelectrochemical field.

Titanium-Phosphonate-Based Metal-Organic Frameworks with Hierarchical Porosity for Enhanced Photocatalytic Hydrogen Evolution

KAUST Repository

Li, Hui; Sun, Ying; Yuan, Zhong-Yong; Zhu, Yun-Pei; Ma, Tianyi

2018-01-01

Photocatalytic hydrogen production is crucial for solar-to-chemical conversion process, wherein high-efficiency photocatalysts lie in the heart of this area. Herein a new photocatalyst of hierarchically mesoporous titanium-phosphonate-based metal-organic frameworks, featuring well-structured spheres, periodic mesostructure and large secondary mesoporosity, are rationally designed with the complex of polyelectrolyte and cathodic surfactant serving as the template. The well-structured hierarchical porosity and homogeneously incorporated phosphonate groups can favor the mass transfer and strong optical absorption during the photocatalytic reactions. Correspondingly, the titanium phosphonates exhibit significantly improved photocatalytic hydrogen evolution rate along with impressive stability. This work can provide more insights into designing advanced photocatalysts for energy conversion and render a tunable platform in photoelectrochemical field.

Hierarchical structure of genetic distances: Effects of matrix size, spatial distribution and correlation structure among gene frequencies

Directory of Open Access Journals (Sweden)

Flávia Melo Rodrigues

1998-06-01

Full Text Available Geographic structure of genetic distances among local populations within species, based on allozyme data, has usually been evaluated by estimating genetic distances clustered with hierarchical algorithms, such as the unweighted pair-group method by arithmetic averages (UPGMA. The distortion produced in the clustering process is estimated by the cophenetic correlation coefficient. This hierarchical approach, however, can fail to produce an accurate representation of genetic distances among populations in a low dimensional space, especially when continuous (clinal or reticulate patterns of variation exist. In the present study, we analyzed 50 genetic distance matrices from the literature, for animal taxa ranging from Platyhelminthes to Mammalia, in order to determine in which situations the UPGMA is useful to understand patterns of genetic variation among populations. The cophenetic correlation coefficients, derived from UPGMA based on three types of genetic distance coefficients, were correlated with other parameters of each matrix, including number of populations, loci, alleles, maximum geographic distance among populations, relative magnitude of the first eigenvalue of covariance matrix among alleles and logarithm of body size. Most cophenetic correlations were higher than 0.80, and the highest values appeared for Nei's and Rogers' genetic distances. The relationship between cophenetic correlation coefficients and the other parameters analyzed was defined by an "envelope space", forming triangles in which higher values of cophenetic correlations are found for higher values in the parameters, though low values do not necessarily correspond to high cophenetic correlations. We concluded that UPGMA is useful to describe genetic distances based on large distance matrices (both in terms of elevated number of populations or alleles, when dimensionality of the system is low (matrices with large first eigenvalues or when local populations are separated

Beyond Creation of Mesoporosity: The Advantages of Polymer-Based Dual-Function Templates for Fabricating Hierarchical Zeolites

KAUST Repository

Tian, Qiwei

2016-02-05

Direct synthesis of hierarchical zeolites currently relies on the use of surfactant-based templates to produce mesoporosity by the random stacking of 2D zeolite sheets or the agglomeration of tiny zeolite grains. The benefits of using nonsurfactant polymers as dual-function templates in the fabrication of hierarchical zeolites are demonstrated. First, the minimal intermolecular interactions of nonsurfactant polymers impose little interference on the crystallization of zeolites, favoring the formation of 3D continuous zeolite frameworks with a long-range order. Second, the mutual interpenetration of the polymer and the zeolite networks renders disordered but highly interconnected mesopores in zeolite crystals. These two factors allow for the synthesis of single-crystalline, mesoporous zeolites of varied compositions and framework types. A representative example, hierarchial aluminosilicate (meso-ZSM-5), has been carefully characterized. It has a unique branched fibrous structure, and far outperforms bulk aluminosilicate (ZSM-5) as a catalyst in two model reactions: conversion of methanol to aromatics and catalytic cracking of canola oil. Third, extra functional groups in the polymer template can be utilized to incorporate desired functionalities into hierarchical zeolites. Last and most importantly, polymer-based templates permit heterogeneous nucleation and growth of mesoporous zeolites on existing surfaces, forming a continuous zeolitic layer. In a proof-of-concept experiment, unprecedented core-shell-structured hierarchical zeolites are synthesized by coating mesoporous zeolites on the surfaces of bulk zeolites. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Hierarchical Reliability Control Method for a Space Manipulator Based on the Strategy of Autonomous Decision-Making

Directory of Open Access Journals (Sweden)

Xin Gao

2016-01-01

Full Text Available In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on this, a multivariable and multiconstraint optimization model is constructed. Second, a hierarchical system control model which incorporates the operational reliability factors is constructed. The control process of the space manipulator is divided into three layers: task planning, path planning, and motion control. Operational reliability related performance parameters are measured and used as the system’s feedback. Taking the factors affecting the operational reliability into consideration, the system can autonomously decide which control layer of the system should be optimized and how to optimize it using a control level adjustment decision module. The operational reliability factors affect these three control levels in the form of control variable constraints. Simulation results demonstrate that the proposed method can achieve a greater probability of meeting the task accuracy requirements, while extending the expected lifetime of the space manipulator.

Improved Adhesion and Compliancy of Hierarchical Fibrillar Adhesives.

Science.gov (United States)

Li, Yasong; Gates, Byron D; Menon, Carlo

2015-08-05

The gecko relies on van der Waals forces to cling onto surfaces with a variety of topography and composition. The hierarchical fibrillar structures on their climbing feet, ranging from mesoscale to nanoscale, are hypothesized to be key elements for the animal to conquer both smooth and rough surfaces. An epoxy-based artificial hierarchical fibrillar adhesive was prepared to study the influence of the hierarchical structures on the properties of a dry adhesive. The presented experiments highlight the advantages of a hierarchical structure despite a reduction of overall density and aspect ratio of nanofibrils. In contrast to an adhesive containing only nanometer-size fibrils, the hierarchical fibrillar adhesives exhibited a higher adhesion force and better compliancy when tested on an identical substrate.

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

Directory of Open Access Journals (Sweden)

Guangwei Gao

Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

Cartilage extracellular matrix as a biomaterial for cartilage regeneration.

Science.gov (United States)

Kiyotake, Emi A; Beck, Emily C; Detamore, Michael S

2016-11-01

The extracellular matrix (ECM) of various tissues possesses the model characteristics that biomaterials for tissue engineering strive to mimic; however, owing to the intricate hierarchical nature of the ECM, it has yet to be fully characterized and synthetically fabricated. Cartilage repair remains a challenge because the intrinsic properties that enable its durability and long-lasting function also impede regeneration. In the last decade, cartilage ECM has emerged as a promising biomaterial for regenerating cartilage, partly because of its potentially chondroinductive nature. As this research area of cartilage matrix-based biomaterials emerged, investigators facing similar challenges consequently developed convergent solutions in constructing robust and bioactive scaffolds. This review discusses the challenges, emerging trends, and future directions of cartilage ECM scaffolds, including a comparison between two different forms of cartilage matrix: decellularized cartilage (DCC) and devitalized cartilage (DVC). To overcome the low permeability of cartilage matrix, physical fragmentation greatly enhances decellularization, although the process itself may reduce the chondroinductivity of fabricated scaffolds. The less complex processing of a scaffold composed of DVC, which has not been decellularized, appears to have translational advantages and potential chondroinductive and mechanical advantages over DCC, without detrimental immunogenicity, to ultimately enhance cartilage repair in a clinically relevant way. © 2016 New York Academy of Sciences.

Implementation of a Monte Carlo based inverse planning model for clinical IMRT with MCNP code

International Nuclear Information System (INIS)

He, Tongming Tony

2003-01-01

Inaccurate dose calculations and limitations of optimization algorithms in inverse planning introduce systematic and convergence errors to treatment plans. This work was to implement a Monte Carlo based inverse planning model for clinical IMRT aiming to minimize the aforementioned errors. The strategy was to precalculate the dose matrices of beamlets in a Monte Carlo based method followed by the optimization of beamlet intensities. The MCNP 4B (Monte Carlo N-Particle version 4B) code was modified to implement selective particle transport and dose tallying in voxels and efficient estimation of statistical uncertainties. The resulting performance gain was over eleven thousand times. Due to concurrent calculation of multiple beamlets of individual ports, hundreds of beamlets in an IMRT plan could be calculated within a practical length of time. A finite-sized point source model provided a simple and accurate modeling of treatment beams. The dose matrix calculations were validated through measurements in phantoms. Agreements were better than 1.5% or 0.2 cm. The beamlet intensities were optimized using a parallel platform based optimization algorithm that was capable of escape from local minima and preventing premature convergence. The Monte Carlo based inverse planning model was applied to clinical cases. The feasibility and capability of Monte Carlo based inverse planning for clinical IMRT was demonstrated. Systematic errors in treatment plans of a commercial inverse planning system were assessed in comparison with the Monte Carlo based calculations. Discrepancies in tumor doses and critical structure doses were up to 12% and 17%, respectively. The clinical importance of Monte Carlo based inverse planning for IMRT was demonstrated

Coralline-Like N-Doped Hierarchically Porous Carbon Derived from Enteromorpha as a Host Matrix for Lithium-Sulfur Battery.

Science.gov (United States)

Ji, Shengnan; Imtiaz, Sumair; Sun, Dan; Xin, Ying; Li, Qian; Huang, Taizhong; Zhang, Zhaoliang; Huang, Yunhui

2017-12-22

Coralline-like N-doped hierarchically porous carbon (CNHPC) was prepared through a hydrothermal carbonization process using a sea pollutant enteromorpha as the starting material. The addition of a small amount of glucose during carbonization improved the yield of carbon, and the inherent N contents, especially for pyrrolic N and pyridinic N atoms. After loading 40 wt. % sulfur, the CNHPC/S composite, as a cathode in a Li-S battery, exhibited an initial discharge capacity of 1617 mAh g -1 (96.5 % of theoretical capacity) at 0.1 C and a capacity loss of 0.05 % per charge-discharge cycle after 500 cycles at 0.5 C with a stable Coulombic efficiency of 100 % in carbonate based electrolyte. Such a great performance can be attributed to the coralline-like hierarchically porous infrastructure and inherently abundant N doping. Given the conversion of waste pollutants into valuable energy-storage materials and the easy process, this work features a promising approach to prepare C/S cathodes for Li-S batteries. The special structural and textural characteristics of CNHPC might be attractive to other practical applications such as supercapacitors and catalysis. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Superhydrophobic surface based on a coral-like hierarchical structure of ZnO.

Directory of Open Access Journals (Sweden)

Jun Wu

2010-12-01

Full Text Available Fabrication of superhydrophobic surfaces has attracted much interest in the past decade. The fabrication methods that have been studied are chemical vapour deposition, the sol-gel method, etching technique, electrochemical deposition, the layer-by-layer deposition, and so on. Simple and inexpensive methods for manufacturing environmentally stable superhydrophobic surfaces have also been proposed lately. However, work referring to the influence of special structures on the wettability, such as hierarchical ZnO nanostructures, is rare.This study presents a simple and reproducible method to fabricate a superhydrophobic surface with micro-scale roughness based on zinc oxide (ZnO hierarchical structure, which is grown by the hydrothermal method with an alkaline aqueous solution. Coral-like structures of ZnO were fabricated on a glass substrate with a micro-scale roughness, while the antennas of the coral formed the nano-scale roughness. The fresh ZnO films exhibited excellent superhydrophilicity (the apparent contact angle for water droplet was about 0°, while the ability to be wet could be changed to superhydrophobicity after spin-coating Teflon (the apparent contact angle greater than 168°. The procedure reported here can be applied to substrates consisting of other materials and having various shapes.The new process is convenient and environmentally friendly compared to conventional methods. Furthermore, the hierarchical structure generates the extraordinary solid/gas/liquid three-phase contact interface, which is the essential characteristic for a superhydrophobic surface.

Superhydrophobic hierarchical arrays fabricated by a scalable colloidal lithography approach.

Science.gov (United States)

Kothary, Pratik; Dou, Xuan; Fang, Yin; Gu, Zhuxiao; Leo, Sin-Yen; Jiang, Peng

2017-02-01

Here we report an unconventional colloidal lithography approach for fabricating a variety of periodic polymer nanostructures with tunable geometries and hydrophobic properties. Wafer-sized, double-layer, non-close-packed silica colloidal crystal embedded in a polymer matrix is first assembled by a scalable spin-coating technology. The unusual non-close-packed crystal structure combined with a thin polymer film separating the top and the bottom colloidal layers render great versatility in templating periodic nanostructures, including arrays of nanovoids, nanorings, and hierarchical nanovoids. These different geometries result in varied fractions of entrapped air in between the templated nanostructures, which in turn lead to different apparent water contact angles. Superhydrophobic surfaces with >150° water contact angles and <5° contact angle hysteresis are achieved on fluorosilane-modified polymer hierarchical nanovoid arrays with large fractions of entrapped air. The experimental contact angle measurements are complemented with theoretical predictions using the Cassie's model to gain insights into the fundamental microstructure-dewetting property relationships. The experimental and theoretical contact angles follow the same trends as determined by the unique hierarchical structures of the templated periodic arrays. Copyright © 2016 Elsevier Inc. All rights reserved.

An enhanced hierarchical control strategy for the Internet of Things-based home scale microgrid

DEFF Research Database (Denmark)

Guan, Yajuan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

2017-01-01

As the intelligent control and detection technology improving, more and more smart devices/sensors can be used to increase the living standard. In order to integrate the Internet of Things (IoT) with microgrid (MG), an enhanced hierarchical control strategy for IoT-based home scale MG is proposed...

Delocalization transition for the Google matrix.

Science.gov (United States)

Giraud, Olivier; Georgeot, Bertrand; Shepelyansky, Dima L

2009-08-01

We study the localization properties of eigenvectors of the Google matrix, generated both from the world wide web and from the Albert-Barabási model of networks. We establish the emergence of a delocalization phase for the PageRank vector when network parameters are changed. For networks with localized PageRank, eigenvalues of the matrix in the complex plane with a modulus above a certain threshold correspond to localized eigenfunctions while eigenvalues below this threshold are associated with delocalized relaxation modes. We argue that, for networks with delocalized PageRank, the efficiency of information retrieval by Google-type search is strongly affected since the PageRank values have no clear hierarchical structure in this case.

Hierarchical porous photoanode based on acid boric catalyzed sol for dye sensitized solar cells

Energy Technology Data Exchange (ETDEWEB)

Maleki, Khatereh [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Abdizadeh, Hossein [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Center of Excellence for High Performance Materials, University of Tehran, Tehran (Iran, Islamic Republic of); Golobostanfard, Mohammad Reza, E-mail: Mohammadreza.Golbostanfard@gmail.com [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of); Adelfar, Razieh [School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, P.O. Box: 14395-553, Tehran (Iran, Islamic Republic of)

2017-02-01

Highlights: • Acid boric can thoroughly leads to the hierarchical porous titania structure. • Boron is introduced into titania lattice which causes slight blueshift of bandgap. • The optimized sol parameters are H{sub 3}BO{sub 3}/TTiP = 0.45, DI/TTiP = 4.5, and 0.17 M. • Optimized paste parameters is not changed compared to conventional pastes. • The DSSC based on H{sub 3}BO{sub 3} catalyzed sol shows promising efficiency of 2.91%. - Abstract: The hierarchical porous photoanode of the dye sensitized solar cell (DSSC) is synthesized through non-aqueous sol-gel method based on H{sub 3}BO{sub 3} as an acid catalyst and the efficiencies of the fabricated DSSC based on these photoanodes are compared. The sol parameters of 0.17 M, water mole ratio of 4.5, acid mole ratio of 0.45, and solvent type of ethanol are introduced as optimum parameters for photoanode formation without any detectable cracks. The optimized hierarchical photoanode mainly contains anatase phase with slight shift toward higher angles, confirming the doping of boron into titania structure. Moreover, the porous structure involves two ranges of average pore sizes of 20 and 635 nm. The diffuse reflectance spectroscopy (DRS) shows the proper scattering and blueshift in band gap. The paste parameters of solid:liquid, TiO{sub 2}:ethyl cellulose, and terpineol:ethanol equal to 11:89, 3.5:7.5, and 25:64, respectively, are assigned as optimized parameters for this novel paste. The photovoltaic properties of short circuit current density, open circuit voltage, fill factor, and efficiency of 5.89 mA/cm{sup 2}, 703 mV, 0.7, and 2.91% are obtained for the optimized sample, respectively. The relatively higher short circuit current of the main sample compared to other samples is mainly due to higher dye adsorption in this sample corresponding to its higher surface area and presumably higher charge transfer confirmed by low R{sub S} and R{sub ct} in electrochemical impedance spectroscopy data. Boric acid as

Deliberate change without hierarchical influence?

DEFF Research Database (Denmark)

Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

2017-01-01

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...

Survival of contact processes on the hierarchical group

Czech Academy of Sciences Publication Activity Database

Athreya, S.R.; Swart, Jan M.

2010-01-01

Roč. 147, č. 3 (2010), s. 529-563 ISSN 0178-8051 R&D Projects: GA ČR GA201/06/1323 Institutional research plan: CEZ:AV0Z10750506 Keywords : contact process * survival * hierarchical group * coupling * renormalization group Subject RIV: BA - General Mathematics Impact factor: 1.590, year: 2010 http://library.utia.cas.cz/separaty/2010/SI/swart-0342729.pdf

Self-assembled biomimetic superhydrophobic hierarchical arrays.

Science.gov (United States)

Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

2013-09-01

Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

The conversion of spatial planning in Denmark

DEFF Research Database (Denmark)

Galland, Daniel

2014-01-01

Danish spatial planning has been increasingly subjected to significant structural, functional and conceptual reorientations over the past two decades. The comprehensive hierarchical framework wherein planning policies and practices used to operate became considerably modified after the implementa......Danish spatial planning has been increasingly subjected to significant structural, functional and conceptual reorientations over the past two decades. The comprehensive hierarchical framework wherein planning policies and practices used to operate became considerably modified after...... the implementation of a local government reform back in 2007. The reform abolished the county level, which implied the re-scaling of planning policies, functions and responsibilities to municipal and national levels. This situation brought about radical shifts concerning the implementation of land-use tasks...

In-situ Fabrication of a Freestanding Acrylate-based Hierarchical Electrolyte for Lithium-sulfur Batteries

International Nuclear Information System (INIS)

Liu, M.; Jiang, H.R.; Ren, Y.X.; Zhou, D.; Kang, F.Y.; Zhao, T.S.

2016-01-01

Graphical abstract: We present a freestanding acrylate-based hierarchical electrolyte. This quasi-solid electrolyte is assembled by in-situ gelation of a pentaerythritol tetraacrylate (PETEA)-based gel polymer electrolyte (GPE) into a polymethyl methacrylate (PMMA)-based electrospun network. The prepared polymer battery renders a suppressed shuttle effect and much enhanced cycle life. - Highlights: • A freestanding Acrylate-based Hierarchical Electrolyte was in-situ crafted. • The high conductivity is due to strong uptake ability and elimination of separator. • The polymer battery renders a superior high rate capability and excellent retention. • First-principle calculations prove anchoring ability of ester functional groups. • Cell modeling shows geometric design effectively suppresses polysulfide flux. - Abstract: A number of methods have been attempted to suppress the shuttle effect in lithium-sulfur (Li-S) batteries to improve battery performance. Conventional methods, however, reduce the ionic conductivity, sacrifice the overall energy density and increase the cost of production. Here, we report a facile synthesis of an acrylate-based hierarchical electrolyte (AHE). This quasi-solid electrolyte is assembled by in-situ gelation of a pentaerythritol tetraacrylate (PETEA)-based gel polymer electrolyte (GPE) into a polymethyl methacrylate (PMMA)-based electrospun network. The structural similarity and synergetic compatibility between the electrospun network and GPE provide the AHE an ester-rich robust structure with a high ionic conductivity of 1.02 × 10 −3 S cm −1 due to the strong uptake ability and the elimination of commercial separator. The S/AHE/Li polymer battery also renders a high rate capability of 645 mAh g −1 at 3C, while maintaining excellent retention at both high and low current densities (80.3% after 500 cycles at 0.3C and 91.9% after 500 cycles at 3C). First-principle calculations reveal that the reduced shuttle effect can be

Spatio-Temporal Audio Enhancement Based on IAA Noise Covariance Matrix Estimates

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2014-01-01

A method for estimating the noise covariance matrix in a mul- tichannel setup is proposed. The method is based on the iter- ative adaptive approach (IAA), which only needs short seg- ments of data to estimate the covariance matrix. Therefore, the method can be used for fast varying signals....... The method is based on an assumption of the desired signal being harmonic, which is used for estimating the noise covariance matrix from the covariance matrix of the observed signal. The noise co- variance estimate is used in the linearly constrained minimum variance (LCMV) filter and compared...

Gradient-based stochastic estimation of the density matrix

Science.gov (United States)

Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton

2018-03-01

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.

Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework

Science.gov (United States)

Alameddine, Ibrahim; Karmakar, Subhankar; Qian, Song S.; Paerl, Hans W.; Reckhow, Kenneth H.

2013-10-01

The total maximum daily load program aims to monitor more than 40,000 standard violations in around 20,000 impaired water bodies across the United States. Given resource limitations, future monitoring efforts have to be hedged against the uncertainties in the monitored system, while taking into account existing knowledge. In that respect, we have developed a hierarchical spatiotemporal Bayesian model that can be used to optimize an existing monitoring network by retaining stations that provide the maximum amount of information, while identifying locations that would benefit from the addition of new stations. The model assumes the water quality parameters are adequately described by a joint matrix normal distribution. The adopted approach allows for a reduction in redundancies, while emphasizing information richness rather than data richness. The developed approach incorporates the concept of entropy to account for the associated uncertainties. Three different entropy-based criteria are adopted: total system entropy, chlorophyll-a standard violation entropy, and dissolved oxygen standard violation entropy. A multiple attribute decision making framework is adopted to integrate the competing design criteria and to generate a single optimal design. The approach is implemented on the water quality monitoring system of the Neuse River Estuary in North Carolina, USA. The model results indicate that the high priority monitoring areas identified by the total system entropy and the dissolved oxygen violation entropy criteria are largely coincident. The monitoring design based on the chlorophyll-a standard violation entropy proved to be less informative, given the low probabilities of violating the water quality standard in the estuary.

Fast Multipole Method as a Matrix-Free Hierarchical Low-Rank Approximation

KAUST Repository

Yokota, Rio; Ibeid, Huda; Keyes, David E.

2018-01-01

There has been a large increase in the amount of work on hierarchical low-rank approximation methods, where the interest is shared by multiple communities that previously did not intersect. This objective of this article is two-fold; to provide a thorough review of the recent advancements in this field from both analytical and algebraic perspectives, and to present a comparative benchmark of two highly optimized implementations of contrasting methods for some simple yet representative test cases. The first half of this paper has the form of a survey paper, to achieve the former objective. We categorize the recent advances in this field from the perspective of compute-memory tradeoff, which has not been considered in much detail in this area. Benchmark tests reveal that there is a large difference in the memory consumption and performance between the different methods.

Fast Multipole Method as a Matrix-Free Hierarchical Low-Rank Approximation

KAUST Repository

Yokota, Rio

2018-01-03

There has been a large increase in the amount of work on hierarchical low-rank approximation methods, where the interest is shared by multiple communities that previously did not intersect. This objective of this article is two-fold; to provide a thorough review of the recent advancements in this field from both analytical and algebraic perspectives, and to present a comparative benchmark of two highly optimized implementations of contrasting methods for some simple yet representative test cases. The first half of this paper has the form of a survey paper, to achieve the former objective. We categorize the recent advances in this field from the perspective of compute-memory tradeoff, which has not been considered in much detail in this area. Benchmark tests reveal that there is a large difference in the memory consumption and performance between the different methods.

Hierarchical Cu precipitation in lamellated steel after multistage heat treatment

Science.gov (United States)

Liu, Qingdong; Gu, Jianfeng

2017-09-01

The hierarchical distribution of Cu-rich precipitates (CRPs) and related partitioning and segregation behaviours of solute atoms were investigated in a 1.54 Cu-3.51 Ni (wt.%) low-carbon high-strength low-alloy (HSLA) steel after multistage heat treatment by using the combination of electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) and atom probe tomography (APT). Intercritical tempering at 725 °C of as-quenched lathlike martensitic structure leads to the coprecipitation of CRPs at the periphery of a carbide precipitate which is possibly in its paraequilibrium state due to distinct solute segregation at the interface. The alloyed carbide and CRPs provide constituent elements for each other and make the coprecipitation thermodynamically favourable. Meanwhile, austenite reversion occurs to form fresh secondary martensite (FSM) zone where is rich in Cu and pertinent Ni and Mn atoms, which gives rise to a different distributional morphology of CRPs with large size and high density. In addition, conventional tempering at 500 °C leads to the formation of nanoscale Cu-rich clusters in α-Fe matrix. As a consequence, three populations of CRPs are hierarchically formed around carbide precipitate, at FSM zone and in α-Fe matrix. The formation of different precipitated features can be turned by controlling diffusion pathways of related solute atoms and further to tailor mechanical properties via proper multistage heat treatments.

Global Crop Monitoring: A Satellite-Based Hierarchical Approach

Directory of Open Access Journals (Sweden)

Bingfang Wu

2015-04-01

Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

Changes of hierarchical network in local and world stock market

Science.gov (United States)

Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

2017-10-01

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

Is regional planning dead or just coping?

DEFF Research Database (Denmark)

Galland, Daniel

2012-01-01

and welfarist state project towards being a domain characterised by growth-oriented strategies that stand for neoliberal political agendas. In analysing this process I show that hierarchical forms of governance and statutory mechanisms embedded within them have been largely substituted by emerging soft spaces......How is regional planning transformed in increasingly changing socioeconomic and political contexts? How are regional planning policies and practices ultimately shaped and why? With this paper I propose and apply an analytical model based on notions of state theory, state spatial selectivity, new...

Investigation on Reliability and Scalability of an FBG-Based Hierarchical AOFSN

Directory of Open Access Journals (Sweden)

Li-Mei Peng

2010-03-01

Full Text Available The reliability and scalability of large-scale based optical fiber sensor networks (AOFSN are considered in this paper. The AOFSN network consists of three-level hierarchical sensor network architectures. The first two levels consist of active interrogation and remote nodes (RNs and the third level, called the sensor subnet (SSN, consists of passive Fiber Bragg Gratings (FBGs and a few switches. The switch architectures in the RN and various SSNs to improve the reliability and scalability of AOFSN are studied. Two SSNs with a regular topology are proposed to support simple routing and scalability in AOFSN: square-based sensor cells (SSC and pentagon-based sensor cells (PSC. The reliability and scalability are evaluated in terms of the available sensing coverage in the case of one or multiple link failures.

Behavior-based evacuation planning

KAUST Repository

Rodriguez, Samuel

2010-05-01

In this work, we present a formulation of an evacuation planning problem that is inspired by motion planning and describe an integrated behavioral agent-based and roadmap-based motion planning approach to solve it. Our formulation allows users to test the effect on evacuation of a number of different environmental factors. One of our main focuses is to provide a mechanism to investigate how the interaction between agents influences the resulting evacuation plans. Specifically, we explore how various types of control provided by a set of directing agents effects the overall evacuation planning strategies of the evacuating agents. ©2010 IEEE.

Behavior-based evacuation planning

KAUST Repository

Rodriguez, Samuel; Amato, Nancy M

2010-01-01

In this work, we present a formulation of an evacuation planning problem that is inspired by motion planning and describe an integrated behavioral agent-based and roadmap-based motion planning approach to solve it. Our formulation allows users to test the effect on evacuation of a number of different environmental factors. One of our main focuses is to provide a mechanism to investigate how the interaction between agents influences the resulting evacuation plans. Specifically, we explore how various types of control provided by a set of directing agents effects the overall evacuation planning strategies of the evacuating agents. ©2010 IEEE.

Neutrino mass matrix: Inverted hierarchy and CP violation

International Nuclear Information System (INIS)

Frigerio, Michele; Smirnov, Alexei Yu.

2003-01-01

We reconstruct the neutrino mass matrix in the flavor basis, in the case of an inverted mass hierarchy (ordering), using all available experimental data on neutrino masses and oscillations. We analyze the dependence of the matrix elements m αβ on the CP violating Dirac δ and Majorana ρ and σ phases, for different values of the absolute mass scale. We find that the present data admit various structures of the mass matrix: (i) hierarchical structures with a set of small (zero) elements; (ii) structures with equalities among various groups of elements: e-row and/or μτ-block elements, diagonal and/or off-diagonal elements; (iii) 'democratic' structure. We find the values of phases for which these structures are realized. The mass matrix elements can anticorrelate with flavor: inverted partial or complete flavor alignment is possible. For various structures of the mass matrix we identify the possible underlying symmetry. We find that the mass matrix can be reconstructed completely only in particular cases, provided that the absolute scale of the mass is measured. Generally, the freedom related to the Majorana phase σ will not be removed, thus admitting various types of mass matrix

Managing the systems approach to training using a flexible Hierarchical data base

International Nuclear Information System (INIS)

Housman, E.; Bush, E.R.

1993-01-01

Task analysis/curriculum design for a nuclear power station results in a massive amount of data, which must be sequenced and ordered to create an effective program design. This is an almost impossible task without the use of computerized data base. Beginning in 1989, San Onofre nuclear generating station (SONGS) undertook a task analysis/program design project to verify the structure and sequence (design) of all accredited training program. A flex hierarchical data-base management system was designed to store and manage the data collected during the project. For the Operations Training Programm alone ∼8000 tasks, 90,000 knowledges and abilities, and 10,000 learning objectives were entered into this data base

Leadership styles across hierarchical levels in nursing departments.

Science.gov (United States)

Stordeur, S; Vandenberghe, C; D'hoore, W

2000-01-01

Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.

Beyond Creation of Mesoporosity: The Advantages of Polymer-Based Dual-Function Templates for Fabricating Hierarchical Zeolites

KAUST Repository

Tian, Qiwei; Liu, Zhaohui; Zhu, Yihan; Dong, Xinglong; Saih, Youssef; Basset, Jean-Marie; Sun, Miao; Xu, Wei; Zhu, Liangkui; Zhang, Daliang; Huang, Jianfeng; Meng, Xiangju; Xiao, Feng-Shou; Han, Yu

2016-01-01

Direct synthesis of hierarchical zeolites currently relies on the use of surfactant-based templates to produce mesoporosity by the random stacking of 2D zeolite sheets or the agglomeration of tiny zeolite grains. The benefits of using nonsurfactant

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

Science.gov (United States)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community

A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier

Directory of Open Access Journals (Sweden)

Yanzhen Zhou

2016-09-01

Full Text Available Machine learning techniques have been widely used in transient stability prediction of power systems. When using the post-fault dynamic responses, it is difficult to draw a definite conclusion about how long the duration of response data used should be in order to balance the accuracy and speed. Besides, previous studies have the problem of lacking consideration for the confidence level. To solve these problems, a hierarchical method for transient stability prediction based on the confidence of ensemble classifier using multiple support vector machines (SVMs is proposed. Firstly, multiple datasets are generated by bootstrap sampling, then features are randomly picked up to compress the datasets. Secondly, the confidence indices are defined and multiple SVMs are built based on these generated datasets. By synthesizing the probabilistic outputs of multiple SVMs, the prediction results and confidence of the ensemble classifier will be obtained. Finally, different ensemble classifiers with different response times are built to construct different layers of the proposed hierarchical scheme. The simulation results show that the proposed hierarchical method can balance the accuracy and rapidity of the transient stability prediction. Moreover, the hierarchical method can reduce the misjudgments of unstable instances and cooperate with the time domain simulation to insure the security and stability of power systems.

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.

Hierarchical Traces for Reduced NSM Memory Requirements

Science.gov (United States)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

Science.gov (United States)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

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 prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

Hierarchical probing for estimating the trace of the matrix inverse on toroidal lattices

Energy Technology Data Exchange (ETDEWEB)

Stathopoulos, Andreas [College of William and Mary, Williamsburg, VA; Laeuchli, Jesse [College of William and Mary, Williamsburg, VA; Orginos, Kostas [College of William and Mary, Williamsburg, VA; Jefferson Lab

2013-10-01

The standard approach for computing the trace of the inverse of a very large, sparse matrix $A$ is to view the trace as the mean value of matrix quadratures, and use the Monte Carlo algorithm to estimate it. This approach is heavily used in our motivating application of Lattice QCD. Often, the elements of $A^{-1}$ display certain decay properties away from the non zero structure of $A$, but random vectors cannot exploit this induced structure of $A^{-1}$. Probing is a technique that, given a sparsity pattern of $A$, discovers elements of $A$ through matrix-vector multiplications with specially designed vectors. In the case of $A^{-1}$, the pattern is obtained by distance-$k$ coloring of the graph of $A$. For sufficiently large $k$, the method produces accurate trace estimates but the cost of producing the colorings becomes prohibitively expensive. More importantly, it is difficult to search for an optimal $k$ value, since none of the work for prior choices of $k$ can be reused.

Hierarchical silicon nanowires-carbon textiles matrix as a binder-free anode for high-performance advanced lithium-ion batteries

Science.gov (United States)

Liu, Bin; Wang, Xianfu; Chen, Haitian; Wang, Zhuoran; Chen, Di; Cheng, Yi-Bing; Zhou, Chongwu; Shen, Guozhen

2013-01-01

Toward the increasing demands of portable energy storage and electric vehicle applications, the widely used graphite anodes with significant drawbacks become more and more unsuitable. Herein, we report a novel scaffold of hierarchical silicon nanowires-carbon textiles anodes fabricated via a facile method. Further, complete lithium-ion batteries based on Si and commercial LiCoO2 materials were assembled to investigate their corresponding across-the-aboard performances, demonstrating their enhanced specific capacity (2950 mAh g−1 at 0.2 C), good repeatability/rate capability (even >900 mAh g−1 at high rate of 5 C), long cycling life, and excellent stability in various external conditions (curvature, temperature, and humidity). Above results light the way to principally replacing graphite anodes with silicon-based electrodes which was confirmed to have better comprehensive performances. PMID:23572030

Fabrication of semi-transparent super-hydrophobic surface based on silica hierarchical structures

KAUST Repository

Chen, Ping-Hei

2011-01-01

This study successfully develops a versatile method of producing superhydrophobic surfaces with micro/nano-silica hierarchical structures on glass surfaces. Optically transparent super hydrophobic silica thin films were prepared by spin-coating silica particles suspended in a precursor solution of silane, ethanol, and H2O with molar ratio of 1:4:4. The resulting super hydrophobic films were characterized by scanning electron microscopy (SEM), optical transmission, and contact angle measurements. The glass substrates in this study were modified with different particles: micro-silica particles, nano-silica particles, and hierarchical structures. This study includes SEM micrographs of the modified glass surfaces with hierarchical structures at different magnifications. © 2011 The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg.

Planning of dairy farm and dairy plant based ecotourism

Science.gov (United States)

Sarnyoto, A. S.; Tama, I. P.; Tantrika, C. F. M.

2017-06-01

One of a dairy production company producing pasteurized milk and yoghurt drink, whose brand has widely known in East Java, has a factory plant in Batu City, one of tourism destinations in Indonesia. Behind the factory plant, there is a vacant land with an estimated total area of 2.3 ha and a vacant cowshed which had not been used for cattle ranching. Because of that, the company planned to develop the vacant land as a dairy farm and plant based ecotourism. In addition, dairy farm and dairy plant based tourism attractions are still rarely found in Batu. Thus, the first aim of this study was to analyse the potencies of the company that related to future plans of ecotourism built. The second aim was to set up the strategies that can be done in order to actualize the ecotourism project. The next aim was to plan the ecotourism, especially the facilities planning and the facilities arrangement on the vacant land. Strategic management approach was used to analyse the potencies and to determine the strategies. To select the proper facilities, tourists were asked to give appraisal by using questionnaire. Appraisal result was mapped onto four quadrants spatial map to see advantages and shortcomings of each facility along with choosing the right facilities to be built. Those facilities and tourist activities were compared with ecotourism criteria to make sure that the facilities were appropriate to provide not only entertainment but also ecotourism function. To arrange the chosen facilities, the step in Systematic Layout Planning were conducted to generate a propose layout of facilities arrangement. Based on potencies analysis, in Internal-External matrix, the company current position was on quadrant 2 (grow and build), with the most appropriate strategy was intensive or integrative. The proposed strategies were to build the new infrastructure, to renovate cowshed, and to add new tourism facilities on the land. There were 11 selected facilities based on MDS. Moreover, based

Superhydrophobic SERS substrates based on silicon hierarchical nanostructures

Science.gov (United States)

Chen, Xuexian; Wen, Jinxiu; Zhou, Jianhua; Zheng, Zebo; An, Di; Wang, Hao; Xie, Weiguang; Zhan, Runze; Xu, Ningsheng; Chen, Jun; She, Juncong; Chen, Huanjun; Deng, Shaozhi

2018-02-01

Silicon nanostructures have been cultivated as promising surface enhanced Raman scattering (SERS) substrates in terms of their low-loss optical resonance modes, facile functionalization, and compatibility with today’s state-of-the-art CMOS techniques. However, unlike their plasmonic counterparts, the electromagnetic field enhancements induced by silicon nanostructures are relatively small, which restrict their SERS sensing limit to around 10-7 M. To tackle this problem, we propose here a strategy for improving the SERS performance of silicon nanostructures by constructing silicon hierarchical nanostructures with a superhydrophobic surface. The hierarchical nanostructures are binary structures consisted of silicon nanowires (NWs) grown on micropyramids (MPs). After being modified with perfluorooctyltriethoxysilane (PFOT), the nanostructure surface shows a stable superhydrophobicity with a high contact angle of ˜160°. The substrate can allow for concentrating diluted analyte solutions into a specific area during the evaporation of the liquid droplet, whereby the analytes are aggregated into a small volume and can be easily detected by the silicon nanostructure SERS substrate. The analyte molecules (methylene blue: MB) enriched from an aqueous solution lower than 10-8 M can be readily detected. Such a detection limit is ˜100-fold lower than the conventional SERS substrates made of silicon nanostructures. Additionally, the detection limit can be further improved by functionalizing gold nanoparticles onto silicon hierarchical nanostructures, whereby the superhydrophobic characteristics and plasmonic field enhancements can be combined synergistically to give a detection limit down to ˜10-11 M. A gold nanoparticle-functionalized superhydrophobic substrate was employed to detect the spiked melamine in liquid milk. The results showed that the detection limit can be as low as 10-5 M, highlighting the potential of the proposed superhydrophobic SERS substrate in

Hierarchical CaCO3 chromatography: a stationary phase based on biominerals.

Science.gov (United States)

Sato, Kosuke; Oaki, Yuya; Takahashi, Daisuke; Toshima, Kazunobu; Imai, Hiroaki

2015-03-23

In biomineralization, acidic macromolecules play important roles for the growth control of crystals through a specific interaction. Inspired by this interaction, we report on an application of the hierarchical structures in CaCO3 biominerals to a stationary phase of chromatography. The separation and purification of acidic small organic molecules are achieved by thin-layer chromatography and flash chromatography using the powder of biominerals as the stationary phase. The unit nanocrystals and their oriented assembly, the hierarchical structure, are suitable for the adsorption site of the target organic molecules and the flow path of the elution solvents, respectively. The separation mode is ascribed to the specific adsorption of the acidic molecules on the crystal face and the coordination of the functional groups to the calcium ions. The results imply that a new family of stationary phase of chromatography can be developed by the fine tuning of hierarchical structures in CaCO3 materials. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of action planning and coping planning within the theory of planned behaviour

DEFF Research Database (Denmark)

Pakpour, Amir H.; Zedi, Isa mohammadi; Chatzisarantis, Nikos

2011-01-01

Objective: Patients on dialysis have low physical activity levels. The aim of the study was to examine the validity of action planning and coping planning within the theory of planned behaviour framework, for predicting physical activity behaviour of patients on hemodialysis. Methods: One hundred...... and forty four patients who were undergoing emodialysis were selected from dialysis centers. The mean age of the patients was 56.61 (SD= 11.38) years. The patients completed a questionnaire including variables from the theory of planned behaviour, action planning and coping planning. Physical activity...... was prospectively assessed at 4-weeks with the validated International Physical Activity Questionnaire self-report measure. A hierarchical regression analysis was performed to examine the effects of action planning and coping planning on physical activity behaviour. Results: There was a main effect for coping...

Fracture Toughness of Carbon Nanotube-Reinforced Metal- and Ceramic-Matrix Composites

International Nuclear Information System (INIS)

Chen, Y.L.; Liu, B.; Hwang, K.C.; Chen, Y.L.; Huang, Y.

2011-01-01

Hierarchical analysis of the fracture toughness enhancement of carbon nanotube- (CNT-) reinforced hard matrix composites is carried out on the basis of shear-lag theory and fracture mechanics. It is found that stronger CNT/matrix interfaces cannot definitely lead to the better fracture toughness of these composites, and the optimal interfacial chemical bond density is that making the failure mode just in the transition from CNT pull-out to CNT break. For hard matrix composites, the fracture toughness of composites with weak interfaces can be improved effectively by increasing the CNT length. However, for soft matrix composite, the fracture toughness improvement due to the reinforcing CNTs quickly becomes saturated with an increase in CNT length. The proposed theoretical model is also applicable to short fiber-reinforced composites.

Improvement of Internal Audit Planning Method through Application of Risk Card by the Indices of Value-Based Management System of Joint-Stock Company

OpenAIRE

Oleksandr Smetanko

2014-01-01

The Article deals with issues of improving methods of planning and carrying out internal audit in conditions of risk-oriented approach to audit according to the indices of value-based management system - VBM (Value Based Management) using the risk card (risk matrix). A risk card (risk matrix) method has been disclosed taking into account risk level of each of the key factors influencing joint-stock company value rates. Recommendations have been given and abstract of working document has been ...

Hierarchical Sets: Analyzing Pangenome Structure through Scalable Set Visualizations

DEFF Research Database (Denmark)

Pedersen, Thomas Lin

2017-01-01

of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https...

Extension of mixture-of-experts networks for binary classification of hierarchical data.

Science.gov (United States)

Ng, Shu-Kay; McLachlan, Geoffrey J

2007-09-01

For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another extension is to quantify cluster-specific information on data hierarchy by random effects via the generalized linear mixed-effects model (GLMM). The extension of ME networks is implemented by allowing for correlation in the hierarchical data in both the gating and expert networks via the GLMM. The proposed model is illustrated using a real thyroid disease data set. In our study, we consider 7652 thyroid diagnosis records from 1984 to early 1987 with complete information on 20 attribute values. We obtain 10 independent random splits of the data into a training set and a test set in the proportions 85% and 15%. The test sets are used to assess the generalization performance of the proposed model, based on the percentage of misclassifications. For comparison, the results obtained from the ME network with independence assumption are also included. With the thyroid disease data, the misclassification rate on test sets for the extended ME network is 8.9%, compared to 13.9% for the ME network. In addition, based on model selection methods described in Section 2, a network with two experts is selected. These two expert networks can be considered as modeling two groups of patients with high and low incidence rates. Significant variation among the predicted cluster-specific random effects is detected in the patient group with low incidence rate. It is shown that the extended ME network outperforms the ME network for binary classification of hierarchical data. With the thyroid disease data, useful information on the relative log odds of patients with diagnosed conditions at different periods can be

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

Directory of Open Access Journals (Sweden)

Jun Ren

2014-01-01

Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

Parallel-hierarchical processing and classification of laser beam profile images based on the GPU-oriented architecture

Science.gov (United States)

Yarovyi, Andrii A.; Timchenko, Leonid I.; Kozhemiako, Volodymyr P.; Kokriatskaia, Nataliya I.; Hamdi, Rami R.; Savchuk, Tamara O.; Kulyk, Oleksandr O.; Surtel, Wojciech; Amirgaliyev, Yedilkhan; Kashaganova, Gulzhan

2017-08-01

The paper deals with a problem of insufficient productivity of existing computer means for large image processing, which do not meet modern requirements posed by resource-intensive computing tasks of laser beam profiling. The research concentrated on one of the profiling problems, namely, real-time processing of spot images of the laser beam profile. Development of a theory of parallel-hierarchic transformation allowed to produce models for high-performance parallel-hierarchical processes, as well as algorithms and software for their implementation based on the GPU-oriented architecture using GPGPU technologies. The analyzed performance of suggested computerized tools for processing and classification of laser beam profile images allows to perform real-time processing of dynamic images of various sizes.

A Hierarchical Multiple-Level Approach to the Assessment of Interpersonal Relatedness and Self-Definition: Implications for Research, Clinical Practice, and DSM Planning.

Science.gov (United States)

Luyten, Patrick; Blatt, Sidney J

2016-01-01

Extant research suggests there is considerable overlap between so-called 2-polarities models of personality development; that is, models that propose that personality development evolves through a dialectic synergistic interaction between 2 key developmental tasks across the life span-the development of self-definition on the one hand and of relatedness on the other. These models have attracted considerable research attention and play a central role in DSM planning. This article provides a researcher- and clinician-friendly guide to the assessment of these personality theories. We argue that current theoretical models focus on issues of relatedness and self-definition at different hierarchically organized levels of analysis; that is (a) at the level of broad personality features, (b) at the motivational level (i.e., the motivational processes underlying the development of these dimensions), and (c) at the level of underlying internal working models or cognitive affective schemas, and the specific interpersonal features and problems in which they are expressed. Implications for further research and DSM planning are outlined.

Preparation and surface modification of hierarchical nanosheets-based ZnO microstructures for dye-sensitized solar cells

Energy Technology Data Exchange (ETDEWEB)

Meng, Yongming; Lin, Yu, E-mail: linyuyrr@163.com; Lin, Yibing; Yang, Jiyuan

2014-02-15

This paper reports a simple one-step hydrothermal route for the preparation of hierarchical nanosheets-based ZnO microstructures and their application to dye-sensitized solar cells. The morphologies of the products were controlled by the dosage of the reactants. Their physical characteristics were detected by X-ray diffraction, a field-emission scanning electron microscope and a surface analyzer. It is proved that the sample of ZnO microspheres with larger surface area and stronger light-trapping capacity since the superiority of their entirely spherical structures exhibits better photoelectrochemical properties than the mixtures of ZnO microspheres and ZnO microflowers. A dye-sensitized solar cell assembled by the ZnO microspheres as photoanode shows an energy conversion efficiency of 2.94% after surface modification by tetrabutyl titanate solution at 90 {sup °}C. This result is over 1.6 times higher than the non-modified cell fabricated by the ZnO microspheres on the basis of the external improvement and the stability enhancement for the dye-sensitized ZnO photoanode. - Graphical abstract: Influences on energy conversion efficiency of the dye-sensitized solar cells assembled by decorating hierarchical nanosheets-based ZnO microstructures with tetrabutyl titanate solution at different temperatures. Display Omitted - Highlights: • Hierarchical nanosheets-based ZnO microstructures were controllably synthesized. • The ZnO microspheres show good optical and electrochemical properties. • The ZnO microspheres were modified by C{sub 16}H{sub 36}O{sub 4}Ti solution. • Remarkable increase of conversion efficiency is observed after surface modification.

Inheritance rules for Hierarchical Metadata Based on ISO 19115

Science.gov (United States)

Zabala, A.; Masó, J.; Pons, X.

2012-04-01

Mainly, ISO19115 has been used to describe metadata for datasets and services. Furthermore, ISO19115 standard (as well as the new draft ISO19115-1) includes a conceptual model that allows to describe metadata at different levels of granularity structured in hierarchical levels, both in aggregated resources such as particularly series, datasets, and also in more disaggregated resources such as types of entities (feature type), types of attributes (attribute type), entities (feature instances) and attributes (attribute instances). In theory, to apply a complete metadata structure to all hierarchical levels of metadata, from the whole series to an individual feature attributes, is possible, but to store all metadata at all levels is completely impractical. An inheritance mechanism is needed to store each metadata and quality information at the optimum hierarchical level and to allow an ease and efficient documentation of metadata in both an Earth observation scenario such as a multi-satellite mission multiband imagery, as well as in a complex vector topographical map that includes several feature types separated in layers (e.g. administrative limits, contour lines, edification polygons, road lines, etc). Moreover, and due to the traditional split of maps in tiles due to map handling at detailed scales or due to the satellite characteristics, each of the previous thematic layers (e.g. 1:5000 roads for a country) or band (Landsat-5 TM cover of the Earth) are tiled on several parts (sheets or scenes respectively). According to hierarchy in ISO 19115, the definition of general metadata can be supplemented by spatially specific metadata that, when required, either inherits or overrides the general case (G.1.3). Annex H of this standard states that only metadata exceptions are defined at lower levels, so it is not necessary to generate the full registry of metadata for each level but to link particular values to the general value that they inherit. Conceptually the metadata

Enhanced fuzzy-connective-based hierarchical aggregation network using particle swarm optimization

Science.gov (United States)

Wang, Fang-Fang; Su, Chao-Ton

2014-11-01

The fuzzy-connective-based aggregation network is similar to the human decision-making process. It is capable of aggregating and propagating degrees of satisfaction of a set of criteria in a hierarchical manner. Its interpreting ability and transparency make it especially desirable. To enhance its effectiveness and further applicability, a learning approach is successfully developed based on particle swarm optimization to determine the weights and parameters of the connectives in the network. By experimenting on eight datasets with different characteristics and conducting further statistical tests, it has been found to outperform the gradient- and genetic algorithm-based learning approaches proposed in the literature; furthermore, it is capable of generating more accurate estimates. The present approach retains the original benefits of fuzzy-connective-based aggregation networks and is widely applicable. The characteristics of the learning approaches are also discussed and summarized, providing better understanding of the similarities and differences among these three approaches.

Bio-inspired configurable multiscale extracellular matrix-like structures for functional alignment and guided orientation of cells.

Science.gov (United States)

Bae, Won-Gyu; Kim, Jangho; Choung, Yun-Hoon; Chung, Yesol; Suh, Kahp Y; Pang, Changhyun; Chung, Jong Hoon; Jeong, Hoon Eui

2015-11-01

Inspired by the hierarchically organized protein fibers in extracellular matrix (ECM) as well as the physiological importance of multiscale topography, we developed a simple but robust method for the design and manipulation of precisely controllable multiscale hierarchical structures using capillary force lithography in combination with an original wrinkling technique. In this study, based on our proposed fabrication technology, we approached a conceptual platform that can mimic the hierarchically multiscale topographical and orientation cues of the ECM for controlling cell structure and function. We patterned the polyurethane acrylate-based nanotopography with various orientations on the microgrooves, which could provide multiscale topography signals of ECM to control single and multicellular morphology and orientation with precision. Using our platforms, we found that the structures and orientations of fibroblast cells were greatly influenced by the nanotopography, rather than the microtopography. We also proposed a new approach that enables the generation of native ECM having nanofibers in specific three-dimensional (3D) configurations by culturing fibroblast cells on the multiscale substrata. We suggest that our methodology could be used as efficient strategies for the design and manipulation of various functional platforms, including well-defined 3D tissue structures for advanced regenerative medicine applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Microgrids and distributed generation systems: Control, operation, coordination and planning

Science.gov (United States)

Che, Liang

Distributed Energy Resources (DERs) which include distributed generations (DGs), distributed energy storage systems, and adjustable loads are key components in microgrid operations. A microgrid is a small electric power system integrated with on-site DERs to serve all or some portion of the local load and connected to the utility grid through the point of common coupling (PCC). Microgrids can operate in both grid-connected mode and island mode. The structure and components of hierarchical control for a microgrid at Illinois Institute of Technology (IIT) are discussed and analyzed. Case studies would address the reliable and economic operation of IIT microgrid. The simulation results of IIT microgrid operation demonstrate that the hierarchical control and the coordination strategy of distributed energy resources (DERs) is an effective way of optimizing the economic operation and the reliability of microgrids. The benefits and challenges of DC microgrids are addressed with a DC model for the IIT microgrid. We presented the hierarchical control strategy including the primary, secondary, and tertiary controls for economic operation and the resilience of a DC microgrid. The simulation results verify that the proposed coordinated strategy is an effective way of ensuring the resilient response of DC microgrids to emergencies and optimizing their economic operation at steady state. The concept and prototype of a community microgrid that interconnecting multiple microgrids in a community are proposed. Two works are conducted. For the coordination, novel three-level hierarchical coordination strategy to coordinate the optimal power exchanges among neighboring microgrids is proposed. For the planning, a multi-microgrid interconnection planning framework using probabilistic minimal cut-set (MCS) based iterative methodology is proposed for enhancing the economic, resilience, and reliability signals in multi-microgrid operations. The implementation of high-reliability microgrids

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

Science.gov (United States)

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

DEFF Research Database (Denmark)

Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun

2014-01-01

This paper introduces a reconfigurable compositional scheduling framework, in which the hierarchical structure, the scheduling policies, the concrete task behavior and the shared resources can all be reconfigured. The behavior of each periodic preemptive task is given as a list of timed actions, ...

Analysis hierarchical model for discrete event systems

Science.gov (United States)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

Fuzzy Quantitive Strategic Planning Matrix dalam Perencanaan Strategi Perguruan Tinggi

Directory of Open Access Journals (Sweden)

Fera Tri Wulandari

2016-01-01

Full Text Available The strategic plan helps the college in determining the direction of the college to achieve a desired future and provides a framework for achieving competitive advantage. In the strategic planning process, the selection of strategies is essential if universities do not have the resources to implement all the strategies. FQSPM designed to determine the relative attractiveness of each alternative strategy using triangular fuzzy numbers. Merger FQSPM and FTOPSIS used in the decision-making process on strategic planning by a college to conduct the election strategy based on the results of internal and external analysis. The results of the strategic planning helps colleges determine the direction to achieve the desired future so that colleges can anticipate environmental changes and predict the risk while continuing to adjust the action with the aim to be achieved college. Keywords: Strategic Planning; SWOT; Fuzzy QSPM; Fuzzy TOPSIS

Maintaining consistency between planning hierarchies: Techniques and applications

Science.gov (United States)

Zoch, David R.

1987-01-01

In many planning and scheduling environments, it is desirable to be able to view and manipulate plans at different levels of abstraction, allowing the users the option of viewing and manipulating either a very detailed representation of the plan or a high-level more abstract version of the plan. Generating a detailed plan from a more abstract plan requires domain-specific planning/scheduling knowledge; the reverse process of generating a high-level plan from a detailed plan Reverse Plan Maintenance, or RPM) requires having the system remember the actions it took based on its domain-specific knowledge and its reasons for taking those actions. This reverse plan maintenance process is described as implemented in a specific planning and scheduling tool, The Mission Operations Planning Assistant (MOPA), as well as the applications of RPM to other planning and scheduling problems; emphasizing the knowledge that is needed to maintain the correspondence between the different hierarchical planning levels.

Environmental impact assessment of the industrial estate development plan with the geographical information system and matrix methods.

Science.gov (United States)

Ghasemian, Mohammad; Poursafa, Parinaz; Amin, Mohammad Mehdi; Ziarati, Mohammad; Ghoddousi, Hamid; Momeni, Seyyed Alireza; Rezaei, Amir Hossein

2012-01-01

The purpose of this study is environmental impact assessment of the industrial estate development planning. This cross-sectional study was conducted in 2010 in Isfahan province, Iran. GIS and matrix methods were applied. Data analysis was done to identify the current situation of the region, zoning vulnerable areas, and scoping the region. Quantitative evaluation was done by using matrix of Wooten and Rau. The net score for impact of industrial units operation on air quality of the project area was (-3). According to the transition of industrial estate pollutants, residential places located in the radius of 2500 meters of the city were expected to be affected more. The net score for impact of construction of industrial units on plant species of the project area was (-2). Environmental protected areas were not affected by the air and soil pollutants because of their distance from industrial estate. Positive effects of project activities outweigh the drawbacks and the sum scores allocated to the project activities on environmental factor was (+37). Totally it does not have detrimental effects on the environment and residential neighborhood. EIA should be considered as an anticipatory, participatory environmental management tool before determining a plan application.

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

Science.gov (United States)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

Fracture Toughness of Carbon Nanotube-Reinforced Metal- and Ceramic-Matrix Composites

Directory of Open Access Journals (Sweden)

Y. L. Chen

2011-01-01

Full Text Available Hierarchical analysis of the fracture toughness enhancement of carbon nanotube- (CNT- reinforced hard matrix composites is carried out on the basis of shear-lag theory and facture mechanics. It is found that stronger CNT/matrix interfaces cannot definitely lead to the better fracture toughness of these composites, and the optimal interfacial chemical bond density is that making the failure mode just in the transition from CNT pull-out to CNT break. For hard matrix composites, the fracture toughness of composites with weak interfaces can be improved effectively by increasing the CNT length. However, for soft matrix composite, the fracture toughness improvement due to the reinforcing CNTs quickly becomes saturated with an increase in CNT length. The proposed theoretical model is also applicable to short fiber-reinforced composites.

Library designs for generic C++ sparse matrix computations of iterative methods

Energy Technology Data Exchange (ETDEWEB)

Pozo, R.

1996-12-31

A new library design is presented for generic sparse matrix C++ objects for use in iterative algorithms and preconditioners. This design extends previous work on C++ numerical libraries by providing a framework in which efficient algorithms can be written *independent* of the matrix layout or format. That is, rather than supporting different codes for each (element type) / (matrix format) combination, only one version of the algorithm need be maintained. This not only reduces the effort for library developers, but also simplifies the calling interface seen by library users. Furthermore, the underlying matrix library can be naturally extended to support user-defined objects, such as hierarchical block-structured matrices, or application-specific preconditioners. Utilizing optimized kernels whenever possible, the resulting performance of such framework can be shown to be competitive with optimized Fortran programs.

Immunophenotype Discovery, Hierarchical Organization, and Template-based Classification of Flow Cytometry Samples

Directory of Open Access Journals (Sweden)

Ariful Azad

2016-08-01

Full Text Available We describe algorithms for discovering immunophenotypes from large collections of flow cytometry (FC samples, and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters, a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples, while ignoring noise and small sample-specific variations.We have applied the template-base scheme to analyze several data setsincluding one representing a healthy immune system, and one of Acute Myeloid Leukemia (AMLsamples. The last task is challenging due to the phenotypic heterogeneity of the severalsubtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML, and were able to distinguish Acute Promyelocytic Leukemia from other subtypes of AML.

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

Bungartz HJ, Rank E, Niggl A, Romberg R. Extending the p-Version of Finite Elements by an Octree-Based Hierarchy. In: Widlund OB, Keyes DE (eds...generalization to higher dimensions. We test hierarchical refinement of NURBS for some elementary fluid and structural analysis problems in two and three...with straightforward implementation in tree data structures and simple generalization to higher dimensions. We test hierarchical refinement of NURBS

ℋ-matrix techniques for approximating large covariance matrices and estimating its parameters

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Keyes, David E.

2016-01-01

In this work the task is to use the available measurements to estimate unknown hyper-parameters (variance, smoothness parameter and covariance length) of the covariance function. We do it by maximizing the joint log-likelihood function. This is a non-convex and non-linear problem. To overcome cubic complexity in linear algebra, we approximate the discretised covariance function in the hierarchical (ℋ-) matrix format. The ℋ-matrix format has a log-linear computational cost and storage O(knlogn), where rank k is a small integer. On each iteration step of the optimization procedure the covariance matrix itself, its determinant and its Cholesky decomposition are recomputed within ℋ-matrix format. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

ℋ-matrix techniques for approximating large covariance matrices and estimating its parameters

KAUST Repository

Litvinenko, Alexander

2016-10-25

In this work the task is to use the available measurements to estimate unknown hyper-parameters (variance, smoothness parameter and covariance length) of the covariance function. We do it by maximizing the joint log-likelihood function. This is a non-convex and non-linear problem. To overcome cubic complexity in linear algebra, we approximate the discretised covariance function in the hierarchical (ℋ-) matrix format. The ℋ-matrix format has a log-linear computational cost and storage O(knlogn), where rank k is a small integer. On each iteration step of the optimization procedure the covariance matrix itself, its determinant and its Cholesky decomposition are recomputed within ℋ-matrix format. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

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...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... 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...

Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

Science.gov (United States)

Czégel, Dániel; Palla, Gergely

2015-12-10

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.

Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

Science.gov (United States)

Czégel, Dániel; Palla, Gergely

2015-01-01

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology. PMID:26657012

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production.

Science.gov (United States)

Sauppe, Sebastian

2017-01-01

Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

Science.gov (United States)

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

QUEUEING DISCIPLINES BASED ON PRIORITY MATRIX

Directory of Open Access Journals (Sweden)

Taufik I. Aliev

2014-11-01

Full Text Available The paper deals with queueing disciplines for demands of general type in queueing systems with multivendor load. A priority matrix is proposed to be used for the purpose of mathematical description of such disciplines, which represents the priority type (preemptive priority, not preemptive priority or no priority between any two demands classes. Having an intuitive and simple way of priority assignment, such description gives mathematical dependencies of system operation characteristics on its parameters. Requirements for priority matrix construction are formulated and the notion of canonical priority matrix is given. It is shown that not every matrix, constructed in accordance with such requirements, is correct. The notion of incorrect priority matrix is illustrated by an example, and it is shown that such matrixes do not ensure any unambiguousness and determinacy in design of algorithm, which realizes corresponding queueing discipline. Rules governing construction of correct matrixes are given for canonical priority matrixes. Residence time for demands of different classes in system, which is the sum of waiting time and service time, is considered as one of the most important characteristics. By introducing extra event method Laplace transforms for these characteristics are obtained, and mathematical dependencies are derived on their basis for calculation of two first moments for corresponding characteristics of demands queueing

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Kendall’s tau and agglomerative clustering for structure determination of hierarchical Archimedean copulas

Directory of Open Access Journals (Sweden)

Górecki J.

2017-01-01

Full Text Available Several successful approaches to structure determination of hierarchical Archimedean copulas (HACs proposed in the literature rely on agglomerative clustering and Kendall’s correlation coefficient. However, there has not been presented any theoretical proof justifying such approaches. This work fills this gap and introduces a theorem showing that, given the matrix of the pairwise Kendall correlation coefficients corresponding to a HAC, its structure can be recovered by an agglomerative clustering technique.

Three-Dimensional-Bioprinted Dopamine-Based Matrix for Promoting Neural Regeneration.

Science.gov (United States)

Zhou, Xuan; Cui, Haitao; Nowicki, Margaret; Miao, Shida; Lee, Se-Jun; Masood, Fahed; Harris, Brent T; Zhang, Lijie Grace

2018-03-14

Central nerve repair and regeneration remain challenging problems worldwide, largely because of the extremely weak inherent regenerative capacity and accompanying fibrosis of native nerves. Inadequate solutions to the unmet needs for clinical therapeutics encourage the development of novel strategies to promote nerve regeneration. Recently, 3D bioprinting techniques, as one of a set of valuable tissue engineering technologies, have shown great promise toward fabricating complex and customizable artificial tissue scaffolds. Gelatin methacrylate (GelMA) possesses excellent biocompatible and biodegradable properties because it contains many arginine-glycine-aspartic acids (RGD) and matrix metalloproteinase sequences. Dopamine (DA), as an essential neurotransmitter, has proven effective in regulating neuronal development and enhancing neurite outgrowth. In this study, GelMA-DA neural scaffolds with hierarchical structures were 3D-fabricated using our custom-designed stereolithography-based printer. DA was functionalized on GelMA to synthesize a biocompatible printable ink (GelMA-DA) for improving neural differentiation. Additionally, neural stem cells (NSCs) were employed as the primary cell source for these scaffolds because of their ability to terminally differentiate into a variety of cell types including neurons, astrocytes, and oligodendrocytes. The resultant GelMA-DA scaffolds exhibited a highly porous and interconnected 3D environment, which is favorable for supporting NSC growth. Confocal microscopy analysis of neural differentiation demonstrated that a distinct neural network was formed on the GelMA-DA scaffolds. In particular, the most significant improvements were the enhanced neuron gene expression of TUJ1 and MAP2. Overall, our results demonstrated that 3D-printed customizable GelMA-DA scaffolds have a positive role in promoting neural differentiation, which is promising for advancing nerve repair and regeneration in the future.

A nodal method based on matrix-response method

International Nuclear Information System (INIS)

Rocamora Junior, F.D.; Menezes, A.

1982-01-01

A nodal method based in the matrix-response method, is presented, and its application to spatial gradient problems, such as those that exist in fast reactors, near the core - blanket interface, is investigated. (E.G.) [pt

Kinetically Controlled Synthesis of Pt-Based One-Dimensional Hierarchically Porous Nanostructures with Large Mesopores as Highly Efficient ORR Catalysts.

Science.gov (United States)

Fu, Shaofang; Zhu, Chengzhou; Song, Junhua; Engelhard, Mark H; Xia, Haibing; Du, Dan; Lin, Yuehe

2016-12-28

Rational design and construction of Pt-based porous nanostructures with large mesopores have triggered significant considerations because of their high surface area and more efficient mass transport. Hydrochloric acid-induced kinetically controlled reduction of metal precursors in the presence of soft template F-127 and hard template tellurium nanowires has been successfully demonstrated to construct one-dimensional hierarchical porous PtCu alloy nanostructures with large mesopores. Moreover, the electrochemical experiments demonstrated that the PtCu hierarchically porous nanostructures synthesized under optimized conditions exhibit enhanced electrocatalytic performance for oxygen reduction reaction in acid media.

Kinetically Controlled Synthesis of Pt-Based One-Dimensional Hierarchically Porous Nanostructures with Large Mesopores as Highly Efficient ORR Catalysts

Energy Technology Data Exchange (ETDEWEB)

Fu, Shaofang; Zhu, Chengzhou; Song, Junhua; Engelhard, Mark H.; Xia, Haibing; Du, Dan; Lin, Yuehe

2016-12-28

Rational design and construction of Pt-based porous nanostructures with large mesopores have triggered significant considerations because of their high surface area and more efficient mass transport. Hydrochloric acid-induced kinetic reduction of metal precursors in the presence of soft template F-127 and hard template tellurium nanowires has been successfully demonstrated to construct one-dimensional hierarchical porous PtCu alloy nanostructures with large mesopores. Moreover, the electrochemical experiments demonstrated that the resultant PtCu hierarchically porous nanostructures with optimized composition exhibit enhanced electrocatalytic performance for oxygen reduction reaction.

Hierarchical model-based predictive control of a power plant portfolio

DEFF Research Database (Denmark)

Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp

2011-01-01

One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...... optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...

Hierarchical multi-scale classification of nearshore aquatic habitats of the Great Lakes: Western Lake Erie

Science.gov (United States)

McKenna, J.E.; Castiglione, C.

2010-01-01

Classification is a valuable conservation tool for examining natural resource status and problems and is being developed for coastal aquatic habitats. We present an objective, multi-scale hydrospatial framework for nearshore areas of the Great Lakes. The hydrospatial framework consists of spatial units at eight hierarchical scales from the North American Continent to the individual 270-m spatial cell. Characterization of spatial units based on fish abundance and diversity provides a fish-guided classification of aquatic areas at each spatial scale and demonstrates how classifications may be generated from that framework. Those classification units then provide information about habitat, as well as biotic conditions, which can be compared, contrasted, and hierarchically related spatially. Examples within several representative coastal or open water zones of the Western Lake Erie pilot area highlight potential application of this classification system to management problems. This classification system can assist natural resource managers with planning and establishing priorities for aquatic habitat protection, developing rehabilitation strategies, or identifying special management actions.

Hierarchical structure of the European countries based on debts as a percentage of GDP during the 2000-2011 period

Science.gov (United States)

Kantar, Ersin; Deviren, Bayram; Keskin, Mustafa

2014-11-01

We investigate hierarchical structures of the European countries by using debt as a percentage of Gross Domestic Product (GDP) of the countries as they change over a certain period of time. We obtain the topological properties among the countries based on debt as a percentage of GDP of European countries over the period 2000-2011 by using the concept of hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)). This period is also divided into two sub-periods related to 2004 enlargement of the European Union, namely 2000-2004 and 2005-2011, in order to test various time-window and observe the temporal evolution. The bootstrap techniques is applied to see a value of statistical reliability of the links of the MSTs and HTs. The clustering linkage procedure is also used to observe the cluster structure more clearly. From the structural topologies of these trees, we identify different clusters of countries according to their level of debts. Our results show that by the debt crisis, the less and most affected Eurozone’s economies are formed as a cluster with each other in the MSTs and hierarchical trees.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

OpenAIRE

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-01-01

Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without ex...

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir

2018-02-24

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Charara, Ali; Keyes, David E.

2018-01-01

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

Multi-documents summarization based on clustering of learning object using hierarchical clustering

Science.gov (United States)

Mustamiin, M.; Budi, I.; Santoso, H. B.

2018-03-01

The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

RBAC-Matrix-based EMR right management system to improve HIPAA compliance.

Science.gov (United States)

Lee, Hung-Chang; Chang, Shih-Hsin

2012-10-01

Security control of Electronic Medical Record (EMR) is a mechanism used to manage electronic medical records files and protect sensitive medical records document from information leakage. Researches proposed the Role-Based Access Control(RBAC). However, with the increasing scale of medical institutions, the access control behavior is difficult to have a detailed declaration among roles in RBAC. Furthermore, with the stringent specifications such as the U.S. HIPAA and Canada PIPEDA etc., patients are encouraged to have the right in regulating the access control of his EMR. In response to these problems, we propose an EMR digital rights management system, which is a RBAC-based extension to a matrix organization of medical institutions, known as RBAC-Matrix. With the aim of authorizing the EMR among roles in the organization, RBAC-Matrix also allow patients to be involved in defining access rights of his records. RBAC-Matrix authorizes access control declaration among matrix organizations of medical institutions by using XrML file in association with each EMR. It processes XrML rights declaration file-based authorization of behavior in the two-stage design, called master & servant stage, thus makes the associated EMR to be better protected. RBAC-Matrix will also make medical record file and its associated XrML declaration to two different EMRA(EMR Authorization)roles, namely, the medical records Document Creator (DC) and the medical records Document Right Setting (DRS). Access right setting, determined by the DRS, is cosigned by the patient, thus make the declaration of rights and the use of EMR to comply with HIPAA specifications.

Detecting Hierarchical Structure in Networks

DEFF Research Database (Denmark)

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

2012-01-01

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...... 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....... 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....

Hierarchical Agent-Based Integrated Modelling Approach for Microgrids with Adoption of EVs and HRES

Directory of Open Access Journals (Sweden)

Peng Han

2014-01-01

Full Text Available The large adoption of electric vehicles (EVs, hybrid renewable energy systems (HRESs, and the increasing of the loads shall bring significant challenges to the microgrid. The methodology to model microgrid with high EVs and HRESs penetrations is the key to EVs adoption assessment and optimized HRESs deployment. However, considering the complex interactions of the microgrid containing massive EVs and HRESs, any previous single modelling approaches are insufficient. Therefore in this paper, the methodology named Hierarchical Agent-based Integrated Modelling Approach (HAIMA is proposed. With the effective integration of the agent-based modelling with other advanced modelling approaches, the proposed approach theoretically contributes to a new microgrid model hierarchically constituted by microgrid management layer, component layer, and event layer. Then the HAIMA further links the key parameters and interconnects them to achieve the interactions of the whole model. Furthermore, HAIMA practically contributes to a comprehensive microgrid operation system, through which the assessment of the proposed model and the impact of the EVs adoption are achieved. Simulations show that the proposed HAIMA methodology will be beneficial for the microgrid study and EV’s operation assessment and shall be further utilized for the energy management, electricity consumption prediction, the EV scheduling control, and HRES deployment optimization.

Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

Energy Technology Data Exchange (ETDEWEB)

Xiong, Xiaopeng, E-mail: xpxiong@xmu.edu.cn; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju [Xiamen University, Department of Materials Science and Engineering, College of Materials (China)

2013-08-15

We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30-70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials.

Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

Science.gov (United States)

Xiong, Xiaopeng; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju

2013-08-01

We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30-70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials.

Novel hierarchical microparticles super-assembled from nanoparticles with the induction of casein micelles

International Nuclear Information System (INIS)

Xiong, Xiaopeng; Duan, Jiangjiang; Wang, Yong; Yu, Zhaoju

2013-01-01

We have demonstrated a solution-based synthesis of novel waxberry-like hierarchical ZnO microparticles in the presence casein micelles under mild conditions. The microstructures of the sub-micrometer-sized hierarchical microparticles were characterized, and the synthesis conditions were optimized. The formation mechanism of the hierarchical microparticle was analyzed through control experiments. The hierarchical ZnO microparticles are found to be super-assemblies of 30–70 nm ZnO nanoparticles, which are thought to be based on casein micelle induction followed by Ostwald ripening. In the same manner, copper-based hierarchical microparticles with a similar morphology have also been successfully synthesized. By controlling the synthetic time or temperature, solid or hollow microparticles can be fabricated. The narrowly distributed ZnO microparticles have a high specific surface area, exhibiting great potential application in fields such as photocatalytic and energy conversion. Our findings may meanwhile open a new bottom-up strategy in order to construct structurally sophisticated nanomaterials

Online credit card fraud prediction based on hierarchical temporal ...

African Journals Online (AJOL)

This understanding gave birth to the Hierarchical Temporal Memory (HTM) which holds a lot of promises in the area of time-series prediction and anomaly detection problems. This paper demonstrates the behaviour of an HTM model with respect to its learning and prediction of online credit card fraud. The model was ...

Using a matrix-analytical approach to synthesizing evidence solved incompatibility problem in the hierarchy of evidence.

Science.gov (United States)

Walach, Harald; Loef, Martin

2015-11-01

The hierarchy of evidence presupposes linearity and additivity of effects, as well as commutativity of knowledge structures. It thereby implicitly assumes a classical theoretical model. This is an argumentative article that uses theoretical analysis based on pertinent literature and known facts to examine the standard view of methodology. We show that the assumptions of the hierarchical model are wrong. The knowledge structures gained by various types of studies are not sequentially indifferent, that is, do not commute. External validity and internal validity are at least partially incompatible concepts. Therefore, one needs a different theoretical structure, typical of quantum-type theories, to model this situation. The consequence of this situation is that the implicit assumptions of the hierarchical model are wrong, if generalized to the concept of evidence in total. The problem can be solved by using a matrix-analytical approach to synthesizing evidence. Here, research methods that produce different types of evidence that complement each other are synthesized to yield the full knowledge. We show by an example how this might work. We conclude that the hierarchical model should be complemented by a broader reasoning in methodology. Copyright © 2015 Elsevier Inc. All rights reserved.

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

Science.gov (United States)

Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Interval-valued intuitionistic fuzzy matrix games based on Archimedean t-conorm and t-norm

Science.gov (United States)

Xia, Meimei

2018-04-01

Fuzzy game theory has been applied in many decision-making problems. The matrix game with interval-valued intuitionistic fuzzy numbers (IVIFNs) is investigated based on Archimedean t-conorm and t-norm. The existing matrix games with IVIFNs are all based on Algebraic t-conorm and t-norm, which are special cases of Archimedean t-conorm and t-norm. In this paper, the intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm are employed to aggregate the payoffs of players. To derive the solution of the matrix game with IVIFNs, several mathematical programming models are developed based on Archimedean t-conorm and t-norm. The proposed models can be transformed into a pair of primal-dual linear programming models, based on which, the solution of the matrix game with IVIFNs is obtained. It is proved that the theorems being valid in the exiting matrix game with IVIFNs are still true when the general aggregation operator is used in the proposed matrix game with IVIFNs. The proposed method is an extension of the existing ones and can provide more choices for players. An example is given to illustrate the validity and the applicability of the proposed method.

Comparison of CT based-CTV plan and CT based-ICRU38 plan in brachytherapy planning of uterine cervix cancer

International Nuclear Information System (INIS)

Cho, Jung Keun; Han, Tae Jong

2007-01-01

Purpose : In spite of recent remarkable improvement of diagnostic imaging modalities such as CT, MRI, and PET and radiation therapy planing systems, ICR plan of uterine cervix cancer, based on recommendation of ICRU38(2D film-based) such as point A, is still used widely. A 3-dimensional ICR plan based on CT image provides Dose-Volume Histogram(DVH) information of the tumor and normal tissue. In this study, we compared tumor-dose, rectal-dose and bladder-dose through an analysis of DVH between CTV plan and ICRU38 plan based on CT image. Method and Material : We analyzed 11 patients with a cervix cancer who received the ICR of Ir-192 HDR. After 40Gy of external beam radiation therapy, ICR plan was established using PLATO(Nucletron) v.14.2 planning system. CT scan was done to all the patients using CT-simulator(Ultra Z, Philips). We contoured CTV, rectum and bladder on the CT image and established CTV plan which delivers the 100% dose to CTV and ICRU plan which delivers the 100% dose to the point A. Result : The volume(average±SD) of CTV, rectum and bladder in all of 11 patients is 21.8±6.6cm 3 , 60.9±25.0cm 3 , 111.6±40.1cm 3 respectively. The volume covered by 100% isodose curve is 126.7±18.9cm 3 in ICRU plan and 98.2±74.5cm 3 in CTV plan(p=0.0001), respectively. In (On) ICRU planning 22.0cm 3 of CTV volume was not covered by 100% isodose curve in one patient whose residual tumor size is greater than 4cm, while more than 100% dose was irradiated unnecessarily to the normal organ of 62.2±4.8cm 3 other than the tumor in the remaining 10 patients with a residual tumor less than 4cm in size. Bladder dose recommended by ICRU 38 was 90.1±21.3% and 68.7±26.6% in ICRU plan and in CTV plan respectively(p=0.001) while rectal dose recommended by ICRU 38 was 86.4±18.3% and 76.9±15.6% in ICRU plan and in CTV plan, respectively(p=0.08). Bladder and rectum maximum dose was 137.2±50.1%, 101.1±41.8% in ICRU plan and 107.6±47.9%, 86.9±30.8% in CTV plan, respectively

Electrochemical design of ZnO hierarchical structures for dye-sensitized solar cells

Czech Academy of Sciences Publication Activity Database

Guerin, V. M.; Rathouský, Jiří; Pauporté, T.

2012-01-01

Roč. 102, JUL 2012 (2012), s. 8-14 ISSN 0927-0248 R&D Projects: GA AV ČR KAN100400702 Institutional research plan: CEZ:AV0Z40400503 Keywords : ZnO hierarchical structures * epitaxy * dye-sensitized solar cell Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.630, year: 2012

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

Environmental Impact Assessment of the Industrial Estate Development Plan with the Geographical Information System and Matrix Methods

Science.gov (United States)

Ghasemian, Mohammad; Poursafa, Parinaz; Amin, Mohammad Mehdi; Ziarati, Mohammad; Ghoddousi, Hamid; Momeni, Seyyed Alireza; Rezaei, Amir Hossein

2012-01-01

Background. The purpose of this study is environmental impact assessment of the industrial estate development planning. Methods. This cross-sectional study was conducted in 2010 in Isfahan province, Iran. GIS and matrix methods were applied. Data analysis was done to identify the current situation of the region, zoning vulnerable areas, and scoping the region. Quantitative evaluation was done by using matrix of Wooten and Rau. Results. The net score for impact of industrial units operation on air quality of the project area was (−3). According to the transition of industrial estate pollutants, residential places located in the radius of 2500 meters of the city were expected to be affected more. The net score for impact of construction of industrial units on plant species of the project area was (−2). Environmental protected areas were not affected by the air and soil pollutants because of their distance from industrial estate. Conclusion. Positive effects of project activities outweigh the drawbacks and the sum scores allocated to the project activities on environmental factor was (+37). Totally it does not have detrimental effects on the environment and residential neighborhood. EIA should be considered as an anticipatory, participatory environmental management tool before determining a plan application. PMID:22272210

Environmental Impact Assessment of the Industrial Estate Development Plan with the Geographical Information System and Matrix Methods

Directory of Open Access Journals (Sweden)

Mohammad Ghasemian

2012-01-01

Full Text Available Background. The purpose of this study is environmental impact assessment of the industrial estate development planning. Methods. This cross-sectional study was conducted in 2010 in Isfahan province, Iran. GIS and matrix methods were applied. Data analysis was done to identify the current situation of the region, zoning vulnerable areas, and scoping the region. Quantitative evaluation was done by using matrix of Wooten and Rau. Results. The net score for impact of industrial units operation on air quality of the project area was (−3. According to the transition of industrial estate pollutants, residential places located in the radius of 2500 meters of the city were expected to be affected more. The net score for impact of construction of industrial units on plant species of the project area was (−2. Environmental protected areas were not affected by the air and soil pollutants because of their distance from industrial estate. Conclusion. Positive effects of project activities outweigh the drawbacks and the sum scores allocated to the project activities on environmental factor was (+37. Totally it does not have detrimental effects on the environment and residential neighborhood. EIA should be considered as an anticipatory, participatory environmental management tool before determining a plan application.

Environmental Impact Assessment of the Industrial Estate Development Plan with the Geographical Information System and Matrix Methods

International Nuclear Information System (INIS)

Ghasemian, M.; Poursafa, P.; Amin, O.M.; Rezaei, A.H.; Ziarati, M.; Ghoddousi, H.; Momeni, S.A.; Rezaei, A.H.

2012-01-01

Background. The purpose of this study is environmental impact assessment of the industrial estate development planning. Methods. This cross-sectional study was conducted in 2010 in Isfahan province, Iran. GIS and matrix methods were applied. Data analysis was done to identify the current situation of the region, zoning vulnerable areas, and scoping the region. Quantitative evaluation was done by using matrix of Wooten and Rau. Results. The net score for impact of industrial units operation on air quality of the project area was (-3). According to the transition of industrial estate pollutants, residential places located in the radius of 2500 meters of the city were expected to be affected more. The net score for impact of construction of industrial units on plant species of the project area was (-2). Environmental protected areas were not affected by the air and soil pollutants because of their distance from industrial estate. Conclusion. Positive effects of project activities outweigh the drawbacks and the sum scores allocated to the project activities on environmental factor was (+37). Totally it does not have detrimental effects on the environment and residential neighborhood. EIA should be considered as an anticipatory, participatory environmental management tool before determining a plan application

Convergence analysis of modulus-based matrix splitting iterative methods for implicit complementarity problems.

Science.gov (United States)

Wang, An; Cao, Yang; Shi, Quan

2018-01-01

In this paper, we demonstrate a complete version of the convergence theory of the modulus-based matrix splitting iteration methods for solving a class of implicit complementarity problems proposed by Hong and Li (Numer. Linear Algebra Appl. 23:629-641, 2016). New convergence conditions are presented when the system matrix is a positive-definite matrix and an [Formula: see text]-matrix, respectively.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

International Nuclear Information System (INIS)

Enoki, Motohiro; Ishiyama, Tomoaki; Kobayashi, Masakazu A. R.; Nagashima, Masahiro

2014-01-01

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Anti-hierarchical evolution of the active galactic nucleus space density in a hierarchical universe

Energy Technology Data Exchange (ETDEWEB)

Enoki, Motohiro [Faculty of Business Administration, Tokyo Keizai University, Kokubunji, Tokyo 185-8502 (Japan); Ishiyama, Tomoaki [Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Kobayashi, Masakazu A. R. [Research Center for Space and Cosmic Evolution, Ehime University, Matsuyama, Ehime 790-8577 (Japan); Nagashima, Masahiro, E-mail: enokimt@tku.ac.jp [Faculty of Education, Nagasaki University, Nagasaki, Nagasaki 852-8521 (Japan)

2014-10-10

Recent observations show that the space density of luminous active galactic nuclei (AGNs) peaks at higher redshifts than that of faint AGNs. This downsizing trend in the AGN evolution seems to be contradictory to the hierarchical structure formation scenario. In this study, we present the AGN space density evolution predicted by a semi-analytic model of galaxy and AGN formation based on the hierarchical structure formation scenario. We demonstrate that our model can reproduce the downsizing trend of the AGN space density evolution. The reason for the downsizing trend in our model is a combination of the cold gas depletion as a consequence of star formation, the gas cooling suppression in massive halos, and the AGN lifetime scaling with the dynamical timescale. We assume that a major merger of galaxies causes a starburst, spheroid formation, and cold gas accretion onto a supermassive black hole (SMBH). We also assume that this cold gas accretion triggers AGN activity. Since the cold gas is mainly depleted by star formation and gas cooling is suppressed in massive dark halos, the amount of cold gas accreted onto SMBHs decreases with cosmic time. Moreover, AGN lifetime increases with cosmic time. Thus, at low redshifts, major mergers do not always lead to luminous AGNs. Because the luminosity of AGNs is correlated with the mass of accreted gas onto SMBHs, the space density of luminous AGNs decreases more quickly than that of faint AGNs. We conclude that the anti-hierarchical evolution of the AGN space density is not contradictory to the hierarchical structure formation scenario.

Immobilization of Bacillus subtilis lipase on a Cu-BTC based hierarchically porous metal-organic framework material: a biocatalyst for esterification.

Science.gov (United States)

Cao, Yu; Wu, Zhuofu; Wang, Tao; Xiao, Yu; Huo, Qisheng; Liu, Yunling

2016-04-28

Bacillus subtilis lipase (BSL2) has been successfully immobilized into a Cu-BTC based hierarchically porous metal-organic framework material for the first time. The Cu-BTC hierarchically porous MOF material with large mesopore apertures is prepared conveniently by using a template-free strategy under mild conditions. The immobilized BSL2 presents high enzymatic activity and perfect reusability during the esterification reaction. After 10 cycles, the immobilized BSL2 still exhibits 90.7% of its initial enzymatic activity and 99.6% of its initial conversion.

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.

Hierarchical-control-based output synchronization of coexisting attractor networks

International Nuclear Information System (INIS)

Yun-Zhong, Song; Yi-Fa, Tang

2010-01-01

This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production

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Sebastian Sauppe

2017-09-01

Full Text Available Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

A Hierarchical Linear Model for Estimating Gender-Based Earnings Differentials.

Science.gov (United States)

Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

1998-01-01

Estimates of gender earnings inequality in data from 116,431 Jewish workers were compared using a hierarchical linear model (HLM) and ordinary least squares model. The HLM allows estimation of the extent to which earnings inequality depends on occupational characteristics. (SK)

A Spreadsheet-Based, Matrix Formulation Linear Programming Lesson

DEFF Research Database (Denmark)

Harrod, Steven

2009-01-01

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

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...

Reduced density matrix functional theory via a wave function based approach

Energy Technology Data Exchange (ETDEWEB)

Schade, Robert; Bloechl, Peter [Institute for Theoretical Physics, Clausthal University of Technology, Clausthal (Germany); Pruschke, Thomas [Institute for Theoretical Physics, University of Goettingen, Goettingen (Germany)

2016-07-01

We propose a new method for the calculation of the electronic and atomic structure of correlated electron systems based on reduced density matrix functional theory (rDMFT). The density-matrix functional is evaluated on the fly using Levy's constrained search formalism. The present implementation rests on a local approximation of the interaction reminiscent to that of dynamical mean field theory (DMFT). We focus here on additional approximations to the exact density-matrix functional in the local approximation and evaluate their performance.

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

Science.gov (United States)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

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.

Hierarchical species distribution models

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Analytical and numerical studies of creation probabilities of hierarchical trees

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S.S. Borysov

2011-03-01

Full Text Available We consider the creation conditions of diverse hierarchical trees both analytically and numerically. A connection between the probabilities to create hierarchical levels and the probability to associate these levels into a united structure is studied. We argue that a consistent probabilistic picture requires the use of deformed algebra. Our consideration is based on the study of the main types of hierarchical trees, among which both regular and degenerate ones are studied analytically, while the creation probabilities of Fibonacci, scale-free and arbitrary trees are determined numerically.

Ensemble-based hierarchical multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. Van den; Jansen, J.D.

2014-01-01

In an earlier study, two hierarchical multiobjective methods were suggested to include short-term targets in life-cycle production optimization. However, this earlier study has two limitations: (1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

Ensemble-based hierarchical multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Van den Hof, P.M.J.; Jansen, J.D.

2014-01-01

In an earlier study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this earlier study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

Real-Time Pricing-Based Scheduling Strategy in Smart Grids: A Hierarchical Game Approach

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Jie Yang

2014-01-01

Full Text Available This paper proposes a scheduling strategy based on real-time pricing in smart grids. A hierarchical game is employed to analyze the decision-making process of generators and consumers. We prove the existence and uniqueness of Nash equilibrium and utilize a backward induction method to obtain the generation and consumption strategies. Then, we propose two dynamic algorithms for the generators and consumers to search for the equilibrium in a distributed fashion. Simulation results demonstrate that the proposed scheduling strategy can match supply with demand and shift load away from peak time.

Matrix-based system reliability method and applications to bridge networks

International Nuclear Information System (INIS)

Kang, W.-H.; Song Junho; Gardoni, Paolo

2008-01-01

Using a matrix-based system reliability (MSR) method, one can estimate the probabilities of complex system events by simple matrix calculations. Unlike existing system reliability methods whose complexity depends highly on that of the system event, the MSR method describes any general system event in a simple matrix form and therefore provides a more convenient way of handling the system event and estimating its probability. Even in the case where one has incomplete information on the component probabilities and/or the statistical dependence thereof, the matrix-based framework enables us to estimate the narrowest bounds on the system failure probability by linear programming. This paper presents the MSR method and applies it to a transportation network consisting of bridge structures. The seismic failure probabilities of bridges are estimated by use of the predictive fragility curves developed by a Bayesian methodology based on experimental data and existing deterministic models of the seismic capacity and demand. Using the MSR method, the probability of disconnection between each city/county and a critical facility is estimated. The probability mass function of the number of failed bridges is computed as well. In order to quantify the relative importance of bridges, the MSR method is used to compute the conditional probabilities of bridge failures given that there is at least one city disconnected from the critical facility. The bounds on the probability of disconnection are also obtained for cases with incomplete information

Constructing HVS-Based Optimal Substitution Matrix Using Enhanced Differential Evolution

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Shu-Fen Tu

2013-01-01

Full Text Available Least significant bit (LSB substitution is a method of information hiding. The secret message is embedded into the last k bits of a cover-image in order to evade the notice of hackers. The security and stego-image quality are two main limitations of the LSB substitution method. Therefore, some researchers have proposed an LSB substitution matrix to address these two issues. Finding the optimal LSB substitution matrix can be conceptualized as a problem of combinatorial optimization. In this paper, we adopt a different heuristic method based on other researchers’ method, called enhanced differential evolution (EDE, to construct an optimal LSB substitution matrix. Differing from other researchers, we adopt an HVS-based measurement as a fitness function and embed the secret by modifying the pixel to a closest value rather than simply substituting the LSBs. Our scheme extracts the secret by modular operations as simple LSB substitution does. The experimental results show that the proposed embedding algorithm indeed improves imperceptibility of stego-images substantially.

Certification plan for safety and PRA codes

International Nuclear Information System (INIS)

Toffer, H.; Crowe, R.D.; Ades, M.J.

1990-05-01

A certification plan for computer codes used in Safety Analyses and Probabilistic Risk Assessment (PRA) for the operation of the Savannah River Site (SRS) reactors has been prepared. An action matrix, checklists, and a time schedule have been included in the plan. These items identify what is required to achieve certification of the codes. A list of Safety Analysis and Probabilistic Risk Assessment (SA ampersand PRA) computer codes covered by the certification plan has been assembled. A description of each of the codes was provided in Reference 4. The action matrix for the configuration control plan identifies code specific requirements that need to be met to achieve the certification plan's objectives. The checklist covers the specific procedures that are required to support the configuration control effort and supplement the software life cycle procedures based on QAP 20-1 (Reference 7). A qualification checklist for users establishes the minimum prerequisites and training for achieving levels of proficiency in using configuration controlled codes for critical parameter calculations

Class hierarchical test case generation algorithm based on expanded EMDPN model

Institute of Scientific and Technical Information of China (English)

LI Jun-yi; GONG Hong-fang; HU Ji-ping; ZOU Bei-ji; SUN Jia-guang

2006-01-01

A new model of event and message driven Petri network(EMDPN) based on the characteristic of class interaction for messages passing between two objects was extended. Using EMDPN interaction graph, a class hierarchical test-case generation algorithm with cooperated paths (copaths) was proposed, which can be used to solve the problems resulting from the class inheritance mechanism encountered in object-oriented software testing such as oracle, message transfer errors, and unreachable statement. Finally, the testing sufficiency was analyzed with the ordered sequence testing criterion(OSC). The results indicate that the test cases stemmed from newly proposed automatic algorithm of copaths generation satisfies synchronization message sequences testing criteria, therefore the proposed new algorithm of copaths generation has a good coverage rate.

Static and dynamic friction of hierarchical surfaces.

Science.gov (United States)

Costagliola, Gianluca; Bosia, Federico; Pugno, Nicola M

2016-12-01

Hierarchical structures are very common in nature, but only recently have they been systematically studied in materials science, in order to understand the specific effects they can have on the mechanical properties of various systems. Structural hierarchy provides a way to tune and optimize macroscopic mechanical properties starting from simple base constituents and new materials are nowadays designed exploiting this possibility. This can be true also in the field of tribology. In this paper we study the effect of hierarchical patterned surfaces on the static and dynamic friction coefficients of an elastic material. Our results are obtained by means of numerical simulations using a one-dimensional spring-block model, which has previously been used to investigate various aspects of friction. Despite the simplicity of the model, we highlight some possible mechanisms that explain how hierarchical structures can significantly modify the friction coefficients of a material, providing a means to achieve tunability.

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

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Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

2017-11-01

In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

HiPS - Hierarchical Progressive Survey Version 1.0

Science.gov (United States)

Fernique, Pierre; Allen, Mark; Boch, Thomas; Donaldson, Tom; Durand, Daniel; Ebisawa, Ken; Michel, Laurent; Salgado, Jesus; Stoehr, Felix; Fernique, Pierre

2017-05-01

This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.

Theoretical treatment of molecular photoionization based on the R-matrix method

International Nuclear Information System (INIS)

Tashiro, Motomichi

2012-01-01

The R-matrix method was implemented to treat molecular photoionization problem based on the UK R-matrix codes. This method was formulated to treat photoionization process long before, however, its application has been mostly limited to photoionization of atoms. Application of the method to valence photoionization as well as inner-shell photoionization process will be presented.

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

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.

Fabrication and condensation characteristics of metallic superhydrophobic surface with hierarchical micro-nano structures

Science.gov (United States)

Chu, Fuqiang; Wu, Xiaomin

2016-05-01

Metallic superhydrophobic surfaces have various applications in aerospace, refrigeration and other engineering fields due to their excellent water repellent characteristics. This study considers a simple but widely applicable fabrication method using a two simultaneous chemical reactions method to prepare the acid-salt mixed solutions to process the metal surfaces with surface deposition and surface etching to construct hierarchical micro-nano structures on the surface and then modify the surface with low surface-energy materials. Al-based and Cu-based superhydrophobic surfaces were fabricated using this method. The Al-based superhydrophobic surface had a water contact angle of 164° with hierarchical micro-nano structures similar to the lotus leaves. The Cu-based surface had a water contact angle of 157° with moss-like hierarchical micro-nano structures. Droplet condensation experiments were also performed on these two superhydrophobic surfaces to investigate their condensation characteristics. The results show that the Al-based superhydrophobic surface has lower droplet density, higher droplet jumping probability, slower droplet growth rate and lower surface coverage due to the more structured hierarchical structures.

On a hierarchical construction of the anisotropic LTSN solution from the isotropic LTSN solution

International Nuclear Information System (INIS)

Foletto, Taline; Segatto, Cynthia F.; Bodmann, Bardo E.; Vilhena, Marco T.

2015-01-01

In this work, we present a recursive scheme targeting the hierarchical construction of anisotropic LTS N solution from the isotropic LTS N solution. The main idea relies in the decomposition of the associated LTS N anisotropic matrix as a sum of two matrices in which one matrix contains the isotropic and the other anisotropic part of the problem. The matrix containing the anisotropic part is considered as the source of the isotropic problem. The solution of this problem is made by the decomposition of the angular flux as a truncated series of intermediate functions and replace in the isotropic equation. After the replacement of these into the split isotropic equation, we construct a set of isotropic recursive problems, that are readily solved by the classic LTS N isotropic method. We apply this methodology to solve problems considering homogeneous and heterogeneous anisotropic regions. Numerical results are presented and compared with the classical LTS N anisotropic solution. (author)

Hierarchical Control Strategy for Active Hydropneumatic Suspension Vehicles Based on Genetic Algorithms

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Jinzhi Feng

2015-02-01

Full Text Available A new hierarchical control strategy for active hydropneumatic suspension systems is proposed. This strategy considers the dynamic characteristics of the actuator. The top hierarchy controller uses a combined control scheme: a genetic algorithm- (GA- based self-tuning proportional-integral-derivative controller and a fuzzy logic controller. For practical implementations of the proposed control scheme, a GA-based self-learning process is initiated only when the defined performance index of vehicle dynamics exceeds a certain debounce time threshold. The designed control algorithm is implemented on a virtual prototype and cosimulations are performed with different road disturbance inputs. Cosimulation results show that the active hydropneumatic suspension system designed in this study significantly improves riding comfort characteristics of vehicles. The robustness and adaptability of the proposed controller are also examined when the control system is subjected to extremely rough road conditions.

A robust H∞ control-based hierarchical mode transition control system for plug-in hybrid electric vehicle

Science.gov (United States)

Yang, Chao; Jiao, Xiaohong; Li, Liang; Zhang, Yuanbo; Chen, Zheng

2018-01-01

To realize a fast and smooth operating mode transition process from electric driving mode to engine-on driving mode, this paper presents a novel robust hierarchical mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics models of powertrain and clutch actuating mechanism, a hierarchical control structure including two robust H∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H∞controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L2-gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed hierarchical control approach can obtain the good control performance: mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.

Hierarchically structured transparent hybrid membranes by in situ growth of mesostructured organosilica in host polymer

Science.gov (United States)

Vallé, Karine; Belleville, Philippe; Pereira, Franck; Sanchez, Clément

2006-02-01

The elaborate performances characterizing natural materials result from functional hierarchical constructions at scales ranging from nanometres to millimetres, each construction allowing the material to fit the physical or chemical demands occurring at these different levels. Hierarchically structured materials start to demonstrate a high input in numerous promising applied domains such as sensors, catalysis, optics, fuel cells, smart biologic and cosmetic vectors. In particular, hierarchical hybrid materials permit the accommodation of a maximum of elementary functions in a small volume, thereby optimizing complementary possibilities and properties between inorganic and organic components. The reported strategies combine sol-gel chemistry, self-assembly routes using templates that tune the material's architecture and texture with the use of larger inorganic, organic or biological templates such as latex, organogelator-derived fibres, nanolithographic techniques or controlled phase separation. We propose an approach to forming transparent hierarchical hybrid functionalized membranes using in situ generation of mesostructured hybrid phases inside a non-porogenic hydrophobic polymeric host matrix. We demonstrate that the control of the multiple affinities existing between organic and inorganic components allows us to design the length-scale partitioning of hybrid nanomaterials with tuned functionalities and desirable size organization from ångström to centimetre. After functionalization of the mesoporous hybrid silica component, the resulting membranes have good ionic conductivity offering interesting perspectives for the design of solid electrolytes, fuel cells and other ion-transport microdevices.

An Algorithm for Inspecting Self Check-in Airline Luggage Based on Hierarchical Clustering and Cube-fitting

Directory of Open Access Journals (Sweden)

Gao Qingji

2014-04-01

Full Text Available Airport passengers are required to put only one baggage each time in the check-in self-service so that the baggage can be detected and identified successfully. In order to automatically get the number of baggage that had been put on the conveyor belt, dual laser rangefinders are used to scan the outer contour of luggage in this paper. The algorithm based on hierarchical clustering and cube-fitting is proposed to inspect the number and dimension of airline luggage. Firstly, the point cloud is projected to vertical direction. By the analysis of one-dimensional clustering, the number and height of luggage will be quickly computed. Secondly, the method of nearest hierarchical clustering is applied to divide the point cloud if the above cannot be distinguished. It can preferably solve the difficult issue like crossing or overlapping pieces of baggage. Finally, the point cloud is projected to the horizontal plane. By rotating point cloud based on the centre, its minimum bounding rectangle (MBR is obtained. The length and width of luggage are got form MBR. Many experiments in different cases have been done to verify the effectiveness of the algorithm.

Interaction of light with hematite hierarchical structures: Experiments and simulations

Science.gov (United States)

Distaso, Monica; Zhuromskyy, Oleksander; Seemann, Benjamin; Pflug, Lukas; Mačković, Mirza; Encina, Ezequiel; Taylor, Robin Klupp; Müller, Rolf; Leugering, Günter; Spiecker, Erdmann; Peschel, Ulf; Peukert, Wolfgang

2017-03-01

Mesocrystalline particles have been recognized as a class of multifunctional materials with potential applications in different fields. However, the internal organization of nanocomposite mesocrystals and its influence on the final properties have not yet been investigated. In this paper, a novel strategy based on electrodynamic simulations is developed to shed light on how the internal structure of mesocrystals influences their optical properties. In a first instance, a unified design protocol is reported for the fabrication of hematite/PVP particles with different morphologies such as pseudo-cubes, rods-like and apple-like structures and controlled particle size distributions. The optical properties of hematite/PVP mesocrystals are effectively simulated by taking their aggregate and nanocomposite structure into consideration. The superposition T-Matrix approach accounts for the aggregate nature of mesocrystalline particles and validate the effective medium approximation used in the framework of the Mie theory and electromagnetic simulation such as Finite Element Method. The approach described in our paper provides the framework to understand and predict the optical properties of mesocrystals and more general, of hierarchical nanostructured particles.

Constraint-based Attribute and Interval Planning

Science.gov (United States)

Jonsson, Ari; Frank, Jeremy

2013-01-01

In this paper we describe Constraint-based Attribute and Interval Planning (CAIP), a paradigm for representing and reasoning about plans. The paradigm enables the description of planning domains with time, resources, concurrent activities, mutual exclusions among sets of activities, disjunctive preconditions and conditional effects. We provide a theoretical foundation for the paradigm, based on temporal intervals and attributes. We then show how the plans are naturally expressed by networks of constraints, and show that the process of planning maps directly to dynamic constraint reasoning. In addition, we de ne compatibilities, a compact mechanism for describing planning domains. We describe how this framework can incorporate the use of constraint reasoning technology to improve planning. Finally, we describe EUROPA, an implementation of the CAIP framework.

Matrix polyelectrolyte capsules based on polysaccharide/MnCO₃ hybrid microparticle templates.

Science.gov (United States)

Wei, Qingrong; Ai, Hua; Gu, Zhongwei

2011-06-15

An efficient strategy for biomacromolecule encapsulation based on spontaneous deposition into polysaccharide matrix-containing capsules is introduced in this study. First, hybrid microparticles composed of manganese carbonate and ionic polysaccharides including sodium hyaluronate (HA), sodium alginate (SA) and dextran sulfate sodium (DS) with narrow size distribution were synthesized to provide monodisperse templates. Incorporation of polysaccharide into the hybrid templates was successful as verified by thermogravimetric analysis (TGA) and confocal laser scanning microscopy (CLSM). Matrix polyelectrolyte microcapsules were fabricated through layer-by-layer (LbL) self-assembly of oppositely charged polyelectrolytes (PEs) onto the hybrid particles, followed by removal of the inorganic part of the cores, leaving polysaccharide matrix inside the capsules. The loading and release properties of the matrix microcapsules were investigated using myoglobin as a model biomacromolecule. Compared to matrix-free capsules, the matrix capsules had a much higher loading capacity up to four times; the driving force is mostly due to electrostatic interactions between myoglobin and the polysaccharide matrix. From our observations, for the same kind of polysaccharide, a higher amount of polysaccharide inside the capsules usually led to better loading capacity. The release behavior of the loaded myoglobin could be readily controlled by altering the environmental pH. These matrix microcapsules may be used as efficient delivery systems for various charged water-soluble macromolecules with applications in biomedical fields. Copyright © 2010 Elsevier B.V. All rights reserved.

Hierarchical structure of biological systems: a bioengineering approach.

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.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

A new plan quality index for nasopharyngeal cancer SIB IMRT.

Science.gov (United States)

Jin, X; Yi, J; Zhou, Y; Yan, H; Han, C; Xie, C

2014-02-01

A new plan quality index integrating dosimetric and radiobiological indices was proposed to facilitate the evaluation and comparison of simultaneous integrated boost (SIB) intensity modulated radiotherapy (IMRT) plans for nasopharyngeal cancer (NPC) patients. Ten NPC patients treated by SIB-IMRT were enrolled in the study. Custom software was developed to read dose-volume histogram (DVH) curves from the treatment planning system (TPS). A plan filtering matrix was introduced to filter plans that fail to satisfy treatment protocol. Target plan quality indices and organ at risk (OAR) plan quality indices were calculated for qualified plans. A unique composite plan quality index (CPQI) was proposed based on the relative weight of these indices to evaluate and compare competing plans. Plan ranking results were compared with detailed statistical analysis, radiation oncology quality system (ROQS) scoring results and physician's evaluation results to verify the accuracy of this new plan quality index. The average CPQI values for plans with OAR priority of low, normal, high, and PTV only were 0.22 ± 0.08, 0.49 ± 0.077, 0.71 ± 0.062, and -0.21 ± 0.16, respectively. There were significant differences among these plan quality indices (One-way ANOVA test, p plans were selected. Plan filtering matrix was able to speed up the plan evaluation process. The new matrix plan quality index CPQI showed good consistence with physician ranking results. It is a promising index for NPC SIB-IMRT plan evaluation. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Measuring methods of matrix diffusion

International Nuclear Information System (INIS)

Muurinen, A.; Valkiainen, M.

1988-03-01

In Finland the spent nuclear fuel is planned to be disposed of at large depths in crystalline bedrock. The radionuclides which are dissolved in the groundwater may be able to diffuse into the micropores of the porous rock matrix and thus be withdrawn from the flowing water in the fractures. This phenomenon is called matrix diffusion. A review over matrix diffusion is presented in the study. The main interest is directed to the diffusion of non-sorbing species. The review covers diffusion experiments and measurements of porosity, pore size, specific surface area and water permeability

Hyaluronic acid based hydrogel system for soft tissue regeneration and drug delivery

Science.gov (United States)

Jha, Amit Kumar

We have developed hyaluronic acid (HA)-based, biomimetic hydrogel matrices that are hierarchically structured, mechanically robust and biologically active. Specifically, HA-based hydrogel particles (HGPs) with controlled sizes, defined porosity, and improved stability were synthesized using different inverse emulsion systems and crosslinking chemistries. The resultant particles either contained residual functional groups or were rendered reactive by subsequent chemical modifications. HA-based doubly crosslinked networks (DXNs) were synthesized via covalent crosslinking of HA HGPs with soluble HA macromers carrying mutually reactive functional groups. These hybrid matrices are hierarchical in nature, consisting of densely crosslinked HGPs integrated in a loosely connected secondary matrix. Their mechanical properties and degradation kinetics can be readily tuned by varying the particle size, functional group density, intra- and interparticle crosslinking. To improve the biological functions of HA HGPs, perlecan domain I (PlnDI), a basement membrane proteoglycan that has strong affinity for various heparin binding growth factors (HBGFs), was successfully conjugated to the particles through the core protein via a flexible poly(ethylene glycol) (PEG) linker. The immobilized PlnDI maintains its ability to bind bone morphogenetic proteins (BMP-2) and modulates its in vitro release. A similar, sustained release of BMP-2 was achieved by encapsulating BMP-2-loaded HGPs within a photocrosslinked HA matrix. When encapsulated in HA DXNs, primary bovine chondrocytes were able to maintain their phenotype, proliferate readily and produce abundant glycosaminoglycan. Finally, cell-adhesive HA DXNs were fabricated by encapsulating gelatin-decorated HA HGPs in a secondary HA matrix. Human MSCs were shown to adhere to the composite matrix through the focal adhesion sites clustered on particle surface. The cell-adhesive composite matrices supported hMSC proliferation and migration into

Hierarchical sets: analyzing pangenome structure through scalable set visualizations

Science.gov (United States)

2017-01-01

Abstract Motivation: The increase in available microbial genome sequences has resulted in an increase in the size of the pangenomes being analyzed. Current pangenome visualizations are not intended for the pangenome sizes possible today and new approaches are necessary in order to convert the increase in available information to increase in knowledge. As the pangenome data structure is essentially a collection of sets we explore the potential for scalable set visualization as a tool for pangenome analysis. Results: We present a new hierarchical clustering algorithm based on set arithmetics that optimizes the intersection sizes along the branches. The intersection and union sizes along the hierarchy are visualized using a composite dendrogram and icicle plot, which, in pangenome context, shows the evolution of pangenome and core size along the evolutionary hierarchy. Outlying elements, i.e. elements whose presence pattern do not correspond with the hierarchy, can be visualized using hierarchical edge bundles. When applied to pangenome data this plot shows putative horizontal gene transfers between the genomes and can highlight relationships between genomes that is not represented by the hierarchy. We illustrate the utility of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. Availability and Implementation: The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https://cran.r-project.org/web/packages/hierarchicalSets) Contact: thomasp85@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28130242

A Delphi-matrix approach to SEA and its application within the tourism sector in Taiwan

International Nuclear Information System (INIS)

Kuo, N.-W.; Hsiao, T.-Y.; Yu, Y.-H.

2005-01-01

Strategic Environmental Assessment (SEA) is a procedural tool and within the framework of SEA, several different types of analytical methods can be used in the assessment. However, the impact matrix used currently in Taiwan has some disadvantages. Hence, a Delphi-matrix approach to SEA is proposed here to improve the performance of Taiwan's SEA. This new approach is based on the impact matrix combination with indicators of sustainability, and then the Delphi method is employed to collect experts' opinions. In addition, the assessment of National Floriculture Park Plan and Taiwan Flora 2008 Program is taken as an example to examine this new method. Although international exhibition is one of the important tourism (economic) activities, SEA is seldom about tourism sector. Finally, the Delphi-matrix approach to SEA for tourism development plan is established containing eight assessment topics and 26 corresponding categories. In summary, three major types of impacts: resources' usages, pollution emissions, and local cultures change are found. Resources' usages, such as water, electricity, and natural gas demand, are calculated on a per capita basis. Various forms of pollution resulting from this plan, such as air, water, soil, waste, and noise, are also identified

Synthesis of hierarchical porous honeycomb carbon for lithium-sulfur battery cathode with high rate capability and long cycling stability

International Nuclear Information System (INIS)

Qu, Yaohui; Zhang, Zhian; Zhang, Xiahui; Ren, Guodong; Wang, Xiwen; Lai, Yanqing; Liu, Yexiang; Li, Jie

2014-01-01

Highlights: • A novel HPHC was prepared by a simple template process. • The HPHC as matrix to load sulfur for Lithium-Sulfur battery cathodes. • S-HPHC cathode shows high rate capability and long cycling stability. • The sulfur-HPHC composite presents electrochemical stability up to 300 cycles at 1.5 C. - Abstract: Sulfur has a high specific capacity of 1675 mAh g −1 as lithium battery cathode, but its rapid capacity fading due to polysulfides dissolution presents a significant challenge for practical applications. Here we report a novel hierarchical porous honeycomb carbon (HPHC) for lithium-sulfur battery cathode with effective trapping of polysulfides. The HPHC was prepared by a simple template process, and a sulfur-carbon composite based on HPHC was synthesized for lithium-sulfur batteries by a melt-diffusion method. It is found that the elemental sulfur was dispersed inside the three-dimensionally hierarchical pores of HPHC based on the analyses. Electrochemical tests reveal that the sulfur-HPHC composite shows high rate capability and long cycling stability as cathode materials. The sulfur-HPHC composite with sulfur content of 66.3 wt% displays an initial discharge capacity of 923 mAh g −1 and a reversible discharge capacity of 564 mAh g −1 after 100 cycles at 2 C charge-discharge rate. In particular, the sulfur-HPHC composite presents a long term cycling stability up to 300 cycles at 1.5 C. The results illustrate that the electrochemical reaction constrained inside the interconnected macro/meso/micropores of HPHC would be the dominant factor for the excellent high rate capability and long cycling stability of the sulfur cathode, and the three-dimensionally honeycomb carbon network would be a promising carbon matrix structure for lithium-sulfur battery cathode

Chitin/clay microspheres with hierarchical architecture for highly efficient removal of organic dyes.

Science.gov (United States)

Xu, Rui; Mao, Jie; Peng, Na; Luo, Xiaogang; Chang, Chunyu

2018-05-15

Numerous adsorbents have been reported for efficient removal of dye from water, but the high cost raw materials and complicated fabrication process limit their practical applications. Herein, novel nanocomposite microspheres were fabricated from chitin and clay by a simple thermally induced sol-gel transition. Clay nanosheets were uniformly embedded in a nanofiber weaved chitin microsphere matrix, leading to their hierarchical architecture. Benefiting from this unique structure, microspheres could efficiently remove methylene blue (MB) through a spontaneous physic-sorption process which fit well with pseudo-second-order and Langmuir isotherm models. The maximal values of adsorption capability obtained by calculation and experiment were 152.2 and 156.7 mg g -1 , respectively. Chitin/clay microspheres (CCM2) could remove 99.99% MB from its aqueous solution (10 mg g -1 ) within 20 min. These findings provide insight into a new strategy for fabrication of dye adsorbents with hierarchical structure from low cost raw materials. Copyright © 2018 Elsevier Ltd. All rights reserved.

An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data.

Directory of Open Access Journals (Sweden)

Jinjun Tang

Full Text Available An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly introduced to use historical positioning information to employ curve-curve matching between vehicle trajectories and shapes of candidate roads. It improves matching performance by overcoming the disadvantage of traditional map-matching algorithm only considering current information. An average historical distance is used to measure similarity between vehicle trajectories and road shape. The input of system includes three variables: distance between position point and candidate roads, angle between driving heading and road direction, and average distance. As the number of fuzzy rules will increase exponentially when adding average distance as a variable, a hierarchical fuzzy inference system is then applied to reduce fuzzy rules and improve the calculation efficiency. Additionally, a learning process is updated to support the algorithm. Finally, a case study contains four different routes in Beijing city is used to validate the effectiveness and superiority of the proposed method.

Carbon Nano tubes Based Mixed Matrix Membrane for Gas Separation

International Nuclear Information System (INIS)

Sanip, S.M.; Ismail, A.F.; Goh, P.S.; Norrdin, M.N.A.; Soga, T.; Tanemura, M.; Yasuhiko, H.

2011-01-01

Carbon nano tubes based mixed matrix membrane (MMM) was prepared by the solution casting method in which the functionalized multi walled carbon nano tubes (f-MWNTs) were embedded into the polyimide membrane and the resulting membranes were characterized. The effect of nominal MWNTs content between 0.5 and 1.0 wt % on the gas separation properties were looked into. The morphologies of the MMM also indicated that at 0.7 % loading of f- MWNTs, the structures of the MMM showed uniform finger-like structures which have facilitated the fast gas transport through the polymer matrix. It may also be concluded that addition of open ended and shortened MWNTs to the polymer matrix can improve its permeability by increasing diffusivity through the MWNTs smooth cavity. (author)

Matrix-Vector Based Fast Fourier Transformations on SDR Architectures

Directory of Open Access Journals (Sweden)

Y. He

2008-05-01

Full Text Available Today Discrete Fourier Transforms (DFTs are applied in various radio standards based on OFDM (Orthogonal Frequency Division Multiplex. It is important to gain a fast computational speed for the DFT, which is usually achieved by using specialized Fast Fourier Transform (FFT engines. However, in face of the Software Defined Radio (SDR development, more general (parallel processor architectures are often desirable, which are not tailored to FFT computations. Therefore, alternative approaches are required to reduce the complexity of the DFT. Starting from a matrix-vector based description of the FFT idea, we will present different factorizations of the DFT matrix, which allow a reduction of the complexity that lies between the original DFT and the minimum FFT complexity. The computational complexities of these factorizations and their suitability for implementation on different processor architectures are investigated.

BiOCl nanowire with hierarchical structure and its Raman features

International Nuclear Information System (INIS)

Tian Ye; Guo Chuanfei; Guo Yanjun; Wang Qi; Liu Qian

2012-01-01

BiOCl is a promising V-VI-VII-compound semiconductor with excellent optical and electrical properties, and has great potential applications in photo-catalysis, photoelectric, etc. We successfully synthesize BiOCl nanowire with a hierarchical structure by combining wet etch (top-down) with liquid phase crystal growth (bottom-up) process, opening a novel method to construct ordered bismuth-based nanostructures. The morphology and lattice structures of Bi nanowires, β-Bi 2 O 3 nanowires and BiOCl nanowires with the hierarchical structure are investigated by scanning electron microscope (SEM) and transition electron microscope (TEM). The formation mechanism of such ordered BiOCl hierarchical structure is considered to mainly originate from the highly preferred growth, which is governed by the lattice match between (1 1 0) facet of BiOCl and (2 2 0) or (0 0 2) facet of β-Bi 2 O 3 . A schematic model is also illustrated to depict the formation process of the ordered BiOCl hierarchical structure. In addition, Raman properties of the BiOCl nanowire with the hierarchical structure are investigated deeply.

Matrix product operators, matrix product states, and ab initio density matrix renormalization group algorithms

Science.gov (United States)

Chan, Garnet Kin-Lic; Keselman, Anna; Nakatani, Naoki; Li, Zhendong; White, Steven R.

2016-07-01

Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm use two superficially different languages: an older language of the renormalization group and renormalized operators, and a more recent language of matrix product states and matrix product operators. The same algorithm can appear dramatically different when written in the two different vocabularies. In this work, we carefully describe the translation between the two languages in several contexts. First, we describe how to efficiently implement the ab initio DMRG sweep using a matrix product operator based code, and the equivalence to the original renormalized operator implementation. Next we describe how to implement the general matrix product operator/matrix product state algebra within a pure renormalized operator-based DMRG code. Finally, we discuss two improvements of the ab initio DMRG sweep algorithm motivated by matrix product operator language: Hamiltonian compression, and a sum over operators representation that allows for perfect computational parallelism. The connections and correspondences described here serve to link the future developments with the past and are important in the efficient implementation of continuing advances in ab initio DMRG and related algorithms.

Settlement Networks in Polish Spatial Development Regional Plans

Science.gov (United States)

Sołtys, Jacek

2017-10-01

In 1999, ten years after the great political changes in Poland, 16 self-governed regions (in Polish: voivodeship) were created. According to Polish law, voivodeship spatial development plans, or regional plans in short, determine basic elements of the settlement network. No detailed regulations indicate the specific elements of the settlement network or what features of these elements should be determined. For this reason, centres as elements of the settlement network are variously named in different regions and take the form of various models. The purposes of the research described in this article are: (1) recognition and systematization of settlement network models determined in regional plans; and (2) assessment of the readability of determination in planning and its usefulness in the practice of regional policy. Six models of settlement networks in regional plans have been identified and classified into types and sub-types. Names of specific levels of centres indicate that they were classified according to two criteria: (1) level of services, which concerns only 5 voivodships; and (2) importance in development, which concerns the 11 other voivodships. The hierarchical model referring to the importance of development is less understandable than the one related to services. In the text of most plans, centres of services and centres of development are treated independently from their names. In some plans the functional types of towns and cities are indicated. In some voivodships, specifications in the plan text are too general and seem to be rather useless in the practice of regional policy. The author suggests that regional plans should determine two kinds of centres: hierarchical service centres and non-hierarchical centres of development. These centres should be further distinguished according to: (1) their role in the activation of surroundings; (2) their level of development and the necessity of action for their development; and (3) the types of actions

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

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Bilal Jan

2017-01-01

Full Text Available Wireless sensor networks (WSN are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment

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Muhammad Fayaz

2017-10-01

Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.

Hierarchical multiple binary image encryption based on a chaos and phase retrieval algorithm in the Fresnel domain

International Nuclear Information System (INIS)

Wang, Zhipeng; Hou, Chenxia; Lv, Xiaodong; Wang, Hongjuan; Gong, Qiong; Qin, Yi

2016-01-01

Based on the chaos and phase retrieval algorithm, a hierarchical multiple binary image encryption is proposed. In the encryption process, each plaintext is encrypted into a diffraction intensity pattern by two chaos-generated random phase masks (RPMs). Thereafter, the captured diffraction intensity patterns are partially selected by different binary masks and then combined together to form a single intensity pattern. The combined intensity pattern is saved as ciphertext. For decryption, an iterative phase retrieval algorithm is performed, in which a support constraint in the output plane and a median filtering operation are utilized to achieve a rapid convergence rate without a stagnation problem. The proposed scheme has a simple optical setup and large encryption capacity. In particular, it is well suited for constructing a hierarchical security system. The security and robustness of the proposal are also investigated. (letter)

Hierarchical processing in the prefrontal cortex in a variety of cognitive domains

Directory of Open Access Journals (Sweden)

Hyeon-Ae eJeon

2014-11-01

Full Text Available This review scrutinizes several findings on human hierarchical processing within the prefrontal cortex (PFC in diverse cognitive domains. Converging evidence from previous studies has shown that the PFC, specifically Brodmann area (BA 44, may function as the essential region for hierarchical processing across the domains. In language fMRI studies, BA 44 was significantly activated for the hierarchical processing of center-embedded sentences and this pattern of activations was also observed in artificial grammar. The same pattern was observed in the visuo-spatial domain where BA44 was actively involved in the processing of hierarchy for the visual symbol. Musical syntax, which is the rule-based arrangement of musical sets, has also been construed as hierarchical processing as in the language domain such that the activation in BA44 was observed in a chord sequence paradigm. P600 ERP was also engendered during the processing of musical hierarchy. Along with a longstanding idea that a human’s number faculty is developed as a by-product of language faculty, BA44 was closely involved in hierarchical processing in mental arithmetic. This review extended its discussion of hierarchical processing to hierarchical behavior, that is, human action which has been referred to as being hierarchically composed. Several lesion and TMS studies supported the involvement of BA44 for hierarchical processing in the action domain. Lastly, the hierarchical organization of cognitive controls was discussed within the PFC, forming a cascade of top-down hierarchical processes operating along a posterior-to-anterior axis of the lateral PFC including BA44 within the network. It is proposed that PFC is actively involved in different forms of hierarchical processing and specifically BA44 may play an integral role in the process. Taking levels of proficiency and subcortical areas into consideration may provide further insight into the functional role of BA44 for hierarchical

Fast matrix factorization algorithm for DOSY based on the eigenvalue decomposition and the difference approximation focusing on the size of observed matrix

International Nuclear Information System (INIS)

Tanaka, Yuho; Uruma, Kazunori; Furukawa, Toshihiro; Nakao, Tomoki; Izumi, Kenya; Utsumi, Hiroaki

2017-01-01

This paper deals with an analysis problem for diffusion-ordered NMR spectroscopy (DOSY). DOSY is formulated as a matrix factorization problem of a given observed matrix. In order to solve this problem, a direct exponential curve resolution algorithm (DECRA) is well known. DECRA is based on singular value decomposition; the advantage of this algorithm is that the initial value is not required. However, DECRA requires a long calculating time, depending on the size of the given observed matrix due to the singular value decomposition, and this is a serious problem in practical use. Thus, this paper proposes a new analysis algorithm for DOSY to achieve a short calculating time. In order to solve matrix factorization for DOSY without using singular value decomposition, this paper focuses on the size of the given observed matrix. The observed matrix in DOSY is also a rectangular matrix with more columns than rows, due to limitation of the measuring time; thus, the proposed algorithm transforms the given observed matrix into a small observed matrix. The proposed algorithm applies the eigenvalue decomposition and the difference approximation to the small observed matrix, and the matrix factorization problem for DOSY is solved. The simulation and a data analysis show that the proposed algorithm achieves a lower calculating time than DECRA as well as similar analysis result results to DECRA. (author)

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

Science.gov (United States)

Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

2017-09-01

Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Strengthen Cloud Computing Security with Federal Identity Management Using Hierarchical Identity-Based Cryptography

Science.gov (United States)

Yan, Liang; Rong, Chunming; Zhao, Gansen

More and more companies begin to provide different kinds of cloud computing services for Internet users at the same time these services also bring some security problems. Currently the majority of cloud computing systems provide digital identity for users to access their services, this will bring some inconvenience for a hybrid cloud that includes multiple private clouds and/or public clouds. Today most cloud computing system use asymmetric and traditional public key cryptography to provide data security and mutual authentication. Identity-based cryptography has some attraction characteristics that seem to fit well the requirements of cloud computing. In this paper, by adopting federated identity management together with hierarchical identity-based cryptography (HIBC), not only the key distribution but also the mutual authentication can be simplified in the cloud.

Not dead yet: the rise, fall and persistence of the BCG Matrix

OpenAIRE

Madsen, Dag Øivind

2017-01-01

The BCG Matrix was introduced almost 50 years ago, and is today considered one of the most iconic strategic planning techniques. Using management fashion theory as a theoretical lens, this paper examines the historical rise, fall and persistence of the BCG Matrix. The analysis highlights the role played by fashion-setting actors (e.g., consultants, business schools and business media) in the rise of the BCG Matrix. However, over time, portfolio planning models such as the BCG Matrix were atta...

Heteroscedasticity resistant robust covariance matrix estimator

Czech Academy of Sciences Publication Activity Database

Víšek, Jan Ámos

2010-01-01

Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf

Practical application of Integrated National Energy Planning (INEP) using microcomputers

International Nuclear Information System (INIS)

Munasinghe, M.

1989-01-01

The paper describes the use of a practical microcomputer-based, hierarchical modelling framework for Integrated National Energy Planning (INEP), and policy analysis. The rationale for the concept and the development of the methodology are traced, following the energy crises of the 1970s. Details of the INEP process, which includes analysis at three hierarchical levels (the energy-microeconomic, energy sector and energy subsector) are given. A description of the various models, the scenarios and assumptions used in the analysis, as well as the linkages and interactions, is provided. The Sri Lanka energy situation is summarized, and the principal energy issues and options derived from the modelling are used to synthesize a national energy strategy. (author). 11 refs, 8 figs, 11 tabs

Growth Mechanism of Pumpkin-Shaped Vaterite Hierarchical Structures

Science.gov (United States)

Ma, Guobin; Xu, Yifei; Wang, Mu

2015-03-01

CaCO3-based biominerals possess sophisticated hierarchical structures and promising mechanical properties. Recent researches imply that vaterite may play an important role in formation of CaCO3-based biominerals. However, as a less common polymorph of CaCO3, the growth mechanism of vaterite remains not very clear. Here we report the growth of a pumpkin-shaped vaterite hierarchical structure with a six-fold symmetrical axis and lamellar microstructure. We demonstrate that the growth is controlled by supersaturation and the intrinsic crystallographic anisotropy of vaterite. For the scenario of high supersaturation, the nucleation rate is higher than the lateral extension rate, favoring the ``double-leaf'' spherulitic growth. Meanwhile, nucleation occurs preferentially in as determined by the crystalline structure of vaterite, modulating the grown products with a hexagonal symmetry. The results are beneficial for an in-depth understanding of the biomineralization of CaCO3. The growth mechanism may also be applicable to interpret the formation of similar hierarchical structures of other materials. The authors gratefully acknowledge the financial support from National Science Foundation of China (Grant Nos. 51172104 and 50972057) and National Key Basic Research Program of China (Grant No. 2010CB630705).

Comparison of CT based-CTV plan and CT based-ICRU38 plan in brachytherapy planning of uterine cervix cancer

International Nuclear Information System (INIS)

Shim, Jin Sup; Jo, Jung Kun; Si, Chang Keun; Lee, Ki Ho; Lee, Du Hyun; Choi, Kye Suk

2004-01-01

Although Improve of CT, MRI Radio-diagnosis and Radiation Therapy Planing, but we still use ICRU38 Planning system(2D film-based) broadly. 3-Dimensional ICR plan(CT image based) is not only offer tumor and normal tissue dose but also support DVH information. On this study, we plan irradiation-goal dose on CTV(CTV plan) and irradiation-goal dose on ICRU 38 point(ICRU38 plan) by use CT image. And compare with tumor-dose, rectal-dose, bladder-dose on both planning, and analysis DVH Sample 11 patients who treated by Ir-192 HDR. After 40 Gy external radiation therapy, ICR plan established. All the patients carry out CT-image scanned by CT-simulator. And we use PLATO(Nucletron) v.14.2 planing system. We draw CTV, rectum, bladder on the CT image. And establish plan irradiation- dose on CTV(CTV plan) and irradiation- dose on A-point(ICRU38 plan) CTV volume(average±SD) is 21.8±26.6 cm 3 , rectum volume(average±SD) is 60.9±25.0 cm 3 , bladder volume(average±SD) is 116.1±40.1cm 3 sampled 11 patients. The volume including 100% dose is 126.7±18.9 cm 3 on ICRU plan and 98.2±74.5 cm 3 on CTV plan. On ICRU planning, the other one's 22.0 cm 3 CTV volume who residual tumor size excess 4cm is not including 100% isodose. 8 patient's 12.9±5.9 cm 3 tumor volume who residual tumor size below 4 cm irradiated 100% dose. Bladder dose(recommended by ICRU 38) is 90.1±21.3 % on ICRU plan, 68.7±26.6% on CTV plan, and rectal dose is 86.4±18.3%, 76.9±15.6%. Bladder and Rectum maximum dose is 137.2±5.9%, 101.1±41.8% on ICRU plan, 107.6±47.9%, 86.9±30.8% on CTV plan. Therefore CTV plan more less normal issue-irradiated dose than ICRU plan. But one patient case who residual tumor size excess 4 cm, Normal tissue dose more higher than critical dose remarkably on CTV plan. 80% over-Irradiated rectal dose(V80rec) is 1.8±2.4 cm 3 on ICRU plan, 0.7±1.0 cm 3 on CTV plan. 80% over-Irradiated bladder dose(V80bla) is 12.2%±8.9 cm 3 on ICRU plan, 3.5±4.1 cm 3 on CTV plan. Likewise, CTV

Implementation of biological tissue Mueller matrix for polarization-sensitive optical coherence tomography based on LabVIEW

Science.gov (United States)

Lin, Yongping; Zhang, Xiyang; He, Youwu; Cai, Jianyong; Li, Hui

2018-02-01

The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.

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

Directory of Open Access Journals (Sweden)

Yuliya Vladimirovna Dubrovskaya

2016-10-01

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

Hierarchical Bayesian Models of Subtask Learning

Science.gov (United States)

Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Power flow analysis for islanded microgrid in hierarchical structure of control system using optimal control theory

Directory of Open Access Journals (Sweden)

Thang Diep Thanh

2017-12-01

Full Text Available In environmental uncertainties, the power flow problem in islanded microgrid (MG becomes complex and non-trivial. The optimal power flow (OPL problem is described in this paper by using the energy balance between the power generation and load demand. The paper also presents the hierarchical control structure which consists of primary, secondary, tertiary, and emergency controls. Clearly, optimal power flow (OPL which implements a distributed tertiary control in hierarchical control. MG consists of diesel engine generator (DEG, wind turbine generator (WTG, and photovoltaic (PV power. In the control system considered, operation planning is realized based on profiles such that the MG, load, wind and photovoltaic power must be forecasted in short-period, meanwhile the dispatch source (i.e., DEG needs to be scheduled. The aim of the control problem is to find the dispatch output power by minimizing the total cost of energy that leads to the Hamilton-Jacobi-Bellman equation. Experimental results are presented, showing the effectiveness of optimal control such that the generation allows demand profile.

Role of matrix metalloproteinases in recurrent corneal melting

Czech Academy of Sciences Publication Activity Database

Brejchová, K.; Lisková, P.; Čejková, Jitka; Jirsová, K.

2010-01-01

Roč. 90, č. 5 (2010), s. 583-590 ISSN 0014-4835 Institutional research plan: CEZ:AV0Z50390512 Keywords : corneal melting * extracellular matrix degradation * matrix metalloproteinases Subject RIV: FF - HEENT, Dentistry Impact factor: 2.817, year: 2010

Operational workforce planning for check-in counters at airports

DEFF Research Database (Denmark)

Stolletz, Raik

2010-01-01

This paper addresses operation models for workforce planning for check-in systems at airports. We characterize different tasks of the hierarchical workforce planning problem with time-dependent demand. A binary linear programming formulation is developed for the fortnightly tour scheduling problem...

Wetting and Dewetting Transitions on Submerged Superhydrophobic Surfaces with Hierarchical Structures.

Science.gov (United States)

Wu, Huaping; Yang, Zhe; Cao, Binbin; Zhang, Zheng; Zhu, Kai; Wu, Bingbing; Jiang, Shaofei; Chai, Guozhong

2017-01-10

The wetting transition on submersed superhydrophobic surfaces with hierarchical structures and the influence of trapped air on superhydrophobic stability are predicted based on the thermodynamics and mechanical analyses. The dewetting transition on the hierarchically structured surfaces is investigated, and two necessary thermodynamic conditions and a mechanical balance condition for dewetting transition are proposed. The corresponding thermodynamic phase diagram of reversible transition and the critical reversed pressure well explain the experimental results reported previously. Our theory provides a useful guideline for precise controlling of breaking down and recovering of superhydrophobicity by designing superhydrophobic surfaces with hierarchical structures under water.

Hierarchically Nanostructured Transition Metal Oxides for Lithium‐Ion Batteries

Science.gov (United States)

Zheng, Mingbo; Tang, Hao; Li, Lulu; Hu, Qin; Zhang, Li; Xue, Huaiguo

2018-01-01

Abstract Lithium‐ion batteries (LIBs) have been widely used in the field of portable electric devices because of their high energy density and long cycling life. To further improve the performance of LIBs, it is of great importance to develop new electrode materials. Various transition metal oxides (TMOs) have been extensively investigated as electrode materials for LIBs. According to the reaction mechanism, there are mainly two kinds of TMOs, one is based on conversion reaction and the other is based on intercalation/deintercalation reaction. Recently, hierarchically nanostructured TMOs have become a hot research area in the field of LIBs. Hierarchical architecture can provide numerous accessible electroactive sites for redox reactions, shorten the diffusion distance of Li‐ion during the reaction, and accommodate volume expansion during cycling. With rapid research progress in this field, a timely account of this advanced technology is highly necessary. Here, the research progress on the synthesis methods, morphological characteristics, and electrochemical performances of hierarchically nanostructured TMOs for LIBs is summarized and discussed. Some relevant prospects are also proposed. PMID:29593962

The response-matrix based AFEN method for the hexagonal geometry

International Nuclear Information System (INIS)

Noh, Jae Man; Kim, Keung Koo; Zee, Sung Quun; Joo, Hyung Kook; Cho, Byng Oh; Jeong, Hyung Guk; Cho, Jin Young

1998-03-01

The analytic function expansion nodal (AFEN) method, developed to overcome the limitations caused by the transverse integration, has been successfully to predict the neutron behavior in the hexagonal core as well as rectangular core. In the hexagonal node, the transverse leakage resulted from the transverse integration has some singular terms such as delta-function and step-functions near the node center line. In most nodal methods using the transverse integration, the accuracy of nodal method is degraded because the transverse leakage is approximated as a smooth function across the node center line by ignoring singular terms. However, the AFEN method in which there is no transverse leakage term in deriving nodal coupling equations keeps good accuracy for hexagonal node. In this study, the AFEN method which shows excellent accuracy in the hexagonal core analyses is reformulated as a response matrix form. This form of the AFEN method can be implemented easily to nodal codes based on the response matrix method. Therefore, the Coarse Mesh Rebalance (CMR) acceleration technique which is one of main advantages of the response matrix method can be utilized for the AFEN method. The response matrix based AFEN method has been successfully implemented into the MASTER code and its accuracy and computational efficiency were examined by analyzing the two- and three- dimensional benchmark problem of VVER-440. Based on the results, it can be concluded that the newly formulated AFEN method predicts accurately the assembly powers (within 0.2% average error) as well as the effective multiplication factor (within 0.2% average error) as well as the effective multiplication factor (within 20 pcm error). In addition, the CMR acceleration technique is quite efficient in reducing the computation time of the AFEN method by 8 to 10 times. (author). 22 refs., 1 tab., 4 figs

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.

Feature-Based Visual Short-Term Memory Is Widely Distributed and Hierarchically Organized.

Science.gov (United States)

Dotson, Nicholas M; Hoffman, Steven J; Goodell, Baldwin; Gray, Charles M

2018-06-15

Feature-based visual short-term memory is known to engage both sensory and association cortices. However, the extent of the participating circuit and the neural mechanisms underlying memory maintenance is still a matter of vigorous debate. To address these questions, we recorded neuronal activity from 42 cortical areas in monkeys performing a feature-based visual short-term memory task and an interleaved fixation task. We find that task-dependent differences in firing rates are widely distributed throughout the cortex, while stimulus-specific changes in firing rates are more restricted and hierarchically organized. We also show that microsaccades during the memory delay encode the stimuli held in memory and that units modulated by microsaccades are more likely to exhibit stimulus specificity, suggesting that eye movements contribute to visual short-term memory processes. These results support a framework in which most cortical areas, within a modality, contribute to mnemonic representations at timescales that increase along the cortical hierarchy. Copyright © 2018 Elsevier Inc. All rights reserved.

Hierarchical HMM based learning of navigation primitives for cooperative robotic endovascular catheterization.

Science.gov (United States)

Rafii-Tari, Hedyeh; Liu, Jindong; Payne, Christopher J; Bicknell, Colin; Yang, Guang-Zhong

2014-01-01

Despite increased use of remote-controlled steerable catheter navigation systems for endovascular intervention, most current designs are based on master configurations which tend to alter natural operator tool interactions. This introduces problems to both ergonomics and shared human-robot control. This paper proposes a novel cooperative robotic catheterization system based on learning-from-demonstration. By encoding the higher-level structure of a catheterization task as a sequence of primitive motions, we demonstrate how to achieve prospective learning for complex tasks whilst incorporating subject-specific variations. A hierarchical Hidden Markov Model is used to model each movement primitive as well as their sequential relationship. This model is applied to generation of motion sequences, recognition of operator input, and prediction of future movements for the robot. The framework is validated by comparing catheter tip motions against the manual approach, showing significant improvements in the quality of catheterization. The results motivate the design of collaborative robotic systems that are intuitive to use, while reducing the cognitive workload of the operator.

Operating Theatre Planning and Scheduling.

NARCIS (Netherlands)

Hans, Elias W.; Vanberkel, P.T.; Hall, R.

2012-01-01

In this chapter we present a number of approaches to operating theatre planning and scheduling. We organize these approaches hierarchically which serves to illustrate the breadth of problems confronted by researchers. At each hierarchicalplanning level we describe common problems, solution

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.

Carbon fiber reinforced hierarchical orthogrid stiffened cylinder: Fabrication and testing

Science.gov (United States)

Wu, Hao; Lai, Changlian; Sun, Fangfang; Li, Ming; Ji, Bin; Wei, Weiyi; Liu, Debo; Zhang, Xi; Fan, Hualin

2018-04-01

To get strong, stiff and light cylindrical shell, carbon fiber reinforced hierarchical orthogrid stiffened cylinders are designed and fabricated. The cylinder is stiffened by two-scale orthogrid. The primary orthogrid has thick and high ribs and contains several sub-orthogrid cells whose rib is much thinner and lower. The primary orthogrid stiffens the bending rigidity of the cylinder to resist the global instability while the sub-orthogrid stiffens the bending rigidity of the skin enclosed by the primary orthogrid to resist local buckling. The cylinder is fabricated by filament winding method based on a silicone rubber mandrel with hierarchical grooves. Axial compression tests are performed to reveal the failure modes. With hierarchical stiffeners, the cylinder fails at skin fracture and has high specific strength. The cylinder will fail at end crushing if the end of the cylinder is not thickened. Global instability and local buckling are well restricted by the hierarchical stiffeners.

The MIL-88A-Derived Fe3O4-Carbon Hierarchical Nanocomposites for Electrochemical Sensing

Science.gov (United States)

Wang, Li; Zhang, Yayun; Li, Xia; Xie, Yingzhen; He, Juan; Yu, Jie; Song, Yonghai

2015-01-01

Metal or metal oxides/carbon nanocomposites with hierarchical superstructures have become one of the most promising functional materials in sensor, catalysis, energy conversion, etc. In this work, novel hierarchical Fe3O4/carbon superstructures have been fabricated based on metal-organic frameworks (MOFs)-derived method. Three kinds of Fe-MOFs (MIL-88A) with different morphologies were prepared beforehand as templates, and then pyrolyzed to fabricate the corresponding novel hierarchical Fe3O4/carbon superstructures. The systematic studies on the thermal decomposition process of the three kinds of MIL-88A and the effect of template morphology on the products were carried out in detail. Scanning electron microscopy, transmission electron microscopy, X-ray powder diffraction, X-ray photoelectron spectroscopy and thermal analysis were employed to investigate the hierarchical Fe3O4/carbon superstructures. Based on these resulted hierarchical Fe3O4/carbon superstructures, a novel and sensitive nonenzymatic N-acetyl cysteine sensor was developed. The porous and hierarchical superstructures and large surface area of the as-formed Fe3O4/carbon superstructures eventually contributed to the good electrocatalytic activity of the prepared sensor towards the oxidation of N-acetyl cysteine. The proposed preparation method of the hierarchical Fe3O4/carbon superstructures is simple, efficient, cheap and easy to mass production. It might open up a new way for hierarchical superstructures preparation. PMID:26387535

Matrix completion by deep matrix factorization.

Science.gov (United States)

Fan, Jicong; Cheng, Jieyu

2018-02-01

Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inverse planning for interstitial gynecologic template brachytherapy: truly anatomy-based planning

International Nuclear Information System (INIS)

Lessard, Etienne; Hsu, I-Chou; Pouliot, Jean

2002-01-01

Purpose: Commercially available optimization schemes generally result in an undesirable dose distribution, because of the particular shapes of tumors extending laterally from the tandem. Dose distribution is therefore manually obtained by adjusting relative dwell time values until an acceptable solution is found. The objective of this work is to present the clinical application of an inverse planning dose optimization tool for the automatic determination of source dwell time values in the treatment of interstitial gynecologic templates. Methods and Materials: In cases where the tumor extends beyond the range of the tandem-ovoid applicator, catheters as well as the tandem are inserted into the paravaginal and parametrial region in an attempt to cover the tumor volume. CT scans of these patients are then used for CT-based dose planning. Dose distribution is obtained manually by varying the relative dwell times until adequate dose coverage is achieved. This manual planning is performed by an experienced physician. In parallel, our in-house inverse planning based on simulated annealing is used to automatically determine which of all possible dwell positions will become active and to calculate the dwell time values needed to fulfill dose constraints applied to the tumor volume and to each organ at risk. To compare the results of these planning methods, dose-volume histograms and isodose distributions were generated for the target and each organ at risk. Results: This procedure has been applied for the dose planning of 12 consecutive interstitial gynecologic templates cases. For all cases, once the anatomy was contoured, the routine of inverse planning based on simulated annealing found the solution to the dose constraints within 1 min of CPU time. In comparison, manual planning took more than 45 min. The inverse planning-generated plans showed improved protection to organs at risk for the same coverage compared to manual planning. Conclusion: This inverse planning tool

Hierarchical activated mesoporous phenolic-resin-based carbons for supercapacitors.

Science.gov (United States)

Wang, Zhao; Zhou, Min; Chen, Hao; Jiang, Jingui; Guan, Shiyou

2014-10-01

A series of hierarchical activated mesoporous carbons (AMCs) were prepared by the activation of highly ordered, body-centered cubic mesoporous phenolic-resin-based carbon with KOH. The effect of the KOH/carbon-weight ratio on the textural properties and capacitive performance of the AMCs was investigated in detail. An AMC prepared with a KOH/carbon-weight ratio of 6:1 possessed the largest specific surface area (1118 m(2) g(-1)), with retention of the ordered mesoporous structure, and exhibited the highest specific capacitance of 260 F g(-1) at a current density of 0.1 A g(-1) in 1 M H2 SO4 aqueous electrolyte. This material also showed excellent rate capability (163 F g(-1) retained at 20 A g(-1)) and good long-term electrochemical stability. This superior capacitive performance could be attributed to a large specific surface area and an optimized micro-mesopore structure, which not only increased the effective specific surface area for charge storage but also provided a favorable pathway for efficient ion transport. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-performance supercapacitors based on hierarchically porous graphite particles

Energy Technology Data Exchange (ETDEWEB)

Chen, Zheng; Wen, Jing; Yan, Chunzhu; Rice, Lynn; Sohn, Hiesang; Lu, Yunfeng [Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095 (United States); Shen, Meiqing [School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072 (China); Cai, Mei [General Motor R and D Center, Warren, MI 48090 (United States); Dunn, Bruce [Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095 (United States)

2011-07-15

Hierarchically porous graphite particles are synthesized using a continuous, scalable aerosol approach. The unique porous graphite architecture provides the particles with high surface area, fast ion transportation, and good electronic conductivity, which endows the resulting supercapacitors with high energy and power densities. This work provides a new material platform for high-performance supercapacitors with high packing density, and is adaptable to battery electrodes, fuel-cell catalyst supports, and other applications. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

Directory of Open Access Journals (Sweden)

Salvador Dura-Bernal

Full Text Available Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance. Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom

Process quality planning of quality function deployment for carrot syrup

Science.gov (United States)

Ekawati, Yurida; Noya, Sunday; Widjaja, Filemon

2017-06-01

Carrot products are rarely available in the market. Based on previous research that had been done using QFD to generate product design of carrots products, the research to produce the process quality planning had been carried out. The carrot product studied was carrot syrup. The research resulted in a process planning matrix for carrot syrup. The matrix gives information about critical process plan and the priority of the critical process plan. The critical process plan on the production process of carrot syrup consists of carrots sorting, carrots peeling, carrots washing, blanching process, carrots cutting, the making of pureed carrots, filtering carrot juice, the addition of sugar in carrot juice, the addition of food additives in carrot juice, syrup boiling, syrup filtering, syrup filling into the bottle, the bottle closure and cooling. The information will help the design of the production process of carrot syrup.

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Hierarchical vs non-hierarchical audio indexation and classification for video genres

Science.gov (United States)

Dammak, Nouha; BenAyed, Yassine

2018-04-01

In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

Phase-based Planning for Railway Infrastructure Projects

DEFF Research Database (Denmark)

Li, Rui

2017-01-01

is important in terms of economy and rail operations. This study presents two types of Phase-based Decision Support System (PDSS), i.e. Functional Phase-Based Planning Approach (F-PBPA) and Process-Oriented Phase-Based Planning Approach (PO-PBPA). They are used for decision support for the planning...... of the railway infrastructure maintenance activities at the strategic planning level. The objective is to achieve better economy, as well as improve cost efficiency. F-PBPA consists of ve main phases: Data Collection, Technical Optimization (TeO), Economic Optimization (EcO), Constrained Optimization (Co...... the costs. Finally, constrained optimization (CoO) includes additional constraints and it allows the railway expert to adjust input parameters, thereby to obtain alternative maintenance plans. PO-PBPA contains another systematic phase based process. With a focus on Life Cycle Cost (LCC), PO-PBPA can guide...

Designing matrix organizations that work: Lessons from the P&G case

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Ronald Jean Degen

2010-08-01

Full Text Available The matrix organization concept emerged from the US aerospace industry in the 1960s and was adopted by many companies in the early 1970s. In the late 1970s and early 1980s many companies were experiencing trouble with its operation and many argued like Peters & Waterman in their bestseller In search of excellence in 1982 (p. 306 that the matrix was too complex to work properly. Galbraith (2009, p. 10-14 explains that the reason for the problems were that the matrix in these organizations was wrongly adopted, hastily installed, and inappropriately implemented. He explains that adopting a matrix structure requires a collaborative organization form, proper power, and accountability distribution, complementing changes to the information systems, planning and budgeting process, the performance evaluation and bonus system, and so on. The purpose of this paper is to illustrate why companies adopted the matrix, what problems they had, the solutions for these problems based on Galbraith (2009 and other authors like Davis & Lawrence (1977, and the state of the art of matrix structure design today like the P&G front-back hybrid matrix organization. To illustrate the historical evolution of organization structure to the simple matrix and then to more complex matrix organizations we used the P&G case (Piskorski & Spadini 2007.

Integrating design and production planning with knowledge-based inspection planning system

International Nuclear Information System (INIS)

Abbasi, Ghaleb Y.; Ketan, Hussein S.; Adil, Mazen B.

2005-01-01

In this paper an intelligent environment to integrate design and inspection earlier to the design stage. A hybrid knowledge-based approach integrating computer-aided design (CAD) and computer-aided inspection planning (CAIP) was developed, thereafter called computer-aided design and inspection planning (CADIP). CADIP was adopted for automated dimensional inspection planning. Critical functional features were screened based on certain attributes for part features for inspection planning application. Testing the model resulted in minimizing the number of probing vectors associated with the most important features in the inspected prismatic part, significant reduction in inspection costs and release of human labor. In totality, this tends to increase customer satisfaction as a final goal of the developed system. (author)

Mechanical and corrosion behaviors of developed copper-based metal matrix composites

Science.gov (United States)

Singh, Manvandra Kumar; Gautam, Rakesh Kumar; Prakash, Rajiv; Ji, Gopal

2018-03-01

This work investigates mechanical properties and corrosion resistances of cast copper-tungsten carbide (WC) metal matrix composites (MMCs). Copper matrix composites have been developed by stir casting technique. Different sizes of micro and nano particles of WC particles are utilized as reinforcement to prepare two copper-based composites, however, nano size of WC particles are prepared by high-energy ball milling. XRD (X-rays diffraction) characterize the materials for involvement of different phases. The mechanical behavior of composites has been studied by Vickers hardness test and compression test; while the corrosion behavior of developed composites is investigated by electrochemical impedance spectroscopy in 0.5 M H2SO4 solutions. The results show that hardness, compressive strength and corrosion resistance of copper matrix composites are very high in comparison to that of copper matrix, which attributed to the microstructural changes occurred during composite formation. SEM (Scanning electron microscopy) reveals the morphology of the corroded surfaces.

Iris Image Classification Based on Hierarchical Visual Codebook.

Science.gov (United States)

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

Science.gov (United States)

Nemeth, Noel N.; Bednarcyk, Brett A.; Pineda, Evan J.; Walton, Owen J.; Arnold, Steven M.

2016-01-01

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

Science.gov (United States)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

The Hierarchical Perspective

Directory of Open Access Journals (Sweden)

Daniel Sofron

2015-05-01

Full Text Available This paper is focused on the hierarchical perspective, one of the methods for representing space that was used before the discovery of the Renaissance linear perspective. The hierarchical perspective has a more or less pronounced scientific character and its study offers us a clear image of the way the representatives of the cultures that developed it used to perceive the sensitive reality. This type of perspective is an original method of representing three-dimensional space on a flat surface, which characterises the art of Ancient Egypt and much of the art of the Middle Ages, being identified in the Eastern European Byzantine art, as well as in the Western European Pre-Romanesque and Romanesque art. At the same time, the hierarchical perspective is also present in naive painting and infantile drawing. Reminiscences of this method can be recognised also in the works of some precursors of the Italian Renaissance. The hierarchical perspective can be viewed as a subjective ranking criterion, according to which the elements are visually represented by taking into account their relevance within the image while perception is ignored. This paper aims to show how the main objective of the artists of those times was not to faithfully represent the objective reality, but rather to emphasize the essence of the world and its perennial aspects. This may represent a possible explanation for the refusal of perspective in the Egyptian, Romanesque and Byzantine painting, characterised by a marked two-dimensionality.

Comparisons of Flow Patterns over a Hierarchical and a Non-hierarchical Surface in Relation to Biofouling Control

Directory of Open Access Journals (Sweden)

Bin Ahmad Fawzan Mohammed Ridha

2018-01-01

Full Text Available Biofouling can be defined as unwanted deposition and development of organisms on submerged surfaces. It is a major problem as it causes water contamination, infrastructures damage and increase in maintenance and operational cost especially in the shipping industry. There are a few methods that can prevent this problem. One of the most effective methods which is using chemicals particularly Tributyltin has been banned due to adverse effects on the environment. One of the non-toxic methods found to be effective is surface modification which involves altering the surface topography so that it becomes a low-fouling or a non-stick surface to biofouling organisms. Current literature suggested that non-hierarchical topographies has lower antifouling performance compared to hierarchical topographies. It is still unclear if the effects of the flow on these topographies could have aided in their antifouling properties. This research will use Computational Fluid Dynamics (CFD simulations to study the flow on these two topographies which also involves comparison study of the topographies used. According to the results obtained, it is shown that hierarchical topography has higher antifouling performance compared to non-hierarchical topography. This is because the fluid characteristics at the hierarchical topography is more favorable in controlling biofouling. In addition, hierarchical topography has higher wall shear stress distribution compared to non-hierarchical topography

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

Science.gov (United States)

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Hierarchical Delay-Dependent Distributed Coordinated Control for DC Ring-Bus Microgrids

DEFF Research Database (Denmark)

Dou, Chunxia; Yue, Dong; Zhang, Zhanqiang

2017-01-01

In this paper, a hierarchical distributed coordinated control method is proposed based on the multi-agent system for dc ring-bus microgrids to improve the bus voltage performance. First, a two-level multi-agent system is built, where each first-level unit control agent is associated with a distri......In this paper, a hierarchical distributed coordinated control method is proposed based on the multi-agent system for dc ring-bus microgrids to improve the bus voltage performance. First, a two-level multi-agent system is built, where each first-level unit control agent is associated...

Hierarchical Synthesis of Coastal Ecosystem Health Indicators at Karimunjawa National Marine Park

Science.gov (United States)

Danu Prasetya, Johan; Ambariyanto; Supriharyono; Purwanti, Frida

2018-02-01

The coastal ecosystem of Karimunjawa National Marine Park (KNMP) is facing various pressures, including from human activity. Monitoring the health condition of coastal ecosystems periodically is needed as an evaluation of the ecosystem condition. Systematic and consistent indicators are needed in monitoring of coastal ecosystem health. This paper presents hierarchical synthesis of coastal ecosystem health indicators using Analytic Hierarchy Process (AHP) method. Hierarchical synthesis is obtained from process of weighting by paired comparison based on expert judgments. The variables of coastal ecosystem health indicators in this synthesis consist of 3 level of variable, i.e. main variable, sub-variable and operational variable. As a result of assessment, coastal ecosystem health indicators consist of 3 main variables, i.e. State of Ecosystem, Pressure and Management. Main variables State of Ecosystem and Management obtain the same value i.e. 0.400, while Pressure value was 0.200. Each main variable consist of several sub-variable, i.e. coral reef, reef fish, mangrove and seagrass for State of Ecosystem; fisheries and marine tourism activity for Pressure; planning and regulation, institutional and also infrastructure and financing for Management. The highest value of sub-variable of main variable State of Ecosystem, Pressure and Management were coral reef (0.186); marine tourism pressure (0.133) and institutional (0.171), respectively. The highest value of operational variable of main variable State of Ecosystem, Pressure and Management were percent of coral cover (0.058), marine tourism pressure (0.133) and presence of zonation plan, regulation also socialization of monitoring program (0.53), respectively. Potential pressure from marine tourism activity is the variable that most affect the health of the ecosystem. The results of this research suggest that there is a need to develop stronger conservation strategies to facing with pressures from marine tourism

An approach based on Hierarchical Bayesian Graphical Models for measurement interpretation under uncertainty

Science.gov (United States)

Skataric, Maja; Bose, Sandip; Zeroug, Smaine; Tilke, Peter

2017-02-01

It is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications. In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.

Hierarchical Data Replication and Service Monitoring Methods in a Scientific Data Grid

Directory of Open Access Journals (Sweden)

Weizhong Lu

2009-04-01

Full Text Available In a grid and distributed computing environment, data replication is an effective way to improve data accessibility and data accessing efficiency. It is also significant in developing a real-time service monitoring system for a Chinese Scientific Data Grid to guarantee the system stability and data availability. Hierarchical data replication and service monitoring methods are proposed in this paper. The hierarchical data replication method divides the network into different domains and replicates data in local domains. The nodes in a local domain are classified into hierarchies to improve data accessibility according to bandwidth and storage memory space. An extensible agent-based prototype of a hierarchical service monitoring system is presented. The status information of services in the Chinese Scientific Data Grid is collected from the grid nodes based on agent technology and then is transformed into real-time operational pictures for management needs. This paper presents frameworks of the hierarchical data replication and service monitoring methods and gives detailed resolutions. Simulation analyses have demonstrated improved data accessing efficiency and verified the effectiveness of the methods at the same time.

Hierarchical oxide-based composite nanostructures for energy, environmental, and sensing applications

Science.gov (United States)

Gao, Pu-Xian; Shimpi, Paresh; Cai, Wenjie; Gao, Haiyong; Jian, Dunliang; Wrobel, Gregory

2011-02-01

Self-assembled composite nanostructures integrate various basic nano-elements such as nanoparticles, nanofilms and nanowires toward realizing multifunctional characteristics, which promises an important route with potentially high reward for the fast evolving nanoscience and nanotechnology. A broad array of hierarchical metal oxide based nanostructures have been designed and fabricated in our research group, involving semiconductor metal oxides, ternary functional oxides such as perovskites and spinels and quaternary dielectric hydroxyl metal oxides with diverse applications in efficient energy harvesting/saving/utilization, environmental protection/control, chemical sensing and thus impacting major grand challenges in the area of materials and nanotechnology. Two of our latest research activities have been highlighted specifically in semiconductor oxide alloy nanowires and metal oxide/perovskite composite nanowires, which could impact the application sectors in ultraviolet/blue lighting, visible solar absorption, vehicle and industry emission control, chemical sensing and control for vehicle combustors and power plants.

Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture

DEFF Research Database (Denmark)

Marzband, Mousa; Parhizi, Narges; Savaghebi, Mehdi

2016-01-01

In this paper, a comprehensive real-time interactive EMS framework for the utility and multiple electrically-coupled MGs is proposed. A hierarchical bi-level control scheme-BLCS with primary and secondary level controllers is applied in this regard. The proposed hierarchical architecture consists...... are treated as uncertainties in the proposed structure. In order to handle the uncertainties, Taguchi0s orthogonal array testing-TOAT approach is utilized. Then, the shortage or surplus of the MGs power should be submitted to a central EMS-CEMS in the secondary-level. In order to validate the proposed control...

Hierarchical Velocity Control Based on Differential Flatness for a DC/DC Buck Converter-DC Motor System

Directory of Open Access Journals (Sweden)

R. Silva-Ortigoza

2014-01-01

Full Text Available This paper presents a hierarchical controller that carries out the angular velocity trajectory tracking task for a DC motor driven by a DC/DC Buck converter. The high level control is related to the DC motor and the low level control is dedicated to the DC/DC Buck converter; both controls are designed via differential flatness. The high level control provides a desired voltage profile for the DC motor to achieve the tracking of a desired angular velocity trajectory. Then, a low level control is designed to ensure that the output voltage of the DC/DC Buck converter tracks the voltage profile imposed by the high level control. In order to experimentally verify the hierarchical controller performance, a DS1104 electronic board from dSPACE and Matlab-Simulink are used. The switched implementation of the hierarchical average controller is accomplished by means of pulse width modulation. Experimental results of the hierarchical controller for the velocity trajectory tracking task show good performance and robustness against the uncertainties associated with different system parameters.

High-energy supercapacitors based on hierarchical porous carbon with an ultrahigh ion-accessible surface area in ionic liquid electrolytes

Science.gov (United States)

Zhong, Hui; Xu, Fei; Li, Zenghui; Fu, Ruowen; Wu, Dingcai

2013-05-01

A very important yet really challenging issue to address is how to greatly increase the energy density of supercapacitors to approach or even exceed those of batteries without sacrificing the power density. Herein we report the fabrication of a new class of ultrahigh surface area hierarchical porous carbon (UHSA-HPC) based on the pore formation and widening of polystyrene-derived HPC by KOH activation, and highlight its superior ability for energy storage in supercapacitors with ionic liquid (IL) as electrolyte. The UHSA-HPC with a surface area of more than 3000 m2 g-1 shows an extremely high energy density, i.e., 118 W h kg-1 at a power density of 100 W kg-1. This is ascribed to its unique hierarchical nanonetwork structure with a large number of small-sized nanopores for IL storage and an ideal meso-/macroporous network for IL transfer.A very important yet really challenging issue to address is how to greatly increase the energy density of supercapacitors to approach or even exceed those of batteries without sacrificing the power density. Herein we report the fabrication of a new class of ultrahigh surface area hierarchical porous carbon (UHSA-HPC) based on the pore formation and widening of polystyrene-derived HPC by KOH activation, and highlight its superior ability for energy storage in supercapacitors with ionic liquid (IL) as electrolyte. The UHSA-HPC with a surface area of more than 3000 m2 g-1 shows an extremely high energy density, i.e., 118 W h kg-1 at a power density of 100 W kg-1. This is ascribed to its unique hierarchical nanonetwork structure with a large number of small-sized nanopores for IL storage and an ideal meso-/macroporous network for IL transfer. Electronic supplementary information (ESI) available: Sample preparation, material characterization, electrochemical characterization and specific mass capacitance and energy density. See DOI: 10.1039/c3nr00738c

Adaptive hierarchical multi-agent organizations

NARCIS (Netherlands)

Ghijsen, M.; Jansweijer, W.N.H.; Wielinga, B.J.; Babuška, R.; Groen, F.C.A.

2010-01-01

In this chapter, we discuss the design of adaptive hierarchical organizations for multi-agent systems (MAS). Hierarchical organizations have a number of advantages such as their ability to handle complex problems and their scalability to large organizations. By introducing adaptivity in the

Photo-driven autonomous hydrogen generation system based on hierarchically shelled ZnO nanostructures

International Nuclear Information System (INIS)

Kim, Heejin; Yong, Kijung

2013-01-01

A quantum dot semiconductor sensitized hierarchically shelled one-dimensional ZnO nanostructure has been applied as a quasi-artificial leaf for hydrogen generation. The optimized ZnO nanostructure consists of one dimensional nanowire as a core and two-dimensional nanosheet on the nanowire surface. Furthermore, the quantum dot semiconductors deposited on the ZnO nanostructures provide visible light harvesting properties. To realize the artificial leaf, we applied the ZnO based nanostructure as a photoelectrode with non-wired Z-scheme system. The demonstrated un-assisted photoelectrochemical system showed the hydrogen generation properties under 1 sun condition irradiation. In addition, the quantum dot modified photoelectrode showed 2 mA/cm 2 current density at the un-assisted condition

Planning applications in image analysis

Science.gov (United States)

Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

1994-01-01

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

Nanocomposites based on hierarchical porous carbon fiber@vanadium nitride nanoparticles as supercapacitor electrodes.

Science.gov (United States)

Ran, Fen; Wu, Yage; Jiang, Minghuan; Tan, Yongtao; Liu, Ying; Kong, Lingbin; Kang, Long; Chen, Shaowei

2018-03-28

In this study, a hybrid electrode material for supercapacitors based on hierarchical porous carbon fiber@vanadium nitride nanoparticles is fabricated using the method of phase-separation mediated by the PAA-b-PAN-b-PAA tri-block copolymer. In the phase-separation procedure, the ionic block copolymer self-assembled on the surface of carbon nanofibers, and is used to adsorb NH 4 VO 3 . Thermal treatment at controlled temperatures under an NH 3  : N 2 atmosphere led to the formation of vanadium nitride nanoparticles that are distributed uniformly on the nanofiber surface. By changing the PAN to PAA-b-PAN-b-PAA ratio in the casting solution, a maximum specific capacitance of 240.5 F g -1 is achieved at the current density of 0.5 A g -1 with good rate capability at a capacitance retention of 72.1% at 5.0 A g -1 in an aqueous electrolyte of 6 mol L -1 KOH within the potential range of -1.10 to 0 V (rN/A = 1.5/1.0). Moreover, an asymmetric supercapacitor is assembled by using the hierarchical porous carbon fiber@vanadium nitride as the negative electrode and Ni(OH) 2 as the positive electrode. Remarkably, at the power density of 400 W kg -1 , the supercapacitor device delivers a better energy density of 39.3 W h kg -1 . It also shows excellent electrochemical stability, and thus might be used as a promising energy-storage device.

NEW METHODS FOR IMPLANT MATRIX FORMATION BASED ON ELECTROSPINNING AND BIOPRINTING TECHNOLOGIES

Directory of Open Access Journals (Sweden)

V. N. Vasilets

2009-01-01

Full Text Available New implant materials for regenerative and replacement surgery based on biodegradable polymers like collagens and polyoxybutirates are developed. Porous structures with controllable morphology were formed from biodegradable polymers using electrospinning and bioprinting technologies. The matrixes were studied by visible and electron scanning microscopy as well as INTEGRA Tomo scanning probe platform making possible the restoration of inner 3D structure of polymer matrix. 

A nodal method based on the response-matrix method

International Nuclear Information System (INIS)

Cunha Menezes Filho, A. da; Rocamora Junior, F.D.

1983-02-01

A nodal approach based on the Response-Matrix method is presented with the purpose of investigating the possibility of mixing two different allocations in the same problem. It is found that the use of allocation of albedo combined with allocation of direct reflection produces good results for homogeneous fast reactor configurations. (Author) [pt

Hierarchical Bayesian sparse image reconstruction with application to MRFM.

Science.gov (United States)

Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves

2009-09-01

This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.

Strategic planning at the national level: Evaluating and ranking energy projects by environmental impact

International Nuclear Information System (INIS)

Thorhallsdottir, Thora Ellen

2007-01-01

A method for evaluating and ranking energy alternatives based on impact upon the natural environment and cultural heritage was developed as part of the first phase of an Icelandic framework plan for the use of hydropower and geothermal energy. The three step procedure involved assessing i) site values and ii) development impacts within a multi-criteria analysis, and iii) ranking the alternatives from worst to best choice from an environmental-cultural heritage point of view. The natural environment was treated as four main classes (landscape + wilderness, geology + hydrology, species, and ecosystem/habitat types + soils), while cultural heritage constituted one class. Values and impacts were assessed within a common matrix with 6 agglomerated attributes: 1) diversity, richness, 2) rarity, 3) size (area), completeness, pristineness, 4) information (epistemological, typological, scientific and educational) and symbolic value, 5) international responsibility, and 6) scenic value. Standardized attribute scores were used to derive total class scores whose weighted sums yielded total site value and total impact. The final output was a one-dimensional ranking obtained by Analytical Hierarchical Process considering total predicted impacts, total site values, risks and uncertainties as well as special site values. The value/impact matrix is compact (31 cell scores) but was considered to be of sufficient resolution and has the advantage of facilitating overview and communication of the methods and results. The classes varied widely in the extent to which value assessments could be based on established scientific procedures and the project highlighted the immense advantage of an internationally accepted frame of reference, first for establishing the theoretical and scientific foundation, second as a tool for evaluation, and third for allowing a global perspective

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.

An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

Science.gov (United States)

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

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.

A Weibull-based compositional approach for hierarchical dynamic fault trees

International Nuclear Information System (INIS)

Chiacchio, F.; Cacioppo, M.; D'Urso, D.; Manno, G.; Trapani, N.; Compagno, L.

2013-01-01

The solution of a dynamic fault tree (DFT) for the reliability assessment can be achieved using a wide variety of techniques. These techniques have a strong theoretical foundation as both the analytical and the simulation methods have been extensively developed. Nevertheless, they all present the same limits that appear with the increasing of the size of the fault trees (i.e., state space explosion, time-consuming simulations), compromising the resolution. We have tested the feasibility of a composition algorithm based on a Weibull distribution, addressed to the resolution of a general class of dynamic fault trees characterized by non-repairable basic events and generally distributed failure times. The proposed composition algorithm is used to generalize the traditional hierarchical technique that, as previous literature have extensively confirmed, is able to reduce the computational effort of a large DFT through the modularization of independent parts of the tree. The results of this study are achieved both through simulation and analytical techniques, thus confirming the capability to solve a quite general class of dynamic fault trees and overcome the limits of traditional techniques.

Hierarchical patch-based co-registration of differently stained histopathology slides

Science.gov (United States)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

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.

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

Science.gov (United States)

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures.

Science.gov (United States)

Schargott, M

2009-06-01

A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

Energy Technology Data Exchange (ETDEWEB)

Schargott, M [Institute of Mechanics, Technische Universitaet Berlin, Strd 17 Juni 135, 10623 Berlin (Germany)], E-mail: martin.schargott@tu-berlin.de

2009-06-01

A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

International Nuclear Information System (INIS)

Schargott, M

2009-01-01

A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface

Internet-based system for simulation-based medical planning for cardiovascular disease.

Science.gov (United States)

Steele, Brooke N; Draney, Mary T; Ku, Joy P; Taylor, Charles A

2003-06-01

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.

Comparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site